For Zyn Camus Only

e-collaborative_networks.pdf

Home >Human Resource Management homework help >For Zyn Camus Only

ISSN 0885-3134 / 2009 $9.50 + 0.00. DOI 10.2753/PSS0885-3134290202

In the globalized business environment, the Internet is chang- ing the way fi rms do business and, as a result, organizations are introducing more products at faster rates, with shorter life cycles (Rackham and De Vincentis 1999). To remain competi- tive, strategic alliances are increasingly important (Day 2000) and are moving to virtual means of communication.

This study focuses on a fi rm that has close, long-term alli- ances in a three-tiered value chain. We use the term network to describe the formal relationships among fi rms in the value chain. We examine how value-chain members communicate at a group level, via Internet-based collaboration (e.g., ongo- ing communications among all members of the value chain). Internet-based collaboration (hereafter, e-collaboration) refers to business-to-business (B2B) interactions supported by the Internet. To study e-collaboration, the researchers gained ac- cess to a technology fi rm that specializes in building Internet- based networks. The task facing customer account managers (CAMs) who work for the technology fi rm is to sell, imple- ment, and manage e-collaborative environments.

The sales team, especially the CAM, takes the lead in continually improving the collaborative software platform. As the market environment changes, with a changing mix of competitors and economic conditions, the client becomes aware of the need for more information and improved decision criteria. Collaborative software has the potential to contribute on both of these dimensions.

The information technology fi rm in this study designs, implements, and maintains software for the client, and selects components of that software from various vendors. Members of the sales team are certifi ed by vendor fi rms to implement the vendor software (e.g., Oracle and SAP software). It is incumbent upon the CAM to convince the vendors to con- tinually modify their offerings. In the case of a vendor such as Oracle, its collaborative software is positioned as an alterna- tive to the market leaders—IBM and Microsoft. Oracle has recently revised and renamed its collaborative software and now markets it under the name of “Beehive.” While Beehive is being launched and modifi ed, there is no better time for the technology fi rm under study to suggest modifi cations that meet clients’ anticipated future needs. For instance, this could provide Oracle with a competitive advantage over IBM’s Lotus Domino offering and Microsoft’s Groove.

The differences between e-collaboration and traditional face-to-face collaboration lead to an important question that we address in this study: “How does communication software infl uence e-collaboration?” To address this question, we em- ploy a case study method to investigate one globally operative, U.S.-based technology fi rm. We selected this fi rm as its core

E-COLLABORATIVE NETWORKS: A CASE STUDY ON THE NEW ROLE OF THE SALES FORCE

Candice R. Hollenbeck, George M. Zinkhan, Warren French, and Ji Hee Song

Internet-based developments are generating opportunities for enhancing business-to-business operations. One approach involves the adoption of e-collaborative networks, which have the potential to strengthen communications between the members of a value-chain network. An effective communication interface within the value chain is central to the client’s productivity, and the sales force plays an important role in facilitating this process. Here, we examine an e-collaborative network built and sustained by one global, U.S.-based technology fi rm. Using an extended case study method, we iden- tify software capabilities that infl uence e-collaboration and discuss the mediating role of the sales team: (1) monitoring communal involvement, (2) identifying prospective e-collaborative fi rms, (3) inspiring a cooperative environment, and (4) fostering a sense of trust. We offer performance metrics and suggest implications for the sales force.

Candice R. Hollenbeck (Ph.D., University of Georgia), Visiting As- sistant Professor of Marketing, Terry College of Business, University of Georgia, [email protected].

George M. Zinkhan (Ph.D., University of Michigan), Coca-Cola Company Chair of Marketing, Terry College of Business, University of Georgia, [email protected].

Warren French (Ph.D., Penn State University), Cousins Professor of Ethics, Terry College of Business, University of Georgia, wfrench@ terry.uga.edu.

Ji Hee Song (Ph.D., University of Georgia), Assistant Professor of Marketing, College of Business and Economics, University of Seoul, [email protected].

The fourth author acknowledges and is thankful for the 2007 sum- mer research support of the College of Business and Economics, Towson University.

126 Journal of Personal Selling & Sales Management

business is establishing e-collaborative networks, and, within the fi rm, the CAMs play an important role in both selling and managing e-collaboration. Therefore, the purpose of this study is twofold: (1) to identify software capabilities that infl uence e-collaboration and (2) to discuss the role of the CAMs in enabling positive connections among members of an e-collaborative network.

THE BENEFITS OF E-COLLABORATION

E-collaboration is different from traditional face-to-face col- laboration in terms of (1) speed, (2) communication, and (3) the nature of network formation. Speed signifi cantly advances the abilities of vendor–client alliances in terms of effi ciency and effectiveness. Products are easily customized, transaction times are minimized, cycle times are reduced, and labor costs are lowered (Cannon and Homburg 2001; Corsten and Kumar 2005). In addition, Internet-based collaboration has the potential to deliver superior customer value by pro- viding a greater level of communication among both buyer and supplier organizations (Kennedy and Deeter-Schmelz 2001). According to Martin and Grbac (2003), e-collaboration can leverage a fi rm’s market orientation through improved vendor–client relationships, which, in turn, lead to heightened customer responsiveness.

Internet functions have potential to improve the nature of network formation, as members are closely connected through continuous dialogue (Watson, Zinkhan, and Pitt 2004). Research shows that e-collaboration can be used to create a stronger social atmosphere (when compared to traditional collaboration) that facilitates confi dence, information sharing, and other prosocial behaviors (Kennedy and Deeter-Schmelz 2001). Developing strong, e-collaboration with important accounts within a value-chain network strengthens member relationships and provides fi rms with superior fi nancial per- formance (Lambe, Spekman, and Hunt 2000; Morgan and Hunt 1999; Weitz and Bradford 1999).

