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barbecue_blues_sauce_company.rtf
Barbecue Blues Sauce Company
Background Information
Shamara Williams was an accountant in Peoria, Illinois, and had two hobbies about which she was very passionate, collecting blues music and perfecting her homemade bar- becue sauce recipe. She regularly entertained guests by playing her music and feeding them dishes prepared with her barbecue sauce. Four years ago, at the urging of her friends, she abruptly quit her job to pursue a life-long dream of owning her own business. Using her savings and money borrowed from family members, she purchased a small food processing facility and began bottling her sauce. Because her two hobbies had always been inseparable, Ms. Williams decided to employ the name Barb ec ue Blue s as her brand. Thus, Barbecue Blues Sauce Company was born.
The initial strategy was to sell the sauce through retail grocery stores and specialty food markets within a three- state region. Indeed, the strategy was so effective that after three years, Barbecue Blues had captured an 18% share of the retail barbecue sauce market in the region. The third and fourth years of operation were stable, but there was
virtually no growth in unit sales, and increases in revenue were largely attributable to inflation. To assist her in devising a strategy for sales growth, Ms. Williams hired a marketing director, Heather Cohen.
Ms. Cohen advocated extending the line of barbecue sauces, so Ms. Williams created a new ‘‘Chicago style’’ barbecue sauce. She gathered together the group of friends who had originally encouraged her to enter the barbecue sauce business. After sampling the new sauce, all of them thought it was very different from the original sauce in terms of flavor, but of the same level of quality. This posi- tive initial response led Ms. Cohen to commission a mar- keting research study to be conducted by InfoGather to determine consumer reactions to the new sauce.
Shortly before the marketing research report was completed, Ms. Cohen resigned from Barbecue Blues Sauce Company to take a position at a larger food pro- cessing company, so Ms. Williams needs your assistance in interpreting the study’s findings. The Executive Summary of the report is presented in Exhibit 1.
E x h i b i t 1
InfoGather: Barbecue Blues Restaurants Study
Executive Summary
Marketing Problem
To determine whether the new barbecue sauce formula should be marketed, in addition to the original Barbecue Blues sauce, through retail grocery and specialty stores; and if so, which of the following two brand names should be used: Barbecue Blues–Chicago Style Sauce or Barbecue Blues–Spicy Blend Sauce?
Summary of Findings
Of the 728 study participants:
Approximately 83% claimed to use barbecue sauce at home (i.e., 56% use it frequently and 27% use it occasionally). Of these 604 barbecue sauce users ...
- Approximately 41% use barbecue sauce exclusively when cooking outdoors, 24% use barbecue sauce exclusively when cooking indoors, and 35% use barbecue sauce for both indoor and outdoor cooking.
The average number of times in the last month barbecue sauce was used while cooking at home was 2.67. Approximately 52% reacted favorably to the new barbecue sauce (i.e., 21% liked it and 31% liked it very much).
- Approximately 49% reacted favorably when ‘‘Chicago Style’’ was the subbrand name (i.e., 12% liked it and 37% liked it
very much).
- Approximately 53% reacted favorably when ‘‘Spicy Blend’’ was the subbrand name (i.e., 29% liked it and 24% liked it very much).
Approximately 43% indicated they would be likely to purchase the new barbecue sauce (i.e., 25% were likely and 19% were very likely).
- Approximately 45% indicated they would be likely to purchase the new barbecue sauce when ‘‘Chicago Style’’ was the subbrand name (i.e., 27% were likely and 18% were very likely).
1This case was prepared by Jon R. Austin, Ph.D., Associate Professor of Marketing, Cedarville University, 251 North Main Street, Cedarville, OH 45314. © Cengage Learning
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case 2
Kinshasa Abroad—African Cuisine and Culture (A)1
Youlou Kabasella owned and operated a restaurant and nightclub in Kinshasa, Zaire, for nearly 14 years. The restaurant’s menu was filled with popular dishes and drinks from the region. In addition to his food and bev- erage services, Mr. Kabasella provided a dance floor and live Zairian/Congolese rumba and soukous music. While the popularity of most musical styles in Africa were largely confined to specific countries or regions, rumba and soukous were popular throughout the African continent.
Anticipating increased political turmoil, Mr. Kabasella and his family left Zaire in 1995 and ended up living with relatives in Dayton, Ohio. Soon thereafter, they moved to Columbus, Ohio, where he worked odd jobs to make ends meet. A Columbus businessperson befriended him and offered to loan him the capital necessary to establish a new restaurant. In 2003, Mr. Kabasella opened Kinshasa Abroad in the downtown area of Columbus. Like his former restaurant, it has a dance floor and features Zairian/Congolese rumba and soukous music. On most nights, recorded music from the top artists of the genre is played. There are, however, a few Congolese bands, such as Tabu Ley Rochereau & Orchestra Afrisa International and Les Quatre Etoiles (The Four Stars), that occasionally tour the United States and as a favor to their fellow countryman (Mr. Kabasella) play at Kinshasa Abroad whenever they are in the area. A cover of $10 is charged when there are live acts, but there is otherwise no cover charge. The res- taurant has 20 quads (tables for four), 15 deuces (tables for two), and larger parties can be accommodated by pushing tables together.
Mr. Kabasella and his wife prepare and serve a variety of African entrees. Some of their specialties include
Peanut Stew, Beef and Greens in Peanut Sauce, Muamba Nsusu (Congo chicken soup), Malay Curry (stewed lamb in a curry sauce), Samaki wa Kupaka (grilled fish in a coconut-tamarind sauce), Nyama Choma (roasted spare ribs seasoned with curry), and Liboke de Poisson (fish in banana leaf). The entrees are accompanied by various African side dishes such as Plantains in Coconut Milk, Baton de Manioc and Chikwangue (made from cassava tubers), Irio (peas, pota- toes, corn, and greens), Maharagwe (red beans), and Mbaazi wa Nazi (pigeon peas in coconut milk). The Kabasellas also serve a variety of soft drinks imported from Africa along with the usual American beverages found in casual dining restaurants.
When contemplating opening the restaurant, Mr. Kabasella had predicted it would generate immedi- ate interest due to the cultural diversity in the Columbus area. Moreover, because of the restaurant’s proximity to Ohio State University, he thought there would be a high level of awareness and interest in African cuisine and music. Despite his optimism, and the ads he regularly places in local and school newspapers, Mr. Kabasella has been discouraged by the fact that customer turnout and revenue have been far short of what had been projected.
Questions
- If you were to serve as a research consultant for Mr. Kabasella, what information would you need to enable you to help him diagnose his marketing problem(s)?
- Create a list of probing questions you would ask Mr. Kabasella if you were going to meet with him to help him specify (a) the manager’s decision prob- lem and (b) research problems.
1This case was prepared by Jon R. Austin, Ph.D., Associate Professor of Marketing, Cedarville University, 251 North Main Street, Cedarville, OH 45314.
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case 3
E-Food and the Online Grocery Competition
When everybody’s busy, something’s got to give. The online grocery industry (that is, grocery shopping online and home delivery of purchased items) has developed slowly over the past 20 years to address today’s consumer demands of convenience and time savings. Perhaps the best known provider in the industry is Peapod.com, an operation that began outside Chicago. Since its founding in 1989, it has expanded to 18 U.S. markets, making over 10 million deliveries to over 270,000 customers. Other national competitors have entered the market, but only a few have had any staying power. One of these is netgrocer
- om which delivers groceries and an assortment of other merchandise as well across the country using FedEx. In addition to larger multi-market online grocers, there have been many local providers.
Online grocery services typically provide virtual stores through which the electronic visitor navigates, as if pushing a shopping cart in a traditional grocer. The user clicks on items to purchase, which are placed in the user’s cart. When complete, the user is ‘‘checked out,’’ specifying a delivery date and time. Users pay delivery costs proportionate to each shopping bill.
The software allows the user to store his or her pref- erences in a personal shopping list that can be altered, adding or deleting items as necessary with each e-visit. Across the various providers, the software also usually allows easy consumer comparison. For example, the SKUs in a particular category may be sorted by brand name, by price, by value (price per ounce, for example), by what is on ‘‘feature’’ (sale and point-of-purchase pro- motions), by various dietetic goals (such as ‘‘healthy,’’ ‘‘low fat’’), and so on. The user may write in ‘‘notes,’’ to specify in more detail, for example, ‘‘Please pick up green (unripe) bananas, not yellow ones,’’ or ‘‘If Fancy Feast is out of beef, please get turkey instead,’’ which
instruct the professional shopper as to the user’s par- ticular preferences. Categories of items that can be purchased are continually expanding, from foods to drugstore items and other merchandise.
Online grocery providers tend to conduct the online business very well, if customer satisfaction, repeat visits, and word-of-mouth advertising are any indicators. That is, the software provided, the merchandise selected, the delivery reliability, and so on, are valued by the customer, with few complaints. Most users are women, employed full-time, and married, with well-above-average house- hold incomes.
Ashley Sims is an M.B.A. student, taking her last term of classes, and thinking about starting up a local online grocer. She’s certain that by learning from the templates of the current providers in other markets, she, too, can run the logistics of the business. However, she hopes that, given her contacts with computer experts, she can create a competitive advantage in the software setup, if she understands the consumers’ mindset as they travel through the e-grocery stores. She wants to know just what a user is thinking from the first click onto the Web site to the last ‘‘Done Shopping’’ click off the site. This knowledge would allow her to offer better advice to her software developers in terms of what features would facilitate the visitors’ navigation through the grocery store. Data like these would help improve the system, and it would also lend great insight to the consumers’ decision processes.
Questions
- What is the decision problem?
- What is (are) the research problem(s)?
- Prepare a research proposal to submit to an online grocer on behalf of your research team.
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case 4
Kinshasa Abroad—African Cuisine and Culture (B)1
Youlou Kabasella and his wife opened a restaurant in Columbus, Ohio, called Kinshasa Abroad. The underly- ing concept is to provide a unique African cultural expe- rience in terms of cuisine, music, and atmosphere. Mr. Kabasella had expected immediate success due to the cultural diversity in the area and proximity to Ohio State University. However, customer turnout and reve- nue have fallen well short of his projections. He is seek- ing guidance from a consultant as to how marketing research might help him understand why performance has been below expectations and identify some possible ways to turn around performance.
Bill Christianson returned to his office after his initial meeting with Mr. Kabasella at Kinshasa Abroad. He felt confident that Mr. Kabasella had answered his questions honestly and comprehensively. However, he was less confident that the client’s perspective alone was a suffi- cient basis for formulating the marketing problem. As he reflected on the meeting, he began to create a list of questions he had about what might account for the lack- luster performance of Kinshasa Abroad.
It is clear that Mr. Kabasella is not pursuing a well- defined market segment, but that is probably true of most restaurants in the area, perhaps even of some that are highly successful. But what segments would be most inclined to frequent Kinshasa Abroad? What groups would be most interested in African food and beverages? Would these same groups be the ones most interested in African music? Are there groups interested in dancing in a restaurant environment?
The absence of a target market might account for why the advertising messages Mr. Kabasella places in local newspapers are so general in nature. What have consumers thought when they have seen these ads? Specifically, what comes to mind when they think of African food, African beverages, or African music? Are their thoughts at all consistent with what the food, bev- erages, and music are really like? Among consumers who have not tried Kinshasa Abroad, what would their reac- tions be if they sampled African food, beverages, or music? Are there more effective ways to communicate the nature of an African restaurant to people in Ohio? Are there some ‘‘hot button’’ advertising themes that could be employed if Mr. Kabasella better understood certain consumer groups?
Apart from the above questions, there is the issue of the perceived quality of the menu items at Kinshasa Abroad. In particular, have previous patrons been satis- fied with their dining experiences? Also, how satisfied were they with the atmosphere? What has motivated previous patrons to try Kinshasa Abroad? Have they been motivated by cultural curiosity, a more basic search for novelty, or something else? Was this a one-time-only experience, or do they see Kinshasa Abroad as a viable dining alternative in the future?
At a broader level, what are people in the area seek- ing when they dine out on different occasions? What types of food and entertainment are they seeking when they go to restaurants on these occasions? Does Kinshasa Abroad provide an experience that is consistent with what is being sought on any of these occasions? What changes might Kinshasa Abroad consider in its concept to make itself more attractive to consumer groups in Columbus, Ohio?
These questions and more kept swirling around in Bill’s mind as he tried to identify Kinshasa Abroad’s underlying marketing problem(s). Because you were also at the meeting with Mr. Kabasella, Bill shared his thoughts with you and asked you to help him attack these issues.
Questions
- What consumer groups (possible target markets) should be studied using exploratory research methods?
- What secondary sources are available that might provide useful information for this project?
- Sort through the issues Bill Christianson identified above and any others you think may be relevant. Which ones would be best addressed using depth interviews, and which ones would be more appro- priately investigated with focus group interviews?
- Create a list of open-ended questions you would propose using in the depth interviews to capture the insights necessary to more precisely define Kinshasa Abroad’s marketing problem(s).
- Create a list of open-ended questions a focus group moderator could use to guide participants through a discussion of issues that might generate insights concerning Kinshasa Abroad’s marketing problem(s).
1This case was prepared by Jon R. Austin, Ph.D., Associate Professor of Marketing, Cedarville University, 251 North Main Street, Cedarville, OH 45314.
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case 5
Student Computer Lab1
A major university served over 2,000 undergraduate and graduate students majoring in business administration. The large number of students enrolled in the Business School coupled with increasing use of computer technol- ogy by faculty and students created overwhelming demands on the Business School’s computer center. In order to respond, the Business School decided to upgrade its computer facilities.
Rod Stevenson, director of the Student Computer Center (SCC), opened a new computer lab in the fall of 2007. The new lab offered specialized software required by student courses and the latest technology in hardware and software.
Computer Lab Project
After operating for six months, Stevenson recognized some potential problems with the new computer lab. Although the number of computers had doubled, student suggestions and complaints indicated that the demand for computers at times exceeded the available resources. To address this problem, Stevenson established a task force to investigate the level of student satisfaction with the computer lab. The task force was made up of four graduate students and was established in January 2008. The task force aimed to help the computer lab identify student needs and provide suggestions on how those needs could be most effectively met.
The first activity of the task force was to examine available information on the lab and its functions and resources. Services offered by the computer lab included network and printer access. The lab usually had three to four lab monitors to collect money for printouts and answer any of the student’s questions. Lab hours were 8:00 a.m. to 9:30 p.m. on weekdays and 8:00 a.m. to 5:00
- on Saturdays and Sundays.
After reviewing available information on the lab, the task force decided it needed to conduct some research before making recommendations on the services offered. Exhibit 1 displays a proposal written by the task force outlining the information to be obtained and the time frame for the research.
Focus Group Study
Stevenson received the proposal and approved it. He agreed with the task force’s use of focus groups to gain a
preliminary understanding of the students’ attitudes. The focus groups would identify existing problems better than secondary research, although the process of collecting and analyzing the data would be more time consuming. After receiving approval, the task force posted information around the Business School to alert students that focus groups were being conducted. Free laser copies were offered as an incentive for participa- tion. Students were selected based on their interest. The student focus group was held on March 10, 2008. Seven students participated, five graduate and two undergradu- ate. Transcripts are provided in Exhibit 2.
Because one of the responsibilities of the lab moni- tors is to assist students with questions and problems, separate focus groups were also conducted on March 9, 2008, and March 11, 2008, with eight lab monitors. Information from both the student and lab monitor focus groups was used as a guide to develop questions for the second phase, a student survey. Information from the focus groups was reduced to a list of key issues, which were then categorized. An exhaustive list of state- ments was devised to address potential user attitudes with respect to each issue. When the list was complete, statements were revised, combined, or eliminated to a set that succinctly covered the original key issue categories. The questionnaire was then pretested and finally admin- istered to a sample of students attending class in the Business School.
Questions
- Did the moderator do an adequate job of getting the information needed by the SCC?
- Do you think it was wise to have a group with both graduate and undergraduate students included?
- Analyze the focus group transcript very thoroughly. Make a list of problems and ideas generated for the student computer lab.
- What do you see as the benefits and limitations of the focus group findings? Do you think the task force plan for utilizing the focus groups is appropriate?
1The contributions of Monika E. Wingate to the development of this case are gratefully acknowledged.
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E x h i b i t 1 Task Force Proposal
DATE: February 1, 2008 TO: Rod Stevenson
FROM: Computer Center Improvement Task Force RE: Computer Lab Research Proposal
Background: In 2007, the Business School opened a new student computer lab. Through suggestions and complaints, the SCC realizes that there is a service delivery problem in that student demand for computers at times exceeds available resources.
The aim of this research is to help the SCC identify student needs and provide suggestions on how those needs can be most effectively met. The results of this research will be limited to the student computer lab. Other Business School computer facili- ties, such as the computer classrooms and the multimedia lab, are outside the scope of this project.
Objectives: The research objectives are as follows:
- Determine overall student satisfaction with the lab
- Identify current problem areas
- Collect student recommendations for improvements
Methodology: The research design is divided into two parts, exploratory research followed by descriptive research. The exploratory research would attempt to gain a better understanding of students’ perceptions of the computer lab and to identify the issues that concern them. The student survey would aim to quantify the magnitude of these problems and to develop recommendations.
Focus Groups: The task force feels that focus groups would be the most appropriate method for exploratory research. Two sets of focus groups are recommended. One set will focus on students who use the computer lab, while the other will address the lab monitors who deal with student problems on a daily basis.
Student Survey: The focus group information would be used to develop questions for a subsequent survey. Since the population of interest is students enrolled in the Business School, this survey would be administered to students attending classes within the Business School, both graduates and undergraduates.
Time Schedule Completed By
Focus Groups March 11
Questionnaire Design April 2
Pretest Questionnaire April 9
Survey April 23
Data Analysis May 10
E x h i b i t 2
Student Focus Group Transcript
Moderator: I’m Robert from Professional Interviewing. I really appreciate your participation in this group session. As you can see, I am taping this session so I can review all of your comments. We are here tonight to talk about the computer lab at the Business School. As business students, you all have access to the lab for your class assignments. How do you think the computer lab is meeting your needs?
Lisa: I think there is a problem with the lab because the folks who are using computers don’t know about computers. That’s been reflected in the fact that you go to one computer and you pick up a virus. These people don’t know anything about viruses, they’re transmitting them all over the place, nobody is scanning for viruses, and there’s something that could easily be put on the systems.
Oliver: I think there has to be training for the people who are watching the computers. They are ignorant. You ask them any question and they can’t answer it. It’s a computer lab and this computer doesn’t seem to be doing the thing that it should be doing, why? Why is this network different from the rest? How are we supposed to handle this network? They don’t know.
Lisa: Not only that, they don’t know any of the software.
Oliver: Absolutely!
Lisa: This is like I have Word at home and this is WordPerfect, ‘‘How do I do XYZ in WordPerfect?’’ They don’t know. They say, let
me go check with John and it takes three of them to try to answer the question. (Continued)
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E x h i b i t 2
Student Focus Group Transcript (Continued)
Marion: And there are three of them!
Lisa: I know!
Oliver: There is always a big queue so you cannot get onto a Windows machine; you have to go to Pagemaker Plus if you need to make a presentation. You cannot go to these WordPerfect machines that have just keyboard entries. But there are very few computers and a lot of lines in the peak times and they are just not equipped to handle it. They have so many staff over there, five people, all of these people, but not one of them will help anyone.
Moderator: How about you, Jennifer, have you experienced this?
Jennifer: Yeah, I even had it today. I just don’t have time to wait in line to get a computer. It’s a half hour sometimes to go in and get one.
Lisa: And that’s now. At the end of the semester it’s worse.
Jennifer: Yeah, it gets worse.
Lisa: It takes an hour and there’s no sign-up. There’s no regular sign-up.
Mike: They truncated the hours the last two weeks of the semester.
Jennifer: You could take these four people and turn that into one educated person, or take the four people and have one uneducated person there 24 hours a day. That would be nice. If all they’re going to do is take your card and give you your copy, why do you have to have four of them? That’s all they’re doing. And studying.
Moderator: How about you, I didn’t get your name?
Tammy: Tammy.
Moderator: Welcome, Tammy, how about you. What kind of things have you come across?
Tammy: What I’m hearing are a lot of the problems I’ve seen, too. I just think there needs to be more computers in the lab and the hours need to be longer.
Mike: I don’t think they need more computers. They just need to expand the hours and the computing labs.
Oliver: I had an idea where they don’t need more computers. One suggestion I already put in the suggestion box is to have people bring their own computers. Why doesn’t a grad student who is going to be here for two years, going to interface with technology when he leaves here, spend a thousand dollars and go buy his own system? They should do that. Have your own computer here, I’m saying it’s a requirement. It’s a requirement at a lot of universities that you come with your own system. Then you don’t have to worry, you don’t need access to our labs. Now for undergraduates we still have similar problems, but it would put less stress on the system.
Moderator: What would you suggest for people who would say, okay I can get this computer system, but I have to get this software for this class, and this software for this class, and this software. That is a lot of money.
Oliver: Yeah, we can already jump into the network from home. All you need is the software.
Lisa: I don’t think so.
Oliver: You can get in. I can check my mail and stuff.
Lisa: But not software.
Oliver: Oh, software. I haven’t tried, so I don’t know.
Tammy: Getting back to the machine. I’d love to have my own machine but I don’t want to have it if I don’t have to. As long as we have all these other computers, why not use what we’ve got?
Mike: I can’t afford it. If you want to buy a good computer, a decent printer, a decent monitor, you are still going to spend between
$1,600 and $2,000.
Oliver: I think while we’re in school the school should support us with computers.
Mike: I think one of the reasons there aren’t enough computers is that people who aren’t enrolled in the Business School have access to the lab. In the old building, they always checked your ID.
Tammy: Yeah. Why don’t we use the card machines? They were working, weren’t they? They had the doors closed and you used a key card.
Oliver: I think the old lab was better because they controlled people coming and going.
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E x h i b i t 2
Student Focus Group Transcript (Continued)
Mike: Yeah. Gatekeeping.
Tammy: They had hours when only graduate students could come in. I think that’s something that should be started again because they have a lot more papers to type up.
Mike: I don’t see why this lab isn’t open 24 hours. I really don’t. Why aren’t the labs open 24 hours?
Lisa: Monitor problem, they need someone to monitor them, to work with them.
Jennifer: Three people, three eight-hour shifts.
Mike: They don’t have a budget to increase their hours. They need to double the hours, like not having four monitors at one time.
Moderator: There are peak hours and there are hours that there are a lot of open computers, where people don’t generally come in. If there was a way to monitor those times and put a schedule up, people could come in and indicate a time when we could go there. Continually monitor that, what do you think about that?
Mike: Every hour is a peak hour, particularly at the end of the semester.
Oliver: I think it would be a good way of trying to smooth it out, because that’s what you are trying to do. Have people go there when it’s not so busy. But then what about times like today? I happened to get out of class one-half hour early and went downstairs and used it. But if I hadn’t signed up early, there were a million folks in there. There are some trade-offs, but I think it’s a great idea to try and smooth it out. This morning there were four of us in there at 8:00 or 8:15 when it opened, and I don’t think anybody else showed up until 10:00.
Mike: Another problem in the lab right now is that there are a lot of computers that are broken at one time.
Oliver: Oh yeah!
Mike: There are six of them right now that aren’t working.
Oliver: That’s from people not knowing what they are doing. I was sitting down there on one of the old machines and there was a gentleman sitting next to me who couldn’t figure out why it wouldn’t work. He took his disk out and shut the computer off.
When it came back on it got a boot error. Then he got scared and he just left. He didn’t go tell anyone. The monitors are looking from the other side, so they don’t know there is anything wrong. Someone comes in, they just look around, and see that the computer is broken, or it’s not booted up, and so on. That’s why I am saying, it’s the students themselves. People need to know how to use the system.
Ira: I think there should be a small note pasted next to the computers with instructions as to how to use each computer.
Marion: Even a template for the word processing.
Ira: Even a small hint for troubleshooting, please don’t do this and do this.
Tammy: I think an excellent model for this are the computer labs in the dorms. The first time you use them, they scan your ID to
be sure you are a dorm resident, they know if it’s the first time you are using it, they ask you to make sure you know how to use the software. They have a rack with every different kind of title and anything you need to use the software. They tell you exactly what’s going to come up on the machine and what you have to do. I’m sure the Business School can get copies of it all and
then just copy it.
Marion: We have no reference guides for the software.
Tammy: And then they have the guides there. The little orange books.
Moderator: Are there any other concerns we haven’t talked about?
Ira: Is there any way the cost for a laser print can be reduced?
Tammy: It kills me.
Ira: It should be 7 cents. It is 6 cents in the library.
Tammy: You used to have the option to go to a dot matrix printer. They changed that this semester. The only way to go to the dot matrix was to go to an AT&T machine. Don’t tell me someone is looking at cost.
Ira: I think the initial cost is pretty high, that is why they’re keeping it at 10 cents.
Jennifer: If they are planning on getting more printers, I think they should have at least one or two individual print stations where you can grab your stuff. If you’re working on your resume and you want to print on bond paper or do envelopes, the people behind the desk won’t let you do it because they don’t know if other people are going to send before you do, they don’t know
what is going to come out. (Continued)
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E x h i b i t 2
Student Focus Group Transcript (Continued)
Oliver: Or they waste your paper because they can’t coordinate it.
Jennifer: So I think there should be some individual workstations.
Oliver: I have something to say and maybe I’m the only one with this problem. I always find that when I go there and I am working alone, other groups are creating a racket, so it’s really frustrating. I’m working on a project, I need to think. I don’t need this kind of heavy distraction, this loud talk. I go and work in groups too, we try to whisper. There should be some kind of discipline in the computer lab. I think I may be the only one being that sensitive, but I think silence has to be maintained. It is a computer lab,
it is a place for people working, if you’re having a fun time go have it outside.
Moderator: How effective do you think their waiting lists system is?
Tammy: It stinks.
Ira: I didn’t even know they had one.
Tammy: It would be better to set up a physical waiting list where there would be chairs or a bench or something like that.
Ira: Or like a number.
Tammy: Or six chairs in a row and you sit down next to the computers and that means you are next to get on; then if you leave the next person can move down and then you can see that no one is getting in front of you.
Oliver: It worked pretty well for me. Every time I used the waiting list I had to wait for maybe a half hour and my name was called and I could get a computer. I have no complaints. This happened every time. There was no problem. I had no problems at all.
Mike: Until now I didn’t even know there was a waiting list. If there was an open computer, I would just sit down.
Tammy: I found out the hard way, I went down and sat down and someone told me.
