Miss Hillary

JOURNAL OF BUSINESS LOGISTICS

Volume 30, Number 1 Table of Contents 2009

1 “Marketing/Logistics Relationships: Influence on Capabilities and Performance”

Patricia J. Daugherty, Haozhe Chen, Daniel D. Mattioda, and Scott J. Grawe

Effective marketing/logistics relationships can help to create, develop, and maintain critical

capabilities to support long-term firm success. Recent research focuses on two distinct

capabilities—information capabilities and firm-wide integration. Empirical results are provided

confirming the proposed relationship between marketing logistics relationship effectiveness and

the two capabilities. Further, the capabilities are shown to positively impact logistics performance.

Key Words: Firm-wide integration; Information capability; Logistics performance;

Marketing/Logistics relationships; Structural equation modeling

19 “Modeling Uncertain Forecast Accuracy in Supply Chains with Postponement”

Larry J. LeBlanc, James A. Hill, Jerry Harder, and Gregory W. Greenwell

We examine a situation where a manufacturer operates in a two-mode production environment.

The first mode could involve overseas vendors and manufacturing facilities. If additional units are

later required, the company must use its second mode—more expensive last-minute domestic

vendors and manufacturing sites. We develop a new methodology for analyzing the impact of

forecast accuracy on the decision to postpone production. We examine the interaction of forecast

accuracy, shortage vs. holding costs, transportation costs and the cost of postponing production in

the supply chain of a single product facing uncertain demand. Our model can be used to analyze

the cost of important changes, such as increasing forecast accuracy, reducing the cost of

backorders, lowering the cost of delaying production, or lowering transportation costs. Our model

allows a firm to understand its overall cost structure so that it can accurately evaluate the impact of

improved forecast accuracy and lowered costs in the context of postponement.

Key Words: Forecasting; Probabilistic models; Production planning; Supply chain management

33 “Product Returns Processing: An Examination of Practices of Manufacturers,

Wholesalers/Distributors, and Retailers”

James R. Stock and Jay P. Mulki

Few research studies have published specific empirical data regarding the reverse logistics

practices of companies. This multi-stage study employed interviews, site visits, and a mail survey

to collect responses from 230 members of the Warehousing Education and Research Council

(WERC) regarding their reverse logistics practices. Results suggest that in spite of the growing

importance of reverse logistics, few executives have product return processing as their primary

responsibility and often undertake this activity along with other job responsibilities. Most firms

handle the product returns process themselves and typically within the same facilities that handle

forward logistics. Returning items directly to stock, repackaging and returning to stock, and

selling as scrap, were the three top disposition options employed by firms. Results indicate that,

contrary to general understanding, the majority of retailers and wholesalers reported a recovery

rate of over 75% of product cost. Several hypotheses developed from the published literature on

reverse logistics were tested. In many instances, these hypotheses were formulated on anecdotal

information or single case studies and had not been empirically tested prior to this research being

conducted.

Key Words: Manufacturers; Product returns; Retailers; Reverse logistics; Wholesalers/Distributors

vii

JOURNAL OF BUSINESS LOGISTICS, Vol. 30, No. 1, 2009 33

PRODUCT RETURNS PROCESSING: AN EXAMINATION OF PRACTICES OF

MANUFACTURERS, WHOLESALERS/DISTRIBUTORS, AND RETAILERS

by

James R. Stock

University of South Florida

and

Jay P. Mulki

Northeastern University

INTRODUCTION

Processing product returns has become a critical activity for organizations in the as the volume of goods

flowing back through the supply chain rapidly increases (Guide et al. 2006). It has been reported that the value of

products being returned exceeds an estimated $100 billion per year and averages about 6 percent of sales (Guide et

al. 2006; Stock 2001). It is estimated that product returns could range from 15% for mass merchandisers to 35% for

e-commerce retailers (Gentry 1999). Product returns are part of reverse logistics which includes a combination of

other activities such as recycling, refurbishing, and repair, as well as waste disposal (Stock 2001). It is believed that

while product returns are known to account for a large proportion of reverse logistics activities, manufactures are

able to recover only a portion of the value of the returned products because of processing delays (Guide et al. 2006).

For more than two decades, practitioners and researchers have been concerned with issues relating to “product

returns” and “reverse logistics.” They have repeatedly advocated the need for more specific data, that is, empirical

research on the topics (e.g., product remanufacturing and refurbishing, product returns, environmental aspects of

packaging, product disposal, recycling, reusable containers, source reduction, life cycle analysis, product

stewardship, green marketing, sustainability). Organizations have also realized that a better understanding of product

returns and efficient management of reverse logistics can provide them with a competitive advantage. Sound

practices in product returns and reverse logistics can be a “win-win” situation benefiting both customers and the firm

(Stock 2004). When effectively handled, product return processes can help firms recover value. Furthermore, they

can aid in the development of customer return policies that can increase customer loyalty (Rogers et al. 2002) and

improve product sales (Mukhopadhyay and Setoputro 2005). Better understanding of issues related to product

returns can also help identify areas in manufacturing or marketing where corrective actions might be necessary. In

addition, with growing environmental concerns and legal regulations associated with green marketing and

sustainability, activities related to product disposal in reverse logistics can provide insights into strategies for

sustainable development (Srivastava and Srivastava 2006).

However, it is possible that some organizations still do not realize the critical nature of product returns as it

relates to profitability and customer service, nor the benefits associated with efficient product returns. Organizations

are more likely to perceive the product returns function as an additional cost to be incurred in their normal business

practices (Stock 2004). In view of this, there is a need to understand the place of product returns and reverse

logistics in an organization’s marketing mix strategy, and the level of importance they would assign to reverse

logistics as compared to traditional forward logistics.

Product return policies and processes differ by type of business. For example, manufacturers may want to define

return policies in stricter and narrower terms and may be concerned about the more liberal return policies of retailers

34 STOCK AND MULKI

(Gentry 1999). Firms also vary in whether or not they perform product returns processing in-house or outsource it to

a third-party. Outsourcing or partnering with others can be an attractive option to exploit benefits of economies of

scale if the firm’s product return volumes are low (Stock 1998). Often, firms specializing in handling product returns

are able to achieve economies of scale by combining volumes from multiple companies. Small individual firms see

outsourcing to these firms as an attractive option to lower costs associated with processing product returns.

An important component of the reverse logistics process is to accurately evaluate each product returned in order

to determine the most optimal disposition option. Typically, stations or physical locations are set up in the facility

handling the product returns where personnel evaluate each item being returned. Personnel are trained to make

determinations whether items should be discarded, repackaged, repaired, refurbished, remanufactured, or a myriad

of other possible options (Rogers and Tibben-Lembke 1999; Stock 2004).

Product disposition is another area where further studies can help the process. Retailers may decide to return the

product to the supplier due to defects, obsolescence or overstocks (Rogers and Tibben-Lembke 1999). Options for

disposal processes of product returns can vary with firms and can range from refurbishing, reselling, recycling, or

destroying the returned products (UK Department of Transport 2004). While some returned products can be

repackaged and sold as new, due to legal or other restrictions some products can not be resold as new once the

product has been returned by customers. For example, while an electronic part could be refurbished and sold, a

circuit breaker may have to be disposed of differently (Rogers and Tibben-Lembke 1999). If a firm is not able to

resell the items, they often end up in land fills, or perhaps recycled. Also, the profit margins could be lower for the

manufacturer because in addition to the refurbishing cost, the product often must be sold at a lower price. In view of

this, manufacturers’ desire to maximize profits often dictates the proportion of product that gets refurbished

(Vorasayan and Ryan 2006).

Stock, Speh, and Shear (2002) state that in the U.S. consumers return products valued at more than $100 billion

each year, which is more than the GDP of 66% of the countries in the world. As firms begin to grasp the cost

implications of product returns, “return avoidance” is being considered as a desired alternative. The Reverse

Logistics Executive Council (RLEC) states that return avoidance entails examining ways to minimize the number of

products entering the return stream. Return avoidance, which can be acomplished by ensuring higher quality

products, increasing user friendliness of product, and managing promotional programs aimed at unloading the

products to the retailers, could be a critical part of a reverse logistics program.

This article uses the empirical data collected from manufacturers, wholesalers/distributors and retailers on

product returns processing to achieve the following major objectives. First, results should facilitate a better

understanding of what takes place in these business sectors and provide some benchmarks regarding reverse

logistics practices. Second, it will examine several hypotheses that have been suggested in various published

articles, but never tested. It is expected that testing of these hypotheses will help provide answers to questions such

as the level of importance of product returns, whether recovered value is high enough to justify product recovery

efforts, and the resources expended in various stages of the product return process.

SELECTED LITERATURE REVIEW

During the last decade, much has been published in terms of case studies and anecdotal information regarding

product returns. However, there are relatively few research studies that have examined empirical data (Srivastava

and Srivastava 2006). Stock (1992) was one of the earliest writers to call for more research in the area, although his

White Paper on reverse logistics was primarily a literature review of the topic. Much of his research dealt with

environmental aspects of reverse logistics, specifically source reduction, recycling, substitution and waste disposal.

He developed five major findings: (1) logistics executives needed to anticipate future environmental regulatory

changes; (2) logistics executives needed to be aware of the “green marketing revolution,” (3) procurement should be

aware of the need to acquire secondary raw materials, (4) logistics executives should implement efficient and

effective reverse logistics systems, and (5) some management persons should be assigned reverse logistics and

environmental responsibilities (Stock 1992, p. vi).

Sarkis (1995) addressed the reverse logistics chain and its role in product development, the product life cycle,

and recycling. He provided examples for each item, and discussed and posited several issues that needed to be

JOURNAL OF BUSINESS LOGISTICS, Vol. 30, No. 1, 2009 35

addressed through further research. Later, Stock (1998) and Rogers and Tibben-Lembke (1999) expanded the view

of reverse logistics to include additional activities such as processing product returns, disposition of physical goods

to obtain maximum recovery value, and the remanufacturing/refurbishing of items. These researchers included some

empirical data about reverse logistics, but each employed different research designs in collecting their data.

