An Examination of Socially Responsible Firms' Board Structure

This study investigates the structure of the board of directors at socially responsible (SR) firms. Using a sample of 394 SR firms and comparing these to a matched sample of firms, I find that SR firms have characteristics associated with effective board structures. For instance, SR firms have more outsiders and women directors, and less instance of CEO/Chairman duality than non-SR firms. Results are similar when using a continuous measure of social responsibility. Also, I document that SR firms have higher Governance Index scores than the matched sample. Overall, this suggests that a reason for shareholders' appeal in socially responsible firms and mutual funds may be because these firms have stronger governance mechanisms in place than do non-SR firms. In addition, it appears that effective governance structures are more likely to exist in firms that focus on a broad range of stakeholders, rather than in firms that have a strict focus on shareholder wealth maximization.     

Incentive for Peer‐to‐Peer Knowledge Sharing among Farmers in Developing Economies

This study examines the peer‐to‐Peer interactions among farmers when both knowledge learning and sharing are available. We construct a stylized model in which heterogeneous farmers are endowed with their initial production capabilities and can post questions in the platform for help. A representative expert regularly monitors the forum and provides answers to the farmers’ questions, but may be non‐responsive sometimes due to the limited capacity. A knowledgeable core user (farmer) can choose to be silent or responsive, and is allowed to strategically determine the informativeness of her answers. The farmers face the minimum quantity restriction for attracting the buyers, and must make production before the time of sales. We show that in equilibrium the core user never provides answers that are more informative than the expert's, irrespective of her ex ante knowledge level. Redesigning or restructuring the platform does not help eliminate this inefficient knowledge provision. We also find that hiring more staff to frequently monitor the forum turns out to be detrimental for the peer‐to‐peer interactions. Moreover, the competition on knowledge sharing between the platform expert and the core user features strategic complementarity sometimes but strategic substitution at other times. Third, charging for the platform usage may discourage uninformative answers, but it could also discourage the core user from sharing knowledge with other farmers.     

Toward an Effective Design of Behavioral Health Care Delivery: An Empirical Analysis of Care for Depression

A criticism of behavioral health care delivery is that it has largely missed the social determinants of behavioral health disorders and their diagnosis. Toward addressing this criticism, this study evaluates the delivery of behavioral health care as a part of primary care operations. Focusing on the treatment of depression, the study results show that: (i) primary care clinics operating in communities with superior social environment characteristics are associated with improved depression outcomes in the short term, and (ii) psychosocial resources (social and emotional support) and the built environment (man‐made resources and infrastructure to support human activity) of primary care clinics are associated with sustaining the improvement in depression outcome in the long term. Centering our attention on IT‐enabled, evidence‐based, and affordable primary care as mechanisms that can enable the integration of behavioral and medical care delivery, the results suggest that IT‐enabled and evidence‐based primary care are associated with improvements in depression outcomes. We also find that the effect of improving the affordability of behavioral health care delivery depends on the community's socioeconomic status. Primary care clinics in socioeconomically disadvantaged communities practicing cost‐containment are associated with improvements in depression outcomes, and, therefore, can contribute toward reducing disparities in behavioral health care delivery. Counter to our original expectations, we find that the effect of evidence‐based care on improvements on depression outcomes increases as the availability of medically trained behavioral health care specialists practicing in a community increases lending support to concerns that primary care clinics in resource‐rich communities obtain greater benefit from quality improvement interventions.     

Supply‐Chain Research Opportunities with the Poor as Suppliers or Distributors in Developing Countries

Many social enterprises and some companies have developed supply chains with the poor as suppliers or distributors to alleviate poverty and to create revenues for themselves. Such supply chains have created new research opportunities because they raise issues fundamentally different from those examined in the existing operations management literature. We report this phenomenon of supply chains with the poor as suppliers or distributors in developing countries and identify operations management (OM) research opportunities. We also provide some stylized models to serve as potential seeds for modeling‐based research in this area.     

Supply Chain Vulnerability Analysis Using Scenario‐Based Input‐Output Modeling: Application to Port Operations

Disruptive events such as natural disasters, loss or reduction of resources, work stoppages, and emergent conditions have potential to propagate economic losses across trade networks. In particular, disruptions to the operation of container port activity can be detrimental for international trade and commerce. Risk assessment should anticipate the impact of port operation disruptions with consideration of how priorities change due to uncertain scenarios and guide investments that are effective and feasible for implementation. Priorities for protective measures and continuity of operations planning must consider the economic impact of such disruptions across a variety of scenarios. This article introduces new performance metrics to characterize resiliency in interdependency modeling and also integrates scenario‐based methods to measure economic sensitivity to sudden‐onset disruptions. The methods will be demonstrated on a U.S. port responsible for handling $36.1 billion of cargo annually. The methods will be useful to port management, private industry supply chain planning, and transportation infrastructure management.     