Chestnut Ridge Country Club
The Chestnut Ridge Country Club has long maintained a distinguished reputation as one of the outstanding country clubs in the Elma, Tennessee, area. The club’s golf facilities are said by some to be the finest in the state, and its dining and banquet facilities are highly regarded as well. This reputation is due in part to the commitment by the board of directors of Chestnut Ridge to offer the finest facilities of any club in the area. For example, several negative comments by club mem- bers regarding the dining facilities prompted the board to survey members to get their feelings and perceptions of the dining facilities and food offerings at the club. Based on the survey findings, the board of directors established a quality control committee to oversee the dining room, and a new club manager was hired.
Most recently, the board became concerned about the number of people seeking membership to Chestnut Ridge. Although no records are kept on the number of membership applications received each year, the board sensed that this figure was declining. They also believed that membership applications at the three competing country clubs in the area—namely, Alden, Chalet, and Lancaster—were not experiencing similar declines. Because Chestnut Ridge had other facilities, such as tennis courts and a pool, that were comparable to the facilities at these other clubs, the board was perplexed as to why mem- bership applications would be falling at Chestnut Ridge.
To gain insight into the matter, the board of direc- tors hired an outside research firm to conduct a study of the country clubs in Elma, Tennessee. The goals of the research were (1) to outline areas in which Chestnut Ridge fared poorly in relation to other clubs in the area;
- to determine people’s overall perception of Chestnut Ridge; and (3) to provide recommendations for ways to increase membership applications at the club.
Research Method
The researchers met with the board of directors and key personnel at Chestnut Ridge to gain a better understand- ing of the goals of the research and the types of services and facilities offered at a country club. A literature search of published research relating to country clubs uncov- ered no studies. Based solely on their contact with indi- viduals at Chestnut Ridge, therefore, the research team developed the survey contained in Exhibit 1. Because personal information regarding demographics and
attitudes would be asked of those contacted, the researchers decided to use a mail questionnaire.
The researchers thought it would be useful to survey members from Alden, Chalet, and Lancaster country clubs in addition to those from Chestnut Ridge for two reasons: (1) Members of these other clubs would be knowledgeable about the levels and types of services and facilities desired from a country club and (2) They had at one time represented potential members of Chestnut Ridge. Hence, their perceptions of Chestnut Ridge might reveal why they chose to belong to a different country club.
No public documents were available that contained a listing of each club’s members. Consequently, the researchers decided to contact each of the clubs person- ally to try to obtain a mailing list. Identifying themselves as being affiliated with an independent research firm conducting a study on country clubs in the Elma area, the researchers first spoke to the chairman of the board at Alden Country Club. The researchers told the chair- man that they could not reveal the organization sponsor- ing the study but that the results of their study would not be made public. The chairman was not willing to provide the researchers with the mailing list. The chair- man cited an obligation to respect the privacy of the club’s members as his primary reason for turning down the research team’s request.
The researchers then made the following proposal to the board chairman: In return for the mailing list, the researchers would provide the chairman a report on Alden members’ perceptions of Alden Country Club. In addition, the mailing list would be destroyed as soon as the surveys were sent. The proposal seemed to please the chairman, for he agreed to give the researchers a list- ing of the members and their addresses in exchange for the report. The researchers told the chairman they had to check with their sponsoring organization for approval of this arrangement.
The research team made similar proposals to the chairmen of the boards of directors of both the Chalet and Lancaster country clubs. In return for a mailing list of the club’s members, they promised each chairman a report outlining their members’ perceptions of their clubs, contingent on approval from the research team’s sponsoring organization. Both chairmen agreed to sup- ply the requested list of members. The researchers sub- sequently met with the Chestnut Ridge board of directors. In their meeting, the researchers outlined the situation and asked for the board’s approval to provide
each of the clubs with a report in return for the mailing
1The contributions of David M. Szymanski to the development of this case are gratefully acknowledged.
lists. The researchers emphasized that the report would
case 6 523
E x h i b i t 1
Questionnaire Used to Survey Alden, Chalet, and Lancaster
Country Club Members
- Of which club are you currently a member?
- How long have you been a member of this club?
- How familiar are you with each of the following country clubs?
Alden Country Club
very familiar (I am a member or I have visited the club as a guest)
somewhat familiar (I have heard of the club from others)
unfamiliar
Chalet Country Club
very familiar (I am a member or I have visited the club as a guest)
somewhat familiar (I have heard of the club from others)
unfamiliar
Chestnut Ridge Country Club
very familiar (I am a member or I have visited the club as a guest)
somewhat familiar (I have heard of the club from others)
unfamiliar
Lancaster Country Club
very familiar (I am a member or I have visited the club as a guest)
somewhat familiar (I have heard of the club from others)
unfamiliar
- The following is a list of factors that may be influential in the decision to join a country club. Please rate the factors according to their im- portance to you in joining your country club. Circle the appropriate response, where 1 not at all important and 5 extremely important.
Golf facilities 1 2 3 4 5
Tennis facilities 1 2 3 4 5
Pool facilities 1 2 3 4 5
Dining facilities 1 2 3 4 5
Social events 1 2 3 4 5
Family activities 1 2 3 4 5
Number of friends who are members 1 2 3 4 5
Cordiality of members 1 2 3 4 5
Prestige 1 2 3 4 5
Location 1 2 3 4 5
- The following is a list of phrases pertaining to Alden Country Club. Please place an X in the space that best describes your impressions of Alden. The ends represent extremes; the center position is neutral. Do so even if you are only vaguely familiar with Alden.
Club landscape is attractive. : : : : : : : : Club landscape is unattractive. Clubhouse facilities are poor. : : : : : : : : Clubhouse facilities are excellent. Locker room facilities are excellent. : : : : : : : : Locker room facilities are poor.
Club management is ineffective. : : : : : : : : Club management is effective.
Dining room atmosphere is pleasant. : : : : : : : : Dining room atmosphere is unpleasant. Food prices are unreasonable. : : : : : : : : Food prices are reasonable.
Golf course is poorly maintained. : : : : : : : : Golf course is well maintained. Golf course is challenging. : : : : : : : : Golf course is not challenging. Membership rates are too high. : : : : : : : : Membership rates are too low.
- The following is a list of phrases pertaining to Chalet Country Club. Please place an X in the space that best describes your impressions of Chalet. Do so even if you are only vaguely familiar with Chalet.
Club landscape is attractive. : : : : : : : : Club landscape is unattractive. Clubhouse facilities are poor. : : : : : : : : Clubhouse facilities are excellent. Locker room facilities are excellent. : : : : : : : : Locker room facilities are poor.
524 case 6
E x h i b i t 1
Questionnaire Used to Survey Alden, Chalet, and Lancaster
Country Club Members (Continued)
Club management is effective. : : : : : : : : Club management is ineffective.
Dining room atmosphere is pleasant. : : : : : : : : Dining room atmosphere is unpleasant. Food prices are unreasonable. : : : : : : : : Food prices are reasonable.
Food quality is excellent. : : : : : : : : Food quality is poor.
Golf course is poorly maintained. : : : : : : : : Golf course is well maintained. Golf course is challenging. : : : : : : : : Golf course is not challenging. Tennis courts are in excellent condition. : : : : : : : : Tennis courts are in poor condition. There are too many tennis courts. : : : : : : : : There are too few tennis courts.
Membership rates are too high. : : : : : : : : Membership rates are too low.
- The following is a list of phrases pertaining to Chestnut Ridge Country Club. Please place an X in the space that best describes your im- pressions of Chestnut Ridge. Do so even if you are only vaguely familiar with Chestnut Ridge.
Club landscape is attractive. : : : : : : : : Club landscape is unattractive. Clubhouse facilities are poor. : : : : : : : : Clubhouse facilities are excellent. Locker room facilities are excellent. : : : : : : : : Locker room facilities are poor.
Club management is ineffective. : : : : : : : : Club management is effective.
Dining room atmosphere is pleasant. : : : : : : : : Dining room atmosphere is unpleasant. Food prices are unreasonable. : : : : : : : : Food prices are reasonable.
Food quality is excellent. : : : : : : : : Food quality is poor.
Golf course is poorly maintained. : : : : : : : : Golf course is well maintained.
Tennis courts are in poor condition. : : : : : : : : Tennis courts are in excellent condition. There are too many tennis courts. : : : : : : : : There are too few tennis courts.
Swimming pool is in poor condition. : : : : : : : : Swimming pool is in excellent condition. Membership rates are too high. : : : : : : : : Membership rates are too low.
- The following is a list of phrases pertaining to Lancaster Country Club. Please place an X in the space that best describes your impres- sions of Lancaster. Do so even if you are only vaguely familiar with Lancaster.
Club landscape is attractive. : : : : : : : : Club landscape is unattractive. Clubhouse facilities are poor. : : : : : : : : Clubhouse facilities are excellent. Locker room facilities are excellent. : : : : : : : : Locker room facilities are poor.
Club management is ineffective. : : : : : : : : Club management is effective.
Dining room atmosphere is pleasant. : : : : : : : : Dining room atmosphere is unpleasant. Food prices are unreasonable. : : : : : : : : Food prices are reasonable.
Food quality is excellent. : : : : : : : : Food quality is poor.
Golf course is poorly maintained. : : : : : : : : Golf course is well maintained.
Tennis courts are in poor condition. : : : : : : : : Tennis courts are in excellent condition. There are too many tennis courts. : : : : : : : : There are too few tennis courts.
Swimming pool is in poor condition. : : : : : : : : Swimming pool is in excellent condition. Membership rates are too high. : : : : : : : : Membership rates are too low.
- Overall, how would you rate each of the country clubs? Circle the appropriate response, where 1 poor and 5 excellent. Alden 1 2 3 4 5
Chalet 1 2 3 4 5
Chestnut Ridge 1 2 3 4 5
Lancaster 1 2 3 4 5
- The following questions are designed to give a better understanding of the members of country clubs. Have you ever been a member of another club in the Elma area?
yes no
Approximately what is the distance of your residence from your club in miles?
0–2 miles 3–5 miles 6–10 miles 10+ miles
Age: 21–30 31–40 41–50 51–60 61 or over Sex: male female
Marital status: married single widowed divorced Number of dependents including yourself:
2 or less 3–4 5 or more
(Continued)
case 6 525
E x h i b i t 1
Questionnaire Used to Survey Alden, Chalet, and Lancaster
Country Club Members (Continued)
Total family income:
Less than $20,000
$20,000–$29,999
$30,000–$49,999
$50,000–$99,999
$100,000 or more
Do not know/Refuse to answer
Thank you for your cooperation!
contain no information regarding Chestnut Ridge nor information by which each of the other clubs could com- pare itself to any of the other clubs in the area, in con- trast to the information to be provided to the Chestnut Ridge board of directors. The report would only contain a small portion of the overall study’s results. After care- fully considering the research team’s arguments, the board of directors agreed to the proposal.
Membership Surveys
A review of the lists subsequently provided by each club showed that Alden had 114 members, Chalet had 98 members, and Lancaster had 132 members. The researchers believed that 69 to 70 responses from each membership group would be adequate. Anticipating a 70 to 75% response rate because of the unusually high involvement and familiarity of each group with the sub- ject matter, the research team decided to mail 85 to 90 surveys to each group; a simple random sample of mem- bers was chosen from each list. In all, 87 members from each country club were mailed a questionnaire (348 sur- veys in total). Sixty-three usable surveys were returned from each group (252 in total) for a response rate of 72%. Summary results of the survey are presented in the exhibits. Exhibit 2 gives members’ overall ratings of the
country clubs, and Exhibit 3 shows their ratings of the various clubs on an array of dimensions. Exhibit 4 is a breakdown of attitudes toward Chestnut Ridge by the three different membership groups: Alden, Chalet, and Lancaster. The data are average ratings of respondents. Exhibit 2 scores are based on a five-point scale, where ‘‘1’’ is poor and ‘‘5’’ is excellent. The last two are based on seven-point scales in which ‘‘1’’ represents an extremely negative rating and ‘‘7’’ an extremely positive rating.
Questions
- What kind of research design is being used? Is it a good choice?
- Do you think it was ethical for the researchers not to disclose the identity of the sponsoring organiza- tion? Do you think it was ethical for the boards of directors to release the names of their members in return for a report that analyzes their members’ per- ceptions toward their own club?
- Overall, how does Chestnut Ridge compare to the other three country clubs (Alden, Chalet, and Lancaster)?
- In what areas might Chestnut Ridge consider mak- ing improvements to attract additional members?
E x h i b i t 2 Average Overall Ratings of Each Club by Club Membership of the
Respondent
Membership
Club Rated
Alden
Chalet
Lancaster
Alden
4.57
3.64
3.34
Chalet
2.87
3.63
2.67
Chestnut Ridge
4.40
4.44
4.20
Lancaster
3.60
3.91
4.36
526
case 6
Composite Ratings Across All Members
3.85
3.07
4.35
3.95
E x h i b i t 3 Average Ratings of the Respective Country Clubs across Dimensions
Country Club
Dimension Alden Chalet Chestnut Ridge Lancaster
Club landscape
6.28
4.65
6.48
5.97
Clubhouse facilities
5.37
4.67
6.03
5.51
Locker room facilities
4.99
4.79
5.36
4.14
Club management
5.38
4.35
5.00
5.23
Dining room atmosphere
5.91
4.10
5.66
5.48
Food prices
5.42
4.78
4.46
4.79
Food quality
a
4.12
5.48
4.79
Golf course maintenance
6.17
5.01
6.43
5.89
5.10
4.52
5.08
4.14
4.00
3.89
Golf course challenge 5.14 5.01 a 4.77
Condition of tennis courts b
Number of tennis courts b
Swimming pool b b 4.66 5.35
Membership rates 4.49 3.97 5.00 4.91
aQuestion not asked
bNot applicable
E x h i b i t 4 Attitudes toward Chestnut Ridge by Members of the Other
Country Clubs
Dimension Alden Chalet Lancaster
Club landscape
6.54
6.54
6.36
Clubhouse facilities
6.08
6.03
5.98
Locker room facilities
5.66
5.35
5.07
Club management
4.97
5.15
4.78
Dining room atmosphere
5.86
5.70
5.41
Food prices
4.26
4.48
4.63
Food quality
5.52
5.75
5.18
Golf course maintenance
6.47
6.59
6.22
Condition of tennis courts
4.55
4.46
4.55
Number of tennis courts
4.00
4.02
3.98
Swimming pool
5.08
4.69
4.26
Membership rates
5.09
5.64
4.24
case 6 527
case 7
Suchomel Chemical Company
Suchomel Chemical Company was an old-line chemical company that was still managed and directed by its foun- der, Jeff Suchomel, and his wife, Carol. Jeff served as president and Carol as chief research chemist. The com- pany, which was located in Savannah, Georgia, manufac- tured a number of products that were used by consumers in and around their homes. The products included waxes, polishes, tile grout, tile cement, spray cleaners for windows and other surfaces, aerosol room sprays, and insecticides. The company distributed its products regionally. It had a particularly strong consumer follow- ing in the northern Florida and southern Georgia areas.
The company had not only managed to maintain but had also increased its market share in several of its key lines in the past half dozen years in spite of increased competition from the national brands. Suchomel Chemical had done this largely through product innova- tion, particularly innovation that emphasized modest product alterations rather than new technologies or dra- matically new products. Jeff and Carol both believed that the company should stick to the things it knew best rather than try to be all things to all people and in the process spread the company’s resources too thin, particu- larly given its regional nature. One innovation the com- pany was now considering was a new scent for its insect spray, which was rubbed or sprayed onto a person’s body. The new scent had undergone extensive testing both in the laboratory and in the field. The tests indi- cated that it repelled insects, particularly mosquitoes, as well as or even better than the two leading national brands. One thing that the company was particularly concerned about as it considered the introduction of the new brand was what to call it.
The Insecticide Market
The insecticide market had become a somewhat tricky one to figure out over the past several years. Although there had been growth in the purchase of insecticides in general, much of this growth had occurred in the tank liquid market. The household spray market had decreased slightly during the same time span. Suchomel Chemical had not suffered from the general sales decline, however, but had managed to increase its sales of spray insecticides slightly over the past three years. The company was hoping that the new scent formulation might allow it to make even greater market share gains.
The company’s past experience in the industry led it to believe that the name that was given to the new prod- uct would be a very important element in the product’s success, because there seemed to be some complex interactions between purchase and usage characteristics
among repellent users. Most purchases were made by married women for their families. Yet repeat purchase was dependent on support by the husband that the prod- uct worked well. Therefore, the name must appeal to both the buyer and the end user, but the two people are not typically together at the time of purchase. To com- plicate matters further, past research indicated that a product with a name that appeals to both purchaser and end user would be rejected if the product’s name and scent do not match. In sum, naming a product that is used on a person’s body is a complex task.
Research Alternatives
The company followed its typical procedures in develop- ing possible names for the new product. First, it asked those who had been involved in the product’s develop- ment to suggest names. It also scheduled some informal brainstorming sessions among potential customers. Subjects in the brainstorming sessions were simply asked to throw out all the names they could possibly think of with respect to what a spray insecticide could or should be called. A panel of executives, mostly those from the product group but a few from corporate management as well, then went through the names and reduced the large list down to a more manageable subset based on their personal reactions to the names and subsequent discus- sion about what the names connoted to them. The sub- set of names was then submitted to the corporate legal staff, who checked them for possible copyright infringe- ment. Those that survived this check were discussed again by the panel, and a list of 20 possibilities was gen- erated. Those in the product group were charged with the responsibility of developing a research design by which the final name could be chosen.
The people charged with the name test were consid- ering two different alternatives for finding out which name was preferred. Both alternatives involved personal interviews at shopping malls. More specifically, the group was planning to conduct a set of interviews at one randomly determined mall in Atlanta, Savannah, Tallahassee, and Orlando. Each set of interviews would involve 100 respondents. The target respondents were married females, ages 21 to 54, who had purchased the product category during the past year. Likely looking respondents would be approached at random and asked if they had used any insect spray at all over the past year and then asked their age. Those who qualified would be asked to complete the insecticide-naming exercise using one of the two alternatives being considered.
Alternative 1 involved a sort of the 20 tentative names by the respondents. The sort would be conducted in the
528 case 7
following way. First, respondents would be asked to sort the 20 names into two groups based on their appropri- ateness for an insect repellent. Group 1 was to consist of the 10 best names and Group 2 the 10 worst. Next, respondents would be asked to select the four best from Group 1 and the four worst from Group 2. Then they would be asked to pick the one best from the subset of the four best and the one worst from the subset of the four worst. Finally, all respondents would be asked why they picked the specific names they did as the best and the worst.
Alternative 2 also had several stages. All respondents would first be asked to rate each of the 20 names on a seven-point semantic differential scale with end anchors ‘‘Extremely inappropriate name for an insect repellent’’ and ‘‘Extremely appropriate name for an insect repel- lent.’’ After completing this rating task, they would be asked to spray the back of their hands or arm with the product. They would then be asked to repeat the rating task using a similar scale, but this time it was
one in which the polar descriptors referred to the appro- priateness of the name with respect to the specific scent. Next they would be asked to indicate their interest in buying the product by again checking one of the seven positions on a scale that ranged from ‘‘Definitely would not buy it’’ to ‘‘Definitely would buy it.’’ Finally, each respondent would be asked why she selected each of the names she did as being most appropriate for insect repel- lents in general and the specific scent in particular.
Questions
- Evaluate each of the two methods being considered for collecting the data. Which would you recom- mend and why?
- How would you use the data from each method to decide what the brand name should be?
- Do you think that personal interviews in shopping malls are a useful way to collect these data? If not, what would you recommend as an alternative?
case 7 529
case 8
Premium Pizza Inc.1
The past several decades have shown an increase in the use of promotions (coupons, cents-off deals marked on the package, free gifts, etc.), primarily because of their success at increasing short-term purchase behavior. In fact, sales promotion has been estimated to account for over one-half of the typical promotion budget, while advertising accounts for less than half. In many indus- tries, however, the initial benefit of increased sales has resulted in long-term escalation of competition. As firms are forced to ‘‘fight fire with fire,’’ special offer follows special offer in a never-ending spiral of promotional deals.
The fast-food industry has been one of the most strongly affected by this trend. Pizzas come two for the price of one; burgers are promoted in the context of a double-deal involving cuddly toys for the kids; tacos are reduced in price on some days, but not on others. It is within this fiercely competitive, erratic environment that Premium Pizza Corporation has grown from a small local chain into an extensive Midwestern network with national aspirations. Over the past few years, Jim Battaglia, vice president of marketing, has introduced a number of promotional offers, and Premium Pizza par- lors have continued to flourish. Nevertheless, as the company contemplates further expansion, Jim is con- cerned that he knows very little about how his customers respond to his promotional deals. He believes that he needs a long-term strategy aimed at maximizing the effectiveness of dollars spent on promotions. And, as a first step, he thinks it is important to assess the effective- ness of his existing offers.
Specific Objectives
In the past, Jim has favored the use of five types of cou- pons, and he now wants to determine their independent appeal, together with their relation to several identifiable
characteristics of fast-food consumers. The five promo- tional concepts are listed in Exhibit 1. The consumer characteristics that Jim’s experience tells him warrant investigation include number of children living at home, age of youngest child, propensity to eat fast food, pro- pensity to eat Premium Pizza in particular, preference for slices over pies, propensity to use coupons, and occupation.
The specific research problems of the study can be summarized as follows:
- Evaluate the independent appeal of the five promo- tional deals to determine which deals are most preferred;
- Determine why certain deals are preferred; and
- Examine the relationships between the appeal of each promotional concept and various consumer characteristics.
Proposed Methodology
After much discussion, Jim’s research team finally decided that the desired information could best be gathered by means of personal interviews, using a combi- nation of open- and closed-ended questions. A medium- sized shopping mall on the outskirts of a metropolitan area in the Midwest was selected as the research site. Shoppers were intercepted by professional interviewers while walking in the mall and asked to participate in a survey requiring five minutes of their time.
The sampling procedure used a convenience sample in which interviewers were instructed to approach any- one passing by, provided that they met certain criteria (see Exhibit 2). In sum, the sample of respondents was restricted to adult men and women between the ages of 18 and 49 who had both purchased lunch, dinner, or carryout food at a fast-food restaurant in the past seven
E x h i b i t 1
Five Promotional Concepts
Coupon A: Get a medium soft drink for 5 cents with the purchase of any slice.
Coupon B: Buy a slice and get a second slice of comparable value free.
Coupon C: Save 50 cents on the purchase of any slice and receive one free trip to the salad bar.
Coupon D: Buy a slice and a large soft drink and get a second slice free.
Coupon E: Get a single-topping slice for only 99 cents.
1The contributions of Jacqueline C. Hitchon to this case are gratefully acknowledged.
530 case 8
days and had eaten restaurant pizza within the last 30 days, either at a restaurant or delivered to the home. In addition, interviewers were warned not to exercise any bias during the selection process, as they would do, for example, if they approached only those people who looked particularly agreeable or attractive. Finally, inter- viewers were asked to obtain as close as possible a 50–50 split of male and female participants.
The questionnaire was organized into three sections (Exhibit 3). The first section contained the screening questions aimed at ensuring that respondents qualified for the sample. In the second section, respondents were asked to evaluate on 10-point scales the appeal of each of the five promotional concepts based on two factors:
perceived value and likelihood of use. After they had evaluated a concept, interviewees were asked to give rea- sons for their likelihood-of-use rating. The third and final section consisted of the questions on consumer characteristics that Jim believed to be pertinent.
The questionnaire was to be completed by the inter- viewer based on the respondent’s comments. In other words, the interviewer read the questions aloud and wrote down the answer given in each case by the inter- viewee. It was decided to show respondents an example of each coupon before they rated it. For this purpose, enlarged photographs of each coupon were produced. It was also thought necessary to depict the 10-point scales that consumers would use to evaluate the promotional
E x h i b i t 2
Interviewer Instructions
Below are suggestions for addressing each question. Please read all of the instructions before you begin questioning people.
Interviewer Instructions
Approach shoppers who appear to be between 18 and 49 years of age. Since we would like equal numbers of respondents in each age category and a 50% male-female ratio, please do not select respondents based on their appeal to you. The interview should take approximately five minutes. When reading questions, read answer choices if indicated.
Question 1: Terminate any respondent who has not eaten lunch or dinner from any fast-food restaurant in the last seven days.
Question 2: Terminate any respondent who has not eaten pizza within the last 30 days. This includes carry-out, drive-thru, or dining in.
Question 3: Terminate respondent if not between 18 and 49 years of age. If between 18 and 49, circle the appropriate number answer. For this question, please read the question and the answer choices.
After completing questions 1 through 3, hand respondent the coupon booklet. Make sure that the booklet and the response sheets are the same color. Also check to see that the coupon booklet number indicated on the upper right-hand corner of the response sheet matches the coupon book number.
Question 4: Ask the respondent to open the coupon booklet and read the first coupon concept. Read the first section of Question 4 showing the respondent that the scales are provided on the page above the coupon concept. Enter his or her answer in the box provided.
Read the second section of the question and enter respondent’s answer in the second box provided.
When asking the respondent, ‘‘Why did you respond as you did for use,’’ please record the first reason mentioned and use the lines provided to probe and clarify the reasons.
This set of instructions applies to Questions 5 through 8. Periodically remind the respondent to look at the scales provided on the page above the coupon concept that he or she is looking at.
Question 9: Enter number of children living at home. If none, enter the number zero and proceed to Question 11.
Question 10: Enter age of youngest child living at home in the box provided.
Question 11: Read the question and each answer slowly. Circle the number corresponding to the appropriate answer.
Question 12: Read the question and each answer slowly. Circle the number corresponding to the appropriate answer. If answer is never, proceed to Question 14. Otherwise, continue to Question 13.
Question 13: Circle the number corresponding to the appropriate answer. Do not read answer choices.
Question 14: Circle the number corresponding to the appropriate answer. Do not read answer choices.
Question 15: Read the question and each answer slowly. Circle the number corresponding to the appropriate answer.
Question 16: Read the question and each answer slowly. Circle the number corresponding to the appropriate answer.
Question 17: If an explanation is requested for occupation, please tell respondent that we are looking for a broad category or title. ‘‘No occupation’’ is not an acceptable answer. If this should happen, please probe to see if the person is a student, homemaker, retired, unemployed, etc.
At the end of the questionnaire, you are asked to indicate whether the respondent was male or female. Please circle the appropriate answer. This is not a question for the respondent.
case 8 531
E x h i b i t 3
Questionnaire
Response Number Coupon Book
(Approach shoppers who appear to be between the ages of 18 and 49 and say . . . )
Hi, I’m from Midwest Research Services. Many companies like to know your preferences and opinions about new products and promotions. If you have about 5 minutes, I’d like to have your opinions in this marketing research stud y .
