Flow Coordination and Information Sharing in Supply Chains: Review,Implications, and Directions for Future Research

Advances in information technology, particularly in the e‐business arena, are enabling firms to rethink their supply chain strategies and explore new avenues for inter‐organizational cooperation. However, an incomplete understanding of the value of information sharing and physical flow coordination hinder these efforts. This research attempts to help fill these gaps by surveying prior research in the area, categorized in terms of information sharing and flow coordination. We conclude by highlighting gaps in the current body of knowledge and identifying promising areas for future research.     

e‐Business and Supply Chain Management

In recent years, the area of Supply Chain Management has generated a substantial amount of interest both by managers and researchers. This interest has also been fueled by the growth in the development and application of e‐business technologies. These technologies enable the supply chain manager to make coordinated decisions by integrating the diverse and sometimes conflicting objectives of the various trading partners in a chain. The purpose of this paper is to: (a) highlight strategic and tactical issues for analyzing supply chains in an e‐business setting based on papers published in this special issue; and (b) describe future research opportunities in this emerging interdisciplinary area.     

The Impact of E‐Replenishment Strategy on Make‐to‐Order Supply Chain Performance

This research investigates the impact of electronic replenishment strategy on the operational activities and performance of a two‐stage make‐to‐order supply chain. We develop simulation‐based rolling schedule procedures that link the replenishment processes of the channel members and apply them in an experimental analysis to study manual, semi‐automated, and fully automated e‐replenishment strategies in decentralized and coordinated decision‐making supply chain structures. The average operational cost reductions for moving from a manual‐based system to a fully automated system are 19.6, 29.5, and 12.5%, respectively, for traditional decentralized, decentralized with information sharing, and coordinated supply chain structures. The savings are neither equally distributed among participants, nor consistent across supply chain structures. As expected, for the fully coordinated system, total costs monotonically decrease with higher levels of automation. However, for the two decentralized structures, under which most firms operate today, counter‐intuitive findings reveal that the unilateral application of e‐procurement technology by the buyer may lower his purchasing costs, but increase the seller's and system's costs. The exact nature of the relationship is determined by the channel's operational flexibility. Broader results indicate that while the potential economic benefit of e‐replenishment in a decentralized system is substantial, greater operational improvements maybe possible through supply chain coordination.     

Supply Chain Knowledge and Performance: A Meta‐Analysis

Many firms make significant investments into developing and managing knowledge within their supply chains. Such investments are often prudent because studies indicate that supply chain knowledge (SCK) has a positive influence on performance. Key questions still surround the SCK–performance relationship, however. First, what is the overall relationship between SCK and performance? Second, under what conditions is the relationship stronger or weaker? To address these questions, we applied meta‐analysis to 35 studies of the SCK–performance relationship that collectively include more than 8,400 firms. Our conservative estimate is that the effect size of the overall relationship is  = .39. We also find that the SCK–performance relationship is stronger when (i) examining operational performance, (ii) gathering data from more than one supply chain node, (iii) gathering data from multiple countries, (iv) examining service industries, and (v) among more recently published studies. We also found that studies that embraced a single theory base (as opposed to using multiple ones) had a stronger SCK–performance relationship. Looking to the future, our meta‐analysis highlights the need for studies to (i) include lags between the measurement of SCK and performance, (ii) gather upstream data when examining innovation, (iii) examine SCK within emerging countries, and (iv) provide much more information relative to the nuances of the SCK examined.     

