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SWOT (strengths, weaknesses, opportunities, threats) analysis is a powerful approach for evaluating the strengths and weaknesses of an organization with an internal perspective. The approach also takes into account the opportunities and the threats from an external point of view. These features make SWOT a commonly used approach in strategic management. The purpose of this paper is to propose an integrated SWOT analysis with multiple preference relations technique, to show the application of the proposed methodology, to prioritize the strategic factors and to present alternative strategies for ABC, a case company, which is targeting to use social media more effectively.

In this study, expert opinions are used to identify SWOT factors of ABC on social media. The obtained findings are evaluated and each factor is prioritized by means of the multiple preference relations technique.

The proposed evaluation model has four main groups, namely, strengths, weaknesses, opportunities, threats, under which 17 factors are identified. As a result of the evaluations, “O2: Opportunity to contact a large number of users simultaneously at affordable cost” has the highest importance level among other factors. Alternative strategies are developed based on the obtained results.

Decision-makers who have different backgrounds or ideas can state their preferences in different formats. Multiple preference relations technique is used to combine different assessments. SWOT analysis with multiple preference relations technique with a group decision-making perspective is proposed. This is the first time the method is used in the social media-related literature. With this study, the most appropriate social media strategic factors are selected for ABC and alternative strategies are determined based on the results.

Today, companies are confronting a changing environment, which has never been faced before. It has been well accepted that with recent technological advances, barriers are eliminated and a new global market has been established. In order to obtain better results and customer satisfaction, the companies have to listen the voice of the customer and to produce value added products and services by reducing the cycle time. This requires an active and an effective management of operational functions and customer/supplier relationship. Information systems and technologies are the most important strategic tools supporting information and knowledge management in order to increase corporate responsiveness and enhanced performance. The objective of this study is to suggest an information‐based responsive organizational network framework supporting efficient management of company‐wide functions and customer/supplier relationships.

Today, customers are generally perceived to be demanding higher quality and better performing products, in shorter and more predictable development cycle-times and at a lower cost. These market pressures drive firms to collaborate with possible partners in product development (PD) processes. However, the selection of a suitable partner for an effective PD is not an easy decision and is associated with complexity. The purpose of this paper is to propose an integrated multi-criteria decision-making (MCDM) approach to effectively evaluate PD partners.

The proposed evaluation procedure consists of several steps. First, based on a literature review and expert validation, the strategic main and sub-criteria of the PD partner selection process that companies consider the most important are identified. After constructing the evaluation criteria hierarchy, the criteria weights are calculated by applying the Analytic Hierarchy Process (AHP) method. The VIKOR (a compromise ranking) method is used to obtain the final partner ranking results. A case study is given to demonstrate the potential of the methodology. In the last part of the study, a sensitivity analysis is performed to determine the influence of criteria weights on the decision making process.

The PD partner evaluation model contains three main criteria, namely, partner, collaboration and PD-oriented criteria, with 13 sub-criteria. The market position, competency of the partner, compatibility, technical expertise and complementarity are found as the most considerable evaluation criteria for the ABC case company. Results of the sensitivity analysis from different cases demonstrate that the integrated AHP-VIKOR model is quite sensitive to the weights assigned to the evaluation criteria. This finding underlines the importance of forming a capable, qualified group of experts for the decision-making procedure. The results of the empirical study show that the proposed evaluation framework is practical for solving partner selection problems.

Partner selection is critical to the success of a collaborative PD process. The main contribution of this paper is the definition and development of an effective evaluation framework to guide managers for suitable PD partner selection. In our knowledge, there exists no study in the literature that combines the established AHP VIKOR model for PD partner selection problem. This study can be useful to researchers to better understand PD partner selection problem theoretically, as well as to organizations in designing better satisfying PD partner evaluation systems.

Aims to formalize the benchmarking process by proposing methods and tools for the steps of the process. Focuses on the first two phases of the benchmarking process: measurement and self analysis (phase 1), and determination of subject and partners of a benchmarking study (phase 2). For this purpose, related to the first phase, a method of diagnosis is employed. In the second phase, three different data analysis methods (lexical analysis, principal components analysis and common factor analysis) are utilized. These two phases serve the purpose of an internal benchmarking (comparison between different domains of activities in the enterprise) and of an external benchmarking study (comparison between different enterprises). Three enterprises are selected for the benchmarking application. Related data are collected and analyzed, and results are reported.

This paper aims to examine the current state of reverse supply chain management (RSCM) initiatives in several Turkish industries.

This study is based on an exploratory research regarding RSCM activities of Turkish automotive, white goods, electric/electronics, and furniture industries. The sample consists of all the companies included in the Top‐500 Industrial Enterprises List of The Assembly of the Istanbul Chamber of Industry (ISO).

The research findings show that the RSCM initiatives in the considered industries are still in a very early stage. Companies' involvement in product returns is mostly due to the legislative liabilities, and system inadequacies are emphasized as the most important reason for not being able to implement an efficient RSCM.

