PROMETHEE Group Decision Support System and the House of Quality

Quality function deployment (QFD) is a multi-step method that monitors customer needs throughout a product development process. The House of Quality (HOQ) exercise undertaken in the first phase of QFD is considered as the most important, since customer needs must be accurately translated into a set of technical requirements for the final product. This paper provides a PROMETHEE group decision support system (GDSS) approach that integrates the design preferences of the QFD team. We highlight the selection and ranking of the technical requirements in the HOQ exercise, where a group of multidisciplinary decision makers (DMs) in a globally dispersed QFD team is required to input their individual preferences. Our approach advances the HOQ group decision making context in three important areas. First, it treats each criterion and DM as unique in terms of the preference function and threshold levels. Second, it seeks a multi-criteria approach for the HOQ process, where some DMs may play a more important role than others on a certain criterion. Third, sensitivity analysis through the Geometrical Analysis for Interactive Assistance (GAIA) plane provides valuable information about the conflicts, similarities, or independencies between the criterion and the DMs, respectively. A case on an automotive part illustrates the performance of the PROMOTHEE approach with GAIA.     

Multiple Attribute Group Decision Making Method Based on Utility Theory Under Interval-Valued Intuitionistic Fuzzy Environment

In this paper, a kind of multiple attribute group decision making problem is studied, where there is no original information about the weights of importance of the attributes and the decision makers (DMs), and the attribute values are given in the form of interval-valued intuitionistic fuzzy numbers (IVIFNs). To solve this problem, a new method is proposed based on utility theory. In the proposed method, the weights of importance of the DMs and the attributes are all determined by using the intuitionistic indexes of related IVIFNs. And then, the alternatives are compared by using their composite interval indexes which are generated based on utility theory. Finally, two numerical examples are proposed to demonstrate the effectiveness of the proposed method.     

Multi-Party Negotiation When Agents Have Subjective Estimates of Bargaining Powers

This paper presents a method for generating Pareto-optimal solutions in multi-party negotiations. In this iterative method, decision makers (DMs) formulate proposals that yield a minimum payoff to their opponents. Each proposal belongs to the efficient frontier, DMs try to adjust to a common one. In this setting, each DM is supposed to have a given bargaining power. More precisely each DM is supposed to have a subjective estimate of the power of the different parties. We study the convergence of the method, and provide examples where there is no possible agreement resulting from it.     

Selection of a Representative Value Function for Robust Ordinal Regression in Group Decision Making

In this paper, we introduce the concept of a representative value function in a group decision context. We extend recently proposed methods UTA^GMS-GROUP and UTADIS^GMS-GROUP with selection of a compromise and collective preference model which aggregates preferences of several decision makers (DMs) and represents all instances of preference models compatible with preference information elicited from DMs. The representative value function is built on results of robust ordinal regression, so its representativeness can be interpreted in terms of robustness concern. We propose a few procedures designed for multiple criteria ranking, choice, and sorting problems. The use of these procedures is conditioned by both satisfying different degrees of consistency of the preference information provided by all DMs, as well as by some properties of particular decision making situations. The representative value function is intended to help the DMs to understand the robust results, and to provide them with a compromise result in case of conflict between the DMs.     

Monte Carlo Simulation Techniques in a Decision Support System for Group Decision Making

This paper describes a group decision support system based on an additive multi-attribute utility model for identifying a consensus strategy in group decision-making problems where several decision-makers or groups of decision-makers elicit their own preferences separately. On the one hand, the system provides procedures to quantify the DMs or group of DMs preferences separately. This involves assessing the DMs or group of DMs component utilities that represent their preferences regarding the respective possible attribute values and objective weights that represent the relative importance of the criteria. On the other hand, we propose Monte Carlo simulation techniques for identifying a consensus strategy. An iterative process will be carried out, where, after the simulations have been performed, the imprecise component utilities and weights corresponding to the different DMs or groups of DMs are tightened to output more meaningful information in the next simulations to achieve a consensus strategy. Finally, an application to the evaluation of remedial strategies for restoring contaminated aquatic ecosystems illustrates the usefulness and flexibility of this decision support tool.     