The Impact of Competitive Strategy and Supply Chain Strategy on Business Performance: The Role of Environmental Uncertainty*

This article investigates the relationships among competitive strategy, supply chain strategy, and business performance while examining the moderating effect of environmental uncertainty. A total of 604 questionnaires were collected from three cities in China, and the statistical results show significant moderating effects of external environment on the relationships among competitive strategy, supply chain strategy, and business performance. Firms that primarily focus on a differentiation strategy emphasize an agile supply chain strategy. Cost leaders are inclined to implement both lean and agile supply chain strategies, but their emphasis on agile strategy is significantly greater in a volatile environment than in a stable environment. The choice of supply chain strategy does not appear to be an “either‐or” decision and firms could adopt either a lean or an agile strategy, or both, depending on the environment. This article provides significant managerial implications for supply chain practitioners to co‐align supply chain strategy and competitive strategy with the environment to improve performance.     

Equity‐Based Incentives and Supply Chain Buy‐Back Contracts*

We analyze the effect of equity‐based incentives in a supply chain with a downstream firm and an upstream supplier. By using the operational decision as a signal to influence external investors’ beliefs, the downstream firm's manager intends to maximize a convex combination of the interim share price and the terminal cash flows. We show that equity‐based incentives create a side effect. Specifically, with a universal buy‐back contract, the deadweight loss of signaling induced by equity‐based incentives could spread throughout the supply chain and cause chain‐wide damages. To mitigate such undesirable consequences, we propose a new mechanism to eliminate the inefficiency. We derive the optimal mechanism that maximizes the downstream firm's profits subject to the constraint that the supply chain efficiency is not undermined. In contrast to the full‐information benchmark, this mechanism gives positive surplus to the supplier. [Submitted: January 5, 2011. Revisions received: June 20, 2011; December 11, 2011. Accepted: December 22, 2011.]     

Special Research Focus on Supply Chain Linkages: Challenges for Design and Management in the 21st Century*

Supply chain management is a central and important area for academic research due to its impact on firms competing in today's global economy. Managing the flow of materials from supply sources to the ultimate customer represents a major challenge for today's managers. To assist managers, the concept of supply chain management has been adopted by many business leaders as an important way to assist in designing, planning, and controlling the network of facilities and tasks that comprise the many stages of the supply chain. In turn, the flow of academic research in the area has increased to provide a better set of guidelines for effective implementation and execution. This article sets the stage for recently completed research concentrating on supply chain management issues. First, a definition of supply chain management is provided and compared to recent usage in this area and logistics management. Also, a framework is provided that structures this dynamic and complex management task. Second, a review of past research is presented to illustrate the many paths supply chain management has traveled, and important contributions to supply management understanding and decision making. Third, recently completed research articles are introduced that have been selected to be part of this special issue of Decision Sciences. And fourth, future research directions for supply chain management that need to be pursued by interested investigators are discussed.     

Leveraging Supply Chain Integration through Planning Comprehensiveness: An Organizational Information Processing Theory Perspective

This study extends prior research on supply chain planning and integration by examining the underlying capabilities by which firms exploit the information they gain from integration activities. We use organizational information processing theory (OIPT) to develop hypotheses that identify the comprehensiveness of an organization's supply chain planning capabilities as an important mediator in the relationship between its supply chain integration activities and its operational performance. Further, our interpretation of OIPT suggests that an organization's usage of technology‐enabled supply chain management systems (SCMS) moderates these effects. Using survey data from 445 global firms, we estimate the corresponding moderated‐mediation structural model. The results indicate that usage of SCMS enables organizations to better utilize the information they gain from external integration efforts (relationships with customers and suppliers), thus improving the comprehensiveness of their supply chain planning capabilities. In contrast, the use of SCMS appears to be a partial substitute for internal integration as a driver of planning comprehensiveness. Most importantly, the results suggest that planning comprehensiveness is a significant generative means by which integration and technology investments produce superior operational performance. These findings provide a richer and more theoretically grounded explanation of relationships between supply chain integration, supply chain planning, and operational performance.     

