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In the fabric manufacturing industry, various unfavorable factors, including machine fault and yarn breakage, can easily cause fabric defects and affect product quality, begetting huge economic losses to enterprises. Thus, automatic fabric defect detection systems have become an important development direction. Herein, the most common defects in the fabric production process, like ribbon yarn, broken yarn, cotton ball, holes, yarn shedding and stains, are detected. Current fabric defect detection systems afford low detection accuracy and a high missed detection rate for small target fabric defects. Therefore, this study proposes deep learning technology for automatically detecting fabric defects by improving the YOLOv5s target detection algorithm. The improved algorithm is termed YOLOv5s-4SCK, which can effectively detect fabric defects. This study aims to discuss the aforementioned issues.

Specifically, based on the YOLOv5s algorithm, first, the structure of YOLOv5s is modified to add a small target detection layer, fully utilize deep and shallow features and reduce the missed detection rate of small target fabric defects. Second, the integration of CARAFE upsampling enables the effective retention of feature information and maintenance of a certain computational efficiency, thereby improving the detection accuracy. Finally, the K-Means++ clustering algorithm is used to analyze the position of the center point of the prior box to better obtain the anchor box and improve the average accuracy and evaluation index of detection.

The research results show that the YOLOv5s-4SCK algorithm increases the accuracy by 4.1% and the detection speed by 2 f.s-1 compared to the original YOLOv5s algorithm, and it effectively improves the original YOLOv5s problem of high missed detection rate of small targets.

The YOLOv5s-4SCK proposed in this paper can effectively reduce the missed detection rate of fabric defects, improve the detection efficiency and has certain industrial value.

The proposed algorithm can quickly identify fabric defects, effectively improving the detection rate. In the future, the proposed algorithm will be applied in the actual industry.

Automatic fabric defect detection reduces the manpower of inspectors, and the proposed YOLOv5s-4SCK algorithm is also suitable for other recognition fields.

The proposed YOLOv5s-4SCK algorithm has been tested using real cloth to ensure its accuracy, and its performance is better than the original YOLOv5s algorithm.

There is a growing literature in nonparametric econometrics in the recent two decades. Given the space limitation, it is impossible to survey all the important recent developments in nonparametric econometrics. Therefore, we choose to limit our focus on the following areas. In Section 2, we review the recent developments of nonparametric estimation and testing of regression functions with mixed discrete and continuous covariates. We discuss nonparametric estimation and testing of econometric models for nonstationary data in Section 3. Section 4 is devoted to surveying the literature of nonparametric instrumental variable (IV) models. We review nonparametric estimation of quantile regression models in Section 5. In Sections 2–5, we also point out some open research problems, which might be useful for graduate students to review the important research papers in this field and to search for their own research interests, particularly dissertation topics for doctoral students. Finally, in Section 6 we highlight some important research areas that are not covered in this paper due to space limitation. We plan to write a separate survey paper to discuss some of the omitted topics.

The purpose of this paper is to conduct an in-depth exploration of the special context and user experiences of live video streaming and to provide insights regarding an interpretation of the contextualization experiences model.

This study used netnography, online interviews and the physical travel of researchers to the field for field participation and observations. The combination of netnography and online interviews combined online and offline studies to achieve greater consistency in the data collection, analysis and other processes.

The findings of the study can be classified into a three-stage situational context approach, which is presented in the form of propositions. Finally, the insights of the contextualization experiences model are presented.

This study resulted in the development of a substantive theory that provides insight into interpreting the contextualization experiences model. The theory was developed based on raw data to enable it to explain the phenomena in the context of similar instances of live video streaming.

Three types of industrial buyer-seller relational process models are available: joining theory, stage theory, and state theory. However, historically, these models have developed based on the knowledge and cultural context of the Western world. Several researchers note that national culture may have an impact on international industrial buyer-seller relationships. Including culture in the models is highly important, especially as the business environment is increasingly more global and different countries have different business cultures. The goal of this paper is to define the most suitable industrial buyer-seller relational process models for describing relationships in various contexts. The paper includes a through literature review and a single case study in order to reach this objective. A new state theory model evolved during the research. It consists of two beginning states: searching and starting; four purely middles states: constant/static, decline, growth, and troubled; and a purely end state: termination. The state of dormant/inert is both a middle state and an end state, that is, when the relational actors are not in contact does not mean that the relationship has ended, but instead, for example, new legislation may have been implemented, which requires the actors to evaluate their relationship and its future. A relationship goes through the two beginning states in the order mentioned above, but after that, any state may occur.

Building upon the framework of glocalization, the purpose of this paper is to summarize the development of National Basketball Association (NBA) in Chinese market, explore its successful and unsuccessful places, and propose strategies of glocalization for the NBA as well as other overseas sport leagues.

The current case study was organized by summarizing the developmental history of NBA in China, analyzing its current promotional practices, investigating into its marketing strategies, and extrapolating practical references for other sport leagues aiming to penetrating into the Chinese marketplace.

