PRODUCT FULFILLMENT IN SUPPLY CHAINS SUPPORTING INTERNET‐RETAILING OPERATIONS

Customer service, based on economical logistics operations across the supply chain, is key to the realization of sustainable levels of profitability in Internet retailing. Concentrating on inventory and product‐release operations, an empirical simulation model suggests that inventory centralization and market demand growth positively affect the level of cost‐effective service received by online shoppers. The results also show that under increasing demand levels, Internet retailers can provide optimal service to consumers by fulfilling orders through inventories located at their own facilities and avoid relying on inventories held elsewhere in the supply chain.     

INTERNET RETAILING INTERMEDIATION: A MULTILEVEL ANALYSIS OF INVENTORY LIQUIDITY AND FULFILLMENT GUARANTEES

Internet retailers intermediate online markets by setting prices, matching wholesalers' supply with consumers' demand, affording inventory liquidity, and meeting fulfillment guarantees to consumers. Little attention has been given to studying the two latter intermediation functions. To fill this research gap, this study examined a sample of 25 mainstream online retailers in some 704 transactions with consumers. The study evaluates the inventory liquidity and the fulfillment guarantees these Internet retailers provide to consumers. Furthermore, it presents a path‐analysis model, which suggests that retailers coordinate their actual and promised inventory‐liquidity and delivery performance to satisfy the fulfillment guarantees made to consumers. Moreover, the results show that key transactional attributes (i.e., the net price and the number of items fulfilled) commonly present in Internet markets and visible to all market participants impact both the levels of inventory liquidity and the delivery performance of the transactions between consumers and Internet retailers.     

How to serve online consumers in rural markets: Evidence-based recommendations

Online shopping is growing significantly among rural consumers interested in overcoming product assortment limitations in their local markets. Retailers are taking notice, and some are looking for first-mover-advantage opportunities in rural areas where they see greater potential for growth when compared to saturated urban markets. However, expanding to these areas presents significant and unresolved challenges related to last mile fulfillment caused by low levels of population density as well as other socioeconomic and demographic characteristics. In this article, we present an integrated set of recommendations for online retailers to differentiate strategies to serve rural markets efficiently. To that end, we partnered with an online grocery retailer to examine differences between rural and urban consumers across online shopping preferences that significantly impact fulfillment costs. We draw on those differences and existing knowledge on last mile fulfillment operations to propose a tailored consumer value proposition and operational model for last mile fulfillment in rural markets.     

The Role of Schedule Mismatch in Ending Inventory Decisions in the Presence of Price Cuts

In the high‐tech sector, component suppliers are often able to offer preannounced price cuts (price markdowns) to manufacturers due to technological innovation that allows them to produce the existing components at lower costs. In this context, manufacturers (buyers) are primarily concerned with their existing inventory carried beyond the price cuts in order to lower inventory costs. In this research, we develop a newsvendor‐based decision model for this problem based on our experience in industry and a focal case study environment. Specifically, we consider the issue of delivery and demand uncertainties, and the interplay of the buying firm's operating hours and the transportation carrier's delivery hours, which combine to influence inventory costs and order fulfillment. We illustrate the results with numerical examples and sensitivity analyses, using a real world data set. We found that stockout cost plays a critical role in the ending inventory decisions. Lowering stockout cost will benefit buyers from lower risk of obsolescence costs.     

A model of demand,productivity and foreign location decision among Taiwanese firms

We develop a theoretical framework to examine the relative importance of firm demand and productivity in firm decisions to export and where to locate foreign direct investments. The model shows that the equilibrium firm decision depends on product technology, consumer preference for product quality, fixed investment costs of establishing a foreign subsidiary, transportation costs and relative wages. Our empirical results confirm the predictions of the theoretical model. Firm-level demand and productivity components are important in explaining the decision to participate in foreign markets with their relative importance depending on the firm's organizational form (exports versus FDI) and the destination of the investments. In general, FDI firms are more productive than exporting firms regardless of FDI destinations. FDI firms also have a higher demand component than exporters and this demand component is stronger than productivity. Finally, among FDI firms, while those with a high demand index and productivity have a significantly higher propensity to invest in high-income countries, firm productivity is the sole determinant of firms undertaking FDI in low-income countries.     

