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This paper aims to develop strategy and policy suggestions to increase the competitiveness of SMEs in the textile industry by analyzing the variables that affect competitiveness and contribute to competitiveness literature by adopting a holistic approach to the analysis of competitiveness variables. A hybrid model composed of Delphi and fuzzy DEMATEL (Decision-Making Trial and Evaluation Laboratory) methods were used to gather and analyze the competitiveness variables. This led to the identification of the 15 most important of 73 competitiveness variables relevant to SME competitiveness in the textile industry. These variables were analysed and ranked, and their causal relationships were mapped. The results obtained from the model may function as a reference for SME managers aiming to increase their firm’s competitive power.

Ever-changing conditions and emerging new challenges affect the ability of the healthcare sector to survive with the current system, and to maintain its processes effectively. In the healthcare sector, the conservation of the natural resources is being obstructed by insufficient infrastructure for managing residual waste resulting from single-use medical materials, increased energy use, and its environmental burden. In this context, circularity and sustainability concepts have become essential in healthcare to meliorate the sector’s negative impacts on the environment. The main aim of this study is to identify the barriers related to circular economy (CE) in the healthcare sector, apply big data analytics in healthcare, and provide solutions to these barriers. The contribution of this research is the detailed examination of the current healthcare literature about CE adaptation, and a proposal for a big data-enabled solutions framework to barriers to circularity, using fuzzy best-worst Method (BWM) and fuzzy VIKOR. Based on the findings, managerial, policy, and theoretical implementations are recommended to support sustainable development initiatives in the healthcare sector.

PurposeThe existence of long memory and persistent volatility characteristics of cryptocurrencies justifies the investigation of return and volatility/shock spillovers between traditional financial market asset classes and cryptocurrencies. The purpose of this paper is to investigate the dynamic relationship between the cryptocurrencies, namely Bitcoin and Ethereum, and stock market indices of G7 and E7 countries to analyze the return and volatility spillover patterns among these markets by means of multivariate (MGARCH) approach.Design/methodology/approachApplying the newly developed VAR-GARCH-in mean framework with the BEKK representation, the empirical results reveal that there exists an evidence of mean and volatility spillover effects among Bitcoin and Ethereum as the proxies for the cryptocurrencies, and stock markets reviewed.FindingsInterestingly, the direction of the return and volatility spillover effects is unidirectional in most E7 countries, but bidirectional relationship was found in most G7 countries. This can be explained as the presence of a strong return and volatility interaction among G7 stock markets and crypto market.Originality/valueOverall, the results of this study are of particular interest for portfolio management since it provides insights for financial market participants to make better portfolio allocation decisions. It is also increasingly important to understand the volatility transmission mechanism across these markets to provide policymakers and regulatory bodies with guidance to eliminate the negative impact of cryptocurrency's volatility on the stability of financial markets.

The purpose of this study is to explore the factors affecting organizational commitment, to analyze relations between these factors by introducing a new model, and to reveal how these factors specifically affect work commitment and intention to quit the job. The factors were pooled after extensive literature research. A two-phase pilot study was applied, along with normality tests, factor analysis, discriminant validity, and regression analysis. The final form of the survey was conducted with 205 participants actively employed in an organization. Important findings of the study suggest that work commitment is positively affected by organizational trust, the importance of the job, affective commitment, normative commitment, and negatively affected by self-confidence. Organizational trust and affective commitment negatively affect intention to quit, whereas self-confidence and talent positively affect intention to quit. By introducing an originally proposed organizational commitment model, this study presents an up-to-date analysis of some overlooked factors in the literature and suggests new factors potentially affecting organizational commitment, work commitment, and intention to quit. The outputs of this study can be utilized by organizations in making strategic decisions about indubitably one of the most precious assets of organizations: employees.