The current case study concluded that when facing the current challenges, the NBA needs to bring authentic American cultural commodities while adding Chinese characteristics to accommodate local fans. Meanwhile, the NBA management needs to continue seeking ways to work out and through the differences in government models and cultural contexts between China and USA. In addition, this study suggested that the research framework of glocalization would be an ever intriguing inquiry needed for other sport organizations or leagues seeking expansion to overseas markets.

A thorough case study with the NBA that has achieved huge successes in Chinese markets will provide valuable implications for sport leagues to broaden their overseas markets.

The objective of this study is to examine how the heterogeneity of the institutional environments within a single country influences International Financial Reporting Standards (IFRS) convergence and earnings quality based on a meso- and multi-level approach.

Using hierarchical linear modeling (HLM) to capture the between-group heteroskedasticity and within-cluster interdependence, this study investigates the simultaneous effect by incorporating institutional factors residing at different hierarchical levels and the interaction effects of factors within the same level on IFRS convergence and earnings quality in the largest IFRS adopter, China.

The results show that after IFRS convergence (i.e. 2007–2015), earnings quality decreases in terms of conservatism. However, the further analysis indicates that the strong institutional environment could mitigate the negative impact of IFRS on conservatism.

Consistent with the emphasis of heterogeneity within a country by Terracciano et al. (Science, 2005, 310 (5745)), this study indicates that the heterogeneity in the institutional environments and the simultaneous effect of the multilevel institutional environments within a single country cannot be ignored. This study also indicates that, equally important, research methodology plays a substantial role in investigating the outcomes of IFRS convergence. Finally, this study, based on an integrated theory, adopts a meso-paradigm linking macro- and micro-level institutions to provide comprehensive insights into IFRS convergence and conservatism.

The purpose of this paper is to conceptualise and measure the construct of fan engagement through social networking sites (SNS).

A multi-stage procedure was completed to validate the proposed fan engagement through SNS model with three first-order constructs (fan-to-fan relationships, team-to-fan relationships and fan co-creation). First, a preliminary analysis of the proposed items to capture fan engagement through SNS was conducted through expert review. Second, an assessment of item reliability and construct validity was completed using confirmatory factor analysis (CFA). Finally, CFA and subsequent structural equation model were conducted to review the psychometric properties and to test the relationships between the proposed construct with online and offline behavioural intentions.

The results indicate good psychometric properties of the constructs of fan-to-fan relationships, team-to-fan relationships and fan co-creation, and these three constructs were significantly related with the second-order construct of fan engagement through SNS. Additionally, the construct of fan engagement through SNS was significantly related to both online and offline behavioural intentions.

These findings suggest that teams should use SNS to interact with fans, to allow fans to share experiences and to involve fans in co-creation processes aimed at increasing engagement and subsequent positive behavioural intentions towards the team.

This study extends previous research by measuring fan engagement through SNS as a multidimensional construct, and testing its predictive effect on fans’ online and offline behavioural intentions. Several suggestions for future studies and strategies for increasing fan engagement can be drawn from this study.

This study aims to examine members’ perceptions of interactivity in brand communities on social networking sites in the Super Basketball League (SBL) context in Taiwan.

The proposed model was empirically evaluated using survey data collected from 332 followers of the SBL teams’ Facebook pages on their perceptions of brand communities. Structural equation modeling was used to examine the relationships in the research model.

The results suggest significant relationships between perceived interactivity and community benefits, including special treatment, social influence, sense of membership and the notion that community satisfaction has a strong and positive effect on brand loyalty. Both social influence and a sense of membership positively affect community satisfaction. However, special treatment negatively affects community satisfaction. Perceived interactivity positively affects a sense of membership and social influence, which, in turn, positively affect community satisfaction.

This study examines the effects of members’ perceived interactivity and community benefits. The results significantly advance the understanding of the antecedents of members’ loyalty to specific brands. The study offers insights into practical ways of improving community satisfaction and brand loyalty by running brand communities on social networking sites. The findings also augment the theory of brand management.

In 2017, the Chinese Super League (CSL), the first professional football division in the People’s Republic of China (PRC), became the highest-spending league in the international players’ transfer market, with a total spending of €377m. Moreover, the government of the PRC is backing the CSL with an ambitious football plan. Therefore, the purpose of this paper is to examine the governance of the CSL by questioning the organisational viability of the league.

In addition to the relevant international literature, this study is based on 14 recent scholarly articles published in Mandarin from 2013 to 2018 to reflect the national academic debate. Moreover, website research on all CSL clubs has been conducted. The institutional analysis follows the integrative change model of Cunningham (2002) complemented by agency and bureaucracy theory.

The CSL still faces substantial governance problems caused by the divergence of goal setting, organisational inefficiencies and compliance issues. The organisational change is notably constrained by internal competitive value commitments and external power dependency.

The institutional findings on the CSL provide a starting point for empirical studies. The approach contributes to the theory of sport governance processes.

The material and insights are informative for decision makers to evaluate the competitiveness of the CSL.

This paper is the first international in-depth analysis of the governance of the CSL using the body of knowledge published in Mandarin.