Impact of Value‐Added Service Features in e‐Retailing Processes: An Econometric Analysis of Web Site Functions

We examine the impact of three classes of Web site functions (foundational, customer‐centered, and value‐added) upon e‐retailer performance. Using secondary panel data for 2007–2009 on operating characteristics of over 600 e‐retailers, our econometric analysis finds that only the value‐added service functions are positively associated with changes in e‐retail sales revenues across time. We also observe a decreasing marginal impact of deploying additional value‐added service features. To account for possible alternate explanations, we control for firm‐ and time‐specific fixed effects, merchant types, merchandise categories, and order fulfillment strategies. By further decomposing e‐retail sales revenues into Web site traffic, conversion rate, and average order value, we find that Web site functions affect e‐retail sales revenues mainly through their impact on Web site traffic. Our investigation demonstrates the empirical research usefulness of the Voss conceptual e‐service sand cone model. Our results identify for managers where to focus ongoing e‐retailing system development efforts, yet suggest that focusing too many retailing capabilities on exploratory and experimental value‐added service features may backfire, potentially leading to worsening e‐retailer performance.     

Improving Valuation Under Consumer Search: Implications for Pricing and Profits

There is a growing trend in the retail industry to improve customer experience. In this article, we study retailer‐initiated strategies to increase consumer valuation for a product under duopoly. In such a setting, it is possible that a consumer's valuation may be increased by one retailer; however, the consumer may decide to buy the product from the competitor. We consider a two‐stage game where retailers first decide whether to invest in improvements in customer valuation and then engage in price competition. We computationally explore the Nash equilibria in terms of both investment and pricing. We find that in the majority of cases retailers price in a manner to discourage their local customers to buy from the competitor. Next, we focus on the pricing game and theoretically characterize the pricing Nash equilibrium. We find that a retailer could overcome competitive effects by improving consumer valuation beyond a certain threshold. We also find that a retailer who does not invest could benefit from competition in situations where his competitor increases consumer valuation beyond a threshold. Finally, we explore through a computational study the Nash equilibria of the two‐stage game using an alternate model to establish the robustness of our findings.     

Assessing Markups,Service Quality,and Product Attributes in Music CDs' Internet Retailing

We investigate trade‐offs among markups, service quality, and product attributes across customer, Internet retailer, and wholesaler echelons. Research has documented the reality of retail price dispersion, but little is known about how retail markups, in particular, are related to service quality and product attributes. For example, do Internet retailers deliver superior service in return for high markups? Do product characteristics affect the relationship between service and markups for retailers? To examine these issues, we first developed a model of Internet retail profitability that separates revenues and costs related to sales from other profit sources. This framework allowed us to position our work alongside the extant literature about Internet retailing. Moreover, it led us to synthesize service quality dimensions found in Internet retailing studies. We subsequently developed a critical‐event study based on the profit model and the synthesis of service quality dimensions to delineate service aspects that retailers should emphasize to address buyers' utility. Finally, we collected data from Internet purchases across retailers to isolate markup‐service quality trade‐offs along our delineated service aspects. We find that high markups are associated with superior performance across service quality dimensions. Furthermore, this trade‐off becomes more acutely defined when products with variable popularity are transacted.     

An Information‐Processing Approach for Evaluating In‐Store Retail Operational Design Strategies

We develop a model to evaluate retail store operational design strategies using an information‐processing perspective of organizational design. We propose that three model constructs pertaining to in‐store shopper task uncertainty—the product mix complexity, the service production complexity, and the product mix changeover—create shopper encounter information requirements (IR). These requirements can be met using specific retail service operational design choices for managing shopper encounters, namely, designing layouts for self‐service (SS) and providing employees with task empowerment (TE). The model is then operationalized using a two‐stage approach to develop new multi‐item, measurement scales. The psychometric properties and predictive validity of the scales and model are then confirmed by using structural equation modeling with survey data from 175 merchandise retail store managers. We find that our model can be generically applied across the retail industry to understand how shopper encounter IR motivate retailer store design choices and can be used to determine whether to design stores for SS or to provide store employees with TE. We then evaluate the efficacy of the studied store design choices on customer delivery satisfaction, and offer some suggestions for future research.     