(If refused, terminate)
Have you eaten lunch or dinner in, or carried food away from, a fast-food restaurant in the last seven days? . . . (must answer yes to continue)
Have you eaten restaurant pizza within the last thirty days, either at the restaurant or by having it delivered? . . . (must answer yes to continue)
Which age group are you in? (read answers, circle number)
1 18–24 2 25–34 3 35–49 4 Other—Terminate interview
I am now going to show you fi ve different coupon concepts and ask you three questions for each. Please respond to each coupon independently of the others. Look at the next coupon only when I ask you to.
Please read the fi rst coupon concept. Using a ten-point scale, how would you rate this concept if one represents very poor val ue and ten represents very good value?
Looking at the second scale, how would you rate this concept if one represents de fi nitely would not use and ten represents de fi nitely would use?
Why did you respond as you did for use?
Please turn the page and read the next coupon concept. Ignoring the last coupon and using the same scale, how would you rate this concept in terms of value?
Referring to the second scale, how would you rate this concept in terms of your likeliness to use? Why did you respond as you did for use?
Please turn the page and read the next coupon concept. Ignoring the last coupon and using the same scale, how would you rate this concept in terms of value?
Referring to the second scale, how would you rate this concept in terms of your likeliness to use? Why did you respond as you did for use?
Please turn the page and read the next coupon concept. Ignoring the last coupon and using the same scale, how would you rate this concept in terms of value?
Referring to the second scale, how would you rate this concept in terms of your likeliness to use? Why did you respond as you did for use?
532 case 8
E x h i b i t 3
Questionnaire (Continued)
Please turn the page and read the next coupon concept. Ignoring the last coupon and using the same scale, how would you rate th is concept in terms of value?
Referring to the second scale, how would you rate this concept in terms of your likeliness to use? Why did you respond as you did for use?
Thank you. The following questions will help us classify the preceding information.
How many children do you have living at home?
If answer is none, proceed to question 11.
What is the age of your youngest child?
How often do you eat fast food for lunch or dinner?
(read answers, circle number) 1 Once per month or less
2 Two to three times per month 3 Once or twice a week
4 More than twice a week
How often do you eat at Premium Pizza?
(read answers, circle number) 1 Never visited Premium Pizza
- Once per month or less
- Two to three times per month 4 Once a week or more
If answer is never, proceed to question 14.
Do you yourself usually buy whole pies or slices at Premium Pizza?
- whole pies
- slices (circle one)
Have you used fast-food or restaurant coupons in the last 30 days?
1 yes 2 no
(circle one)
Have you ever used coupons for Premium Pizza?
(read answers, circle number) 1 Never
2 I sometimes use them when I have them. 3 I always use them when I have them.
What is your marital status:
(read answers, circle number) 1 Single
- Married
- Divorced, separated, widowed
What is your occupation?
This is not a question for the respondent.
Please circle appropriate answer—respondent was: 1 male
2 female (circle number)
Thank you for your participation—Terminate interview at this time.
case 8 533
E x h i b i t 4 Stimuli
Very Poor Value
2
3
4
5
6
7
8
9
10
Very Good Value
Definitely Would Not Use
2
3
4
5
6
7
8
9
10
Definitely Would Use
COUPON
Premium Pizza, Inc.
offer. Coupons and scales were therefore assembled in a booklet so that, as the interviewer showed each double- page spread, the respondent would see the scales on the top page and the coupon in question on the bottom page (see Exhibit 4).
Because the researcher wished to counterbalance the order in which the coupons were viewed and rated, the five coupons were organized into booklets of six different sequences. Each sequence was subsequently bound in one of six distinctly colored binders. A total of 96 question- naires were then printed in six different colors to match the binder. In this way, there were 16 questionnaires of each color, and the color of the respondent’s question- naire indicated the sequence that he or she had seen.
The questionnaire and procedure were pretested at a mall similar to the target mall and were found to be satisfactory.
Questions
- Is the choice of mall intercept interviews an appro- priate data collection method given the research objectives?
- Do you think that there are any specific criteria that the choice of shopping mall should satisfy?
- Evaluate the instructions to interviewers.
- Evaluate the questionnaire.
- Do you think that it is worthwhile to present the coupons in a binder, separate from the question- naire? Why or why not?
- Do you consider it advisable to rotate the order of presentation of coupons? Why or why not?
534 case 8
case 9
First Federal Bank of Bakersfield
The Equal Credit Opportunity Act, which was passed in 1974, was partially designed to protect women from dis- criminatory banking practices. It forbade, for example, the use of credit evaluations based on gender or marital status. Although adherence to the law has changed the way many bankers do business, women’s perception that there is a bias against them by a particular financial insti- tution often remains unless some specific steps are taken by the institution to counter that perception.
Close to a dozen ‘‘women’s banks’’—that is, banks owned and operated by and for women—opened their doors during the 1980s with the specific purpose of tar- geting and promoting their services to this otherwise underdeveloped market. Although women’s banks cur- rently are evolving into full-service banks serving a wide range of clients, a number of traditional banks are moving in the other direction by attempting to develop services that are targeted specifically toward women. Many of these institutions see such a strategy as a viable way to attract valuable customers and to increase their market share in the short term while gaining a competitive advantage by which they can compete in the long term as the roles of women in the labor force gain in importance. One can find, with even the most cursory examination of the trade press, examples of credit-card advertising that depicts single, affluent, and head-of-the-household female card holders; financial seminar programs for wives of affluent professional men; informational literature that details how newly divorced and separated women can obtain credit; and entire packages of counseling, educa- tional opportunities, and special services for women.
The First Federal Bank of Bakersfield was interested in developing its own program of this kind. The execu- tives were curious about a number of issues. Were wom- en’s financial needs being adequately met in the Bakersfield area? What additional financial services would women especially like to have? How do Bakersfield’s women feel about banks and bankers? Was First Federal in a good position to take advantage of the needs of women? What channels of communication might be best to reach women who might be interested in the services that First Federal had to offer?
The executives believed that First Federal might have some special advantages if it did try to appeal to women. For one thing, the Bakersfield community seemed to be quite sensitive to the issues being raised by the feminist movement. For another, First Federal was a small, per- sonal bank. The executives thought that women might be more comfortable in dealing with a smaller, more personalized institution and that the bank might not have the traditional ‘‘image problem’’ among women that larger banks might have.
Research Objectives
One program the bank executives were considering that they believed might be particularly attractive to women was a series of financial seminars. The seminars could cover a number of topics, including money management, wills, trusts, estate planning, taxes, insurance, invest- ments, financial services, and establishing a credit rating. The executives were interested in determining women’s reactions to each of these potential topics. They were also interested in knowing what the best format might be in terms of location, frequency, length of each pro- gram, and so on, if there was a high level of interest. Consequently, they decided that the bank should con- duct a research study that had the assessment of the fi- nancial seminar series as its main objective but that also shed some light on the other issues they had been debat- ing. More specifically, the objectives of the research were as follows:
- Determine the interest that exists among women in the Bakersfield area for seminars on financial matters.
- Identify the reasons why Bakersfield women would change, or have changed, their banking affiliations.
- Examine the attitudes of Bakersfield women to- ward financial institutions and the people who run them.
- Determine if there was any correlation between the demographic characteristics of women in the Bakersfield area and the services they might like to have.
- Analyze the media usage habits of Bakersfield-area women.
Method
The assignment to develop a research strategy by which these objectives could be assessed was given to the bank’s internal marketing research department. The department consisted of only five members—Beth Anchurch, the research director, and four project analysts. As Anchurch pondered the assignment, she was concerned about the best way to proceed. She was particularly concerned with the relatively short amount of time she was given for the project. Top executives thought that there was promise in the seminar idea. If they were right, they wanted to get on with designing and offering the seminars before any of their competitors came up with a similar idea. Thus, they specified that they would like the results of
case 9 535
the research department’s investigation to be available within 45 to 50 days.
As Anchurch began to contemplate the data collec- tion, she became particularly concerned with whether the study should use mail questionnaires or telephone interviews. She had tentatively ruled out personal inter- views because of the short deadline that had been imposed. After several days of contemplating the alterna- tives, she finally decided that it would be best to collect the information by telephone. Further, she decided that it would be better to hire out the telephone interviewing than to use her four project analysts to make the calls.
Anchurch believed that the multiple objectives of the project required a reasonably large sample of women so that the various characteristics of interest would be suffi- ciently represented to enable some conclusions to be drawn about the population of Bakersfield as a whole. After pondering the various cross tabulations in which the bank executives would be interested, she finally decided that a sample of 500 to 600 adult women would be sufficient. The sample was to be drawn from the white pages of the Bakersfield telephone directory by the Bakersfield Interviewing Service, the firm that First Federal had hired to complete the interviews.
The sample was to be drawn using a scheme in which two names were selected from each page of the direc- tory, first by selecting two of the four columns on the page at random and then by selecting the fifteenth name in each of the selected columns. The decision to sample names from each page was made so that each interviewer could operate with certain designated pages of the direc- tory, since each was operating independently out of her home.
The decision to sample every fifteenth name in the selected columns was determined in the following way. First, there were 328 pages in the directory with four columns of names per page. There were 80 entries per column on average, or approximately 26,240 listings. Using Bureau of the Census data on household composi- tion, it was estimated that 20% of all households would be ineligible for the study because they did not contain an adult female resident. This meant that only 20,992 (0.80 3 26,240) of the listings would probably qualify. Since 500 to 600 names were needed, it seemed easiest to select two columns on each page at random and to take the same numbered entry from each column. The interviewer could then simply count or measure down from the top of the column. The number 15 was deter- mined randomly; thus, the fifteenth listing in the
randomly selected columns on each page was called. If the household did not answer or if the women of the house refused to participate, the interviewers were instructed to select another number from that column through the use of an abbreviated table of random num- bers that each was given. They were to use a similar pro- cedure if the household that was called did not have an adult woman living there.
First Federal decided to operate without callbacks because the interviewing service charged heavily for them. Anchurch did think it would be useful to follow up with a sample of those interviewed to make sure that they indeed had been called, since the interviewers for Bakersfield Interviewing Service operated out of their own homes and it was impossible to supervise them more directly. She did this by selecting at random a handful of the surveys completed by each interviewer. She then had one of her project assistants call that respondent, verify that the interview had taken place, and check the accuracy of the responses of a few of the most important questions. This audit revealed absolutely no instances of interviewer cheating.
The completed interview forms were turned over to First Federal for its own internal analysis. As part of this analysis, the project analyst compared the demographic characteristics of those contacted to the demographic characteristics of the population in the Bakersfield area as reported in the 2000 census. The comparison is shown in Exhibit 1. The analyst also prepared a summary of the nonresponses and refusals by interviewer. This compari- son is shown in Exhibit 2.
Questions
- Compare the advantages and disadvantages of using telephone interviews rather than personal interviews or mail questionnaires to collect the needed data.
- The short deadline moved Anchurch to forgo per- sonal interviews and mail questionnaires, but there were other options besides telephone interviews. Could you make a case for another communication method that might be appropriate here?
- Given the large number of not-at-home attempts, was First Federal wise to skip callbacks? Why or why not?
- If you were Anchurch, would you be happy with the performance of the Bakersfield Interviewing Service? Why or why not?
536 case 9
E x h i b i t 1 Selected Demographic Comparison of Survey Respondents with Bureau of Census Data
PERCENTAGE OF WOMEN
Characteristic/Category Survey Census
Marital Status
Married
53
42
Single
30
40
Separated
1
2
Widowed
9
9
Divorced
7
7
Age
18–24
23
23
25–34
30
28
35–44
16
14
45–64
18
21
65þ
13
14
Income
Less than $10,000
9
29
$10,000-$19,999
19
29
$20,000-$50,000
58
36
More than $50,000
2
6
Refused
12
E x h i b i t 2 Results of Calls by Interviewer
NUMBER OF NOT-AT-HOMES
Interviewer Line Busy No Answer
INELIGIBLESa
NUMBER OF REFUSALS
Initial After Partial Completion
NUMBER OF COMPLETIONS
1
7
101
36
15
0
30
2
2
45
13
16
0
30
3
11
71
23
17
7
30
4
14
56
47
35
6
39
5
9
93
10
23
13
30
6
5
102
28
63
14
35
7
6
36
17
16
0
18
8
7
107
23
13
0
30
9
11
106
36
47
0
30
10
10
55
6
35
9
30
11
38
83
48
92
0
30
12
5
22
3
8
0
9
13
23
453
102
65
7
99
14
12
102
27
31
0
19
15
7
173
29
66
0
34
16
2
65
9
33
0
22
Total
169
1,670
457
575
56
515
1,839
631
aNo adult female resident.
case 9 537
case 10
Caldera Industries1
Chris Totten has just begun a summer internship at Caldera Industries, a national supplier of electronics components. Caldera’s clients include OEM (original equipment manufacturers) firms that market televisions, home stereo and audio, and computer products to the general public. Returning from lunch, Chris finds a memo and questionnaire in her mailbox (see Exhibits 1 and 2).
Questions
- Evaluate the questionnaire in relation to the issues raised by Manuel Ortega.
- How would you recommend the instrument be pretested?
E x h i b i t 1
Caldera Industries
Serving our Customers’ Electronics Needs for over 22 Years
CI
Internal Memorandum
TO: Chris Totten
Marketing Analyst Intern
cc: Caren Menlo Marketing Manager
From: Manuel Ortega
Vice President for Sales and Marketing
Date: May 23, 2003
Regarding: Evaluation of Market Research Questionnaire
In three weeks, I will be meeting with executives from a number of our client companies. One of the items on the agenda is the research project our company has agreed to undertake on their behalf. At that meeting, the final version of our questionnaire will be distributed and approved.
On the attached pages is an initial draft of the Consumer Electronics Questionnaire we plan on using for the study. As the newly hired marketing intern, and because of your marketing research coursework experience, I suggested to our marketing manager, Caren Menlo, that reviewing the questionnaire would make an ideal first assignment for you. She agreed.
Please examine the attached questionnaire and provide me with a written memo of your analysis, comments, and suggestions for improvement (if you believe any are warranted) within two (2) weeks. More specifically, I am interested in your comments on the following issues:
- The type and amount of information being sought
- Appropriateness of the type of questionnaire designed and its method of administration
- The content of questions in the draft document
- Response formats used for the various questions
- Question wording
- Question sequencing
- Physical characteristics and layout of the instrument
I am also interested in any comments or suggestions you have on pretesting the questionn aire. I look forward to reading your memo.
1This case was prepared by Michael R. Luthy, Ph.D., Professor of Marketing, W. Fielding Rubel School of Business, Bellarmine University, 2001 Newburg Road, Louisville, KY 40205. Reprinted with permission.
538 case 10
E x h i b i t 2 Consumer Electronics Research Questionnaire
Directions: This questionnaire has been developed for a consortium of computer and home entertainment companies (who wish to remain anonymous). Complete all questions and mail this questionnaire to us today.
Quality Research Associates 5716 N. Woodlawn Court Champaign, IL 61820
- Name:
- Sex:
- How old are you:
Mr. Mrs.
- Intelligence: Only completed college degree (Bachelor’s)
Completed some graduate work
Completed graduate degree
Completed graduate degree beyond masters
- Ethnic Status: White Asian
Black Indian
Asian Other What?
- Political Party Support: Democrat
Republican
Independent
Other
- Your Occupation:
- Spouse’s Name and Age:
- Number of Children: (if children, go to question 61)
- Your Company:
- Your Work Fax Number: ( ) -
- How Long Have You Been Married: Never married
Less than a year
Between 1 and 5 years
Over 5 but less than 10 years
Over 15 years but less than 20 years
More than 20 years
- Your Annual Income: $
- Social Security Number: - -
- The sponsors of this research are constantly introducing new products that they believe you (and your loved one, if any) will be interested in. In order to better make you aware of these offerings, please provide your telephone number below.
( ) -
- Do you own a computer at home or at work?
Yes No
- During an average week, how much time do you spend on it?
Hours Minutes
- Doing what mostly?
For each of the products listed below, please indicate the extent of your satisfaction with it, ceteris paribus, by either circling or placing an “X” on the line to the right of each statement.
- Apple Computers and Peripherals.
- Gateway Computers and Peripherals.
- Dell Computers and Peripherals.
- IBM Computers and Peripherals.
- Samsung Computers and Peripherals.
- Hewlett-Packard Computers and Peripherals.
- MacIntosh Computers and Peripherals.
- Hitachi, Ltd. Computers and Peripherals.
- Unisys Computers and Peripherals.
- Tandy Computers and Peripherals.
Mild Satisfaction Extremely Satis fi ed
(Continued)
case 10 539
E x h i b i t 2
Consumer Electronics Research Questionnaire (Continued)
29. Without being too loquacious, what emerging trends or technologies do you see as important to you that computer manufacturers
(both hardware and software) should consider in developing new products?
30. How many different computer chatrooms have you visited in the last month?
1–2
2–3
3–4
more than four
Below is a listing of ways in which people interact with consumer electronics on a quasi regular basis. What percentage of your time do
you typically spend with each?
On A verage,
Check Below Number of
If Yo u Do Do “Others” Present
Not Use Use During Y our Usage
31. % Work related computer activities
32. % Entertainment related computer activities
33. % Watching Network Television
34. % Watching Cable Television
35. % Watching Premium Cable Services
36. % Watching Rented Movies on VCR
37. % Watching Rented Movies on DVD
38. % Listening to Music on Radio or on CD’s
39. % Other (specify)
Referencing the music you listen to, vis à vis your response to question 38 above (see question 38 if needed), which are your favorite
musical periods or types? Please indicate your first 10 choices in numerical order.
40. Earlier than Renaissance
41. Renaissance
42. Baroque
43. Classical
44. Romantic
45. Impressionistic
46. Neo-Classical
47. Contemporary
48. Contemporary Christian
49. Rock
50. Hard Rock
51. Grunge Rock
52. Jazz
53. Easy Listening
54. Jazz/Rock Fusion
55. Bluegrass
56. Contemporary
57. Folk Music
58. Country
59. Western
60. Other
540 case 10
E x h i b i t 2 Consumer Electronics Research Questionnaire (Continued)
- Chart your child’s usage of the following computer-related activities in 2002: (A never, B once to twice a per month, C once to twice a week, D every week, E twice or more per week, F daily, G multiple times a day). If you have more than one child, use the computer usage of the oldest.
Word Processing
EXCEL
Database Programs
Internet “Surfing”
Internet Chatrooms
Games
Jan 1–Jan 15
Jan 16–Jan 31
Feb 1–Feb 15
Feb 16–Feb 28
Mar 1–Mar 15
Mar 16–Mar 31
Apr 1–Apr 15
Apr 16–Apr 30
May 1–May 15
May 16–May 31
Jun 1–Jun 15
Jun 16–Jun 30
Jul 1–Jul 15
Jul 16–Jul 31
Aug 1–Aug 15
Aug 16–Aug 31
Sep 1–Sep 15
Sep 16–Sep 30
Oct 1–Oct 15
Oct 16–Oct 31
Nov 1–Nov 15
Nov 16–Nov 30
After completing, return to question 23
What is the most you would be willing to spend to purchase the following consumer electronic products if you were going to purchase them within the next year? and why?
- $ DVD player
- $ External Zip drive
- $ Big Screen Television
- $ Portable Stereo or Television
- $ Digital Camera
Why?
- To what degree do you believe that access to the Internet A E is important to your family’s entertainment needs?
- What emerging trends or technologies do you see as important to you that computer manufacturers (both hardware and software ) should consider in developing new products?
- On a separate sheet of paper, please provide the names and addresses of at least three (3) friends or relatives that have r ecently (within the last two years) purchased an advanced consumer electronics product so that we may contact them.
Mail your completed questionnaire in a standard business size envelope to:
Quality Research Associates 4518 North Trails End Cleveland, OH 34454
(a first-class stamp will be needed)
case 10 541
case 11
School of Business1
The School of Business, one unit in a public university enrolling over 40,000 students, has approximately 2,100 students in its bachelor’s, master’s, and doctorate pro- grams emphasizing such areas of business as accounting, finance, information and operations management, mar- keting, management, and others. Because the School of Business must serve a diverse student population on lim- ited resources, it feels it is important to accurately meas- ure students’ satisfaction with the school’s programs and services.
Accurate measurement of student satisfaction will ena- ble the school to target improvement efforts to those areas of greatest concern to students, whether that be by major, support services, or some other aspect of their educational experience. The school feels that improving its service to its customers (students) will result in more satisfied alumni, better community relations, additional applicants, and increased corporate involvement. Because graduate and undergraduate students are believed to have different expectations and needs, the school plans to investigate the satisfaction of these two groups separately.
In a previous survey of graduating seniors using open-ended questions, three primary areas of concern were identified: the faculty, classes/curriculum, and resources. Resources consisted of five specific areas: Undergraduate Advising Services, the Learning Center, Computer Facilities, the Library, and the Career Services Office. The research team for this project devel- oped five-point Likert scale questions to measure stu- dents’ satisfaction in each of these areas. In addition, demographic questions were included to determine whether satisfaction with the school was a function of a student’s grade point average, major, job status upon graduation, or gender. Previous surveys used by the
School of Business and other published satisfaction scales provided examples of questions and question formats. Exhibit 1 shows the questionnaire that was used.
Although the survey contained primarily Likert scale questions, a few open-ended questions were also asked. Specifically, respondents were asked to list the Business School’s strengths and weaknesses as well as their reasons for not using the various resource areas. The responses obtained to the question seeking the school’s strengths and weaknesses were classified into four major sub- groups: classes, reputation, resources, and professors. A sample of the actual verbatims are provided in Exhibit 2.
Questions
- Considering customer satisfaction as it applies to a university setting, what are some other areas in addition to those identified for the project that may contribute to students’ satisfaction/dissatisfaction with their education experience?
- Does the current questionnaire provide information on students’ overall satisfaction with their undergrad- uate degree program? Explain. What revisions are necessary to this questionnaire to obtain an overall satisfaction rating?
- Can the School of Business use the results of this study to target the most important areas for improvement? Explain. Identify changes to the ques- tionnaire that would allow the school to target areas based on importance.
- What are the advantages and disadvantages of using open-ended questions to identify the school’s strengths and weaknesses? Taking the responses in Exhibit 2, what system would you use for coding these responses?
1The contributions of Sara Pitterle to the development of this case are gratefully acknowledged.
542 case 11
E x h i b i t 1
Survey of Graduating Business Stu
dents
In your opinion, what ar e the greatest strengths and weaknesses of the Business School?
Str ongly
Strengths
W eaknesses
CLASSES/CURRICULUM
Please indicate the extent to which you agr ee with the following statements.
Str ongly Neither
Agr ee Agr ee Agr ee/Disagree
Disagree
Disagree
I was satisfied with the quality of classes I took within my major.
(1) (2) (3)
(4)
(5)
I was able to take enough electives within my major.
(1) (2) (3)
(4)
(5)
“Lecture-Driven” vs. “Project” or “Group” class formats are most useful for learning.
(1) (2) (3)
(4)
(5)
The business school taught too much theory and not enough about real-life applications
.
(1) (2) (3)
(4)
(5)
Creative problem solving was encouraged in my classes.
(1) (2) (3)
(4)
(5)
My classes were too large.
(1) (2) (3)
(4)
(5)
I was challenged by my coursework.
(1) (2) (3)
(4)
(5)
There were not enough group projects in my classes.
(1) (2) (3)
(4)
(5)
More night courses should be offered.
(1) (2) (3)
(4)
(5)
Overall, the material presented in my classes was current.
(1) (2) (3)
(4)
(5)
F ACU L TY
Str ongly Neither
Str ongly
Agr ee Agr ee Agr ee/Disagree
Disagree
Disagree
My professors are concerned about my future success.
(1) (2) (3)
(4)
(5)
Overall, the Business School professors are good teachers.
(1) (2) (3)
(4)
(5)
The Business School places too much emphasis on research and not enough on teaching.
(1) (2) (3)
(4)
(5)
Overall, my professors were accessible outside of class.
(1) (2) (3)
(4)
(5)
The Business School takes my comments on professor evaluation forms seriously.
(1) (2) (3)
(4)
(5)
Overall, my professors provided adequate office hours during the semester.
(1) (2) (3)
(4)
(5)
(Continued)
case 11 543
E x h i b i t 1
Survey of Graduating Business Students (Continued)
Overall, my professors encouraged students to raise relevant questions during class.
(1) (2) (3) (4) (5)
My professors tested memorization skills on exams more than my ability to apply concepts.
(1) (2) (3) (4) (5)
Overall, the Business School professors interacted well with students.
(1) (2) (3) (4) (5)
My professors showed creativity in their teaching methods.
(1) (2) (3) (4) (5)
My professors are at the leading edge of knowledge in their fields.
(1) (2) (3) (4) (5)
I approve of TA’s teaching foundation courses.
(1) (2) (3) (4) (5)
My professors were stimulating.
(1) (2) (3) (4) (5)
RESOURCES
Advising
Did you ever use the undergraduate advising of fi ce?
(1) Yes (2) No
If not, why not?
If you answered yes to the question above, please complete the remainder of the questions regarding Advising. If you answered no,
please proceed to the following section—Learning Cente r .
S tro n g ly Neither S tro n g ly
Agr ee Agr ee Agr ee/Disagree Disagree Disagree
The undergraduate advising office played a big role in helping me plan my business curriculum.
(1) (2) (3) (4) (5)
The undergraduate advising office should have more advisors.
(1) (2) (3) (4) (5)
The advisor(s) in the undergraduate advising office was (were) helpful.
(1) (2) (3) (4) (5)
The staff in the advising office was helpful.
(1) (2) (3) (4) (5)
I felt like I was bothering the advisor(s) in the undergraduate advising office if I asked him/her a question.
(1) (2) (3) (4) (5)
The advisor(s) in the undergraduate advising office was (were) concerned about my needs.
(1) (2) (3) (4) (5)
If there were more undergraduate advisors, I would have utilized the advising services more often.
(1) (2) (3) (4) (5)
Advice offered by the advising office was not helpful to me.
(1) (2) (3) (4) (5)
544 case 11
E x h i b i t 1
Survey of Graduating Business Students (Continued)
Lear ning Center
Did you ever use The Learning Center?
(1) Yes (2) No
If not, why not?
If you answered yes to the question above, please complete the remainder of the questions regarding The Learning Cente r . If you answered no, please proceed to the following section—Career-Services Facilities/Staff.
S tro n g ly Neither S tro n g ly Agr ee Agr ee Agr ee/Disagree Disagree Disagree
The Learning Center was useful to me.
(1) (2) (3) (4) (5)
The staff at the Learning Center are helpful.
(1) (2) (3) (4) (5)
The Learning Center needs to extend its hours.
(1) (2) (3) (4) (5)
Career-Services Facilities/Staf f
Did you ever use the Career-Services of fi ce as a resource in your search for full- or part-time employment?
(1) Yes (2) No
If not, why not?
If you answered yes to the question above, please complete the remainder of the questions regarding Career-Services Facilities/Staff. If you answered no, please proceed to the following section—Computer Facilities/Staff.
