A key problem in retail management is the fix of adequate product variety, and perceived variety, through management of stock on hand. In managing this process, the retailer must strike a balance between over-stockings such that inventory management costs are higher than they need be, and risking stock outs that potentially result in lost sales and possible long term negative erect. In practical retail settings such as those encountered in the supermarket retailing industry, this process involves literally thousands of individualist skus (stock keeping units).
A number of prior studies have examined how creation unavailability (via a temporary stock out) influences sales for a presented product (sku). In this paper, we extend this analysis and also take a somewhat deferent view. That is, we not only consider sort sales for a presented manufacturer, but also analyze the impact o stock outs on collection sales for a retailer. Viewed from the retailer's perspective, the potential sales expiration in a collection could be realized as digit of three possibly interdependent outcomes. First, a consumer could move to a stock out on a preferred creation (i), by purchasing another (j). In this case, on a presented shopping trip, collection revenues and profitability surer only to the extent that j is a less desirable sale for the retailer. Second, the consumer could end to defer purchase in the creation category. Third, and perhaps most serious, the consumer could switch stores either on the current trip or at forthcoming visits. In this environment, it is essential for the retailer to understand: (1) the extent to which each behavior occurs, and (2) the relationship between these consumer outcomes and potential exogenous drivers, such as the severity of the stock out, no uniformity in consumer preferences over the inexplicit creation miscellanea and the type of creation category. Furthermore, in considering these three activity outcomes (switching, deferral, accumulation switching), and their interdependencies, it is also essential to consider time-dependence and the cumulative impact of stock outs over time. For example, a consumer who repeatedly encounters stock out on favorite sort may initially move by deferring purchase in the category, but ultimately may end up change stores.
Practically, stock outs are an extremely important managerial problem. Their prevalence in consumer settings has been well documented, as stock out levels of 10-30% have proven to be the norm, rather than the exception in many retail settings.
In a recent study of national supermarket chains (Andersen Consulting, 1996), 8.2% of items were out-of-stock on a exemplary afternoon (this rate was more than 15% for advertised items). The stock out problem was worse in categories such as bottled water (10.7%) and chilled juice (10.0%), and modify ranged nationwide from 8-10% for such staple items as milk. A 1987 Consumer Reports study of mail-order companies showed that this issue is not to traditional retail settings, as demonstrated by the fact that mail-order customers reported out-of-stock items as their most frequent complaint. From a managerial viewpoint, the prevalence of stock outs have a number of implications that result in everyday trade that must be made. Balancing the benefit of adding more products to a collection with the cost associated with the higher likelihood of stockpots, and balancing the outlay of maintaining a certain level of inventory versus the outlay of stock outs (both monetary and ill-will), are only two of many traders the retailer must consider.
The greater part of out-of-stock studies in the marketing literature are empirical in nature. These studies point to a difference of stock-out reactions. Consumers can: switch to another product, buy the missing component in a competing store, defer the acquire to a next shopping occasion, or drop the acquire altogether (Corstjens and Corstjens, 1995). Some researchers attain a further distinction between switching to another brand and/or variety- an option referred to as "item switching" hereafter-and switching to another package size. The empirical studies expose that component switching is the predominant reaction, followed by filler switching. Store switching and canceling/deferring the acquire are less often observed, yet remain important as they haw entail serious perverse consequences for the manufacturer and/or retailer. 220 Journal of Retailing Vol. 76, No. 2 2000 The studies mentioned above provide valuable, but fragmented insights into factors linked with the heterogeneity in OOS responses. Reaction differences hit been related to product-, consumer-, and situation-characteristics, such as the perceived venture of product substitution, degree of loyalty towards the OOS component and OOS store, the urgency with which the creation is needed, and acquire motivation (Schary and Christopher, 1979; Emmelhainz et al., 1991)
Ideally, an calculation of the outlay of a stock out should consider both its realizable and intangible components. The realizable factor is easily quantified by the contribution margin of the unsold item. The intangible factor is trickier. Consumers may reduce forthcoming purchases and influence other consumers with perverse comments. In addition, there may be a additive gist by which a second or third stock out happening will have a stronger perverse impact than the first one. In contrast, consumer loyalty to the accumulation may be so strongly based on a assorted variable (e.g. price, location, or lack of competition) the gist of stock outs is negligible.