Self‐Service Operations at Retail Stores: The Role of Inter‐Customer Interactions

Inter‐customer interactions are important to the operation of self‐services in retail settings. More specifically, when self‐service terminals are used as part of customers’ checkout processes in retail operations without the explicit involvement of retailers as the direct service providers, inter‐customer interactions become a significant managerial issue. In this article, we examine the impact of inter‐customer interactions at retail self‐service terminals on customers’ service quality perceptions and repeat purchase intentions at retail stores. We conduct a scenario‐based experimental design (N = 674) using a 2 × 2 factorial design in which inter‐customer interactions are divided into “positive” vs. “negative” and occur during the “waiting” or during the actual “transaction” stages of self‐services at a retail store. We use attribution theory to develop the hypotheses. The results demonstrate that, through their interactions, fellow customers can exert influences on a focal customer's quality perceptions and repeat purchasing intentions toward a retail store. Furthermore, these influences were impacted by how customers attribute blame or assign responsibility toward the retail store. Service operations managers should leverage these interactions by designing into self‐service settings the capacities and interfaces that are best suited for customers’ co‐production of their self‐service experiences.     

Analysis of Effects of Operational Execution on Repeat Purchasing for Heterogeneous Customer Segments

Many retailers are increasingly turning to home delivery as a new arena of operational competition. This study controlled for industry by investigating the online home delivery grocery business, and an analysis of 1,919 customers of home delivery grocers identified four groups of online customers based on reasons for selecting this service. These four groups were next linked to operational execution in terms of service, product, and Internet quality, and found to vary in predicable ways. Subsequent to the initial data collection, five month's of post hoc longitudinal purchasing history was collected on the four groups of online customers to determine the relative profitability. Finally, as a follow‐on analysis, the study used regression to predict future consumer purchases based upon operational execution. Time savings and service quality emerged as the two most important independent variables in terms of future buying from such online home delivery services.     

Why Competition from a Multi‐Channel E‐Tailer Does Not Always Benefit Consumers*

Empirical studies have delivered mixed conclusions on whether the widely acclaimed assertions of lower electronic retail (e‐tail) prices are true and to what extent these prices impact conventional retail prices, profits, and consumer welfare. For goods that require little in‐person pre‐ or postsales support such as CDs, DVDs, and books, we extend Balasubramanian's e‐tailer‐in‐the‐center, spatial, circular market model to examine the impact of a multichannel e‐tailer's presence on retailers' decisions to relocate, on retail prices and profits, and consumer welfare. We demonstrate several counter‐intuitive results. For example, when the disutility of buying online and shipping costs are relatively low, retailers are better off by not relocating in response to an e‐tailer's entry into the retail channel. In addition, such an entry—a multichannel strategy—may lead to increased retail prices and increased profits across the industry. Finally, consumers can be better off with less channel competition. The underlying message is that inferences regarding prices, profits, and consumer welfare critically depend on specifications of the good, disutility and shipping costs versus transportation costs (or more generally, positioning), and competition.     

SERVICE PROCESS CONFIGURATIONS IN ELECTRONIC RETAILING: A TAXONOMIC ANALYSIS OF ELECTRONIC FOOD RETAILERS

We developed a taxonomy of service processes in electronic retailing using data from 255 electronic food retailers. The taxonomy is comprised of eight service process configurations. Analysis of publicly available data on on‐line customer ratings for 52 retailers in the study sample shows that the ordering of the configurations in the taxonomy on a continuum of low to high flexibility is associated positively with (i) customer satisfaction with web site aesthetics, web site navigation, product selection, product information, customer support, and ease of return, and (ii) customer loyalty.     

Co‐Op Advertising in Dynamic Retail Oligopolies

We study a supply chain in which a consumer goods manufacturer sells its product through a retailer. The retailer undertakes promotional expenditures, such as advertising, to increase sales and to compete against other retailer(s). The manufacturer supports the retailer’s promotional expenditure through a cooperative advertising program by reimbursing a portion (called the subsidy rate) of the retailer’s promotional expenditure. To determine the subsidy rate, we formulate a Stackelberg differential game between the manufacturer and the retailer, and a Nash differential subgame between the retailer and the competing retailer(s). We derive the optimal feedback promotional expenditures of the retailers and the optimal feedback subsidy rate of the manufacturer, and show how they are influenced by market parameters. An important finding is that the manufacturer should support its retailer only when a subsidy threshold is crossed. The impact of competition on this threshold is nonmonotone. Specifically, the manufacturer offers more support when its retailer competes with one other retailer but its support starts decreasing with the presence of additional retailers. In the case where the manufacturer sells through all retailers, we show under certain assumptions that it should support only one dominant retailer. We also describe how we can incorporate retail price competition into the model.     

