Investment in Facility Changeover Flexibility for Early Entry into High‐Tech Markets

A model is introduced to analyze the manufacturing‐marketing interface for a firm in a high‐tech industry that produces a series of high‐volume products with short product life cycles on a single facility. The one‐time strategic decision regarding the firm's investment in changeover flexibility establishes the link between market opportunities and manufacturing capabilities. Specifically, the optimal changeover flexibility decision is determined in the context of the firm's market entry strategy for successive product generations, the changeover cost between generations, and the production efficiency of the facility. Moreover, the dynamic pricing policy for each product generation is obtained as a function of the firm's market entry strategy and manufacturing efficiency. Our findings provide insights linking internal manufacturing capabilities with external market forces for the high‐tech and high‐volume manufacturer of products with short life cycles. We show the impact of manufacturing efficiency and a firm's ability to benefit from volume‐based learning on the dynamic pricing policy for each product generation. The results demonstrate the benefits realized by a firm that works with its manufacturing equipment suppliers to develop more efficient and flexible technology. In addition, we explore how opportunities afforded by pioneer advantage enable a firm operating a less efficient facility to realize long term competitive advantage by deploying an earlier market entry strategy.     

An Advanced Heuristic for Multiple‐Option Spare Parts Procurement after End‐of‐Production

After‐sales service is a major source of profit for many original equipment manufacturers in industries with durable products. Successful engagement in after‐sales service improves customer loyalty and allows for competitive differentiation through superior service like an extended service period during which customers are guaranteed to be provided with service parts. Inventory management during this period is challenging due to the substantial uncertainty concerning demand over a long time horizon. The traditional mechanism of spare parts acquisition is to place a large final order at the end of regular production of the parent product, causing major holding costs and a high level of obsolescence risk. With an increasing length of the service period, more flexibility is needed and can be provided by adding options like extra production and remanufacturing. However, coordinating all three options yields a complicated stochastic dynamic decision problem. For that problem type, we show that a quite simple decision rule with order‐up‐to levels for extra production and remanufacturing is very effective. We propose a heuristic procedure for parameter determination which accounts for the main stochastic and dynamic interactions in decision making, but still consists of relatively simple calculations that can be applied to practical problem sizes. A numerical study reveals that the heuristic performs extremely well under a wide range of conditions, and therefore can be strongly recommended as a decision support tool for the multi‐option spare parts procurement problem. A comparison with decision rules adapted from practice demonstrates that our approach offers an opportunity for major cost reductions.     

Strong Duality for a Multiple‐Good Monopolist

We characterize optimal mechanisms for the multiple‐good monopoly problem and provide a framework to find them. We show that a mechanism is optimal if and only if a measure μ derived from the buyer's type distribution satisfies certain stochastic dominance conditions. This measure expresses the marginal change in the seller's revenue under marginal changes in the rent paid to subsets of buyer types. As a corollary, we characterize the optimality of grand‐bundling mechanisms, strengthening several results in the literature, where only sufficient optimality conditions have been derived. As an application, we show that the optimal mechanism for n independent uniform items each supported on [c,c+1] is a grand‐bundling mechanism, as long as c is sufficiently large, extending Pavlov's result for two items Pavlov, 2011. At the same time, our characterization also implies that, for all c and for all sufficiently large n, the optimal mechanism for n independent uniform items supported on [c,c+1] is not a grand‐bundling mechanism.     

Using Real‐Time Decision Tools to Improve Distributed Decision‐Making Capabilities in High‐Magnitude Crisis Situations*