A Simulation Model Of Multi‐Echelon Retail Inventory With Cross‐Channel Product Returns

This study explores the relationship between a retailer's product returns processing structure and Multi‐Echelon inventory system performance under cross‐channel and same‐channel product returns policies with nonstationary demand. Our research contributes to the growing body of reverse logistics literature, offering insight into how a retailer's logistical returns management strategy can impact inventory effectiveness in cross‐channel retail environments. Adopting a contingency framework, we develop research hypotheses which we test through experimentation on a Multi‐Echelon retail inventory system within a discrete‐event simulation. Model parameters are derived from data collected from a large U.S. retailer of consumer durable and nondurable goods. We find an amplifying effect of a cross‐channel returns policy on the positive relationship between a decentralized returns processing structure and inventory effectiveness. Further, through our analysis of nonstationarity in demand and resulting returns, we uncover strong main and interaction effects that seasonal demand variation can have on inventory outcomes, even under only moderate levels of seasonality. Our results highlight the need for firms to align logistical structures for returns processing with the returns policy and the external environment, while also lending credence to calls within the logistics literature for improved modeling of nonstationary demand in inventory management research.     

The evolving role of hit and niche products in brick-and-mortar retail category assortment planning: A large-scale empirical investigation of U.S. consumer packaged goods

Long tail theory, the notion that the future of retailing could involve shifting product assortments to offer more product variety to precisely serve the unique needs of individual customers, has largely been proven true in the context of online distribution. However, it has been implicitly assumed that this theory does not apply to brick-and-mortar selling situations due to higher supply side inventory costs and higher demand side consumer search costs. Academics and practitioners alike have thus advocated for the use of Pareto rules to make category assortment planning decisions about product inventory breadth and depth in the brick-and-mortar channel. This research directly challenges this received wisdom by noting that the widespread prevalence and use of mobile technology is causing information flows to speed up for consumers even while performing traditional shopping tasks. Such information flows should theoretically favor the strategic importance of niche products in the long tail of the sales distribution. A large-scale empirical analysis of consumer packaged goods brick-and-mortar retailing data indicates that this alternative prediction is indeed true. This research contributes to a larger body of research as well that has documented how major environmental forces are shifting the nature of retail strategy, particularly in the brick-and-mortar channel.     

A Comparison of Buyback and Trade‐In Policies to Acquire Used Products for Remanufacturing

We study how acquisition policies for used products as a source for a remanufactured consumer product affect system performance. We introduce a consumer choice model of new product purchase and used product return, which is consistent with the classic Bass diffusion model of sales over time. We capture new and remanufactured product sales, the evolution of the install base, and consumer return and repurchase decisions over the life cycles of new and remanufactured product. Our analyses lead to two main findings on the acquisition policies. First, if the buyback price is less than the margin of a new product, then a trade‐in policy is likely to yield higher profit than a buyback policy. Second, we show that the profitability is highest when the time lag between the introduction of a new product and initial demand for a remanufactured version of the product is at or near the sweet spot, which is the age of the product at which the costs of acquisition and remanufacturing are at minimum. Further, when the time lag between the introduction of a new product and initial demand for its remanufactured version is near the sweet spot, then simple pricing methods are close to optimal.     

Cognitive Lock‐In Effects on Consumer Purchase Intentions in the Context of B2C Web Sites

The perspective of power law of practice and human capital model asserts that cognitive search costs, cognitive transaction costs, and cognitive switching costs are three lock‐in mechanisms that a business‐to‐consumer (B2C) Web site holds to retain customers. Whether the ability of customer value or the lock‐in mechanism is more dominant for retaining online shoppers has received recent attention, but remains unresolved in the literature. This study sheds light on perceived value and cognitive lock‐in to develop a research model to predict consumer purchase intentions. Empirical results obtained from a survey of customers of a B2C Web site are used to examine the proposed model. Implications of cognitive lock‐in and product cues for increasing purchase intentions are also discussed.     

INDIVIDUAL AND ENVIRONMENTAL IMPACTS ON SUPPLY CHAIN INVENTORY MANAGEMENT: AN EXPERIMENTAL INVESTIGATION OF INFORMATION AVAILABILITY AND PROCEDURAL RATIONALITY

Some strategies for mitigating ordering inefficiencies in supply chains advise sharing information among decision‐makers. However, there has been little consideration of how individual perceptions intervene in the use of available information in decision‐making processes. This article reports the results of an experiment in which participants were instructed to minimize inventory holding and backlog costs for their supply chains as a whole. The analysis suggests that additional information affects supply chain inventory management costs only when rational decision‐making processes are followed. Decreased costs are observed when rational decision‐making is applied with backlog information. In contrast, increased costs are observed when consumer demand information is available.     