S tro n g ly Neither S tro n g ly Agr ee Agr ee Agr ee/Disagree Disagree Disagree
Overall, the Career-Services office has been a valuable resource in my job search.
(1) (2) (3) (4) (5)
The staff in the Career-Services office are helpful.
(1) (2) (3) (4) (5)
The Career-Services office is/was my main resource used in my search for my job.
(1) (2) (3) (4) (5)
In my opinion, the Career-Services office is understaffed.
(1) (2) (3) (4) (5)
I was pleased with the number of companies interviewing at the Career-Services office within my major.
(1) (2) (3) (4) (5)
The Career-Services office is successful at attracting desirable employers to interview on campus.
(1) (2) (3) (4) (5)
The sign-up process for interviews at the Career-Services office is fair.
(1) (2) (3) (4) (5)
The Career-Services office provides enough information on how to use the Resume Expert software.
(1) (2) (3) (4) (5)
The Career-Services office offers adequate interview training.
(1) (2) (3) (4) (5)
(Continued)
case 11 545
E x h i b i t 1
Survey of Graduating Business Students (Continued)
Computer Facilities/Staf f
Did you ever use the Business School’s computer facilities?
(1) Yes (2) No
If not, why not?
If you answered yes to the question above, please complete the remainder of the questions regarding Computer Facilities/Staff. If you
answered no, please proceed to the following section—Library Facilities/Staff.
S tro n g ly Neither S tro n g ly
Agr ee Agr ee Agr ee/Disagree Disagree Disagree
The computer room needs to extend its weekend hours.
(1) (2) (3) (4) (5)
The computer room needs to extend its night hours.
(1) (2) (3) (4) (5)
More computers are needed in the computer room.
(1) (2) (3) (4) (5)
More printers are needed in the computer facilities.
(1) (2) (3) (4) (5)
The computer-room staff is helpful.
(1) (2) (3) (4) (5)
A computer was available when I needed to use one.
(1) (2) (3) (4) (5)
Librar y Facilities/Staf f
Did you use the Business School’s library facilities?
(1) Yes (2) No
If not, why not?
If you answered yes to the question above, please complete the remainder of the questions regarding Library Facilities/Staff. If you
answered no, please proceed to the following section—Student Organizations.
S tro n g ly Neither S tro n g ly
Agr ee Agr ee Agr ee/Disagree Disagree Disagree
The Library staff is helpful.
(1) (2) (3) (4) (5)
The Library has adequate study space.
(1) (2) (3) (4) (5)
546 case 11
E x h i b i t 1
Survey of Graduating Business Students (Continued)
Student Organizations
W e re you a member of any Business School student organizations?
(1) Yes (2) No
If not, why not?
If you answered yes to the question above, please complete the remainder of the questions regarding Student Organizations. If y ou answered no, please proceed to the following section—GENERAL.
How many organizations were you a member of?
(1) 1
(2) 2
(3) 3
(4) 4
Did you hold an of fi ce? (1) Yes (2) No
Do you believe the faculty and staff were supportive of the student organizations?
(1) Yes (2) No (3) Don’t know
What were your reasons for joining?
GENERAL
Str ongly Neither Str ongly Agr ee Agr ee Agr ee/Disagree Disagree Disagree
My Business School education has given me a sense of accomplishment.
(1) (2) (3) (4) (5)
The Business School is well respected nationally.
(1) (2) (3) (4) (5)
My undergraduate degree has prepared me well for a successful career in business.
(1) (2) (3) (4) (5)
The caliber of my classmates enhanced my learning.
(1) (2) (3) (4) (5)
The Business School should require more computer courses.
(1) (2) (3) (4) (5)
The copying facilities at the Business School are inadequate.
(1) (2) (3) (4) (5)
My undergraduate experience was disappointing.
(1) (2) (3) (4) (5)
The Business School placed too much emphasis on a high GPA and not enough on learning.
(1) (2) (3) (4) (5)
I felt like a number here at the Business School.
(1) (2) (3) (4) (5)
The Business School should have a mandatory class on ethics for undergraduates.
(1) (2) (3) (4) (5)
(Continued)
case 11 547
E x h i b i t 1
Survey of Graduating Business Students (Continued)
Please indicate the extent to which you agree that each of the following factors POSITIVE L Y CONTRIBUTED to the quality of your
overall undergraduate business education:
S tro n g ly Neither S tro n g ly
Agr ee Agr ee Agr ee/Disagree Disagree Disagree
Class size in major classes:
(1) (2) (3) (4) (5)
Class size in required courses:
(1) (2) (3) (4) (5)
Group projects:
(1) (2) (3) (4) (5)
Case studies:
(1) (2) (3) (4) (5)
Multiple-choice exams:
(1) (2) (3) (4) (5)
Use of creative thought:
(1) (2) (3) (4) (5)
Guest lecturers:
(1) (2) (3) (4) (5)
Required classes:
(1) (2) (3) (4) (5)
Number of electives you can take:
(1) (2) (3) (4) (5)
Number of required computer courses:
(1) (2) (3) (4) (5)
Please indicate the extent to which you agree that each of the following core classes POSITIVE L Y CONTRIBUTED to the quality of your
overall undergraduate business education:
Comp Sci (1) (2) (3) (4) (5)
Managerial Acctg 302 (1) (2) (3) (4) (5)
Financial Acctg 200 (1) (2) (3) (4) (5)
Communications 320 (1) (2) (3) (4) (5)
Business Law 330 (1) (2) (3) (4) (5)
Corporate Finance 510 (1) (2) (3) (4) (5)
Marketing 520 (1) (2) (3) (4) (5)
Org. Behavior 530 (1) (2) (3) (4) (5)
Business Statistics 570 (1) (2) (3) (4) (5)
Mgt of Serv-Mfg Op 574 (1) (2) (3) (4) (5)
OVERALL (1) (2) (3) (4) (5)
GENERAL INFORMATION
Please mark the number corresponding to your gender:
(1) Female (2) Male
Are you a state resident?
(1) Yes (2) No
Please mark the number(s) corresponding to your major(s).
(1) Accounting (7) Marketing
(2) Actuarial Science (8) Quantitative Analysis
(3) Diversified (9) Real Estate
(4) Finance (10) Risk Management
(5) Information Systems (11) Transportation and Public Utilities
(6) Management and Human Resources
548 case 11
E x h i b i t 1
Survey of Graduating Business Students (Continued)
Please mark the number corresponding to your G P A.
(1) 3.5–4.0 (2) 3.0–3.49 (3) 2.5–2.99 (4) 2.0–2.49
Please mark the number of years it will take you to graduate.
(1) 31⁄2 (2) 4 (3) 41⁄2 (4) 5 (5) >51⁄2
During the program (excluding summers), have you been employed?
(1) Employed full time (2) Employed part time (3) Not employed
What do you plan to do upon graduation?
- full-time employment
- part-time employment
- graduate school
- other, please specify
If you intend to work full time, please specify if you:
- have already accepted a position
- are still in the process of interviewing
- other, please specify
THANK YOU FOR COMPLETING THE SUR VEY OF GRADUA TING BUSINESS STUDENTS
E x h i b i t 2
A Sample of the Survey Responses to Question 1 Regarding Strengths
and Weaknesses
Strengths Weaknesses
Breadth of courses and disciplines. Not enough real-life applications.
The increase in group projects was also helpful. Core classes tedious.
Classes in your major are relatively small. Too much emphasis on GPA.
Excellent faculty advising (not undergrad advising). Lack of advisors.
Good faculty. Excellent profs. Lack of support facilities.
Has a good reputation. Awful undergraduate advising. Required some thought-provoking classes (literature, Classes are too much on theory.
philosophy). The computer classes are a waste of time.
Free laser printing in the computer lab. Too many unnecessary core requirements that could be used The resources for information gathering are great. for another class or elective.
The options of resources available are great. Too many exams scheduled in the 6th and 12th weeks.
The competitiveness, quality of students. Too many required group projects. Nice that classes aren’t greatly dependent on Fridays (open to Can’t get classes when needed.
work or volunteering). Too few resources for the number of students.
Clear curriculum of what classes are needed if in Pre-Business Students not treated as individuals. or Business—although there are a lot of them, the core Not enough computers.
classes allow you to touch all majors. Makes students take core classes in each function of business.
A well-respected and less costly route to a business undergrad Need more case studies and seminar-type classes with fewer degree than other alternatives available. students.
National reputation. There is too much memorization and not enough practical A few good professors that make up for all the bad ones. application of knowledge.
Some of the professors are terrific and really care about the Making appointments to see advisors. students. Professors expect too much.
Computer courses are too technical.
case 11 549
case 12
Young Ideas Publishing Company
How does a company go about marketing products to a specific niche of the teenage market? That is the ques- tion confronting Bev Halley, co-owner of Young Ideas Publishing Company. Halley is convinced that her unconventional novels for young people would be very attractive to at least a segment of the teenaged market. She is unsure, however, about how to reach this ‘‘non- conformist’’ segment of the market.
Background
Three years ago, Halley wrote her first novel, a youth- oriented book (ages 15–18) entitled Illusions of Summer. None of the major publishers would publish the book, however, primarily because it dealt with several contro- versial social and political concerns. Most publishers sim- ply felt that such topics would not be of interest to enough high school teenagers to justify publication, although many agreed that the novel was of publication quality in other respects.
Frustrated in her efforts to publish her novel, Halley and a business partner, Teresa Martinez, decided to form their own publishing company and publish the book themselves. Both believed that teenagers would be inter- ested in social and political topics and would buy the book. Thus, Young Ideas Publishing Company was born. Halley hoped that effective marketing of the book on a local basis by the company might encourage national distributors to alter their positions toward the novel.
When Illusions of Summer was released, it was very well received by several literary critics, winning promis- ing reviews and awards. Despite its critical success, how- ever, commercial acceptance has been much harder to find. During the first 24 months after publication, only about 1,500 copies of the book have been sold, mostly through local bookstores, mail orders, and the company’s Web site. Most distributors were unwilling to handle the book because it was not from an established publisher. With few channels through which to market the prod- uct, it remains virtually unknown outside of a limited local market.
Even with this poor showing from a commercial standpoint, Halley continued to believe that so-called ‘‘nonconformist’’ teenagers would be willing to buy books of this nature. Accordingly, she wrote and pub- lished a second novel, Ultimate Choices. Once again, the novel dealt with several controversial issues for teens and social and political concerns; once again, the critics reacted favorably. Initial sales for Ultimate Choices have been better than they were for Illusions of Summer;
currently (two months after publication), about 250 cop- ies have been sold. By talking to clerks in local book- stores, Halley has learned that most of the books are being sold to teenagers.
Nature of the Problem
Although encouraged by the good reviews and increased sales of the second book, Halley and Martinez are con- cerned about the future of Young Ideas Publishing Company. The company has struggled to break even so far, and Martinez has indicated that the survival of the company may well depend on the success of the new novel.
Both partners are still convinced that a market exists for the novels. They now recognize, however, that they may not know enough about the teenage market to effectively market the novels. For example, they believe that insights are needed in the following areas:
- Will high school teenagers specifically select young adult novels, or do they think that these are written for younger teens?
- Are teenagers interested in social and political issues?
- Where do high school teenagers usually obtain books for pleasure reading?
- Do teens purchase books for themselves, or do parents purchase books for them?
- What types of promotional items do high school teens enjoy most?
- What advertising media are most effective in reach- ing teens?
- How do ‘‘nonconformist’’ teens differ on these issues from other teens?
You have been hired by Young Ideas Publishing Company to develop and implement a research project to investigate these ideas. Resources are limited; Halley would like the results of the research within 60 days.
Questions
- Based on the information provided and your knowl- edge of marketing and marketing research, define the research problem.
- How would you propose to measure the degree of nonconformity? Develop a set of items intended to assess this construct.
- What is the target population for your study?
- Discuss your proposed sampling plan, including the implications for the implementation of the project.
550 case 12
case 13
Newt vs. Toade1
Shortly after assuming his position as majority leader of the U.S. Senate four years ago, Republican Senator James Newton began receiving overwhelmingly negative cover- age in the news media. A year later, he was reprimanded by his colleagues for an admitted breach of Senate ethics that had occurred prior to his becoming majority leader. Although his infraction was not serious enough to force him to resign, he was nicknamed ‘‘Newt’’ by his detrac- tors, and his job approval ratings plummeted. While it seems implausible to most observers now, he would like to make a political recovery and become a viable candidate for the presidency in the next election.
Nearly two years ago, Senator Newton’s aides hired a public relations firm to help boost his approval ratings among all registered voters. Between January and December of that year, however, nothing this firm tried had any impact. At that point Salvadore Toade, principal owner of Toade & Associates, a relatively new public relations firm, approached Newton’s top aides with the following bold proposal. ‘‘If the Senator will turn the account over to my firm, my associates and I will develop and implement a new public relations campaign and will initially bill him only for out-of-pocket expenses. If after six months the senator’s overall approval rating among all registered voters remains at 18%, the current level in vir- tually every media poll, or if it moves lower, no additional payment will be required. But, if his approval rating increases in that time period from the baseline level of 18%, the senator must pay $10,000 for every percentage point it has gone up.’’
Senator Newton agreed to the deal. In July, he received a letter from Toade & Associates claiming his approval rating among registered voters had increased
15 points and requesting payment in the amount of
$150,000. Toade & Associates indicated it had con- ducted its own poll because, unlike six months ago when all of the media-sponsored polls reported similar approval ratings (i.e., approximately 18%), recent polls reported approval ratings ranging from as low as 13% to as high as 27%. Because none of the media-sponsored polls indicated an increase as large as 15 points (using 18% as the baseline), Newton asked his lawyers to inves- tigate the sampling plan used by Toade to measure his approval rating. The investigation produced the follow- ing deposition from Mr. Toade himself:
We exercised great care to do things very scien- tifically. To ensure that people from every
1This case was prepared by Jon R. Austin, Ph.D., Associate Professor of Marketing, Cedarville University, 251 North Main Street, Cedarville, OH 45314.
socioeconomic group were represented, we defined five different groups based on household income: (1) Under $20,000, (2) $20,000-$34,999,
(3) $35,000-$59,999, (4) $60,000-$99,999, and
(5) $100,000 and above. We then obtained com- prehensive national lists of people in each income category. Within each list, our software numbered the names from 1 to n and used a random-number generator to select 1,000 names. We then called each of the 5,000 names generated and interviewed everybody willing to participate. The overall refusal rate was 9%, and none of the income groups had refusal rates any larger than 12%. Our partici- pation rate was so high because we asked only two questions: (1) ‘‘Are you familiar with James Newton, majority leader of the U.S. Senate?’’ and
(2) ‘‘Do you approve or disapprove of Senator Newton’s performance as majority leader?’’
Being dissatisfied with Toade’s study, Senator Newton asked his staff to commission a study with an in- dependent research firm using the same questions employed in the Toade study. For political and financial reasons, a firm from the senator’s home state was employed rather than one of the larger Washington- based polling agencies. This survey found the senator’s approval rating had improved by only 5 points. Therefore, Newton sent a letter to Toade summarizing the findings and enclosed a check for $50,000.
Angry that Newton had not paid the full $150,000, Mr. Toade dispatched his lawyers to look into the mat- ter. The transcript of an interrogation of the research director who managed Newton’s study included the following statement:
We felt it to be very important to ensure that every region of the country was fairly represented. Therefore, we identified all of the major newspa- pers in each of the 50 states. Within each state, we selected the newspaper with the largest number of subscribers. With the assistance of Republican members of Congress in each state, we obtained a random list of 250 subscribers for each selected newspaper. I want to emphasize, each newspaper randomly selected the names for our list. Our interviewers then called as many names on each list as were necessary to get 100 people to complete the survey. Using this approach, we obtained a total sample size of 5,000. As you know, our survey found that Senator Newton’s approval rating had not increased nearly as much as indicated in your client’s study.
case 13 551
Questions
- What is the target population?
- What population parameter is being estimated, and what statistic is being calculated?
- What sampling frames were used in each of the two studies?
- What type of sampling procedure was employed in the study conducted by Toade & Associates? Explain the basis of your determination.
- Do you believe the sampling procedure employed in the Toade study was appropriate given the objec- tive of measuring the senator’s overall job approval rating? Describe your reasoning in detail.
- What type of sampling procedure was employed in the study conducted by the research firm on behalf
of Senator Newton? Explain the basis of your determination.
- Do you believe the sampling procedure employed in the study conducted for Senator Newton was appropriate given the objective of measuring the senator’s overall job approval rating? Describe your reasoning in detail.
- Which of the two studies do you believe produced the numbers that are most trustworthy? Explain why you have drawn this conclusion.
- Design a sampling plan that could be used in a new study that you believe would provide the fairest way to resolve this case. Describe in detail your rea- soning for proposing this method of sampling.
552 case 13
case 14
Rockway Publishing Company, Inc.1
The Problem
Rockway Publishing Company publishes telephone direc- tories for suburban and rural communities. Headquartered in a large Midwestern metropolitan area, Rockway pub- lishes directories for over 80 markets, mostly in the Midwestern and southern parts of the United States. The telephone directories are published as an alternative to, and in competition with, directories published by the local telephone companies serving these markets. Rockway has been very successful in offering yellow-page advertisers a quality product at competitive rates. However, there have been some problems with distribution.
The distribution of the directories is handled in one of two ways. Winston Delivery Company has been under contract for the past two years to hand deliver directories in suburban areas and small cities. Winston hires college students, at minimum wage plus car expenses, to make the deliveries. Each student is given an assigned area of streets and rural routes to cover. For some locations, particularly where the households are heavily rural, the directories are sent through the mail. Recently, Rockway’s salespeople have been receiving complaints from advertisers that some of their customers have not received a directory. It is believed by some of the salespeople that as many as 10 to 15% of households, in any given market, are not receiving a directory.
Survey Method
Faced with the prospect that not all of the directories intended for households are being delivered, Ron
Combs, president of Rockway, instituted a plan for measuring the discrepancy. Approximately three weeks after a directory is delivered in an area, a sample of households is telephoned, and respondents are asked if the directory has been received. The results are tabulated according to whether the household has a city or rural address. To be counted, the respondent must be sure that the book has been received or has not been received. Respondents who are uncertain or don’t know are given more information about the time of delivery, what the face of the book looks like, and how it was delivered (by mail or by hand). If they are still uncertain, they are replaced in the sample and not included in the tally. The respondent may be anyone in the household who answers the phone or is available at the time of the call. Combs wants to ensure that sampling error is not greater than þ/- 2 percentage points.
The Sampling Plan
The sampling frame is an internally produced cross directory of white-page listings by street. The inter- viewer goes through the pages, arbitrarily pulling names from the listings. If a respondent says a directory has not been received, additional calls are made on that street to determine if the entire street was missed. However, these additional calls are not included in the survey results.
Exhibit 1 shows the results of the survey for areas dis- tributed to in the most recent months.
E x h i b i t 1 Survey Results
HAND DELIVERED MAIL DELIVERED
Area 1 Area 2 Area 3 Area 4 Area 5
Total area population
35,000
50,000
69,000
85,000
155,000
City
24,000
45,700
52,000
43,000
100,000
Rural
11,000
4,300
17,000
42,000
55,000
Total sample
525
750
1,035
1,275
2,325
City
325
650
775
685
1,325
Rural
200
100
260
590
1,000
Overall percentage
88%
90%
95%
85%
92%
receiving directory
1This case was prepared by Paul D. Boughton, Ph.D., Associate Professor of Marketing, Saint Louis University, 3674 Lindell Blvd., St. Louis, MO 63108.
case 14 553
The total sample size for each area was determined by taking 1.5% of the area population. The breakdown between city and rural sample is arbitrary and the result of actual calls completed.
Combs wants to determine three things: (1) the over- all soundness of the sampling plan; (2) the amount of sampling error in the results; and (3) the amount of response error by respondents.
Questions
- What type of sample is being taken? Are city and ru- ral residents being represented adequately? What other approach would you recommend and why?
- What is the range of sampling error experienced from Area 1 to Area 5? (Assume 95% level of confi- dence.) How can Combs’s error goal of þ/- 2 per- centage points be achieved?
- What would you recommend as a sample size for each of the five areas?
- Does Combs have enough information to determine respondent error? What would you recommend he do to obtain this information?
554 case 14
case 15
Fancher Golf Center1
As a boy growing up in Harrisonburg, Virginia, Brian Fancher dreamed of being a professional golfer. His remarkable talent prompted his teammates to select him as captain of the high school golf team during both his junior and senior years, and he led the team to many tournament championships. This success did not go unnoticed by college coaches, and he was offered schol- arships by the University of Texas at Austin, UCLA, Stanford, and Pepperdine University. He initially planned to accept Stanford’s offer because the school has an impeccable academic reputation and is the alma mater of his idol Tiger Woods. However, when visiting Pepperdine’s mountain-side campus, with its breathtak- ing view of the Pacific Ocean, Brian knew he was des- tined to spend his college days in Malibu, California.
Brian’s freshman year at Pepperdine was unremark- able, but he emerged as the team’s star during his sopho- more year. During his last two seasons, he experienced enough success to begin believing his dream of a profes- sional career might actually come to fruition. After grad- uation, he pursued his goal by entering the PGA Qualifying Tournament (‘‘Q-school’’) but failed to qual- ify. Dejected, he returned home to Virginia and worked for a year as an assistant teaching professional at a local country club. The following year, his fortunes changed when he qualified at the PGA Q-school and received his PGA tour card. In his first season on the tour, he missed the cut at several tournaments but managed to earn enough money to keep his playing card. His financial sit- uation changed the next season when in the first tourna- ment he lost a sudden death playoff, came in second place, and earned $631,700. He had six more top-10 fin- ishes, earning him a total of $2,243,500, before tragedy struck. While playing the first round of a tournament, Brian’s club caught a tree root during his downswing, resulting in serious wrist and shoulder injuries. Surgeons were able to repair the damage but informed Brian that his professional playing days had come to an end.
Feeling confused by what had transpired, Brian returned home to seek solace and counsel from his fam- ily. Shortly thereafter, his mother experienced serious health problems; this made him decide to remain in his hometown. Despite his bitter disappointment, Brian still loved golf and wanted to earn his living by being involved in the game in some way. Several friends urged him to begin offering golf lessons, but his year at the country club made him realize he wanted more inde- pendence than that job offered. Based on discussions
1This case was prepared by Jon R. Austin, Ph.D., Associate Professor of Marketing, Cedarville University, 251 North Main Street, Cedarville, OH 45314.
with people in the community, he began to believe there might be an opportunity to invest what remained of his PGA Tour earnings to create a ‘‘Golf Center’’ in Harrisonburg. The concept was to have state-of-the-art indoor and outdoor training facilities. Initially, he would provide all of the golf instruction, but more instructors would be hired as finances permitted. The Fancher Golf Center would also offer high-end golf equipment along with custom club-fitting services. Brian felt confident he could create excitement and interest by periodically inviting friends from the PGA tour to come to the center for playing exhibitions, question-and-answer forums, and autograph sessions.
Harrisonburg, Virginia, is a quiet, unassuming com- munity of approximately 41,000 people located in the heart of the Shenandoah Valley. A central fixture in town is James Madison University (JMU), which enrolls over 16,000 students. There are a few smaller commun- ities in the immediate vicinity, but Brian and his associ- ates were hopeful the city of Staunton, because its population of roughly 24,000 has a similar demographic profile as Harrisonburg, might be a viable secondary market even though it is located 25 miles to the south. To obtain assistance in testing the viability of his busi- ness idea, Brian contacted the Shenandoah Valley Small Business Development Center which is housed at JMU. The center arranged for JMU students in a marketing research course to conduct some research on his behalf. Discussions between Brian, the marketing research professor, and students produced the following list of research problems:
Among the populations of (1) permanent Harrisonburg residents 18–70 years of age, (2) JMU stu- dents, and (3) Staunton residents 18–70 years of age:
- Determine the percentage of consumers who clas- sify themselves as serious golfers.
- Determine the frequency of playing golf during the spring (March through May), summer (June through August), and fall (September through November) seasons.
- Measure the level of satisfaction with current play- ing abilities.
- Measure the level of satisfaction with current
- golf instruction opportunities, (b) high-end golf equipment sources, and (c) club-fitting serv- ices in the area.
- Measure evaluations of the proposed golf center concept.
case 15 555
- Measure intentions to utilize (a) the golf instruc- tion services or (b) club-fitting services if the pro- posed golf center were opened.
The marketing research professor divided the class into three teams. Each team conducted a study that addressed all of the research objectives for one of the three target populations. Presented next are brief descriptions of how the teams collected the data for their studies.
Team 1
This team focused on the ‘‘permanent Harrisonburg res- idents 18–70 years of age’’ population. Using the inter- cept method, they administered a survey at Valley Mall. Of the 613 shoppers they approached, 227 were within the designated age range, and 143 of these shoppers agreed to complete the survey.
Team 2
This team conducted a study of the JMU student popu- lation. Because two members had extensive experience building Web pages, the group decided to take an inno- vative approach. They obtained the e-mail distribution lists for 12 campus organizations and sent an e-mail mes- sage to every fourth person on each list (a total of 2,219
messages) asking the person to visit the team’s Web site and complete an online survey. Using this approach, the team obtained 392 completed questionnaires.
Team 3
This team examined the ‘‘Staunton residents 18–70 years of age’’ population. Because Staunton is 25 miles away, the team decided to conduct telephone interviews. Moreover, the Small Business Development Center agreed to pay for the long-distance calls as long as they were made from the center’s telephone bank. The team members worked at the center during normal hours of operation (8:00 a.m. to 5:00 p.m.). Using systematic sampling, and the Staunton telephone directory as a sampling frame, they made 472 calls and obtained 96 completed surveys.
Questions
- For each team, identify all of the types of error that were likely introduced by the data collection pro- cess. Discuss why you believe particular procedures produced each type of error you identify.
- What could have been done to prevent/minimize each type of error by conducting the study differently?
- What might be done to deal with each type of error now that it has occurred?
556 case 15
case 16
Fabhus, Inc.
Fabhus, Inc., a manufacturer of prefabricated homes located in Atlanta, Georgia, had experienced steady, sometimes spectacular, growth since its founding in the early 1950s. In recent years, however, things have not been so rosy, with sales dropping about 20% from their high point three years earlier, in spite of a very attractive interest-rate environment for home building.
In an attempt to offset the decline in sales, company management decided to use marketing research to get a better perspective on their customers so that they could better target their marketing efforts. After much discus- sion, the members of the executive committee finally determined that the following questions would be important to address in this research effort:
- What is the demographic profile of the typical Fabhus customer?
- What initially attracts these customers to a Fabhus home?
- Do Fabhus home customers consider other factory- built homes when making their purchase decision?
- Are Fabhus customers satisfied with their homes? If they are not, what particular features are unsatisfactory?