Multi‐organizational collaborative decision making in high‐magnitude crisis situations requires real‐time information sharing and dynamic modeling for effective response. Information technology (IT) based decision support tools can play a key role in facilitating such effective response. We explore one promising class of decision support tools based on machine learning, known as support vector machines (SVM), which have the capability to dynamically model and analyze decision processes. To examine this capability, we use a case study with a design science approach to evaluate improved decision‐making effectiveness of an SVM algorithm in an agent‐based simulation experimental environment. Testing and evaluation of real‐time decision support tools in simulated environments provides an opportunity to assess their value under various dynamic conditions. Decision making in high‐magnitude crisis situations involves multiple different patterns of behavior, requiring the development, application, and evaluation of different models. Therefore, we employ a multistage linear support vector machine (MLSVM) algorithm that permits partitioning decision maker response into behavioral subsets, which can then individually model and examine their diverse patterns of response behavior. The results of our case study indicate that our MLSVM is clearly superior to both single stage SVMs and traditional approaches such as linear and quadratic discriminant analysis for understanding and predicting behavior. We conclude that machine learning algorithms show promise for quickly assessing response strategy behavior and for providing the capability to share information with decision makers in multi‐organizational collaborative environments, thus supporting more effective decision making in such contexts.     

Impulse Balance and Multiple‐Period Feedback in the Newsvendor Game

Human subjects in the newsvendor game place suboptimal orders: orders are typically between the expected profit‐maximizing quantity and mean demand (“pull‐to‐center bias”). In previous work, we have shown that impulse balance equilibrium (IBE), which is based on a simple ex post rationality principle along with an equilibrium condition, can predict ordering decisions in the laboratory. In this study, we extend IBE to standing orders and multiple‐period feedback and show that it predicts—in line with previous findings—that constraining newsvendors to make a standing order for a sequence of periods moves the average of submitted orders toward the optimum.     

Technology‐Based New Product Development Partnerships*

Hypotheses were developed to capture the dynamic capabilities that result from interfirm partnerships during the joint new product development (NPD) process—the ability to build, integrate, and reconfigure existing resources to adapt to rapidly changing environments. These capabilities, in turn, were proposed to have a positive impact on NPD performance outcomes: (a) proportion of new product success and (b) superior new product commercialization. In contexts where the locus of innovation is rapidly changing, the impact of interfirm NPD dynamic capabilities was hypothesized to be diminished in high‐technology contexts, especially for buyers (original equipment manufacturers) and to a lesser extent for suppliers. Still, technology‐based interfirm NPD partnerships were predicted to ultimately outperform low‐technology ones in both NPD performance outcomes. Finally, information technology (IT) support for NPD was hypothesized to influence the interfirm NPD partnership's dynamic capabilities. Using survey data from 72 auto company managers and their suppliers, the proposed model in which IT support for NPD influences the success of interfirm NPD partnerships through the mediating role of interfirm NPD partnership dynamic capabilities in high‐ and low‐technology contexts was generally supported. The results shed light on the nature of technology‐based interfirm NPD partnerships and have implications for their success. Theoretical and managerial implications are discussed.     

An Empirical Investigation in Sustaining High‐Quality Performance

Many organizations that were once quality leaders have had challenges sustaining high‐quality performance. Although research has examined frameworks and concepts that lead to high‐quality performance, few studies examine how to sustain high‐quality performance. Sustaining performance may require additional capabilities from what it takes to achieve it. Drawing on quality management literature, organizational resilience literature, and the theory of dynamic capabilities in the strategy literature, this study empirically investigates the effects of four capabilities that help sustain high‐quality performance. The analysis shows that capabilities in improvement, innovation, sensing weak signals, and responsiveness all help sustain high‐quality performance. This suggests that what it takes to achieve high‐quality performance is different, in part, from what it takes to sustain it. The data comes from a survey of 147 manufacturing business units. The analysis shows that the relative benefits of these capabilities may depend on the level of competitive intensity and environmental uncertainty. The findings provide empirical support for a theoretical model and practical guidance for sustaining quality performance.     

Towards a Theory of Competitive Progression: Evidence from High‐Tech Manufacturing

This study replicates and extends Ferdows and De Meyers' observed ‘sand cone’ model of cumulative competitive capabilities by means of Roth's related competitive progression theory (CPT). Using path analysis, we model and test the relationships among the generic competitive capability constructs of conformance quality, delivery reliability, volume flexibility, and low cost as predicted by CPT. Our results, drawn from a sample of high‐tech manufacturers, provide further evidence that on average, these four capabilities are acquired both cumulatively and in that sequence. We also find that each generic capability increases operational know‐how and reduces non‐value‐added directly and/or indirectly through the enhancement of successive capabilities in the progression, which in turn improves profitability. The paper contributes a theoretical rationale for the observed sand cone effect, describes how the competitive progression acts to influence accelerated organizational learning over an innovation cycle, and offers evidence that combinative capabilities have strategic value for high‐tech manufacturers.     