The advantages of virtual, B2B interactions are explored in the extant literature, and we compile these benefi ts of e-collaboration into four overarching themes—productivity, cognitive culture, social connections, and agility. Harrison- Walker and Neeley (2004) note that more than half of all e-commerce occurs in B2B markets. According to Sharma (2002), organizations that take advantage of Internet effi cien- cies are outperforming organizations that utilize traditional modes of operation. Thus, the adoption rate of such effi ciencies is important to a fi rm’s overall productivity and competitive advantage in the marketplace. Shoemaker (2001) suggests that nonadopters of new technologies will be unable to compete. As such, a successful organization must utilize Internet capabilities to build vendor–client relationships. Long-term relationships, emphasizing personalized communication, are essential for

growth (Berry and Parasuraman 1991) and are among the most durable competitive advantages (Day 2000). Thus, the fi rst benefi t of e-collaboration is enhanced productivity.

The second benefi t of e-collaboration is a cognitive culture. As Kennedy and Deeter-Schmelz suggest, when considering the Internet and its role in B2B segments, “a distinction must be made between using the Internet as an information gather- ing tool versus its use as a transaction tool” (2001, p. 279). This study explores the Internet as a transactional tool, and the software capabilities that make transactions effective. When collaborative networks are virtual, both vendor and client or- ganizations are able to discuss business operations, regardless of geographical proximity. The transaction of information al- lows users to create a cognitive culture that enhances memory, judgment, and reasoning when making organizational deci- sions, as the network provides a methodology for organizing empirical, factual knowledge.

There are also social benefi ts associated with participation in e-collaborative networks (Schultz and Evans 2002). In utilizing e-collaborative networks, vendors and clients are able to con- nect with a group of like-minded individuals with common goals, and this is one step toward a “relationship orientation” (Day 2000) which provides a competitive advantage for fi rms. In addition, an e-collaborative network is an effective tool for vendors and clients as it continually streamlines the transactional process.

The fourth benefi t of e-collaborative networks is agility in responding to customer needs. Virtual networks enhance vendor–client relationships by providing a speedy, convenient means of communication among key customer accounts. Speedy, virtual feedback provides businesses with the op- portunity to react immediately to the needs and concerns of the marketplace, and it allows each member of the network participatory ownership in the production cycle. To excel in today’s technology-driven environment, fi rms must integrate formalized, customer relationship tools in order to adapt to the needs of different customers (Arnett and Badrinarayanan 2005).

METHOD

To identify software capabilities and to discuss the role of the CAMs in enabling positive connections among members of an e-collaborative network, we employ an “extended case study method” that utilizes “ethnographic techniques” (see Arnould, Price, and Otnes 1999; Burawoy 1991, 1998). Our interpretative approach allowed the researchers to “understand complex social processes” (Drumwright 1994; Miles and Huberman 1994) that take place in a virtual environment and to become “locally situated within the context” (Denzin and Mick 2001) of the e-collaborative network being studied. We chose a case study design because it provides a bounded

Spring 2009 127

framework for collecting data from one technology fi rm. Case study research provides an intensive, holistic description and analysis of a single phenomenon (Yin 2002).

Data collection followed qualitative techniques outlined by prior studies (Hudson and Ozanne 1988; Spiggle 1994): identifying multiple sources of evidence, creating a database of information, and maintaining a chain of evidence via an electronic journal. We employed an “emergent design” (see Arnould and Price 1993), in which “succeeding methodologi- cal steps are based on the steps already taken and imply the presence of a continuously interacting and interpreting inves- tigator” (Price, Arnould, and Tierney 1995, p. 88). We used three exploratory data collection methods—in-person depth interviews, group interviews, and extended observations. The use of multiple methods, multiple investigators, and multiple data sources strengthens the validity of our fi ndings.

The Case

Over a period of two years, 42 in-person interviews were conducted with experienced salespeople of an international, information technology fi rm. To ensure confi dentiality, the researchers agreed to withhold the name of the fi rm in all published materials. The fi rm under study has over 100,000 employees, operates in more than 100 countries, and is a leader in the information technology industry. Much of the fi rm’s business resides in creating and maintaining vendor– client e-collaborative networks. Vendor–client fi rms hire the information technology fi rm to improve the vendor–client network productivity.

CAMs play an important role in the information technol- ogy fi rm, as they facilitate vendor–client relations by introduc- ing innovative technological solutions to everyday business problems. CAMs become an innovative partner with client fi rms and are ready to help clients create value through innova-

tion, not only in products and services, but in the relational aspects of their business. For instance, the technology fi rm is hired by a network (i.e., a group of companies with long-term alliances) to develop innovative, technological solutions to increase productivity between the client and vendors in the network. Each company pays a portion of the total consulta- tion fee which is provided to the technology fi rm. CAMs, who represent the technology fi rm, are not only involved in the start-up of the network but are also involved in the long-term functioning of the e-collaborative network. CAMs and the sales team (i.e., the information technology specialists working under the customer account managers) provide consulting, delivery expertise, advanced technologies and accelerators in solution design, development, and integration. These services are designed to address vendor–client issues with business outcomes that benefi t the entire e-collaborative network.

In-Depth Interviews

The informants were recruited using a purposive sampling design (Miles and Huberman 1994). The selection criteria con- sisted of sales team members who have (1) a minimum of fi ve years sales experience, (2) participate regularly in Internet-based collaboration, and (3) have fi rsthand knowledge of vendor– client “e-collaborative” relationships. During the interviews, informants conveyed the details of their role and involvement with e-collaborative networks. Informants were asked open- ended questions regarding their experiences and probed to fully understand concepts, behaviors, or ideas. An interview guide was used by the researchers to provide a semistructured format during the one-on-one sessions (see Table 1).