顾客策略行为下差异产品两阶段定价模型研究

互联网和信息技术的发展,为零售商收集顾客信息带来方便的同时,也使得消费者变得越来越具有策略性和选择性。首先,构建零售商只销售一种高质量产品的情形,研究其两阶段的定价策略,并分析产品的跨期折扣因子对产品的零售价格、销售量和零售商利润的影响。然后,考虑零售商可提供高质量和低质量两种产品的情形,顾客在第一销售期、第二销售期都可以选择两种产品。构建两阶段的定价决策模型,并分析产品的跨期折扣因子、顾客对低质量产品的接受度等参数对产品两阶段的零售价格、销售量的影响。最后,用数值算例分析了第二种模型下顾客对低质量产品的接受度等模型参数对零售商两阶段总利润的影响,然后比较了第一种和第二种模型下高质量产品的零售价格和销售量。研究结论较全面的分析了顾客策略行为对差异产品两阶段销售期的定价决策的影响,为零售商进行定价优化决策提供了十分重要的参考。     

A Stochastic Inventory Model With Fast‐Ship Commitments

We present a multiperiod model of a retail supply chain, consisting of a single supplier and a single retailer, in which regular replenishment occurs periodically but players have the option to support fast delivery when customers experience a stockout during a replenishment period. Because expedited shipments increase the supplier's transportation cost, and possibly production/inventory costs, the supplier typically charges a markup over and above the prevailing wholesale price for fast‐shipped items. When fast shipping is not supported, items are backordered if customers are willing to wait until the start of the next replenishment period. We characterize the retailers and the supplier's optimal stocking and production policies and then utilize our analytical framework to study how the two players respond to changes in supply chain parameters. We identify a sufficient condition such that the centralized supply chain is better off with the fast‐ship option. We find a range of markups for fast‐ship orders such that the fast‐ship option is preferred by both the supplier and the retailer in a decentralized chain. However, a markup that is a win–win for both players may not exist even when offering fast‐ship option is better for the centralized chain. Our analysis also shows that depending on how the markup is determined, greater customer participation in fast‐ship orders does not necessarily imply more profits for the two players. For some predetermined markups, the retailer's profit with the fast‐ship option is higher when more customers are willing to wait. However, the retailer may not be able to benefit from the fast‐ship option because the supplier may choose not to support the fast‐ship option when fast‐ship participation increases due to the fact that the fast‐ship participation rate adversely affects the initial order size.     

Promotion Planning and Supply Chain Contracting in a High–Low Pricing Environment

Demand forecast errors threaten the profitability of high–low price promotion strategies. This article shows how to match demand and supply effectively by means of two‐segment demand forecasting and supply contracts. We find that demand depends on the path of past retail prices, which leads to only a limited number of reachable demand states. However, forecast errors cannot be entirely eliminated because competitive promotions entail some degree of random (i.e., last‐minute) pricing. A hedging approach can be deployed to distribute demand risk efficiently over multiple promotional campaigns and within the supply chain. A retailer that employs a portfolio of forward, option, and spot contracts can avoid both stockouts and excess inventories while achieving the first‐best solution and Pareto improvements. We provide an improved forecasting method as well as stochastic programs to solve for optimal production and purchasing policies such that the right amount of inventory is available at the right time. By connecting a stockpiling model of demand with the supply side, we derive insights on optimal risk management strategies for both manufacturers and retailers in a market environment characterized by frequent price promotions and multiple discount levels. We employ a data set of the German retail market for a key generator of store traffic—namely, diapers.     

Managing Internet Product Returns: A Focus on Effective Service Operations

Product returns present one of the biggest operational challenges in the world of Internet retailing due to the sheer volume and cost of processing returns. But returns also represent an often‐missed opportunity to manage customer relationships and build customer loyalty to the retailer. Based upon data from a survey of 464 customers of five different Internet retailers, this article explores how firms' returns management systems affect loyalty intentions. We draw upon extant literature in the fields of Internet retailing, service quality, supply chain management, and customer satisfaction/loyalty to develop a model and a set of hypotheses relating ten latent variables in the service returns offering area. Our resulting structural equation model provides evidence of the impact of the returns management system upon customer loyalty intentions. The model also identifies effects on loyalty intentions arising from customers' satisfaction with, and perceptions of, the value of the returns service offered. These findings will help inform managers' choices regarding investment in the returns management system as an element of service quality improvement and a potential means of improved profitability. In addition, this study's empirical exploration and testing of a returns management model in the Internet retailing environment is a contribution to the currently underrepresented body of academic literature linking marketing and supply chain management in the context of end consumers.     

