A robust fuzzy possibilistic AHP approach for partner selection in international strategic alliance

The international strategic alliance is an inevitable solution for making competitive advantage and reducing the risk in today’s business environment. Partner selection is an important part in success of partnerships, and meanwhile it is a complicated decision because of various dimensions of the problem and inherent conflicts of stockholders. The purpose of this paper is to provide a practical approach to the problem of partner selection in international strategic alliances, which fulfills the gap between theories of inter-organizational relationships and quantitative models. Thus, a novel Robust Fuzzy Possibilistic AHP approach is proposed for combining the benefits of two complementary theories of inter-organizational relationships named, (1) Resource-based view, and (2) Transaction-cost theory and considering Fit theory as the perquisite of alliance success. The Robust Fuzzy Possibilistic AHP approach is a noveldevelopment of Interval-AHP technique employing robust formulation; aimed at handling the ambiguity of the problem and let the use of intervals as pairwise judgments. The proposed approach was compared with existing approaches, and the results show that it provides the best quality solutions in terms of minimum error degree. Moreover, the framework implemented in a case study and its applicability were discussed

The Success Factors in Measuring the Millennial Generation’s Energy-Saving Behavior Toward the Smart Campus

The millennial generation has a pivotal role in leading the industrial digital revolution. Energy-saving behavior and millennials’ awareness of energy consumption for educational context become crucial in performing a smart campus. This study tries to identify the success factors in measuring the millennial generation’s energy-saving Behavior toward the smart campus. The measurement model considers two significant constructs, including energy-saving attitudes with energy-saving education (organizational saving climate); energy-saving education and environment knowledge (personal saving climate); and energy-saving information publicity as sub-indicators, and construct energy-saving Behavior viz sub-indicators Behavior regarding energy and behavior control. In order to determine the preference level of each indicator and sub-indicator, the Fuzzy Analytical Hierarchy Process (Fuzzy-AHP) approach was executed by disseminating the questionnaire to 100 respondents from energy practitioners, students, and academicians in Indonesia. The calculation reveals that the energy-saving behavior construct has a higher priority value (0.94) than the energy-saving attitude (0.06). Meanwhile, energy-saving education and environment knowledge (personal saving climate) have been analyzed at the cutting-edge sub-indicator, followed by energy-saving information publicity and education (organizational saving climate). In addition, the sub-indicator for behaviors regarding energy becomes more demanding compared to behavioral control. As a novelty, the priority analysis of this Model aids the management of the campus and government in developing smart campus policies and governance. This Model can be used as a guideline for the management level to execute the smart campus practices. Thus, the effectiveness and optimization of smart campus transformation can be cultivated and accelerated. Besides, the potential coming of risks can be avoidable

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

Corporate Firm-Level Knowledge Accumulation and Engineering Manpower Outsourcing

Firm-level knowledge is a key resource providing a competitive advantage in innovation for enterprises. Outsourcing strategies reveal trends in strategic business administration. However, internal knowledge accumulation (KA) and engineering manpower outsourcing (EMO) produce opposing effects on firm-level knowledge. This study analyzes the relationship between KA and EMO among enterprises in Taiwan by means of expert interviews, an analytic hierarchy process (AHP), and a fuzzy logic inference system (FLIS). The results show that, compared to EMO, firm-level KA affords a greater degree of influence on the effectiveness of firm-level knowledge. Based on the literature and expert interviews, the three sub-variables of knowledge integration ability (KIA), knowledge absorption ability (KAA), and knowledge sharing ability (KSA) are extracted from the KA variable, and the three sub-variables of cost, resources, and strategy are extracted from the EMO variable

An Analytic Hierarchy Process for The Evaluation of Transport Policies to Reduce Climate Change Impacts

Transport is the sector with the fastest growth of greenhouse gases emissions, both in developed and in developing countries, leading to adverse climate change impacts. As the experts disagree on the occurrence of these impacts, by applying the analytic hierarchy process (AHP), we have faced the question on how to form transport policies when the experts have different opinions and beliefs. The opinions of experts have been investigated by a means of a survey questionnaire. The results show that tax schemes aiming at promoting environmental-friendly transport mode are the best policy. This incentives public and environmental-friendly transport modes, such as car sharing and car pooling.Analytic Hierarchy Process, Transport Policies, Climate Change

A framework for assessing trust in e-government services under uncertain environment