The 1968 Progressive Grocer niudy was a ordering of digit writing documenting the frequency of stock outs observed for items sold in supermarkets.\" In oppositeness to prior stock out studies that tried to judge the outlay of a stock out on the foundation of unsold inventory only. Progressive Grocer looked into consumer behavior. When recording stock outs, a difference was prefabricated between availability of creation on shelves and availability in the store; the latter message that the creation is only acquirable in the accumulation backroom. The learning also reported breakdowns for creation categories, life of the week, levels of sort loyally captured by certain creation categories, and most importantly-SDL response.
In examining the reactions of liquor accumulation customers in Ohio. director and Grabner additional lo the think of SDL salutation by proposing a conventional help that charted al! possible responses to stockrooms
Consumers were to analyze where they had to inform intended activity following the stock -Out. After recording the frequency of stock outs and the intended responses, director and Grabner then estimated the outlay of stock outs. An important contribution of this think was the scheme for systematically classifying flavored possible consumer responses to stock outs. which influenced most SDL studies that followed.
Shycon and Sprague also proposed a help for estimating the cost of stock outs. But focused on the indiscriminate level. They used stock out probabilities to judge the likelihood of retailer reprisals for supplier service failures. Therefore, both models were looking at client salutation as a means to judge the outlay of stock outs. Both methods prefabricated key assumptions in their estimations. For example. Waiter and Grabner assumed that an out-of-stock item would be acquirable in a week. Shycon and Sprague's assumptions were based on averages obtained in pilot studies (proportion of out-of-stocks that resulted in forfeited sales).
A unique move was developed by Charlton and Ehrenberg. Instead of using surveys, they conducted an experiment. For 25 weeks, 158 consumers were visited at home and given the opportunity to purchase from a activity of three brands apiece of purifying and of tea. The brands were especially created for the study. Stock outs were introduced during the study, and the activity of consumers measured. Consumers typically substituted the out-of-stock sort but returned to it with the restoration of supplies. Motes and Castleberry conducted a partial copy of the think using actual brands of potato chips and cereal. They obtained kindred results indicating a sort switch activity to the stock out followed by a convey to the preferred product once the stock out condition was eliminated. These digit studies did not consider the possibility of switching stores in salutation to the stock out.
Senary and Becker also investigated the long-term gist of an out-of-stock condition.11 The opportunity arose from a Teamster strike in Seattle in 1971 that limited the cater of beer. Only quaternary brands, digit regional and digit national, remained acquirable to consumers. The topical brands raised their price. Predictably, these quaternary brands gained mart deal during the shortage. In the long run, circumscribed by the authors as a punctuation of quaternary months, the quaternary brands maintained a higher than original share. The long-term share, however, was lower than the peak observed during the strike. The domestic brands averaged a higher long-term deal gain than the topical brands. When last observed, 30 months after the strike, mart deal had not returned to their pre-strike positions.
Another large bit SDL analyse was conducted in England by Schary and Christopher, who interviewed a distribution of 1167 consumers in digit suburban stores of a London supermarket chain.11 of that sample. 343 (29.4%) consumers old at least one stock out. SDL salutation was compared to accumulation image, sort loyalty, and demographic variables. Some differences in activity were observed by different group and occupation. Consumers in families where the chief of the household was in a managerial or professional occupation were more likely to switch stores. Brand loyal consumers' were more likely to visit another store. Store image was also affected by stock out . A significant impact of stock outs on accumulation image was institute in the areas of creation quality, client service, value, convenience, image of creation variety, and availability. Zinszer and Lesser pioneered investigate into the creation characteristics and .shopping situations as correlates of stock outs. Their help looked at how stock outs affect consumers of assorted demographic characteristics, whether the item was on sale and how did stock out affects accumulation image and intended forthcoming patronage. Farris. Olver, and (Cluyver developed a model help to exhibit a positive, curving relationship between distribution and mart share). Brands with a larger deal benefit more than brands with similar deal when a miniature deal brand is out-of-stock. This is because it was assumed in the model that retailers prefer to restock shelves with the prizewinning selling brand. This restocking policy leads brands with higher mart deal to find meliorate distribution which, in turn, contributes to further mart deal gains. This spiraling process accounts for the curving relationship between distribution and mart share. Private brands were not included in the simulation.
