CATALOG RETAILER IN-STOCK PERFORMANCE: AN ASSESSMENT OF CUSTOMER SERVICE LEVELS

Taylor, John C

The purpose of this article is to provide insights into the degree to which firms are actually delivering on the promise of modern day supply chain management. The research reported here examines the level of in-stock customer service levels in the catalog retail channel, and provides comparisons to the level of service found in prior studies of the bricks and mortar retail channel. A number of leading supply chain management logistics textbooks and articles have focused on the evolution of the supply chain and its ability to deliver excellent service levels at low cost. For instance, one leading text states that:

The frequent occurrence of service failures that characterized the past is increasingly being replaced by a growing managerial commitment to zero defect or what is commonly called six-sigma performance. Perfect orders - delivering the desired assortment and quantity of products to the correct location on time - once the exception, are now becoming the expectation (Bowersox, Closs, and Bixby 2002).

Given this level of expectation, what level of customer service, in terms of on-shelf in-stock position is actually being delivered by retailers at the end of the supply chain?

Success in retailing clearly requires high levels of customer service as suggested by the above quote. Indeed, as retailers have increased their drive to capture a "lifetime stream of profits," they have increased their emphasis on customer loyalty, which is built on customer service (Blackwell 1997). One recent study noted that loyalty is critical to long term profitability - reporting that a 5% increase in customer retention can lead to a 25% increase in profitability (Lowe 2002; Reichheld 1993). Retailers have long sought to build long-term relationships with their best customers by offering convenient locations, fast check-out, and high levels of in-stock product availability. Among these variables, none has received more attention in recent years than assuring that products are available when and where the customer wants to buy them. Much of Wal-Mart's success has been attributed to its ability to keep its shelves consistently stocked with low-cost products (Fawcett 2000; Stalk, Evans, and Schulman 1992). By contrast, K-mart has been singled out as a poor in-stock company, with many analysts citing this as a key reason behind the retailer's bankruptcy filing (Merrick 2002; Moses 2001). An executive at Kohl's reiterated the central role of product availability, saying, "in retailing, the single biggest customer service complaint is not having the item" (Faircloth 1998). In today's hectic and hurried world, customers simply do not have the time or the desire to search for unavailable products (Fawcett and Cooper 1998). And while the single occasional stockout may not be a problem, repeated stock-outs of multiple items, for long periods of time, can be especially problematic for retailers. Stock-outs rapidly lead to dissatisfaction and the possibility that the customer will opt to "try the competition" (Zeithaml, Berry, and Parasuraman 1993). If the customer service experience at the competition leads to a high-satisfaction outcome, the customer may be lost forever, eliminating a lifetime stream of profits.

While product availability is an important concern for almost all retailers, it is absolutely vital in the distance-shopping retail sector, which is comprised of catalog and e-commerce retailers. Distance-shopping offers convenience, but is highly impersonal with minimal human interaction (Verdisco 2000). Thus, the distance-shopping environment forces participating retailers to focus on customer service via fulfillment. Unlike their bricks and mortar counterparts, catalog and e-retailers do not have the opportunity to differentiate themselves on variables such as store location, instore contact with staff, merchandising attractiveness, or general store atmosphere. These variables are well established as critical to establishing satisfaction and determining long-term purchase intentions (Baker, Levy, and Grewal 1992; Bitner 1992; Donovan and Rossiter 1982). Because these variables are not available in the distance-shopping environment, product availability and fulfillment become primary factors in a reduced set of variables available for achieving differentiation (Eroglu, Machleit, and Davis 2001).