A range of informants took part in our study, represent- ing a balance of both males and females with ages ranging from 28 to 53. To ensure confi dentiality, the fi rm’s name and informants’ names are not disclosed. All informants are

Table 1 Interview Guide for In-Depth Interviews

Open-Ended Questions

1 Please describe your role as a salesperson within your organization. 2 Explain e-collaboration and how it works. 3 What are the key features of e-collaboration? 4 Think of an e-collaborative network that you are intimately involved with and tell me about the members of that network. 5 Explain how network members are involved in e-collaboration. 6 What specifi c role(s) do you, as a salesperson, play within e-collaborative networks? 7 What software capabilities are necessary to make e-collaboration successful? 8 Which software features are most important in e-collaboration? 9 Think of a software capability that you rely on and tell me a recent story about how that specifi c capability made you feel successful. 10 Think of software that failed you recently and explain how you managed in light of the technical diffi culty. 11 Describe how e-collaboration advances certain processes in the network. 12 Explain how e-collaboration has changed the way businesses function. 13 In your opinion, how will e-collaborative networks shape the future?

128 Journal of Personal Selling & Sales Management

assigned a number and a letter of the alphabet according to their time zone (e.g., E = EST, C = CST, M = MST, P = PST, A = AKST, H = HAST). In the fi ndings section, informants are identifi ed fi rst by time zone and interview number; second, by their sex; and third, by their age. Interviews, lasting anywhere from 60 to 90 minutes in length, were audiotaped and tran- scribed verbatim. For reliability and validity, three informants reviewed a copy of our fi ndings to verify the analysis. These informants corroborated our analysis (specifi cally Tables 2–4 and Figure 1), and no contradictory data emerged.

Group Interview

Once preliminary fi ndings were reviewed by three informants, a group interview was conducted by the fi rst author to extend our “situational knowledge” (Burawoy 1998) by providing a group-driven discussion of sales team activities. A depart- ment consisting of 12 salespeople participated in the group interview. The group provided insights in how CAMs work with the sales team in selling, implementing, and managing e-collaborative environments.

The session began with “word associations” and “mental mapping exercises” (see Mariampolski 2001), which helped the researcher understand the role of the sales team in managing e-collaborative networks. The group discussion concluded with characteristics of successful e-collaborative networks and a discussion of industries that would benefi t from e-collaboration. The group session lasted approximately 90 minutes and was audiotaped and transcribed.

Extended Observations of an E-Collaborative Network

“Extended observations” allowed the four researchers to sys- tematically record virtual interactions and behaviors in online environments (see Burawoy 1998; Woodside and Samuel 1981). The researchers spent approximately 15 hours over the course of four months recording observations. Observations of vendor–client interactions in e-collaborative networks pro- vided confi rmatory data and deeper insights into communal behaviors. Observations followed a netnographic approach as outlined by Kozinets (2002). The researchers observed online interactions to experience the culture of the network from an insider’s point of view. The researchers took notes as a means of systematically recording observations. Observations were used to explore the role of the sales force with regard to vendor– client interactions, with our emphasis on reaching an in-depth understanding of the virtual context (Carson et al. 2002).

Analysis

For data analysis, we used a “constant comparative method” to create categories of information by likening individual incidents (Spiggle 1994; Strauss and Corbin 1998). First, we

identifi ed theoretical propositions premised upon the extant literature. Next, we aggregated the data (e.g., interview tran- scripts, observational notes) and then condensed participants’ interviews, using the constant comparative method to interpret common patterns and identify themes (Strauss and Corbin 1998). Finally, the authors compared emergent themes with preexisting theory in establishing our fi ndings.

FINDINGS

Our literature review notes four important benefits of e-collaborative networks—productivity, cognitive culture, social connections, and agility. Based on our fi ndings, Figure 1 illustrates how the benefi ts of e-collaborative networks can be maximized.

Software

Data analysis reveals four software capabilities that facilitate effective e-collaboration—navigational structure, customiza- tion and fl exibility, interactivity features, and structural as- surance cues. These four software capabilities enable balanced reciprocity, group effi cacy, a sense of community, and trust sentiments. Table 2 highlights these fi ndings.

As illustrated in Figure 1, the sales team plays a mediating role in maximizing the benefi ts of e-collaboration. Specifi - cally, we fi nd that the sales team enables positive connections by (1) monitoring communal involvement, (2) identifying prospective e-collaborative fi rms, (3) inspiring a cooperative environment, and (4) fostering a sense of trust.

Monitoring Communal Involvement

Once a collaborative network is established, it must be man- aged effectively in order to enhance productivity. This is the area where the sales team is vital to the network’s longevity and usefulness. In our study, the information technology fi rm’s sales team manages the network. If one of the other value- chain members managed the network, then that individual may be tempted to tailor the network for self-interest, rather than considering what is best for the group. The sales team represents a neutral source for monitoring and managing communal involvement. Effective management improves vendor–client experiences and engages their interest to such an extent that they will be motivated to be an active part of the community.

As a salesperson, I try to engage members of the network in ongoing communications. If I fi nd one fi rm to be particu- larly uninterested in the Web site or lacking confi dence in its capabilities, I personally get involved and I emphasize the benefi ts of e-collaboration. I am usually able to win over those fi rms who may have initial reservations about the Web site’s capabilities. (P2, F, 36)

Spring 2009 129

Table 2 Software Capabilities that Maximize the Benefi ts of E-Collaboration

Capability 1 A Navigational Structure That Supports Reciprocity

Description Members of a network who are involved in an exchange fulfi ll the expectations of reciprocity through continuous e-collaboration, thus creating balanced reciprocity (e.g., something is given in return for something received).

Examples Navigational structures include various elements such as links, layout, and a search function that foster continuous e-collaboration. Examples of reciprocity include revealing the selling fi rm’s cost structure in response to the buying fi rm’s revealing which competitors are being seriously considered.