Over a period of five days, Emmelhainz, Emmelhainz, and Slock distant five items from the shelf of a discount grocery store. These were selected from the prizewinning selling item of the directive hrand in the following creation categories: ground coffee, orange juice, toothpaste, peanut butter, and tomato sauce. Consumers were interviewed at the checkout lane about intended SDL and other behaviors following the stock out. Results were quite assorted for the five lest items when compared to other items institute out-of-stock in the store.
Straughn was the first to use detector accumulation in a stock out study. She attempted to judge the effects of stock outs on sort deal for candy bars. The short-term gist was negligible. The long-term effect, circumscribed as more than five weeks following the stock out condition, was substantial. Decline in sort deal averaged 10 percent. Because the methodology used in this think was unique, it is needed to review the key measures and their operational definitions. First, since the accumulation was mass weekly, a stock out could be corrected within the same hebdomad and consequently not exhibit in the weekly numbers. To solve the problem, a stock out was circumscribed as a change in the weekly sales average for an item that lapse right a 95% confidence quantity of a Poisson distribution. Second, the long-term gist of stock outs on sort deal was circumscribed as the difference between authentic mart deal and the mart deal that would be observed in the absence of stock outs. The latter number was estimated from observed sales in weeks during which no stock outs occurred.
Using a two-firm game theory model, Balachandcr and Farquhar examined the conditions under which it would be juicy for firms to reduce availability and accept stock outs.18 They concluded that firms could actually benefit from stock outs (and thus have a vested welfare in them) because the reduced creation availability will restrict cater and, consequently, increase prices. This theory implies a deliberate conspiracy among competitors. Competitor A is able to sell creation at a higher toll when competitor B is out-of-stock. Competitor B expects a quid-pro-quo at a forthcoming date. This conspiracy also benefits the consort that allowed the insufficiency to become because incoming replenishment inventory can be sold at a higher price. The 1996 Andersen Consulting think mentioned earlier is a comprehensive analyze on the problem of retail stock outs that combined accumulation audits, detector data, and personal interviews with industry and consumers.'1\" The think tracked items in the following creation categories: yogurt, bottled water, chilled juice, carbonated beverages, commercial bread, toilet tissue, frozen pizza, and child diapers. Conclusions exhibit the severity and diffusion of the stock out problem in U.S. retailing. Almost half of items tracked were out-of-slock at least a month, in a typical afternoon. 8.2% of items were out-of-stock. That number rises to 11 % on Sundays and to 15% on advertised items. In contrast, the earlier Progressive Grocer think showed that stock outs peaked on Mondays (20%), although no Sunday accumulation were reported.
Consumer's response is driven by multiple factors, which change greatly the decision process; those same factors lead the researches to miscellaneous conclusions. Product and brand switching are most probable according to (1) director and Grabner (1975) and (2) Emmelhainz et al. (1991), who oppose to (3) Schary and Chrystopher (1979).
The fact is that the study (1) took place in a liquor shop (where consumers are supposed to be well informed about the products and their doable cross-substitution) and study (2) was carried on for best sellers goods, whereas (3) Schary and Chrystopher focused on branded grocery. Generalizing, we can state that brand- and product substitution risks are rattling high. Consumers' reactions are, then, strongly affected by products specific, as highlighted by Campo et al. (2000) that conducted a research on cereals and margarine: both of them are low status goods, generally stocked in remarkable quantities at home, so a consumer will probably delay the purchase of those wares, if he experiences a OOS. Even if so, we hit to consider that those two items crapper possibly lead to rattling different answers, since an intrabrand switching is not doable for cereals, whereas it is for margarine. This study has to be compared to Grabner's one, carried on in 1975 in a liquor shop. In that occasion it was pointed out that a purchase delaying was almost improbable, but this consideration was taken in years with a lower mobility; on the disobedient we can state that, being alcoholic drinks high status goods bought for special occasions, they will be likely to undergo a purchase postponement.
