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This study tests the signaling and tunneling models of dividend policies by examining the relationship between the ownership structure and the dividend payout in a setting where strong institutional governance and weak firm-level governance coexist.

Chinese American Depository Receipts (ADRs) listed in the US offer an excellent opportunity to study dividend policy where strong institutional governance and weak firm-level governance coexist. Using a sample of 161 Chinese ADRs from 2004 to 2018, this study examines the relationship between the firm's ownership structure and cash dividend policy.

This study shows that high levels of controlling shareholder ownership and high levels of state ownership are associated with high dividend payouts. A high level of controlling shareholder ownership has a negative effect on its firm value. Dividend payments in those firms mitigate the negative effect, consistent with the signaling (substitution) model. A high level of state ownership is beneficial to its firm value. However, high dividend payment in those firms decreases the benefit, supporting the tunneling model.

This study covers 161 Chinese ADRs listed in the US with a total market capitalization of over $2 trillion and reveals that dividend tunneling could occur in Chinese government controlled ADRs. Findings in this study would offer valuable insights for US investors and regulators.

This paper extends the tunneling hypothesis to the topic of dividend policy in a setting where strong institutional governance and weak firm-level governance coexist. This study shows that tunneling through dividends can happen among Chinese government controlled ADRs in the US. It also complements the literature by extending the examination of the dividend tunneling model from a relatively small universe of master limited partnership (Atanssov and Mandell, 2018) to a larger universe of Chinese ADRs listed in the US with a total market capitalization over $2 trillion US dollars.

In the ever-evolving digital landscape, this study aims to explore which specific personality traits contribute to the innovativeness of startups, with a particular emphasis on understanding how technology adoption mediates this relationship. By doing so, the authors strive to unveil the nuanced dynamics of personality, technology adoption and startup innovativeness in the digital era.

The authors conduct a quantitative empirical analysis using a sample of 1,314 German startups. This study utilizes a mediation analysis to examine the effects of personality traits on the innovativeness of startups, taking technology adoption as a mediator into account.

The empirical results show certain personality traits have direct effects on innovativeness. Also, the results show that technology adoption is a driver of startup innovativeness. In addition, these traits are (partially) mediated by technology adoption.

The results shed new light on the interplay of entrepreneurs' personality and technology adoption in relation to startup innovativeness and therefore underline the importance of technology in this triangular relationship. The authors employ secondary data from startups in Germany, which complicates generalization of the results to other geographical and cultural contexts.

This study contributes to the scientific debate on the role of personality traits in entrepreneurship by providing empirical evidence on the mediating effect of technology adoption in the relationship between personality traits and startup innovativeness. The findings offer valuable insights for researchers, entrepreneurs and policymakers interested in understanding and promoting innovativeness in the context of startups.

This paper examines the relationship between transport connectivity and regional economic development in China. It develops measurements appropriate for transport connectivity based on a set of evaluation models. This model is used to analyze the logistic connectivity of China’s 31 provinces by focusing on 11 variables, including some new factors (Density of road network, Density of railway network, Number of Internet Users) not used in previous studies, over the 13-year period from 2002 to 2014. Using panel data regression analysis, the empirical results show a statistically significant and positive impact of transport connectivity (factors like Density of road network, Density of railway network and Number of Internet Users) on economic development in China. In particular, the Number of internet users is a key factor reflecting information connectivity in all the variables. Comparative analysis regarding economic development is conducted to benchmark between coastal provinces and interior provinces. Like most previous research, this study yields the same finding of higher impact of transport connectivity on economic development in eastern provinces than in western provinces. This study suggests that decentralized decision-making will be significantly more efficient for analyzing regional infrastructure development. It also shows that the influence of transport connectivity on economic development is dependent on a certain developmental stage. This suggests that an economic region should adopt different development strategies for transport connectivity during different stages of development.

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.

This research examines the impact of the National Rural E-commerce Comprehensive Demonstration Project (NRECDP) on poverty reduction and income growth in rural China.

The study develops a theoretical framework, which considers the role of geographical, technological, institutional and cultural factors for the e-commerce poverty alleviation (e-CPA) model. Empirically, this study applies the difference-in-differences (DID) model and the event study approach to evaluate the effectiveness of NRECDP on the basis of large-scale county-level and household-level panel data spanning 2010 to 2020.

The study found that the NRECDP, as a government-led, information and communication technology (ICT)-enabled, market-based program, has led to a significant increase in per capita output of primary industry employees, as well as in the disposable income of rural residents, especially those in national-level poverty-stricken (NP) counties. The interventions of the NRECDP achieved these positive outcomes through transportation and Internet infrastructure improvement, ICT adoption and human capital accumulation in impoverished towns and villages in remote rural areas. These effects are larger in the eastern region of China, followed by the central region, whereas the weakest effects were found in the western region. However, we found little evidence of the NRECDP increasing household developmental expenditure.