In distance-shopping, the ultimate goal is the hassle-free delivery of product to the customer - nothing is more frustrating than finding a desired product is out-of-stock (Verdisco 2000). The importance of product availability in distance-shopping was recently highlighted by a study that found that 41% of shoppers cited stock-outs as the reason for abandoning their on-line shopping carts (Red Herring 2001). Another study reported that poor initial experiences dramatically reduce the likelihood that a distance-shopper will return (Neuborne 2000). Exacerbating the challenge is the fact that distance-shoppers' fulfillment expectations have been raised to a new level by the promises of an e-commerce society. Emphasizing the need for rapid fulfillment in online retailing, one analyst commented, "there's a demand for speed that these orders carry with them" (Cooke 2000). Another executive elaborated on this idea, noting, "When customers order on the internet by noon, they expect the order to be shipped out that afternoon" (Cooke 2000). While these expectations have been generated by e-retailers, they have created a new "e-consumer species" with a "click and you shall receive" mentality that extends to catalog and, to a lesser extent, other retailers as well (Eckley 2001). Thus, it has been said that, "logistics and fulfillment are crucial operations to direct marketing channels" (Direct Marketing 2001) and "almost overnight, fulfillment has grown to be a strategic issue" (Eckley 2001).

The research reported here examines the ability of catalog retailers to provide high levels of in-stock product availability. Catalog retailers have been around far longer than e-retailers and should have the experience needed to excel in the fulfillment dimension of customer service. As one analyst noted, "catalog companies already have strong distribution and delivery capabilities" (Sullivan 2000). Another analyst claimed that all retailers should look to catalog retailers for a model of how to operate fulfillment efficiently (Gourley 1996). Even so, there is some question about the ability of catalog retailers to deliver efficient and effective fulfillment. For example, Federated's Fingerhut catalog division established a business model based on its delivery expertise where it offered to manage the fulfillment requirements of e-retailers. Fingerhut initially won fulfillment contracts from 22 e-retailers, but within a couple years was down to eight because of complaints about "poor fulfillment service and poor inventory controls" (Berner 2000).

Given the importance of customer service in the modern supply chain and the expectation of near perfect orders, and given the importance of customer service in the catalog channel, this research is focused on trying to better understand the level of in-stock performance actually being delivered to end consumers using this channel. The key research questions then are:

* How good a job are catalog retailers doing of achieving a high initial fill rate in their offerings?

* How well do catalog retailers do on this measurement compared to bricks and mortar retailers?

THE IN-STOCK CHALLENGE AT CATALOG RETAILERS

Catalog retailers had total sales of $126.0 billion dollars in 2002 (Benman 2003). While these sales represented only 4% of the overall $3.2 trillion U.S. retail sector, almost 50% of all consumers are believed to have made purchases via the catalog retail channel (Hansen 2001). Catalog retailers play a stronger role in certain sectors, such as in apparel where catalog sales totaled $17.2 billion or 9.4% of the total $183.9 billion sold across all channels in 1999 (The NPD Group 2001). Even so, the overall industry is quite fragmented with over 8,500 catalogers in operation in 2000, distributing over 14.3 billion catalogs a year (Coleman and Blackmon 1999; Reinartz and Kumar 2000).

It is within this unique channel that the investigation of in-stock performance was carried out. While very little past research has been conducted regarding in-stock performance in the catalog retail industry, some insight can be gained by evaluating the broader literature concerning retail in-stock performance. The following points have been made:

* Stock-outs have been identified as a problem in numerous studies since 1968, with stock-out rates ranging from 4 to 12.2% (Mason and Wilkinson 1981 ; Progressive Grocer \ 968; Schary and Becker 1980; Supermarket Business 1996; Taylor and Fawcett 2001). In the most recent study, the stock-out rate was 7.6% for non-advertised items and 16.5% for advertised items (Taylor and Fawcett 2001). Zinn and Liu (2001) also recently reported on the results of an experiment on stock-out impact and reviewed much of the above literature while concluding that stock-out rates vary considerably by retail format.

* Stock-outs adversely impact company performance, leading to lost sales, dissatisfied customers, decreased market share, and increased costs (Emmelhainz, Emmelhainz, and Stock 1991; Emmelhainz, Stock, and Emmelhainz 1991; Schary and Becker 1980; Schary and Christopher 1979; Walter and Grabner 1975; Zinszer and Lesser 1981). The study by Zinn and Liu (2001) also found that consumers are generally able to separate a single and recent stockout experience from other dimensions of their overall attitude toward a store, casting some doubt on the general perception that stock-outs significantly damage a store's overall image.

