Operations Management Community Research Articles

Operations Management in the Age of the Sharing Economy: What Is Old and What Is New?

The sharing economy, a term we use to refer to business models built around on-demand access to products and services mediated by online platforms that match many small suppliers or service providers to many small buyers, has emerged as an important area of study in operations management. We first describe three canonical applications that have garnered much attention from the operations management community. We use these applications to highlight distinguishing features of sharing economy business models and to point out research questions that are new. Then we draw connections between classical operations management theory/models and theory/models that have been used to study sharing economy applications. We do so to put in context some of the recent work on sharing economy, and to showcase the underlying modeling toolkit and identify opportunities for future research.

Technical Note—Error Noted in “Order-Based Cost Optimization in Assemble-to-Order Systems” by Lu and Song (2005)

Discrete convexity, which extends submodularity to integer vectors, has been used in the economics and management literature to characterize the behavior of optimal policies. One of its variants, called L♮-convexity, has enabled recent advances in various operations management systems. In a paper published by Operations Research in 2005, an assemble-to-order inventory system was shown to have the L♮-convexity property, which was used to motivate an efficient algorithm. In a technical note, “Error Noted in ‘Order-Based Cost Optimization in Assemble-to-Order Systems’ by Lu and Song (2005)” by Bolandnazar, Huh, McCormick, and Murota, the authors show that the proof in that paper is incorrect and L♮-convexity may not hold. Despite this error, the authors credit Lu and Song for introducing this useful concept to the operations management community.

OM Forum—New Opportunities for Operations Management Research in Sustainability

Operations management (OM) research has made several important contributions to environmental sustainability over the last two decades. In this article, we point to a new opportunity on the horizon—the circular economy movement, which is gaining significant traction in practice. We introduce the concept and highlight the building blocks behind it. We also explain why this trend in practice can provide an opportunity for the OM community. To do so, we describe four companies that have been positioned as prime examples of implementing the circular economy concept and discuss the operational challenges faced by them. We draw on them to identify several promising and open questions for OM research and explain why an operations perspective is critical in this context.

A Smart-City Scope of Operations Management

We are entering an era of great expectations towards our cities. The vision of “smart city” has been pursued worldwide to transform urban habitats into superior efficiency, quality and sustainability. This phenomenon prompts us to ponder what role the scholars in operations management (OM) can assume. In this essay, we express our initial thoughts on expanding OM to the smart-city scope. We review smart-city initiatives of governments, industry, national laboratories and academia. We argue that the smart-city movement will transition from the tech-oriented stage to the decision-oriented stage. Hence, a smart city can be perceived as a system scope within which planning and operational decisions are orchestrated at the urban scale, reflective of multidimensional needs, and adaptive to massive data and innovation. The benefits of studying smart-city OM are manifold and significant: contributing to deeper understanding of smart cities by providing advanced analytical frameworks, pushing OM knowledge boundaries (such as data-driven decision making), and empowering the OM community to deliver much broader impacts than before. We discuss several research opportunities to embody these thoughts, in the interconnected contexts of smart buildings, smart grid, smart mobility and new retail. These opportunities arise from the increasing integration of systems and business models at the urban scale.

Enabling Smarter Cities with Operations Management

Recent development of new technologies and data analytics has unleashed the so-called smart city movement, which has been transforming the ways that cities (and their services) operate. This movement is in line with the Operations Management (OM) community's pursuit of innovative research questions, and part of our community has already started working on this exciting area of smart city OM. In this article, we shall discuss (i) the potential contribution that OM can make to the smart city movement, i.e., how OM research may help inform discussion and decision making in the public and private sectors. In particular, the core principle of making cities smarter is in line with the OM literature. We then discuss (ii) how and why SC operations can be an interesting topic that possibly expands the scope and depth of OM theory, through drawing links to the existing and new streams of OM literature. Finally, we present (iii) a few promising research directions and examples, in domains such as energy, transportation (mobility), and retail.

Operational Risk in Financial Services: A Review and New Research Opportunities

We present a framework to describe and analyze operational risk in financial services from an operations management perspective, focusing in particular on process design, process management, and human behavior aspects. The financial services industry differs from other service industries in ways that affect the nature of the operational risks it is subject to. In recent decades, many books and papers have focused on operational risk in financial services; however, this literature has focused mainly on the conceptual and statistical aspects of operational risk management and not on its operational aspects. Operational risk in financial services has not received much attention from the operations management community. The framework presented here is based on the premise that operational risk in financial services can reap significant benefits from research done in the theory and practice of operations management in manufacturing industries as well as in other services industries. The objective of this study is to propose particular challenges and questions raised in the practice of operational risk management that may stimulate future research in this particular area of operations management.

