The design of robust value-creating supply chain networks: A critical review

This paper discusses Supply Chain Network (SCN) design problem under uncertainty, and presents a critical review of the optimization models proposed in the literature. Some drawbacks and missing aspects in the literature are pointed out, thus motivating the development of a comprehensive SCN design methodology. Through an analysis of supply chains uncertainty sources and risk exposures, the paper reviews key random environmental factors and discusses the nature of major disruptive events threatening SCN. It also discusses relevant strategic SCN design evaluation criteria, and it reviews their use in existing models. We argue for the assessment of SCN robustness as a necessary condition to ensure sustainable value creation. Several definitions of robustness, responsiveness and resilience are reviewed, and the importance of these concepts for SCN design is discussed. This paper contributes to framing the foundations for a robust SCN design methodology.     

Splitting up value: A critical review of residual income theories

This paper deals with the notion of residual income, which may be defined as the surplus profit that residues after a capital charge (opportunity cost) has been covered. While the origins of the notion trace back to the 19th century, in-depth theoretical investigations and widespread real-life applications are relatively recent and concern an interdisciplinary field connecting management accounting, corporate finance and financial mathematics (Peasnell, 1981, 1982; Peccati, 1987, 1989, 1991; Stewart, 1991; Ohlson, 1995; Arnold and Davies, 2000; Young and O’Byrne, 2001; Martin, Petty and Rich, 2003). This paper presents both a historical outline of its birth and development and an overview of the main recent contributions regarding capital budgeting decisions, production and sales decisions, implementation of optimal portfolios, forecasts of asset prices and calculation of intrinsic values. A most recent theory, the systemic-value-added approach (also named lost-capital paradigm), provides a different definition of residual income, consistent with arbitrage theory. Enfolded in Keynes’s (1936) notion of user cost and forerun by Pressacco and Stucchi (1997), the theory has been formally introduced in Magni (2000a,b,c; 2001a,b; 2003), where its properties are thoroughly investigated as well as its relations with the standard theory; two different lost-capital metrics have been considered, for value-based management purposes, by Drukarczyk and Schueler (2000) and Young and O’Byrne (2001). This work illustrates the main properties of the two theories and their relations, and provides a minimal guide to construction of performance metrics in the two approaches.     

Operational research and ethics: A literature review

Any human activity raises ethical questions, questions about ‘good’ and ‘right’ ways to act and to live; or to put it differently, questions of values and responsibility. From its inception operational research (OR) has engaged with such questions in terms of professional behavior, the handling of preferences in OR, the societal role of OR, the process of OR intervention and the content of OR analysis. As a result, analytical methods and processes have been developed to help clients explore the ethical dimension of their decisions. The paper reviews the literature published in selected OR journals (Management Science; Operations Research; Interfaces; the European Journal of Operational Research; the Journal of the Operations Research Society; Omega; International Transactions in Operational Research; the Journal of Multi-Criteria Decision Analysis), organizing it along the lines of OR’s core competences. The review identifies a number of significant research programmes that are well established and are being energetically pursued; the research findings are being applied to a wide range of important issues. Ethical questions lie at the heart of the great governmental and commercial issues of the day: economic growth and instability; inequality and injustice; environmental degradation and sustainability. They also lie at the heart of the more mundane decisions of day-to-day OR. ‘Ethics’ therefore provides a useful focus for OR both in terms of raising the awareness of all concerned and in providing a theme for research. As a result of the review some research questions are suggested. There is much of interest, much to do.     

A network formulation of market equilibrium problems and variational inequalities

This paper shows that market equilibrium problems of production may generally be modelled as equilibrium flow problems in networks and that their equilibrium conditions can be visualized as a variational inequality. This connection would allow us to transplant directly elements of the well-developed theory of equilibrium flow in networks to the theory of market equilibrium.     

A model of market power and efficiency in private electronic exchanges

We investigate how private electronic markets (PEMs) can be used as a strategic tool by a large producer to compete against a consortium of smaller producers. We model the competition between a Large Producer and Consortium of producers in a two-tier supply chain as a game and characterize the resulting Subgame Perfect Nash Equilibrium. Our results demonstrate that as the costs of inputs to production increase, there are greater returns to ownership of a private exchange. Further, we demonstrate strong welfare enhancing effects of the PEM as the production efficiency of upstream suppliers declines. Finally, from a policy standpoint we show that when upstream suppliers are highly efficient, the creation of a private electronic exchange by the Large Producer will result in significant welfare loss.     

Optimisation of gravity-fed water distribution network design: A critical review

This paper surveys the literature on the optimisation of water distribution network design. The water distribution network design (WDND) optimisation problem entails finding the material and diameter of each pipe in the network so that the total cost of the network is minimised without violating any hydraulic constraints. This is a difficult combinatorial optimisation problem, in which decision variables are discrete and both cost function and constraints are non-linear. Over the past 30 years, a large number of methods, especially in the field of (meta) heuristics, have been developed to solve this problem, most of which obtain good results on the available benchmark networks. In addition to outlining the basic features of each method, a detailed computational comparison is presented. Based on this comparison, some issues with the current state of the art in this domain are discussed, and some future research directions are suggested. Additionally, the need for an adequate set of benchmark instances is motivated, and the minimal requirements for an instance set generator are discussed.     