The Severity of Supply Chain Disruptions: Design Characteristics and Mitigation Capabilities

Supply chain disruptions and the associated operational and financial risks represent the most pressing concern facing firms that compete in today's global marketplace. Extant research has not only confirmed the costly nature of supply chain disruptions but has also contributed relevant insights on such related issues as supply chain risks, vulnerability, resilience, and continuity. In this conceptual note, we focus on a relatively unexplored issue, asking and answering the question of how and why one supply chain disruption would be more severe than another. In doing so, we argue, de facto, that supply chain disruptions are unavoidable and, as a consequence, that all supply chains are inherently risky. Employing a multiple‐method, multiple‐source empirical research design, we derive novel insights, presented as six propositions that relate the severity of supply chain disruptions (i) to the three supply chain design characteristics of density, complexity, and node criticality and (ii) to the two supply chain mitigation capabilities of recovery and warning. These findings not only augment existing knowledge related to supply chain risk, vulnerability, resilience, and business continuity planning but also call into question the wisdom of pursuing such practices as supply base reduction, global sourcing, and sourcing from supply clusters.     

Managing Differentiation‐Integration Duality in Supply Chain Integration*

Existing research focuses on the positive returns to operational performance of firms’ supply chain integration (SCI) with suppliers, buyers, and customers. We draw on differentiation‐integration duality and contingency theory to suggest that manufacturing firms should seek to achieve both integration through supply chain coordination activities and differentiation through modularity‐based manufacturing practices (MBMP). Using a sample of 261 manufacturing firms, we identify an inverse U‐shaped relationship between SCI and operational performance. Furthermore, we find support for the importance of differentiation‐integration duality as a fit between high levels of SCI and high levels of MBMP results in enhanced operational performance. We find support for a contingency perspective as fit is especially critical at higher levels of environmental uncertainty. Implications for theory, practice, and further research are suggested.     

A Transaction‐Efficiency Analysis of an Internet Retailing Supply Chain in the Music CD Industry*

The emergence of the Internet may have fundamentally altered the mechanisms underlying information exchanges between sellers and end consumers. However, little attention has been given to the impact these mechanisms have on the efficiency of supply chain operations. This paper begins to address this deficiency in the literature by evaluating supply chain transaction efficiency effects from Internet purchases by consumers. It develops and empirically tests a theoretical framework examining the role Internet purchases have in establishing transaction‐efficiency levels in product exchanges involving sellers, placed at different supply chain echelons, and consumers. The theoretical framework integrates the transaction‐cost and internet economics, inter‐organizational information systems, and supply chain management literatures. Empirical testing, via structural equation modeling, is based on archival data in the Internet music CD market. The results show that Internet‐mediated purchases by consumers allow for greater transaction efficiencies when inventory ownership is postponed farther upstream in the supply chain and supply chain echelons are disintermediated. The results also indicate that channel structure configuration, defined by the supply chains' Internet retailing echelon, moderates these transaction efficiency effects.     

绿色供应链管理的集成特性和体系结构

绿色供应链管理是一种现代企业的可持续发展模式。本文论述了绿色供应链管理的概念,分析了绿色供应链管理的集成特性,并建立了绿色供应链管理的体系结构。     

The Interdisciplinary Future of Supply Chain Management Research

Since the term supply chain management (SCM) was first introduced over 30 years ago, the field of SCM has undergone numerous transformations. Today, it is a prevailing theme in scholarly and popular research, and numerous disciplines claim its ownership. However, current and emerging SCM research challenges are becoming increasingly more complex. Fragmented and "siloed" research efforts across a range of disciplines may not be adequate to address the full complexities associated with these phenomena. We interviewed 50 SCM academic thought leaders, across a range of disciplines, and 20 SCM executives with the goal of helping researchers develop a consistent stream of work that builds on existing research, identifies relevant research directions, and provides guidance for the future. Although there were some differences in opinions, there was consensus on the boundary characteristics of SCM, as well as the identification of interdisciplinary research (IDR) as necessary for the enablement of SCM to address the numerous current and emerging intractable SCM challenges. In this article, we present these findings and provide a path forward based on the collective wisdom of these academics and executives.     