Interview Illustrations RFPs are posted online and all communication is through the Internet . . . this really streamlines the process for our sales management team. The sales team is able to make clients feel like they are part of the co- creation process from the very beginning. . . . The Web makes response times quick and this helps facilitate a team atmosphere. Speedy responses are important for the network to maintain good communication (E12, M, 36).

When I need to get in touch with someone in the network, I just look up their contact information on the Web site. I always look there fi rst because it is easy and convenient and the links for contact information are clearly identifi ed (C5, F, 32).

Capability 2 Customization and Flexibility That Enable Group Effi cacy

Description Customization and fl exibility refer to a fi rm’s ability to defi ne its own services more clearly and to deliver services to other members in the network in a manner that suits the specialized needs of each fi rm in the network.

Examples Customization and fl exibility enhance group effi cacy by allowing each member of the network to tailor the Web site to its own business model (e.g., personalization features).

Interview Illustrations Different companies have different value chain needs depending on the stability or volatility of their product. Therefore, the Web site needs to be capable of delivering to those value-chain variables. If the Web design is fl exible, then any member of the value chain has the freedom to customize its use of the portal so that the needed and expected results are seen. The fl exibility and adaptability of the Web design also make the group more cohesive (E30, M, 29).

Being able to customize certain features on the Web site is important in connecting the group. There has to be a level of commitment on behalf of each member so that all value-chain functions are streamlined through the portal. As commitment is developed, there will be a deeper, more complete usage of the Web site. The more you can customize, the more the Web site is tailored to your business model, and this makes it easier for each member of the value chain to transact business (E3, F, 48).

Capability 3 Interactivity Features That Provide a Sense of Community

Description Interactivity is defi ned as the extent to which network members respond to or are willing to facilitate each other’s communication goals.

Examples The Web design needs to provide ways to increase two-way communication or stimulate network members’ engagement with the site (e.g., chat rooms, instant messaging, discussion forums, webcasts, videoconferencing).

Interview Illustrations The Web site becomes a tool that value-chain members use to interact with each other. You’ve got to become connected and committed to the process and the result is that you will become more reliant on the Web site for everyday business functions (E19, F, 28).

The portal has the same effect as a conference call or a webcast in that a number of team members are collaborating. But the advantage of the Web site is that it gives each member a chance to interact with each other as opposed to just being the leader of the webcast or conference call. It also offers an inexpensive way to meet on a regular basis without having to physically fl y people around the world (C10, M, 44).

Capability 4 Structural Assurance Cues That Facilitate Trust

Description Structural assurance refers to assessment of success due to safety nets such as legal recourse, guarantees, and regulations.

(continues)

130 Journal of Personal Selling & Sales Management

To maintain and expand an e-collaborative community, new offerings and linkages must continually be evaluated and added when benefi cial. According to salesperson P2, com- munal interaction is important for individual involvement and even more so for the broader integration effort. In other words, to maintain a strong client base, the sales force must regularly monitor the way clients are doing business and then apply expertise to improve network relations.

The fi rm under study has relied on the concept of “coaching groups” to involve vendors and clients in the use of collabora- tive software, as expressed by one informant:

Coaching groups will at times act as a sales force, by conduct- ing meeting with clients to enumerate the cost savings and other benefi ts of the collaborative network, as well as which area can be functioned together to best fi t their business models. (E15, M, 28)

The sales team in our study monitored communal involve- ment by identifying customer interests and integrating those interests so that network members are motivated to become

part of the e-collaborative community. Coaching groups rep- resent just one example of how the sales team accomplished this task.

Identifying Prospective E-Collaborative Firms

The salespeople in our study use business intelligence to defi ne and implement effective e-collaborative networks. This means that salespeople must know which businesses are most likely to fi nd advantages in joining e-collaborative networks. Organiza- tions and salespeople who are able to understand and adapt to e-collaborative technological innovations will likely achieve productive gains and improve customer satisfaction (Good and Schultz 1997; Jaworski and Kohli 1993; Peppers and Rogers 1998). According to salesperson E4, “before engaging fi rms in the network mind-set, the salesperson must determine whether potential fi rms are fi t for the network strategy.” In other words, salespeople must determine if potential network members are conducive to e-collaborative innovations. Table 3 outlines industry characteristics that are more favorable to reciprocal

Table 2 Continued

Examples Network members must believe that protective structures are in place (e.g., security, privacy statement, contact number of network moderator, reliability marks of hardware and software tools used for the network).

Interview Illustrations Simple privacy statements and Web site moderators are important tactics used to increase trust. Value-chain members want to know that their information is safe and secure. When dealing in a virtual environment, fi rms want to be assured that their information is treated with the utmost care and protection, and trust in the Web site is an important part of an effectively functioning network (E10, M, 50).

Businesses need to have full confi dence in the functioning of the Web site before they are willing to share sensitive data through the Web site. Businesses need to be able to use Web sites easily and they want to know that their information is secure. Our network provides the security that information is kept in-house where it is needed. With the high number of hoaxes and scams related to predators penetrating Internet Web sites, safety features give value-chain members the confi dence that their data are secure (P22, F, 31).

Table 3 Favorable and Unfavorable Characteristics for Reciprocal Strategies

Favorable Unfavorable

Extremely competitive industries Industries with little competition Developing industries Established, bureaucratic industries Well-organized industries that rely on good relationships with Rigorous regulation standards their suppliers Industries where operations span multiple geographies Products with standard features and standard offerings Industries requiring that customers perceive varying brand Products with low fl exibility positions across business units Industries requiring varying customer segments and product mixes Products with low customer interactivity Industries using “just-in-time” operating strategies Centralized operational decision making Industries with time-sensitive product launches Price-sensitive industries

Note: Firm characteristics are based on informants’ descriptions during the group interview.

Spring 2009 131

strategies used in e-collaboration. The fi rm characteristics in Table 3 are based on informants’ descriptions of favorable and unfavorable environments during a group interview with 12 salespeople.