Stock (1998) utilized qualitative methods to analyze published and proprietary company reports and other

materials relating to reverse logistics and product returns. He then conducted in-depth case studies of several

companies located in North America and Europe. His findings were based on a qualitative analysis of published

documents and personal interviews with multiple executives in a number of companies. While he developed a large

number of findings from his research, some of the most significant included the potential cost savings and customer

service improvements that can result from implementing good reverse logistics practices, identifying the importance

of process mapping of the reverse logistics process, highlighting the need for specific cost information regarding

reverse logistics activities, recognizing that reverse logistics strategies and tactics require the multi-functional

approach of many areas within and between firms, and good reverse logistics processes usually have positive

environmental impacts (Stock 1998, pp. 7-8).

Rogers and Tibben-Lembke (1999) utilized a combination approach, i.e., company interviews and a mail survey

of reverse logistics executives. Based on the findings, Rogers and Tibben-Lembke (1999) recommended that firms

could improve the economics of reverse logistics by focusing on improving gate keeping technology, making

disposition decisions earlier, decreasing cycle times by speeding up the pace of returns processing, and better data

management. Both publications, while examining different industries and companies, highlighted the need for more

empirical research on the topics of reverse logistics and product returns. Prior to these studies, most published

material was anecdotal, that is, overviews of what individual companies were doing to handle product returns, reuse

packaging, remanufacture or refurbish products, and other reverse logistics practices.

Much of the research on product returns and reverse logistics has been specific to an industry or product

category. For example, Autry, Daugherty, and Richey (2001) reported on the predictors of reverse logistics

performance and satisfaction for firms selling electronic goods through catalogues. They found that performance

measured by indicators such as satisfaction and profitability was influenced by size of the firm, sales volume, and

whether the company had an internal or external arrangement for disposition.

Other researchers such as Meade and Sarkis (2002) focused on the critical determinants in firm’s selection of a

third-party logistics provider. Their model suggested that product position in its life cycle, organizational strategic

performance requirements, and the role played by reverse logistics in meeting firms environmental and customer

needs, were important.

De Koster, de Brito, and Van de Vendel (2001) outlined the factors that contributed to combining or separating

inbound and outbound flows during the handling of product returns for food stores, department stores, and mail

order companies. Their findings suggested that retailers were not as good in performing reverse logistics compared

to their ability in handling forward flows.

Richey, Genchev, and Daugherty (2005) examined automobile after-market firms and showed that reverse

logistics program efficiency and effectiveness could be increased by innovation and properly allocating resources.

Tan and Kumar (2006) compared the economics of refurbished parts versus part replacements for the computer

industry. The findings of their study stated that delay in transportation associated with processing returns negatively

impacts the economic viability of reverse logistics. Wu and Cheng (2006) looked at the supply chains in China,

Taiwan and Hong Kong to identify problems and developed a common model of reverse logistics for the industries

and companies examined. Their research led them to suggest that processing of product returns was not

economically viable due to lower values of recovered products since the cost of recovery exceeded the recovered

value.

Mukhopadhyay and Setoputro (2004) examined reverse logistics in an e-business context, specifically looking at pricing and return policies of Internet businesses. This study linked the e-tailer return policy to customer

sensitivity to the rate of return parameter. Findings of this study suggested that sellers’ return policies were more

restrictive if customers were sensitive to the rate of return parameter and were more likely to abuse the seller’s

return policies. The same authors (Mukhopadhyay and Setoputro 2006) examined the role of 4-PL’s in the

36 STOCK AND MULKI

outsourcing of reverse logistics activities and identified situations where optimal “win-win” results could be

obtained by all parties.

While each of the research studies examined a variety of reverse logistics issues, they were all in agreement that

more empirical research needed to be done on the topic. As evidenced in the overview of logistics and supply chain

management doctoral dissertations (Stock and Broadus 2006), more researchers have begun to examine reverse

logistics/product returns. The authors identified 13 dissertations completed between 1999 and 2004 dealing with

some aspect of reverse logistics/product returns. While 13 dissertations is not a large number, the number of

dissertations increased twofold from the 6 dissertations published on the subject between 1992 and 1998. Only 12

were published in the twenty years between 1970 and 1991 in the U.S. As a result of the continuing calls for more

empirical research on reverse logistics and product returns, this present research study was initiated to examine what

reverse logistics activities were being undertaken within three major industry sectors—manufacturing,

wholesaler/distributor, and retailing—and to identify some benchmarks for evaluating company practices. The focus

of this research was only on product returns and not packaging materials or waste disposal.

HYPOTHESES

Until recently, the majority of published articles on reverse logistics and product returns provided anecdotal

evidence of the rising importance of these issues. While the assertions and recommendations were intuitively

appealing and straightforward, most research studies have not specifically developed and tested hypotheses related

to product returns processing. While this research was primarily descriptive in nature, some of the previously

published literature suggested that certain hypotheses could be developed and tested. In those instances, this research

study examined several previously untested hypotheses and they are discussed in the following paragraphs.

Academics and practitioners agree that there is a growing focus on reverse logistics and product returns as firms

are beginning to take a strategic perspective of the process (Wu and Cheng 2006). Managers state that a well

administered reverse logistics program can reduce costs, improve customer service, and project an environmentally

friendly image, thus providing the firm with a competitive edge in the current market (Rogers et al. 2002; Srivastava

and Srivastava 2006). Stockholders, on their part, place a lot of emphasis on effective reverse logistics and product

returns partly prompted by the need to comply with legislative and legal obligations (Alvarez-Gil et al. 2007). The

increased strategic importance and the realization of the competitive edge offered by effectively managed reverse

logistics processes should make product returns a critical function.

One issue that has not yet been resolved is that of whether organizations should establish separate supply chain

channels for forward and reverse logistics. Rogers and Tibben-Lembke (2001) stated: “for returns to be proceeded

effectively and efficiently, they should usually be separated from the forward channel” (p. 141). Chopra and Meindl

(2007) argued that because customer priorities and supply chain strategy for the distribution of products are different

than for product returns, different supply chains should be established. Speh (2007) also seemed to infer that

multiple supply chains are needed to handle forward versus reverse logistics when he stated: “reversing the flow of

product in the supply chain… is a valuable service because reverse processes are outside the normal supply chain

process and often require significant time and attention” (pp. 235-236). Finally, Wisner, Leong, and Tan (2005)

seemed to take the view that reverse logistics could be accomplished in the same supply chain as forward logistics

when they stated: “Extending integration can also include reverse logistics, or integrating the process of product

returns back up the supply chain” (p. 458). The authors then went on to suggest that a separate reverse logistics

channel could be established: “Competitive pressures, increased legislation, and the desire to better utilize resources

are forcing many firms to design an effective reverse flow system” (p. 458).

None of these authors cited any specific research to support their positions, so it is possible that reverse logistics

could be accomplished in the same or different supply chain channels, although most authors appear to support

separate channels being established. Irrespective of whether an organization utilizes the same or different supply

chains however, there is general agreement that some specific person, group or department should be directly

responsible for reverse logistics.

Relating to the notion that a specific person should be directly responsible for reverse logistics, Stock, Speh, and

Shear (2002) recommended that if the firm intends to make a profit on the product returns activity, then this

JOURNAL OF BUSINESS LOGISTICS, Vol. 30, No. 1, 2009 37

responsibility should be assigned to senior managers with good business acumen. Many of the firms surveyed in this

research believed that the effectiveness of reverse logistics could be improved by making it a separate function in

the organization instead of having it attached to the forward distribution network (Rogers and Tibben-Lembke

2001). Based on these previously published articles, the following hypothesis is presented:

H1: Product returns are primarily handled by a management-level person in manufacturing,

retailing or wholesale/distributor firms.

Utilizing articles authored by House (1971) and Autry (2005), elevating reverse logistics and product return as a

separate function at a management level would imply that reverse logistics and product returns processing should

enjoy a similar status as that of forward distribution. Having reverse logistics as a separate function would also

reduce or eliminate its subordinate status to forward distribution, thus minimizing chances of multiple reporting and

role conflicts.

In organizations, managers are tasked with providing structure and specific directions in allocating tasks,

establishing procedures, setting expectations and rewards, thus reducing ambiguity and conflicts regarding functions

and goals (House 1971). Organizational behavior theories suggest that growth in organizations results in greater

differentiation in structure (Blau 1970). When faced with handling (i.e., processing) multiple functions and different

specialties, managers realize that they end up spending more time supervising these functions compared to

managing a homogenous function (Blau and Schoenherr 1971). Research also indicates that formalization of rules,

processes and procedures to guide operations increase efficiency (Autry 2005). Sub-division of responsibilities and

creating a functional group is likely to improve performance (Blau 1970). Studies propose that functional

differentiation and professionalization are known to infuse commitment to move beyond the current status towards

greater acceptance of technological innovations and provide motivation to be recognized within the organization

(Damanpour 1987). Having executives higher in the organizational hierarchy provides weight or importance to the

function as these executives can act as champions for improvements and improve communication and coordination

throughout the firm (Sinha and Van de Ven 2005). This would suggest that as the importance of the product return

function increases, this function would require management by a senior executive in the firm. Based on this, the

following hypothesis is presented:

H2: A majority of manufacturing, retailing or wholesale/distributor firms are likely to have a single

person responsible for product returns processing.

Meade and Sakris (2002) found that selection of third-party options are often guided by a firm’s strategic

performance requirements. Businesses recognize the need to focus on core competencies and view third-party

sources as a logical choice for handling reverse logistics activities in the absence of a separate function within the

organization for product returns. Researchers also believe that firms should give serious consideration to third-party

processing, if the current product return function is a part-time operation handled by more than one employee along

with other functions (Stock, Speh, and Shear 2006). This is because third-parties with reverse logistics as a core

competency have efficiencies of operation and are able to combine volumes from multiple companies for economies

of scale (UK Department of Transport 2004). In addition, third-parties specializing in product returns have unique

channels for product disposition in addition to providing a single central place for potential buyers of returned goods

due to the large volumes they process (Rogers and Tibben-Lembke 2001). Thus, outsourcing is a viable option for

firms without a dedicated returns process and for those that are unable to realize costs savings due to lower volumes

of product returns (Discount Store News 1999; Gorick 2005). Based on these articles, the following hypothesis is

presented:

H3: When reverse logistics or product returns is not a single person responsibility, the product

returns function is most often outsourced to third-parties.