ON‐THE‐JOB SEARCH AND MORAL HAZARD

We analyze the interaction between intertemporal incentive contracts and search frictions associated with on‐the‐job search. In our model, agency problems call for wage contracts with deferred compensation. At the same time workers do on‐the‐job search. Deferred compensation improves workers' incentives to exert effort but distorts their on‐the‐job search decisions. We show that deferred compensation is less attractive when the value to the worker–firm pair of on‐the‐job search is high. Moreover, the interplay between search frictions and wage contracts creates feedback effects. If firms in equilibrium use contracts with deferred compensation, fewer firms with vacancies enter the on‐the‐job search market, and this in turn reduces the distortions created by deferred compensation. These feedback effects between the incentive contracts used and the activity level in the search markets can lead to multiple equilibria: a low‐turnover equilibrium where firms use deferred compensation, and a high‐turnover equilibrium where they do not. Furthermore, the model predicts that firms are more likely to use deferred compensation when search frictions are high and when the gains from on‐the‐job search are small.     

Dynamic Supply Risk Management with Signal‐Based Forecast,Multi‐Sourcing,and Discretionary Selling

We examine the critical role of advance supply signals—such as suppliers’ financial health and production viability—in dynamic supply risk management. The firm operates an inventory system with multiple demand classes and multiple suppliers. The sales are discretionary and the suppliers are susceptible to both systematic and operational risks. We develop a hierarchical Markov model that captures the essential features of advance supply signals, and integrate it with procurement and selling decisions. We characterize the optimal procurement and selling policy, and the strategic relationship between signal‐based forecast, multi‐sourcing, and discretionary selling. We show that higher demand heterogeneity may reduce the value of discretionary selling, and that the mean value‐based forecast may outperform the stationary distribution‐based forecast. This work advances our understanding on when and how to use advance supply signals in dynamic risk management. Future supply risk erodes profitability but enhances the marginal value of current inventory. A signal of future supply shortage raises both base stock and demand rationing levels, thereby boosting the current production and tightening the current sales. Signal‐based dynamic forecast effectively guides the firm's procurement and selling decisions. Its value critically depends on supply volatility and scarcity. Ignoring advance supply signals can result in misleading recommendations and severe losses. Signal‐based dynamic supply forecast should be used when: (a) supply uncertainty is substantial, (b) supply‐demand ratio is moderate, (c) forecast precision is high, and (d) supplier heterogeneity is high.     

Single‐ and Multiple‐Informant Research Designs to Examine the Human Resource Management−Performance Relationship

During the last decades, many empirical studies have analysed the relationship between human resource management and firm performance. Despite the call for multiple‐rater designs, a relatively large number of researchers still rely on survey responses provided by a single informant in each organization. Single‐informant designs suffer from a number of problems, especially when the responses provided by different types of raters across firms are pooled into a single dataset prior to assessing their equivalence across raters. Using an illustration of the relationship between high performance work systems and firm performance, in this paper we observe that responses provided by managers holding different positions (human resource managers and sales managers) differ significantly and therefore pooling their responses into a single dataset may result in confusing conclusions. Furthermore, we demonstrate that differences arise in the estimated parameters when a multiple‐key‐informant approach, compared to a single‐informant design, is adopted. For these reasons, data collection using multiple key informants is recommended, based on the assumption that some raters in the firm will be more knowledgeable about the variables of interest than others.     

