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Time headway (THW) is an essential parameter in traffic safety and is used as a typical control variable by many vehicle control algorithms, especially in safety-critical ADAS and automated driving systems. However, due to the randomness of human drivers, THW cannot be accurately represented, affecting scholars’ more profound research.

In this work, two data sets are used as the experimental data to calculate the goodness-of-fit of 18 commonly used distribution models of THW to select the best distribution model. Subsequently, the characteristic parameters of traffic flow are extracted from the data set, and three variables with higher importance are extracted using the random forest model. Combining the best distribution model parameters of the data set, this study obtained a distribution model with adaptive parameters, and its performance and applicability are verified.

In this work, two data sets are used as the experimental data to calculate the goodness-of-fit of 18 commonly used distribution models of THW to select the best distribution model. Subsequently, the characteristic parameters of traffic flow are extracted from the data set, and three variables with higher importance are extracted using the random forest model. Combining the best distribution model parameters of the data set, this study obtained a distribution model with adaptive parameters, and its performance and applicability are verified.

The results show that the proposed model has a 62.7% performance improvement over the distribution model with fixed parameters. Moreover, the parameter function of the distribution model can be regarded as a quantitative analysis of the degree of influence of the traffic flow state on THW.

The purpose of this paper is to synthesize the extant literature on green innovation (GI), and more importantly, to provide future directions for GI research from the innovation ecosystem (IE) perspective.

A systematic literature review is conducted to summarize the status of current GI research, followed by content analysis to identify connectivity and crossovers between key concepts in the bodies of GI and IE literature. Then, the authors propose a green innovation ecosystem (GIE) framework and offer recommendations for future research on GI.

It is evident that the bodies of GI and IE literature overlap on the roles of external actors, and yet, there is scant research investigating GI activities from the IE perspective. Moreover, there are multiple directions worthy of future research applying the proposed GIE framework.

Though the concept of ecosystem has become pervasive in innovation management research, this study is one of the first works to introduce IE concepts and propositions in the GI research context. This paper provides new knowledge on GIEs and sets the basis for further investigation.

This paper aims to provide a framework of the supervised hyperspectral classification, to study the traditional flowchart of hyperspectral image (HIS) analysis and processing. HSI technology has been proposed for many years, and the applications of this technology were promoted by technical advancements.

First, the properties and current situation of hyperspectral technology are summarized. Then, this paper introduces a series of common classification approaches. In addition, a comparison of different classification approaches on real hyperspectral data is conducted. Finally, this survey presents a discussion on the classification results and points out the classification development tendency.

The core of this survey is to review of the state of the art of the classification for hyperspectral images, to study the performance and efficiency of certain implementation measures and to point out the challenges still exist.

The study categorized the supervised classification for hyperspectral images, demonstrated the comparisons among these methods and pointed out the challenges that still exist.

This study aims to examine the effects of job crafting on the work engagement of tour leaders mediated by person-job fit and the meaningfulness of work.

Derived from a sample of 331 tour leaders in China, the data for this research were analyzed using partial least squares structural equation modeling.

The findings revealed that job crafting increased tour leaders’ person-job fit and meaningfulness of work, which stimulated their work engagement. Tour leaders’ person-job fit also increased their work engagement and perceptions of the meaningfulness of work. Enhancing the work meaningfulness of tour leaders can significantly increase their work engagement. Person-job fit and meaningfulness of work had a significant mediating effect between job crafting and tour leaders’ work engagement.

Managers need to provide external conditions for tour leaders’ job crafting by expanding structural and social job resources and by creating more stimulating job environments. Managers can enhance tour leaders’ work engagement by shaping their work meaning and person-job fit.

First, this study empirically tested the effects of job crafting on tour leaders’ work engagement, thus directly addressed the lack of academic attention paid to this topic. Second, this study examines the mediating role of person-job fit and meaningfulness of work, with regard to tour leaders’ job crafting and work engagement, based on an integrative concept model.

Important developments of China's securities markets within the last two years, namely, the Share Reform, the warrant market, the innovative listed open-end funds (and exchange-traded funds), corporate bonds with detachable warrants, exchange-traded asset-backed securities, are described. The discussion focuses on unique, innovative features of these products, as compared to their counterparts available in more mature markets (when applicable), and points to possible future research themes. The proposed rules with regard to stock index futures and credit trading are also discussed.

As live streaming becomes a widely used online sales mode, previously content-centred anchors are attempting to switch to e-commerce live streaming. The purpose of this research was to explore the mechanisms that prompt consumers to stay or leave after content anchors transfer to live e-commerce broadcasts. In addition, we explored the factors affecting consumption from the perspectives of anchors, consumers and the external environment.

We distributed questionnaires to a group of fans who had experienced the transition of content anchors to live streaming and received back 375 valid questionnaires. Using psychological contract theory, we constructed a theoretical model for the scenario in which content anchors transition to live e-commerce broadcasting and analysed the data using partial least squares structural equation modelling (PLS-SEM).