Another reverse logistics matter that has been examined by a number of writers has been the education and

training of employees. Trade reports indicate that product returns may cost as much as three to four times the cost of

outbound shipments (Andel and Aichlmayr 2002). Return product handling costs can be as high as $35-$42 billion

per year or about 3-4 % of the $1.1 trillion 2005 logistics costs (Cooke 2006). This implies that there is an urgent

need to improve the product return process to make it more effective and thus enhance competitiveness in the

marketplace (Rogers and Tibben-Lembke 2001; Stuart et al. 2005). As the profile and visibility of reverse logistics

38 STOCK AND MULKI

rises in the organization, processes and strategies for reverse logistics are also attracting greater interest and scrutiny

(Rao, Stenger, and Wu 1994). In addition, since the returned product goes through various stages in the process,

potentials for errors increase. To counter this, experts have recommended better training of employees in the product

returns process as part of best practice (Stock 1996). Industry reports suggest that this training can be both formal

and informal and can range from overseeing how returns are processed to teaching how to repackage items

(Kuzeljevich 2004). Current training methods involve providing employees with operating procedures manuals,

mentoring of workers by other more experienced employees, or more informal methods (Stock, Speh, and Shear

2006). Thus most of the training could be on-the-job training and may consist of looking over employee’s shoulders.

Based on these published articles, the following hypothesis is presented:

H4: A minority (less than 50%) of firms use formal methods involving written materials, Internet,

etc. to train employees involved in product returns processing.

Firms are motivated to recover as much value as possible from returned products. However, there is not enough

published information about the recovered values of returned products in relation to the costs incurred in processing

them. In fact, Wu and Cheng (2006) suggested that publishers are better off discarding the returns rather than

processing them. Further, it is also believed that if the returned products remain longer in reverse channels, they can

negatively impact profitability. This could be due to higher inventory levels, transportation and warehousing costs,

as well as deterioration and product obsolescence with the passage of time (Blackburn et al. 2004; Stock 2001). On

the other hand, if returned products are processed at points closer to the customer, the time lag is shorter as products

avoid traveling up the distribution channel to the manufacturer and then back down to the wholesaler and retailer.

Quicker processing and turn-around help recover greater value from the returned products (Rogers and Tibben-

Lembke 2001). In view of this, it is likely that retailers who are closest to the consumer in the distribution chain

should be able to get higher product recovery rates compared to wholesalers/distributors or manufacturers. Based on

these articles, the following hypothesis is presented:

H5: Recovery rates (as % of cost) are higher for retailers when compared to manufacturers or

wholesalers/distributors.

Multiple authors have indicated that firms often utilize return authorizations (RA’s) for accepting returns. Much

of the published information on the use of RA’s has been anecdotal, that is, viewpoints of practitioners working in

the field of product returns, qualitative interviews of reverse logistics practitioners, and case studies of companies

involved in various aspects of product returns processing (Guide and Van Wassenhove 2002; Mukhopadhyay and

Setoputro 2004; Richey et al. 2005; Rogers and Tibben-Lembke 2001; Stock 1998, 2004). While the benefits of

RA’s seem apparent, there have not been any published studies that specifically demonstrate that a majority of firms

utilize these documents as a means of processing product returns. In this research study, this specific issue is

addressed, leading to the following hypothesis:

H6: A majority of firms (more than 50%) use return authorizations (RA’s) for accepting product

returns.

Product disposition refers to the different ways business organizations try to recover the costs of the products

that were returned. The following examples illustrate the multiple ways that returned items are processed. For items

with product dating that are nearing their expiration dates, they can be maintained in temporary storage and picked

and shipped to customers first. Thus, they are not “mixed” with other items with longer expiration dates (Stock

2004). If the products being returned are in damaged boxes, yet are in otherwise perfect condition, repackaging of

the items can take place immediately if packaging supplies are maintained at the returns processing facility. While

this is not a common occurrence, some computer and electronic components are processed in this way, resulting in

the items being returned to inventory much more quickly (Stock 2004).

Another example in the electronic components industry occurs when returned items may only have small

cosmetic imperfections that do not impact usability, or they may have a defective part that has been replaced and are

now in working order, but not in “as new” condition. These items can be used as warranty replacements and/or

resold with appropriate indication that they are not “brand new.”

As per industry sources, often the returned items are in fact not defective but have entered the return stream

because the customers changed their mind or did not understand how to operate the product (Rogers and Tibben-

Lembke 2001). A recent study reported that retailers most often send back the non-defective customer returns to the

JOURNAL OF BUSINESS LOGISTICS, Vol. 30, No. 1, 2009 39

manufacturers without even testing them. This results in manufacturers returning these non-defective items directly

back-to-stock or into inventory after a cursory examination (Rogers and Tibben-Lembke 2001). Studies indicate that

between 17-20% of the product returns went directly back-to-stock to be sold as new (Blackburn et al. 2004; Rogers

and Tibben-Lembke 2001). Based on these published articles, the following hypotheses are presented:

H7: Manufacturers will have more product returns placed directly back-in-stock or inventory than

retailers or wholesalers/distributors.

H8: Manufacturers will have more products repackaged and returned to stock than retailers or

wholesalers/distributors.

Often the manufacturers are concerned about selling the returned products to brokers. This is because, in

addition to lower prices, manufacturers are concerned about the loss of “brand equity.” Once the product is sold to

the broker, manufacturers do not control how these products are sold. Firms fear the impact on brand image if these

products end up in bargain outlets or sold in flea markets (Rogers and Tibben-Lembke 2001). Thus the final option

for manufacturers, when the product can not be sold as is or can not be refurbished, is selling it as scrap or

destroying it to recover primary materials. Thus, the following hypothesis is presented:

H9: Manufacturers will have more returned products sold as scrap or destroyed than retailers or

wholesalers/distributors.

The largest category of customer product returns is attributed to buyer’s remorse, usage problems or defects

(UK Department of Transport 2004). Retailers and wholesalers are at the front line and are closer to the customer

and generally faced with more returns. Rogers and Tibben-Lembke (2001) showed that, in spite of the overall desire

to tighten return policies, retailer return policies were still considered liberal. This liberal policy could have been

based on the retailers’ wish that manufacturers bear the cost of generous return policies (Tsay 2001). However, this

seems to be changing. There are indications that the retailers are beginning to focus on individual customer profitability , minimization of unprofitable customer transactions, and getting rid of ‘bad’ customers (Triest 2005;

Zeithaml, Bitner, and Gremler 2006). This would suggest an increased tightening of product return policies to discourage customers who indulge in too many returns. Several of the respondents in Rogers and Tibben-Lembke’s

(2001) study felt that the liberal return days are going to be a thing of the past – “it was mentioned in a number of

interviews that the days of ‘no questions asked’ returns are ending” (p. 136). Based on these published articles, the

following hypothesis is presented:

H10: More product returns are refused by retailers than by manufacturers or wholesalers/distributors.

To test these hypotheses, a research design involving a mail survey of practitioners involved in reverse

logistics/product returns was utilized.

METHODOLOGY

Practitioners involved in some aspect of product returns processing were the subjects of the data collection

effort. Personal interviews were conducted with executives who had reverse logistics responsibilities at more than

20 manufacturers, retailers, and wholesalers/distributors. The firms interviewed were approximately equally

distributed between the three groups. The interviews helped refine the questions being asked of survey respondents

and also helped to supplement the data obtained via a mail survey of the Warehousing Education and Research

Council (WERC) membership. The majority of survey questions were developed from the literature and/or the

personal experiences of the authors from previous reverse logistics research. The interviews provided insights into

the wording of the survey questions to maximize understandability and response rate. Respondents are more likely

to answer surveys that they perceive to be relevant to them and what they do. The actual site visits required 4-6

hours of time and involved tours of the product returns processing facility.

An interview guide was used for all site visits, although a few questions varied between firms because they

were partially dependent on the specific products, customers, and markets of each firm. In about 75 % of the firms

40 STOCK AND MULKI

who agreed to participate in the site visit phase of the research, confidentiality or non-disclosure agreements were

used. As a result of the site visits, a review of secondary source materials and the researchers’ experience in the

field, a 4-page mail survey was developed and pre-tested with more than two dozen practitioners directly involved in

reverse logistics activities (Note: a copy of the survey instrument can be found in the Appendix).

With the development of the finalized instrument, three mailings of the survey were sent to manufacturer,

retailer, and wholesaler/distributor members of WERC. Potential respondents to the survey were selected from a

review of the WERC membership list. First, the list was reviewed and only manufacturing, wholesale/distributor and

retailing firms were included. If only one person was shown for a particular company, they were selected if they

held some type of management position. If more than one individual was a WERC member from a specific

company, the titles of the persons were examined. If one of the members had specific reverse logistics or product

returns in their job title, they were selected. If not, and this was typically the case, the highest ranking person in the

company was selected. It was believed that the senior person would have the most knowledge about their firm’s

product returns processing.

The survey questionnaire indicated that this was a WERC-sponsored research project. Respondents were asked

to indicate the type of business organization at which they were employed from the choices provided

(manufacturing, retailing, wholesaler/distributor, government, or other). Survey questions also required them to

choose the industry category from the seventeen sectors (categories) provided. (e.g., pharmaceutical, appliances,

electronics). In addition, they were asked to indicate their job title from the list of job titles (corporate officer,

manager, director, supervisor, staff specialist or other). Finally respondents were asked to indicate their primary job

responsibility; the one responsibility that required most of their time (general management, logistics, marketing,

reverse logistics, warehouse operations or other).

Respondents could request a summary of the survey findings by sending their business card with their returned

survey, by indicating their name and address on the survey, or by requesting the survey results in a separate letter.

