Theory Development in Operations Management: Extending the Frontiers of a Mature Discipline via Qualitative Research

This invited paper discusses theory development in operations management. Many stellar researchers have made excellent contributions to theory development in our field. Operations management is a maturing discipline. Recently, theory driven empirical research has become common in top‐tier journals in our field. Impelled by this trend and due to the path dependency of research, in general, researchers have examined operations phenomena using theories from management and organizational science. How do we extend the frontiers of knowledge in our maturing discipline? How do we develop theories within the field of operations management? In examining some of the seminal ideas that have shaped our field, a common characteristic is that they relied on observational studies and conceptual reasoning. Is it time for us to stress the usefulness of qualitative research methods in our field? Could this lead to an intellectual renewal in our field and extend the frontier of a maturing discipline? This paper explores these questions and advances the notion that qualitative analysis needs to be emphasized more than it has been in recent past. This paper is meant to provoke discussion among empirical researchers in operations management.     

The Financial Impact of FSC Certification in the United States: A Contingency Perspective

This article focuses on an important and emergent standard for sustainable operations management: the Forest Stewardship Council (FSC) certification. Unlike similar certifications, its focus is on the entire upstream supply chain, reflecting the criticality of supply chain management to ensure sustainable products. We investigate the financial impact from FSC certification, offering valuable decision support for managers considering this certification. Taking a contingency perspective, we view a firm's supply chain position and its prior certification to the ISO 14001 standard as influencing the results. Drawing on signaling theory, we suggest that firms farther downstream in the supply chain realize significantly greater abnormal financial performance benefits than firms upstream in the supply chain. We further hypothesize that firms that were not ISO 14001 certified at the time of FSC certification realize significantly greater abnormal financial performance benefits than firms that did have the ISO 14001 certification. To test these hypotheses, we utilize financial data of all publicly traded firms in the United States that have obtained the FSC certification, and assess whether FSC certification leads to abnormal performance benefits considering the above contingencies. Data collected from the FSC Certificate Database and Compustat, employed in an event study, provide support for our hypotheses. Overall, our findings contribute to research on decision making in the context of sustainable operations management, and offer a plausible explanation for contradictory results in prior studies. We highlight the applicability of signaling theory to decision sciences research, and stress the need to consider contingencies in sustainability management research.     

On multi-criteria chance-constrained capacitated single-source discrete facility location problems

This work aims at investigating multi-criteria modeling frameworks for discrete stochastic facility location problems with single sourcing. We assume that demand is stochastic and also that a service level is imposed. This situation is modeled using a set of probabilistic constraints. We also consider a minimum throughput at the facilities to justify opening them. We investigate two paradigms in terms of multi-criteria optimization: vectorial optimization and goal programming. Additionally, we discuss the joint use of objective functions that are relevant in the context of some humanitarian logistics problems. We apply the general modeling frameworks proposed to the so-called stochastic shelter site location problem. This is a problem emerging in the context of preventive disaster management. We test the models proposed using two real benchmark data sets. The results show that considering uncertainty and multiple objectives in the type of facility location problems investigated leads to solutions that may better support decision making.     

Measurement Equivalence Using Generalizability Theory: An Examination of Manufacturing Flexibility Dimensions

As the field of decision sciences in general and operations management in particular has matured from theory building to theory testing over the past two decades, it has witnessed an explosion in empirical research. Much of this work is anchored in survey‐based methodologies in which data are collected from the field in the form of scale items that are then analyzed to measure latent unobservable constructs. It is important to assess the invariance of scales across groups in order to reach valid, scientifically sound conclusions. Because studies have often been conducted in the field of decision sciences with small sample sizes, it further exacerbates the problem of reaching incorrect conclusions. Generalizability theory can more effectively test for measurement equivalence in the presence of small sample sizes than the confirmatory factor analysis (CFA) tests that have been conventionally used for assessing measurement equivalency across groups. Consequently, we introduce and explain the generalizability theory (G‐theory) in this article to examine measurement equivalence of 24 manufacturing flexibility dimension scales that have been published in prior literature and also compare and contrast G‐theory with CFA. We show that all the manufacturing flexibility scales tested in this study were invariant across the three industry SIC groups from which data were collected. We strongly recommend that G‐theory should always be used for determining measurement equivalence in empirical survey‐based studies. In addition, because using G‐theory alone does not always reveal the complete picture, CFA techniques for establishing measurement equivalence should also be invoked when sample sizes are large enough to do so. Implications of G‐theory for practice and its future use in operations management and decision sciences research are also presented.     

