A hybrid multiple-criteria decision analysis framework for corporate social responsibility implementation applied to an extractive industry case study

Integration of corporate social responsibility (CSR) into a company’s mainstream strategy is a complex task. Practical implementation of CSR requires analysis of both the external and internal environments to determine the prospects and challenges significantly influencing integration of sustainability into business strategy. In order to overcome limitations of single multiple-criteria decision analysis models, this paper proposes a hybrid integrated framework combining cognitive mapping and analytic networks process (ANP) to determine, prioritise and select CSR programmes for implementation. The strategic cognitive map serves as a foundation to build the ANP network and identify the importance of CSR programmes. A knapsack optimisation method is then used to optimally assign resources to CSR alternatives. We demonstrate the usefulness of the framework through a case study in the extractive sector. The framework was empirically tested with 61 respondents using postal and online surveys, MBA workshops, and conference networking.     

Community facilitation of problem structuring and decision making processes: Experiences from the EU LEADER+ programme

This paper reports on the work carried out supporting a rural community in Denmark under the LEADER+ programme. This is a programme that supports development in particularly vulnerable rural regions of the European countries members of EU. It supports creative and innovative projects that can contribute to long-term and sustainable development in these regions. The main tasks have been the organisation and facilitation of conferences and workshops to structure the problematic situation of identifying and designing innovative projects for the development of the community and to support decision making processes related to the agreement on action plans. Learning to design, plan, manage and facilitate conferences and workshops have also being another central activity. The main purpose of these conferences and workshops was not only problem structuring and decision making in connection with community development but also the transfer of facilitation skills and appropriate methods to the community.     

Extension of VIKOR method for decision making problem with interval numbers

The VIKOR method was developed for multi-criteria optimization of complex systems. It determines the compromise ranking list and the compromise solution obtained with the initial (given) weights. This method focuses on ranking and selecting from a set of alternatives in the presence of conflicting criteria. It introduces the multi-criteria ranking index based on the particular measure of “closeness” to the “ideal” solution. The aim of this paper is to extend the VIKOR method for decision making problems with interval number. The extended VIKOR method’s ranking is obtained through comparison of interval numbers and for doing the comparisons between intervals, we introduce α as optimism level of decision maker. Finally, a numerical example illustrates and clarifies the main results developed in this paper.     

Extension of VIKOR method for multi-criteria group decision making problem with linguistic information

A new method is proposed to solve multi-criteria group decision making problems in which both the criteria values and criteria weights take the form of linguistic information based on the traditional idea of VIKOR method. Firstly, the linguistic criteria weights given by all decision makers are transformed into trapezoidal fuzzy numbers, and then aggregated and defuzzified to crisp values. Secondly, the individual linguistic decision matrix given by each decision maker (DM) is transformed into 2-tuple linguistic decision matrix, and then aggregated into collective 2-tuple linguistic decision matrix by 2-tuple linguistic arithmetic mean operation. Thirdly, the 2-tuple linguistic values (_Si,_αi),$(S_i\text{,}{\alpha }_i)\text{,}$(_Ri,_αi)$(R_i\text{,}{\alpha }_i)$ and (_Qi,_αi)$(Q_i\text{,}{\alpha }_i)$ are calculated by defining the 2-tuple linguistic positive ideal solution (TL-PIS) and 2-tuple linguistic negative ideal solution (TL-NIS). Furthermore, the compromise solution can be obtained. Finally, a numerical example is used to illustrate the application of the proposed approach, and the method is verified by comparing the evaluation result with that of 2-tuple linguistic TOPSIS (TL-TOPSIS) method.     

Extension of VIKOR method for decision making problem based on hesitant fuzzy set

The multiple criteria decision making (MCDM) methods VIKOR and TOPSIS are all based on an aggregating function representing “closeness to the ideal”, which originated in the compromise programming method. The VIKOR method of compromise ranking determines a compromise solution, providing a maximum “group utility” for the “majority” and a minimum of an “individual regret” for the “opponent”, which is an effective tool in multi-criteria decision making, particularly in a situation where the decision maker is not able, or does not know to express his/her preference at the beginning of system design. The TOPSIS method determines a solution with the shortest distance to the ideal solution and the greatest distance from the negative-ideal solution, but it does not consider the relative importance of these distances. And, the hesitant fuzzy set is a very useful tool to deal with uncertainty, which can be accurately and perfectly described in terms of the opinions of decision makers. In this paper, we develop the E-VIKOR method and TOPSIS method to solve the MCDM problems with hesitant fuzzy set information. Firstly, the hesitant fuzzy set information and corresponding concepts are described, and the basic essential of the VIKOR method is introduced. Then, the problem on multiple attribute decision marking is described, and the principles and steps of the proposed E-VIKOR method and TOPSIS method are presented. Finally, a numerical example illustrates an application of the E-VIKOR method, and the result by the TOPSIS method is compared.     