In this study, a novel framework was proposed to assess the trust in e-government (e-Gov) services under an uncertain environment. The proposed framework was applied in Iranian municipality websites of e-Gov services to evaluate the readiness score of trust in e-Gov services. A unique hybrid research methodology was proposed. In the first phase, a comprehensive set of indices were determined from an extensive literature review and finalized by employing the fuzzy Delphi method. In the second phase, Interval-Valued Intuitionistic Fuzzy Sets (IVIFS) was utilized to model the problem’s uncertainty with Analytic called IVIFS- Hierarchy Process (AHP) to determine the importance of indices and indicators by assigning the weights. In the third phase, the Fuzzy Evaluation Method (FEM) is followed for assessing the readiness score of indices in case studies. The findings indicated that “Trust in government” is the most significant index affecting citizen’s trust in e-Gov services while “Maintenance and support” has the least impact on user’s intention to use e–Gov services. The study is one of the few to indicate significant indices of trust in e-Gov services in developing countries. The study shows the importance of indicators and indices by assigning a weight. Additionally, the framework can assess the readiness score of various case studies. Research Implications: The study contributes by introducing a unique research methodology that integrates three phases, including Fuzzy Delphi, IVIFS AHP and Fuzzy Evaluation method. Moreover, the Fuzzy sets theory helps to reach a more accurate result by modeling the inherent ambiguity of indicators and indices. Interval-Valued Intuitionistic Fuzzy models the ambiguity of experts’ judgments in an interval. The study helps policy makers to monitor wider aspects of trust in e-Gov services as well as understanding their importance. The study enables policy makers to apply the framework to any potential case studies to evaluate the readiness score of indices and recognizing strengths and weakness of trust dimensions as well as recommending advice for improving the situation

Barriers to Information and Digital Technologies Adoption in Humanitarian Supply Chain Management : A Fuzzy AHP Approach

Peer reviewedPostprin

The development of a project typology and selection tool to improve decision-making in sustainable projects

Decision-making in sustainable projects is a complex and challenging process, especially during the initiating and planning phases of project development, due to influence from several external factors, as well as the uncertain environments surrounding their creation. It is essential to improve the decision-making process in sustainable projects during these two phases by relying on strong decision-making tools. The first contribution in this work identifies gaps in the literature of how institutionalization can impact sustainable projects through the effects of institutional isomorphisms from institutional theory. This helps decision makers better understand the relationship between institutionalization and sustainable projects. The second contribution is a sustainable project typology based on the affects that the coercive, normative, and mimetic institutional pressures have on common key sustainable project characteristics. The typology can improve decision-making by providing realistic predictions about the project early in the planning phase. The third contribution further develops this typology into a project selection tool that can be used in the initiating phase. It applies the Fuzzy Analytic Hierarchy Process (FAHP) to rank the key project characteristics based on importance as selection criteria by utilizing the literature as the voice of expert opinion. Because using the literature as a source of expert opinion can present its own set of challenges, the fourth contribution considers how the choice of selection tool inputs can impact project selection. Accordingly, Subject Matter Experts (SMEs) are utilized as an alternative source of expert opinion in an effort to validate the previously generated results and compare how these selection criteria are prioritized in literature and practice --Abstract, page iv

Providing a Hybrid Methodology to Solve the Supplier Selection Problems: Application of MCDM Techniques

The emphasis of supply chain management (SCM) is majorly on the relationship between enterprise alliance and core enterprise. One of the main decision-making problems in SCM is choosing strategic partners, which also is the key to a prosperous SCM. In the present study, SCM is investigated using the analytical hierarchy process (AHP) simulation approach o examine the uncertainty involved in AHP and reduce its risk to some extent. Finally, this approach is employed to solve the problem of supplier selection in SCM

Analysis of the Factors Affecting the Adoption of Management Information Systems

The present study was conducted with the aim to identify and rank the factors affecting the successful adoption of management information systems in medical centers of Kerman (Iran). For this purpose, based on research literature and experts’ interview 27 criteria were identified in four dimensions and categorized. Then, considering the causal relationships between them and the importance of each indicator, the AHP and DEMATEL multi-criteria decision making approach was used in the Intuitionistic fuzzy environment. In the present study, the weight of dimensions was determined using AHP method and then the causal relationships between dimensions and degree of influence and effectiveness of each dimension were determined using DEMTEL technique. The results obtained that the dimension of senior management support is identified as the most important dimension. Then, the dimensions of information quality, system quality, and finally the user experience are important.https://dorl.net/dor/20.1001.1.20088302.2022.20.3.4.1