VIKOR Technique:A Systematic Review of the State of the Art Literature on Methodologies and Applications

The main objective of this paper is to present a systematic review of the VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) method in several application areas such as sustainability and renewable energy. This study reviewed a total of 176 papers, published in 2004 to 2015, from 83 high-ranking journals; most of which were related to Operational Research, Management Sciences, decision making, sustainability and renewable energy and were extracted from the “Web of Science and Scopus” databases. Papers were classified into 15 main application areas. Furthermore, papers were categorized based on the nationalities of authors, dates of publications, techniques and methods, type of studies, the names of the journals and studies purposes. The results of this study indicated that more papers on VIKOR technique were published in 2013 than in any other year. In addition, 13 papers were published about sustainability and renewable energy fields. Furthermore, VIKOR and fuzzy VIKOR methods, had the first rank in use. Additionally, the Journal of Expert Systems with Applications was the most significant journal in this study, with 27 publications on the topic. Finally, Taiwan had the first rank from 22 nationalities which used VIKOR technique

What attracts vehicle consumers’ buying:A Saaty scale-based VIKOR (SSC-VIKOR) approach from after-sales textual perspective?

Purpose: The increasingly booming e-commerce development has stimulated vehicle consumers to express individual reviews through online forum. The purpose of this paper is to probe into the vehicle consumer consumption behavior and make recommendations for potential consumers from textual comments viewpoint. Design/methodology/approach: A big data analytic-based approach is designed to discover vehicle consumer consumption behavior from online perspective. To reduce subjectivity of expert-based approaches, a parallel Naïve Bayes approach is designed to analyze the sentiment analysis, and the Saaty scale-based (SSC) scoring rule is employed to obtain specific sentimental value of attribute class, contributing to the multi-grade sentiment classification. To achieve the intelligent recommendation for potential vehicle customers, a novel SSC-VIKOR approach is developed to prioritize vehicle brand candidates from a big data analytical viewpoint. Findings: The big data analytics argue that “cost-effectiveness” characteristic is the most important factor that vehicle consumers care, and the data mining results enable automakers to better understand consumer consumption behavior. Research limitations/implications: The case study illustrates the effectiveness of the integrated method, contributing to much more precise operations management on marketing strategy, quality improvement and intelligent recommendation. Originality/value: Researches of consumer consumption behavior are usually based on survey-based methods, and mostly previous studies about comments analysis focus on binary analysis. The hybrid SSC-VIKOR approach is developed to fill the gap from the big data perspective

Combining DRSA decision-rules with FCA-based DANP evaluation for financial performance improvements

This study proposes a combined method to integrate soft computing techniques and multiple criteria decision making (MCDM) methods to guide semiconductor companies to improve financial performance (FP) – based on logical reasoning. The complex and imprecise patterns of FP changes are explored by dominance-based rough set approach (DRSA) to find decision rules associated with FP changes. Companies may identify its underperformed criterion (gap) to conduct formal concept analysis (FCA) – by implication rules – to explore the source criteria regarding the underperformed gap. The source criteria are analysed by decision making trial and evaluation laboratory (DEMATEL) technique to explore the cause-effect relationship among the source criteria for guiding improvements; in the next, DEMATEL-based analytical network process (DANP) can provide the influential weights to form an evaluation model, to select or rank improvement plans. To illustrate the proposed method, the financial data of a real semiconductor company is used as an example to show the involved processes: from performance gaps identification to the selection of five assumed improvement plans. Moreover, the obtained implication rules can integrate with DEMATEL analysis to explore directional influences among the critical criteria, which may provide rich insights and managerial implications in practice. First published online: 17 Sep 201

Design of an Analysis Model for Strategic Behavior in the Digital Economy

Nowadays, multi-criteria decision-making techniques are highly developed, and are widely applied in multiple fields. They model and solve decisional problems by optimising multiple conflicting objectives. These techniques are very useful because they simultaneously analyse all the different criteria, and select the best alternatives according to the decision-maker’s objectives and preferences. An important issue in this context is the adequacy of the structure of corporate long-term financing and its potential impact on the sustainable development of the long-term business plan. The purpose of this study is to advance the analysis of these strategic decisions, measuring the a posteriori results and analysing their coherence with the strategies followed a priori. To do this, sustainable strategic decisions will be mathematically modelled and parametrised, creating a system to study the preferences followed and to describe the corporate behaviour. This system is applied as a case example for two leading companies in the digital sector, and the corresponding results over the last few years are evaluated

Multiple criteria approach applied to digital transformation in fashion stores: the case of physical retailers in Spain

