Assumptions and methodologies in OR

This paper argues that the subject of methodology is importnat for OR practitioners and academics. It isolates four common assumptions about OR from the normal literature of OR, and shows how they lead to identifiable methodological positions. It is argued that the future of OR depends, in part at least, on methodological debate. If it is to be successful, this debate requires some understanding of the assumptions of other people.     

Why modelling and model use matter

When OR/MS analysts develop a model, how are they intending this model to be used? There are many different ways in which OR/MS models may be classified and one important categorisation is the intended use of the model. Some models are intended for routine use on a frequent basis, with little or no human intervention. Others form part of human decision process and provide support to that process. Considering model validation, data requirements, added value and possible pitfalls leads to a theory of model use based on four categories: decision automation, routine decision support, investigation and improvement, and generating insights for debate. A pilot investigation in an OR/MS group demonstrates that this categorisation could provide the basis for empirical research into a theory of model use in operational research. A theory of model use would be of value to academics, who could prioritise their work, and to practitioners, who could place their own work in a broader landscape.     

Examining the strategy development process through the lens of complex adaptive systems theory

The development of strategy remains a debate for academics and a concern for practitioners. Published research has focused on producing models for strategy development and on studying how strategy is developed in organisations. The Operational Research literature has highlighted the importance of considering complexity within strategic decision making; but little has been done to link strategy development with complexity theories, despite organisations and organisational environments becoming increasingly more complex. We review the dominant streams of strategy development and complexity theories. Our theoretical investigation results in the first conceptual framework which links an established Strategic Operational Research model, the Strategy Development Process model, with complexity via Complex Adaptive Systems theory. We present preliminary findings from the use of this conceptual framework applied to a longitudinal, in-depth case study, to demonstrate the advantages of using this integrated conceptual model. Our research shows that the conceptual model proposed provides rich data and allows for a more holistic examination of the strategy development process.     

Operational Research in Organizations: a Metaphorical Analysis

The range of possible ways in which OR influences and is influenced by the organization in which it takes place is great. These influences will be due in part to the nature of the organization involved and such factors cannot be considered in general. However, other factors will have their roots in the generic processes and character found in OR and organizations. A potentially useful way of investigating these factors is to ask what part OR plays in an organization. The particular view held of organizations and of the behaviour of people within them will determine how this aspect of OR is understood. In this paper Morgan's method of organizational analysis based upon the idea of metaphor is adopted to explore the place of OR in organizations. This approach explicitly uses a multi-faceted style of analysis, which is seen to be preferable to one which is more partial in its treatment of organization.     

Computationally modeling organizational learning and adaptability as resource allocation: An artificial adaptive systems approach

A framework for and a computational model of organizational behavior based on an artificial adaptive system (AAS) is presented. An AAS, a modeling approach based on genetic algorithms, enables the modeling of organizational learning and adaptability. This learning can be represented as decisions to allocate resources to the higher performing organizational agents (i.e., individuals, groups, departments, or processes, depending on the level of analysis) critical to the organization's survival in different environments. Adaptability results from the learning function enabling the organizations to change as the environment changes. An AAS models organizational behavior from a micro-unit perspective, where organizational behavior is a function of the aggregate actions and interactions of each of the individual agents of which the organization is composed. An AAS enables organizational decision making in a dynamic environment to be modeled as a satisficing process and not as a maximization process. To demonstrate the feasibility and usefulness of such an approach, a financial trading adaptive system (FTAS) organization is computationally modeled based on the AAS framework. An FTAS is an example of how the learning mechanism in an AAS can be used to allocate resources to critical individuals, processes, functions, or departments within an organization.     

Selecting tolerances in chance-constrained programming: A multiple objective linear programming approach

An importance issue concerning the practical application of chance-constrained programming is the lack of a rational method for choosing risk levels or tolerances on the chance constraints. While there has also been much recent debate on the relationship, equivalence, usefulness, and other characteristics of chance-constrained programming relative to stochastic programming with recourse, this paper focuses on the problem of improving the selection of tolerances within the chance-constrained framework. An approach is presented, based on multiple objective linear programming, which allows the decision maker to be more involved in the tolerance selection process, but does not demand a priori decisions on appropriate tolerances. An example is presented which illustrates the approach.     

‘A festering sore’: the issue of professionalism in the history of the Operational Research Society

An essential component of the history of Operational Research (OR) in Britain is the institutional development of the discipline. In this respect, a defining element is the debate on the issue of professionalism, which took place within the Operational Research Society (ORS) in the later 1960s and 1970s. For the historian, the debate provides major insights into the composition of the OR community at a critical stage in its development following on the sustained expansion of ORS membership in the 1960s. As this article reveals, the proposed movement of the ORS from ‘learned society’ to ‘professional’ status proved to be a deeply divisive issue, with a hard core of ORS members, both academics and practitioners, combining to resist the recommendations of the contemporary ORS Council and the leading officers of the Society. The article focuses on the debates on what one protagonist viewed as ‘a festering sore’ in the history of the ORS. In this respect, it provides a prologue to a second article commenting on the origins and results of the recent decision of the ORS Council to establish a professional membership grade—‘Fellow of the Operational Research Society’.     