Management scientists and managers: Experiences of an OR-practitioner with a critical interface

What management scientists can do still outstrips the use made of such skills by management. However, breakthroughs are being made in building the benefits of management science into the structure, systems, and management processes of firms. This is where management science must be if it is to be effective; solutions on an ad hoc basis are usually not acceptable by top management.Here described is a framework for determining the management style of any particular firm. The implication is that then a strategy can be developed for systematically positioning management science endeavors in such a way that the benefits are actually accepted by top management as dealing with the problems and issues management itself perceives. Unless a solution addresses the problem that concerns top management, the solution will never be considered seriously, even if it is ‘correct’.The taxonomy of management styles was developed by the author emperically in the course of his management consulting with many films in a variety of industries worldwide. If focuses on the nature of the decision-making process, and is presented here for the first time in print.     

Planning of capacities and orders in build-to-order automobile production: A review

In an attempt to achieve a competitive edge, automotive companies operate global production networks to offer an ever increasing product variety, shorter and reliable lead times as well as competitively priced products. Cars are no longer exclusively produced based on standardized product configurations and stable sales plans but are increasingly build-to-order to match the needs of individual customers. Operations Research (OR) may contribute towards successful build-to-order operations. This is likewise reflected by the appreciable number of published papers on industry specific OR applications. To provide readers with an overview about these OR models and applications we identify current and future research issues based on the review of 49 works. We focus on two important planning objects which have not been considered in prior reviews: the planning of capacities and orders. To bridge the gap between conceptual works on the one hand and quantitative contributions on the other, we provide a framework for the structuring of planning tasks. Existing models are classified according to this framework and open issues that should be addressed in OR are discussed.     

A review of recent research on green road freight transportation

Road freight transportation is a major contributor to carbon dioxide equivalent emissions. Reducing these emissions in transportation route planning requires an understanding of vehicle emission models and their inclusion into the existing optimization methods. This paper provides a review of recent research on green road freight transportation.     

A review of trade credit literature: Opportunities for research in operations

Trade credit arises when a buyer delays payment for purchased goods or services. Its nature has predominantly been an area of inquiry for researchers from the disciplines of finance, marketing, and economics but it has received relatively little attention in other domains. In our article, we provide an integrative review of the existing literature and discuss conflicting study outcomes. We organize the relevant literature into seven areas of inquiry and analyze four in detail: trade credit motives, order quantity decisions, credit term decisions, and settlement period decisions. Additionally, we derive a detailed agenda for future research in these areas.     

Equilibrium model of a credit market: Statement of the problem and solution methods

An equilibrium model of a credit market is proposed and examined. The credit price or the interest rate in the model is determined by the consistent interaction of two macroscopic factors: supply and demand. Methods for computing an equilibrium interest rate are suggested. The methods are interpreted as market-balancing dynamics. The convergence of the methods is proved.     

Managing contribution and capital market risk in a funded public defined benefit plan: Impact of CVaR cost constraints

Using a Monte Carlo framework, we analyze the risks and rewards of moving from an unfunded defined benefit pension system to a funded plan for German civil servants, allowing for alternative strategic contribution and investment patterns. In the process we integrate a Conditional Value at Risk (CVaR) restriction on overall plan costs into the pension manager’s objective of controlling contribution rate volatility. After estimating the contribution rate that would fully fund future benefit promises for current and prospective employees, we identify the optimal contribution and investment strategy that minimizes contribution rate volatility while restricting worst-case plan costs. Finally, we analyze the time path of expected and worst-case contribution rates to assess the chances of reduced contribution rates for current and future generations. Our results show that moving toward a funded public pension system can be beneficial for both civil servants and taxpayers.     

Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey

This paper presents a comprehensive review of 196 studies which employ operational research (O.R.) and artificial intelligence (A.I.) techniques in the assessment of bank performance. Several key issues in the literature are highlighted. The paper also points to a number of directions for future research. We first discuss numerous applications of data envelopment analysis which is the most widely applied O.R. technique in the field. Then we discuss applications of other techniques such as neural networks, support vector machines, and multicriteria decision aid that have also been used in recent years, in bank failure prediction studies and the assessment of bank creditworthiness and underperformance.     

Globalization, social development, and operations research: an exploration of strategies for success

This paper argues that in today’s world order, policy-making takes precedence over analytical and technical models that have historically formed the mainstay of Operations Research. The structural and human dimensions of this transition is discussed in the form of six Policy Imperatives aimed at the creation of a world order that makes it more humane and less vulnerable to failure. It is proposed that though OR occupies a prominent role in developmental initiatives, in order for its successful implementation in meeting social goals, the context in which it is invoked must be conducive to social transformation. An earlier version of this paper was presented at the International Conference on Operations Research for Development (ICORD) held December 27–30, 2002 at Anna University, Chennai. The author would like to acknowledge the helpful comments of anonymous reviewers. He would also like to thank Professor K.S.P. Rao of Anna University for his gracious assistance.     