Decision‐Making Analytics Using Plural Resilience Parameters for Adaptive Management of Complex Systems

It is critical for complex systems to effectively recover, adapt, and reorganize after system disruptions. Common approaches for evaluating system resilience typically study single measures of performance at one time, such as with a single resilience curve. However, multiple measures of performance are needed for complex systems that involve many components, functions, and noncommensurate valuations of performance. Hence, this article presents a framework for: (1) modeling resilience for complex systems with competing measures of performance, and (2) modeling decision making for investing in these systems using multiple stakeholder perspectives and multicriteria decision analysis. This resilience framework, which is described and demonstrated in this article via a real‐world case study, will be of interest to managers of complex systems, such as supply chains and large‐scale infrastructure networks.     

Knowledge Creation and Dissemination in Operations and Supply Chain Management

During the last 25 years, the ecosystem of knowledge creation and dissemination in operations and supply chain management has improved remarkably. We now see OM as a vibrant community and an ecosystem in steady state. Yet, there are many opportunities ahead to revitalize our field and to expand our influence. In the spirit of continuous improvement, we propose that we focus our major efforts on accelerating the following four developments: First, having greatly expanded the domain of operations management, we should continue to expand its boundaries. Second, after a visible increase in exploratory studies, our community should accelerate our pursuit of such research. Third, we encourage OM faculty to develop programs that enable Ph.D. students to carry out part of their work in actual organizational settings. Fourth, we should further strengthen our interactions with the business community and create mechanisms to systematically disseminate our research to its members.     

Research Constituents and Authorship Patterns in the Production and Operations Management Journal

The Production and Operations Management Society is the largest professional society dedicated to creating and disseminating knowledge in product and process design, operations, and supply chains for the management of manufacturing and services. Its research journal, Production and Operations Management (POM), covers all topics in the discipline and all research paradigms to serve the entire community. Since its inception in 1992, POM has become recognized as a top tier outlet for operations management research. We identify research institutions in the operations management community that have played major roles in developing the journal based on the research of their faculty members and doctoral graduates. Our findings show that the constituency of the journal reflects the constituency of the society.     

A Note on the Growth of Research in Service Operations Management

We present an empirical assessment of the productivity of individuals and institutions in terms of service operations management (SOM) research. We reviewed five mainstream operations management journals over a 17‐year time period to generate a sample of 463 articles related to service operations. The results indicate that SOM research has been growing and key contributions are being made by an array of researchers and institutions.     

Distributed Decision‐Making in Supply Chains and Private E‐Marketplaces

This paper develops a distributed decision‐making framework for the players in a supply chain or a private e‐marketplace to collaboratively arrive at a global Pareto‐optimal solution. In this model, no player has complete knowledge about all the costs and constraints of the other players. The decision‐making framework employs an iterative procedure, based on the Integer L‐shaped method, in which a master problem is solved to propose global solutions, and each player uses his local problems to construct feasibility and optimality cuts on the master problem. The master problem is modeled as a mixed‐integer program, and the players' local problems are formulated as linear programs. Collaborative planning scenarios in private e‐marketplaces and in supply chains were formulated and solved for test data. The results show that this distributed model is able to achieve near‐optimal solutions considerably faster than the traditional centralized approach.     

Introduction to the Special Issue on E‐Auctions for Procurement Operations

We present nine papers on e‐auctions for procurement operations. The first of the issue's three sections is a foreword highlighting current trends and future research directions. The second section is composed of three commissioned survey papers, covering auctions within e‐sourcing events, electronic markets for truckload transportation, and games and mechanism design in machine scheduling. The final section consists of five research papers on the following topics: whether auction parameters affect buyer surplus in e‐auctions for procurement, collusion in second‐price auctions under minimax regret, the effect of timing on jump bidding in ascending auctions, market‐based allocation with indivisible bids, and ranked items auctions and online advertisement.     

Operations in Financial Services—An Overview

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.     

Training,Production, and Channel Separation in ITC's E‐Choupal Network

In recent years, I.T.C. Limited (hereafter ITC) developed the “e‐Choupals” for the rural areas of India. In this new business model, ITC reaches implicit agreements with some farmers (inside the network) that they can sell the products directly to ITC at the market price in the local market, but allow the farmers, both inside and outside the network, to access valuable information through the e‐Choupals. In this study, we investigate ITC's incentive of offering such opportunities, especially to those farmers outside the network, and analyze the farmers’ strategic quantity decisions. We show that the implicit agreement behaves as a formal contract, regardless of the price elasticity of the local market: Once reaching an agreement with ITC, the farmers always give priority to delivering directly to ITC. The e‐Choupal network leads naturally to the complete separation of selling channels, provided that ITC's capacity constraint is not tight. Surprisingly, in a variety of scenarios, ITC finds it optimal to provide the best available training to the farmers outside the network. We further show that our results are not prone to potential cheating in the mandi system, the possible exploitation via postponed payments, and the stochastic effects on the market‐clearing price.     