Favorable conditions include industries that are competi- tive, have multiple points of contact, require varying customer segments and product mixes, and are sensitive to changes in the marketplace. Unfavorable conditions include industries with little competition, established bureaucracies, and low changeability. In addition, during the group interview, in- formants discussed how two industries that the information technology fi rm is currently targeting could benefi t from e-collaborative software. Table 4 lists the industries and the associated benefi ts.

Inspiring a Cooperative Environment

Our fi ndings show that the sales force is responsible for edu- cating and motivating both vendor and client organizations to take advantage of strategic partnerships. For instance, our informants suggest that vendor–client partnerships enable the customization of products and services by blurring the boundaries of power and infl uence. Because interactions take place in a virtual setting, the infl uence of an individual’s race, sex, or position is given less attention. According to salesperson E14, “the Internet makes everything an even playing ground where we are all working together to accomplish tasks and negligible things such as someone’s title are not as powerful in a virtual setting.” A cooperative environment is one of several salient characteristics of effective e-collaboration. Salesperson

E14 shares her experience with an e-collaborative network and highlights the interconnected qualities of virtual networks.

People can come together regardless of their biases. This is why it is an important tool in business. It bridges the gap between potential competitors by allowing them to help each other accomplish their own organizational goals. (E14, F, 28)

Similarly, salesperson A1 emphasizes that the sales force plays a central role in managing the collaborative environment and in providing direction for the group.

Often the sales force will be responsible for seeding discus- sions to help draw out personal narrative. Successful com- munities always seem to have someone who leads [typically a salesperson], perhaps by maintaining a sense of direction for the group or defi ning the environment . . . and a cooperative environment is the primary goal. (A1, M, 42)

As suggested by salespeople E14 and A1, the sales team plays an important role in facilitating a cooperative e-collaborative environment. E-collaborative technologies offer salespeople the ability to bring vendor and client organizations together through common goals.

Fostering a Sense of Trust

We found that the salespeople foster a sense of trust by two methods: (1) being technologically savvy and (2) being per- sonally involved in every aspect of e-collaboration. Because the sales force is technologically adept, the information tech- nology fi rm in our study is able to capitalize on marketplace

Table 4 Industry Benefi ts from E-Collaborative Software

Industry Examples Benefi ts

Entertainment Industry Cost Effective • The members of the community can buy and sell scripts/stories/manuscripts through this service. Information Sharing • Press releases can be discussed with individuals, lawyers, etc. • Different writers/artists can share information • Link audience feedback/suggestions from the Web site to the community for use by producers and writers Pharmaceutical Industry Cost Effective • BETA meetings for products can be done remotely • Focus group meetings for a drug/product Information Sharing • Labs can share chemical compositions/formulas, provide help, discuss FDA issues globally • Genetic complex bio-analysis, DNA diagrams, and research analysis downloadable to individual personal computer to be shared and discussed with other scientists

Note: Industry examples and associated benefi ts are based on informants’ descriptions during the group interview.

132 Journal of Personal Selling & Sales Management

opportunities by positioning its salespeople as network fa- cilitators. When salespeople fail to adopt new technologies, studies show that companies receive nominal returns on their technological investments (see Jones, Sundaram, and Wynne 2002; Venkatesh and Davis 2000), and this outcome is, in part, due to the underutilization of the sales force.

The salespeople in our study are involved in all aspects of e-collaboration from start-up to maintenance. As such, the salespeople are most adept at defi ning successful e-collaborative networks. Based on our group interview data, we developed a table that illustrates the salient characteristics of effective e-collaborative networks. Table 5 outlines key phrases and statements used by the informants in our study when asked to defi ne “successful” e-collaborative networks during our group interview with 12 salespeople. Informants’ comments about successful networks revolved around issues of trust. Success- ful network characteristics that embody the foundations of trust are summarized along with related software capabilities (see Table 5).

A major impediment to trust, as identifi ed by our infor- mants, is a legal barrier. Specifi cally, there is a question about who owns the ideas generated by members of the value chain in the course of their e-collaborative efforts. This impediment must be overcome if e-collaboration is to be successful and profi table. In the fi rm that we study, the sales team creates a fl exible agreement that is tailored to each situation. In other words, the conditions of ownership vary, depending on the specifi c circumstance of each value-chain member. Factors af- fecting the agreement include who creates, fl eshes out, models (e.g., builds software for), implements, and profi ts from the innovative idea.

PERFORMANCE METRICS

Here, we discuss how the sales team is evaluated in terms of performance. The fi rm in this study measures the sales team’s success according to the network’s success. Variables used to determine the success of the network, and thus the

Figure 1 Maximizing the Benefi ts of E-Collaboration

Notes: A and C are derived from the fi ndings; B is derived from the literature.