STRATEGIC INVENTORY OPTIMIZATION

A company's inventory metrics are often viewed as critical indicators of its supply chain performance although inventory costs are only a fraction of total supply chain costs comprised of supplier, manufacturing, transportation, and warehousing costs, as well as inventory costs. Moreover, inventories across the supply chain are dependent on acquisition and distribution decisions. We discuss how simulation and optimization models can be combined to integrate analysis of inventory and supply chain network design decisions in performing a total cost analysis. An application of the models to plans for distributing retail products to an expanding network of stores is reviewed.     

Just‐in‐Time Retail Distribution: A Systems Perspective on Cross‐Docking

Cross‐docking is a just‐in‐time strategy for distribution logistics. It is aimed at reducing inventory levels and distribution lead times by creating a seamless flow of products from suppliers to customers. Prior supply chain literature has argued that creating such a seamless product flows requires a holistic view on cross‐docking management, aimed at synchronizing cross‐docking operations at the distribution center with its inbound and outbound network logistics. This paper provides an in‐depth case study illustrating how cross‐docking operations can be managed more holistically in a retail distribution context. A discrete event simulation model has been developed to understand and improve the cross‐docking operations of a large grocery retailer in the Netherlands. The model is used to quantitatively evaluate two proposed changes that exploit opportunities in the design and control of the retailer's distribution network. An extensive real‐world data set is used as input to the model. Overall, the case and simulation results show that a holistic cross‐docking management approach can indeed improve system‐wide performance, which further stresses the importance of making cross‐dock operational decisions making and network decisions together.     

Television ad-skipping,consumption complementarities and the consumer demand for advertising

Endogenous consumption of advertising is common. Consumers choose to change channels to avoid TV ads, click away from paid online video ads, or discard direct mail without reading advertised details. As technological advances give firms improved abilities to target individual consumers through various media, it is becoming increasingly important for models to reflect the endogenous nature of ad consumption and to consider the implications that ad choice has for firms’ targeting strategies. With this motivation, we develop an empirical model of consumer demand for advertising in which demand for ads is jointly determined with demand for the advertised products. Building on Becker and Murphy (The Quarterly Journal of Economics, 108(4), 941–964 1993)’s ideas, the model treats advertising as a good over which consumers have utility and obtains demands as the outcome of a joint utility maximization problem. Leveraging new data that links household-level TV ad-viewing with product purchases, we provide empirical evidence that is consistent with the model: ad-skipping is found to be lower when a household has purchased more of the advertised brand, and purchases are higher when more ads have been watched recently, suggesting that advertising and product consumption are jointly determined. Fitting a structural model of joint demand to the data, we evaluate consumer welfare and advertiser profitability in advertising targeting counterfactuals motivated by an “addressable” future of TV. We find that targeting on the predicted ad-skip probability is an attractive strategy, as it indirectly selects consumers that value the product. Reflecting the positive view of advertising in the model, we also find that net consumer welfare may increase in several targeting scenarios. This occurs because under improved targeting, firms shift advertising to those who are likely to value it. At the same time, consumers that do not value the ads end up skipping them, mitigating possible welfare losses. Both forces are relevant to assessing advertising effects in a world with improved targeting and ad-skipping technology.     

Online information search termination patterns across product categories and consumer demographics

While accessing information online, consumers exhibit differences in their patterns of search, that is, time spent per search episode and search frequency. The search patterns vary across both consumer characteristics and product categories. We empirically investigate consumer online information search termination patterns, and relate the differences to product categories and consumer characteristics. Findings of such an empirical study would be useful for planning communication strategies, website design, etc. The model is calibrated on empirical data collected through online surveys. We find that consumer learning occurs when consumers search across search goods, but not when they search across experience goods.     

Information Asymmetry in Consumer Perceptions of Quality‐Differentiated Food Products

Increasing consumer demand for quality‐differentiated food products has given rise to a large quantity of food product classifications related to production practices and locations. Some food product claims such as native have no clear definitions and may have ambiguous connotations for different consumers. We analyze whether asymmetry in information affects consumer preferences and willingness to pay for ambiguous claims using the native attribute. An empirical application of pecans is used in the analysis to compare native and improved pecan varieties. With no evidence in the literature of additional benefits of native varieties, the results showed that consumers preferred native varieties. Furthermore tastes and preferences for all product attributes were heterogeneous; heterogeneity in preference for the native attribute was only significant at the 10% level.     