The unknown in decision making: What to do about it

The unknown or “other” that affects our lives is what we usually very much want to know about to cope with uncertainty. We often suspect that it affects us with partial and indefinite evidence that it exists but we only have uncertain feelings about it. Even when we do not know what it is we would like to allow for its influence in our explaining the outcome of a decision. One way to deal with the many factors of a decision is to include the unknown as one of them and then determine its priority of influence on the outcome by comparing it with other factors. We are able to do that to the extent that we are sure of what we know and of the residual that remains outside our understanding that may also have some effect on what we do. Confidence from good understanding and past success are what we need in order to judge the potential significance of what we do not know on the outcome. We can then perform sensitivity analysis to see how much effect unknown factors can have on the stability of the choice we make. Pairwise comparisons make it possible to tackle this idea explicitly and rather simply. This note illustrates how to prioritize and test the effect of the unknown alongside the known.     

Generalizing variance to allow the inclusion of decision attitude in decision making under uncertainty

The problem of decision making under uncertainty is considered. It is noted that an alternative is described in terms of an uncertainty profile. We observe that a major difficulty in the decision process is the comparison of these uncertainty profiles. We discuss the need for introducing some features of an uncertainty profile to help simplify this comparison. We note that the quantification of these simplifying features involves some subjective considerations about the decision makers preferences. We introduce the idea of the decision maker’s attitudinal character to help in the formulation of these considerations. We then investigate two important features associated with an uncertainty profile. The first, the representative value, is a generalization of expected value commonly used under probabilistic uncertainty. The second, called the measure of deviation, provides a generalization of the concept of variance. We show how these new measures allows us to consider uncertainty profiles other then just the probabilistic one. They also allow us introduce other decision maker attitudes then the one implicitly assumed with the expected value and variance.     

Using Foucault to analyse ethics in the practice of problem structuring methods

As a new generation of problem-structuring methods (PSM) develops in operational research (OR) practice, the issue of ethics needs attention. This paper aims to contribute to examining ethics in the practice of problem structuring. The paper argues that PSM could influence ethical reflection but the scope of new developments is limited, as it is also the scope of ethical codes or norms in OR. Ethics needs to be understood as a continuous development by individuals in relation to existing frameworks and codes. This view of ethics is inspired by Michel Foucault's ideas on power and ethics. Using Foucault's ideas, two main areas of inquiry are suggested to enhance critical reflection about ethics: (a) individualization of forms of ethics, and (b) possibilities and constraints of ethics in power relations. Using these two areas, practitioners reflect on the ethics of their practice and relate it to their own ethical development.     

On the problem of weights in multiple criteria decision making (the noncompensatory approach)

This paper shows how the notion of ‘relative importance of attributes’ can be defined within the framework of the noncompensatory approach to multiple criteria decision making. The problem of weights then appears as a problem of functional representation of relations. We state some theoretical results concerning this problem and outline a practical decision-aid (Tactic) based on the ideas introduced in the paper.     

Quantitative problem structuring methods for multi-actor problems: an analysis of reported applications

Problem structuring methods (PSMs) are proposed as vital tools for coping with complex and unstructured problems that help decision-makers make decisions or come to a shared understanding of a problem situation. Despite their popularity, choosing a PSM for an unstructured problem situation is problematic as good categorization and evaluation of PSMs is lacking. As a first step we postulate a categorization of quantitative PSMs applied to multi-actor situations. We list the different application areas, the types of design that were used, and the type of outcomes the methods provide. To understand why and how certain PSMs are applied, we categorize applications of metagames/conflict analysis, hypergames, drama theory, Q-methodology, and transactional analysis. We find that method choice and validation of the applications are yet underdeveloped for this specific sub-field, and suggest further work on this as it will help to understand the added value of PSMs.     

Measuring consensus in decision making: an application to maritime command and control

An important component of maritime command and control is the information that has value to Royal Navy commanders in making campaign decisions. Studies aimed at identifying information requirements generally do so in a wargame context with several test subjects assuming command roles. An important adjunct to this work then is the assessment of how closely the subjects agree that the proposed information set is indeed valuable. In this paper, we focus on assessing the degree to which the test subjects participating in a MoD sponsored maritime command and control study agreed to a proposed set of information elements deemed valuable to taking combat decisions. The methodology involves the simulation of naval combat. The participants (former Royal Navy Captains and Admirals) are asked to choose a course of action that best accomplishes a stated mission. Information is provided on request. Each pair of participants is characterized by its set of information requirements. The objectives are (1) to define an overall information set that minimizes disagreement among the participants in some way; and (2) to develop a metric that assesses the amount of disagreement among the participants. Two metrics are presented: a mean consensus and a median consensus.     

WASAN: The development of a facilitated methodology for structuring a waste minimisation problem

This paper contributes a new methodology called Waste And Source-matter ANalyses (WASAN) which supports a group in building agreeable actions for safely minimising avoidable waste. WASAN integrates influences from the Operational Research (OR) methodologies/philosophies of Problem Structuring Methods, Systems Thinking, simulation modelling and sensitivity analysis as well as industry approaches of Waste Management Hierarchy, Hazard Operability (HAZOP) Studies and As Low As Reasonably Practicable (ALARP). The paper shows how these influences are compiled into facilitative structures that support managers in developing recommendations on how to reduce avoidable waste production. WASAN is being designed as Health and Safety Executive Guidance on what constitutes good decision making practice for the companies that manage nuclear sites. In this paper we report and reflect on its use in two soft OR/problem structuring workshops conducted on radioactive waste in the nuclear industry.     