Decision Techniques for Town Development

Town development is a complex process which has wide physical, social and economic consequences. Its impact varies as between private and public developers and the community at large, and it is a potent source of conflict. Techniques are needed to evaluate the consequences of decisions in this field from the various points of view. There is a need both for evaluating alternative solutions to the same problem and for evaluating alternative ways of investing the same resources. Decisions about town development involve the trinity of appearance, amenity and costs. It is easier to reach rational decisions when the consequences of alternative choices have been quantified than when they consist of a large number of factors relating to separate attributes, some of which are qualitative. It is necessary to understand the conflicts of interest, to evaluate the social and economic benefits and to provide indicators which measure the balances of advantage between alternative policies.Town development is a long-term and enduring process. Both its costs and benefits are spread over long periods of time and evaluation of its consequences can only be based on predictions. Many of the costs and benefits are indirect and frequently suitable cost data are not available; special cost studies are often necessary to enable the consequences to be evaluated. Many of the benefits are, of course, a matter of opinion, but some benefits can be evaluated by experienced observers, although even then there are still problems of weighting; in some other cases the benefits can be quantified by using indirect measures. Because costs and benefits are spread over time, values must be discounted, the possible effects on the decision of the rate chosen must be studied.Broadly, there are two methods of summarizing the results of the analysis, “costs in use” based on balance sheets for comparing alternative means to the same end and “cost-benefit ratio” for investment type problems. The latter technique is related in some forms to business investment choice techniques. These techniques have a value in many fields in addition to their use in town development.     

Number of alternatives and efficiency in different types of top-management decisions

What are the causes of the efficiency of complex strategic decisions? To answer this question, the impact of information searching, alternative designing, and complexity of a decision problem on its decision quality are analyzed in a longitudinal study of 83 top-management decisions, made the by executive board of a medium-sized firm (1380 employees). Decision quality is negatively influenced by the complexity of the decision problem. Alternative designing has a strong positive impact on decision quality. Information search shows no significant relationship to decision quality. The results indicate that designing of alternatives is an important instrument to counter the challenges of complex strategic decision-problems. However, one should not simply maximize the number of alternatives. There seems to be a very small optimal number beyond which decision quality will decrease. Besides, alternative designing has to be coordinated with other problem-solving activities, namely goal formation, process organization, and information searching.     

A two-phase tabu search approach to the location routing problem

In many distribution systems, the location of the distribution facilities and the routing of the vehicles from these facilities are interdependent. Although this interdependence has been recognized by academics and practitioners alike, attempts to integrate these two decisions have been limited. The location routing problem (LRP), which combines the facility location and the vehicle routing decisions, is NP-hard. Due to the problem complexity, simultaneous solution methods are limited to heuristics. This paper presents a two-phase tabu search architecture for the solution of the LRP. First introduced in this paper, the two-phase approach offers a computationally efficient strategy that integrates facility location and routing decisions. This two-phase architecture makes it possible to search the solution space efficiently, thus producing good solutions without excessive computation. An extensive computational study shows that the TS algorithm achieves significant improvement over a recent effective LRP heuristic.     

Beyond internal OR groups

The paper reviews the prospects of OR applied by dispersed practitioners, small providers of OR services, academics and OR consultants, in other words OR applied by those not located inside internal OR groups. Many in the UK have regarded the activities of OR groups as the defining practice of our profession. The Survival and Success of OR Groups (SSOR) study indicates that within a fairly stable population of OR practitioners the number of internal OR groups is in decline while the number of external, consulting groups is growing. There are good reasons in terms of the diffusion of innovation for assuming that this trend will continue. Against that possibility, the OR profession in the UK needs to reassess the defining aspects of OR and the implications for the activities of the profession in the future. Using the language of strategy, the profession needs to identify its core competencies, define how they are distinctive, consider how they can be developed and maintained, and determine through which channels they can be delivered. One of the key battlegrounds is within the management consultancies where the competing approaches of management science and organisational development vie for supremacy.     

Critical rationalism in practice: Strategies to manage subjectivity in OR investigations

The philosophical position referred to as critical rationalism (CR) is potentially important to OR because it holds out the possibility of supporting OR’s claim to offer managers a scientifically ‘rational’ approach. However, as developed by Karl Popper, and subsequently extended by David Miller, CR can only support practice (deciding what to do, how to act) in a very limited way; concentrating on the critical application of deductive logic, the crucial role of subjective judgements in making technical and moral choices are ignored or are at least left underdeveloped. By reflecting on the way that managers, engineers, administrators and other professionals take decisions in practice, three strategies are identified for handling the inevitable subjectivity in practical decision-making. It is argued that these three strategies can be understood as attempts to emulate the scientific process of achieving intersubjective consensus, a process inherent in CR. The perspective developed in the paper provides practitioners with a way of understanding their clients’ approach to decision-making and holds out the possibility of making coherent the claim that they are offering advice on how to apply a scientific approach to decision-making; it presents academics with some philosophical challenges and some new avenues for research.     