Data‐Driven Supply Chain Orientation and Financial Performance: The Moderating Effect of Innovation‐Focused Complementary Assets

Drawing on the complementary assets framework, this study explores the moderating effect of innovation‐focused complementary assets (CA‐I) on the relationship between a data‐driven supply chain orientation (DDSCO) and firm financial performance. To test the moderating effect, survey data gathered from 329 manufacturing firms in China were analysed using a moderated regression analysis. The results indicate that DDSCO has a significant positive effect on financial performance, and that capabilities for product and process innovation function as complementary assets moderating the DDSCO–performance relationship. The findings suggest that innovation‐focused complementary assets are performance differentiators when paired with a DDSCO and explain why some firms obtain financial benefits from the development of a DDSCO while others do not. Specifically, competitive advantage from a DDSCO may not be realized unless CA‐I and potentially other complementary assets are harnessed, thus providing useful practical guidance to managers. Hence, the study provides empirical support for the complementary assets framework.     

Learning‐by‐Doing,Organizational Forgetting,and Industry Dynamics

Learning‐by‐doing and organizational forgetting are empirically important in a variety of industrial settings. This paper provides a general model of dynamic competition that accounts for these fundamentals and shows how they shape industry structure and dynamics. We show that forgetting does not simply negate learning. Rather, they are distinct economic forces that interact in subtle ways to produce a great variety of pricing behaviors and industry dynamics. In particular, a model with learning and forgetting can give rise to aggressive pricing behavior, varying degrees of long‐run industry concentration ranging from moderate leadership to absolute dominance, and multiple equilibria.     

Over‐the‐Counter Markets

We study how intermediation and asset prices in over‐the‐counter markets are affected by illiquidity associated with search and bargaining. We compute explicitly the prices at which investors trade with each other, as well as marketmakers' bid and ask prices, in a dynamic model with strategic agents. Bid–ask spreads are lower if investors can more easily find other investors or have easier access to multiple marketmakers. With a monopolistic marketmaker, bid–ask spreads are higher if investors have easier access to the marketmaker. We characterize endogenous search and welfare, and discuss empirical implications.     

Inter‐organizational Cooperation and Environmental Change: Moderating Effects between Flexibility and Innovation Performance

The paper investigates the moderator effect of inter‐organizational cooperation in the relationship between workplace flexibility and innovation performance. This research question is important because innovation is dependent on the strategic integration of technological knowledge, requiring organizations to acquire new capabilities rapidly or to ensure the presence of knowledge that may be beyond existing internal capabilities. Inter‐organizational cooperation constitutes a relevant mechanism for a firm to increase its knowledge base concerning new products and processes. High‐cooperation firms may have more opportunities to take advantage of flexibility for innovation performance because it facilitates the access and dispersion of knowledge within the firm. We test the research hypotheses in a sample of manufacturing and service firms. The results contribute to the literature on flexibility and innovation because they demonstrate that inter‐organizational cooperation moderates the relationship between flexibility and innovation performance. We discuss the implications of these results for future research and managerial practice.     

End‐of‐Life Inventory Problem with Phaseout Returns

We consider the service parts end‐of‐life inventory problem of a capital goods manufacturer in the final phase of its life cycle. The final phase starts as soon as the production of parts terminates and continues until the last service contract expires. Final order quantities are considered a popular tactic to sustain service fulfillment obligations and to mitigate the effect of obsolescence. In addition to the final order quantity, other sources to obtain serviceable parts are repairing returned defective items and retrieving parts from phaseout returns. Phaseout returns happen when a customer replaces an old system platform with a next‐generation one and returns the old product to the original equipment manufacturer (OEM). These returns can well serve the demand for service parts of other customers still using the old generation of the product. In this study, we study the decision‐making complications as well as cost‐saving opportunities stemming from phaseout occurrence. We use a finite‐horizon Markov decision process to characterize the structure of the optimal inventory control policy. We show that the optimal policy consists of a time‐varying threshold level for item repair. Furthermore, we study the value of phaseout information by extending the results to cases with an uncertain phaseout quantity or an uncertain schedule. Numerical analysis sheds light on the advantages of the optimal policy compared to some heuristic policies.     