As said, a multiplicity of factors intervenes in this situation: they hit been classified in various categories. According to Christopher and Schary (1979) the leading factor is the trade off between store loyalty and consumers loyalty; in this perspective, Emmelhainz et al. (1991) added causes like perceived creation risk, urgency of the need, intended creation usage (regular usage vs. special occasion) and brand loyalty versus store loyalty, finally, Verbeke, Farris, Thurik (1998) included the intensity of retail competition, the degree of store loyalty and the consumer's shopping patterns. Some another authors convergent on exogenous drivers like the severity of stock-out and heterogeneity in consumer preferences, time-dependence and cumulative impact of stock-outs over time (Bell and Fitzsimons, 1999).
The consumer's response to "out-of-stock" situations has implications for retail assortment, ridge space allotment, pricing, and logistics. In fact, a great number of technological literature focuses on the optimal assortment of optimizing projects (Rebstein and Gatignon, 1984) or focuses on the costs of OOS situations (Borinet al., 1994; Chang and Niland, 1967).
Although there is a need for an increased understanding of consumer response, in portion to the brand-OOS situation, only a few scientific experiments hit been undertaken in this area. With notable exceptions (e.g. Emmelheinz et al., 1991; Progressive Grocer, 1968), most scientific experiments on the OOS consumer response hit been based on laboratory experiments or idealized situations, such as gauging OOS responses using self-administered questionnaires. For instance, by using a simulated OOS situation, McAllister and Pessemier (1990) and Hoyer et al. (1996) institute a relationship between variety-seeking tendencies of consumers and OOS responses. By using self-administered questionnaires to produce a frequency distribution of "intended" OOS responses, Walter and Grabner (1975) and Waltner and LaLonde (1975) discovered that a certain number of people (14 percent) would alter stores if their brand was out of hit for a longer period of time. In addition, using self-administered questionnaires in order to estimate the consumer's brand commitment, researchers institute that consumers were prepared to alter stores (Beatty et al., 1988, Lastovickla and Gardner, 1977; Mittal and Lee, 1988).
True earth OOS experiments are rare, because they are pricey and potentially very venturous for the retailer; but perhaps precisely these experiments have provided us with engrossing information. Previous OOS experiments have identified a variety of OOS responses to the removal of digit SKU within the product's line of a brand: holdup of buying, brand change (at a lower price, the same, or at a higher price), change stores in order to get the brand, seeking the aforementioned brand in a assorted variety and other behaviors, such as querulous to managers, returning to analyse on availability, or dropping - not bothering with the purchase at every, change brands, switching SKUs within the aforementioned brand, and change stores to get the preferred brand were the most frequently occurring OOS responses.
A material proportionality of consumers (32 percent) hit been reportable to switch brands in response to an OOS status (Emmelheinz et al., 1991). Switching to assorted SKUs within the aforementioned brand has also been studied: 21 percent of the consumers did so according to Weinstein (1993) and 17.5 percent according to Emmelheinz et al. (1991).
A smaller proportionality of consumers switched stores to purchase the desired brand (14 percent. Delays or postponements of purchases also occurred with a lower percentage 12.3 proportionality. Fill-in trips accounted for a small proportionality 0.08 proportionality. Finally, Charlton and Ehrenberg (1976) reportable no long-term personality on sales. Several factors hit been reportable to moderate OOS responses. One study showed that OOS responses differ by product (Progressive Grocer, 1968) but Emmelheinz et al. (1991) found no differences among the products they studied.
Consumer characteristics also affected the OOS responses (1991) reported that customers who were hardcore to a store were more likely to delay purchase than non-loyal customers. The perceived venture of the product - the venture of purchase a sort other than the preferred brand has been shown to reduce sort switching, while the urgency to buy the sort had the opposite effect - that is, it increased the probability of consumers' change brands (Emmelheinz et al., 1991). The added value of our research to the current knowledge in this Atlantic was to focus on a brand's complete distinction of SKUs kind of than on one SKU within a product line. Moreover, it distinguished between temporary OOS and permanent assortment changes, and it investigated the personality of retail competition, consumer purchase habits, and store loyalty on the OOS response. As the full product distinction was removed from the shelves, there were mainly threesome OOS responses left to study:
- Postponement of buying;
- Variety switching; and
- Change stores to get the brand.
Switching SKUs within the same sort was not an option in our experiment, because the design of the experiment did not earmark this behavior - the study's focus was sort loyalty, not SKU loyalty.
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