An e-mail pre-contact from WERC was sent to all potential respondents approximately 7-10 days prior to mailing of

the survey, encouraging their response to the survey they would be receiving. As a result of these efforts, the total

response rate for the survey prior to the removal of some responses that failed to provide necessary information for

analysis was 242 (22.1 % of 1095).

Tests for Non-response Bias

The four-page surveys were color coded for each mailing and as responses were returned, they were date

stamped so that early versus late respondents could be compared and thus test for non-response bias (Armstrong and

Overton 1977). Responses were received over an eight-week period. Differences between early and late respondents

were checked using the 145 responses received during the first two weeks versus 45 responses received during the

last three weeks. ANOVA models and t-tests did not show any statistically significant differences in responses

between the early responses versus late responses.

As an additional test for non-response bias, a single mailing of a one-page survey to non-respondents was done

two weeks after the third mailing of the four-page survey. A total of 103 one-page surveys were returned, which

were used as a second measure to test for non-response bias. Such tests for non-response bias are important in that

the results of the survey could not be generalized to the population-at-large if bias existed.

After analysis of the early versus late respondents and a comparison of the non-respondents to those completing

the full survey, it was determined that there were no statistically significant differences that existed and results

obtained could be generalized to the entire WERC member population of manufacturers, retailers, and

wholesalers/distributors.

Sample Summary Statistics

The survey responses represented a total of 16 industry sectors plus “other.” Of the 230 responses, 23 did not

indicate any industry category, and 55 responses stated their industry as “other.” Six industry sectors, namely,

Automotive (11), Chemicals & Plastics (10), Clothing & Textiles (12), Department Stores (14), Food & Beverage

JOURNAL OF BUSINESS LOGISTICS, Vol. 30, No. 1, 2009 41

(42) and Paper and related (17) sectors accounted for most of the (106 out of 230) responses. The remaining 58

responses were distributed among the 10 other industry categories named in the survey.

Respondents included Corporate Officers (N = 40), Directors (N = 60), Managers (N = 108), and Supervisors

(N = 7). Fifteen indicated “Other” and 12 respondents did not indicate their position. Of the business groups,

responses were provided by manufacturing firms (N = 92), retailing (N = 23) and wholesalers/distributors (N = 115).

There was only one (1) response from government, seven (7) indicated “other” and four (4) did not indicate any

business group. In sum, the majority of the respondent population consisted of approximately equal proportions of

manufacturers and wholesalers/distributors, with a small number of retailers included. In view of this, all the

analyses were conducted by using the 230 responses from three business groups: manufacturers, retailers, and

wholesalers/distributors.

FINDINGS

SPSS 14 for windows was used for conducting the analysis. Descriptive statistical analysis and ANOVA

comparisons were used to test the various hypotheses. Contingency table analysis utilizing the Chi-square statistic

was used for the nominal-scaled data. When the overall Chi-square was significant, the various pairs of attributes

were examined to determine which relationships were statistically significant. The findings of the study are

presented in two parts. In the first part we describe the details of the product return process based on the study data.

In the second part we provide results from testing the stated hypotheses.

Section I: The Product Returns Process

Steps in Product Returns Processing

In general, product return process activities can be grouped into four steps or stages: (1) Receiving—includes

unloading, distribution of product returns to processing centers; (2) Processing—consists of activities such as data

entry and issuing customer credits; (3) Sortation—inspection and routing of returns to disposition point; and (4)

Disposition—putting the product back into inventory or temporary storage, repackaging, repair, refurbishing or

remanufacturing. It could be argued that there is a step that precedes these four which might be labeled “pre-

receipt.” This would include activities such as shipping the product returns to the processing facility, getting

authorization and completing the return authorization forms, and preparing the returned item for processing. In this

research, we specifically examined the process once the items reached the product returns processing facility.

Survey results indicate that the last three (2, 3, and 4) steps consume a large percentage of the time spent in

product return process. Results indicate that on average, respondents in the three business groups spent about 31% of

the time on processing, about 26% on sortation, 26% on disposition and about 17% on receiving.

Use of Warehouse Space

Almost all respondents in the three business types (>90%) indicated that they used their regular

warehouses/distribution centers to process product returns as opposed to having a dedicated returns processing

facility. Most manufacturers and wholesalers use less than 25 % of their existing warehouse space for processing

returns. Interestingly, about 19 % (4/23) of the retailers indicated that they used more than 75 % of their warehouse

space for returns processing, suggesting that they combined forward and reverse logistics in the same area. Of

course, this would apply to retailers that have dedicated product returns processing facilities. Facilities performing

both forward and reverse logistics activities would only utilize a small portion of their buildings for processing

product returns. Compared to this, 1.3 % (1/78) of manufacturers and 2.9 % (3/103) of wholesalers indicated use of

more than 75 % of warehouse space for product return processing. This finding is consistent with the researcher’s

experience that retailers utilize dedicated product returns facilities to a larger degree than do manufacturers and

wholesalers/distributors. Typically, retailers will see more returns than other supply chain members who are further

away from the final customer.

When return rates and/or volumes are low, a combined facility is usually optimal. A combined facility is

defined as a warehouse or DC where both forward and reverse logistics activities occur in the same location. When

42 STOCK AND MULKI

return volumes are low, they can typically be handled in a portion of the warehouse or DC where forward logistics

takes place. When return volumes are high, or when significant processing of the returns is necessary, such as

refurbishing or remanufacturing of the items, a dedicated facility makes more sense.

Warehouse Operations

Respondents indicated that a total of 1725 full time employees (FTE) were involved in warehouse operations.

Of these, 1217 (71 %) were classified as operations (those people that actually handle the returns), 238 (14 %)

administrative/clerical, 157 (9 %) supervisory, and 113 (7 %) managerial employees. On average, there were 6.6

FTE operations workers, 1.6 FTE administrative positions, 1.1 FTE supervisory positions, and 1.2 FTE managerial

positions in the warehouse processing product returns.

Product Disposition

Product disposition refers to the ways business organizations deployed to recover the costs of the products that

were returned. Products that went through the return process were generally dispositioned as follows:

1. returned directly to inventory

2. repackaged and returned to inventory

3. repaired or refurbished

4. destroyed or sold as scrap

5. turned over to a third-party/secondary market

6. donated to charity

Often, product disposition is handled in multiple ways as opposed to a single approach. As shown in Table 1,

responses suggest that 88.3 % of them send a portion of their products directly to inventory, 81.8 % destroy or sell

portions as scrap, 61.4 % repackage items and return some portion to inventory, 4.1 % refurbish, and 37 % indicate

they donate some product returns to charity. This indicates that the returning to stock either directly or by

repackaging and selling as scrap are the two major disposition methods. The survey did not specifically examine

what recovery percentage was obtained from each disposition option nor was data collected regarding the actual

amounts of returned products placed back into inventory, and these questions will have to be answered with

additional future research. For example, even though a large percentage of survey respondents (88.3 %) return items

directly to inventory, we do not know how many products that represents. It is also possible that a product category

or SKU is returned to inventory, but only a small percentage of all of the products or SKU’s received.

TABLE 1

PROCESSED PRODUCT DISPOSITION

(% responding that they utilize the method of disposition)

Method of Disposition Percent

Response

Recovery

Rate

Returned directly to inventory 88.3 % High

Repackaged and retuned to inventory 61.4 High

Repaired or refurbished 4.1 High

Destroyed or sold as scrap 81.8 Low

Third-party/secondary market 19.0 Medium

Donated to charity 37.2 Low-Medium

Other 19.9 Low

JOURNAL OF BUSINESS LOGISTICS, Vol. 30, No. 1, 2009 43

Existence of Published Standards

Respondents were asked about the existence of published standards for each step of the product returns process.

For the receiving activity, manufacturers and retailers indicated that they used standards about one-half of the time.

Wholesalers/distributors did not use standards for receiving as often (42 % of the time). In the processing activity,

results were similar. Manufacturers and retailers utilized standards about two-thirds of the time, while

wholesalers/distributors used them about one-half of the time. For sortation, only retailers used standards frequently

(64 % of the time), while manufacturers and wholesalers/distributors employed standards 46 % and 39 %

respectively. Finally, for disposition, all respondent categories utilized standards about one-half of the time.

However, these differences among the components of the product return process were not statistically significant.

With reverse logistics and product returns programs still not fully developed in some firms, it was not surprising

that a larger number of companies did not have standards in the product return process. On the other hand, a

reasonable number had standards, so there is progress taking place regarding firm’s awareness that reverse logistics

is an important aspect of the business. As more firms place additional emphasis on managing product returns more

effectively and efficiently, the use of standards will no doubt increase.

Type of Standards Used

Respondents were asked to indicate the type of standards used by them for the eight activities commonly used

by firms in evaluating product returns processing efficiency and effectiveness (see Table 2). Responses suggested

that a majority of the respondents in all three business groups did not use standards for these activities. When the

business groups did use standards, the extent of the use of standards varied. This reflects the general condition

relative to the use of standards and metrics within many companies and industries and has been identified as an area

of “need” in supply chain performance standards.

For example, the Council of Supply Chain Management Professionals has published a series of Supply Chain

Management Process Standards that includes the returns process. Supply Chain Visions, the author of the series,

identified five process areas where standards were required: (1) Receiving and warehousing; (2) Transport; (3)

Repair and Refurbishment; (4) Communicate; and (5) Manage Customer Expectations. They also identified typical

best-practice processes. To illustrate, as part of receiving and warehousing, the sub-process of “systems integration”

was identified. A suggested minimum process standard was the following: Order management and returns processes

are integrated using common systems to capture orders, shipments, and return authorizations/information. The

authors identified the following as a best practice: Returns are matched against original orders by item and quantity

(Supply Chain Visions 2004).

Table 2 shows the percent of respondents in each group indicating that they use standards for the above eight

activities. It appears that use of standards seems to be higher for activities 1, 3, 4 and 6 for retailers and 1-3, 6, and 7

for wholesalers. Part of the reason for this is that retailers and wholesalers/distributors are positioned closer to the

final customer and are expected to be more responsive to customer returns. Thus, they would be more likely to have

standards for product returns processing. The results in Table 2 indicate that a higher percent of retailers use

standards for pieces/returns handled by employee per hour (activity 1) compared to wholesalers and manufacturers.