The Impact of Forecast Errors on Early Order Commitment in a Supply Chain*

Supply chain partnership involves mutual commitments among participating firms. One example is early order commitment, wherein a retailer commits to purchase a fixed‐order quantity and delivery time from a supplier before the real need takes place. This paper explores the value of practicing early order commitment in the supply chain. We investigate the complex interactions between early order commitment and forecast errors by simulating a supply chain with one capacitated supplier and multiple retailers under demand uncertainty. We found that practicing early order commitment can generate significant savings in the supply chain, but the benefits are only valid within a range of order commitment periods. Different components of forecast errors have different cost implications to the supplier and the retailers. The presence of trend in the demand increases the total supply chain cost, but makes early order commitment more appealing. The more retailers sharing the same supplier, the more valuable for the supply chain to practice early order commitment. Except in cases where little capacity cushion is available, our findings are relatively consistent in the environments where cost structure, number of retailers, capacity utilization, and capacity policy are varied.     

Modeling Supply Chain Dynamics: A Multiagent Approach*

A global economy and increase in customer expectations in terms of cost and services have put a premium on effective supply chain reengineering. It is essential to perform risk-benefit analysis of reengineering alternatives before making a final decision. Simulation provides an effective pragmatic approach to detailed analysis and evaluation of supply chain design and management alternatives. However, the utility of this methodology is hampered by the time and effort required to develop models with sufficient fidelity to the actual supply chain of interest. In this paper, we describe a supply chain modeling framework designed to overcome this difficulty. Using our approach, supply chain models are composed from software components that represent types of supply chain agents (e.g., retailers, manufacturers, transporters), their constituent control elements (e.g., inventory policy), and their interaction protocols (e.g., message types). The underlying library of supply chain modeling components has been derived from analysis of several different supply chains. It provides a reusable base of domain-specific primitives that enables rapid development of customized decision support tools.     

A Modeling Framework for Supply Chain Simulation: Opportunities for Improved Decision Making*

Owing to its inherent modeling flexibility, simulation is often regarded as the proper means for supporting decision making on supply chain design. The ultimate success of supply chain simulation, however, is determined by a combination of the analyst's skills, the chain members' involvement, and the modeling capabilities of the simulation tool. This combination should provide the basis for a realistic simulation model, which is both transparent and complete. The need for transparency is especially strong for supply chains as they involve (semi)autonomous parties each having their own objectives. Mutual trust and model effectiveness are strongly influenced by the degree of completeness of each party's insight into the key decision variables. Ideally, visual interactive simulation models present an important communicative means for realizing the required overview and insight. Unfortunately, most models strongly focus on physical transactions, leaving key decision variables implicit for some or all of the parties involved. This especially applies to control structures, that is, the managers or systems responsible for control, their activities and their mutual attuning of these activities. Control elements are, for example, dispersed over the model, are not visualized, or form part of the time‐indexed scheduling of events. In this article, we propose an alternative approach that explicitly addresses the modeling of control structures. First, we will conduct a literature survey with the aim of listing simulation model qualities essential for supporting successful decision making on supply chain design. Next, we use this insight to define an object‐oriented modeling framework that facilitates supply chain simulation in a more realistic manner. This framework is meant to contribute to improved decision making in terms of recognizing and understanding opportunities for improved supply chain design. Finally, the use of the framework is illustrated by a case example concerning a supply chain for chilled salads.     

