Knowledge that Transforms

We analyze the benefits of inventory pooling in a multi‐location newsvendor framework. Using a number of common demand distributions, as well as the distribution‐free approximation, we compare the centralized (pooled) system with the decentralized (non‐pooled) system. We investigate the sensitivity of the absolute and relative reduction in costs to the variability of demand and to the number of locations (facilities) being pooled. We show that for the distributions considered, the absolute benefit of risk pooling increases with variability, and the relative benefit stays fairly constant, as long as the coefficient of variation of demand stays in the low range. However, under high‐variability conditions, both measures decrease to zero as the demand variability is increased. We show, through analytical results and computational experiments, that these effects are due to the different operating regimes exhibited by the system under different levels of variability: as the variability is increased, the system switches from the normal operation to the effective and then complete shutdown regimes; the decrease in the benefits of risk pooling is associated with the two latter stages. The centralization allows the system to remain in the normal operation regime under higher levels of variability compared to the decentralized system.

Managing development decisions for new products based on dynamically evolving technologies is a complex task, especially in highly competitive industries. Product managers often have to choose between introducing an incrementally better, safe new product early and a superior, yet highly risky, product later. Recommendations for managing such performance vs. time‐to‐market trade‐offs often ignore competitive reactions to development decisions. In this paper, we study how a firm could incorporate the presence of a strategic competitor in making technology selection and investment decisions regarding new products. We consider a model in which an innovating firm and its rival can introduce a new product immediately or pursue a more advanced product for later launch. Further, the firm can reduce the uncertainty surrounding product development by dedicating more resources; the effectiveness of this investment depends on the firm's innovative capacity. Our model generates two sets of insights. First, in highly competitive industries, firms can adopt different technologies and effectively use introduction timing to mitigate the effects of price competition. More importantly, the firm could strategically invest in the advanced product to influence its rival's technology choice. We characterize equilibrium development and investment decisions of the firms, and derive innovative capacity hurdles that govern a firm's choice between the risky and safe alternatives. The effects of development flexibility—where firms might have the option to revert to the safe product if the advanced product fails—are also considered.

We provide an overview of the state of the art in research on operations in financial services. We start by highlighting a number of specific operational features that differentiate financial services from other service industries, and discuss how these features affect the modeling of financial services. We then consider in more detail the various different research areas in financial services, namely systems design, performance analysis and productivity, forecasting, inventory and cash management, waiting line analysis for capacity planning, personnel scheduling, operational risk management, and pricing and revenue management. In the last section, we describe the most promising research directions for the near future.

We examine the drivers of project performance and customer satisfaction in outsourced software projects using a proprietary panel dataset. The data cover 822 customer observations related to 182 unique projects executed by an India‐based software services vendor. Adopting a multidisciplinary perspective, we investigate how project planning, team stability, and communication effectiveness impact project performance and customer satisfaction. We delineate the direct and interactive influences of the antecedent variables. We also examine how these influences are moderated by two important project contexts: (a) the nature of software work (maintenance and development vs. testing projects) and (b) project maturity (new vs. mature projects). Among other results, we demonstrate that, when project planning capabilities are high, the positive impact of team stability and communication effectiveness on project performance is even higher. In addition, our results suggest that the impact of communication on project performance is muted when team stability is high. Finally, we also demonstrate that the impact of the antecedent variables on project performance varies with the nature of software work. Our findings offer specific and actionable insights to managers that can help them manage outsourced projects better, and open up new research perspectives in the context of outsourced project management.

This paper examines the controversial role that Group Purchasing Organizations (GPOs) play in the supply chains for healthcare products. Among the controversies, perhaps the most fundamental one is whether or not GPOs reduce purchasing costs for their members. However, the fiercest controversy is around the “contract administration fees (CAFs)” that GPOs charge to manufacturers. We examine these and other controversies using a Hotelling duopoly model. Among our conclusions: GPOs increase competition between manufacturers and lower prices for healthcare providers. However, GPOs reduce manufacturers' incentives to introduce innovations to existing products. We also demonstrate that the existence of lower off‐contract prices is not, per se, evidence of anticompetitive behavior on the part of GPOs. Indeed, we demonstrate that, under certain circumstances, the presence of a GPO lowers off‐contract prices. We also examine the consequences of eliminating the “safe harbor” provisions that permit healthcare GPOs to charge CAFs to manufacturers, and conclude that it would not affect any party's profits or costs.