A higher number of retailers also used standards for total pieces/returns processed per day and error rates for

items scanned (activity 3 & 4). A higher percent of wholesalers used standards for time from receipt to crediting

customer’s account (activity 2) as well as for assessing total returns processing time (activity 6). There were no

significant differences in the respondents regarding the use of standards for time to receipt to initial returns

processing (activity 7) step and for assessing the number of pieces returned to stock per day (activity 8). Almost

none of the manufacturers used standards for assessing error rates for items scanned (activity 4), perhaps assuming

that such errors would be minimal since all of the returns they receive should be theirs and not some other

manufacturers.

44 STOCK AND MULKI

In general, successful management of reverse logistics/product returns requires the use of productivity,

utilization and performance metrics. For each category, the following definitions are offered (A. T. Kearney 1991).

Productivity = Output produced ÷ Input consumed

Utilization = Capacity or resources used ÷ Capacity or resources available

Performance = Actual output produced ÷ Standard output produced

TABLE 2

USE OF STANDARDS IN THE PRODUCT RETURN PROCESS

(% responding that they utilize standards)

Type of Business Organization

Activity Manufacturing Retailing Wholesaler 2

1. Pieces/returns handled by

employee per hour 10 % 52 % 23 % 0.00

2. Time from receipt to crediting of

customer account 16 14 30 0.04

3. Total pieces/returns processed

per day 19 48 26 0.02

4. Error rates for items scanned 1 33 11 0.00

5. Error rates for incorrect

disposition 1 20 7 0.00

6. Total returns processing time 13 23 28 0.03

7. Time from receipt to initial

returns processing 17 19 26 0.27

8. Number of pieces/items returned

to stock per day 11 23 20 0.26

Table 3 identifies some selected metrics used by companies to more efficiently and effectively manage the

reverse logistics/product returns process. The metrics should be useful for companies seeking to measure and

evaluate various aspects of their product returns/reverse logistics process. Not every metric will be useful for every

firm but they do provide a good starting point for companies.

Section II: Results of Hypotheses Testing

A total of ten (10) hypotheses were tested for this study using survey responses from 230 respondents. Results

showed support for all of the hypotheses ( <0.05) except for H2, H3 and H7. H1 was supported as the results show

that return processing was generally assigned to middle or senior management positions in the organization. As

shown in Table 4, out of the 230 total responses, 208 (90 %) held managerial or higher positions. On a percentage

basis, 47 % (108/230) of the respondents were managers followed by directors (60/230 = 26 %) and corporate

officers (40/230 = 17 %). Chi-square ( 2) was 11.02, degrees of freedom (df) = 3, and p = 0.00. An analysis of the

three combinations of business organizations (mfg.-retail; mfg.-wholesale; retail-wholesale) revealed that only the

manufacturers and retailers were significantly different statistically (p = .02). Retailers were much more likely than

manufacturers to have more senior management personnel responsible for reverse logistics.

JOURNAL OF BUSINESS LOGISTICS, Vol. 30, No. 1, 2009 45

TABLE 3

PRODUCTIVITY, UTILIZATION AND PERFORMANCE METRICS

Productivity Metrics

• Number of Employees (regular full time, regular part time, flex/temporary) per month (average of all days

in the month, total at end or beginning of the month, or measured on a specific day during each month)

• Units processed per hour, day, month and/or week (overall, receipt, initial sort, refurbishing, return to

vendor, charity/donation, destroy)

• Cost per unit returned for: labor (returns processing labor, contracted labor, other), supplies, packaging,

administrative

• Number of units/pieces processed per hour (overall and for each employee) for each stage of the product

returns process

• Labor cost per piece received

• Percentage of total units/pieces bar-coded

• Units/pieces received divided by units/pieces salvaged on a daily, weekly, or year-to-date (YTD) basis

• Number of pallets received versus number of pallets processed

• Total number of product scans at initial processing per hour, day, week or YTD

• Number of returned pieces/items still not processed after 48 hours (time will vary by company and

individual standards)

• Total units/pieces received versus RA units/pieces authorized

• Percentage of items authorized for return but not received

• Percentage of items received and authorized

• Package condition of returns that are received

Utilization Metrics

• Amount of temporary storage space utilized at end of day, week or month

• Employees (regular full time, regular part time, flexible) used in returns processing versus employees

available

• Number of totes/containers used versus number of totes/containers available

• Receiving and/or shipping doors used versus doors available

• Units/pieces received for each inbound transportation carrier (overall, daily, weekly, monthly, YTD)

Performance Metrics

• Sortation accuracy (total unit errors inventories that are inaccurately sorted as compared to total locations

checked)

• Over/short accuracy (total items inventoried as compared to total items shipped)

• Salvage percentage for each product class/category

• Hours required to complete each stage of the returns process and hours overall (broken down by employee,

product category/class, time period)

• Units/pieces processed per hour, day, week and YTD

• Salvage value per unit/piece

• Accuracy level for each employee in terms of number of items handled, number of errors, and percentage

correct decisions

• Damage amounts (in units, percent of the total) by type of damage

Source: Stock, J. R. (2004), Product Returns/Reverse Logistics in Warehousing: Strategies, Policies and Programs,

Oak Brook, IL: Warehousing Education & Research Council, pp. 53-55.

46 STOCK AND MULKI

TABLE 4

JOB TITLE

(Number of Responses)

Type of Business Organization

Manufacturers Retailers Wholesalers Total 2

Corporate Officer 3 5 32 40 0.00

Director 24 3 33 60

Manager 57 12 39 108

Other/Supervisor 8 3 11 22

Total Number of Responses 92 23 115 230

Note: Cramer’s V = 0.2506.

Hypotheses H2 which stated that majority of manufacturing, retailing or wholesale/distributor firms are likely to

have a single person who is responsible for product returns processing was not supported. Results show that except

for retailer sector, product handling was a multiple person responsibility. As shown in Table 5, 65 % (58/89) of

manufacturers and 55 % (63/114) of wholesalers indicated that product handling was a multiple person

responsibility while 65 % (15/23) of the retailers indicated it was a single person responsibility. Chi-square ( 2) was

7.2, degrees of freedom (df) = 2, and p = 0.03. An analysis of the three combinations of business organizations

(mfg.-retail; mfg.-wholesale; retail-wholesale) revealed that only the manufacturers and retailers were significantly

different statistically (p = .02). Retailers typically had a single person responsible for product handling, while

manufacturers had several people responsible.

H3 was also not supported as results showed that majority of the firms have reverse logistics/product return

function done in-house. About 75 % (72/97) of the respondents who had indicated single person responsibility for

reverse logistics conduct product returns in-house. A majority of the respondents indicated in-house processing

irrespective of whether a single or multiple persons were responsible for reverse logistics/product return functions.

In fact, manufacturers’ utilized 3-PL’s only 25 % of the time, retailers only 18 % of the time, and

wholesalers/distributors only 12 % of the time. The differences were not statistically significant, but it does show

that most companies still perform product returns processing in-house.

TABLE 5

PRODUCT HANDLING RESPONSIBILITY

(Number of Responses)

Type of Business Organization

Manufacturers Retailers Wholesalers Total 2

Single Person 31 15 51 97 0.03

Several People (more than one) 58 8 63 129

Total Number of Responses 89 23 114 226

Note: Cramer’s V = 0.1785.

JOURNAL OF BUSINESS LOGISTICS, Vol. 30, No. 1, 2009 47

TABLE 6

PRODUCT HANDLING RESPONSIBILITY—IN-HOUSE VS. THIRD-PARTY

(Number of Responses)

Single Person Responsibility Type of Business Organization

Manufacturers Retailers Wholesalers Total 2

Firm 23 11 38 72 0.07

Third-party 3 3 7 13

Combination 5 1 6 12

Total Number of Responses 31 15 51 97

Further analysis showed that a small portion of the respondents indicated reverse logistics as their primary

responsibility. Table 7 shows the breakdown for primary job responsibility. It appears that in spite of the growing

importance of reverse product flows, few executives (6/227 = 2.6 %) in the industry have reverse logistics as their

primary job responsibility. On the other hand, about 50 % (116/227) of all the respondents indicated that their

primary job responsibility was Warehouse Operations and Management followed by General Management (50/227

= 22 %) and Logistics Planning (49/227 = 22 %). Thus, more often, the reverse logistics function is assigned as a

part of some other organizational function such as Warehouse Operations, General Management or Logistics

Planning. Chi-square ( 2) was 12.55, degrees of freedom (df) = 4, and p = 0.02.

An analysis of the three combinations of business organizations (mfg.-retail; mfg.-wholesale; retail-wholesale)

revealed that manufacturers and wholesalers and retailers were significantly different statistically (p = .02).

Wholesalers were significantly different than both manufacturers and retailers, in that they were much more likely to

have general management responsible for reverse logistics activities. Wholesalers often have to balance the

conflicting demands of manufacturers to overstock versus retailer’s concern about finite selling seasons and

uncertain demand (Tsay 2001). They also may have to consolidate returns from multiple retailers for economic

processing of returned products. This would require that this function be handled by employees with good

management skills.

TABLE 7

PRIMARY JOB RESPONSIBILITY

(Number of Responses)

Type of Business Organization

Manufacturers Retailers Wholesalers Total 2

General Management 13 2 35 50 0.02

Logistics Planning 23 8 18 49

Reverse Logistics 2 2 2 6

Operations/Management 47 10 59 116

Other 5 0 1 6

Total Number of Responses 90 22 115 227

Note: Cramer’s V = 0.1708.

48 STOCK AND MULKI

In view of the above, handling of product returns is likely to be a multiple person responsibility in most

organizations. These findings would support the conclusion that product returns processing is managed usually on a

part-time basis by more than one employee in combination with other forward logistics activities. In addition, the

study results show that over 80 % of the three business groups reported that they had less than five full time

employees under managerial, administrative and supervisory category. H4 stated that only a minority of firms use

formal methods of training. Results support the hypothesis. Only 89 out of 228 (39 %) respondents indicated they

had a formal method involving written training methods.