Method
The research firm that was called in on the project sug- gested conducting a mail survey to past buyers. Preliminary discussions with management revealed that Fabhus had the greatest market penetration near its fac- tory. As one moved farther from the factory, the share of the total new housing business that went to Fabhus declined. The company suspected that this might result from the higher prices of the units due to shipping charges. Fabhus relied on a zone-price system in which prices were based on the product delivered at the con- struction site.
Local dealers actually supervised construction. Each dealer had pricing latitude and could charge more or less
than Fabhus’s suggested list price. Individual dealers were responsible for seeing that customers were satisfied with their Fabhus home, although Fabhus also had a toll-free number that customers could call if they were not satisfied with the way their dealer handled the con- struction or if they had problems moving in.
Considering the potential impact distance and dealers might have, the research team thought it was important to sample purchasers in the various zones as well as cus- tomers of the various dealers. Since Fabhus’s records of houses sold were kept by zone and by date sold within zone, sample respondents were selected in the following way: First, the registration cards per zone were counted. Second, the sample size per zone was determined so that the number of respondents per zone was proportionate to the number of homes sold in the zones. Third, a sam- ple interval, k, was chosen for each zone, a random start between 1 and k was generated, and every kth record was selected. The mail questionnaire shown in Exhibit 1 was sent to the 423 households selected.
A cover letter informing Fabhus’s customers of the general purpose of the survey accompanied the question- naire, and a new $1 bill was included with each survey as an incentive to respond. Furthermore, the anonymity of the respondents was guaranteed by enclosing a self-addressed postage-paid postcard in the survey. Respondents were asked to mail the postcard when they mailed their survey. All those who had not returned their postcards in two weeks were sent a notice reminding them that their survey had not been returned. The combination of incentives, guaranteed anonymity, and follow-up prompted the return of 342 questionnaires for an overall response rate of 81%.
Questions
- Using the data in the file ‘‘FABHUS’’ and analytic techniques of your own choosing, address as best you can the objectives that prompted the research effort in the first place.
- Do you think the research design was adequate for the problems posed? Why or why not?
case 16 557
E x h i b i t 1 Factory-Built Home Owners Survey
- How did you first learn of the factory-built home that you bought? (check one, please) Friend or relative Direct mail
Another customer Newspaper
Realtor Radio
Model home TV
Yellow pages Don’t remember
National magazine Other
(please specify)
- Did you own the land your home is on before you first visited your home builder? Yes No
- How long have you lived in your home? years
- Where did you live before purchasing your factory-built home? (please check one) Rented a house, apartment, or mobile home
Owned a mobile home
Owned a conventionally built home Owned another factory-built home
Other
(please specify)
- Please rate your overall level of satisfaction with your home. (please check one) Very satisfied
Somewhat satisfied Somewhat dissatisfied Very dissatisfied
- How important to you were each of the following considerations in purchasing your factory-built home? (please check one space for each item)
Extremely Slightly Not
Considerations Important Important Important Important
Investment value Quality
Price
Energy features Dealer
Exterior style Floor plan Interior features
Delivery schedule
- Below, please list any other homes you looked at before purchasing the home you chose. Please state the reason you did not purchase the other home.
Name of Home Factory-Built? Reason for Not Purchasing
Yes
No
Yes
No
Yes
No
Yes
No
Now we would like you to please tell us about yourself and your family.
- How many children do you have living at home? children
- What is the age of the head of your household? (check one, please) Under 20 35–44 55–64
20–24 45–54 65 or over
25–34
558 case 16
E x h i b i t 1 Factory-Built Home Owners Survey (Continued)
- What is the occupation of the head of the household? (check one, please) Professional or official Labor or machine operator
Technical or manager Foreman
Proprietor Service worker
Farmer Retired
Craftsperson Other
Clerical or sales
(please specify)
- Which of the following categories includes your family’s total annual income? (check one, please)
Less than $20,000
$50,000-$59,999
$20,000-$29,999
$60,000-$69,999
$30,000-$39,999
$70,000-$79,999
$40,000-$49,999
$80,000 or over
- Is the spouse of the head of the household employed? (check one, please) Spouse employed full-time Spouse not employed
Spouse employed part-time Not married One final question:
- Would you recommend your particular factory-built home to someone interested in building a new home? Yes No
Thank you very much for completing this survey . Y our help in this study is greatly appreciated.
case 16 559
case 17
Marty’s Department Store
Bethany Tate was nervous. As the general manager of the local Marty’s, a regional department store chain based in the southwest United States, she was apprehensive about lackluster sales growth at her store over the most recent quarter. The problem, she believed, was the nearby pres- ence of Naples Clothing Co., a nationally known spe- cialty retailer of clothing that had opened about six months ago. She had expected sales to be flat while the new Naples store went through its honeymoon period with shoppers, but she didn’t expect it to last this long.
Marty’s Department Store
The Marty’s chain was founded in 1967 in Scottsdale, Arizona. The company currently operates 113 stores across a dozen southwestern states. In general, the com- pany’s strategy is to locate stores in strip malls in small to medium-sized cities in an attempt to avoid direct competition with larger retailers in regional shopping centers. Compared with similarly sized regional depart- ment store chains, Marty’s typically performs rather poorly, with lower than average revenue growth and much higher than average cost structure.
The local store had been a bright spot for the com- pany. Located in a small university city (population 43,000, including 15,000 students), the store had enjoyed steady sales growth since its opening four years earlier. The store offers most types of goods usually found in department stores, with the bulk of sales revenues com- ing from clothing. The store prides itself on offering the most complete range of clothing for the whole family available locally. Like all Marty’s stores, the local store sells several national brands as well as its own private label brand. The store normally runs at least one price promotion per month in an attempt to emphasize its attractive prices. Until recently, the store’s primary local competitors included a nationally known department store, a locally owned department store, and several small specialty clothing stores.
Bethany Tate had managed the store for the past two years. She had been a management trainee with the com- pany for only two months when the local store’s original manager left the company to work for a competitor. Although company policy is for all general managers to have been with the company at least a year before being placed in their own stores, the district manager liked Bethany a lot and believed she had the qualities neces- sary to be successful in the retailing industry. Although she was young and relatively inexperienced (this was her first job after graduating from college with a marketing degree), she was bright, worked very hard, and people
seemed to enjoy working with her, even employees twice her age. For the first 18 months, everything had gone smoothly, despite Bethany’s unspoken fears of getting in over her head. Things began to change when Naples came to town.
Naples Clothing Co.
The Naples Clothing Co. chain has been in existence barely 10 years, yet routinely outperforms virtually all other specialty clothing chains. The company sells only its own brand of casual clothes, which it manufactures in various locations around the world. The clothing line is extremely popular at the present time; the Naples Clothing Co. name and logo appear on millions of articles of clothing in current use. In many cases, wearers become walking advertisements for the company. The company emphasizes reasonable everyday prices, with occasional price promotions, particularly on overstocked or out-of-season merchandise.
Initially, the company’s strategy was to locate in newer strip malls in cities of 400,000 and above. The company often opened two to four stores (or more) in these cities. With increasing success, however, the com- pany has begun to locate in selected smaller commun- ities. The stores are uniform in design, appearance, and merchandise selection (with some small regional differ- ences). The stores feature an open, no-frills layout, which helps keep costs low. There are currently 524 Naples Clothing Co. outlets in the United States, with the company opening about 80 new stores per year.
Marketing Research
Bethany Tate was convinced that her revenues were suf- fering due to the popularity of Naples Clothing Co., par- ticularly among college students. Worse, she realized that she had no real idea what college students thought about her store. Recognizing the need for more information, she convinced her district manager to allow her to hire a local research company to determine consumer perceptions of both Marty’s Department Store and Naples Clothing Co. among younger consumers. The company was interested in the results, because they expected to be competing with Naples Clothing Co. in more and more markets.
The research company and Bethany agreed to focus on three key areas in their research with young consum- ers: (1) identifying the attributes of retail stores deemed most important, (2) determining perceptions of Marty’s, and (3) determining perceptions of Naples Clothing Co. for comparison purposes. After some preliminary
560 case 17
exploratory research, the research company developed a one-page (front and back) survey to be administered to local residents between the ages of 18 and 25 (Exhibit 1; the codebook is presented in Exhibit 2). An area sample was used, and surveys were dropped off at each residence within randomly selected clusters. A total of 208 usable questionnaires were received from eligible respondents.
Questions
- Did this research result from planned or unplanned change? Is the research discovery or strategy ori- ented? Explain.
- Suppose that the mean score for ‘‘good service’’ is
4.1 on the five-point ‘‘definitely no-definitely yes’’ scale (see survey). What can you conclude from this
information? How might this score be given more meaning? Explain.
- How important are the various attributes of retail stores to young consumers in this market? Present your answer using (a) mean scores and standard deviations and (b) two-boxes. Technically speaking, can Bethany conclude that service is more impor- tant than atmosphere to these consumers?
- In terms of service quality and employee helpful- ness, do perceptions of Marty’s Department Store differ for those who have visited the store versus those who have not? What would your results mean to Bethany Tate, if anything?
- Overall, how does Marty’s Department Store com- pare with Naples Clothing Co. on key attributes? Are any differences statistically significant? If so, what do they mean?
E x h i b i t 1 Marty’s Questionnaire
PA RT I
Not Important
V er y Important
Service
1
2
3
4
5
Merchandise quality
1
2
3
4
5
Merchandise variety
1
2
3
4
5
Price
1
2
3
4
5
Atmosphere
1
2
3
4
5
Convenience
1
2
3
4
5
Value of brand name
1
2
3
4
5
Merchandise style
1
2
3
4
5
- Please rate how important each of the following items are to you for retail stores on a scale of 1 to 5, where “1” is “not important” and “5” is “very important”:
De fi nitely YES
2
3
4
5
2
3
4
5
2
3
4
5
2
3
4
5
2
3
4
5
2
3
4
5
2
3
4
5
2
3
4
5
2
3
4
5
2
3
4
5
2
3
4
5
2
3
4
5
Yes
No
- Please rate Naples Clothing Co. on each of the following characteristics on a scale of 1 to 5, where “1” is “definitely NO” and “5” is “definitely YES”:
De fi nitely NO
Good service 1
Good quality 1
Good variety 1
Low price 1
Appealing atmosphere 1
Convenient location 1
Brand name is appealing 1
Stylish products 1
Good value 1
Good reputation 1
Fun to shop 1
Helpful employees 1
Have you visited the local Naples Clothing Co.?
(Continued)
case 17 561
E x h i b i t 1 Marty’s Questionnaire (Continued)
- Please rate Marty’s Department Store on each of the following characteristics on a scale of 1 to 5, “1” being “definitely NO” and “5” being “definitely YES.”
Good service Good quality Good variety Low price
De fi nitely NO
De fi nitely YES
2
3
4
5
2
3
4
5
2
3
4
5
2
3
4
5
2
3
4
5
2
3
4
5
2
3
4
5
2
3
4
5
2
3
4
5
2
3
4
5
2
3
4
5
2
3
4
5
Yes
No
1
1
1
1
Appealing atmosphere 1
Convenient location 1
Brand name is appealing 1
Stylish products 1
Good value 1
Good reputation 1
Fun to shop 1
Helpful employees 1
Have you visited the local Marty’s Department Store?
P AR T II
- What do you perceive as the average age of a typical person who shops at the local Naples Clothing Co.?
years old
- What do you perceive as the average age of a typical person who shops at the local Marty’s Department Store?
years old
- Approximately how many times in the past month have you shopped at the following:
- local Marty’s Department Store
times
- local Naples Clothing Co.
times
- Approximately how many times in the past month have you seen an advertisement for Naples Clothing Co. on the following forms of media?
Television: times
Print (newspaper and magazine): times Radio: times
- Approximately how many times in the past month have you seen an advertisement for Marty’s Department Store on the following forms of media?
Television: times
Print (newspaper and magazine): times Radio: times
- Approximately how much money do you spend on clothing each month?
$
Thank you for your time.
562 case 17
E x h i b i t 2 Marty’s Codebook
Columns Variable Name/Description
1–4
5
GEN
ID
Gender
SURVEY ID#
1 = male 2 = female
6
IMP1
Retail Store Attribute Importance - item 1
1–5; Not Important, Very Important
7
IMP2
Retail Store Attribute Importance - item 2
1–5; Not Important, Very Important
8
IMP3
Retail Store Attribute Importance - item 3
1–5; Not Important, Very Important
9
IMP4
Retail Store Attribute Importance - item 4
1–5; Not Important, Very Important
10
IMP5
Retail Store Attribute Importance - item 5
1–5; Not Important, Very Important
11
IMP6
Retail Store Attribute Importance - item 6
1–5; Not Important, Very Important
12
IMP7
Retail Store Attribute Importance - item 7
1–5; Not Important, Very Important
13
IMP8
Retail Store Attribute Importance - item 8
1–5; Not Important, Very Important
14
NAPLES1
Perceptions of Naples Clothing Co., item 1
1–5; Definitely NO, Definitely YES
15
NAPLES2
Perceptions of Naples Clothing Co., item 2
1–5; Definitely NO, Definitely YES
16
NAPLES3
Perceptions of Naples Clothing Co., item 3
1–5; Definitely NO, Definitely YES
17
NAPLES4
Perceptions of Naples Clothing Co., item 4
1–5; Definitely NO, Definitely YES
18
NAPLES5
Perceptions of Naples Clothing Co., item 5
1–5; Definitely NO, Definitely YES
19
NAPLES6
Perceptions of Naples Clothing Co., item 6
1–5; Definitely NO, Definitely YES
20
NAPLES7
Perceptions of Naples Clothing Co., item 7
1–5; Definitely NO, Definitely YES
21
NAPLES8
Perceptions of Naples Clothing Co., item 8
1–5; Definitely NO, Definitely YES
22
NAPLES9
Perceptions of Naples Clothing Co., item 9
1–5; Definitely NO, Definitely YES
23
NAPLES10
Perceptions of Naples Clothing Co., item 10
1–5; Definitely NO, Definitely YES
24
NAPLES11
Perceptions of Naples Clothing Co., item 11
1–5; Definitely NO, Definitely YES
25
NAPLES12
Perceptions of Naples Clothing Co., item 12
1–5; Definitely NO, Definitely YES
26
VISNAT
Visited Naples Clothing Co.?
1 = yes, 2 = no
27
MARTYS1
Perceptions of Marty’s Department Store, item 1
1–5; Definitely NO, Definitely YES
28
MARTYS2
Perceptions of Marty’s Department Store, item 2
1–5; Definitely NO, Definitely YES
29
MARTYS3
Perceptions of Marty’s Department Store, item 3
1–5; Definitely NO, Definitely YES
30
MARTYS4
Perceptions of Marty’s Department Store, item 4
1–5; Definitely NO, Definitely YES
31
MARTYS5
Perceptions of Marty’s Department Store, item 5
1–5; Definitely NO, Definitely YES
32
MARTYS6
Perceptions of Marty’s Department Store, item 6
1–5; Definitely NO, Definitely YES
33
MARTYS7
Perceptions of Marty’s Department Store, item 7
1–5; Definitely NO, Definitely YES
34
MARTYS8
Perceptions of Marty’s Department Store, item 8
1–5; Definitely NO, Definitely YES
35
MARTYS9
Perceptions of Marty’s Department Store item 9
1–5; Definitely NO, Definitely YES
36
MARTYS10
Perceptions of Marty’s Department Store, item 10
1–5; Definitely NO, Definitely YES
37
MARTYS11
Perceptions of Marty’s Department Store, item 11
1–5; Definitely NO, Definitely YES
38
MARTYS12
Perceptions of Marty’s Department Store, item 12
1–5; Definitely NO, Definitely YES
39
40–41
42–43
44–45
46–47
48–49
50–51
52–53
54–55
56–57
58–59
60–62
VISMARTY AGENAP AGEMART SHOPMART SHOPNAP NAPTV NAPPRINT NAPRADIO MARTV MARPRINT MARRADIO MONEY
Visited Marty’s Department Store?
Naples average perceived age of customers Marty’s average perceived age of customers Marty’s times shopped in last month
Naples times shopped in last month
Number of Naples advertisements seen on TV last month Number of Naples advertisements seen in print last month Number of Naples advertisements heard on radio last month Number of Marty’s advertisements seen on TV last month Number of Marty’s advertisements seen in print last month Number of Marty’s advertisements heard on radio last month Average money spent on clothing each month
1 = yes, 2 = no
Missing Data: Blank
case 17 563
Text not available due to copyright restrictions
564
Text not available due to copyright restrictions
565
Text not available due to copyright restrictions
566
APPENDIX
Text not available due to copyright restrictions
Appendix 567
Text not available due to copyright restrictions
568 Appendix
Text not available due to copyright restrictions
Appendix 569
Text not available due to copyright restrictions
570 Appendix
Text not available due to copyright restrictions
Appendix 571
Text not available due to copyright restrictions
572 Appendix
Text not available due to copyright restrictions
Appendix 573
ENDNOTES
CHAPTER 1
- For more information about the re- lationship between market orienta- tion and business performance, see Ahmet H. Kirca, Satish Jayachan- dran, and William O. Bearden, ‘‘Market Orientation: A Meta- Analytic Review and Assessment of Its Antecedents and Impact on Performance,’’ Journal of Marketing, April 2005, pp. 24–41.
- For more information on these examples, see Bruce Horovitz, ‘‘Marketers Take a Close Look at Your Daily Routines,’’ USA Today (April 30, 2007); Jack Neff, ‘‘P&G Kisses Up to the Boss: Consum- ers,’’ Ad v ertising Age (May 2, 2005), downloaded via ProQuest, July 25, 2008; Patricia Sellers, ‘‘Birth of a Rib Joint,’’ Fortune (April 29, 2002), Matthew Swibel, ‘‘Where Money Doesn’t Talk,’’ Forbes (May 24, 2004), Judy Schoenburg, Kim- berlee Salmond, Paula Fleshman, ‘‘Change It Up! What Girls Say About Redefining Leadership,’’ GirlScouts.org; Brian O’Keefe, ‘‘Meet Your New Neighborhood Grocer,’’ Fortune (May 13, 2002).
- Downloaded from the American Marketing Association Web site, http://www.marketingpower.com, July 24, 2008.
- Downloaded from the McDonald’s
U.K. Corporate Web site, http:// www.mcdonalds.co.uk/?f¼y, July 24, 2008; ‘‘How McDonald’s Conquered the UK,’’ Marketing, downloaded from http://www.brandrepublic
.com/, July 24, 2008.
- Lawrence C. Lockley, ‘‘History and Development of Marketing Research,’’ Section 1, p. 4, in Rob- ert Ferber, ed., Hand book of Market- i n g R e s earc h , Copyright VC 1974 by McGraw-Hill, 1974. Used with permission of McGraw-Hill Book Company.
- ‘‘Keio University and Dentsu An- nounce the Commencement of Sec- ond Life Joint Research’’ (July 31, 2007), http:/ /www.keio.ac.jp/.
- Downloaded from the McCann- Erickson WorldGroup Web site,
http://www.mccann.com, July 2,
2002.
- Jack Honomichl, ‘‘Strong Prog- ress,’’ Marketing N ews, August 2008, p. H3.
- Jack Honomichl, ‘‘Acquisitions Up, Growth Rate Varies,’’ Marketing Ne ws, August 2008, p. H3.
- ‘‘Economists and Market and Sur- vey Researchers,’’ O ccu pati on al Out- look Handbook, 2002–2003 edition (Washington, D.C.: Bureau of Labor Statistics), pp. 239–241, down- loaded from ht tp://www.bls.gov/ oco/pdf/ocos013.pdf, July 29, 2008.
CHAPTER 2
- Robert J. Williams, ‘‘Marketing Intelligence Systems: A DEW Line for Marketing Men,’’ Business Man- agement, January 1966, p. 32.
- Peter D. Bennett, ed., Dictionary of Marketing Terms, 2nd ed. (Chicago: American Marketing Association, 1995), p. 167. American Marketing Association, downloaded from www.marketingpower.com, August 2, 2008.
3. Ibid., p. 77.
- Eldon Y. Li, Raymond McLeod, Jr., and John C. Rogers, ‘‘Market- ing Information Systems in Fortune
500 Companies: A Longitudinal Analysis of 1980, 1990, and 2000,’’ Information & Management 38, 2001, pp. 307–322.
- Evan Schuman, ‘‘At Wal-Mart, World’s Largest Retail Data Ware- house Gets Even Larger,’’ October 13, 2004, downloaded from http:// www.eweek.com, August 2, 2008; downloaded from http://walmartst ores/FactsNews/, August 2, 2008; Jeremy Kahn, ‘‘Wal-Mart Goes Shopping in Europe,’’ For tune, June 7, 1999, pp. 105–106.
- ‘‘Protecting Customers’ Personal Information: The Safeguards Rule,’’ downloaded from http://www.ftc
.gov/bcp/edu/microsites/idtheft/bus iness/safeguards.html, July 31,
2008.
- James Studnicki, Frank V. Murphy, Donna Malvey, Robert A. Costello, Stephen L. Luther, and Dennis
C. Werner, ‘‘Toward a Population Health Delivery System: First Steps in Performance Measurement,’’ Health Care Mana gement Review, Winter 2002, pp. 76–95.
- For more information, see Berend Wierenga and Gerrit H. Van Brug- gen, ‘‘Developing a Customized Decision-Support System for Brand Managers,’’ Interfaces, May–June 2001, pp. S128–S145; S. Kanungo,
S. Sharma, and P. K. Jain, ‘‘Evalua- tion of a Decision Support System for Credit Management Decisions,’’ Decision Support Systems 30, 2001, pp. 419–436; R. Jeffrey Thieme, Michael Song, and Roger J. Calan- tone, ‘‘Artificial Neural Network Decision Support Systems for New Product Development Project Selection,’’ Journal of Marketi ng Rese arch, November 2000, pp. 499– 507; and Jehoshua Eliashberg, Jedid-Jah Jonker, Mohanbir S. Sawhney, and Berend Wierenga, ‘‘MOVIEMOD: An Implementable Decision-Support System for Pre- release Market Evaluation of Mo- tion Pictures,’’ Marketing Science, Summer 2000, pp. 226–243.
- For a general discussion of the his- tory of expert systems, see David Brown, ‘‘‘Intelligent’ Systems?’’ In- formation World Review, November 2001, downloaded via ProQuest Direct, August 2, 2008.
Next Gener ation of Data-Mining Applications, ed. Mehmed M. Kant- ardzic and Jozef Zurada (Hoboken, N.J.: 2005 John Wiley & Sons, Inc.), p. 1.
574 Endnotes
Endnotes 575
Company),’’ CI O Magazine, December 1, 2003, downloaded from the CIO Web site, http:// www.cio.com, July 31, 2008.
- Megan Santosus ‘‘Underwriting Knowledge,’’ June 12, 2007, down- loaded from www.cio.com, August 2, 2008.
- Paul, ‘‘Why Three Heads Are Bet- ter Than One.’’
CHAPTER 3
1. Much of the discussion in this sec- tion is based on Anne T. Lawrence and James Weber, Bu sine ss an d S o c i- ety: Stake holders, Ethi cs, Public Policy, 12th ed. (New York: McGraw-Hill Irwin, 2008), pp. 103–107.
CHAPTER 4
1. Frederick Allen, Secret Formula (New York: HarperColling Publish- ers, Inc., 1994).
2. Ibid. p. 401.
- Jeff Ousborne, ‘‘The 25 Dumbest Business Decisions of All Time,’’ MBA J ungle 1, May 2001, pp. 64–70.
- Alex Taylor III, ‘‘Survival on Dealer’s Row,’’ Fortune, March 31, 2008, p. 24.
- Kevin J. Clancy and Peter C. Krieg, ‘‘Surviving Death Wish Research,’’ Marketi ng Research: A Magazi ne of Management & Applications 13, Win- ter 2001, p. 9.
- William I. Zangwill, ‘‘When Cus- tomer Research Is a Lousy Idea,’’ The Wall Street J ournal, March 8, 1993, p. A12. See also Justin Martin, ‘‘Ignore Your Customer,’’ Fortune, May 1, 1995, pp. 121–126.
CHAPTER 5
- Claire Selltiz, Lawrence S. Wrights- man, and Stuart W. Cook, Research M ethods in Social Relations, 3rd ed. (New York: Holt, Rinehart and Winston, 1976), pp. 90–91. See also Fred N. Kerlinger, Foundations of Behavioral Research, 4th ed. (New York: Holt, Rinehart and Winston, 1999). David A. deVaus, Research De sign in Social Research (Thousand Oaks, Calif: Sage Publications, 2000).
- Steven P. Galante, ‘‘More Firms Quiz Customers for Clues About Competition,’’ The Wall Stre et Journal, March 3, 1986, p. 17. See also Thomas L’egare, ‘‘Acting on Customer Feedback,’’ Marketing Research: A Magazi ne of Ma nage me nt
& Applications 8, Spring 1996, pp.
46–51.
- Bob Deierlein, ‘‘A New Louisville Slugger,’’ Beverage World 114, June 1995, pp. 116–117.
- Noah Schachtman, ‘‘Web En- hances Market Research,’’ Advertis- ing Age, June 18, 2001, downloaded via Proquest, August 10, 2008.
- Tom Greenbaum, ‘‘The Case Against Internet Focus Groups,’’ MRA Ale rt Newslette r, April 2002, downloaded from http://www.groups plus.com, August 10, 2008.
- Daniel Gross, ‘‘Lies, Damn Lies, and Focus Groups,’’ Slate, posted October 10, 2003, downloaded from http://slate.msn.com, August 10, 2008.
- This quotation is credited to Dev Patnaik. See Philip Hodgson, ‘‘Focus Groups: Is Consumer Re- search Losing Its Focus?’’ User focus, June 1, 2004, downloaded from http://www.userfocus.co.uk, August 10, 2008.
- Ko de Ruyter, ‘‘Focus versus Nom- inal Group Interviews: A Compara- tive Analysis,’’ Marketing Intelligence and Planning, Vol. 14, No. 6, Janu- ary 1996, pp. 44–50; downloaded via www.proquest.com, August 1, 2008.
- ‘‘Online Extra: Targeting the Uni- versal American Kid,’’ BusinessWeek on line, June 7, 2004, downloaded from http://www.businessweek.com, August 10, 2008.
- Robert K. Yin, Case St udy Researc h: Design and Meth ods (Thousand Oaks, Calif.: Sage Publications, 1994); Robert E. Stake, The Art of C ase Study Research (Thousand Oaks, Calif.: Sage Publications, 1993).
- Jennifer Chang Coupland, ‘‘Invisi- ble Brands: An Ethnography of Households and the Brands in Their Kitchen Pantries,’’ Journal of Consumer Research, June 2005, pp. 106–118, downloaded using the Business Source Elite database, August 10, 2008.