Flow management and its impacts on operational performance

Based on the organisational capability perspective and the concept of flow management, this study examines the inter-relationships between the management of five flows (human, information, decision, logistics and production flows) and their effects on operational performance. The research model was empirically tested using data from 321 Australian companies. The results show that human flow management (HFM) has a positive effect on the management of the other four flows. Further, information flow management (IFM) is positively associated with logistics flow management (LFM), whereas decision flow management (DFM) is positively associated with both production flow management (PFM) and LFM. The results also show that HFM, PFM and LFM can improve operational performance directly, whereas IFM and DFM only enhance operational performance indirectly. Our findings contribute to flow management theories and practices.     

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.     

Editorial for special issue on: humanitarian operations management

Abstract

Over the past decades, there has been increasing interest in studying humanitarian operations management. The mismatch between global humanitarian needs and the resources available, together with chronic vulnerability in many parts of the world, continues to have a direct bearing on the lives of millions of people in need of assistance. It also means that donors have to re-double their efforts to respond to disasters in a more efficient and effective manner. International humanitarian organizations (IHOs) often deal with a mix of disaster response and development programmes simultaneously. This operational mix entails disaster cycle management challenges such as project and programme planning of multi-objective global logistics, balancing earmarked donations for disaster response with budget needs for development programmes, and determining the push-pull boundaries in the supply chain, particularly with the increase in cash transfer programmes. The main purpose of this special issue is to report on research in humanitarian operations management. This special issue attempts to explore and examine the above topical issues at strategic, operational and technical levels.     

Estimation of Deprivation Level Functions using a Numerical Rating Scale

Evaluating and quantifying human suffering in humanitarian operations offers an innovative and potentially powerful way to assess the performance of humanitarian logistics (HL) and help build optimization models. Previous studies have suggested deprivation cost as a metric and have estimated deprivation cost functions for water using willingness‐to‐pay. Our study proposes deprivation levels, defined as the degree of human suffering caused by lack of access to a good or service, and estimates deprivation level functions using a numerical rating scale. Analyzing data collected from respondents with and without disaster experience, we find that individuals in the latter category estimate deprivation differently from the beneficiaries of disaster relief. Our study demonstrates that deprivation levels can be expressed as logistic growth functions with a typical S‐shape, and that these can be integrated into HL optimization models to better account for human suffering.     

客户时间窗变化的物流配送干扰管理模型——基于行为的视角

针对客户时间窗变化而导致的物流配送难以顺利实施这一难题,运用干扰管理思想,以提高物流配送干扰管理决策过程的科学性为目标,结合行为科学中对人的行为感知的研究方法与运筹学中定量的研究手段,分析客户时间窗变化这类干扰事件对客户、物流配送运营商和配送业务员等受扰主体的影响,研究基于行为的扰动度量方法, 构建客户时间窗变化的字典序多目标干扰管理模型,并给出快速高效的求解方法。实例结果表明:本文方法比已有的全局重调度方法和局部重调度方法更实用--能够均衡各方的利益,获得扰动最小的调整方案。     

逆向物流网络设计研究进展

随着环境资源压力的增大,政府法制要求以及社会环保要求的提升,研究者对逆向物流网络的研究日益关注。本文系统地对近几年的逆向物流网络设计研究进行回顾,讨论并对比研究了网络设计研究问题,研究方法,定量模型,求解算法以及逆向物流网络设计中不确定环境方面的研究。探讨了逆向物流网络研究中的不足,为研究者未来的研究方向提供了参考。     

Strategic Management of Operations in the Emergency Department

This study is based on the analysis of field data on the revenues and patient flows that we collected on all adult emergency department (ED) visits to a level‐1 trauma, tertiary referral center. Our objective was to provide researchers in operations a rich overview of the processes, resources, and metrics of financial and operations performance in the ED. We analyze how patients, physicians, hospitals/physician employer groups, and payers are party to the value created and financial workflow of the ED. A waterfall model for professional services revenue is developed that highlights the impacts of changes in processes, resources, scale, complexity, and mix of patients treated in the ED. We also discuss future implications of new compensation models and potential scenarios that will focus upon controlling costs while maximizing population health and patient satisfaction. These models will necessitate re‐engineering of operations in the ED from a strategic perspective. Four major thrusts for selecting the capacity portfolio in the ED operations to align the interests of all the stakeholders are recommended. New avenues for research are also identified.     