Spring 2009 133

T a b

le 5

C h

a ra

ct e ri

st ic

s o

f S

u cc

e ss

fu l E

-C o

ll a b

o ra

ti ve

N e tw

o rk

o rr

e sp

o n

d in

g S

o ft

w a re

C a p

a b

il it

ie s

te ra

ct iv

it y

S tr

u ct

u ra

N a vi

g a ti

o n

a l

C u

st o

m iz

a ti

o n

, a n

d a

ss u

ra n

ce C

h a ra

ct e ri

st ic

s o

f S

u cc

e ss

fu l E

-C o

ll a b

o ra

ti ve

N e tw

o rk

S tr

u ct

u re

a n

F le

x ib

il it

y, a

n d

e n

se o

f C

u e s

a n

d a s

D e fi

n e d

b y

In fo

rm a n

ts D

u ri

n g t

h e G

ro u

p I

n te

rv ie

R e ci

p ro

ci ty

ro u

p E

ffi c

a cy

o m

m u

n it

y T

ru st

B ui

ld in

g co

m m

un it y

is t

he u

nd er

pi nn

in g

o f th

e W

eb d

es ig

n V

T he

f o cu

s is

o n

cu st

o m

er c

o m

m o na

lit ie

H ig

h le

ve ls

o f tr

us t

am o ng

m em

be rs

o f th

e co

lla bo

ra ti ve

n et

w o rk

(t o a

llo w

f o r

pe rs

o na

l s ha

ri ng

) H

ig h

le ve

ls o

f re

sp ec

t fo

r m

em be

rs o

f th

e co

lla bo

ra ti ve

n et

w o rk

V Sa

le s

fo rc

e as

se ss

es c

o lla

bo ra

ti ve

n et

w o rk

p o te

nt ia

l b as

ed o

is ti ng

k no

w le

dg e

o f cu

st o m

er s

Sa le

s fo

rc e

co lla

bo ra

te s

w it h

cu st

o m

er s

to d

es ig

n W

eb o

ffe ri

ng s

o fe

ss io

na l i

nc en

ti ve

s ar

e ev

id en

t fo

r ve

nd o r

an d

cl ie

nt m

em be

C o ns

ta nt

d ia

lo gu

e am

o ng

v en

do r

cl ie

nt m

em be

le f o rc

e in

ve st

s in

r el

ia bl

e ha

rd w

ar e

an d

so ft

w ar

e to

o ls

Sa le

s fo

rc e

ha s

a de

pe nd

ab le

t ec

hn ic

al s

up po

rt s

ta ff

G ua

ra nt

ee d

re lia

bl e

te ch

no lo

O rg

an iz

at io

na l i

nc en

ti ve

s fo

r m

o ti va

ti ng

n et

w o rk

m em

be rs

is cu

ss io

ns in

te gr

at e

re al

-w o rl

d ap

pl ic

at io

le sp

eo pl

e co

m m

it t

o r

es po

ns iv

e fe

ed ba

ck r

eg ar

di ng

c us

to m

nc er

ns o

r qu

es ti o ns

Sa le

sp eo

pl e

co m

m it t

o c

o nt

in uo

us im

pr o ve

m en

t ba

se d

o n

cu st

o m

er f ee

db ac

N ot

es : C

h ar

ac te

ri st

ic s

ar e

li st

ed i

n o

rd er

o f

m os

t fr

eq u

en tl

y d

is cu

ss ed

b y

in fo

rm an

ts . “

V ”

d en

ot es

t h

at t

h e

p ar

ti cu

la r

ch ar

ac te

ri st

ic o

n t

h e

le ft

i s

as so

ci at

ed w

it h

t h

e co

rr es

p on

d in

g so

ft w

ar e

ca p

ab ili

ty .

134 Journal of Personal Selling & Sales Management

performance of the sales team include (1) level of interactions, (2) streamlined activities, (3) fi nancial rewards, and (4) nonfi - nancial rewards. First, according to our informants, successful networks are characterized by consistent interaction among members and regular sharing of information. But measures of success from a business perspective have to be based on more than counts of interaction. In the fi rm that we study, CAMs conducted performance surveys and ensured that hardware and software applications were functioning properly. Develop- ing network performance surveys and distributing them on a regular basis measured how well the community accepted the e-collaborative environment and identifi ed areas for im- provement. Other elements measured were money spent on hardware and software upgrades, funds for sales and advertis- ing, and working capital to keep the network functioning at a level that exceeds demand.

Second, performance surveys were used to determine if daily activities were streamlined for value-chain members. For example, do value-chain members experience reduced transaction time through direct order placement, schedul- ing, billing, and payment? Are value-chain members able to reduce inventory level through coordinated planning (which correspondingly reduces operational costs)? Do value-chain members have a reduced payment collection period?

Third, the salespeople in our study play an important role in conveying the fi nancial rewards to prospective e-collaborative fi rms. In particular, the salespeople communicate the quarterly and annual fi nancial rewards to fi rms in the network using return on investment (ROI), residual income, and net present value (NPV) measures. ROI is a key indicator of performance. For instance, informants use ROI fi gures to provide a frac- tional measure of the producing power of invested capital. This fi gure can be benchmarked in comparison to industry norms. According to M20, residual factors used by the sales force include a measure of the “leftovers” after the fi rm has earned what is considered an acceptable rate on investment in the e-collaborative network. NPV is another key indicator of performance, and it is discounted at an appropriate annual rate of return. For instance, fi rms estimate both the costs of initial investment and the annual maintenance fees related to the network. Using NPV, salespeople are able to determine annual revenues that emanate from e-collaborative networks (and their associated activities).

In addition, the sales force uses annual revenues to demon- strate the network’s success. Annual revenues can be estimated via market research or from historical information from com- parable companies (benchmarking). By performing conjoint pricing, a reasonable estimate of per-transaction price in the prediction of revenues can be calculated. Maintenance costs can be derived from historical numbers of other companies, from internal estimates of equipment and labor requirement, or from bidders’ outsourcing partners. Acceptable rates of

return are customarily available from internal fi nancial depart- ments, or from industry data on historical rates of return of similar investments by other companies. According to E33, “involving the sales team in the cost–benefi t analysis process is important” as fi rms make decisions about the usefulness of e-collaborative networks. CAMs play an important role in determining the right balance of network capabilities and the associated costs. For example, salesperson P11 states that insider knowledge is critical when making such decisions:

The sales team helps in planning specifi c spending on an individual account basis and provides input as to the kinds of offerings that are good fi ts for each account. . . . Sometimes the amount of savings we are accruing speaks louder than anything else. . . . But the sales team typically has some type of insider knowledge and this helps when making decisions. Additional tidbits of insider information become really crucial when making fi nancial decisions and when deciding which rewards are of interest to fi rms. (P11, M, 40)

As conveyed by salesperson P11, the sales force plays a mediat- ing role in decision making and is responsible for conveying types of rewards. According to salesperson P11, the “sales team typically has some type of insider knowledge.” When salespeople have insider knowledge, they are able to deter- mine which fi nancial measures of success are most relevant to network members.