- Kathleen Kerwin, ‘‘How to Market a Groundbreaking SUV,’’ Business- Week online, October 18, 2004, downloaded from http://www.busin essweek.com, August 10, 2008.
- Teresa Fagulha, ‘‘The Once- Upon-A Time Test’’, in Richard Henry Dana, ed., Han dbo ok of Cross-Cultural and Mult icul tural
Personality Assessment (Mahwah, N.J.: Lawrence Earlbaum Associates, 2000), pp. 515–536; Sidney J. Levy, ‘‘Interpreting Consumer Methodol- ogy: Structural Approach to Con- sumer Behavior Focuses on Story Telling,’’ Marke ting Mana gement 2, 1994, pp. 4–14.
CHAPTER 6
- Charles M. Brooks, Patrick J. Kauf- mann, and Donald R. Lichtenstein, ‘‘Trip Chaining Behavior in Multi- Destination Shopping Trips: A Field Experiment and Laboratory Repli- cation,’’ J o urnal of R etai ling 84, No. 1, 2008, pp. 29–38.
- ‘‘Test and Learn,’’ Marke ting Man- agement, May/June 2002, p. 22.
- ‘‘McDonalds Rolls out Coffee Bar Buildout Concept at Select Restau- rants in Southwest,’’ Financial Wire, July 9, 2008, downloaded via Pro- Quest (www.proquest.com), July 11, 2008; Dana Flavelle, ‘‘Competitor Brouhaha Brewing, Starbucks Tests Buck-a-Cup Java,’’ Toronto Star, January 24, 2008, downloaded via EBSCO Host (www.ebscohost
.com), July 11, 2008.
- Robert Walker, ‘‘Working with Marketing Research: A Message to Marketers,’’ Quirk’s, October 2001, downloaded from www.quirks.com, July 11, 2008; ‘‘Test Marketing: What’s in Store,’’ Sal es and Market- ing Mana gement 128, March 15, 1982, pp. 57–85. See also Richard Gibson, ‘‘Pinning Down Costs of Product Introductions,’’ Th e Wa ll Street Journal, November 26, 1990,
p. B1.
- Gabriele Stern, ‘‘GM Expands Its Experiment to Improve Cadillac’s Distribution, Cut Inefficiency,’’ The Wa ll S t ree t J ourn a l, February 8, 1995, p. A12.
- Annetta Miller and Karen Springen, ‘‘Egg Rolls for Peoria,’’ Ne wswe ek, October 12, 1992, pp. 59–60.
- Vanessa O’Connell, ‘‘Altria Drops New Filter Cigarettes in Strategic Setback,’’ The Wall Street Journa l, June 23, 2008, downloaded via ProQuest (www.proquest.com), July 11, 2008.
- Natalie Zmuda and Emily Bryson York, ‘‘McD’s Tries to Slake Con- sumer Thirst for Wider Choice of Drinks,’’ Ad v ertising Age, June 9, 2008, downloaded via EbscoHost
576 Endnotes
(www.ebscohost.com), July 11, 2008; ‘‘Rite Aid Caters to Spanish- Language Customers,’’ DSN Retailing Today, March 28, 2005, downloaded via ProQuest, June 23, 2005; Ellen Florian, ‘‘100 Fastest- Growing Companies,’’ Fortune, September 6, 2004, downloaded from http://www.fortune.com, June 23, 2005.
- Don A. Wright, ‘‘The Perfect Place for a Test Market,’’ The Business Journal, May 21, 2001, p. 12.
- ‘‘GfK Group: Annual Report 2006,’’ downloaded from http:// www.gfk.com/imperia/md/content/ gb_2006/gfk_ar_2006_complete.pdf, July 2, 2008.
- Peter S. Fader, Bruce G. S. Hardie, Robert Stevens, and Jim Findley, ‘‘Forecasting New Product Sales in a Controlled Test Market Environ- ment,’’ downloaded from the Whar- ton College of Business’s Marketing Web site, http://www.marketing. wharton.upenn.edu, June 23, 2005. See also the 10-K SEC filing by In- formation Resources, Inc., March 27, 2003, downloaded from http://sec
.edgar-online.com, July 2, 2008.
- ‘‘BASES Validations,’’ August 2002, downloaded from www.bases.com, July 24, 2008.
- Julie S. Wherry ‘‘Simulated Test Marketing: Its Evolution and Cur- rent State in the Industry,’’ June 2006, MBA Thesis, MIT Sloan School of Management, down- loaded from http://dspace.mit.edu/ bitstream/1721.1/37225/1/85813336. pdf, July 23, 2008.; Jim Miller and Sheila Lundy, ‘‘Test Marketing Plugs into the Internet,’’ Consumer Insight, Spring 2002, pp. 20–23.
CHAPTER 7
- Phaedra Hise, ‘‘Grandma Got Run Over by Bad Research,’’ Inc., January 1998, downloaded September 13, 2008.
- ‘‘You May Not Care but ‘Nappie’ La- joie Batted .422 in 1901,’’ The Wal l Stree t Journa l, September 13, 1974, p. 1.
- David Goetzl, ‘‘Second Magazine Study Touts Value of DTC Drug Ads,’’ Advertising Age, June 28, 1999, p. 22.
- Wally Wood, ‘‘Targeting: It’s in the Cards,’’ Mark eting & Media Decisions, September 1988, pp. 121– 122.
- The figure and surrounding discus- sion are adapted from David W. Stewart and Michael A. Kamins, Se c- ondary Research: Information Sources an d M ethods, 2nd ed. (Thousand Oaks, Calif.: Sage Publications, 1993).
- Enid Burns, ‘‘Top 10 U.S. Search Providers, September 2007,’’ Octo- ber 26, 2007, downloaded from searchenginewatch.com, September 13, 2008.
CHAPTER 8
- ‘‘GIS for Business: Chase Manhat- tan Bank,’’ downloaded from http:// www.gis.com, June 24, 2002.
- Downloaded from the NPD Food- world Web site, http://npdfood world.com, July 5, 2005.
- Downloaded from the NPD Group Web site, http://www.npd.com, October 6, 2008.
- See ‘‘Convenience Store Measure- ment at the Local Level,’’ down- loaded from the Nielsen Web site, http://us.nielsen.com, October 6, 2008.
- In 2005, North American compa- nies were to begin implementing systems that would allow compati- bility with the 13-digit EAN sym- bols used throughout the rest of the world. For more information, see http://www.officialeancode.com/faq
.html, downloaded December 20, 2008.
- ‘‘BSkyB Hangs Marketing Hat on Interactive Ads,’’ Satellite News, November 1, 2004, p. 1, downloaded via ProQuest, October 6, 2008.
- ‘‘Intended User Survey,’’ down- loaded from the Nielsen Web site, http://us.nielsen.com, December 20, 2008; Ken Greenberg, ‘‘Using Pan- els to Understand the Consumer,’’ Consumer Insight, Spring 2002, pp. 16–18, 28, downloaded from the Nielsen Web site, http://www
.acneilsen.com, June 12, 2002; Niel- sen H ousehold Panel (Northbrook, Ill.:
A. C. Nielsen Company, undated).
- Information downloaded from the Arbitron Web site, http://www.arb itron.com, October 6, 2008.
- Information downloaded from the NOP World Web site, http:// www.nopworld.com, July 8, 2005. See also Starch Readership Report: Scope, Method, and U se (Mamaro- neck, N.Y.: Starch INRA Hooper, undated).
- Information downloaded in part from the Experian Simmons Web site, http://www.smrb.com, Octo- ber 6, 2008.
- ‘‘About MRI,’’ downloaded from the company’s Web site, http:// www.mediamark.com, December 20, 2008.
CHAPTER 9
- ‘‘Frito-Lay Profiles Salty Snack Con- sumers,’’ Supermarke t N ews, March 18, 1996, p. 39.
- For a general discussion of the role of attitude in consumer behavior, see
J. Paul Peter and Jerry C. Olson, Cons umer Behavior & Marketing Stra tegy, 7th ed. (Burr Ridge, Ill.: Irwin/McGraw-Hill, 2004).
- Tonita Perea Monsuwe, Benedict G.
C. Dellaert, and Ko de Ruyter, ‘‘What Drives Consumers to Shop Online? A Literature Review,’’ Inter- nati onal Journal of Service Industry Manag ement, Issue 1, 2004, down- loaded via ProQuest, October 8, 2008.
- Albert C. Bemmaor, ‘‘Predicting Behavior from Intention-to-Buy Measures: The Parametric Case,’’ J ournal o f Marketing Research 32, May 1995, pp. 176–191; William J. Infosino, ‘‘Forecasting New Product Sales from Likelihood of Purchase Ratings,’’ Market ing S cience 5, Fall 1986, p. 375.
CHAPTER 10
- Justus J. Randolph, Marjo Virnes, Ilkka Jormanainen, and Pasi J. Ero- nen, ‘‘The Effects of a Computer- Assisted Interview Tool on Data Quality,’’ Educational Tech nology & Society, Vol. 9, No. 3, 2006, pp. 195– 205.
- David H. Wilson, Gary J. Starr, Anne W. Taylor, and Eleonora Dal Grande, ‘‘Random Digit Dialing and Electronic White Pages Samples Compared,’’ Australian and New Zea- land Journal of Public Health 23, December 1999, pp. 627–633.
- Michael W. Link and Robert W. Oldendick, ‘‘Call Screening: Is It Really a Problem for Survey Re- search?’’ Public Opinion Quarte rly 63, Winter 1999, pp. 577–589.
- Rob Farbman, ‘‘Edison Media Research: Has the Do Not Call Registry Turned out to Be a Survey Researcher’s Best Friend?’’ July 1,
Endnotes 577
2005, downloaded from the Edison Media Research Web site, http:// www.edisonresearch.com, October 28, 2008.
CHAPTER 11
- Paco Underhill, Wh y We Bu y: Th e Sc ie nce of Sh opping (New York: Touchstone, 2000), p. 18.
- Bob Becker, ‘‘Take Direct Route When Data-Gathering,’’ Marketing News 33, September 27, 1999, pp. 29 and 31.
- Jeffrey Kluger, ‘‘Oh, Rubbish— A Study of Garbage in Tucson, Arizona Is Used to Collect Dental Hygiene Statistics,’’ Di scov er, August 1994, downloaded from BNET Web site at http://findarticles.com, December 20, 2008.
- Tony Case, ‘‘Getting Personal,’’ Brandweek 41, March 6, 2000, pp. M52–M54.
- Krispy Kreme example (dated December 2002), downloaded from the Williams Inference Center Web site, http://www.williamsinference
.com, July 21, 2005; Barbara Whi- taker, ‘‘Yes, There Is a Job That Pays You to Shop,’’ The New York Time s, March 13, 2005, downloaded
via ProQuest, November 17, 2008.
- ‘‘Undercover Shoppers Find It Increasingly Difficult for Children to Buy M-Rated Games,’’ May 8, 2008, downloaded from ht tp://www.ftc.gov/ opa/2008/05/secretshop.shtm, August 20, 2008.
- Information downloaded from the VirTra Systems Web site, http:// www.virtrasystems.com, July 25, 2005; Betsy Stewart, ‘‘Multimedia Market Research,’’ Marketing Re- search 11, Fall 1999, pp. 14–18; Glen
L. Urban et al., ‘‘Information Accel- eration: Validation and Lessons from the Field,’’ Journal of Marketing Research 34, February 1997, pp. 143– 153; Fareena Sultan and Gloria Barc- zak, ‘‘Turning Marketing Research High-Tech,’’ Marketing Management 8, Winter 1999, pp. 25–29.
- Nicholas Varchaver, ‘‘Scanning the Globe,’’ Fortune, May 31, 2004, pp. 144–156.
- Xavier Dreze and Francois-Xavier Hussherr, ‘‘Internet Advertising: Is Anybody Watching?’’ Jo u r n a l of In te r ac tiv e Mark eting, Autumn 2003, downloaded from ABI/INFORM Global, June 30, 2005.
CHAPTER 12
- Peter D. Bennett, ed., Dictionary of Marketing Ter ms, 2nd ed. (Chicago: American Marketing Association, 1995), p. 173.
- Our classification follows that of Stanley S. Stevens, ‘‘Mathematics, Measurement and Psychophysics,’’ in Stanley S. Stevens, ed., Handbook of Experimental Psychology (New York: John Wiley, 1951), the most accepted classification in the social sciences.
- Elia Kacapyr, ‘‘Money Isn’t Every- thing,’’ American De mographics 18, July 1996, pp. 10–11; Elia Kacapyr, ‘‘The Well-Being Index,’’ American Demographics 18, February 1996, pp. 32–35, 43.
- Tom J. Brown, John C. Mowen, D. Todd Donavan, and Jane W. Licata, ‘‘The Customer Orientation of Service Workers: Personality Trait Effects on Self- and Supervisor Performance Ratings,’’ Journal of Marketing Research 39, February 2002, pp. 110–119.
- Eunkyu Lee, Michael Y. Hu, and Rex S. Toh, ‘‘Are Consumer Survey Results Distorted? Systematic Impact of Behavioral Frequency and Dura- tion on Survey Response Errors,’’ Journal of Marke ting Research 37, February 2000, pp. 125–133.
- See Gilbert A. Churchill, Jr., ‘‘A Paradigm for Developing Better Measures of Marketing Constructs,’’ Journal of Marke ting Research 16, February 1979, pp. 64–73, for a pro- cedure that can be used to construct scales having construct validity. See
J. Paul Peter, ‘‘Construct Validity: A Review of Basic Issues and Market- ing Practices,’’ Journal of Marketing Research 18, May 1981, pp. 133–145, for an in-depth discussion of the no- tion of construct validity. See also Robert DeVellis, Scale D evelopment: Theory and Applications (Thousand Oaks, Calif.: Sage Publications, 1991).
CHAPTER 13
- The scale was first proposed by Ren- sis Likert, ‘‘A Technique for the Measurement of Attitudes,’’ Archi v es of Psychology 140, 1932.
- Charles E. Osgood, George J. Suci, and Percy H. Tannenbaum, The Mea su remen t o f Mea ning ( Champaign: University of Illinois Press, 1957).
- Joel Herche and Brian Engelland, ‘‘Reversed-Polarity Items and Scale
Unidimensionality,’’ Journa l o f t he Academy o f Marke ting Science 24, Fall 1996, pp. 366–374.
- Gilbert A. Churchill, Jr. and J. Paul Peter, ‘‘Research Design Effects on the Reliability of Rating Scales: A Meta-Analysis,’’ Journal of Marketi ng Research 21, November 1984, pp. 360–375.
- Irvine Clarke III, ‘‘Global Marketing Research: Is Extreme Response Style Influencing Your Results?’’ Journal of International Consumer Marketing 12, 4, 2000, pp. 91–110; Churchill and Peter, ‘‘Research Design Effects on the Reliability of Rating Scales.’’
- Jon A. Krosnick et al., ‘‘The Impact of ‘ No Opinion’ Response Options on Data Quality: Nonattitude Reduc- tion or an Invitation to Satisfice?’’ Public Opinion Quarterly 66, Fall 2002, pp. 371–403, downloaded via Pro- Quest, July 15, 2004.
- National Public Radio, ‘‘All Things Considered,’’ September 7, 1999, summary and audio downloaded from the NPR Web site, http://www.npr. org, September 9, 1999; National Public Radio, ‘‘Americans Willing to Pay for Improving Schools,’’ down- loaded from the NPR Web site, http://www.npr.org, September 9, 1999; ‘‘NPR/Kaiser/Kennedy School Education Survey,’’ downloaded from the NPR Web site, http://www.npr
.org, September 9, 1999.
- See Tom J. Brown, ‘‘Using Norms to Improve the Interpretation of Service Quality Measures,’’ Journal of Services Marketing 11, 1, 1997, pp. 66–80.
- Customer satisfaction scores down- loaded from The American Cus- tomer Satisfaction Index at http:// www.theacsi.org/ as listed as ‘‘Scores by Company’’ and ‘‘Scores by Industry’’ on December 2, 2008.
CHAPTER 14
- This procedure is adapted from one suggested by Arthur Kornhaus- er and Paul B. Sheatsley, ‘‘Ques- tionnaire Construction and Interview Procedure,’’ in Claire Selltiz, Lawrence S. Wrightsman, and Stuart W. Cook, Research Methods in Social Relations, 3rd ed. (New York: Holt, Rinehart and Winston, 1976), pp. 541–573.
- Chris Grecco and Hal King, ‘‘Of Browsers and Plug-Ins: Researching
578 Endnotes
Web Surfers’ Technological Capa- bilities,’’ Qu irk’s Marketing Research Review, July 1999, pp. 58–62.
- These questions were suggested by Kornhauser and Sheatsley, ‘‘Ques- tionnaire Construction and Inter- view Procedure.’’ See also Norman Bradburn, Seymour Sudman, and Brian Wansink, Asking Questions, rev. ed. (San Francisco: Jossey-Bass, 2004).
- Sam Gill, ‘‘How Do You Stand on Sin?’’ Ti de 21, March 14, 1947, p. 72.
- Bradburn, Sudman, and Wansink,
Asking Questions, p. 66.
- Ibid.
- Lee Valeriano Lourdes, ‘‘Market- ing: Western Firms Poll Eastern Europeans to Discern Tastes of Nascent Consumers,’’ The Wall Stre et Journa l, April 27, 1992,
p. B1.
- Jeffrey Pope, How Cultural Differ- ences Affect M ulti-Country Research (Minneapolis, Minn.: GfK Custom Research Inc., 1991).
- E. Noelle-Neumann, ‘‘Wanted: Rules for Wording Structural Question- naires,’’ Public Opinion Quarterly 34, Summer 1970, p. 200; Philip Gendall and Janet Hoek, ‘‘A Question of Wording,’’ Marketing Bulletin 1, May 1990, pp. 25–36.
- Linda Kirby, ‘‘Bloopers,’’ Newspaper Rese ar c h C ouncil, January/February 1989, p. 1.
CHAPTER 15
- Joseph R. Hochstim, ‘‘Practical Uses of Sampling Surveys in the Field of Labor Relations,’’ Pr o c eed i ng s o f t h e Conference on Business Application of Stati stical Sampl ing Methods (Monti- cello, Ill.: The Bureau of Business Management, University of Illinois, 1950), pp. 181–182.
- Jack Neff, ‘‘P&G Enlists 13- Year-Olds in Summer Intern Jobs,’’ Advertising Age, June 28, 1999, p. 20.
CHAPTER 16
- For a more thorough discussion of the estimation of sample size for dif- ferent types of samples and charac- teristics other than the mean and proportion, see Paul S. Levy and Stanley Lemeshow, Sam pling of Po p- ulations: Methods and Applications, 4th ed. ( New York: John Wiley, 2008); Morris H. Hansen, William
N. Hurwitz, and William G. Mad- ow, Sample Surve y Me thods a nd Th eory, Vol. I, Meth ods and Applica- tions (New York: John Wiley, 1993); and Leslie Kish, Survey Sampling (New York: John Wiley, 1995).
- ‘‘Number of ‘Cyberchondriacs’— Adults Going Online for Health Information—Has Plateaued or De- clined,’’ July 29, 2008, downloaded from the Harris Interactive Web site, http://www.harrisinteractive.com, August 26, 2008.
- Seymour Sudman, Applied Sampling (San Francisco: Academic Press, 1976), p. 30. See also Patrick Dat- talo, Determining Sample Size: Balanc- ing Power, Precision, and Practicality (New York: Oxford University Press, 2008).
CHAPTER 17
- W. H. Williams, ‘‘How Bad Can ‘Good’ Data Really Be?’’ The Ameri- can S tatistician 32, May 1978, p. 61. See also Judith T. Lessler and William D. Kalsbeek, Nonsampling Errors in Surveys ( New York: John Wiley, 1992).
- Leslie Kish, Survey Sa mpling ( New York: John Wiley, 1995). Chapter 13, ‘‘Biases and Nonsampling Errors,’’ is particularly recommended for discussion of the biases arising from nonobservation.
- W. Edwards Deming, ‘‘On a Pro- bability Mechanism to Attain an Economic Balance between the Resultant Error of Response and the Bias of Nonresponse,’’ Journal of the American Statistical Association 48, December 1953, pp. 766–767. See also Benjamin Lipstein, ‘‘In Defense of Small Samples,’’ Journal of Adve r- tising Research 15, February 1975, pp. 33–40; William C. Dunkelburg and George S. Day, ‘‘Nonresponse Bias and Callbacks in Sample Surveys,’’ Journal of Marketing Research 10, May 1973, pp. 160–168; Lorna Opatow, ‘‘Some Thoughts about How Inter- view Attempts Affect Survey Re- sults,’’ Journal of Advertising Research 31, February/March 1991, pp. RC6– RC9.
- Ronald M. Weiers, Marketing Research, 2nd ed. ( Englewood Cliffs, N.J.: Prentice Hall, 1988), pp. 213– 217.
- Beth Clarkson, ‘‘Research and the Internet: A Winning Combination,’’
Quirk’s Marketing Research Review, July 1999, pp. 46, 48–51.
- Peter H. Reingen and Jerome B. Kernan, ‘‘Compliance with an Inter- view Request: A Foot-in-the-Door, Self-Perception Interpretation,’’ Journa l o f Marke ting Rese arch 14, 1977, pp. 365–369.
- Frances J. Yammarino, Steven J. Skinner, and Terry L. Childers, ‘‘Understanding Mail Survey Re- sponse Behavior: A Meta-Analysis,’’ Public Opinion Quarterly 55, Winter 1991, pp. 613–639.
CHAPTER 18
- Lourdes Lee Valeriano, ‘‘Marketing: Western Firms Poll Eastern Euro- peans to Discern Tastes of Nascent Consumers,’’ The Wa ll Stree t J ournal, April 27, 1992, p. B1.
- Art Shulman, ‘‘War Stories: True- Life Tales in Marketing Research,’’ Quirk’s Marketing Research Review, December 1998, p. 16.
- ‘‘The Gallup Panel,’’ downloaded from www.gallup.com, June 27, 2008.
CHAPTER 19
- See the classic book by Hans Zeisel, Say It with Figures, 5th ed. (New York: Harper and Row, 1968), pp. 16–17, for conditions that would support reporting per- centages with decimal-place accuracy.
- In Chapter 16, we referred to this range as the precision range. After data have been collected and ana- lyzed, it is more appropriate to refer to this range as a confidence interval, because the range itself, which represents the margin of sampling error, is established for a given level of confidence. If we change the level of confidence, the confidence interval itself will also change.
- See the classic book by Darrell Huff, How to Lie with Statistics (New York: Norton, 1954).
- Robert J. Lavidge, ‘‘How to Keep Well-Intentioned Research from Misleading New-Product Plan- ners,’’ Marketing N ew s 18, January 6, 1984, p. 8.
- The binomial distribution tends toward the normal distribution for a fixed p as sample size increases. The tendency is most rapid when p ¼ 0.5. With sufficiently large samples, normal probabilities may
Endnotes 579
be used to approximate binomial probabilities with p’s in this range. As p departs from 0.5 in either direction, the normal approximation becomes less adequate, although it is generally held that the normal ap- proximation may be used safely if the smaller of np or n(1 - p) is 10 or more. If this condition is not satis- fied, binomial probabilities can ei- ther be calculated directly or found in tables that are readily available. In the example, np ¼ 625(0.2) ¼ 125, and n(1 - p) ¼ 500, and thus there is little question about the adequacy of the normal approximation to bino- mial probabilities.
- For an excellent discussion of some of the most common misinterpre- tations of classical significance tests and some recommendations on how to surmount the problems, see Alan G. Sawyer and J. Paul Peter, ‘‘The Significance of Statistical Significance Tests in Marketing Research,’’ Journal o f Marketing Research 20, May 1983, pp. 122–133. See also Jacob Cohen, ‘‘Things I Have Learned (So Far),’’ American Psychologist 45, December 1990, pp. 1304–1312; Jacob Cohen, ‘‘The
Earth Is Round (p,.05),’’ Americ an Psychologist 49, December 1994, pp.
997–1003.
- If we know the total number of packages sold and the number of packages sold for two of the three categories, the number of packages sold in the third category is fixed and cannot vary independently.
- See Tom J. Brown, Thomas E. Barry, Peter A. Dacin, and Richard
F. Gunst, ‘‘Spreading the Word: Investigating Antecedents of Con- sumers’ Positive Word-of-Mouth Intentions and Behaviors in a Retailing Context,’’ Journal of the Academy of Marketi ng Science 33, Spring 2005, pp. 123–138.
- The appropriate test statistics and how they are calculated also differ (1) if population variance is known or unknown and (2) if the dis- tribution of the variable in the pop- ulation is normal (or at least symmetric) or asymmetric. We consider only the common case in which population variance is un- known and the distribution can be assumed to be symmetric.
- For more on the net promoter score, see Frederick F. Reichheld,
‘‘The One Number You Need to Grow,’’ Harvard Business Review 81, December 2003, pp. 46–54. For a different perspective, see Timothy
L. Keiningham, Bruce Cooil, Tor Wallin Andreassen, and Lerzan Ak- soy, ‘‘A Longitudinal Examination of Net Promoter and Firm Reve- nue Growth,’’ Journal of Marketi ng 71, July 2007, pp. 39–51; and Gina Pingitore, Neil A. Morgan, Lopo
L. Rego, Adriana Gigliotti, and Jay Meyers, ‘‘The Single-Question Trap,’’ Marketing Research 19, Summer 2007, pp. 9–13.
CHAPTER 21
- William J. Gallagher, Report Writi ng for Mana gement (Reading, Mass.: Addison-Wesley, 1969), p. 78. Much of this introductory section is also taken from this excellent book. See also Pnenna Sageev, Hel ping Researchers Write, So Managers Can Understand (Columbus, Ohio: Batelle Press, 1995).
- Taken from William Zinsser, On Writing W ell, 6th ed. (New York: Harper and Row, 1998), pp. 7–8, a modern classic for writers that is as helpful as it is fun to read.
GLOSSARY
A
Accuracy The degree to which the reasoning in the report is logical and the information correct.
Advocacy research Research conducted to support a position rather than to find the truth about an issue.
Alternative hypothesis The hypothesis that a proposed result is true for the population.
Analysis of variance (ANOVA) A statistical technique used with a continuous dependent variable and one or more categorical independent variables.
Area sample A form of cluster sampling in which areas (for example, census tracts, blocks) serve as the primary sampling units. The population is divided into mutually exclusive and exhaustive areas using maps, and a random sample of areas is selected.
Assumed consequences A problem that occurs when a question is not framed so as to clearly state the consequences, and thus it generates different responses from individuals who assume different consequences.
Attitude An individual’s overall evaluation of something.
Awareness/knowledge Insight into, or understanding of facts about, some object or phenomenon.