This paper investigates the reverse supply chain practices of selected industries in Turkey and aims to enable researchers to use this study as a building block in understanding these practices and related problems. The limitation of this study is to solely include the medium and large‐sized companies in the industries.

Reverse supply chain operations contribute to the economic sustainability by reducing waste and saving energy and material. In this research, an empirical study in the electronics, white goods, automotive and furniture industries is conducted, and potential research opportunities are discussed to streamline reverse supply chain activities in the industries. Hence, this study can be viewed as an attempt to increase the level of awareness on reverse supply chain issues.

No field study has been conducted to analyze reverse supply chain activities of the industries in Turkey. This research is a pioneering study and will provide a benchmark for the various research activities on related topics.

The Internet offers companies many opportunities to implement new business models, called e(electronic)‐business in short, and to reinforce their competitiveness in the market. It is currently suggested that business‐to‐business commerce, which is one of the dominant segments in e‐business, is going to develop around e‐marketplaces. However, the new millennium has witnessed the rise and fall of many “dot.com” firms and now both the companies and the investors are extremely cautious about the performance and effectiveness of the e‐marketplaces. To get more benefit from this digital marketplace, suggests the use of fuzzy logic based on multi‐criteria evaluation as a superior means of improving the efficiency of the decision making for the e‐marketplace selection under uncertain conditions. This evaluation approach, in which both fuzzy analytic hierarchy process and fuzzy Delphi methodologies are employed, enables one to deal with the uncertainty and vagueness from subjective perception and the experiences of humans in a group decision process and ensures a more convincing and effective decision making. Also shows the application of the approach on a real life case.

This paper seeks to propose a managerial decision framework for different levels of supply chain, by addressing the strategic importance of competence values in supply chain effectiveness.

A conceptual framework for supply chain effectiveness is defined in levels of supply chain targets, knowledge management dynamics, competence levels and competence success attributes. Analysis of literature in the areas of competence management, knowledge management, supply chain and value chain management resulted in defining the factors of the model. Surveys of industrial practices were used to validate the choice of factors. The analytical network process (ANP) is used to determine the most beneficial competence success attributes in a case study performed for three companies that participate in different stages of the textile supply chain.

Individual competence in continuous learning and networking, as well as innovativeness of the team are found to be the three most important competence attributes in supply chain effectiveness.

The case study is executed in the regional textile industry. New case studies in other industries will help improve the framework. Further international surveys can improve the detail level of factors used.

The study creates awareness of knowledge management dynamics and competence management for companies which are in need of innovation to improve their supply chain competitiveness.

The proposed decision framework is one of the first efforts to consider the importance of competence in supply chain success. The ANP method is used to offer an accurate analysis of interdependent factors observed in management of knowledge dynamics and competence levels.

Under the digital wave and the new industrial competition pattern, the automobile industry is facing multiple challenges such as the redefinition of new technologies and supply chain changes. The purpose of this study is to link big data analytics and artificial intelligence (BDA-AI) with digital supply chain transformation (DSCT) by taking Chinese automobile industry firms as a sample and to consider the role of supply chain internal integration (SCII), supply chain external integration (SCEI) and supply chain agility (SCA) between them.

Data were collected from 192 Chinese firms in the automotive industry and analyzed using partial least squares structural equation modeling (PLS-SEM). Importance-performance map analysis is used to extend the standard results reporting of path coefficient estimates in PLS-SEM.

The results indicate that BDA-AI, SCII, SCEI and SCA positively influence DSCT. In addition, this study found that SCII, SCEI and SCA play an intermediary role in BDA-AI and DSCT.

The paper enriches the research on the mechanism of digital resources affecting DSCT and expands the research of organizational information processing theory in the context of digital transformation. The paper explores how the resources deployed by firms change the strategic measures of firms from the perspective of responsiveness. By exploring the positive impact of SCA as a response capability on the DSCT strategy and its intermediary role between digital resources and DSCT, which is helpful to the further theoretical development of logistics and supply chain disciplines.

The purpose of this paper is to examine the status of green supply chain management (GSCM) research in terms of how the field is represented along a number of dimensions including journal, year, country, university, publishing house, authors, research design, research methods, data analysis techniques, multi criteria decision-making methods, research topics/issues and major industries actively involved.

A range of online databases from 1998 to August 2013 were searched containing the word “green supply chain” in their title and in the phrases to provide a comprehensive listing of journal articles on GSCM. Based on this a total of 177 articles were found and the information on a series of variables was gathered. Each of these articles was further reviewed and classified. The review and classification process was independently verified. All papers were allocated to the main and sub-categories based on the major focus.

The major findings shows that survey research holds greater credibility and the trend in survey research is moving from exploratory to model building and testing. GSCM research related to organizational practices, environmental issues, process, performance and sustainability were found to be most widely published topics within the GSCM domain.

This paper is limited in reviewing those articles which contains the word “green supply chain” in the title and the phrases of the articles.

The present review will provide increased understanding of the current state of research and what still needs to be investigated in the GSCM discipline.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.