Recovery rate was defined as the monetary value recovered from the item being returned as a percentage of

original cost after processing the returned product item. Overall results indicate a high rate of recovery. More than

one-half of all the respondents (97/184) indicated that product recovery rate as a percentage of original cost was

above 75 %. For this analysis, recovery rates as percent of costs were divided into four quartiles: small, medium,

large and very large. Recovery rate was termed as “very large” for recoveries over 75 %, “large” for 51-75 %,

“medium” for 26-50 %, and “small” for less than 25 % recovery. Again however, as in other product return

activities, there was variability between the three business groups.

H5 stated that recovery rates (as % of cost) for returned products are higher for retailers compared to

manufacturers or wholesale/distributors. Study results supported this as 69 % (11 of 16) retailers reported recovery

rates in the top quartile, followed by 61 % (58 of 95) of wholesalers and 38 % (28 of 73) of manufacturers. As we

had hypothesized, closer proximity to the customers allows the retailers, and to some extent wholesalers, to put the

returned product back to the stock to be sold thus avoiding potential for devaluing the product due obsolescence.

Table 8 shows the quartile breakdown of responses for recovery rates by business group. Chi-square ( 2) was 12.74,

degrees of freedom (df) = 6, and p = 0.05. An analysis of the three combinations of business organizations (mfg.-

retail; mfg.-wholesale; retail-wholesale) revealed that only the manufacturers and wholesalers were significantly

different statistically (p = .02). Wholesalers tended to recover greater amounts of the original cost of returned

products than manufacturers. As stated before, wholesalers are much closer to customers in the logistics chain and

thus are able to turn around the returned product quicker and realize higher returns.

TABLE 8

RECOVERY RATE AS A PERCENTAGE OF ORIGINAL COST

(Number of Responses)

Type of Business Organization

Manufacturers Retailers Wholesalers Total 2

Quartile 1 –Small (0- 25%) 15 2 9 26 0.05

Quartile 2 -Medium (26- 50%) 12 2 15 29

Quartile 3 –Large (51- 75%) 18 1 13 32

Quartile 4-Very Large (76% and above) 28 11 58 97

Total Number of Responses 73 16 95 184

Note: Cramer’s V = 0.1861.

Being close to the point-of-sale, retailers have more disposition options as well as shorter processing time.

These factors seem to result in retailers reporting high recovery rates while manufacturers who have fewer

disposition options report lower percentage recovery rates. Clothing, textiles and general merchandise were in the

high recovery category for retailers while it was automotive parts, paper and related products, food and beverages

for wholesalers. For example, a large Internet and mail order catalogue retailer experienced 80-90 % recovery rates

for its returned products. If the return requires minimal cleaning or replacement of missing or damaged buttons or

clasps, and the garments only need pressing to remove wrinkles, in most instances, the item can be resold. Many of

the items returned to the company were still in their original, unopened packaging and thus could be placed directly

JOURNAL OF BUSINESS LOGISTICS, Vol. 30, No. 1, 2009 49

back into inventory. On occasion, customers are known to order more than one size, color or style of an item to

compare them with the intention of returning the ones they do not want.

Another clothing retailer, with both direct marketing and “brick and mortar” stores located in shopping malls,

experienced similar recovery rates for returned products due to their thorough and detailed processing procedures.

Employees tasked with processing returns are provided detailed instructions about steaming, cleaning, repairing and

refurbishing items. The detailed instructions are provided so that employees fully understand the process and can

accomplish their tasks in the shortest possible time period, with the results being lower costs and higher productivity

levels (Stock 2004).

Additional analyses indicated that about 26 % of the retailing, 7 % of manufacturing and 9 % of wholesalers

had more than 5 processing stations. Stations are physical locations where each product return is evaluated by a

person and usually includes scanners and computers that allow personnel to input information about the product

being returned. In essence, a higher percentage of multiple product return stations suggest that retailers handle

significantly more returns than manufacturers or wholesales/distributors. Second, it would mean that retailers want

returns handled more expeditiously compared to manufacturers and wholesalers. Third, retailers have the most

complex returns processing since there could be multiple reasons for product returns. Table 9 provides details of

product handling by the three business groups.

TABLE 9

NUMBER OF PRODUCT RETURN PROCESSING STATIONS (Percent Responses)

Type of Business Organization

Manufacturers Retailers Wholesalers 2

0 8 % 4 % 3 %

1 67 48 62

2 13 9 15

3-5 6 13 12

Number of Product

Stations

>5 7 26 9

.08

Results support the hypothesis H6 that majority of firms use “return authorizations” (85.4 %) for product returns

and require a pre-approval (71.8 %) of the return authorizations for accepting product returns. We had hypothesized

(H7) that manufacturers will place a greater portion of products directly in stock compared to retailers or

wholesalers. However, results of the analyses showed that the wholesale segment had the highest percentage of

recovered product returned directly to stock ( = 55.5, Std. Dev. = 32.3) followed by manufacturers ( = 37.8, Std.

Dev. = 30.8) and retailers ( = 32.7, Std. Dev. = 34.4). The differences between wholesalers and the two segments

were statistically significant ( = 0.05). There were no statistically significant differences in the mean percent of

products returned directly to stock between manufacturers and retailers.

Hypothesis H8 stated that manufacturers will have more product packaged and returned to stock compared to

wholesalers/distributors. Results support this hypothesis as manufacturers had the highest percent ( = 22.2, Std.

Dev. = 25.2) while wholesalers had the lowest percent of returns being repackaged ( = 12.3, Std. Dev. = 18.7)

before returning to stock. We believe that food industry product returns to stock were primarily at the wholesale

level and reflect the lower percentages of products being repackaged and returned to stock. Finally, in the product

disposition area, H9 was supported as wholesalers reported lower percent ( = 14.4, Std. Dev. = 18.7) of product

returns destroyed or sold as scrap compared to manufacturers who reported the highest percent ( = 23.7, Std. Dev.

= 26.7). The key factor of any product returns processing strategy is to identify the various options for the

disposition of items and to select the option(s) that maximize recovery rate(s).

Hypothesis H10 stated that more product returns are refused by retailers than wholesalers/distributors or

manufacturers. Results show that overall 51.3 % (118/230) of all the respondents refused to accept some of the

product returns. Refusal to accept product return was highest for retailers at 65 % (15/23), followed by wholesalers

50 STOCK AND MULKI

57 % (66/115) and lowest for manufacturers 40 % (37/92) thus supporting H10. Chi-square ( 2) was 8.01, degrees of

freedom (df) = 2, and p = 0.02. An analysis of the three combinations of business organizations (mfg.-retail; mfg.-

wholesale; retail-wholesale) revealed that only manufacturers and wholesalers were significantly different

statistically (p = .02). Wholesalers were significantly more likely to refuse product returns from customers (who

would be retailers) than manufacturers (whose customers would be some combination of wholesalers and/or

retailers).

TABLE 10

PRODUCT RETURNS REFUSED

(Number of Responses)

Type of Business Organization

Manufacturers Retailers Wholesalers Total 2

Not refused 55 8 49 112 0.02

Refused 37 15 66 118

Total Number of Responses 92 23 115 230

Note: Cramer’s V = 0.1866.

SUMMARY AND CONCLUDING REMARKS 1

In this empirical examination of product returns processing in the manufacturing, wholesale/distributor and

retailing sectors, it was found that in spite of the growing importance of reverse logistics and product returns

processing in the business and academic literature, these activities have still not assumed a widespread high level of

importance within organizations. While senior executives are often given the responsibility of overseeing the

process, it is not their main function. It appears these executives generally handle this function along with other

responsibilities, so in essence, product returns processing is still a “part-time” activity in most organizations.

As previously discussed in the Introduction and Selected Literature Review, others have commented on the

potential benefits associated with having dedicated product returns personnel. There is no substitute for full-time

effort being devoted to a process such as product returns. Part-time effort does not allow sufficient time to fully

evaluate and investigate potential improvements in the process nor provide the day-to-day oversight needed to

ensure the process runs smoothly. Also, by having a full-time manager in charge of product returns, better

coordination of forward and reverse logistics can occur.

Regarding all of the hypotheses being examined, Table 11 provides a summary of the hypotheses that were

tested.

We found that business types typically use a single labor shift operation for the product returns process. This

was not unexpected inasmuch as the vast majority of organizations have a relatively small to moderate amount of

products being returned, thus requiring less time and fewer employees to handle returns. On average, organizations

employ 6.6 FTE (full time equivalent) production workers, 1.6 FTE administrative persons, 1.1 FTE supervisory

persons, and 1.2 FTE managers in the facility that processes product returns. Additionally, the majority of the

facilities operate with only a single product returns processing station.

As seen from the on-site visits, firms utilize a fairly consistent process for handling product returns; that is, the

steps or stages employed for processing product returns does not significantly vary from firm to firm. Once products

are received and the processing of the returns begins, the three most common methods of product disposal were

1

Material presented in this section are based exclusively on the mail survey, company interviews and on-site visits,

and/or previously published research that was cited earlier in the paper.

JOURNAL OF BUSINESS LOGISTICS, Vol. 30, No. 1, 2009 51

returning the product directly to stock, selling the items as scrap, and returning items to stock after repackaging

(although repackaging was less common in the food and beverage industry). In some instances, the percentage of

returns that go back into inventory for resale was much higher than has been previously reported in the literature.

Obviously, the recovery rates for items that go back into stock for resale are much higher than most other disposition

options, which accounts for the higher than expected recovery rates measured in this research study.