Fourth, nonfi nancial means of evaluating success include traffi c measures (e.g., tracking the number of visits to the network); customer satisfaction measures of the Web site; competitors’ reactions (e.g., competitor attempts to imitate); and measurement of vendor–client feedback, morale, and turnover. With respect to these nonfi nancial measures, the sales force can explain why network traffi c is down or why customers are not satisfi ed. For instance, traffi c measures could be down due to navigational diffi culties. A problem of this nature could be solved through technical improvements. Thus, the performance measures discussed provide a means for evaluating the sales team and the network’s success. Moreover, the performance measures identify areas for improvement.

DISCUSSION

The salespeople in our study exhibited leadership traits, or- chestrated interactive communication, and exuded a positive attitude with respect to their e-collaborative networks. Strong relationships facilitated by the sales team lead to improved communications which, in turn, aid in managing change and meeting the demands of the marketplace (Arnett, Macy, and Wilcox 2005; Weitz and Bradford 1999). Leadership roles that depict salespeople as “orchestrators” are noted in the literature (see Jones et al. 2005; Weitz and Bradford 1999), and this study builds on the extant literature by providing examples

Spring 2009 135

that demonstrate the “orchestrative” role, which we label as a “mediating” role, that the sales team plays in establishing and maintaining effective e-collaborative networks.

Specifi cally, our study fi nds that the sales team created positive connections in e-collaborative networks through (1) monitoring communal involvement, (2) identifying prospective e-collaborative fi rms, (3) inspiring a cooperative environment, and (4) fostering a sense of trust. The salespeople in our study are involved in every aspect of e-collaboration and, as such, they serve as the experts when determining the successfulness and effectiveness of e-collaborative strategies.

The level of performance of the sales team in our study is determined by the success of the e-collaborative network. Variables used to measure success include (1) level of interac- tions, (2) streamlined activities, (3) fi nancial rewards, and (4) nonfi nancial rewards. The sales team plays a mediating role by determining the right balance of costs and the associated benefi ts for value-chain members. Likewise, the sales team plays an important role in communicating both the fi nancial and nonfi nancial rewards to value-chain members.

SALES FORCE IMPLICATIONS

There are several important implications for salespeople. First, salespeople are able to use their market knowledge to improve e-collaboration. As noted by Pass, Evans, and Schlacter (2004), salespeople are used frequently by organizations as a source for market information to improve overall communication strategies. In our case study, the sales team is central to the functioning of e-collaborative networks as they are able to gather market intelligence, coordinate communication among network partners, and stimulate information sharing. Using market knowledge and customer data, the sales force stimulates communal interaction by connecting vendor–client network members with common goals.

Second, salespeople can look for new ways to improve software capabilities. One area could include creative incen- tives that motivate network members to participate in regular communications. Examples of incentives include extrinsic motivation (e.g., fi nancial reward) and intrinsic motivation (e.g., peer-rating system: a member’s message is rated by other members based on usefulness of the message). Another area for improving the transactional function of collaborative software involves creative ways to stimulate virtual value-chain partici- pation. The technology fi rm in this study uses data streams accumulated through virtual participation to enhance a fi rm’s appeal, and this application enables the fi rm to tailor offerings to meet the needs of existing and potential clients. As a result, productivity is enhanced through increased collaboration and through reduced costs. The ability to optimize the effectiveness of data through virtual participation strengthens partnerships with complimentary service providers.

Third, the more technological skills that salespeople can obtain, the more valuable they become to organizations. Organizations develop customized technological solutions to empower the sales force and to defi ne their mix of product offerings, distribution channels, and communication strate- gies. That is, organizations and network members are seeking “tailor-made” solutions that can improve effi ciency, produc- tivity, and market share. As clients demand more customized information and services, the sales force needs to understand and adopt emerging technologies, such as e-collaborative net- works. As a result, salespeople must take on mediating roles in order to facilitate a virtual, communal environment.

REFERENCES

Arnett, Dennis B., and Vishag Badrinarayanan (2005), “En- hancing Customer-Needs-Driven CRM Strategies: Core Selling Teams, Knowledge Management Competence, and Relationship Marketing Competence,” Journal of Personal Selling & Sales Management, 25, 4 (Fall), 329–343.

———, Barry A. Macy, and James B. Wilcox (2005), “The Role of Core Selling Teams in Supplier–Buyer Relation- ships,” Journal of Personal Selling & Sales Management, 25, 1 (Winter), 27–42.

Arnould, Eric J., and Linda L. Price (1993), “River Magic: Ex- traordinary Experience and the Extended Service Encoun- ter,” Journal of Consumer Research, 20 (1), 24–45.

———, ———, and Cele Otnes (1999), “Making Magic Consumption,” Journal of Contemporary Ethnography, 28 (1), 33–68.

Berry, Leonard L., and A. Parasuraman (1991), Marketing Ser- vices: Competing Through Quality, New York: Free Press.

Burawoy, Michael (1991), Ethnography Unbound, Berkeley: University of California Press.

——— (1998), “The Extended Case Method,” Sociological Theory, 16 (1), 4–34.

Cannon, Joseph P., and Christian Homburg (2001), “Buyer– Supplier Relationships and Customer Firm Costs,” Journal of Marketing, 65 (1), 29–43.

Carson, David, Audrey Gilmore, Chad Perry, and Kjell Gron- haug (2002), Qualitative Marketing Research, Thousand Oaks, CA: Sage.

Corsten, Daniel, and Nirmalya Kumar (2005), “Do Suppliers Benefi t from Collaborative Relationships with Large Retail- ers? An Empirical Investigation of Effi cient Consumer Re- sponse Adoption,” Journal of Marketing, 69 (3), 80–94.