A review of the recent contribution of systems thinking to operational research and management science

The systems approach, or systems thinking, has been intimately connected with the development of OR and management science initially through the work of founders such as Churchman and Ackoff and latterly through innovations such as soft systems. In this paper we have undertaken a review of the contribution that systems thinking has been making more recently, especially to the practice of OR. Systems thinking is a discipline in its own right, with many theoretical and methodological developments, but it is also applicable to almost any problem area because of its generality, and so such a review must always be selective. We have looked at the literature from both a theoretical and an applications orientation. In the first part we consider the main systems theories and methodologies in terms of their recent developments and also their applications. This covers: the systems approach, complexity theory, cybernetics, system dynamics, soft OR and PSMs, critical systems and multimethodology. In the second part we review the main domains of application: strategy, information systems, organisations, production and operations, ecology and agriculture, and medicine and health. Our overall conclusion is that while systems may not be well established institutionally, in terms of academic departments, it is incredibly healthy in terms of the quantity and variety of its applications.     

Synergies between operations research and data mining: The emerging use of multi-objective approaches

Operations research and data mining already have a long-established common history. Indeed, with the growing size of databases and the amount of data available, data mining has become crucial in modern science and industry. Data mining problems raise interesting challenges for several research domains, and in particular for operations research, as very large search spaces of solutions need to be explored. Hence, many operations research methods have been proposed to deal with such challenging problems. But the relationships between these two domains are not limited to these natural applications of operations research approaches. The counterpart is also important to consider, since data mining approaches have also been applied to improve operations research techniques. The aim of this article is to highlight the interplay between these two research disciplines. A particular emphasis will be placed on the emerging theme of applying multi-objective approaches in this context.     

A review of operations research models in invasive species management: state of the art,challenges, and future directions

Invasive species are a major threat to the economy, the environment, health, and thus human well-being. The international community, including the United Nations’ Global Invasive Species Program (GISP), National Invasive Species Council (NISC), and Center for Invasive Species Management (CISM), has called for a rapid control of invaders in order to minimize their adverse impacts. The effective management of invasive species is a highly complex problem requiring the development of decision tools that help managers prioritize actions most efficiently by considering corresponding bio-economic costs, impacts on ecosystems, and benefits of control. Operations research methods, such as mathematical programming models, are powerful tools for evaluating different management strategies and providing optimal decisions for allocating limited resources to control invaders. In this paper, we summarize the mathematical models applied to optimize invasive species prevention, surveillance, and control. We first define key concepts in invasive species management (ISM) in a framework that characterizes biological invasions, associated economic and environmental costs, and their management. We then present a spatio-temporal optimization model that illustrates various biological and economic aspects of an ISM problem. Next, we classify the relevant literature with respect to modeling methods: optimal control, stochastic dynamic programming, linear programming, mixed-integer programming, simulation models, and others. We further classify the ISM models with respect to the solution method used, their focus and objectives, and the specific application considered. We discuss limitations of the existing research and provide several directions for further research in optimizing ISM planning. Our review highlights the fact that operations research could play a key role in ISM and environmental decision-making, in particular closing the gap between the decision-support needs of managers and the decision-making tools currently available to management.     

Measurement of preferences with self-explicated approaches: A classification and merge of trade-off- and non-trade-off-based evaluation types

Self-explicated approaches are popular preference measurement approaches for products with many attributes. This article classifies previous self-explicated approaches according to their evaluation types, i.e. trade-off- versus non-trade-off-based, and outlines their advantages and disadvantages. In addition, it proposes a new method, the presorted adaptive self-explicated approach that is based on Netzer and Srinivasan’s (2011) adaptive self-explicated approach and that combines trade-off- and non-trade-off-based evaluation types. Two empirical studies compare this new method with the most popular existing self-explicated approaches, including the adaptive self-explicated approach and paired comparison preference measurement. The new method overcomes the insufficient discrimination between importance weights, as usually found in non-trade-off-based evaluation types; discourages respondents’ simplification strategies, as are frequently encountered in trade-off evaluation types; is easy to implement; and yields high predictive validity compared with other popular self-explicated approaches.     

Design and control of warehouse order picking: A literature review

Order picking has long been identified as the most labour-intensive and costly activity for almost every warehouse; the cost of order picking is estimated to be as much as 55% of the total warehouse operating expense. Any underperformance in order picking can lead to unsatisfactory service and high operational cost for the warehouse, and consequently for the whole supply chain. In order to operate efficiently, the order-picking process needs to be robustly designed and optimally controlled. This paper gives a literature overview on typical decision problems in design and control of manual order-picking processes. We focus on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning. The research in this area has grown rapidly recently. Still, combinations of the above areas have hardly been explored. Order-picking system developments in practice lead to promising new research directions.