Consistency and Recovery in Retail Supply Chains

Practitioners and researchers describe inventory service level with metrics that communicate the likelihood of demand fulfillment without considering the ongoing capabilities of the supplier, for example, in‐stock and fill rate. We develop a method for measuring inventory service level that incorporates such supplier capabilities, namely consistency (the ability of a supplier to fulfill orders repeatedly) and recovery (the ability of a supplier to fulfill orders after a lapse in service). Using data from two retail supply chains, we illustrate our approach. To demonstrate the impact of consistency and recovery on supply chain performance, we model a retailer purchasing from competing suppliers with different levels of consistency and recovery. The model incorporates the retailer's uncertainty about demand and the retailer's uncertainty about its suppliers' service levels. We characterize how the retailer's orders and profitability change with a supplier's delivery performance through numerical experiments calibrated with field data. We find notable differences in market share across suppliers with similar traditional inventory service level metrics but differences in consistency and recovery. Further, we observe that a retailer can increase its profitability by determining orders via consistency and recovery in lieu of common metrics like in‐stock. Given the influence of consistency and recovery on supply chain outcomes, we discuss implications for practice and future research.     

THE LAST MILE: AN EXAMINATION OF EFFECTS OF ONLINE RETAIL DELIVERY STRATEGIES ON CONSUMERS

The Internet has increased the level of importance of the end‐consumer market to transportation carriers. In two between subject experiments, carrier disclosure on retail merchant websites is examined as a strategic differentiation strategy. Predictions are offered concerning effects of carrier disclosure strategies on product delivery‐related expectations, consumer attitudes, and intentions to purchase a product online. Results from Study 1 reveal significant differences between disclosure and nondisclosure of the carrier for numerous product delivery‐related variables, as well as many differences between the six carriers examined in this first study. Study 2 extends these findings by showing that providing consumers with a choice of carrier leads to increased levels of satisfaction with the online experience and greater willingness to buy, relative to nondisclosure and disclosure strategies.     

THE IMPACT OF ORDER FULFILLMENT SERVICE ON RETAILER MERCHANDISING DECISIONS IN THE CONSUMER DURABLES INDUSTRY

Historically, manufacturers held the upper hand in consumer goods supply chain relationships. There has been a pervasive shift of power to retailers over the past 20 years, however, ushering in an era of waning consumer loyalty to manufacturers' brands and increasing loyalty to retailers. While there is extensive research focusing on the manufacturer‐consumer relationship, retailers' increased ability to influence consumer purchases suggests that manufacturers should understand not only consumer perceptions of delivery service, but also retailer perceptions. We incorporate social network theory to examine the manufacturer‐retailer‐consumer linkages in the consumer durables industry, with the emphasis on the retailer in the role of the “broker” (Burt 1992). Specifically, we examine whether retailer perceptions of a manufacturer's order fulfillment service (OFS) positively impacts retailer perceptions of the manufacturer's brand, the importance of the product, and the likelihood of the retailers' salespeople to recommend the product to consumers. The research bridges OFS and retailer purchase behavior in a consumer durables industry characterized by high levels of consumer involvement, brand presence, and personal selling.     

Demand and Revenue Management of Deteriorating Inventory on the Internet: An Empirical Study of Flash Sales Markets

In this study, we investigate demand and revenue management of deteriorating inventory in flash sales markets (FSM). Retailers operating FSM source excess inventories of products from secondary markets in fixed lot sizes and offer them as part of deals that get no replenishments and expire after running for predetermined periods (e.g., 24 hr) or when they sell out, whichever occurs first. We develop a demand forecasting model that incorporates the effects of sentiments conveyed by consumers in discussion forum posts associated with different deals on the deals’ empirical demand rates. We then conduct a survival analysis to find that the empirical demand rates projected from our forecasting model are significant predictors of the deals’ actual time to stockout, even after controlling for their initial inventory provisions and markdowns. We also find that the predicted effects of these demand rates on stockout times are stronger at low markdowns. Our investigation offers insights into different strategies that sellers operating FSM can pursue to improve their inventory performance. These strategies involve decisions that sellers must make both a priori, before deals start, and a posteriori, according to real‐time detection of departures from projected demand rates as deals run their course.     

Consumers' SKU choices in an online supermarket: a latent class approach

Abstract

This study examines the effects of loyalty and e-marketing mix variables on the choices of online consumers at the stock-keeping-unit (SKU) level. Using a panel dataset from an online supermarket, we estimate a discrete choice model of a frequently purchased product; generate the refined smoothing constants of the loyalty variables for brand, size, and SKU; and adopt the latent class approach to address consumer heterogeneity. The findings suggest that SKU loyalty is a better predictor of consumer choices than brand and size loyalty. Although online consumers are not sensitive to the net prices of SKU alternatives, they are attracted to price promotions. While webpage display has little effect on SKU choices, speedy delivery has a positive impact. The latent class approach significantly improves model fitness and classification accuracy. Analysing consumer choices at the SKU level can help online supermarkets with promotion planning and inventory and distribution management to improve customer satisfaction and profitability.