B
Banner A series of cross tabulations between an outcome, or dependent variable, and several (sometimes many) explanatory variables in a single table.
Bar chart A chart in which the relative lengths of the bars show relative amounts of variables or objects.
Behavior What subjects have done or are doing.
Benchmarking Using organizations that excel at some function as sources of ideas for improvement.
Blunder An error that arises during editing, coding, or data entry.
580 Glossary
Branching question A technique used to direct respondents to different places in a questionnaire, based on their response to the question at hand.
C
Case analysis Intensive study of selected examples of the phenomenon of interest.
Categorical measures A commonly used expression for nominal and ordinal measures.
Causal research Research design in which the major emphasis is on determining cause-and-effect relationships.
Census A type of sampling plan in which data are collected from or about each member of a population.
Central-office edit Thorough and exacting scrutiny and correction of completed data collection forms, including a decision about what to do with the data.
Chi-square goodness-of-fit test A statistical test to determine whether some observed pattern
of frequencies corresponds to an expected pattern.
Clarity The degree to which the phrasing in the report is precise.
Cluster sample A probability sampling plan in which (1) the parent population is divided into mutually exclusive and exhaustive subsets and
(2) a random sample of one or more subsets (clusters) is selected.
Codebook A book that contains explicit directions about how data from data collection forms are to be coded in the data file.
Coding The technical procedure by which raw data are transformed into symbols; it involves specifying the alternative categories or classes into which the responses are to be placed and assigning code numbers to the classes.
Coefficient of determination A measure representing the relative proportion of the total variation in
the dependent variable that can be explained or accounted for by the fitted regression equation.
Coefficient of multiple determination In multiple regression analysis, the proportion of variation in the dependent variable that is explained or accounted for by the covariation in the independent variables.
Communication A method of data collection involving questioning of respondents to secure the desired information, using a data collection instrument called a questionnaire.
Comparative-ratings scale A scale requiring subjects to make their ratings as a series of relative judgments or comparisons rather than as independent assessments.
Completeness The degree to which the report provides all the information readers need in language they understand.
Composite measure A measure designed to provide a comprehensive assessment of an object or phenomenon, with items to assess all relevant aspects or dimensions.
Computer-assisted interviewing (CAI) Using computers to manage the sequence of questions and to record the answers electronically through the use of a keyboard.
Conceptual definition A definition in which a given construct is defined in terms of other constructs in the set, sometimes in the form of an equation that expresses the relationship among them.
Conciseness The degree to which the writing in the report is crisp and direct.
Confidence The degree to which one can feel confident that an estimate approximates the true value.
Confidence interval A projection of the range within which a population parameter will lie at a given level of confidence based on a statistic obtained from a probabilistic sample.
Glossary 581
Constant-sum method A comparative-ratings scale in which
an individual divides some given sum among two or more attributes on a basis such as importance or favorability.
Construct validity Assessment of how well the instrument captures the construct, concept, or trait it is supposed to be measuring.
Content validity The adequacy with which the important aspects of the characteristic are captured by the measure; it is sometimes called face validity.
Continuous measures A commonly used expression for interval and ratio measures.
Continuous panel A fixed sample of respondents who are measured repeatedly over time with respect to the same variables.
Contrived setting Subjects are observed in an environment that has been specially designed for recording their behavior.
Controlled test market An entire test program conducted by an outside service in a market in which it can guarantee distribution.
Convenience sample A nonprobability sample in which population elements are included in
the sample because they were readily available.
Cramer’s V A statistic used to measure the strength of relationship between categorical variables.
Cross tabulation A multivariate technique used for studying the relationship between two or more categorical variables. The technique considers the joint distribution of sample elements across variables.
Cross-sectional study Investigation involving a sample of elements selected from the population of interest that are measured at a single point in time.
Cumulative percent breakdown A technique for converting a continuous measure into a categorical measure. The categories are formed based on the cumulative percentages obtained in a frequency analysis.
D
Data mining The use of powerful analytic technologies to quickly and thoroughly explore mountains of data to obtain useful information.
Data-driven decision support system The part of a decision support system that includes the processes used to capture and the methods used to store data coming from a number of external and internal sources. It is the creation of a database.
Debriefing The process of providing appropriate information to respondents after data have been collected using disguise.
Decision problem The problem facing the decision maker for which the research is intended to provide answers.
Decision support system (DSS) A coordinated collection of data, systems, tools, and techniques with supporting software and hardware, by which an organization gathers and interprets relevant information from business and the environment and turns it into a basis for marketing decisions.
Depth interview Interviews with people knowledgeable about the general subject being investigated.
Descriptive research Research design in which the major emphasis is on determining the frequency with which something occurs or the extent to which two variables covary.
Descriptive statistics Statistics that describe the distribution of responses on a variable. The most commonly used descriptive statistics are the mean and standard deviation.
Dialog-driven decision support system The part of a decision support system that permits users to explore the databases by employing the system models to produce reports that satisfy their particular information needs. It is the user interface of the decision support system, which is also called a language system.
Discontinuous panel A fixed sample of respondents who are measured
repeatedly over time but on variables
that change from measurement to measurement.
Discovery-oriented decision problem A decision problem that typically seeks to answer ‘‘what’’ or ‘‘why’’ questions about a problem/ opportunity. The focus is generally on generating useful information.
Disguise The amount of knowledge about the purpose or sponsor of a study communicated to the respondent. An undisguised questionnaire, for example, is one in which the purpose of the research is obvious.
Disguised observation The subjects are not aware that they are being observed.
Double-barreled question A question that calls for two responses and creates confusion for the respondent.
Double-entry Data entry procedure in which data are entered separately by two people in two data files and the data files are compared for discrepancies.
Dummy table A table (or figure) with no entries used to show how the results of the analysis will be presented.
E
Electrical or mechanical observation An electrical or mechanical device observes a
phenomenon and records the events that take place.
Ethics Moral principles and values that govern the way an individual or a group conducts its activities.
Ethnography The detailed observation of consumers during their ordinary daily lives using direct observations, interviews, and video and audio recordings.
Experiment Scientific investigation in which an investigator manipulates and controls one or more independent variables and observes the degree to which the dependent variables change.
Expert system A computer-based, artificial intelligence system that attempts to model how experts in
the area process information to solve the problem at hand.
582 Glossary
Exploratory research Research design in which the major emphasis is on gaining ideas and insights; it is particularly helpful in breaking broad, vague problem statements into smaller, more precise subproblem statements.
External data Data that originate outside the organization for which the research is being done.
External validity The degree to which the results of an experiment can be generalized, or extended, to other situations.
Eye camera A device used by researchers to study a subject’s eye movements while he or she is reading advertising copy.
F
Field edit A preliminary edit, typically conducted by a field supervisor, which is designed to detect the most glaring omissions
and inaccuracies in a completed data collection instrument.
Field experiment Research study in a realistic situation in which one or more independent variables are manipulated by the experimenter under as carefully controlled conditions as the situation will permit.
Filter question A question used to determine if a respondent is likely to possess the knowledge being sought; also used to determine if an individual qualifies as a member of the defined population.
Fixed sample A sample for which size is determined in advance and needed information is collected from the designated elements.
Fixed-alternative
questions Questions in which the responses are limited to stated alternatives.
Focus group An interview conducted among a small number of individuals simultaneously; the interview relies more on group discussion than on directed questions to generate data.
Frequency analysis A count of the number of cases that fall into each category when the categories are based on one variable.
Funnel approach An approach to question sequencing that gets its name from its shape, starting with broad questions and progressively narrowing down the scope.
G
Galvanometer A device used to measure the emotion induced by exposure to a particular stimulus by recording changes in the electrical resistance of the skin associated with the minute degree of sweating that accompanies emotional arousal; in marketing research, the stimulus is often specific advertising copy.
Geodemography The availability of demographic, consumer-behavior, and lifestyle data by arbitrary geographic boundaries that are typically quite small.
Global measure A measure designed to provide an overall assessment of an object or phenomenon, typically using one or two items.
Graphic-ratings scale A scale in which individuals indicate their ratings of an attribute typically by placing a check at the appropriate point on a line that runs from one
extreme of the attribute to the other.
H
Halo effect A problem that arises in data collection when there is carryover from one judgment to another.
Histogram A form of bar chart on which the values of the variable are placed along the x-axis and the absolute frequency or relative frequency of occurrence of the values is indicated along the y-axis.
Human observation Individuals are trained to systematically observe a phenomenon and to record on the observational form the specific events that take place.
Hypotheses Unproven propositions about some phenomenon of interest.
Hypothesis A statement that specifies how two or more measurable variables are related.
Hypothetical construct A concept used in theoretical models to explain how things work. Hypothetical constructs include such things as attitudes, personality, and
intentions—things that cannot be seen but that are useful in theoretical explanations.
I
In-bound telephone surveys A method of data collection in which respondents place a telephone call at their convenience to a research firm and answer questions, typically by pressing buttons on the telephone.
Incidence The percent of a general population or group that qualifies for inclusion in the population.
Independent samples t-test A technique commonly used to determine whether two groups differ on some characteristic assessed on a continuous measure.
Intentions Anticipated or planned future behavior.
Internal data Data that originate within the organization for which the research is being done.
Internal validity The degree to which an outcome can be attributed to an experimental variable and not to other factors.
Internet-based questionnaire A questionnaire that relies on the Internet for recruitment and/or completion; two forms include
e-mail surveys and questionnaires completed on the Web.
Interval scale Measurement in which the assigned numbers legitimately allow the comparison of the size of the differences among and between members.
Item nonresponse A source of nonsampling error that arises when a respondent agrees to an interview but refuses, or is unable, to answer specific questions.
Itemized-ratings scale A scale on which individuals must indicate their ratings of an attribute or object by selecting the response category that best describes their position on the attribute or object.
J
Judgment sample A nonprobability sample in which the sample elements are handpicked because they are expected to serve the research purpose.
Glossary 583
Justice approach A method of ethical or moral reasoning that focuses on the degree to which benefits and costs are fairly distributed across individuals and groups. If the benefits and costs of a proposed action are fairly distributed, an action is considered to be ethical.
K
Knowledge management The systematic collection of employee knowledge about customers, products, and the marketplace.
L
Laboratory experiment Research investigation in which investigators create a situation with exact conditions in order to control some variables and manipulate others.
Leading question A question framed so as to give the respondent a clue as to how he or she should answer.
Line chart A two-dimensional chart constructed on graph paper with the x-axis representing one variable (typically time) and the y-axis representing another variable.
Literature search A search of
statistics, trade journal articles, other articles, magazines, newspapers, and books for data or insight into the problem at hand.
Longitudinal study Investigation involving a fixed sample of elements that is measured repeatedly through time.
M
Mail questionnaire A questionnaire administered by mail to designated respondents with an accompanying cover letter. The respondents return the questionnaire by mail to the research organization.
Mall intercept A method of data collection in which interviewers in a shopping mall stop or interrupt a sample of those passing by to ask them if they would be willing to participate in a research study.
Market testing (test marketing) A controlled experiment done in a limited but carefully selected sector of the marketplace.
Marketing ethics The principles, values, and standards of conduct followed by marketers.
Marketing information system (MIS) A set of procedures and methods for the regular, planned
collection, analysis, and presentation of information for use in making marketing decisions.
Marketing research The function that links the consumer to the marketer through information—information used to identify and define
marketing problems; generate, refine, and evaluate marketing actions; monitor marketing performance; and improve understanding of marketing as a process.
Measurement Rules for assigning numbers to objects to represent quantities of attributes.
Median split A technique for converting a continuous measure into a categorical measure with two approximately equal-sized groups. The groups are formed by ‘‘splitting’’ the continuous measure at its median value.
Model-driven decision support system The part of a decision support system that includes all the routines that allow the user to manipulate the data so as to conduct the kind of analysis the individual desires. It is the collection of analytical tools to interpret the database.
Moderator The individual that meets with focus group participants and guides the session.
Moderator’s guidebook An ordered list of the general (and specific) issues to be addressed during a focus group; the issues normally should move from general to specific.
Motive A need, a want, a drive, a wish, a desire, an impulse, or any inner state that energizes, activates, or moves and that directs or channels behavior toward goals.
Multichotomous question A fixed- alternative question in which respondents are asked to choose the alternative that most closely corresponds to their position on the subject.
Multicollinearity A condition said to be present in a multiple regression analysis when the independent variables are correlated among themselves.
Multiple regression A statistical technique used to derive an equation that relates a single continuous dependent variable to two or more independent variables.
N
Natural setting Subjects are observed in the environment where the behavior normally takes place.
Nominal group A group interview technique which initially limits respondent interaction to a minimum while attempting to maximize input from individual group members.
Nominal scale Measurement in which numbers are assigned to objects or classes of objects solely for the purpose of identification.
Noncoverage error Nonsampling error that arises because of a failure to include some units, or entire sections, of the defined target population in the sampling frame.
Nonprobability sample A sample that relies on personal judgment in the element selection process.
Nonresponse error Nonsampling
error that represents a failure to obtain information from some elements of the population that were selected and designated for the sample.
Nonsampling error Error that arises in research that is not due to sampling; nonsampling error can occur because of errors in conception, logic, interpretation of questions and replies, statistics, arithmetic, analyzing, coding, or reporting.
Normative standard A comparative standard used to provide meaning to raw scale scores.
Not-at-homes Nonsampling error that arises when replies are not secured from some designated sampling units because the respondents are not at home when the interviewer calls.
Null hypothesis The hypothesis that a proposed result is not true for the population. Researchers typically
584 Glossary
attempt to reject the null hypothesis in favor of some alternative hypothesis.
O
Observation A method of data collection in which the situation of interest is watched and the relevant facts, actions, or behaviors are recorded.
Office error Nonsampling error due to data editing, coding, or analysis errors.
Open-ended question A question for which respondents are free to reply in their own words rather than being limited to choosing from among a
set of alternatives.
Operational definition A definition of a construct that describes the operations to be carried out in order for the construct to be measured empirically.
Opinion Verbal expression of an attitude.
Optical scanning The use of scanner technology to ‘‘read’’ responses on paper surveys and to store these responses in a data file.
Ordinal scale Measurement in which numbers are assigned to data on the basis of some order (for example, more than, greater than) of the objects.
Outlier An observation so different in magnitude from the rest of the observations that the analyst chooses to treat it as a special case.
P
Paired sample t-test A technique for comparing two means when scores for both variables are provided by the same sample.
Parameter A characteristic or measure of a population.
Pearson chi-square test of independence A commonly used statistic for testing the null hypothesis that categorical variables are independent of one another.
Pearson product-moment correlation coefficient A statistic that indicates the degree of linear association between two continuous
variables. The correlation coefficient can range from -1 to þ1.
People meter A device used to measure when a television is on, to what channel it is tuned, and who in the household is watching it.
Performance of objective tasks A method of assessing attitudes that rests on the presumption that a subject’s performance of a specific assigned task (for example, memorizing a number of facts) will depend on the person’s attitude.
Personal interview Direct, face-to- face conversation between a representative of the research organization, the interviewer, and a respondent, or interviewee.
Personality Normal patterns of behavior exhibited by an individual; the attributes, traits, and mannerisms that distinguish one individual from another.
Physiological reaction A method of assessing attitudes in which the researcher monitors the subject’s response, by electrical or mechanical means, to the controlled introduction of some stimuli.
Pictogram A bar chart in which pictures represent amounts—for example, piles of dollars for income, pictures of cars for automobile production, people in a row for population.
Pie chart A circle representing a total quantity and divided into sectors, with each sector showing
the size of the segment in relation to that total.
Plus-one sampling A technique used in studies employing telephone interviews, in which a single, randomly determined digit is added to numbers selected from the telephone directory.
Population All cases that meet designated specifications for membership in the group.
Precision The degree of error in an estimate of a population parameter.
Predictive validity The usefulness of the measuring instrument as a predictor of some other characteristic or behavior of the individual; it is sometimes called criterion-related validity.
Pretest Use of a questionnaire (or observation form) on a trial basis in
a small pilot study to determine how well the questionnaire (or observation form) works.
Primary data Information collected specifically for the investigation at hand.
Primary source The originating source of secondary data.
Probability sample A sample in which each target population element has a known, nonzero chance of being included in the sample.
Program strategy A company’s philosophy of how marketing research fits into its marketing plan.
Project strategy The design of individual marketing research studies that are to be conducted.
Projective methods Methods that encourage respondents to reveal their own feelings, thoughts, and behaviors by shifting the focus away from the individual through the use of indirect tasks.
P-value The probability of obtaining a given result if in fact the null hypothesis were true in the population. A result is regarded as statistically significant if the p-value is less than the chosen significance level of the test.
Q
Question order bias The tendency for earlier questions on a questionnaire to influence respondents’ answers to later questions.
Quota sample A nonprobability sample chosen so that the proportion of sample elements with certain characteristics is about the same as the proportion of the elements with the characteristics in the target population.
R
Random error Error in measurement due to temporary aspects of the person or measurement situation and which affects the measurement in irregular ways.
Random-digit dialing (RDD) A technique used in studies using telephone interviews, in which the numbers to be called are randomly generated.
Glossary 585
Randomized-response model An interviewing technique in which potentially embarrassing and relatively innocuous questions are paired, and the question the respondent answers is randomly determined but is unknown to the interviewer.
Ratio scale Measurement that has a natural, or absolute, zero and therefore allows the comparison of absolute magnitudes of the numbers.
Recall loss A type of error caused by a respondent’s forgetting that an event happened at all.
Refusals Nonsampling error that arises because some designated respondents refuse to participate in the study.
Reliability Ability of a measure to obtain similar scores for the same object, trait, or construct across time, across different evaluators, or across the items forming the measure.
Request-for-proposal (RFP) A document that describes, as specifically as possible, the nature of the problem for which research is sought and that asks providers to offer proposals, including cost estimates, about how they would perform the job.
Research design The framework or plan for a study that guides the collection and analysis of the data.
Research problem A restatement of the decision problem in research terms.
Research process The sequence of steps in the design and implementation of a research study.
Research proposal A written statement that describes the marketing problem, the purpose of the study, and a detailed outline of the research methodology.
Research request agreement A document prepared by the researcher after meeting with the decision maker that summarizes the problem and the information that is needed to address it.
Response error Nonsampling error that occurs when an individual provides an inaccurate response, consciously or subconsciously, to a survey item.
Response latency The amount of time a respondent deliberates before answering a question.
Response order bias An error that occurs when the response to a question is influenced by the order in which the alternatives are presented.
Response rate The number of completed interviews with responding units divided by the number of eligible responding units in the sample.
Response set bias A problem that arises when respondents answer questionnaire items in a similar way without thinking about the items.
Reverse scaling A technique in which some of the items on a multi-item scale are written so that the most positive responses are at the opposite end of the scale from where they would normally appear.
Rights approach A method of ethical or moral reasoning that focuses on the welfare of the individual and that uses means, intentions, and features of an act itself in judging its ethicality. If any individual’s rights are violated, the act is considered unethical.
Role playing A projective method in which a researcher will introduce a scenario or context and ask respondents to play the role of a person in the scenario.
S
Sample Selection of a subset of elements from a larger group of objects.
Sample mean The arithmetic average value of the responses on a variable.
Sample standard deviation A measure of the variation of responses on a variable. The standard deviation is the square root of the calculated variance on a variable.
Sample survey Cross-sectional study in which the sample is selected to be representative of the target population and in which the emphasis is on the generation of summary statistics such as averages and percentages.
Sampling error The difference between results obtained from a sample and results that would have been obtained had information been gathered from or about every member of the population.
Sampling frame The list of population elements from which a sample will be drawn; the list could consist of geographic areas, institutions, individuals, or other units.
Sampling interval The number of population elements to count (k) when selecting the sample members in a systematic sample.
Scanner An electronic device that automatically reads the Universal Product Code imprinted on a product, looks up the price in an attached computer, and instantly prints the description and price of the item on the cash register receipt.
Scatter diagram A graphic technique in which a sample element’s scores on two variables are used to position the element on a graph so that the nature of the relationship between the variables can be observed.
Secondary data Information not gathered for the immediate study at hand but for some other purpose.
Secondary source A source of secondary data that did not originate the data but rather secured them from another source.
Self-report A method of assessing attitudes in which individuals are asked directly for their beliefs about or feelings toward an object or class of objects.
Semantic-differential scale A
self-report technique for attitude measurement in which the subjects are asked to check which cell between a set of bipolar adjectives or phrases best describes their feelings toward the object.
Sentence completion A projective method in which respondents are directed to complete a number of sentences with the first words that come to mind.
Sequential sample A sample formed on the basis of a series of successive decisions.
Significance level (a) The acceptable level of Type I error selected by the
586 Glossary
researcher, usually set at 0.05. Type I error is the probability of rejecting the null hypothesis when it is actually true for the population.
Simple random sample A probability sampling plan in which each unit included in the population has a known and equal chance of being selected for the sample.
Simple regression A statistical technique used to derive an equation that relates a single continuous dependent variable to a single independent variable.
Simulated test market (STM) A study in which consumer ratings are obtained along with likely or actual purchase data often obtained in a simulated store environment; the
data are fed into computer models to produce sales and market share predictions.
Single-source data Data that allow researchers to link together purchase behavior, household characteristics, and advertising exposure at the household level.
Snake diagram A diagram that con- nects the average responses to a series of semantic-differential statements, thereby depicting the profile of the object or objects being evaluated.
Snowball sample A judgment sample that relies on the researcher’s ability to locate an initial set of respondents with the desired characteristics.
Split-ballot technique A technique used to combat response bias in which one phrasing is used for a question in one-half of the questionnaires while an alternative phrasing is used in the other one- half of the questionnaires.
Standard test market A test market in which the company sells the product through its normal distribution channels.
Stapel scale A self-report technique for attitude measurement in which respondents are asked to indicate how accurately each of a number of statements describes the object of interest.
Statistic A characteristic or measure of a sample.
Storytelling A projective method of data collection relying on a picture
stimulus such as a cartoon, photograph, or drawing, about which the subject is asked to tell a story.
Strategy-oriented decision problem A decision problem that
typically seeks to answer ‘‘how’’ ques- tions about a problem/opportunity. The focus is generally on selecting al- ternative courses of action.
Stratified sample A probability
sample in which (1) the population is divided into mutually exclusive and exhaustive subsets, and (2) a simple random sample of elements is
chosen independently from each group or subset.
Stratum chart A set of line charts in which quantities are aggregated or a total is disaggregated so that the distance between two lines represents the amount of some variable.
Structure The degree of standardization used with the data collection instrument.
Structured observation The problem has been defined precisely enough
so that the behaviors that will be observed can be specified beforehand, as can the categories that will be used to record and analyze the situation.
Summated-ratings scale A self- report technique for attitude measurement in which respondents indicate their degree of agreement or disagreement with each of a number of statements.
Systematic error Error in measurement that is also known as constant error since it affects the measurement in a constant way.
Systematic sample A probability sampling plan in which every kth element in the population is selected for the sample pool after a random start.
T
Telephone interview Telephone conversation between a representative of the research organization, the interviewer, and a respondent, or interviewee.
Telescoping error A type of error resulting from the fact that most people remember an event as having occurred more recently than it did.
Total sampling elements (TSE) The number of population elements that must be drawn from the population and included in the initial sample pool in order to end up with the desired sample size.
Two-box technique A technique for converting an interval-level rating scale into a categorical measure usu- ally used for presentation purposes. The percentage of respondents choosing one of the top two positions on a rating scale is reported.
U
Undisguised observation The subjects are aware that they are being observed.
Unstated alternative An alternative answer that is not expressed in a question’s options.
Unstructured observation The problem has not been specifically defined, so a great deal of flexibility is allowed the observers in terms of what they note and record.
Utility approach A method of ethical or moral reasoning that focuses on society and the net consequences that an action may have. If the net result of benefits minus costs is
positive, the act is considered ethical; if the net result is negative, the act is considered unethical.
V
Validity The extent to which differences in scores on a measuring instrument reflect true differences among individuals, groups, or situations in the characteristic that it seeks to measure, or true differences in the same individual, group, or situation from one occasion to another, rather than systematic or random errors.
Voice-pitch analysis Analysis that examines changes in the relative frequency of the human voice that accompany emotional arousal.
W
Word association A projective method in which respondents are asked to respond to a list of words with the first word that comes to mind.