* Sound logistics practice plays a key role in both reducing the incidence of stock-outs and assuring higher levels of customer service and satisfaction (Rinehart, Cooper, and Waggenheim 1989; Sharma, Grewal, and Levy 1995; Stank, Daugherty, and Ellinger 1997; Sterling and Lambert 1989).

Improving initial fill rates to enhance customer satisfaction is clearly a vital concern for retailers. Astute management of logistics issues including forecasting, inventory control, SKU management, and quick replenishment can help mitigate the stock-out challenge.

While actual stock-out rates in the catalog channel have not been quantified, industry executives estimate that catalog retailers achieved an 88% initial fill rate in 1998 while targeting an initial fill rate of 92% (Dowling 1998). Assuming the executives were well informed regarding their companies' actual performance and given recent advances in information technology and logistics practice coupled with intensified retail competition, catalog retailers should be achieving in-stock initial fill rate levels in excess of 90%. The question arises, "Have catalog retailers met and exceeded the goal of 92% initial fill rate?" Again, given the emphasis on operational excellence and continuous improvement, this study's first research hypothesis can be stated as follows:

Hypothesis 1: Catalog retailers provide an overall level of service consistent with a goal of an initial fill rate of 92% and believe they are actually achieving an initial fill rate of 88%.

Catalog retailers possess certain advantages and disadvantages as they battle their bricks-andmortar competitors. The primary disadvantage catalog retailers face is physical distance from customers which limits the opportunity to use store location, personal contact, and in-store ambiance as competitive differentiators. However, this lack of opportunity to use physical differentiators makes it all the more important for catalog retailers to differentiate themselves on in-stock position, and we believe this should move them to have superior in-stock performance as compared to bricks and mortar retailers. The primary advantages are operational - catalog retailers tend to have narrower assortments and more centralized distribution (Direct Marketing Association 2001).

In fact, in our sample of retailers, 60% had one DC, 25% had two DCs and just 15% had three or more. This centralized distribution should allow for economies of scale in safety stock levels, technology investment, and overall operations. Catalog retailers have a further advantage in that they don't have to deal with a number of bricks and mortar store operations constraints such as those relating to shortages of labor and management at the store level necessary to move stock from backrooms to the shelf. All of these factors should allow catalog retailers to offer higher in-stock initial fill rate performance at a given cost level. Strategic management suggests that companies leverage their advantages to overcome disadvantages and achieve some competitive advantage (Barney 1991; Hofer 1975; Porter 1980). Thus, catalog retailers should emphasize operational excellence to achieve consistently higher initial fill rates than traditional retailers. This fundamental idea leads to the study's second hypothesis.

Hypothesis 2: Catalog retailers have a lower stock-out percentage than their bricks and mortar counterparts.

While catalog retailers operate under unique circumstances, they share many of the challenges faced by bricks and mortar retailers. Perhaps the greatest challenge in retailing is having the right product selection in the right quantities to meet customer demand. Indeed, this is the essence of the stock-out dilemma - carrying sufficient inventory to meet customer demand 100% of the time is cost prohibitive. The managerial challenge is to make the tradeoff between inventory cost and customer service. Of course, better forecasting and more rapid replenishment should enable companies to improve service and lower inventory levels simultaneously.

The difficulty inherent in matching supply to demand manifests itself in several ways. For instance, approximately one-third of all catalog sales occur in the relatively compressed Christmas season (Grant 2001). Predicting exactly what will be "hot" in anticipation of the hectic Christmas season is a serious challenge since mistakes lead to either stock-outs or markdowns. The challenge is exacerbated by the fact that many Christmas orders must be placed with the manufacturer in the previous spring. Given the high demand, compressed season, and difficulty in forecasting customer preferences, it would seem likely that Christmas out-of-stock rates might be higher than during other times of the year. A similar challenge exists for other seasonal and specialty goods, which are often purchased as special, one-time buys and then heavily promoted (Del Franco 2001).