TOWARD CONTROLLING NONPOINT SOURCE POLLUTION OF GROUNDWATER: A HIERARCHICAL POLICY FORMULATION GAME

An integrative approach to formulating agricultural policy instrument levels is suggested for controlling groundwater quality deterioration from agricultural chemical-use, while reconciling the conflicting goals of primary interest groups in the farm policy process. The paper develops a Stackelberg game-theoretic model of public policy formation that simultaneously determines endogenous price supports and nitrogen-use quota, as well as the optimal permissible water contamination. The analysis distinguishes between the private and social opportunity costs of producing agricultural crops and using groundwater as a repository for nitrate leachate from agricultural sources. It is recognized that the social benefit of using nitrogen in agriculture is less than the private benefit to producers. Private and social benefits, as well as optimal production and pollution solutions, will vary as the relative weights which policymakers attach to different social constituents change. The method developed in this paper may be applicable to any policy process in which policymakers exercise indirect influence over industrial production decisions through economic instruments.     

Analysing factors affecting the choice of emergent human resource capital

Ever since the announcement that UK higher education (HE) fees were to increase up to £9000, many universities have expressed concern about how to attract the best students while offering choice and promoting student mobility through broader access. This in turn has led to questioning how such complexity might be modelled using sophisticated operational research (OR) techniques. Because higher education institutions (HEIs) are now beginning to compete ‘against’ rather than ‘with’ each other, potential students are paying increased attention to where and what they will study, as well as graduate opportunities after their degree. Hence, the quality of education services becomes increasingly vital for HEIs in order to attract potential students. This study seeks to develop a framework of those factors affecting international (non-EU) students’ choice of institution. A number of factors were identified and collated from the existing literature providing a solid foundation on which to base this research. A survey approach was utilised to determine the importance of identified factors based on data collected from students of two different types of institutions (a university and a feeder institution). Through a better understanding of factors such as social influence, financial and career opportunities, universities should be well placed to construct models underpinned by OR principles that will promote scenario modelling and planning within HE.     

How Important are Models to Operational Research?

This paper starts from the assumption that the use of modelsis central to the methodology of operational research (OR).The concept is clarified by reference to its formal use in mathematicallogic. A justification for the use of models in decision makingis given. This is contrasted with the reasons why traditionalOR models are frequently not used by practising OR workers (letalone managers). An attempt is made to resolve this contrastbetween the practice of OR by academics with those closer tocommercial decision making. The proper relationship betweenthe two activities is suggested.     

Inventory and sales effort management under unobservable lost sales

A retailer needs to make decisions regarding how much to order and how much sales effort to exert in an environment with uncertain demand. One intrinsic complexity in a typical retail environment is caused by the fact that the retailer can obtain information about demand only based on sales, as demand itself is unobservable. Taking a Bayesian approach, Lariviere and Porteus (1999) show that in such a setting a retailer should stock more to increase the probability of an exact demand observation. In this article, we extend their work by allowing the retailer to control both the stocking quantity and sales effort, which can be used to affect demand. We show that their insights with respect to information stalking carry over to this setting. In addition, our model allows gaining a better understanding of optimal sales effort strategies. We find that demand management has a dual role in supporting information gathering: while at the beginning of a product life cycle it is optimal to support learning effects by sharply reducing sales effort, at later stages of the product life cycle an aggressive strategy of increased promotional activities can be used to harvest the information gathered in earlier periods.     

A methodology for developing Bayesian networks: An application to information technology (IT) implementation

Bayesian Networks (BNs) are probabilistic inference engines that support reasoning under uncertainty. This article presents a methodology for building an information technology (IT) implementation BN from client–server survey data. The article also demonstrates how to use the BN to predict the attainment of IT benefits, given specific implementation characteristics (e.g., application complexity) and activities (e.g., reengineering). The BN is an outcome of a machine learning process that finds the network’s structure and its associated parameters, which best fit the data. The article will be of interest to academicians who want to learn more about building BNs from real data and practitioners who are interested in IT implementation models that make probabilistic statements about certain implementation decisions.     

The contribution of critical realism as an underpinning philosophy for OR/MS and systems

Many issues are under debate as to the philosophical nature of OR/MS: is it science or technology? Is it natural or social science? Can it be realist as well as being interpretivist? There are also many debates within the philosophy of science itself. This paper proposes that a particular account of the philosophy of science, known as ‘critical realism’, is especially suitable as an underpinning of OR/MS. The structure of the argument of this paper is to outline the main positions within the philosophy of science and highlight their problems, especially from the point of view of OR/MS; then to introduce critical realism and to show how it addresses these problems and how it is particularly appropriate for OR/MS; and finally to illustrate this by considering examples of various practical OR methods.