Continuous improvement and innovation are solid foundations for the textile sector to maintain excellent growth and active sustainability. As the limited resources possessed by textile companies generally result in the incapability of implementing circular economy (CE) strategies simultaneously, recently, researchers advocate that organizations should analyze the influential inter-relationship between key barriers to explore the more dominant determinants for designing improved actions for implementing CE in the textile sector. CE implementation in the textile sector appears to be in its infancy. Although much attention has been paid to CE implementation barriers, the present study tries to fill this research gap by analyzing the causal relationships among the CE barriers in the textile sector. Therefore, the twelve barriers are identified by an extensive literature review, and the application of the Fuzzy Delphi Method (FDM) based on the expert options from the textile sector. Subsequently, the causal inter-relationship among the key CE barriers is based on expert opinions using the decision-making trial and evaluation laboratory (DEMATEL). The results of this study indicate that three key barriers require quick action: “consumers lack knowledge and awareness about reused/recycle (B1)”, “lack of successful business models and frameworks to implement CE (B3)”, and “lack of an information exchange system between different stakeholders (B8)”. In addition, the results provide significant managerial implications, including implementations of CE in the textile sector. Not only should the government build regulations and friendly laws and encourage environmentally-friendly materials but the textile companies should also focus or monitor the recycling methods and quality to overcome the CE implementation issues. In addition, this study contributes to the textile sector transition toward CE by using the novel methodology for determining and prioritizing the key barriers. Finally, this work would help top management and the practitioners to better design effective infrastructural strategies for the textile sector transition towards CE.

Theoretical explanation concerning the psychological well-being of elderly adults as they participate in a particular leisure activity has been rare. Based on the theory of planned behavior and the technology acceptance model, this study sought to understand the Tai Chi Chuan (TCC) participation influence factors, process, and psychological well-being of Chinese people. A self-developed questionnaire was developed to test the hypotheses of this study. Applying structural equation models, a survey of 769 TCC participations were used to test the theoretical model. The results indicated that perceived usefulness significantly and positively affect respondent attitude, family members’ influences significantly and positively affect participants’ subjective norm, and resource facilitating conditions significantly and positively affect perceived behavioral control. Perceived behavioral control, attitude, and subjective norm significantly and positively affect TCC participants. The study lends support to the notion that leisure activity participation is vital for elderly adults and their well-being, and it develops a theoretical reference model for better understanding the leisure participation perceptual reasoning processes of elderly adults. Furthermore, the results offer important implications for health policy makers, clinical prevention, and interventions using participation behavior relationships to develop well-constructed leisure programs to attract and inspire participation and, hence, improve the psychological well-being of elderly adults.

During the past several years, many governments and non-government organizations in the world made efforts to promote policies and activities regarding corporate social responsibility and proposal of relevant regulations. However, scandals of international financial organizations and transnational corporations are enduring issues, which threaten to reduce social responsibility to a mere corporate slogan. This is not only the basis for sustainable operations but, also it is a vital academic issue. Understanding the factors behind the intention of a corporation’s social responsibility practice is a problem that governments and other governance organizations urgently need to solve and is also an issue that scholars and other relevant workers need to pay attention to and investigate. This study tries to discuss the behavioral intention behind social responsibility practices, and to point out exogenous factors, corresponding with theory of reasoned action, among the factors proposed by literature regarding corporate social responsibility. Then we apply structural equation modelling to analyze each hypothesis of the study. Finally, the results show several determinants which empirically affect behavioral intentions towards social responsibility practices. This study serves as a supplement for present literature, which did not clearly explain the reason why corporations hesitate to put social responsibility into action. In addition, although the theory of reasoned action was widely used to discuss the motive of various reasoned actions, the current study might be a pioneer in using theory of reasoned action to discuss the behavioral models for corporate social responsibility practices and discussing the applicability of the theory of reasoned action based on empirical data.

Different sources of risk factors can occur in sustainable supply chain management due to its complex nature. The telecommunication service firm cannot implement multiple improvement practices altogether to overcome the risk factors with limited resources. The industries should evaluate the relationship between risk factors and explore the determinants of improvement measures. The purpose of the present study is to identify and analyze critical risk factors (CRFs) for enhancing sustainable supply chain management practices in the Indian telecommunication industry using interpretive structural modelling (ISM). Risk factors are identified through a literature survey, and then with the help of experts, nine CRFs are identified using a fuzzy Delphi method (FDM). The relationship among these CRFs has been analyzed using ISM, and the driving and the dependence power of those CRFs are analyzed. Results indicate that both “government policies (laws and regulations)” and “the impact of rapid change in technology” are independent or key factors that affect the sustainability of the telecommunications supply chain. In addition, results provide significant managerial implications, including enhanced sustainability, and the government should build justice, fairness, open laws, certainties, and regulations to prevent risk in the telecommunications industry supply chain; service providers should monitor the rapidly evolving technologies and focus on technical learning and organizational capacity development to overcome the impact of technological changes. The contribution of this study is using a novel approach to establish a hierarchical structural model for an effective understanding of CRFs relationships and to explore decisive risk factors that can help telecom service providers to better plan and design effective improvement strategies to enhance sustainability supply chain management.

To stand out in the hot spring tourism industry, customer satisfaction has become the crucial issue for competitiveness. A company cannot implement several customer satisfaction improvement practices altogether with limited resources. Researchers advocate that companies should evaluate the relationships among success factors and explore determinants for their improvement implementation. However, such a relationship evaluation has not yet been adequately performed. This paper intends to explore the determinants for improving hot spring customer satisfaction. Adopting grounded theory (GT) and using data collected from websites, Ctrip and Qunar, the first 12 key factors for customer satisfaction were identified. Then, their interrelationships were assessed by 15 experts, and interpretive structural modeling (ISM) was employed to analyze the interrelationships and the driving and dependence power among key factors. The results show that “Environment Quality”, “Special Resource”, “Convenience”, “Food”, Service Quality”, and “Facilities” were the decisive factors affecting customer satisfaction. The findings offer important implications for hot spring management and practice. The contribution of this study is using a novel approach to establish a hierarchical structural model for comprehensive understanding of factor relationships that influence hot spring tourists’ satisfaction and to explore decisive factors which can help hot spring practitioners to better plan and design effective improvement strategies to attract potential new consumers and retain their current consumers, especially with limited resources.