TABLE 11

HYPOTHESES TESTING

Hypothesis

H1 Product returns are primarily handled by a management-level person in

manufacturing, retailing or wholesale/distributor firms. Supported

H2 A majority of manufacturing, retailing or wholesale/distributor firms are likely

to have a single person who is responsible for product returns processing. Not supported

H3 When reverse logistics or product returns is not a single person responsibility,

the product returns function is most often outsourced to third-parties. Not supported

H4

A minority (less than 50 %) of firms use formal methods involving written

materials, Internet, etc. to train employees involved in product returns

processing

Supported

H5 Recovery rates (as % of cost) are higher for retailers when compared to

manufacturers or wholesalers/distributors. Supported

H6 A majority of firms (more than 50 %) use return authorizations (RA’s) for

accepting product returns. Supported

H7 Manufacturers will have more product returns placed directly back-to-stock or

inventory than retailers or wholesalers/distributors. Not supported

H8 Manufacturers will have more products repackaged and returned to stock than

retailers or wholesalers/distributors. Supported

H9 Manufacturers will have more returned products sold as scrap or destroyed than

retailers or wholesalers/distributors. Supported

H10 More product returns are refused by retailers than by manufacturers or

wholesalers/distributors. Supported

A surprising finding that has not been discussed widely in the literature previously was the recovery rates for

various return disposition options. In this study, product returns processing enabled many organizations to recover a

high percent of the original cost of the products. In some instances the recovery rates exceeded 80 %. Such levels of

recovery have not been widely reported previously. In fact, the typical level of 60-65 % recovery rate is higher than

expected given previously published data. This validates the importance of efficient and effective product returns

processing for improving profitability within organizations.

Studies have indicated the need to decrease the processing time and speed up the turn-around to maintain value

of the returned and reprocessed goods (Blackburn et al. 2004; Stock 2001). Results show that retailers are able to

recover a higher percentage of product value compared to wholesalers and manufacturers. This emphasizes the need

for the retailers and wholesalers, who are located closer to customers in the supply chain, to process the customer

returns instead of sending all or most product returns to suppliers. This will help not only to recover higher value for

the returned product but also helps to maintain the price levels for products in the distribution chain.

The use of outsourcing, or third-parties, for product returns processing has been widely discussed in the

business press. Many case studies have been presented about companies who successfully outsourced product

returns processing to various reverse logistics third-parties. While some organizations do outsource these activities,

results of this study suggest that the vast majority do not. Outsourcing of reverse logistics functions are partly driven

by the firm’s desire to redistribute the products quickly and thus recover value (Meade and Sarkis 2002).

52 STOCK AND MULKI

As determined in the site visits to companies, many of the large mass merchandisers such as Kmart, Sears, and

Target outsource at least a portion of their product returns to a third-party. In the manufacturing sector, electronics

and computer companies such as HP/Compaq outsource product returns, while firms such as CDW and Tech Data

handle returns internally. In the book publishing industry, most firms such as Harcourt and others perform product

returns processing internally. And so it goes; there is a great deal of variability in whether firms utilize third-parties

for processing returns, but in most cases, firms typically perform those activities themselves. As stated before, firms

base their outsourcing decisions on whether reverse logistics functions fit with the core competence of the firm and

based on the potential savings by eliminating expenses associated with activities such as evaluating returns and

repackaging them (Cottrill 2003; Gorick 2005). Lack of critical mass and economies of scale can also be a reason to

look for outside firms to handle product return functions (Discount Store News 1999; Gorick 2005). Thus, the

market potential for product returns outsourcing is likely greater than is presently thought, if, organizations can be

convinced that outsourcing is a viable alternative to doing it themselves. Most firms use existing facilities to handle

both forward and reverse logistics, so the market potential for outsourcing is significant.

This study found that retailers refuse a greater percent of returns compared to wholesalers and manufacturers.

Wholesalers reported refusing a higher amount from their customers (retailers) compared to manufacturer’s refusal

from wholesalers and retailers. As stated before, being close to the point of sale, retailers are often faced with more

customer returns and sales associates are reluctant to restrict returns because it might hurt sales. However, this

appears to be changing. Results show increased refusal from retailers pointing to a tightening of restrictions such as

time periods for return, receipt requirements, etc.

At the manufacturer level, product return transactions are primarily between them and wholesalers or retailers.

The transactions between manufacturers and retailers/wholesalers are generally more formalized with manufacturers

setting somewhat liberal policies of accepting all unsold products returned within prescribed periods of time.

Retailers have to consider manufacturer’s sentiments about costs and the margin impact of product returns (Rogers

and Tibben-Lembke 2001). There is an understanding on both sides about the need to reduce product return volumes

to maintain profitability. Manufacturers also realize that effectively designed vendor friendly return policies help

increase loyalty from some wholesalers or retailers (Rogers et al. 2002).

Very surprising was the fact that with so much academic and practitioner attention being given to benchmarks,

measurement and metrics relating to all aspects of supply chain management, so few organizations use published

standards for processing returns and evaluating elements or components of the process. The apparent lack of interest

in published standards needs to be explored to see whether productivity improvements could be possible with the

use of standards as might be expected intuitively. One would believe that with the higher level of manual operations

in product returns processing, significant improvements might be possible if organizations were measuring the cost

and service elements of the product returns process.

In sum, we posit that good product returns processing can result in improvements in profitability through cost

reductions and higher product recovery rates. It can also mean higher customer service levels as products being

returned are credited to customers sooner and more accurately (with fewer discrepancies). Organizations with

excellent product returns processing capabilities (defined as those having processes that are both efficient and

effective) can have a potential competitive advantage, which gets larger as the magnitude of product returns

increases. Through higher recovery rates of returned products and lower costs resulting from more efficient returns

processing, the “excellent” firms are able to maximize revenues and minimize costs, thus contributing more to the

firm’s bottom line.

As much of the literature on product returns has pointed out, many firms still do not place adequate emphasis on

the product returns process. They handle the product returns they receive, but they typically take longer to process.

Actual processing costs are higher and discrepancies and reconciliations are greater, and cause more customer

dissatisfaction. These firms are more likely to have part-time management personnel responsible for product returns

processing which is unlikely to provide the necessary oversight of the process to ensure optimal efficiency and

effectiveness.

Of course, the best way of optimizing the product returns process is to not have returns at all—referred to as

returns avoidance. Return avoidance policies aimed at minimizing product returns are becoming popular. These

strategies use customer education programs that focus on training the customer in the proper operation and use of

JOURNAL OF BUSINESS LOGISTICS, Vol. 30, No. 1, 2009 53

the product. This is critical since about 50 % of the product returns in consumer electronics are not due to product

defect, but due to customer difficulty in properly operating the product (Rogers et al. 2002). Retailer emphasis on

training customers in the proper use of their products can help in improving customer relations as well as decreasing

costs of product returns. Retailers can help a great deal by initial sorting and by making decisions on processing

versus returning to manufacturer. This could reduce the uncertainty in the timing and quality of returns that has been

blamed for the unpredictability of reconditioning and refurbishing returned products (Guide and Van Wassenhove

2002). The use of various return programs in retail stores that either encourage or discourage customers from

returning products are also important. The store policies on returns can have significant impact on the volume and

type of products being returned.

FUTURE RESEARCH

While the survey results revealed that firms are using metrics to measure and evaluate the product returns

process, much more needs to be done. Future research needs to be directed at establishing the specific criteria that

could be used to evaluate existing product returns metrics and to classify existing metrics from a process, rather than

functional, perspective (Caplice and Sheffi 1994). The metrics evaluated in this research study were identified in the

literature and by persons interviewed in the on-site visits, but that does not necessarily mean that they are the correct

metrics that should be used. Future research should evaluate these metrics using the eight evaluative criteria—

namely, validity, robustness, usefulness, integration, economy, compatibility, level of detail, behavioral soundness—

identified by Caplice and Sheffi (1994). This does not suggest that existing metrics being used are insufficient, but

the metrics were likely not developed with the eight criteria in mind and therefore may, or may not, be the right

measures.

Additional research on the standards being employed by companies processing product returns based on the

metrics selected could potentially reap significant rewards for companies. Historically, published standards have not

been researched by scholars, often because that information is proprietary. While proprietary issues are important,

data can be masked and the identification of key standards does not necessarily “give away” trade secrets or

competitive advantage. It is one thing to know what standards are being used by industry leaders; it is quite another

to have the right systems, policies and procedures in place and to implement these standards effectively and

efficiently. Such data will have to be obtained using qualitative research methods such as case studies. Companies

will typically not be willing to share such information in research that utilizes survey methods.

Additionally, more research utilizing hypotheses testing could be conducted. As indicated in the introduction to

this paper, many published studies, especially those in the trade or professional press, present anecdotal information.

While such information can be useful in aiding companies in pursuing better policies, procedures and programs,

they do not add a great deal to the “body of knowledge” relating to product returns specifically, and reverse logistics

generally. Specific research is needed on many aspects of product returns including such issues as cost recovery in

product returns disposition, optimal layouts of warehouses/DC’s when both forward and reverse logistics operations

are carried out in the same facility, acceptable return rates for various industries, companies and products, and

examination of the best methods of training and development of product returns employees.

While product returns processing is becoming more important, it is also vital that issues relating to eliminating

product returns be examined. For example, the return policies of retail stores impact whether or not customers return

items. Stock rotation and replenishment policies impact the number of items returned to vendors for credits as well

as product disposed of at the retail location. In the electronics industry, with some products being returned

fraudulently, research into the costs and benefits to retailers performing on-site inspections of returns could be

evaluated. Finally, the product returns process, which has been modeled descriptively by Stock (2004) and others,

could be more rigorously tested, with detailed flow charts of each stage of the process being developed. Stock

(2004) presented flow charts modeling each component of the five-stage process he identified, but these were only

examples used by companies in various industries. While they provide guidance to firms and researchers examining

product returns processing, generic process maps or flow charts need to be developed. This would provide a basis

for developing optimal product returns processing systems.

In sum, product returns will continue to be a part of business operations. In some fashion all members of the

supply chain are involved in the process. With increasing competition and higher customer demands, it is important

54 STOCK AND MULKI

that all facets of the supply chain operate at peak efficiency and effectiveness. As a part of the process, products

returns are no exception.

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JOURNAL OF BUSINESS LOGISTICS, Vol. 30, No. 1, 2009 57

APPENDIX

SURVEY INSTRUMENT

Survey on the Role of Warehousing in Product Returns Instructions: We would like to get information on how your firm processes and dispositions product returns. If specific data are not available to answer some items, please provide your best “guesstimate.” Please fill in each blank with the appropriate information. For responses requiring a YES or NO response, just circle the appropriate answer.