The results show that circle culture, mainstream culture, initial trust and live streaming content all positively influenced consumers’ attitudes, whilst consumers’ past shopping experiences negatively influenced consumers’ attitudes. The personal charm of the content anchors did not have a significant effect on consumers’ attitudes. Additionally, we found that only anchors with a significant circle culture and good trust levels amongst fans were able to transition to live e-commerce streaming successfully.

This study extends the application of psychological contract theory to the field of e-commerce and describes the transformation of different types of psychological contracts. The paper’s conclusions provide a reference for decision-making and the implementation of transformation by content-based anchors to live streaming, helping them to coordinate their relationships with fans more effectively.

As an effective tool to promote rational resource allocation and facilitate the development of green management practices such as enterprise digital innovation, the green credit policy has recently gained extensive attention. The purpose of this paper is to analyze the relationship between green credit policies and the digital innovation of enterprises, and to further explore the mechanism of action between them and their boundary conditions.

Based on micro-level data on Chinese firms from 2007 to 2019, this paper constructs a difference-in-differences (DID) model to investigate the impact and intrinsic mechanisms of green credit policies on firms' digital innovation and its boundary conditions, with the help of a quasi-natural experiment, i.e. the Green Credit Guidelines.

Green credit policies inhibit digital innovation and fail to compensate for innovation. The analysis of the mechanism shows that the implementation of green credit policies has a negative impact on digital innovation by increasing the financing constraints faced by firms, and has also a crowding-out effect on R&D investment, resulting in a disincentive to digital innovation. Further analysis reveals that the negative impact of green credit policies on digital innovation is more pronounced in state-owned enterprises, enterprises without financially experienced executives, and in the eastern regions of China.

This study provides empirical evidence to understand the effectiveness and mechanism of influence of green credit policies on enterprise digital innovation, providing also a basis to further improve green credit policies.

This study aims to provide a literature review and bibliometric analysis of sustainable supply chain management using big data. We reviewed the literature on sustainable supply chain management under big data from 2012 to 2019 and extracted 777 articles.

We conducted quantitative analysis and data network visualization of the chosen literature, including authors, journals, countries, research institutions and citations.

We discovered that the development of this interdisciplinary field has gained increasing popularity among researchers around the world, such as China and the US publishing the most articles and Western states having more cooperation, which indicates this research topic is growing in significance globally.

Scientific and technological revolutions such as big data have been incorporated in various industries. Modern supply chain management has also been combined with the advances in data science to achieve sustainability goals. No studies have reviewed the sustainable supply chain management based on big data. This study fills this gap.

This chapter explores the relationship between athletes and sports law within the anti-doping narrative. The World Anti-Doping Code is the most important reference to understand this relationship. Athletes are constantly pressured to meet standards beyond reasonable expectations. This chapter explores the anti-doping narrative from the athletes' perspective, mapping out the inherent legal hurdles impeding delivery of equitable outcomes for the athletes. Such hurdles are the result of lack of bargaining power by the athletes. This chapter critically evaluates the existing literature on the anti-doping narrative and identifies the gaps in the structures affecting the athletes, Sports Governing Bodies and the World Anti-Doping Agency (WADA). This chapter then focuses on the usurpation of athlete's rights through the instrumentality of the WADA Code that appears to predominantly promote and protect the interests of the governing class against those it governs. It is one of the first to analyze the existing anti-doping narrative and its impact on athlete's right within the 2021 WADA Code, which has not introduced any fundamental changes to the existing anti-doping narrative. The chapter argues for a more equitable treatment of the athletes while enforcing the 2021 Code, and for revising the existing anti-doping measures vis-à-vis athletes and opens possible areas of future research.

While the Olympic Games are always under the spotlight, the Paralympic Games are somehow ignored. This paper aims to invite the general public to think about the para-athletes and the differential treatments they received.

Among the participating countries, many of them were unable to win a single Olympic or Paralympic medal. When the dependent variable is left-censored, ordinary least squares regression is asymptotically biased downwards. In the literature, researchers typically employ the maximum likelihood Tobit model to take care of the censoring problem. However, some researchers argue that the Hurdle model has an advantage over the Tobit model in identifying the determinants of winning Olympic medals. Following their wisdom, this paper employs both the Tobit and Hurdle models in analysis.

The empirical evidence gathered in this paper suggests that population size, host status and average years of schooling are the big three socio-economic determinants when it comes to winning medals at the Paralympic Games and Olympic Games. The findings support the hypothesis that sports talent is randomly distributed and a large country has a higher chance to have talented athletes or para-athletes winning the Olympic medals. The strong host advantage also showed up in the following Paralympics but was not so strong at the next Olympics.

This paper not only examines the relationship between various social, economic and political factors in determining the success of a nation in the Paralympic Games but also attempts to identify possible non-traditional determinants.