Goal programming for decision making: An overview of the current state-of-the-art

There have been significant advances in the theory of goal programming (GP) in recent years, particularly in the area of intelligent modelling and solution analysis. The intention of this paper is to provide an overview of these developments, to detail and assess the current state-of-the-art in the subject, and to highlight areas which seem promising for future research. Modelling techniques such as detection and restoration of pareto efficiency, normalisation, redundancy checking, and non-standard utility function modelling are overviewed. The connection between GP and other multi-objective-programming techniques as well as a utility interpretation of GP are examined. The rationality of ranking Multi-Criteria Decision Making techniques, and of placing GP in such a ranking, is discussed.     

Exploring new directions for research in problem structuring methods: on the role of cognitive style

Prior research has argued that cognitive style can have a significant impact on group decision making. In addition, several scholars have proposed that cognitive style can play a key role in the design and use of group decision support systems. However, cognitive style has not received a great deal of attention in the problem structuring methods (PSMs) community. This is surprising, given that PSMs are specifically developed to support a group in their decision making. The purpose of this paper is thus to examine the significance of cognitive style within PSMs. The paper identifies and explores the role of four different cognitive style functions in problem structuring interventions. This analysis is carried out by focusing on the different tasks embedded within a group process supported by PSMs. Implications for the research and practice of PSMs are then discussed.     

Analysis of expected queueing delays for decision making in production planning

Concepts such as Time Based Competition and criticism of traditional cost accounting's role as a basis for decision making in production planning have emphasized the need for operational measures as indicators of manufacturing performance. One such measure is the expected queueing delay at a production facility. In this paper a typical bottleneck work center is considered where semi-manufactured products are processed in batches. The expected queueing delay depends on the batch sizes used at the work center. Emphasis is placed on the derivation of analytical expressions of (bounds on) the minimal expected queueing delay that can be achieved by an optimal batching decision. The analytical expressions can be applied easily to support managerial decisions on reduction of setup time and on expansion of capacity.     

Decision maker preferences for information in complex decision making: New directions for OR intervention

Operations research models are used in many business and non-business entities to support a variety of decision making activities, primarily well-defined, operational decisions. This is due to the traditional emphasis of these models on optimal solutions to pre-specified problems. Some attempts have been made to use OR models in support of more complex, strategic decision making. Traditionally, these models have been developed without explicit consideration for the information processing abilities and limitations of the decision makers, who interact with, provide input to, and receive output from such models.Research in judgement and decision making show that human decisions are influenced by a number of factors including, but not limited to, information presentation modes; information content, modes, e.g., quantitative versus qualitative; order effects such as primacy, recency; and simultaneous versus sequential presentation of data.This article presents empirical research findings involving executive business decision makers and their preferences for information in decision making scenarios. These preference functions were evaluated using OR techniques. The results indicate that decision makers view information in different ways. Some decision makers prefer qualitative, narrative, social information, whereas other prefer quantitative, numerical, firm specific information. Results also show that decision making tasks influence the preference structure of decision makers, but that in general, the preference are relatively stable across tasks.The results imply that for OR models to be more useful in support of non-routine decision making, attention needs to be focused on the information content and presentation effects of model inputs and outputs.     

Combining problem structuring methods to conduct applied research: a mixed methods approach to studying fitness-to-drive in the UK

This paper describes a mixed methods approach using problem structuring methods to conduct applied research into fitness-to-drive arrangements within the UK Department for Transport. Computer-supported group causal mapping was used to collect and structure qualitative data from stakeholder groups concerning the delivery of medical standards on fitness-to-drive. The data were subsequently coded and analysed using the modelling language of soft systems methodology. This enabled data to be linked to the concept of a ‘fitness-to-drive system’ and developed further in the form of systems models based on alternative worldviews. The paper reports on the process of developing and implementing the approach and discusses issues concerning the conduct of mixed methods research using problem structuring methods.     

An intelligent-agent-based fuzzy group decision making model for financial multicriteria decision support: The case of credit scoring

Credit risk analysis is an active research area in financial risk management and credit scoring is one of the key analytical techniques in credit risk evaluation. In this study, a novel intelligent-agent-based fuzzy group decision making (GDM) model is proposed as an effective multicriteria decision analysis (MCDA) tool for credit risk evaluation. In this proposed model, some artificial intelligent techniques, which are used as intelligent agents, are first used to analyze and evaluate the risk levels of credit applicants over a set of pre-defined criteria. Then these evaluation results, generated by different intelligent agents, are fuzzified into some fuzzy opinions on credit risk level of applicants. Finally, these fuzzification opinions are aggregated into a group consensus and meantime the fuzzy aggregated consensus is defuzzified into a crisp aggregated value to support final decision for decision-makers of credit-granting institutions. For illustration and verification purposes, a simple numerical example and three real-world credit application approval datasets are presented.