The study findings have important practical and policy implications for rural e-commerce development and self-sustained poverty alleviation solutions. The research revealed the significance of government NRECDP interventions for increasing rural income, reducing living costs, and empowering the rural population in its multiple social roles, namely, as consumers, producers, employees and microentrepreneurs. The local cultural context may also play a role in ICT adoption and entrepreneurship cultivation with a downstream effect on the effectiveness of e-CPA practices. Policymakers would need to ensure a supportive entrepreneur-friendly environment for rural e-commerce development and continue implementing progressive policies for poverty alleviation.

This study explores poverty alleviation issues in China by developing for the first time a multi-faceted framework that is subsequently tested by both county-level and household-level large-scale observations. Also, it is the first study to provide nationwide empirical evidence on the effectiveness of e-CPA in narrowing down the spatial and digital divides in China. In addition to the impact of geography, technology and governmental support, this study also sheds light on the role of culture in the adoption and diffusion of digital technologies and as a source of local entrepreneurial opportunities.

The increasing urgency to address climate change in construction has made green construction (GC) and sustainability critical topics for academia and industry professionals. However, the volume of literature in this field has made it impractical to rely solely on traditional systematic evidence mapping methodologies.

This study employs machine learning (ML) techniques to analyze the extensive evidence-base on GC. Using both supervised and unsupervised ML, 5,462 relevant papers were filtered from 10,739 studies published from 2010 to 2022, retrieved from the Scopus and Web of Science databases.

Key themes in GC encompass green building materials, construction techniques, assessment methodologies and management practices. GC assessment and techniques were prominent, while management requires more research. The results from prevalence of topics and heatmaps revealed important patterns and interconnections, emphasizing the prominent role of materials as major contributors to the construction sector. Consistency of the results with VOSviewer analysis further validated the findings, demonstrating the robustness of the review approach.

Unlike other reviews focusing only on specific aspects of GC, use of ML techniques to review a large pool of literature provided a holistic understanding of the research landscape. It sets a precedent by demonstrating the effectiveness of ML techniques in addressing the challenge of analyzing a large body of literature. By showcasing the connections between various facets of GC and identifying research gaps, this research aids in guiding future initiatives in the field.

Violence against the police represents an ongoing and serious problem in the USA. In 2014, over 48,000 law enforcement officers assaulted while on duty. Although over one in four of these resulted in injury, little is known about the conditions under which injury is likely to occur. The purpose of this paper is to provide an assessment of the individual and situational factors that predict injurious assaults against law enforcement.

Using logistic regression, the current study analyzes data from the 2012 National Incident-Based Reporting System (NIBRS) on all assaults against the police (n=8,987) in order to understand, within a routine activities theoretical framework, how individual-level characteristics (i.e. officer and offender characteristics) and situational influences (i.e. assignment type, activity type, and location) predict the likelihood that an assault will result in injury.

Overall, findings suggest support for a routine activities theory of violence against the police. Initiating an arrest, one-officer vehicle type, and incidents occurring on highways/roads were all more likely to result in injurious assaults against the police. Other predictors of injury include officer and offender demographics as well as the time the incident took place.

This research was unable to control for some factors that may influence the likelihood of injury such as wearing body armor. Additionally, NIBRS data are not nationally representative, which limits the generalizability of the findings.

This is one of the first papers to use national data to examine the individual and situational factors that predict injurious assaults against law enforcement.

The PMI Risk Framework (PRF) is introduced as a guide to classifying and identifying risks which can be the source of post-merger integration (PMI) failure — commonly referred to as “culture clash.” To provide managers with actionably insight, PRF dissects PMI risk into specific relationship-oriented phenomena, critical to outcomes and which should be addressed during PMI. This framework is a conceptual and theory-grounded integration of numerous perspectives, such as organizational psychology, group dynamics, social networks, transformational change, and nonlinear dynamics. These concepts are unified and can be acted upon by integration managers. Literary resources for further exploration into the underlying aspects of the framework are provided. The PRF places emphasis on critical facets of PMI, particularly those which are relational in nature, pose an exceptionally high degree of risk, and are recurrent sources of PMI failure. The chapter delves into relationship-oriented points of failure that managers face when overseeing PMI by introducing a relationship-based, PMI risk framework. Managers are often not fully cognizant of these risks, thus fail to manage them judiciously. These risks do not naturally abide by common scholarly classifications and cross disciplinary boundaries; they do not go unrecognized by scholars, but until the introduction of PRF the risks have not been assimilated into a unifying framework. This chapter presents a model of PMI risk by differentiating and specifying numerous types of underlying human-relationship-oriented risks, rather than considering PMI cultural conflict as a monolithic construct.