In a perfect world, a catalog retailer would order the right quantity of high-demand seasonal merchandise (no excess inventory and no stock-outs); however, accurate forecasting for such items is very difficult and would likely lead to higher stock-out rates than for year-round merchandise. Similar logic applies to retailer type. That is, apparel retailers are much more fashion sensitive than other catalog retailers and would expect to experience greater difficulty in having the right products - right styles in the right colors and sizes - than counterparts in other sectors such as general gift or category killers. A final supply-and-demand issue involves having enough inventory to meet demand for the duration of a catalog's life. In the first weeks following the mailing of a catalog, fulfillment levels should be very high. However, as the weeks pass, demand uncertainty leads to deteriorating in-stock performance. That is, if the catalog retailer misses the forecast and lacks rapid replenishment capability, stock-outs are more likely to occur the further out from the date of issue of the catalog. These unique supply-and-demand challenges are examined via the following hypotheses.

Hypothesis 3: Stock-out rates are higher during the Christmas season than they are in the summer.

Hypothesis 4: Stock-out rates are higher on high demand promoted items than on randomly selected items, with high demand items being defined as those that would appear to be of high interest and that were promoted.

Hypothesis 5: Stock-out rates are higher for apparel retailers than for general gift or category retailers.

Hypothesis 6: Stock-out rates will increase each week after release of the catalog.

METHODOLOGY

An empirical observational design was developed to investigate the above-stated hypotheses. Catalogs from 200 retailers were gathered and separated into three categories: apparel, general gifts, and category specific retailers. Market dominance and service reputation were used to select the companies to be examined. While there was no foolproof way to estimate market dominance and reputation, our goal was to select the best-known companies from among the catalogs in the pool. The final sample included nine apparel retailers, nine general gift retailers, and seven category killers. Many of the best-known, highest-reputation companies in the catalog business were included. Category killer retailers included kitchen appliances, toys, and home improvement. Office supplies and industrial tools/woodworking supply catalogs were not included because they represented a mix between consumer and business-to-business retailers. Based on available public records, the retailers in the sample had catalog sales of $6.75 billion, and represent about 6% of total consumer catalog sales.

To select specific catalogs for the retailers in the sample, the catalog companies were called to assure that one of the authors was on the mailing list for the retailer. When catalogs were received in the mail, the date of arrival was recorded. Catalogs were examined to make sure none were "clearance" or "special sale" oriented. The catalogs were then reviewed to pick high-demand promotional items and random items. To be selected as a high-demand item, the item had to be promoted in some special or unique way. These items were judged to be of high interest to consumers and were promoted on key pages or in special sections of the catalog. Key pages included those near the order entry page, front and back covers, and special sections. Random items were selected by picking a random item from every nth page in the catalog, where the nth page was the total number of pages divided by the number of items being selected. For each selected item, a specific SKU, and where appropriate, color and size, were noted. Standard colors and sizes were chosen. All high-demand and random items were also reviewed to make sure no "limited quantity" or similar provisions applied.

Each retailer was then called four times, with the initial call coming one week after receipt of the catalog, and the subsequent calls being made once a week thereafter until four weeks of calls were completed for that retailer. This methodology models the actual process and experience of the consumer, capturing the "out-of-stock" experience that an actual customer would have up to the point of actually placing an order. This research method was pre-tested prior to selection of the final sample. Retailers were evaluated during a winter season that extended from late October to early December as well as during a summer season extending from June to July. For the pre-Christmas sample, 12 items were selected from each catalog, half random and half high demand. For the summer season, 24 items were picked from each catalog, again half random and half high demand. A total of 25 catalog retailers, 820 items, and 3,360 checkpoints were examined.