Recent Research Developments of Strategic Consumer Behavior in Operations Management

Strategic consumer behavior has been extensively studied in the Management Science and Operations Management community. We survey recent developments in the literature and review possible operational strategies and decisions to counteract the adverse impact of strategic consumer behavior. Specifically, we broadly characterize these decisions into three classes -- Pricing, Inventory, and Information -- and further discuss the influence of strategic consumer behavior on these decisions and their underlying mechanisms on counteracting consumers' strategic waiting behavior.

Estimating cross-training call center capacity through simulation

Call centers have grown world-wide during the past decade. One of the most important aspects considered by call center managers is the optimization of its operators, which implies covering the highly variable demand and finding an efficient way to assign people to certain shifts in order to achieve a desirable service level and abandonment rate. Another challenge is determining which system setup is appropriate for the specific call center. Should we have a single-skill call center or multi-skill call center? If we do have the latter, how many multi-skill agents should we have on staff? In this case study, we generate and analyze discrete-event systems simulation-optimization models to test the behavior of a real-world call center under the actual configuration and under different levels of cross-training. The model results help call center managers by: 1) determining the optimal number of operators needed for different staff configurations in order to achieve the targets for service level and abandonment; 2) providing information about the trade-off between the key measurements in the call center; and 3) providing useful information about the number of operators needed and used for each hour of operation to estimate the number of four-hour shifts required to achieve the performance targets. Our experimental findings from this case study suggest that a bi-skill call center is economically better in the long-run compared to a full-skill or single-skill call center. This case study augments the call center body of knowledge by providing additional managerial insights for the operations management community.

Operational Risk in Financial Services: A Review and New Research Opportunities

The financial services industry differs from other service industries in ways that affect the nature of the operational risks it is subject to. In recent decades, many books and papers have focused on operational risk in financial services. However, the literature has focused mainly on the conceptual and statistical aspects of operational risk management and not on its operational aspects. Operational risk in financial services has not received much attention from the operations management community. This paper is based on the premise that operational risk in financial services can reap significant benefits from research done on the theory and practice of operations management in other industries. Moreover, the particular challenges and questions raised in the practice of operational risk management may stimulate future research in this particular domain of operations management. We provide a framework to describe and analyze operational risk from an operations management perspective, focusing in particular on process design, process management and human behavior aspects.

Trademark colours: Cadbury vs Nestlé & Beiersdorf vs Unilever

The field of economics associates capacity planning with economic scale size and finds the characteristics of the production function whereas the operations management community focuses on demand fulfillment to reduce the loss of sales or inventory for profit maximization. However, there is a troublesome capacity trade-off for firms that need to achieve economic scale size and demand fulfillment simultaneously; in particular, a firm's demand is variable and some of the variation is random. This study proposes a multi-objective mathematical program with data envelopment analysis (DEA) constraints to set an efficient target which shows a trade-off between the most-productive-scale-size (MPSS) benchmark and a potential demand fulfillment benchmark. The study also employs the minimax regret (MMR) approach and the stochastic programming (SP) technique to address target variations caused by demand fluctuations. The result shows how capacity planning via the proposed models can help managers address the capacity dilemma.

Most productive scale size versus demand fulfillment: A solution to the capacity dilemma

The field of economics associates capacity planning with economic scale size and finds the characteristics of the production function whereas the operations management community focuses on demand fulfillment to reduce the loss of sales or inventory for profit maximization. However, there is a troublesome capacity trade-off for firms that need to achieve economic scale size and demand fulfillment simultaneously; in particular, a firm's demand is variable and some of the variation is random. This study proposes a multi-objective mathematical program with data envelopment analysis (DEA) constraints to set an efficient target which shows a trade-off between the most-productive-scale-size (MPSS) benchmark and a potential demand fulfillment benchmark. The study also employs the minimax regret (MMR) approach and the stochastic programming (SP) technique to address target variations caused by demand fluctuations. The result shows how capacity planning via the proposed models can help managers address the capacity dilemma.

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.

Building theory of sustainable manufacturing using total interpretive structural modelling

The purpose of this paper is to generate theory using total interpretive structural modelling. In this paper, an extensive review of extant literature was undertaken to identify research gaps. To bridge the existing gaps, an approach has been undertaken to further alternative methods in theory building in the field of operations management. This paper presents our arguments supported by extant literature to adopt total interpretive structural modelling technique to generate theory. The total interpretive structural modelling and cross multiplication impact matrix output were synthesised to generate a sustainable manufacturing framework which is the integration of three independent theories. The sustainable manufacturing framework is the unique contribution of this paper, which suggests how human agency theory, institutional theory can contribute to ecological modernisation theory. In future the theory developed can be tested using multivariate analysis using data, gathered through structured questionnaire. Finally, the research limitations and further research directions were outlined which may help operations management community to extend the current theoretical framework to next level.