The Use of Ranking Veto Concept to Mitigate the Compensatory Effects of Additive Aggregation in Group Decisions on a Water Utility Automation Investment

The use of additive models for aggregating group decisions implies they have a compensatory effect in the process of aggregating all decision makers’ (DMs’) preferences. In this kind of model, the final result may produce some extremely undesirable alternatives for one or more DMs. Such alternatives may emerge with a higher ranking than desirable ones, thus generating conflicts and regrets. To overcome this problem the concept of ranking veto is introduced based on a reduction factor combined with the utility of the alternative in order to penalize conflicting alternatives and reduce disagreements in an additive model. A water utility problem was considered as a numerical application to illustrate the model. A decision group method based on MAUT, utility thresholds and a reduction factor is proposed to support group decision in selecting regions that will receive investments in automation over the next 4 years.     

An Extended PROMETHE II Multi-Criteria Group Decision Making Technique Based on Intuitionistic Fuzzy Logic for Sustainable Energy Planning

The implementations of Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) category to complex multi-criteria group decision making (MCGDM) scenarios have been included in thousands areas. Outranking methods such as PROMETHEE II are also greatly employed in energy planning application. In MCGDM methods if decision makers (DMs) are not able to treat precise data in order to define their preferences, the intuitionistic fuzzy set (IFS) theory enables them. IFS attributes are connected with the degree of membership and non-membership, and can be used to draw uncertainty in group decision-making situations. In this paper, a new version of the PROMETHEE II method is proposed, aiming at solving MCGDM problems. Linguistic variables are expressed in the membership function and non-membership function of IFS which are used to assess the weights of all criteria and the ratings of each alternative with respect to each criteria. Conditional normalized Euclidean distance measure is adopted to measure deviations between alternatives on intuitionistic fuzzy set. Then, a ranking algorithm is applied to indicate the order of superiority of alternatives. Finally, a practical example is given to an application of sustainable energy planning to verify our proposed method. Additionally, a comparative analysis is done among the proposed PROMETHEE II method and the intuitionistic fuzzy technique for order preference by similarity to ideal solution (IF-TOPSIS) method and elimination and choice translating reality method (IF-ELECTRE).     

A Distance-Based Consensus Model with Flexible Choice of Rank-Position Weights

In this paper we propose a preference aggregation procedure for those cases in which the decision-makers express their preferences by means of a ranking of alternatives. Among the most applied methods for this purpose are those inspired by the Borda–Kendall rule, which attach to each alternative an aggregated value of the votes received in the different rank positions, and those based on distance measures between individual and collective preferences, which look for the solution that maximizes the consensus. The main idea here is to integrate these two approaches. Taking into account that the information about the values of weights or utilities assigned to each rank position is imprecise, we propose an evaluation of the alternatives using that vector of weights that minimizes the disagreement between DMs. In order to solve the problem, mixed-integer linear programming models are constructed. Two numerical examples are examined to illustrate the applicability of the proposed procedure.     

Developing Group Ordered Weighted Averaging Operator Weights for Group Decision Support

A few single decision-making methods under uncertainty (SDMUU) are available in the literature. The reason for such scarcity seems to be mainly due to too insufficient information to induce a reasonable result for effective decision support. Moreover their final outcomes on the same SDMUU problem may be different depending on which method is applied. A group decision-making method under uncertainty (GDMUU) extends a SDMUU in a sense that a group of individuals, each expressing different opinions, work together to solve a relevant problem. As in a SDMUU, we find that just a few methods are available to solve a GDMUU problem. In the paper, the ordered weighted averaging (OWA) method, originally devised for use with the SDMUU problem, is considered to deal with a GDMUU problem where individuals of a group express their degree of optimism in terms of attitudinal characters. We first find the extreme points corresponding to the attitudinal character and then solve a quadratic mathematical program which minimizes a squared distance from each extreme point identified. Thus the resulting OWA operator weights for the group are located at the center of the weights-space constructed by attitudinal characters. This idea is further extended to deal with uncertain attitudinal character expressed in the form of interval in situations where it is difficult to reliably obtain a precise attitudinal character due to time pressure and a limited domain knowledge and so on.     