In order to check stock status, each catalog's toll-free number was called one week after receipt of the catalog. Calls were counted only if the operator had access to stock status data and could confirm the stock status of each item (several operators did not have access to this data at night). In those cases where the operator did not have stock status data at night, a call back was made the following day to obtain the stock status. After all items were reviewed, the caller completed the call by thanking the operator. In some cases, repeat calls were required to complete the entire list of items. Items were recorded as in-stock if the specific SKU was actually in stock at that time. If the exact SKU was not available, was back ordered, or had been discontinued, it was recorded as out-of-stock. This process was repeated weekly until each catalog had been called four times. As noted above, the entire process was performed twice to cover both Christmas and summer seasons.

RETAIL IN-STOCK PERFORMANCE AND CATALOG RETAILERS

Figure 1 summarizes the overall stock-out performance using two measures: 1) the percent of all checkpoints with an out-of-stock condition (total out-of-stock % for all checkpoints) and 2) the number of items that were out of stock at least once during the evaluation period (at least once during the four checkpoints).

For the total sample (summer and Christmas combined), items were out-of-stock 15.9% of the time. Items stocked out at least once almost twice as often at 28.9%. Stock-out rates are thus considerably higher than industry executives have estimated in recent years and initial fill rate is significantly below the 92% target. This catalog in-stock performance was also significantly lower (p=.05) than the bricks and mortar stock-out rate of 11.8% (see Figure 2) reported in a 2001 article in JBL (Taylor and Fawcett 2001).

Interestingly, the greatest difference between bricks and mortar and catalog in-stock performance occurred among the random items. Specifically, the two channels had similar stock-out rates for "advertised" and "heavily promoted" items (18.5% for catalog retailers and 16.5% for traditional retailers) whereas catalog retailers had a stock-out rate of 13.4% for random items, compared to a 7.6% on-shelf stock-out rate for random items at traditional retailers (see Figure 3).

It is highly doubtful that catalog retailers purposefully stock-out at this level given the nature of today's competitive environment. Demanding customers, fierce rivals, heavy promotional spending, employment of automated order entry and fulfillment systems, and stated industry goals all point to a real need and a sincere desire to achieve high in-stock performance. Rather, these findings reflect a systematic failure in the supply chain somewhere between the supplier, catalog buyers, and catalog retailer fulfillment personnel. An over reliance on one-time buys combined with the challenge of implementing the advanced technologies needed for streamlined fulfillment management throughout the supply chain may underlie the lower-than-expected performance. Clearly, the findings emphasize the continuing challenge to logistics managers in the areas of forecasting, inventory control, and replenishment management.

Moving beyond overall performance to look at the challenge of matching supply to demand under specific circumstances reveals that, as a rule, managers still struggle to obtain accurate forecasts of customer preferences. Focusing first on Christmas-related seasonally, it is interesting to note that the overall stock-out rate did not vary significantly between Christmas and summer selling seasons (16.4 versus 15.7% respectively). However, significantly (p=.05) more items stocked out at least once during the Christmas period compared to the summer season (36.6 versus 25.4% respectively). Although this finding reveals an inability to initially match supply to demand during the volatile Christmas season, it suggests that managers were able to recover and improve their stock position before the end of the study period on at least some occasions. Unfortunately, many retailers never get a second chance to fulfill the purchase desires of individual customers who are pressed to get their Christmas shopping done.

The difficulty in managing high demand items was further confirmed by the comparison of instock performance for high-demand, promoted items versus randomly selected items. Keeping in mind that in this study high demand items are promoted items, the data displayed in Figure 3 visibly show that high-demand items stock out much more frequently (p = .05) than randomly selected items. This finding holds true for all three samples (combined, Christmas, and summer). Catalog retailers continue to wrestle with the challenge of adequately forecasting and replenishing high demand promoted items. The same phenomenon is apparent in the management of fashion-sensitive, SKUcomplex settings. The bar charts shown in Figure 4 reveal that apparel catalog retailers have the greatest difficulty in meeting customer fulfillment expectations.

Apparel retailers stock out significantly (p = .05) more frequently than category-specific catalog companies. The combined challenge of ramping up "hot" items and phasing out "dogs" while getting size and color combinations exactly right makes rapid replenishment via information sharing and relationship building particularly important to apparel retailers.

Finally, the data in Figure 5 show that catalog retailers do indeed stock out more often in the later weeks after a catalog mailing.

