https://sci2s.ugr.es/sites/default/files/files/ScientificImpact/2005-EJOR-Herrera-GDM.pdf

Managing non-homogeneous information in group decision making

In decision-making problems there may be cases in which experts do not have an in-depth knowledge of the problem to be solved. In such cases, experts may not put their opinion forward about certain aspects of the problem, and as a result they may present incomplete preferences, i.e., some preference values may not be given or may be missing. In this paper, we present a new model for group decision making in which experts' preferences can be expressed as incomplete fuzzy preference relations. As part of this decision model, we propose an iterative procedure to estimate the missing information in an expert's incomplete fuzzy preference relation. This procedure is guided by the additive-consistency (AC) property and only uses the preference values the expert provides. The AC property is also used to measure the level of consistency of the information provided by the experts and also to propose a new induced ordered weighted averaging (IOWA) operator, the AC-IOWA operator, which permits the aggregation of the experts' preferences in such a way that more importance is given to the most consistent ones. Finally, the selection of the solution set of alternatives according to the fuzzy majority of the experts is based on two quantifier-guided choice degrees: the dominance and the nondominance degree

/pdf/group-decision-making-model-with-incomplete-fuzzy-preference-3y7r5wjvc5.pdf

Group Decision-Making Model With Incomplete Fuzzy Preference Relations Based on Additive Consistency

Although a large volume of literature is available on mobile commerce (m-commerce), the topic is still under development and offers potential opportunities for further research and applications. Since the subject is at the stage of development, a review of the literature on m-commerce with the objective of bringing to the fore the state-of-art in m-commerce research and applications will initiate further research on the growth of m-commerce technologies. This paper reviews the literature on m-commerce and applications using a suitable classification scheme to identify the gap between theory and practice and future research directions. The 149 m-commerce articles are classified and the results of these are presented based on a scheme that consists of five distinct categories: m-commerce theory and research, wireless network infrastructure, mobile middleware, wireless user infrastructure, and m-commerce applications and cases. A comprehensive list of references is presented. We hope that the findings of this research will provide useful insights into the anatomy of m-commerce literature and be a good source for anyone who is interested in m-commerce. The paper also provides some future directions for research.

A review for mobile commerce research and applications

A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information

https://rua.ua.es/dspace/bitstream/10045/12343/1/paperJEMpublicadoonline.pdf

The whole relationship between environmental variables and firm performance: Competitive advantage and firm resources as mediator variables

The paper provides a comprehensive review of the recent development of revenue management in different industries. We discuss research on different revenue management strategies including pricing, auctions, capacity control, overbooking and forecasting. Related issues such as economic concerns, customer perception, competition and consolidation, implementation, performance evaluation, and common techniques and approaches used for solving revenue management problems are also discussed. Finally, we give our suggestion on some important areas that warrant further research.

An overview of research on revenue management: current issues and future research

This paper aims at multi-objective optimization of single-product for four-echelon supply chain architecture consisting of suppliers, production plants, distribution centers (DCs) and customer zones (CZs). The key design decisions considered are: the number and location of plants in the system, the flow of raw materials from suppliers to plants, the quantity of products to be shipped from plants to DCs, from DCs to CZs so as to minimize the combined facility location and shipment costs subject to a requirement that maximum customer demands be met. To optimize these two objectives simultaneously, four-echelon network model is mathematically represented considering the associated constraints, capacity, production and shipment costs and solved using swarm intelligence based Multi-objective Hybrid Particle Swarm Optimization (MOHPSO) algorithm. This evolutionary based algorithm incorporates non-dominated sorting algorithm into particle swarm optimization so as to allow this heuristic to optimize two objective functions simultaneously. This can be used as decision support system for location of facilities, allocation of demand points and monitoring of material flow for four-echelon supply chain network.

Location and allocation decisions for multi-echelon supply chain network - A multi-objective evolutionary approach

In multiple criteria decision making (MCDM), decision makers (DMs) always give preferences information on alternatives, criteria or decision matrices. Since the DMs may have diverse cultural and educational background and value systems, their preference would be expressed in different ways. This is especially true in cyberspace. In this study, the DMs are asked to express their preferences on a variety of criteria using any one of the following preference formats: preference orderings, utility values, multiplicative preference relation, selected subset, fuzzy selected subset, normal preference relation, fuzzy preference relation, linguistic terms, and pairwise comparison. In addition, we propose a uniformity method and an aggregating method to provide both convenience and accuracy in generating the final outcome and higher DM satisfaction. Finally, the validity of using multiple preference formats in criteria weight determination is verified through an experiment.

Decision consolidation: criteria weight determination using multiple preference formats

In today's globalization, the success of an industry is dependent on cost effective supply chain management under various markets, logistics and production uncertainties. Uncertainties in the supply chain usually decrease profit, i.e. increase total supply chain cost. Demand uncertainty and constraints posed by the every echelon are important factors to be considered in the supply chain design operations. Optimization is no longer a luxury but has become the order of the day. This paper specifically deals with the modeling and optimization of a three echelon supply chain network using the particle swarm optimization/intelligence algorithms.

Application of particle swarm intelligence algorithms in supply chain network architecture optimization

As electronic commerce (EC) (e-commerce) booms, research on factors influencing the adoption of e-commerce has caught researchers' attention. The results of this research stream have facilitated our understanding of e-commerce adoption. However, the research results have been mixed. Furthermore, previous studies placed more focus on organisational factors than on owners' demographic factors. This research was initiated to resolve those conflicting findings and focused on the impact of owners' characteristics in ecommerce adoption. Data collected from 600 Small- and Medium-size Enterprises (SMEs) were analysed with one-way ANOVA and hierarchical regression to investigate the impacts of three organisational characteristics and four owner characteristics. The results revealed that those variables explained a small amount of variance in the extent of e-commerce adoption. The main findings include: (1) managerial experience has impact on the extent of e-commerce adoption and (2) the extent of e-commerce adoption varies across business types. This paper discusses these findings in the context of previous research and implications.

Jason C.H. Chen

Papers

An overview of research on revenue management: current issues and future research

Location and allocation decisions for multi-echelon supply chain network - A multi-objective evolutionary approach

Decision consolidation: criteria weight determination using multiple preference formats

Application of particle swarm intelligence algorithms in supply chain network architecture optimization

Examining the impact of organisational and owner's characteristics on the extent of e-commerce adoption in SMEs