Are People Willing to Buy Natural Disaster Insurance in China? Risk Awareness,Insurance Acceptance,and Willingness to Pay

After the Wenchuan earthquake (magnitude 7.9, May 12, 2008), intensive debates on how China should establish a natural disaster insurance system were initiated among researchers, policymakers, and insurance professionals. Our focus was the social aspects of disaster insurance, explored in China through a nationwide survey. Our questionnaires investigated people's risk awareness, insurance acceptance, their opinions on governmental measures for disaster management, and their willingness to pay for disaster house insurance. We analyzed the results at both regional and individual scales. We found that the integrated hazard index and respondents’ experience of insurance (considered objective factors), and their opinions on the importance of insurance and government responsibility (considered subjective factors) showed strong correlation with the regional overall acceptance of disaster insurance. An individual's decision to participate highly depended on his/her experience of both insurance and disaster and his/her opinion on the importance of insurance as a coping mechanism. Respondents from poverty‐stricken or less‐developed counties were not necessarily more reluctant to accept natural disaster insurance, though they exhibited relatively lower ability to afford insurance. In general, respondents had correct perceptions of natural disasters in their areas; however, people from regions with a greater multihazard threat showed less willingness to accept disaster insurance because they tended to expect the government to undertake to cover losses and considered insurance to be less important. People's willingness to pay for an assumed disaster house insurance was also investigated and analyzed. We consequently discuss the policy implications for developing a disaster insurance system in China.     

Regionalization vs. globalization in advertising research: Insights from five decades of academic study

This paper is a response to calls for more research into the regional–as opposed to global–level of international business operations (Rugman and Verbeke, 2004). Focusing on a key issue in international management, the standardization decision, this paper presents a systematic review of top journal articles published over the last five decades on the subject of advertising standardization at the regional level. The results of this review demonstrate that in the last decade studies have frequently taken a regional rather than international focus of analysis, suggesting a shift in research in line with regionalization theory. However, this study also shows that research on regional standardization has lacked consistency in relation to how the phenomenon should be defined and measured. We present a conceptualization of measurement approaches to international advertising standardization, propose a typology of approaches and discuss their implications for knowledge advancement in the area.     

Decision Sciences Research in China: A Critical Review and Research Agenda—Foundations and Overview*

This article focuses on decision sciences research in China, providing an overview of current research and developing a foundation for future China‐based research. China provides a unique research opportunity for decision sciences researchers, owing to its recent history, rapid economic development, and strong national culture. We examine recent economic reforms and their impact on the development of research questions in the decision sciences, as well as discuss characteristics of the diverse regions in China and their potential as sites for various types of research. We provide a brief overview of recent China‐based research on decision sciences issues relating to national culture, supply chain management, quality management, production planning and control, operations strategy, and new product development and discuss some of the unique methodological challenges inherent in China‐based research. We conclude by looking forward to emerging research opportunities in China.     

Lean and green in the transport and logistics sector – a case study of simultaneous deployment

The transport and logistics sector is of vital importance for the stimulation of trade and hence the economic development of nations. However, over the last few years, this sector has taken central stage in the green agenda due to the negative environmental effects derived from its operations. Several disciplines including operations research and sub-areas of supply chain management such as green supply chains, green logistics and reverse logistics have tried to address this problem. However, despite the work undertaken through these disciplines, theoretical or empirical research into the sequential or simultaneous deployment of the lean and green paradigms, particularly, in the road transport and logistics sector is limited. This paper presents a case study where both paradigms have been combined to improve the transport operations of a world leader logistics organisation in the metropolitan area of Monterrey, Mexico. To do this, a systematic methodology and a novel tool called Sustainable Transportation Value Stream Map (STVSM) were proposed. The results obtained from the case study indicate that the concurrent deployment of the green and lean paradigms through such methodology and the STVSM tool is an effective approach to improve both operational efficiency and environmental performance of road transport operations. The paper can be used as a guiding reference for transport and logistics organisations to undertake improvement projects similar to the one presented in this paper. Additionally, this research also intends to stimulate scholarly research into the application of lean and green paradigms in the transport and logistics sector to expand the limited research pursued in this area.     