For the combined sample the stock-out rate rose from 13.6% just after receipt of the catalog, to 19.4% four weeks after receipt. In-stock performance deteriorated most visibly for the preChristmas sample, with out-of-stock levels increasing from 10.8% after one week to 24.8% after four weeks. (It should be noted that the fourth pre-Christmas checkpoint was no later than December 17.) In-stock performance diminished only slightly over the four-week summer examination period.

High levels of product availability require careful merchandizing, accurate forecasts, and the ability to re-supply as actual demand conditions dictate. Once again, the study findings reveal both initial forecast accuracy and replenishment capability are problem areas. Relatively high stock-out rates immediately after issuance of the catalog highlights the challenge of getting good initial forecasts. Deterioration in stock-out rates over the four-week evaluation period highlights a lost opportunity for catalog retailers as well as the very real potential for alienating customers. The poor immediate pre-Christmas performance is especially glaring given that many of these retailers advertised on their covers "guaranteed" delivery for orders placed up to December 21 or thereabouts.

IMPLICATIONS OF STOCK-OUTS AT CATALOG RETAILERS

Catalog retailers were out-of-stock at 15.9% of all monitored checkpoints - an amazing one in every six purchase occasions. This is a surprisingly high level in today's intensely competitive marketplace where relationship marketing, state-of-the-art logistics, and automated replenishment systems are being embraced. Among the most interesting findings was the fact that catalog retailers had significantly worse stock-out performance than their traditional bricks and mortar counterparts (Taylor and Fawcett 2001). This lower in-stock performance occurred despite the catalog sector's documented advantages of narrower assortments and centralized distribution.

Stock-out situations greatly diminish a primary benefit that comes from buying via catalog the convenience of shopping from your own home. Since catalog retailers lack the opportunity to differentiate themselves via physical proximity, immediacy, personal contact, and experience marketing, the failure to consistently have products in stock is a serious problem. The only real advantage left for catalog companies is to sell products nobody else does. This advantage will be increasingly challenged in a world dominated by super-centers and e-commerce. The in-stock challenge is magnified by seasonality, product velocity, SKU complexity, and the passage of time. Unfortunately, these conditions are facts of life in the retail sector and are unlikely to change in the foreseeable future. The bottom line is that catalog retailers are doing a poor job of living up to their implicit promise of having product in stock when customers want it, especially in the critical weeks leading up to Christmas. The question is, "Why?" The answers may be found in a combination of the following speculative factors, which also present opportunities for future research:

* With a stated goal of 92% initial fill rate, catalog executives have set a remarkably low target that fails to inspire higher levels of performance. The low goal also makes it difficult to cost-justify needed investments in information systems and relationship building needed to more accurately gauge demand and achieve rapid replenishment.

* Forecast accuracy continues to be inadequate (Ferriels 2001). Catalog retailers are too reliant on guessing demand and have failed to leverage their position to track individual customer preferences. While many other retail sectors have sought to implement store cards to better track purchasing patterns of preferred customers, catalog companies have not effectively used the information that they already have regarding customer purchasing habits. They have thus failed to more accurately predict future purchases and have failed to manage demand through tailored promotions. We would note however that these problems are not limited to catalog retailers, and that there are varying degrees of success in utilizing this kind of information at both catalog and bricks and mortar retailers.

* In today's lean-logistics world, it is possible that companies have reduced their inventory levels too much. More than one company has made inventory reduction the goal instead of focusing on lean practices to simultaneously improve efficiency and enhance customer service. Managers must be ever vigilant to take a total cost approach that evaluates all of the costs of a decision-those seen as well as those that are hidden. In a world where substitutes exist, failing to fulfill the needs of one in six customers may be too high a price to pay for lean inventories.

* Catalog retailers often engage in one-time buys that they then make available to their customers. For these purchases, there is no intent to re-supply. Thus, if the initial demand forecast underestimates total demand, quick replenishment is impossible. While Costco and Sam's Club endeavor to create a treasure hunt mentality, most catalog companies are likely to engender more dissatisfaction than curiosity by stocking out of popular items. Catalog retailers must re-evaluate how they communicate the availability of these one-time buy items.