Selling with Money‐Back Guarantees: The Impact on Prices,Quantities, and Retail Profitability

In this paper, we consider a retailer adopting a “money‐back‐guaranteed” (MBG) sales policy, which allows customers to return products that do not meet their expectations to the retailer for a full or partial refund. The retailer either salvages returned products or resells them as open‐box items at a discount. We develop a model in which the retailer decides on the quantity to procure, the price for new products, the refund amount, as well as the price of returned products when they are sold as open‐box. Our model captures important features of MBG sales including demand uncertainty, consumer valuation uncertainty, consumer returns, the sale of returned products as open‐box items, and consumer choice between new and returned products and possibility of exchanges when restocking is considered. We show that selling with MBGs increases retail sales and profit. Furthermore, the second‐sale opportunity created by restocking returned products enables the retailer to generate additional revenues. Our analysis identifies the ideal conditions under which this practice is most beneficial to the retailer. Offering an MBG without restocking increases the new product price. We show that if the retailer decides to resell the returned items as open‐box, the price of the new product further increases, while open‐box items are sold at a discount. On the other hand, customers enjoy more generous refunds along with lower restocking fees. The opportunity to resell returned products also generally decreases the initial stocking levels of the retailer. Our extensive numerical study substantiates the analytical results and sharpens our insights into the drivers of performance of MBG policies and their impact on retail decisions.     

An Exploratory Study of the Impact of e‐Service Process on Online Customer Satisfaction

Although extensive academic research has examined the dynamics of interpersonal interactions between service providers and customers, much less research has investigated customer service encounters through technological interfaces such as the Web in electronic commerce transactions. Corporate websites have become an important point of contact with customers for many companies. Service has been described as one of the most important attributes for online business to influence traffic and sales. However, more research is needed to understand how Web‐based technological capabilities of services affect customer satisfaction. In this paper, we propose viewing the interface between online buyers and sellers through the lens of service management to identify possible determinants of online customer satisfaction. A company's website is considered its electronic service delivery system. We look at this electronic service delivery system from its process point of view. Our findings indicate that as the electronic service delivery system process improves, a customer's perception of the website's ease of use increases, leading to increased service value and perceived control over the process, which increases customer satisfaction. The research provides evidence that the technological capabilities embedded in the website processes are an important factor in determining service quality and ultimately online customer satisfaction.     

The Impact of Geographic Proximity on What to Buy,How to Buy,and Where to Buy: Evidence from High‐Tech Durable Goods Market*

Social contagion effects due to geographical proximity refer to the social effects wherein the behavior of an individual varies with the behavior of other individuals who are geographically close. Although the influence of such effects on consumer choices has been established in several contexts, much of the extant studies have focused on its effect on consumers’ decision of whether to buy a new product or adopt a new innovation. There has been no systematic examination of the influence of geographic proximity on other aspects of consumers’ product buying process such as what to buy (i.e., brand choice), how to buy (i.e., the channel), and where to buy (i.e., retailers). Such effects can matter significantly in high‐technology and durable goods markets and therefore, it is critical to understand the scope of these on consumers’ choice of retailers and channel as well. Drawing on literatures from word of mouth effects, ecommerce, and consumers’ perception of risk in their purchase process, we develop a set of hypotheses on the effect of geographic proximity on consumers’ choices of what to buy, how to buy, and where to buy. Leveraging a microlevel dataset of purchases of personal computers, we develop brand‐, retailer‐, and channel‐related measures of proximity effects at the individual consumer level and estimate a joint disaggregate model of the three choices that make up a product purchase process to test these hypotheses. Our results indicate a significant contagion effect on each of the three choices. Furthermore, we find evidence of a greater effect of geographic proximity on inexperienced consumers—those who are new to the product category. Our results thus help develop a holistic understanding of the influence of social contagion effects on consumers’ decision making.     