An Integrated Group Decision Making Support Model for Corporate Financing Decisions

The essential goal of corporate finance is to maximize corporate value while reducing a firm’s financial risks. Corporate financing decision is a kind of multi-criteria based group decision making that embodies major approaches to handle qualitative criteria and quantitative limitations. However, in literature related to financing decision making, very little research uses decision making trial and evaluation laboratory (DEMATEL) and analytic network process (ANP) methods to consider the impact and dependency of its factors, or uses Goal programming (GP) to find the satisfactory financing decision under the related financial constraints. This study proposes an integrated group decision making support (GDMS) model to assist corporate financing group decision makers (DMs) in obtaining a satisfactory group solution. ANP, DEMATEL and GP are combined in this GDMS model. By using this model, the group DMs can systemically structure a multi-criteria network framework and derive priority weights of those criteria, and then deal with the quantitative financial constraints for a satisfactory group solution. An illustrative case is demonstrated for the effectiveness and practicability of this GDMS model.     

Informal firms in developing countries: entrepreneurial stepping stone or consolation prize?

The potential dynamic benefits of a firm having the option to adopt informal status are analysed. Informality may be a stepping stone, without which formality may never be achieved. This result is obtained for a broad range of realistic parameter values, suggesting a potential dynamic case for government support of informal firms. Informality may alternatively play a converse role as a consolation prize, with a firm only entering an industry (formally) because it recognizes that if profitability is disappointing, it can switch to informality. However, this result is obtained for a range of parameter values so narrow as to be of no practical significance.     

From quantity to quality: understanding slow fashion consumers for sustainability and consumer education

There is a growing interest in slow fashion, a production method which emphasizes quality as a way of achieving sustainability in the fashion industry. In order to develop a sophisticated and targeted marketing strategy, this study aimed to identify potential slow fashion consumer segments and understand their characteristics. The final 221 completed responses from a sample of nationwide U.S. consumers were analyzed by cluster analysis. Based on consumer orientation to slow fashion, four consumer groups were identified: Highly‐involved in slow fashion group, Conventional group, Exclusivity oriented group and Low‐involved in slow fashion group. The characteristics of each group were profiled according to personal values, apparel consumption behaviours and demographics. With distinctive profiles of each group, different marketing strategies were suggested to address the needs of each group effectively. This study extends academic understanding of slow fashion in consumer perspectives, and provides important perspectives for consumer education on apparel consumption.     

A practitioner’s guide to Bayesian estimation of discrete choice dynamic programming models

This paper provides a step-by-step guide to estimating infinite horizon discrete choice dynamic programming (DDP) models using a new Bayesian estimation algorithm (Imai et al., Econometrica 77:1865?C1899, 2009a) (IJC). In the conventional nested fixed point algorithm, most of the information obtained in the past iterations remains unused in the current iteration. In contrast, the IJC algorithm extensively uses the computational results obtained from the past iterations to help solve the DDP model at the current iterated parameter values. Consequently, it has the potential to significantly alleviate the computational burden of estimating DDP models. To illustrate this new estimation method, we use a simple dynamic store choice model where stores offer ??frequent-buyer?? type rewards programs. Our Monte Carlo results demonstrate that the IJC method is able to recover the true parameter values of this model quite precisely. We also show that the IJC method could reduce the estimation time significantly when estimating DDP models with unobserved heterogeneity, especially when the discount factor is close to 1.     

The Perceived Impact of Information Technology on Salespeople's Relational Competencies

Abstract

Cross-cultural service research is an important topic with a rich array of empirical evidence for differences in customer perceptions, attitudes and behaviours. However, the extant literature is almost exclusively focused on differences between cultures at each end of the diversity spectrum (most commonly East vs. West). Contemporary researchers have observed that existing studies fail to acknowledge the substantially greater levels of intra-cluster variation that exist. A cultural cluster is a group of countries that reflect values, attitudes and beliefs stemming from a common cultural ancestry. This seems surprising given the anecdotal evidence and stereotypes that are portrayed in popular culture, media and art. One area where intra-cluster variation may be evident is consumer complaint behaviour and in particular within the Anglo-cultural cluster in countries. A cultural cluster is a group of countries that reflect values, attitudes and beliefs stemming from a common cultural ancestry. The aim of this study is therefore to explore and elucidate the nature of differences in consumer complaint behaviour between cultures traditionally conceived and operationalised as identical. This study presents a qualitative study of 60 in-depth interviews with consumers in the United Kingdom and Australia and identifies differences in complaining styles, parental influence and the conceptualisation of complaining.     