Optimal Reserve Prices in Name‐Your‐Own‐Price Auctions with Bidding and Channel Options

Few papers have explored the optimal reserve prices in the name‐your‐own‐price (NYOP) channel with bidding options in a multiple channel environment. In this paper, we investigate a double‐bid business model in which the consumers can bid twice in the NYOP channel, and compare it with the single‐bid case. We also study the impact of adding a retailer‐own list‐price channel on the optimal reserve prices. This paper focuses on achieving some basic understanding on the potential gain of adding a second bid option to a single‐bid system and on the potential benefits of adding a list‐price channel by the NYOP retailer. We show that a double‐bid scenario can outperform a single‐bid scenario in both single‐channel and dual‐channel situations. The optimal reserve price in the double‐bid scenario is no less than that in the single‐bid case. Furthermore, the addition of a retailer‐own list‐price channel could push up the reserve prices in both single‐bid and double‐bid scenarios.     

Multichannels Strategy Implementation: The Role of Channel Alignment Capabilities*

A firm's distribution channels represent a key portfolio of resources that can be leveraged for competitive advantage. One approach to this portfolio that has become increasingly important in recent years is multichannel distribution (MCD). While this strategy has important benefits in terms of market coverage and firm performance, the use of multiple channels seriously affects downstream channel roles such as service delivery, as the financial rewards to channel members and the services they offer are separated. A channel member who offers poor or no service can free‐ride on the services offered to the same customer from a different channel. We draw on agency theory to explain these negative consequences. Additionally, the resource‐based view of the firm along with capabilities theory provides two key means of alleviating these consequences: channel tracking capabilities and reward alignment capabilities. The study, conducted in an industry facing serious MCD issues (the outdoor sporting goods industry), used key informant data matched to secondary data. Our results show that managers can reap the performance rewards of MCD strategies while minimizing its negative consequences. In particular, monitoring practices such as frequent site visits and phone contact with customers develop the firm's channel tracking capabilities, allowing managers to better monitor downstream activities. This becomes particularly important as the complexity from having multiple channels increases. Likewise, reward alignment capabilities such as retail price maintenance agreements and cooperative advertising enable the manager to minimize conflict among channel participants by ensuring sufficient profitability for all channel members.     

Integrating a Top‐Down and a Bottom‐Up Approach: Formal and Informal Risk‐Handling Strategies in a Utility Company

In this study, we bring together a top‐down and a bottom‐up approach of risk handling. We do so by conceptualizing and qualitatively and quantitatively measuring formal and informal risk‐handling strategies in a Dutch utility company. We conceive of formal risk handling as regulating, training, and educating safety and enforcing rule compliance, while we distinguish three different informal risk‐handling strategies: discretionary specialization, tacit knowledge, and taking personal responsibility. We show that the formal risk‐handling strategy and the three informal risk‐handling strategies can be measured separately. Hence, we have validated the measurement of all four strategies derived from two different risk‐handling approaches. Moreover, we have demonstrated that the perceived use of the four strategies has different effects on unsafe behavior: formal risk handling and tacit knowledge decrease it, discretion increases it, and taking personal responsibility has no effect on unsafe behavior.     

Dynamic Marketing Capabilities: Toward an Integrative Framework

In recent years, the dynamic capabilities view has attracted attention in the management literature, and theoretical papers note many research challenges. Currently, one of the most significant issues is the role of the marketing function in the development of dynamic capabilities, and some recent discussions have even introduced the new term ‘dynamic marketing capabilities’. The main area of interest is how to achieve a well‐integrated framework to serve as the starting point for empirical papers. Although the most recent research proposes a wide range of processes as possible dynamic marketing capabilities, it is difficult to find consensus among these proposals. To resolve this difficulty, this paper seeks to define the dynamic marketing capabilities construct based on accepted components in the generic dynamic capabilities view. More specifically, it defines the role of dynamic marketing capabilities through absorptive capacity and knowledge management. By identifying these components and relating them in an integrative model, the authors propose to explain how dynamic marketing capabilities work and precisely which marketing processes promote both components.