* Many catalog retailers are relatively small, specialty retailers. Lack of size and scale can limit a catalog retailer's ability to enter into collaborative, quick-replenishment relationships with key suppliers. Either they lack the clout or the managerial skills to enter into and manage for rapid re-supply. To the extent that a quick-replenishment model cannot be pursued, greater emphasis is placed on accurate forecasts.

The fast-paced, hectic lifestyle of today's affluent consumer makes distance buying via catalog or web site very attractive for an increasing number of shoppers. To assure the viability of distance shopping, these retailers need to assure that they can adequately meet the fulfillment requirements of their customers. For catalog retailers, this reality probably requires that managers revisit the instock dilemma, setting more rigorous goals as well as investing in systems and relationships capable of identifying fast-moving items and replenishing these items before they stock out. Greater emphasis on tracking customer preferences and tailoring merchandizing efforts may also be needed. These efforts may require changes in both strategy and structure. For e-retailers, the challenge is to avoid the stock-out pitfalls that are prevalent among catalog retailers. Consumers will not always be patient with companies that cannot deliver on their promises of a convenient, hassle-free shopping experience.

LIMITATIONS AND FUTURE RESEARCH

The cost associated with data collection created a need to limit the number of catalog companies evaluated as well as the number of items checked for in-stock availability. The limited sample size is thus the greatest study limitation. Another limitation is created by the fact that the researchers had to rely on operators for data access. It is quite possible that the out-of-stock rates are understated since the design relies on catalog operators stating that an item is out-of-stock. Operators may be biased towards telling the customer that items are in stock - even when they may not be. However, given the level of reported stock-outs we do not believe this was a significant problem. Future studies should attempt to increase the number of catalog retailers examined as well as increase the number of items selected and the time frame over which stock position is measured. A joint academic-industry study would be ideal. This study should also be extended to e-retailers, at least for those that report in-stock status on-line. We would expect them to have more advanced technologies, enhancing their in-stock performance. However, the one study that has looked at e-retailer fill rates reported a 14% stock-out rate (Operations and Fulfillment 2001). Finally, a survey of catalog retail fulfillment executives and/or case studies about the cause of out-of-stock rates in the catalog industry could add insight into the reasons for the relatively poor performance of this retail channel.

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John C. Taylor

Grand Valley State University

Stanley E. Fawcett

Brigham Young University

and

George C. Jackson

Wayne State University

ABOUT THE AUTHORS

John C. Taylor (Ph.D. Michigan State University) is Associate Professor of Marketing and Logistics, Seidman School of Business Administration, Grand Valley State University, Grand Rapids, Michigan. His research interests are in logistics performance and effectiveness, transportation policy, intermodal and rail transportation, and international logistics and transportation. He is a former member of the U.S. Department of Transportation's National Commission on Intermodal Transportation and the National Motor Carrier Advisory Committee. His research has appeared in the Journal of Business Logistics, Transportation Journal, International Journal of Logistics Management, and other academic journals.

Stanley E. Fawcett (Ph.D. Arizona State University) is the Donald L. Staheli Professor of Global Supply Chain Management, Marriott School of Management, Brigham Young University, Provo, Utah. An active researcher, he has published more than 75 articles in the areas of global supply chain management, comparative manufacturing systems, strategic purchasing, performance measurement, and global network design and management. His work has appeared in the Journal of Business Logistics, Transportation Journal, International Journal of Logistics Management, and many other leading journals.

George C. Jackson (Ph.D. Ohio State University) is Associate Professor of Marketing and Logistics at the School of Business Administration, Waync Slate University, Detroit, Michigan. His research interests are in the area of logistics and transportation management, intermodal transportation, and logistics performance and customer service. His research has been published in the Journal of Business Logistics, Transportation Journal, International Journal of Physical Distribution and Logistics Management, and a number of other leading academic journals.

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