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

Evaluating strategies for implementing industry 4.0: a hybrid expert oriented approach of B.W.M. and interval valued intuitionistic fuzzy T.O.D.I.M.

open access articleDeveloping and accepting industry 4.0 influences the industry structure and customer willingness. To a successful transition to industry 4.0, implementation strategies should be selected with a systematic and comprehensive view to responding to the changes flexibly. This research aims to identify and prioritise the strategies for implementing industry 4.0. For this purpose, at first, evaluation attributes of strategies and also strategies to put industry 4.0 in practice are recognised. Then, the attributes are weighted to the experts’ opinion by using the Best Worst Method (BWM). Subsequently, the strategies for implementing industry 4.0 in Fara-Sanat Company, as a case study, have been ranked based on the Interval Valued Intuitionistic Fuzzy (IVIF) of the TODIM method. The results indicated that the attributes of ‘Technology’, ‘Quality’, and ‘Operation’ have respectively the highest importance. Furthermore, the strategies for “new business models development’, ‘Improving information systems’ and ‘Human resource management’ received a higher rank. Eventually, some research and executive recommendations are provided. Having strategies for implementing industry 4.0 is a very important solution. Accordingly, multi-criteria decision-making (MCDM) methods are a useful tool for adopting and selecting appropriate strategies. In this research, a novel and hybrid combination of BWM-TODIM is presented under IVIF information

The "fuzzy front end" of innovation

The fast transformation of technologies into new products or processes is one of the core challenges for any technology-based enterprise. Within the innovation process, we believe, the early phases (fuzzy front end) to have the highest impact on the whole process and the result (Input-Output Process), since it will influence the design and total costs of the innovation extremely. However the Fuzzy Front End is unfortunately the least-well structured part of the innovation process, both in theory and in practice. The focus of the present chapter is on methods and tools to manage the fuzzy front end of the innovation process. Firstly, the activities, characteristics, and challenges of the front end are described. Secondly, a framework of the application fields for different methods and tools is presented: Since a product upgrade requires a different approach compared to radical innovation, where the market is unknown and a new technology is applied, we believe such a framework to be useful for practitioners. Thirdly, a selection of methods and tools that can be applied to the fuzzy front end are presented and allocated within the framework. The methods selected here address process improvements, concept generation, and concept testing. --fuzzy front end,innovation management,stage-gate process,frontloading,triz,dsm-matrix,lead user

Re-Politicising Regulation: Politics: Regulatory Variation and Fuzzy Liberalisation in the Single European Energy Market

[From the introduction] The idea that we are living in the age of the regulatory state has dominated the study of public policy in the European Union and its member states in general, and the study of the utilities sectors in particular.1 The European Commission’s continuous drive to expand the Single Market has therefore been a free-market and rule-oriented project, driven by regulatory politics rather than policies that involve direct public expenditure. The dynamics of European integration are rooted in three central concepts: free trade, multilateral rules, and supranational cooperation. During the 1990s EU competition policy took a ‘public turn’ and set its sights on the public sector.2 EU legislation broke up national monopolies in telecommunications, electricity and gas, and set the scene for further extension of the single market into hitherto protected sectors. Both the integration theory literature (intergovernmentalist and institutionalist alike) and literature on the emergence of the EU as a ‘regulatory state’ assumed that this was primarily a matter of policy making: once agreement had been reached to liberalise the utilities markets a relatively homogeneous process would follow. The regulatory state model fit the original common market blueprint better the old industrial policy approaches. On the other hand, sector-specific studies continue to reveal a less than fully homogeneous internal market. The EU has undergone momentous changes in the last two decades, which have rendered the notion of a homogeneous single market somewhat unrealistic