This research is funded by the Spanish State Research Agency, as part of the project PID2019103880RB-I00/AEI/10.13039/501100011033, and by the Andalusian Government, as part of the project P20_00673.In a very open competitive context where pure online players are consistently gaining market share, the use of digital devices is a steady trend which is penetrating physical retail stores as a tool for retailers to improve customer experience and increase engagement. This need has increased with the COVID-19 pandemic as electronic devices in physical stores reduce the contact between people providing a greater sense of health safety, hence improving the customer experience. This work develops a multiple-criteria decision-making model for retailers who want to digitize their physical stores, providing a systematic approach to manage investment priorities in the organization. Important decisions should involve all different areas of the organization: Finance, Clients, Internal Processes and Learning & Growth departments. This strategic decision can be made hierarchically to obtain consistent decisions, also the use of the Order Weighted Average operator allows for alternative scenarios to be presented and agreed among the different areas of the business. The authors develop a use case for a Spanish fashion retailer. In the most widely agreed scenario the preferred devices were more technologically complex and expensive, while in the scenarios where the head of Finance is more predominant, cheaper and simpler devices were selected.Spanish Government PID2019103880RB-I00/AEI/10.13039/501100011033Andalusian Government P20_0067

Odabir konkurentskih strategija u europskom bankarskom sektoru primjenom pristupa hibridnog odlučivanja

Strategic planning is an eJective tool for long-term planning and utilized by organizations and industries to achieve competitive advantage. Addressing difculties that the European banking sector struggled during and after the global financial crisis (GFC), the purpose of this paper is to raise important questions about the sustainability of the sector and oJers competitive strategy formulations for European policy makers. Empirical findings are accomplished by applying a three phase analysis of SWOT, an integrated model of DEMATEL-ANP (DANP), and fuzzy TOPSIS. Empirical findings from the SWOT analysis suggest a total of twelve factors, which are then incorporated to formulate four strategies. The DANP results illustrate that opportunities dimension has the highest impact and strengths has the lowest among others. The fuzzy TOPSIS results demonstrate that “the European Banking Union (EBU) is expected to remove divergence in the Euro area banking sector” is the most important strategy, whilst “the non-risk based leverage ratio (LR) requirement by Basel III” has the weakest importance among the strategy preferences.Strateško planiranje je učinkovit alat za dugoročno planiranje koje primjenjuju organizacije i industrije za postizanje konkurentske prednosti. S obzirom na poteškoće s kojima se europski bankarski sektor suočava za vrijeme i nakon globalne financijske krize (GFC), svrha ovog rada je podići važna pitanja o održivosti sektora i ponuditi formulacije konkurentnih strategija za europske kreatore politike. Empirijski rezultati postižu se primjenom SWOT analize u tri faze, integriranog modela DEMATEL-ANP (DANP) i ‘fuzzy’ (neizrazitog) TOPSIS-a. Empirijski rezultati SWOT analize ukazuju na ukupno dvanaest čimbenika, koji su potom uključeni u formuliranje četiri strategije. DANP rezultati potvrđuju da faktor prilika ima najveći utjecaj, a snage imaju najniži utjecaj u odnosu na ostala tri faktora. Neizraziti rezultati TOPSIS-a pokazuju da najvažnija strategija jest da “Europska bankovna unija (EBU) ukloni odstupanja u bankarskom sektoru u eurozoni”, dok “zahtjev Basel-a III o nerizičnom omjeru financijske poluge (LR)” ima najmanju važnost medu strategijskim prioritetima

A hybrid model for decision-making in the information and Communications Technology sector

The majority of businesses in the Information and Communications Technology (ICT) sector face decision-making problems on a daily basis. Most of these problems are based on contexts of uncertainty, where decisions are founded on qualitative information which may be imprecise or perception-based. In these cases, the information which is expressed by experts and users of evaluated services can be treated using processes of computing with words (CW). In this paper, we present a hybrid decision-making model especially designed for the ICT sector whereby the experts have the support of an intelligent system which provides information about the opinions of users related to those problems which are to be analysed. These opinions are obtained by using different mechanisms and techniques when users conduct business with the service provider. In addition, we employ a procedure for obtaining consensus between experts which enriches and strengthens the decision-making process

A framework to manage uncertainties in cloud manufacturing environment

This research project aims to develop a framework to manage uncertainty in cloud manufacturing for small and medium enterprises (SMEs). The framework includes a cloud manufacturing taxonomy; guidance to deal with uncertainty in cloud manufacturing, by providing a process to identify uncertainties; a detailed step-by-step approach to managing the uncertainties; a list of uncertainties; and response strategies to security and privacy uncertainties in cloud manufacturing. Additionally, an online assessment tool has been developed to implement the uncertainty management framework into a real life context. To fulfil the aim and objectives of the research, a comprehensive literature review was performed in order to understand the research aspects. Next, an uncertainty management technique was applied to identify, assess, and control uncertainties in cloud manufacturing. Two well-known approaches were used in the evaluation of the uncertainties in this research: Simple Multi-Attribute Rating Technique (SMART) to prioritise uncertainties; and a fuzzy rule-based system to quantify security and privacy uncertainties. Finally, the framework was embedded into an online assessment tool and validated through expert opinion and case studies. Results from this research are useful for both academia and industry in understanding aspects of cloud manufacturing. The main contribution is a framework that offers new insights for decisions makers on how to deal with uncertainty at adoption and implementation stages of cloud manufacturing. The research also introduced a novel cloud manufacturing taxonomy, a list of uncertainty factors, an assessment process to prioritise uncertainties and quantify security and privacy related uncertainties, and a knowledge base for providing recommendations and solutions