INDEX
A
absolute magnitude, 250
accuracy, 488
and objectivity, 190
problems of, 140
ACNielsen, 8, 122, 165, 166, 235
action, 495
administrative control, 200, 204, 210,
212, 216, 217, 218
Advanced General Aviation Transport Experiment (AGATE), 381
advertising,
Internet, 170
multimedia services, 171
print media, 170 television and radio, 167
advertising agencies, 10–12
advertising exposure and effectiveness, measuring, 167–172
advocacy research, 142
Aegis Group’s Synovate, 182 Aeropostale, 87, 93
Agora Inc., 226
alternative hypothesis, 434
Altria, 123
ambiguous words and questions, 300 American Cancer Society, 17 American Customer Satisfaction Index
(ACSI), 282
American Express, 211
American League, 141
American Marketing Association (AMA), 226
American Water Heater Company, 1 analyses involving
categorical and continuous measures, 458
categorical measures, 451–458
continuous measures, 466–475 analysis,
adding variables to an, 459
of variance (ANOVA), 463–466, 473
analyst, 14
analytical approach to ethical problems, 50
AOL Media Network, 171
Apple Computer Inc., 1, 77, 171, 184,
483
Arbitron, 12, 13, 72, 111, 114–115,
168, 169
Arby’s Inc., 137, 138, 139
area sample, 343
Asda, 230
assumed consequences, 304
AT&T Corp., 94, 282
AT&T Wireless, 232
attitude(s), 179
measuring, 267
attitudes/opinions, 179
Avery Fitness Center (AFC), 407, 408–412, 452, 453, 454, 455, 458,
461, 462, 464, 465, 466
project, 423–444
SPSS output, 427–428
Avon, 58
awareness/knowledge, 180
Ayres, Ian, 29
B
BabyAge.com, 234
BackCountry.com, 233
Bacon, Craig, 251 Bank of America, 127 banner, 456
banner tables, cross-tab results, 456 bar chart, 504
bar chart variations, 505 basic univariate statistics,
categorical measures, 423–429
continuous measures, 429–434 BayCare Health System, 25 BedBathandBeyond.com, 234
behavior, 185
Behaviorscan, 121, 127
benchmarking, 94
Berries.com, 233
Best Buy, 483
BestBuy.com, 233
Blockbuster, 300, 301, 302
Blue Smoke, 4
Bluefly.com, 233
BlueNile.com, 233
blunder, 412
Bohounek, Michael, 30
Booz Allen, 125
branching question, 306
brand image, 182
brand purchases, 98
brand-switching analysis, 112–113 British Sky Broadcasting (BSkyB), 167 Buick, 57
Burger King, 43
Burke Inc., 236
business information, 158 business intelligence, links to
marketing intelligence, 29 buyer behavior theory, 178
C
callback, 379
Cameron, Gene, 180
Campbell Soup, 125, 189
CAN, 28
Cargill, 238
Carlson Marketing Group, 180 Cars.com, 1
case analysis, 93
Cassell, Justine, 92
categorical measures, 423
analyses involving, 451, 458 converting continuous measures to,
431
causal research, 38, 79
experiments as, 117
causal research designs, 116–122 causality,
concept of, 117
evidence of, 118–119
CBS, 399
CDUniverse.com, 233
census, 326
census data, 155
central-limit theorem, 355
central-office edit, 401
CfK Custom Research Inc. (CRI), 254 change, planned vs. unplanned, 57 Chase & Sanborn, 8
Chase Manhattan Bank, 162 Cheskin Research, 236 Chicago Housing Authority, 1
Children’s Online Privacy Protection Act, 45
chi-square goodness-of-fit test, 440 Chrysler, 57
Cimermancic, Frank, 88
CitiBank, 17
clarity, 488
classification information list, 307 client meeting, problem formulation,
56
closed-ended
items, coding, 403
questions, 296
cluster sample, 342
Coca-Cola Company, 8, 43, 55, 60, 123
codebook, 407
coded forms, 40
coding, 403–412
closed-ended items, 403
open-ended items, 404 coefficient of
determination, 471
multiple determination, 474
Cohen, Mark, 29
communication, 186
disguised vs. undisguised, 198–200 structured vs. unstructured, 195–197
Index 587
588 Index
CompactAppliance.com, 233, 234
company information, 155
comparative-ratings scale, 274
completeness, 487
composite measure, 276
computer-assisted interviewing (CAI), 209
conceptual definition, 252
concise, 489
conciseness, 489
confidence, 357
confidence interval, 428
for means, 433
for proportions, 426 confidentiality/anonymity, guarantee
of, 390
Conquest Research, 243
conscience money, 70
consistency, 257
constant-sum method, 274
construct validity, 260
content validity, 259
continuous measures, 429
analyses involving, 458
converting to categorical measures, 431
converting to categorical measures, 457
continuous panel, 110
contrived setting, 234 controlled test market, 126 convenience sample, 334
Cooking.com, 233
correlation coefficient, Pearson product-moment, 466
cost estimate, research proposal, 69
Council for Marketing and Opinion Research, 377
CPC International, 8
Cramer’s V, 456
Crayola L.L.C., 120
Crayola.com, 120
CRM, see customer relationship management
cross tabulation, 451
converting continuous measures to categorical measures, 457
Cross, Bob, 138 cross-sectional
analysis, 114
study, 109
cross-tab results, banner tables, 456 Crutchfield.com, 233
cumulative percentage breakdown, 431
Curtis Publishing Company, 8 customer relationship management
(CRM), 30, 31–32
customers, profiling, 161–162
D
data,
analyzing and interpreting, 40 cleaning the, 412–414
collecting, 39
collection of, 374–393
missing, 414
primary, 39, 176–190
secondary, 38
data analysis, 399
coding, 403–412
editing, 401–403
multiple variables, 450–475
preliminary steps, 400–415 variables and hypothesis testing,
422–444
data collection, other methods, 388 data collection forms, 69, 243
designing, 39
data collection method, determining, 38
data file, building the, 406 data mining, 27, 28
data processing, tabulation and, 47 data sources, research design and, 69 data-driven decision support system,
23
debriefing, 200
decision problem, 37, 60
discovery-oriented, 61, 65
strategy-oriented, 61, 65 decision support system (DSS), 21,
23, 26
analytical tools, 25–26
components of, 23–28
database, 23–25
data-driven, 23
dialog-driven, 26–28
model-driven, 25–26
user interface, 26–28
Del Monte, 127
Delsalle, Delphine, 135 demographic data, sample median
household income, 163 demographic/socioeconomic
characteristics, 177
DeNicola, Nino, 236, 237
Dentsu Inc., 10, 12
depth interview, 83
derived population, 351, 352
descriptive research, 38, 79 descriptive research design, 107–116 descriptive statistics, 429
descriptive study, types of, 109 dialog systems, use of, 27 Dialog, 149
dialog-driven decision support system, 26–28
Dialogue Resource Inc., 236 Diamond.com, 233
diary panels (online), 164 direct observation, 223
discontinuous panel, 110
discovery-oriented decision problem, 61, 65
disguise, 198
ethics of, 198 disguised
communication, 198–200
observation, 232
Disney, 252
disproportionate stratified sample, 342 Dodge, 57
Dole, 125
Dominick’s, 96
double-barreled question, 305
double-entry, 413
Dow Jones, 149
DSS, see decision support system, 21 dummy table, 108
importance of, 108
Dun & Bradstreet International Business Locator, 161
E
E*Trade Financial, 1
EasternMountainSport, 233
Eastman Kodak, 94
Ebags.com, 233
eBay, 171
economic censuses, 156–157
editing, 401–403
EDSR, see Electronic Diary Storage and Retrieval
eHarmony.com, 29
electrical observation, 235
Electronic Diary Storage and Retrieval (EDSR), 115
Elliott, Jock, 489
Energy/BBDO, 180
Enron, 182
enterprise resource planning (ERP), 30 environmental differences,
marketing, 8
errors, types of nonsampling, 375–384 ESPN, 111
estimates, 304
multiple, 363 ethical
analysis, practical guidelines, 51 frameworks, applying, 48 problems, analytical approach
to, 50
reasoning, methods of, 43–51 ethics, 42
marketing, 42
ethnography, 94, 95
case against, 97
evaluations, 182
Experian Consumer Research, 171
Index 589
experiment, 117
field, 119
laboratory, 119
expert system, 26
exploratory research, 38, 79, 81–100 exploratory studies, types of, 82 external data, 143
published, 146, 149
external validity, 120
eye camera, 239
F
face validity, 259
faces scale, 273
Federal Trade Commission, 232 Ferrero, 127
field
edit, 401
experiment, 119
work director, 14
filter question, 292
Fingerhut Companies, 27 fit, problems of, 140
fixed sample, 333
fixed-alternative questions, 195
focus group, 84
characteristics of, 85 dark side of, 90
focus group moderator, characteristics of, 91
Foley, Linda, 25
follow-up surveys, 392
Food and Drug Administration, 142 foot-in-the-door technique, 389
Ford Motor Co., 84, 96, 182, 198
Forrester Research Inc., 43, 483 Fox Interactive Media, 171
frequencies, chi-square goodness-of-fit test for, 440
frequency, other uses for, 425 frequency analysis, 424
Frigidaire, 136
Frito-Lay, 120, 121–122, 123, 125, 179
Fry, Art, 58
full-time interviewer, 14
funnel approach, 306 Future Now, Inc., 233–234
G
Gallegos, Michael, 325
Gallup Organization, 206
Gallup, 293
galvanometer, 238
Gartner Research, 25
Geiger, Julian, 93
general economic and statistical information, 158
General Electric Co., 182 General Mills, 61, 123
General Motors Corp., 122, 182, 198
generalizations, 304
geodemography, 161
geographic information system (GIS), 162
geometric mean, 250
GfK AG USA, 12, 13, 126, 127
Girl Scout Research Institute, 4 Girl Scouts, 4, 5
global measure, 276
GMC, 57
Goodyear, 9
Google, 149, 170, 171
Graduate Management Admissions Test (GMAT), 259
Gramm-Leach-Bliley Act, 24
GrandKids Ltd., 140 graphic presentation,
bar chart variations, 505 bar chart, 504
line chart, 502
of report, 500–507
pie chart, 501
stratum chart, 503
graphic-ratings scale, 268
Greenfield Online, 89
H
Haack, Trenton, 236
Halliburton, 29
halo effect, 274
Harley-Davidson, 87, 88, 252
Harris Poll, 360
Helio, 77
Hernandez, Jesus, 325
Herschend Family Entertainment Corporation, 11
Hershkowitz-Coore, Sue, 498
Hewlett-Packard, 223
high structure, advantages and disadvantages, 195
histogram, 425
Home Depot Inc., 138 Honda, 57, 198
Howe, Michael, 138
human observation, 235
hypothesis, 81, 434
testing for individual variables, 439–444
hypothesis testing, 434–439 hypothesis testing procedure, 435 hypothetical construct, 251
I
Ice.com, 233
Identity Theft Resource Center (ITRC), 25, 26
IMS Health Inc., 12
in-bound telephone surveys, 208 incidence, 328
independent samples t-test, 460
indexes, 158
indirect observation, 223
industry information, 155 information,
collecting by communication, 194–218
collecting by observation, 222–239
information control, 200, 203, 209,
210, 216, 217
Information Resources Inc. (IRI), 126, 127, 166, 238
information systems, evolution and design, 21–23
InfoTech Marketing, 148
infoUSA, 331
ING Direct, 4
Integrated Marketing Communi- cations, 485
intelligence gathering, future methods, 32–33
intentions, 183
interjudge reliability, 258
internal data, 143
sources of, 146
Internal Revenue Service, 142, 143
internal validity, 119 international issues, marketing, 8 Internet, 170
internet-based questionnaires, 213
interval scale, 249 interview,
depth vs. personal survey, 85 depth, 83
interviewer characteristics and training, 390
iPod, 184
Ipsos, 12
IRI, 12
item nonresponse, 298, 414
itemized-ratings scale, 269
other, 272
ITRC, see Identity Theft Resource Center
J
J. D. Power and Associates, 180, 199
J. Walter Thompson, 96 JC Penney, 10
Jeep, 57
job opportunities, 13–15 jobs,
titles and responsibilities, 14
types in marketing research, 13–15 John Deere, 111
Johnson & Johnson, 125 Jones, Timothy, 223
judgment sample, 336
junior analyst, 14
justice approach, 48
590 Index
K
Kaiser Family Foundation, 278 Kantar Group, 12
KBToys.com, 234
Keio University, 10
Kellogg, 111
Kennedy School of Government, 278 Kimberly-Clark Corporation, 125
Klein, Scott, 238
Knorr Soup, 167
knowledge management, 28–29 Knowledge Networks, Inc., 325 Kraft, 9
Krispy Kreme, 232
Kroger, 4
L
L.L. Bean, 94 L.L.Bean.com, 233
La Mantia, Simona, 135 laboratory experiment, 119
Lajoie, Napoleon, 141, 142
Landsend.com, 233
Larkin Electronics, 281
Larson, Gordon, 28
Leach, Robert, 167
leading question, 302
Lending Tree, 25
Lexis/Nexis, 149
Lids.com, 233
lifestyle analysis, 179
Likert scale, 270 Lindsey, Dr. Ralph, 67 line chart, 502
literature search, 82
Lodish, Leonard, 121 longitudinal
analysis, 109
study, 109
Lopez, Rogelio, 325
Love, Kathi, 180
low structure, advantages and disadvantages, 197
Lowe’s, 188
Lyons-Cavazos, Miguel, 236, 237
M
mail and e-mail surveys, 384 mail questionnaire, 210
mall intercepts, 202
manager’s decision problem, problem formulation, 60
Maps, Inc., 162
margin of sampling error, 428 marginal totals, 453
Mariampolski, Hy, 188 market
and consumer information, 157 orientation, 2, 24
research director, 14
share and product sales, measuring, 162–167
market testing, 122–130 key issues in, 123 misfires in, 125–126
marketing,
environments affecting, 6
information needed, 3–7 marketing dashboard, example of,
21–22
marketing ethics, 42
marketing information system (MIS), 21, 22, 23, 26, 83, 415
marketing intelligence, gathering, 21–33
linking to other intelligence, 29 project and systems approach,
21–23
project approach, 36–51
systems approach, 21–33 trends in obtaining, 27–33
marketing research, 5
advertising agencies, 10–12
companies, 12–13
environmental differences, 8
ethics of, 42–43
formulate problem, 37
intelligence gathering, 9
international missteps, 8
introduction to, 1
job opportunities, 13–15
job titles and responsibilities, 14 practice of, 7–13
producers of products and services, 9–10
questions answered, 7 reasons for study, 15–16 role of, 2–16
Silver Dollar City, 11–12 steps in, 37–42
types of jobs, 13–15
Marketing Research Association, Inc., 44–47
Marketing Research Insights, 82 marketing research manager, 14 marketing research standards, code of,
44–47
marketing research steps, comments on, 40
Marketing Services Group, 489 MarketResearch.com, 30
McCann-Erickson WorldGroup, 10
McDonald’s, 6, 7, 122, 123, 125, 138,
139
means,
confidence intervals for, 433 independent samples t-test for, 460 paired sample t-test for, 461
measurement, 245
basics of, 244–262
development of, 261
interval scale, 249
nominal scale, 247
ordinal scale, 247
problems in, 251–253
ratio scale, 250
scales of, 245–251
validity of measures, 253–257 measures,
establishing the validity of, 253–257
marketing construct, 261 measuring attitudes and variables,
266–282
mechanical observation, 235 Mediamark Research Inc. (MRI), 172,
180
median split, 431
Meischen, Herb, 238
Meister Brau, 55
Mercedes-Benz, 185
Merry Maids, 303 Metallic Metals Act, 291 Metaphorix, 243
Meyer, Danny, 4
MGA Entertainment Inc., 87 Microsoft Corp., 4, 171, 195, 197, 253,
255, 256, 276
Miller Brewing Company, 55 Miller Business Systems, Inc., 82 MIS, see marketing information
system Mitchell’s, 199
model-driven decision support system, 25–26
moderator, 84
role of, 89
moderator’s guidebook, 89
modified callback, 380
Moen Inc., 188, 189
Mosinee Paper Company, 83 motivation, 185
motive, 185
Motorola, 1, 94
MSN/Windows Live, 171
multichotomous question, 296
multicollinearity, 474
multimedia services, 171 multiple
determination, coefficient of, 474 estimates in a single project, 363 regression, 473
Mystery Shoppers, 233–234
N
N. W. Ayer & Son, 7
National Association for Stock Car Auto Racing (NASCAR), 325
National Basketball Association (NBA), 27
National Consumer Survey, 171 National Eating Trends (NET), 164
Index 591
National Public Radio, 278
National Tax Limitation Committee, 303
National-Do-Not-Call (DNC)
Registry, 206, 208
natural setting, 234
Netflix, 29
Nichols-Shepard Company, 7
Nielsen Company, 8, 12, 13, 77, 110,
143, 145, 167, 168–169, 170, 343,
344
Nielson BuzzMetrics, 77
Nike, 77, 135
NikeWomen, 135
nominal group, 93
nominal scale, 247
noncoverage error, 376
nonprobability sample, 39, 333
nonresponse error, 375, 377
types of, 375–384 nonsampling errors,
impact and importance of, 375 overview of, 385
normal thinking, problem with, 60 normative standard, 281
North American Industry Classifi- cation System (NAICS), 161
Northbrook, 236
not-at-homes, 378
NPD Group, 110, 164, 179
null hypothesis, 434
O
objective tasks, performance of, 267 objectivity and accuracy, 190 observation, 186
collecting information by, 222–239 direct and indirect, 223
disguised, 232
galvanometer, 238
human vs. mechanical, 235 natural vs. contrived setting, 234 structured vs. unstructured, 225 undisguised, 232
unstructured, 230
observation forms, 312–318
observation research, 223–239
examples of, 223
office error, 383
OfficeDepot.com, 234
OfficeMax.com, 234 Ogilvy & Mather, 489 OneStepAhead.com, 234 open-ended
items, coding, 404
questions, 195
opening questions, 306
operational definition, 252
opinion, 179
opportunity vs. problem, 56 optical scanning, 413
oral report, 495–500
delivering the, 497
preparation of, 496
ordinal scale, 247
ordinary least-squares (OLS), 470 Oscar Meyer, 9
outlier, 425
overcoverage error, 377
P
paired sample t-test, 461 parameter(s), 330
vs. statistics, 328
Pardo, Ruben, 325
Parle, 8
Pearson chi-square test of independence, 455
Pearson product-moment correlation coefficient, 466, 467
Penn, David, 243
people meters, 167
PeopleSoft, 43
Pepsico, Inc., 17, 55, 238
percentages, 425
performance of objective tasks, 267 personal interview, 200
personality/lifestyle characteristics, 178
personalization, 391
personnel requirements, research proposal, 69
Pharmaceutical Supply Company, 203 physiological reaction, 267
pictogram, 505
pie chart, 501
Pillsbury, 9, 125
planned change vs. unplanned change, 57
plus-one sampling, 206
point estimate, 357 Poltrack, David F., 399 Pontiac, 57
population, 39, 327
defining the target, 327–330 derived, 351, 352
population mean vs. sample mean, 353
population size and sample size, 363–364
portable people meter (PPM), 169 precision, 357
predictive validity, 259
prenotification, 390
presentation, using notes for a, 499 presentation skills, 496
pretest, 311
primary data, 39, 136
attitudes/opinions, 179
awareness/knowledge, 180
behavior, 185
choices for collecting, 187 collecting, 176–190
demographic/socioeconomic, 177
intentions, 183
motivation, 185
objectivity and accuracy, 190 obtaining, 186–190
personality/lifestyle, 178 speed and cost, 189 types of, 177–186
versatility, 187
primary source, 140
print media, 170
PRIZM (Potential Ratings for Zip Markets), 162
probability sample, 39, 333, 337–343 problem definition,
and background, 68
introduction to, 1
problem formulation, 54–73
clarify problem/opportunity, 58 develop research problems, 64 key steps in, 57
manager’s decision problem, 60 meet with client, 56
process of, 56–68
research request agreement, 66 select research problems, 65
problem vs. opportunity, 56 problem, formulation of, 37 problem/opportunity, clarified for
problem formulation, 58
Procter & Gamble (P&G), 4, 123,
125, 127, 336
producers of products and services, 9–10
product sales and market share, measuring, 162–167
products, producers of, 9–10 program strategy, 37
project approach,
marketing intelligence, 21–23
to marketing intelligence, 36–51 project strategy, 37
projective methods, 97 proportionate stratified sample, 341
proportions, confidence intervals for, 426
p-value, 438
Q
QualiData Research, 188 quality, evidence of, 142 quality perceptions, 182 question order bias, 306 questionnaire(s),
cover letter for, 309–310 design of, 287–312
determine content, 289 form of response, 294 information sought, 287
Internet-based, 213
mail, 210
592 Index
method of administration, 288 methods of administering,
200–218
personal interview, 200 physical characteristics of, 307 preparation checklist, 313–314
question sequence, 305
question wording, 298
recruiting message/script, 308 reexamination of steps, 311 revisions to, 311
telephone interviews, 204 questions, asking good, 244–262 quota sample, 336
R
Ramirez, Jose Luis, 325 random error, 256
random-digit dialing (RDD), 206 randomized-response model, 294 rating scales,
interpreting, 279–282
raw scores vs. norms, 280–282 ratio scale, 250
recall loss, 293
Redwood Shores, 236
Reebok, 181, 183
refusals, 377
reliability, 257
and validity, assessment of, 257–261
request-for-proposal (RFP), 72 research,
advocacy, 142
causal, 38, 79
descriptive, 38, 79
exploratory, 38, 79, 81–100
marketing, 5
observation, 223–239
research budget, and sample size, 365 research design, 77, 78–100
and data sources, 69 descriptive, 107–116
determining, 38
relationships, 80
types of, 79–81 Research in Motion, 1 Research Partners, Ltd., 67 research problem, 37, 64
development for problem formu- lation, 64
select for problem formulation, 65 research process, 37
typical questions, 41
research proposal, 68–70
analysis of, 69
appendices, 70
cost estimate, 69
data collection forms, 69 design and data sources, 69 personnel requirements, 69
problem definition and background, 68
sampling plan, 69
time schedule, 69
research report(s), 483–507
appendices, 494
conclusions and recommendations, 494
data collection and results, 492 executive summary, 491 graphic presentation of results,
500–507
introduction, 492
oral report, 495–500
outline, 491–495
preparation of, 40 table of contents, 491 title page, 491
written, 486–490
research request agreement, 37, 66,
67–68
preparation for problem formulation, 66
research supplier, choosing a, 71–73 research to avoid, 70–71
response
category, ‘‘don’t know,’’ 278 error, 380
incentives, 391
latency, 237
order bias, 298
rate, 384
calculating, 384–388
improving, 388–393
set bias, 275
reverse scaling, 275
RFP, see request-for-proposal rights approach, 49
Rite Aid Pharmacies, 123 RJR Nabisco, 55
role playing, 99
Roth, Susan, 89
Rowland, Janice, 203
Rubbermaid, 57
S
Salesforce.com, 1
Sam’s Club, 138
sample, 39, 326
area, 343
cluster, 342
convenience, 334
designing, 39
disproportionate stratified, 342
fixed, 333
judgment, 336
nonprobability, 39, 333, 334–337
probability, 39, 333
proportionate stratified, 341
quota, 336
sequential, 333
simple random, 338
snowball, 336
stratified, 340
systematic, 338
sample mean, 430
vs. population mean, 353 sample size,
determining, 357–358
with estimating, 358–363 other approaches to determining,
364–368
using anticipated analyses, 366 using research budget, 365 using historical evidence, 367
sample standard deviation, 430 sample survey, 115
sample types, combining, 343–344 sampling, 46–47
and data collection, 325
sampling control, 200, 203, 204, 210,
213, 217
sampling distribution, basics of, 351–355
sampling error, 330, 375
sampling frame, 39, 331
identifying, 331–332
sampling interval, 339
sampling plan, 69
developing, 326–344 sampling procedure, selecting a,
332–333
Samuelson Research Firm, 281 Sanders, Nicola, 135
satisfaction, 182 scale(s),
considerations in designing, 275–279
determining type to use, 279 interpreting rating, 280–282 number of items in a, 276
scale positions, number of, 277 scanner, 165
SCANTRACK, 165
scatter diagram, 467
Schultz, Don, 226–227, 485
Sculley, John, 238
Sears, 10
secondary data, 38, 136–150
advantages of, 137–139
disadvantages of, 140
external, 143
internal, 143
problems of accuracy, 140 problems of fit, 140 published, 146, 147, 149
sources of, 146, 155–159
types of, 143–150 secondary data sources,
business information, 158
census data, 155
company information, 155
Index 593
economic censuses, 156–157 general economic and statistical
information, 158
indexes, 158
industry information, 155
market and consumer information, 157
specialized directories, 158
secondary source, 140
self-report, 267
self-report attitude scales, 267–275 semantic-differential scale, 271
senior analyst, 14
sentence completion, 99
sequential sample, 333 services, producers of, 9–10 Sharapova, Maria, 135
Shell E&P, 28
significance level, 437
Silver Dollar City, Inc. (SDC), 10, 11–12, 82, 256
Silver, Dr. Spencer, 58 simple random sample, 338 simple regression, 470
simulated test market (STM), 128 single-source data, 166
Skil Corporation, 145
slide presentation, tips for, 498 SmartBargains.com, 233, 234
snake diagram, 272
snowball sample, 336
Sonic Corp., 138
specialized directories, 158
Spectra Marketing, 145 speed and cost, 189 Spirig, Nicola, 135
split-ballot technique, 298
sponsor disguise, 391 stacked line chart, 503
Standard Industrial Classification (SIC), 161
standard test market, 124 standardized marketing information
services, 160–172
Stapel scale, 273
Staples.com, 233, 234
Starbucks, 122
Starch Ad Readership, 170 statistic, 330
statistical significance, 455 issues in interpreting, 438
statistician/data processing specialist, 14
statistics vs. parameters, 328
Stillwater Domestic Violence Services, Inc., 67
STM, see simulated test market store audits, 164
storytelling, 99
strategy-oriented decision problem, 61, 65
stratified sample, 340
stratum chart, 503
structure, 195
high, 195
low, 197 structured
communication, 195–197
observation, 225
Subaru, 201
summated-ratings scale, 270
Sunlight, 125
SurLaTable.com, 233, 234
survey length, 392
Survey Sampling International (SSI), 332
Suvak, Jack, 188
Synovate, 12, 110 systematic
error, 255
sample, 338 systems approach,
limitations of, 30
marketing intelligence, 21–23
T
tabulation and data processing, 47 Taco Bell, 124
Target Corp., 138, 139
target population, defining, 327–330 Target, 212
Target.com, 234
techniques, effectiveness of, 393 Technomic Inc., 138
Teen Research Unlimited, 236 telephone
interviews, 204
surveys, 386, 387
telescoping error, 293 television and radio, 167 Tenet Healthcare, 25
Tesco, 225, 228–230
test market,
best and worst, 126 comparing types of, 129 controlled, 126
simulated, 128
standard, 124
types of, 124
test marketing, 122
testing for statistical significance, 455 test-retest reliability, 258
thermometer scale, 268
Thomas, Brad, 11 Thompson, J. Walter, 96 3M Company, 58
TigerDirect.com, 233 time series analysis, 110 TiVo, 399
TNS Global, 135
TNS Media Intelligence, 167 TNS U.S., 12
total error, 383
total sampling elements (TSE), 339 Tower Hobbies, 267, 268
Toyota Motor Company, 57, 77
Toys-4-Kids, 170
Triarc Cos., 138
TrueActive Monitor, 237
24 Hour Fitness, 1
two-box technique, 432
two-way cross tabulation, 451 Tyson Foods, Inc., 251
U
U.S. Census Bureau, 137, 141, 148, 161, 164, 327, 344
U.S. Postal Service, 282 undisguised
communication, 198–200
observation, 232
Unilever, 8
United Way, 67
Universal Product Code (UPC), 165, 166
unplanned change vs. planned change, 57
unstated alternative, 303 unstructured
communication, 195–197
observation, 230
utility approach, 48
V
validity, 257
construct, 260
content, 259
external, 120
internal, 119
predictive, 259
validity and reliability, assessment of, 257–261
validity of measures, establishing, 253–257
value perceptions, 182 Van Unnik, Arjan, 28
variables, adding to an analysis, 459–460
variance, estimating, 360
Vars, Fred, 29
versatility, 187
Vinson, Barbara, 138, 139
VirTra Systems, 234
VISA, 61, 62–64
voice-pitch analysis, 239
Volvo, 185
W
Wal-Mart Stores Inc., 5, 24, 138, 139,
182, 230, 238, 483
Walmart.com, 234
Wanamaker, John, 121
Warner, 8
594 Index
Web analytics, 186
WebTrends, 170
Wendy’s International Inc., 138, 139
Westat Inc., 12
WiedenþKennedy (WþK), 135
Wikipedia, 171
word association, 98
writing standards, 486–490
X
Xerox, 94
Y
Yahoo!, 127, 170, 171
Yoplait, 87
YouTube, 135, 171
Z
Zapp, John, 57
Zollo, Peter, 236
Zoomerang, 116, 214
z-test for comparing sample mean against a standard, 442
proportion against standard, 441