An Integrated Logistic Model for Predictable Disasters

In the aftermath of a disaster, the relief items are transported from temporary warehouses (Staging Areas, SAs) to the Points of Distribution (PODs). Reducing the response time to provide relief items to disaster victims and cost minimization are two important objectives of this study. We propose an integrated optimization model for simultaneously determining (1) locations of staging areas, (2) inventory assignments to these SAs, (3) selecting sizes and numbers of trucks, and (4) routing of trucks from SAs to PODs. We also introduce another variable, a value function, which forces the model to reduce the logistics response time. We study the interactions among these variables through extensive sensitivity analysis. The time horizon for supply of relief items to disaster areas is usually limited to six days after the disaster occurs. Therefore, we use the proposed optimization model in a rolling‐horizon manner, one day at a time. This reduces daily demand uncertainty. We analyze three disaster scenarios: (1) a low impact disaster, (2) a medium impact disaster, and (3) a high impact disaster. We conduct 720 experiments with different parameter values, and provide answers to the following questions that are useful for the logistic managers: (i) What are the right sizes (in terms of storage capacities) of SAs closer to the PODs? (ii) How should the budget be allocated in a disaster scenario? (iii) What mix of different types (in terms of sizes) of trucks should be selected in a given scenario? The most important managerial insights include: (i) operational budget beyond a limit does not improve the operational efficiency, (ii) when the budget is very low, it is essential to select smaller SAs close to the PODs in order to carry out operations in a feasible manner, (iii) when the impact of disaster is high, it is always beneficial to select larger SAs close to the PODs (as long as the budget is not very low), (iv) when the budget is high and the impact of disaster is not very high, the emergency management administrators need to select SAs prudently based on the tradeoff between the operational cost and the humanitarian value, and (v) the cost of operations is higher when all the trucks are of the same type compared to the case when there is a mix of different types of trucks. Also, we find that the optimal selection of SAs is not impacted by different combinations of the types of trucks. The focus of this study is on disasters that can be forecasted in advance and provide some lead time for preparations, for example, hurricanes. In order to understand the disaster management process of such disasters and develop our model, we (i) interviewed several emergency management administrators, and (ii) studied the disaster management processes available in documents released by various government agencies.     

An integrated survey of deterministic project scheduling

There have been many survey papers in the area of project scheduling in recent years. These papers have primarily emphasized modeling and algorithmic contributions for specific classes of project scheduling problems, such as net present value (NPV) maximization and makespan minimization, with and without resource constraints. Paralleling these developments has been the research in the area of project scheduling decision support, with its emphasis on data sets, data generation methods, and so on, that are essential to benchmark, evaluate, and compare the new models, algorithms and heuristic techniques. These investigations have extended the frontiers of research and application in all areas of project scheduling and management. In this paper, we survey the vast literature in this area with a perspective that integrates models, data, and optimal and heuristic algorithms, for the major classes of project scheduling problems. We also include recent surveys that have compared commercial project scheduling systems. Finally, we present an overview of web-based decision support systems and discuss the potential of this technology in enabling and facilitating researchers and practitioners in identifying new areas of inquiry and application.     

Lot sizing and scheduling: a survey of practices in Brazilian companies

The lot sizing and scheduling (LSS) problem has motivated much research in production planning and control. However, while there are many papers on modelling this problem, there is scant research on how it is addressed in the industry. We present a survey of Brazilian industry practices in LSS, intending to understand the problem faced by operations managers, drawing parallels with academic findings to identify gaps between theory and practice and opportunities for future research. We confirm that the main objective of practitioners in companies operating under MTS strategy is to maximise service level, followed by inventory reduction. Availability of raw material, demand uncertainty and safety stock levels, lack of decision support software and the impact of sequence-dependent set-up times are other major concerns highlighted by the practitioners. Lastly, we confirmed that despite the relevant body of research on this problem, there is still a large gap between theory and practice.