Operations Strategy Research in the POMS Journal

In this paper, we examine the operations strategy literature in the POMS journal to determine what has been learned and to suggest new directions for further study in this important area of research. Our review of this literature resulted in the selection of thirty‐one relevant articles, many of which draw upon multiple theoretical perspectives. We identify eight such theoretical perspectives, and go on to classify these perspectives in terms of the scope of inquiry employed in the research (focused versus aggregated) and the researcher's assumptions about choice processes (behavioral versus rational). In doing so, we show that this body of work is dominated by papers that draw upon theoretical perspectives enabling a more holistic scope of inquiry, with a bias towards a view of strategy as a highly rational process. Building on our systematic review and integration of the literature, we suggest multiple areas for future research.     

Rational Inattention Dynamics: Inertia and Delay in Decision‐Making

We solve a general class of dynamic rational inattention problems in which an agent repeatedly acquires costly information about an evolving state and selects actions. The solution resembles the choice rule in a dynamic logit model, but it is biased toward an optimal default rule that is independent of the realized state. The model provides the same fit to choice data as dynamic logit, but, because of the bias, yields different counterfactual predictions. We apply the general solution to the study of (i) the status quo bias; (ii) inertia in actions leading to lagged adjustments to shocks; and (iii) the tradeoff between accuracy and delay in decision‐making.     

Timing the Use of Breast Cancer Risk Information in Biopsy Decision‐Making

Available clinical evidence is inconclusive on whether radiologists should use the patient risk profile information when interpreting mammograms. On the one hand, risk profile information is informative and can improve radiologists’ performance, but on the other hand, it may impair their judgment by introducing biases in mammography interpretation. Therefore, it is important to assess whether and when profile information use translates into improved outcomes. We model the use of profile information in mammography, using a decision theoretic approach and explore the value of profile information using three process design choices: mammography only, unbiased, and biased reading. We estimate the parameters of our model using clinical data and find that using profile information along with the mammography information can achieve a better performance than not using the profile information. However, the better performance is contingent on the weight assigned to the profile information as well as the extent of bias due to profile information. Translating our findings into clinical practice would require properly designed experiments aiming to quantify the effect of the timing and the use of profile information on performance while accounting for radiologist and patient characteristics. When conducting an experiment is not feasible, a uniform operational sequence for interpreting mammograms and related guidelines may be a useful starting point to improve the quality of mammography operations.     

On the Risk Management and Risk Governance of Petroleum Operations in the Barents Sea Area

In this article, we discuss issues of risk management and risk governance with respect to petroleum operations in the Barents Sea area. We will focus on the decision problems related to whether or not to open the Barents Sea for petroleum activities in special vulnerable areas. We will explore to what extent the International Risk Governance Council risk governance framework provides valuable insights for and assistance to the decisionmaker and other stakeholders (including the industry and NGOs). The study covers issues related to risk assessment and appraisal, risk acceptance and tolerability, the use of the precautionary principle, risk perception, stakeholder involvement, risk communication, and risk management. The overall aim of the article is to point to areas where the risk governance could have been and can be improved for these and similar decision problems.     

Three‐Stage Decision‐Making Model under Restricted Conditions for Emergency Response to Ships Not under Control

A ship that is not under control (NUC) is a typical incident that poses serious problems when in confined waters close to shore. The emergency response to NUC ships is to select the best risk control options, which is a challenge in restricted conditions (e.g., time limitation, resource constraint, and information asymmetry), particularly in inland waterway transportation. To enable a quick and effective response, this article develops a three‐stage decision‐making framework for NUC ship handling. The core of this method is (1) to propose feasible options for each involved entity (e.g., maritime safety administration, NUC ship, and ships passing by) under resource constraint in the first stage, (2) to select the most feasible options by comparing the similarity of the new case and existing cases in the second stage, and (3) to make decisions considering the cooperation between the involved organizations by using a developed Bayesian network in the third stage. Consequently, this work provides a useful tool to achieve well‐organized management of NUC ships.     

The Value of Information in Decision‐Analytic Modeling for Malaria Vector Control in East Africa

Decision analysis tools and mathematical modeling are increasingly emphasized in malaria control programs worldwide to improve resource allocation and address ongoing challenges with sustainability. However, such tools require substantial scientific evidence, which is costly to acquire. The value of information (VOI) has been proposed as a metric for gauging the value of reduced model uncertainty. We apply this concept to an evidenced‐based Malaria Decision Analysis Support Tool (MDAST) designed for application in East Africa. In developing MDAST, substantial gaps in the scientific evidence base were identified regarding insecticide resistance in malaria vector control and the effectiveness of alternative mosquito control approaches, including larviciding. We identify four entomological parameters in the model (two for insecticide resistance and two for larviciding) that involve high levels of uncertainty and to which outputs in MDAST are sensitive. We estimate and compare a VOI for combinations of these parameters in evaluating three policy alternatives relative to a status quo policy. We find having perfect information on the uncertain parameters could improve program net benefits by up to 5–21%, with the highest VOI associated with jointly eliminating uncertainty about reproductive speed of malaria‐transmitting mosquitoes and initial efficacy of larviciding at reducing the emergence of new adult mosquitoes. Future research on parameter uncertainty in decision analysis of malaria control policy should investigate the VOI with respect to other aspects of malaria transmission (such as antimalarial resistance), the costs of reducing uncertainty in these parameters, and the extent to which imperfect information about these parameters can improve payoffs.