Adaptive Tactical Pricing in Multi‐Agent Supply Chain Markets Using Economic Regimes

In today's complex and dynamic supply chain markets, information systems are essential for effective supply chain management. Complex decision making processes on strategic, tactical, and operational levels require substantial timely support in order to contribute to organizations' agility. Consequently, there is a need for sophisticated dynamic product pricing mechanisms that can adapt quickly to changing market conditions and competitors' strategies. We propose a two‐layered machine learning approach to compute tactical pricing decisions in real time. The first layer estimates prevailing economic conditions—economic regimes—identifying and predicting current and future market conditions. In the second layer, we train a neural network for each regime to estimate price distributions in real time using available information. The neural networks compute offer acceptance probabilities from a tactical perspective to meet desired sales quotas. We validate our approach in the trading agent competition for supply chain management. When competing against the world's leading agents, the performance of our system significantly improves compared to using only economic regimes to predict prices. Profits increase significantly even though the prices and sales volume do not change significantly. Instead, tactical pricing results in a more efficient sales strategy by reducing both finished goods and components inventory costs.     

A Purchasing Framework for B2B Pricing Decisions and Risk‐sharing in Supply Chains*

This paper presents a common modelling structure for (i) the implementation of operational policies by individual purchasing managers of risk‐sharing agreements among supply‐chain partners, and (ii) the integration of brick and click purchasing policies in a B2B. The problem of price uncertainty created within these two environments is modelled as a stochastic repetitive‐sales problem, applicable to any probability distribution. The model identifies sufficient conditions for regenerative ordering cycles, which allows for the use of the renewal reward theorem. The end result is a two‐price purchasing policy, which may substantially ease implementation problems across a global corporation's purchasing managers world‐wide and across B2B markets.     

Keep Your Friends Close? Supply Chain Design and Disruption Risk

In this article, we evaluate the relationship between supply chain design decisions and supply chain disruption risk. We explore two supply chain design strategies: (i) the dispersion of supply chain partners to reduce supply chain disruption risk versus (ii) the co‐location of supply chain partners to reduce supply chain disruption risk. In addition, we assess supply chain disruption risk from three perspectives: the inbound material flow from the supplier (supply side), the internal production processes (internal), and the outbound material flow to the customer (customer side) as a disruption can occur at any of these locations. We measure disruption risk in terms of stoppages in flows, reductions in flow, close calls (disruptions that were prevented at the last minute), disruption duration (time until normal operation flow was restored), and the spread of disruptions all the way through the supply chain. We use seemingly unrelated regression (SUR) to analyze our data, finding that lead times, especially supply side lead times, are significantly associated with higher levels of supply chain disruption risk. We find co‐location with suppliers appears to have beneficial effects to the reduction of disruption duration, and, overall supply side factors have a higher impact when it comes to supply chain disruption risk than comparable customer side factors.     

Channel Coordination for a Supply Chain with a Risk‐Neutral Manufacturer and a Loss‐Averse Retailer*

This articles considers a decentralized supply chain in which a single manufacturer is selling a perishable product to a single retailer facing uncertain demand. It differs from traditional supply chain contract models in two ways. First, while traditional supply chain models are based on risk neutrality, this article takes the viewpoint of behavioral principal–agency theory and assumes the manufacturer is risk neutral and the retailer is loss averse. Second, while gain/loss (GL) sharing is common in practice, there is a lack of analysis of GL‐sharing contracts in the supply chain contract literature. This article investigates the role of a GL‐sharing provision for mitigating the loss‐aversion effect, which drives down the retailer order quantity and total supply chain profit. We analyze contracts that include GL‐sharing‐and‐buyback (GLB) credit provisions as well as the special cases of GL contracts and buyback contracts. Our analytical and numerical results lend insight into how a manufacturer can design a contract to improve total supply chain, manufacturer, and retailer performance. In particular, we show that there exists a special class of distribution‐free GLB contracts that can coordinate the supply chain and arbitrarily allocate the expected supply chain profit between the manufacturer and retailer; in contrast with other contracts, the parameter values for contracts in this class do not depend on the probability distribution of market demand. This feature is meaningful in practice because (i) the probability distribution of demand faced by a retailer is typically unknown by the manufacturer and (ii) a manufacturer can offer the same contract to multiple noncompeting retailers that differ by demand distribution and still coordinate the supply chains.