Shelf‐space scarcity is a predominant aspect of the consumer goods industry. This paper analyzes its implications for category management. We consider a model where two competing manufacturers sell their differentiated products through a single retailer who determines the shelf space allocated to the category. The scope of category management is pricing. We consider two category management mechanisms: retailer category management (RCM), where the retailer determines product prices and category captainship (CC), where a manufacturer in the category determines them. Our analysis reveals that the retailer can use the form of category management and the category shelf space to control the intensity of competition between manufacturers to his benefit. We also show that the emergence of CC depends on the degree of product differentiation, the opportunity cost of shelf space, and the profit sharing arrangement in the alliance. The equilibrium category shelf space under CC may be higher than under RCM if the value to the retailer of eliminating double marginalization and putting price pressure on the non‐captain manufacturer dominates the loss from sharing the profit with the category captain. CC has been criticized for disadvantaging non‐captain manufacturers. While we provide some support for this claim, we also find that CC may benefit non‐captain manufacturers when implemented by a powerful retailer in categories with sufficiently differentiated products, because the shelf space allocated to the category increases in this case.

In recent years, the competition for shelf space has intensified, as more products now compete for a retail space that has remained roughly constant. In this paper, we analyze the dynamics of this competition in a multi‐supplier retail point. Assuming that sales are shelf space dependent, we consider a retailer that optimizes its shelf space allocation among different products based on their sales level and profit margins. In this context, product manufacturers set their wholesale prices so as to obtain larger shelf space allocations but at the same time keep margins as high as possible. We analyze the equilibrium situation in the supply chain, and find that generally the retailer's and the suppliers' incentives are misaligned, resulting in suboptimal retail prices and shelf space allocations. We however find that the inefficiencies induced by suboptimal shelf space allocation decisions are small relative to those induced by suboptimal pricing decisions.

This paper investigates the impact of self‐service technology (SST) usage on customer satisfaction and retention. Specifically, we disentangle the distinct effects of satisfaction and switching costs as drivers of retention among self‐service customers. Our empirical analysis examines 26,924 multi‐channel customers of a nationwide retail bank. We track each customer's channel usage, overall satisfaction, and retention over a 1‐year period. We find that, relative to face‐to‐face service, customers who use self‐service channels for a greater proportion of their transactions are either no more satisfied, or less satisfied with the service they receive, depending on the channel. However, we also find that these same customers are predictably less likely to defect to a competitor if they are heavily reliant on self‐service channels characterized by high switching costs. Through a mediation model, we demonstrate that, when self‐service usage promotes retention, it does so in a way that is consistent with switching costs. As a robustness check, we examine the behavior of channel enthusiasts, who concentrate transactions among specific channels. Relative to more diversified customers, we find that self‐service enthusiasts in low switching cost channels defect with greater frequency, while self‐service enthusiasts in high switching cost channels are retained with greater frequency.

India is an important frontier for economic growth, investments, and development. The service sector, like the manufacturing industry, in India is booming. Following the trend of their western counterparts, service organizations in India are implementing enterprise‐level information and communication technologies (ICTs) to support service processes. In this paper, we used socio‐technical systems theory to develop hypotheses about the effects of ICTs on the five job characteristics, i.e., skill variety, task identity, task significance, autonomy, and feedback, in the job characteristics model (JCM) in a service organization (a bank) in India. We also tested the entire JCM that relates job characteristics to job satisfaction and job performance via various mediators and moderators. In a 32‐month longitudinal field study of 1743 employees, we gathered one wave of data before an ICT implementation and two waves after the implementation. We found that, although the ICT enriched employees' job characteristics, employees reported significantly lower job satisfaction and job performance. To understand this puzzling finding, we conducted a qualitative study and identified four contextual forces that contribute to these results and hinder successful implementation of ICTs in the service sector in India and, possibly, other developing countries: environmental barriers, learning difficulty, culture shock, and employee valuation.

As service failures are inevitable, firms must be prepared to recover and learn from service failures. Yet, the majority of customers are still dissatisfied with the way firms resolve their complaints. Can learning to reduce service failures reduce customer dissatisfaction, and to what extent are such reductions sustainable? Previous research showed that organizational learning curves for customer dissatisfaction (i) follow a U‐shaped function of operating experience and (ii) are heterogeneous across firms. In this paper, I tease out where the U‐shaped learning‐curve effect and learning‐curve heterogeneity originate: service failure or customers' propensity to complain with a third party given the occurrence of a service failure. Using quarterly data for nine major US airlines over 11 years, I find that the U‐shaped learning‐curve effect and the learning‐curve heterogeneity originate in the propensity to complain. In the long term, reductions in service failure did not translate in sustainable reductions in customer dissatisfaction. Customers' propensity to complain eventually went up. Managing the propensity to complain provides more opportunity for a firm to distinguish itself from competitors.