Deriving Weights from Interval Multiplicative Preference Relations in Group Decision Making

In this article, we investigate group decision making problems with interval multiplicative preference relations (including complete interval multiplicative preference relations and incomplete interval multiplicative preference relations). On the basis of the number of judgments and the consistency degree of each interval multiplicative preference relation, we first give a combined weighting method to derive the weights of decision makers. Then, we establish two linear programming models to derive the weight intervals of alternatives from all individual consistent interval multiplicative preference relations and utilize the continuous ordered weighted averaging operator or the continuous ordered weighted geometric operator to aggregate all the values in each weight interval. In addition, we establish a more general model to check the consistency of all individual interval multiplicative preference relations. In the cases where the optimal objective value of the model is not zero, we can get the optimal weights of alternatives directly, and then utilize these optimal weights and the optimal deviation values derived from the model to construct consistent interval multiplicative preference relations. Furthermore, we discuss some special cases of the established models and illustrate our models with a practical example.     

Corporate Social Responsibility as a Signalling Device for Foreign Direct Investment

A rise in CSR (corporate social responsibility) has accompanied rise in foreign direct investment (FDI) to developing countries in the 1990s. CSR may be serving a signalling function when the entering firm is of an unknown type. Although countries are now competing keenly to attract foreign firms, even so, excessive tax or excess transfers by firms can still cause a Prisoner’s Dilemma structure to the payoffs resulting in an inefficient Nash equilibrium. CSR allows the accommodating firm to reveal its type, making cooperation the equilibrium outcome. The game differs from standard models since signalling changes the payoffs. A unique separating equilibrium exists where only the accommodating firms signal. But, under certain parameter values, a pooling equilibrium where all firms signal, becomes possible. A number of results are derived including the size of CSR expenditure required as a fraction of profits. An example demonstrates their relevance in practical situations.     

From scarcity to abundance: reflections on using African values to combat fraud

By trying to see how one can use African values to fight against fraud, the paper attempts to bring out the structural dimension of this moral cancer by showing how it is linked to the ethical and economic/business systems where it thrives. I start by making some theoretical remarks about how values are to be placed in each socio-cultural setting. An analysis of how the free market economy as a system creates conditions where fraud becomes possible then follows. This is contrasted with an analysis of the African worldview and economic system where the starting point is that material and human resources abound, provided they are shared. The paper ends by suggesting ways in which African ethical values can be merged with the dominant economic system.     

The Cultural Paradigm of the Smaller Firm

This paper presents the findings from an ethnographic study of organizational culture and shared values in four smaller firms, the outcome of which was the identification of the cultural values shared between owner–managers (OMs) and employees in each firm. The research employed Schein's conceptualization of culture as a three-layer phenomenon, consisting of surface artifacts, shared values and beliefs, and basic assumptions. The analytical technique of grounded theory was employed to process the large volume of data gathered during the extended research period. The data reveal a complex array of values in each firm, with only one firm exhibiting a homogenous culture where values are shared by all those working in the organization. In the remaining three firms, five values appear to be shared by all employees; however, this is overlaid by a pattern of subcultures differentiated by distinctive shared values. Interfirm analysis among the four firms found that the values of survival, independence, control, pragmatism, and financial prudence were shared by two or more firms. The research collectively defines these shared values as the cultural paradigm of the smaller firm.     

Compatibility Analysis of Intuitionistic Fuzzy Preference Relations in Group Decision Making

Compatibility analysis is an efficient and important tool used to measure the consensus of opinions within a given group of individuals. In this paper, we give a compatibility measure between intuitionistic preference values and a compatibility measure between intuitionistic preference relations, respectively, and study their properties. It is shown that each individual intuitionistic preference relation and the collective intuitionistic preference relation is perfectly compatible if and only if all the individual intuitionistic preference relations are perfectly compatible. Based on the compatibility measures, a consensus reaching procedure in group decision making with intuitionistic preference relations is developed, and a method for comparing intuitionistic fuzzy values is pointed out, by which the considered objects are ranked and selected. In addition, we extend the developed measures, procedure and method to accommodate group decision making situations with interval-valued intuitionistic preference relations. Numerical analysis on our results through an illustrative example is also carried out.