A Capacitated Facility Location Model with Bidirectional Flows

Supply chains with returned products are receiving increasing attention in the operations management community. The present paper studies a capacitated facility location model with bidirectional flows and a marginal value of time for returned products. The distribution system consists of a single supplier that provides one new product to a set of distribution centers (DCs), which then ships to the final retailers. While at the retailers' site, products can be shipped back to the supplier for reprocessing. Each DC is capacitated and handles stocks of new and/or returned products. The model is a nonlinear mixed-integer program that optimizes DC location and allocation between retailers and DCs. We show that it can be converted to a conic quadratic program that can be efficiently solved. Some valid inequalities are added to the program to improve computational efficiency. We conclude by reporting numerical experiments that reveal some interesting properties of the model.

Introduction to the Special Issue on the Environment

Human population growth and increasing consumption per capita are causing environmental impacts that threaten the survival and well-being of humans and other species on Earth. To sustain natural ecosystems and human populations with a high standard of living, humanity must now reinvent our systems for the production and delivery of goods and services to dramatically reduce the environmental impacts associated with consumption. The operations management community can contribute critical know-how to do so, as demonstrated by the papers in this special issue.

OM Forum—Operations Management Challenges for Some “Cleantech” Firms

A “cleantech” firm is one with an innovative technology and/or business model for serving an existing market with dramatically reduced environmental impact. This paper describes operations management (OM) challenges faced by five cleantech companies, and a few questions that these raise for OM and multidisciplinary research. It aims to fuel readers' motivation to identify and pursue others. The OM community has fundamental roles to play in the creation of an environmentally sustainable economy.

Examining green production and its role within the competitive strategy of manufacturers

Purpose: This paper reviews current literature and contributes a set of findings that capture the current state-of-the-art of the topic of green production. Design/methodology/approach: A literature review to capture, classify and summarize the main body of knowledge on green production and, translate this into a form that is readily accessible to researchers and practitioners in the more mainstream operations management community. Findings: The existing knowledge base is somewhat fragmented. This is a relatively unexplored topic within mainstream operations management research and one which could provide rich opportunities for further exploration. Originality/value: This paper sets out to review current literature, from a more conventional production operations perspective, and contributes a set of findings that capture the current state-of-the-art of this topic.

EMPSO-based optimization for inter-temporal multi-product revenue management under salvage consideration

The retail market is governed by customer behavior, demand pattern and inventory replenishment policies. It is also observed that any decision would prove to be full of errors, and objective of enhancing the market share could not be achieved, without inclusion of these factors and policies. While an extensive set of literature exists on single and multi-product dynamic pricing, the issue of liquidation of leftover inventory has so far received scant attention from the researchers of Operations Management community. The current work primarily tries to bridge this research gap by addressing dual objectives of revenue maximization and reduction of salvaging losses. In this paper an inter-temporal dynamic pricing model for multiple products is developed under a market setup with price-sensitive demand. Ideas proposed by [1] and [2] have been taken into account for constructing a revenue structure. The formulated objective function is found to be tractable for deriving prices and procurement quantities of large product portfolios. A multi-objective problem has been devised to handle the optimization of normal and clearance revenue by satisfying several pragmatic constraints. Subsequently, an effective algorithm deriving its traits from Particle Swarm Optimization has been proposed to address this problem. An illustrative example from retail apparel industry has been simulated and solved by the afore-mentioned approach. To validate the model statistical analysis has been carried out and the managerial insights portrayed to reveal the practical complexities involved.

OM Forum—Managing Customer Experiences: Perspectives on the Temporal Aspects of Service Encounters

Aservice encounter is an experience that extends over time. Therefore, its effective management must include the control of the timing of the delivery of each of the service's elements and the enhancement of the customer's experience between and during the delivery of the various elements. This paper provides a conceptual framework that links the duration of a service encounter to behaviors that have been shown to affect profitability. Analysis of the framework reveals a wide gap between the behavioral assumptions typically made in operations research (OR) and operations management (OM) models and the state of the art in the marketing and psychology literature. The central motivations behind this paper are (1) to help the OR and OM community bridge this gap by bringing to its attention recent findings from the behavioral literature that have implications for the design of queueing systems for service firms and (2) to identify opportunities for further research.

Surgical Suites' Operations Management

Surgical suites are a key driver of a hospital's costs, revenues, and utilization of postoperative resources such as beds. This article describes some commonly occurring operations management problems faced by the managers of surgical suites. For three of these problems, the article also provides preliminary models and possible solution approaches. Its goal is to identify open challenges to spur further research by the operations management community on an important class of problems that have not received adequate attention in the literature, despite their economic importance.