Manufacturer–Retailer Negotiations in the Presence of an Oligopolistic Input Market

When a manufacturer relies solely on its own inputs in making products, the focus of negotiations between the manufacturer and retailer is exclusively on profits in the output (retail) market. In such cases, absent retail competition concerns, standard two‐part tariff negotiations set the per‐unit wholesale price equal to marginal cost, and require fixed transfers from the retailer to the manufacturer. In this article, we recognize that manufacturers often rely on imperfectly competitive markets for at least some inputs. Incorporating this seemingly natural feature has profound implications for manufacturer–retailer negotiations since it shifts their focus from being exclusively on output markets to one that balances strategic concerns in both input and output realms. The article's main result is that the added need to discipline input prices can lead the manufacturer and retailer to write contingent contracts that are cost‐plus and prescribe lump‐sum slotting allowances (i.e., fixed transfer from the manufacturer to the retailer).     

Mechanisms for Increasing Sourcing from Capacity‐Constrained Local Suppliers

The fresh produce supply chain is characterized by large (mainstream) farms that are located far from consumers, and capacity‐constrained (local) farms that are located close to the consumer. In this setting, we study: (i) how leadtime and capacity asymmetry between mainstream and local farms affect a retail grocer's order policy for fresh produce, and (ii) how various operational mechanisms can increase the amount sourced from local farms. We show that this supply chain structure is disadvantageous for local suppliers (farms) because it induces the retailer to treat the local supply as a de facto responsive supply without paying a premium for the responsiveness. This disadvantage is exacerbated when the retailer's objective is to achieve a high service level. We study three mechanisms that can improve conditions for local farms: working with an intermediary, backhauling, and a retail order policy, purchase guarantee, that explicitly supports local farms. The intermediary and backhauling mechanisms help the local farm by making local supply more attractive to the retailer, inducing her to order more locally sourced produce. The intermediary reduces the retailer's overstock and stockout costs whereas backhauling increases the average margin. The purchase guarantee order policy helps local farms at the expense of retail profit. However, we show that purchase guarantee and backhauling are complementary mechanisms that together can benefit the retailer and local farms.     

考虑跨渠道退货的双渠道供应链最优策略

基于零售商线上线下销售与消费者退货并存的双渠道供应链,构建考虑退货的双渠道供应链定价模型以及考虑跨渠道退货策略的双渠道供应链定价决策模型。通过理论分析和数值实验对比,研究集中决策与分散决策下的零售商最优定价策略以及总利润的变化情况,同时分析在不同退货策略下顾客偏好以及退货率对零售商定价和收益的影响。结果表明：零售商渠道的最优价格设置与顾客对渠道的偏好成正比,与退货率成正比。当顾客对某一渠道偏好程度高时,分散决策下的利润要高于集中决策,并且随着该渠道退货率的提高,这种利润差距会进一步扩大,因此零售商应实施分散决策的渠道策略,鼓励线上线下两个渠道进行竞争,从而获得更大的收益。从仿真结果可以看出,对于一般的服装产品,提供跨渠道退货服务的零售商总利润更高,在一定条件下跨渠道服务水平的投入会增加零售商的收入,但这种投入应该控制在一个合理的水平上,并保持服务与顾客回报之间的正相关关系。     

Cooperative sales promotion with a point-sharing policy: Advantages and limitations

Consumption-point programs have been commonly implemented in retail industries in efforts to promote sales and improve customer loyalty. In Korea, many retailers from different industries use a point-sharing policy to augment the conventional consumption-point program of each retailer. In a multi-retailer coalition under such a cooperative sales promotion policy, by purchasing from one coalition retailer, customers earn points that they can redeem points at other retailers in the coalition. On one hand, the introduction of this policy gives customers great flexibility for redeeming earned points, which can increase the demand at all retailers who promote the policy. On the other hand, the additional product costs associated with the points created by one retailer may spill over and be partly borne by other retailers, possibly distorting the coalition members’ equilibrium decisions under decentralized control. Under the general assumptions about the demand functions, we developed a model consisting of two retailers with fixed retail prices and addressed the retailers’ equilibrium decisions under a pure point-sharing policy. The findings suggest that the policy resulted in a cost spillover phenomenon. Then, we revealed that a pure point-sharing policy may fail to maximize the total profit of the coalition. Moreover, we showed that a pure point-sharing policy does not dominate the individual point scheme, which may explain the reason that point sharing is useful but not ubiquitously used in the real world. Our numerical examples also illustrate the way a pure point-sharing policy influences retailers’ profits when retail prices are decision variables. To improve the overall profit under the point-sharing policy further, we propose a target rebate contract to coordinate a pair of retailers. This contract can maximize the total profit and arbitrarily split the profit between retailers.