Day, George S. (2000), “Managing Market Relationships,” Jour- nal of the Academy of Marketing Science, 28 (1), 24–30.

Denzin, Norman K., and David Glen Mick (2001), “The Seventh Moment: Qualitative Inquiry and the Practices of a More Radical Consumer Research,” Journal of Consumer Research, 28 (2), 324–330.

Drumwright, Minette E. (1994), “Socially Responsible Organiza- tional Buying: Environmental Concern as a Noneconomic Buying Criterion,” Journal of Marketing, 58 (3), 1–19.

136 Journal of Personal Selling & Sales Management

Good, David J., and Roberta J. Schultz (1997), “Technological Teaming as a Marketing Strategy,” Industrial Marketing Management, 26 (5), 413–422.

Harrison-Walker, L. Jean, and Sue E. Neeley (2004), “Customer Relationship Building on the Internet in B2B Marketing: A Proposed Typology,” Journal of Marketing Theory & Practice, 12 (1), 19–35.

Hudson, Laurel Anderson, and Julie L. Ozanne (1988), “Alterna- tive Ways of Seeking Knowledge in Consumer Research,” Journal of Consumer Research, 14 (4), 508–521.

Jaworski, Bernard J., and Ajay K. Kohli (1993), “Market Orientation: Antecedents and Consequences,” Journal of Marketing, 57 (3), 53–70.

Jones, Eli, Suresh Sundaram, and Chin Wynne (2002), “Factors Leading to Sales Force Automation Use: A Longitudinal Analysis,” Journal of Personal Selling & Sales Management, 22, 3 (Summer), 145–156.

———, Steven P. Brown, Andris A. Zoltners, and Barton A. Weitz (2005), “The Changing Environment of Selling and Sales Management,” Journal of Personal Selling & Sales Management, 25, 2 (Spring), 105–111.

Kennedy, Karen Norman, and Dawn R. Deeter-Schmelz (2001), “Descriptive and Predictive Analyses of Industrial Buyers’ Use of Online Information for Purchasing,” Jour- nal of Personal Selling & Sales Management, 21, 4 (Fall), 279–290.

Kozinets, Robert V. (2002), “The Field Behind the Screen: Using Netnography for Marketing Research in Online Communi- ties,” Journal of Marketing Research, 39 (1), 61–72.

Lambe, C. Jay, Robert E. Spekman, and Shelby O. Hunt (2000), “Interimistic Relational Exchange: Conceptualization and Propositional Development,” Journal of the Academy of Marketing Science, 28 (2), 212–225.

Mariampolski, Hy (2001), Qualitative Market Research: A Com- prehensive Guide, Thousand Oaks, CA: Sage.

Martin, James H., and Bruno Grbac (2003), “Using Supply Chain Management to Leverage a Firm’s Market Orienta- tion,” Industrial Marketing Management, 32 (1), 25–38.

Miles, Mathew B., and Michael Huberman (1994), Qualitative Data Analysis: An Expanded Sourcebook, 2d ed., Thousand Oaks, CA: Sage.

Morgan, Robert M., and Shelby Hunt (1999), “Relationship- Based Competitive Advantage: The Role of Relationship Marketing in Marketing Strategy,” Journal of Business Research, 46 (3), 281–290.

Pass, Michael W., Kenneth R. Evans, and John L. Schlacter (2004), “Sales Force Involvement in CRM Information Sys- tems: Participation, Support, and Focus,” Journal of Personal Selling & Sales Management, 24, 3 (Summer), 229–234.

Peppers, Don, and Martha Rogers (1998), “Don’t Resist Mar- keting Automation,” Sales & Marketing Management, 150 (9), 32–34.

Price, Linda L., Eric J. Arnould, and Patrick Tierney (1995), “Going to Extremes: Managing Service Encounters and Assessing Provider Performance,” Journal of Marketing, 59 (2), 83–97.

Rackham, Neil, and John De Vincentis (1999), Rethinking the Sales Force, New York: McGraw-Hill.

Schultz, Roberta J., and Kenneth R. Evans (2002), “Strategic Collaborative Communication by Key Account Representa- tives,” Journal of Personal Selling & Sales Management, 22, 1 (Winter), 23–31.

Sharma, Arun (2002), “Trends in Internet-Based Business-to- Business Marketing,” Industrial Marketing Management, 31 (2), 77–84.

Shoemaker, Mary E. (2001), “A Framework for Examining IT- Enabled Market Relationships,” Journal of Personal Selling & Sales Management, 21, 2 (Spring), 177–185.

Spiggle, Susan (1994), “Analysis and Interpretation of Qualitative Data in Consumer Research,” Journal of Consumer Research, 21 (3), 491–503.

Strauss, Anselm C., and Juliet Corbin (1998), Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory, 2d ed., Thousand Oaks, CA: Sage.

Venkatesh, Viswanath, and Fred D. Davis (2000), “A Theoreti- cal Extension of the Technology Acceptance Model: Four Longitudinal Field Studies,” Management Science, 46 (2), 186–204.

Watson, Richard T., George M. Zinkhan, and Leyland F. Pitt (2004), “Object-Orientation: A Tool for Enterprise De- sign,” California Management Review, 46 (4), 89–110.

Weitz, Barton A., and Kevin D. Bradford (1999), “Personal Selling and Sales Management: A Relationship Marketing Perspective,” Journal of the Academy of Marketing Science, 27 (2), 241–254.

Woodside, Arch G., and David M. Samuel (1981), “Observa- tions of Centralized Corporate Procurement,” Industrial Marketing Management, 10 (3), 191–205.

Yin, Robert K. (2002), Case Study Research: Design and Methods, 3d ed., Thousand Oaks, CA: Sage.