Part I. The Product Returns Process

1. Is there one person in your company who has primary responsibility for reverse logistics/product returns?

NO YES If YES, what is their job title? ________________________________________

2. Of all product returns received by your firm, what percentage is handled by:

__________ % Your firm

__________ % Third party __________ % at a dedicated returns facility

__________ % Combination __________ % in our regular warehouse/DC

100 % 100 %

3. For all product returns combined, what is the mixture of those returns?

__________ % planned (e.g., repair, end-of-lease)

__________ % excess/not planned

100 %

4. What is the size of your warehouse/DC where product returns are processed? ________________ sq. ft.

5. What portion of the warehouse/DC is devoted specifically to product returns operations? _______________ %

6. How many FTE employees do you have in your warehouse/DC that are involved in product returns?

__________ Production

__________ Administrative/clerical

__________ Supervisory

__________ Managerial

7. The wages (including benefits) of your full time non-management personnel that process product returns in the warehouse/DC are: ( only one)

_______ Higher than other warehouse/DC personnel

_______ Same as other warehouse/DC personnel

_______ Lower than other warehouse/DC personnel

8. How many labor shifts are used to process returns? ( only one) _______ one _______ two _______ three

9. What type of training does your firm provide for product returns employees? ( only one)

_______ Formal methods involving written training manuals

_______ Informal methods such as mentoring programs, but not including written training manuals

_______ No formal or informal training of product returns employees occurs at our facility

10. What percentage of your products are included in vendor/supplier “zero returns” programs? _______________ %

58 STOCK AND MULKI

APPENDIX (cont.)

RECEIVING:

11. How are product returns received by the warehouse/DC?

__________ % Gaylord’s containing multiple items

__________ % Individual items (loose packages, boxes, totes &/or cartons)

__________ % Pallets of the same or mixed items

100 %

12. Do you use “return authorizations” (RA’s) for product returns? YES NO

13. Do you require pre-approval of “return authorizations” prior to accepting product returns? YES NO

14. Are customers issued return authorization numbers before returning items? YES NO

15. How many product returns receiving stations do you have in your warehouse/DC? ____________________

MATERIAL HANDLING:

16. What equipment do you use in your warehouse/DC to handle product returns? Indicate how many of each item you use. If you do not use an item, place a zero (0) in the blank next to that item.

Number Equipment Type Number Equipment Type

_______ Forklifts

_______ Pallet jacks (electric & manual)

_______ Workstations

_______ Hand scanners

_______ Table scanners

_______ Belt conveyors

_______ Gravity conveyors

_______ Product containers (totes)

_______ Label printers

_______ Carts

_______ Hand held tape machines

_______ Automatic product sorters

_______ Box building machines

_______ Other: ________________

PROCESSING:

17. Are return authorizations computerized (e.g., available from the Internet or in other electronic form) or completed manually?

__________ % Computerized

__________ % Manual

100 %

18. For processing most returns, are receiving and customer crediting combined into one operation? YES NO

19. Do you utilize RETURN LABELS in the product returns process? YES NO

19a. If so, please identify the information contained on the returns labels:

YES NO SKU number

YES NO Customer name

YES NO Item description

YES NO Reason for return (reason code)

YES NO Date

YES NO Stocking location

YES NO Return authorization number

YES NO User ID of employee that processed the item

YES NO Other (please specify) ______________________________

JOURNAL OF BUSINESS LOGISTICS, Vol. 30, No. 1, 2009 59

APPENDIX (cont.)

SORTATION:

20. How are final sorted items assembled or accumulated (circle all that apply)?

UPC/SKU vendor customer disposition option product type Other: __________________

DISPOSITION:

21. Overall, what recovery rate do you get from returned products (respond for your most typical product return):

______________ % (as % of original cost) _______________ % (as % of units returned)

22. Does your firm do any product refurbishing, reconditioning and/or remanufacturing at your warehouse/DC where returns are processed, or are they performed at another location?

__________ % On-site

__________ % At another location

100 %

23. Please indicate for all of your products that go through the returns process, how they are dispositioned:

__________ % Returned directly to stock

__________ % Repackaged and returned to stock

__________ % Repaired or refurbished

__________ % Destroyed or sold for scrap/salvage

__________ % Third party/secondary market

__________ % Donated to charity

__________ % Other: ________________________________________

100 %

Part II. Product Returns Metrics

24. Are there published standards for each component of the product returns process?

YES NO Receiving (including unloading, distribution to processing stations)

YES NO Processing (including data entry, customer credit)

YES NO Sortation (including inspection, routing to disposition point)

YES NO Disposition (including put-away, repackaging, refurbishing)

25. For each of the following activities, please indicate the standards (they may or may not be engineered standards) that you utilize:

We use this metric? If used, what is the standard?

Pieces/returns handled by employee per hour YES NO ______________________________

Time from receipt to initial returns processing YES NO ______________________________

Number of pieces/items returned to stock per day YES NO ______________________________

Time from receipt to crediting of customer’s account YES NO ______________________________

Total pieces/unit/returns processed per day YES NO ______________________________

Error rates for items scanned (# or % of total) YES NO ______________________________

Error rates for incorrect disposition (# or % of total) YES NO ______________________________

Total returns processing time (from receipt to final disposition) YES NO ______________________________

60 STOCK AND MULKI

APPENDIX (cont.)

26. How much time (in hours) are spent on each of the following product returns activities?

Hours Task/Activity

__________ Receiving (including unloading, distribution to processing stations)

__________ Processing (including data entry, customer credit)

__________ Sortation (including inspection, routing to disposition point)

__________ Disposition (including put-away, repackaging, refurbishing)

__________ Total of all product returns activities

27. What is the warehouse/DC throughput time of returned products (total warehouse hours divided by # of units processed)?

__________ hours per unit processed

28. On average, what is the total labor cost per unit to process a typical product return? $ __________ labor cost per piece received

29. On average, what is the cost per unit/piece salvaged? $ ____________ cost per piece salvaged

30. In a typical month, what is the discrepancy rate of returned products received versus returned products that you were expecting (e.g., items returned did not match return authorization data, fewer or more items than indicated were returned)? ___________ %

31. What percentage of returned products received are returned to the sender because they did not meet the return criteria for the product?

_______________ %

Part III. Demographic Data This information is required in order to identify major market segments and to provide more meaningful analysis of the previous sections. Please use approximate figures in the event that exact data are not readily available.

32. Although your firm may be a multi-product company, can you provide an overall estimate of the value of product returns (in dollars or # of units) as a percentage of the total products your firm ships to customers?

__________ % based on dollars __________ % based on # of units

33. On average, at our returns processing warehouse/DC, we receive _________________ (estimated number) returned products/items/pieces each _________________ (per day, week, or month).

34. Type of Business or Organization ( the one most like your organization):

_______ Manufacturing firm

_______ Retailing firm

_______ Government/military

_______ Wholesaler/distributor

_______ Other: _________________________

35. Industry Category ( one category only if you indicated manufacturing or retailing firm in the previous question):

_______ Appliances

_______ Automotive & transport equipment (including parts and aftermarket)

_______ Building materials/lumber products

_______ Chemicals & plastics

_______ Clothing & textiles

_______ Computer hardware/peripheral equipment

_______ Department store/general merchandise

_______ Electronics & related instruments

_______ Food & beverage

_______ Furniture

_______ Hardware

_______ Metal products (fabricated)

_______ Office equipment & supplies (excluding paper)

_______ Paper & related products

_______ Petroleum & petrochemicals

_______ Pharmaceuticals, drug & toilet preparations

_______ Tobacco products

_______ Other: _________________________

JOURNAL OF BUSINESS LOGISTICS, Vol. 30, No. 1, 2009 61

APPENDIX (cont.)

36. What is your job title?

_______ Corporate officer

_______ Director

_______ Manager

_______ Supervisor

_______ Staff specialist

_______ Other: __________________________

37. What is your primary job responsibility (the one responsibility that requires most your time)? ( only one)

_______ General management

_______ Logistics planning/management

_______ Marketing/sales

_______ Reverse logistics/product returns

_______ Warehouse operations/management

_______ Other: _________________________

62 STOCK AND MULKI

ABOUT THE AUTHORS

James R. Stock (Ph.D. The Ohio State University) is Frank Harvey Endowed Chair in Marketing at the

University of South Florida, Tampa. He holds B.S. and MBA degrees from the University of Miami (FL). He

previously held academic faculty appointments at the University of Notre Dame, University of Oklahoma, Air Force

Institute of Technology and Michigan State University. Dr. Stock has published more than 120 publications

including books, monographs, articles and proceedings papers. He formerly served as Editor of the International

Journal of Physical Distribution and Logistics Management and the Logistics Spectrum (published by SOLE). Dr.

Stock has received both the Armitage Medal and Eccles Medal from SOLE—The International Society of Logistics.

He is a frequent speaker at international meetings and other events held in Africa, Asia, Europe and South America.

Professionally, he works extensively with the Council of Supply Chain Management Professionals (CSCMP) and

the Warehousing Education & Research Council (WERC). His major areas of research interest include reverse

logistics and product returns, the marketing/logistics interface, and supply chain management.

Jay Prakash Mulki (Ph.D. University of South Florida) is an Assistant Professor of Marketing at Northeastern

University, Boston, MA. He holds B.S. degree in Chemical Engineering from the University of Mysore (India), and

a MBA from University of Hawaii at Manoa. Professor Mulki brings both academic research and business practice

to his classroom. He has spent nearly 20 years in business, holding senior positions in Fortune 500 companies

before leaving business to pursue his academic interest. In February 2008, Professor Mulki was honored with the

Renfro Fellowship, an award given by the University to recognize consistent achievement in research and for

someone “held in high regard for the quality of his/her teaching.” His research has been published in Journal of

Business Research, Psychology & Marketing, Journal of Personal Selling and Sales Management, International

Journal of Service Industry Management, Journal of Marketing Theory & Practice, and Journal of Business Ethics.

Contact author: James R. Stock, E-mail: [email protected]