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The study aims to examine the causes of the divergent patterns of contemporary transnational engagement with China among new Chinese immigrants and the effect of transnational entrepreneurship on migrants’ integration into their host societies.

It is based on a multi-sited ethnographic study that contains interviews, participant observations, and analysis of relevant event coverage and commentaries by the media, which were conducted between 2008 and 2013 in Singapore, the United States, and China.

The study finds that different migration histories, structural circumstances in both sending and receiving societies, and locations in the transnational social field give rise to divergent patterns of economic transnationalism, and that the rise of China has opened up new avenues for transnational entrepreneurship, which has not only benefited hometown development in China but also created economic opportunities for Chinese immigrants, leading to desirable mobility outcomes. In particular, transnational entrepreneurship has promoted deeper localization rather than deterritorialization and contributed to strengthening the economic base of the existing ethnic enclave, which in turn offers an effective alternative path for migrants’ integration in their host societies.

The study is exploratory in nature. As with all ethnographic studies, its generalizability is limited.

The study suggests that, when transnational entrepreneurship is linked to the existing ethnic social structure in which a particular identity is formed, the effect on the group becomes highly significant. The comparative approach of the study can help unveil different dynamics, processes, and consequences of transnationalism and complex factors behind variations on diasporic development and immigrant integration.

Looking at entrepreneurship beyond nation-state boundaries and beyond the economic gains of individual migrants.

Creativity and innovation have been buzzwords of managerial discourse over the last few decades as they contribute to the long-term survival and competitiveness of firms. Given the non-linear, causally ambiguous, and intangible nature of all innovation-related phenomena, management scholars have been trying to uncover factors that contribute to creativity and innovation from multiple lenses ranging from organizational behavior at the micro-level to strategic management at the macro-level. Along with important and insightful developments in these research streams that evolved independently from one another, human resource management (HRM) research – especially from a strategic perspective – has only recently started to contribute to a better understanding of both creativity and innovation. The goal of this chapter is to review the contributions of strategic HRM research to an improved understanding of creativity at the individual-level and innovation at the firm-level. In organizing this review, the authors rely on the open innovation funnel as a metaphor to review research on both HRM practices and HRM systems that contribute to creativity and innovation. In the last section, the authors focus on more recent developments in HRM research that focus on ambidexterity – as a way for HRM to simultaneously facilitate exploration and exploitation. This chapter concludes with a discussion of future research directions.

Trauma and adverse childhood events are found in the pre‐immigration histories of a cohort of four Chinese Canadian pathological gamblers. The nature of their traumatic experiences, consisting of loss and abandonment, neglect and deprivation, physical and emotional abuse, socioeconomic and political oppression, is elucidated and described. The impact of pre‐immigration trauma and its relationship to the development of pathological gambling post‐immigration are discussed. Upon further corroboration of the existence of pre‐immigration trauma among Chinese and Asian immigrants in future studies, training of counsellors to incorporate an in‐depth pre‐immigration history in the assessment and treatment protocol of immigrants manifesting pathological gambling is recommended.

The purpose of this study is to empirically examine the relationship between executive compensation linked to corporate social responsibility (CSR) and firm risk. It also explores the moderating role of CSR-linked compensation on the relationship between risk-taking incentives provided in executive compensation and firm risk.

This study uses Ordinary Least Squares (OLS) and firm-fixed effects regressions to estimate the association between CSR-linked compensation and firm risk. Furthermore, it employs instrumental variable, propensity score matching and first-order difference approaches to address concerns about endogeneity and sample selection.

Benchmark results show that CSR-linked compensation reduces both total and idiosyncratic measures of risk. Further results indicate that CSR-linked compensation reduces firm risk only when risk is above the optimal level and has no significant effect when risk is below the optimal level. Additionally, tests show that CSR-linked compensation also mitigates the positive effect of Vega of executive compensation on risk and this mitigation effect is significant only when risk is above the optimal level.

The empirical results of this study show that boards can use CSR-linked compensation not only to induce higher social performance but also as a risk management tool to manage risk, especially when risk is above value increasing optimal levels. Furthermore, boards can use CSR-linked compensation to mitigate excessive risk-taking induced by option compensation.

This study contributes to the emerging literature on CSR-linked compensation and firm risk. To our knowledge, this is the first study that documents the direct risk-reducing effect of CSR-linked compensation and its mitigating effect on the relation between Vega of executive compensation and firm risk.

The emergence and rapid expansion of global value chains (GVCs) have profoundly changed and reshaped the global trade regime. Although many determinants of GVC participation of enterprises have been discussed extensively in extant literature, the important influence of local institutional profile on GVC participation is often neglected. The purpose of this paper is to investigate the influence of local institutional profile on GVC participation.

Taking the World Bank Enterprise Survey as the empirical sample, it is used an econometric method (propensity score matching technique) to test the relationship between local institutional profile and GVC participation.

Local institutional quality is positively related to GVC participation. Moreover, GVC participants display better innovation performance than non-participants. Innovation benefit from GVC participation is contingent upon the abilities of the participants, namely, absorptive capacity and research and development collaboration experience. GVC participants who only either export or import is compared with those who export and import; the findings show that the latter benefits more than the former.

This study offers researchers and practitioners a detailed view of local institutional profile and GVC participation.

Most previous research assumes that the outward foreign direct investment (OFDI) decisions of multinational corporations (MNCs) are made independently of the actions or characteristics of their peers. Therefore, the important influence of peer effects on the OFDI strategy is often neglected. The purpose of this paper is to identify two broad categories of peer effects, i.e. learning-based and profit-driven imitations and examine the important influence of peer effects on MNCs’ internationalization strategy.

Using Chinese manufacturing firms as the empirical sample, the authors employ an econometric method (logit regression) to test the relationship between peer effects and an internationalization strategy.

Learning-based and profit-driven imitations are positively associated with a focal MNC’s OFDI decision. Policy uncertainty also positively moderates the relationship between peer effects and the OFDI strategy. Moreover, both peer effects are amplified when a firm is equipped with a dense export network.

The study offers researchers and practitioners a detailed view of interorganizational imitation behavior in terms of an internationalization strategy.

It is well recognized that the construction industry is characterised by inefficient and ineffective service delivery due to various causative factors. Thus this study aims to examine the influential factors affecting public construction project performance in Ethiopia to improve the industry's service delivery.

From the extensive literature reviewed, 58 potential factors affecting construction project performance have been compiled. Based on the evidence accumulated, the conceptual model of this paper has been developed. By using survey questionnaires, valuable data were collected from the construction industry professionals in Ethiopia; analysed and interpreted with the use of both SPSS and AMOS software.

It is concluded that failure factors related to the “performance” of the contractor, the “capability” of the owner, the “project design-procurement process,” and project contract management can significantly contribute to the poor performance of public construction projects in Ethiopia. Ten key factors include inadequate contractor capacity, weak project site management and supervision, weak project management skills and capabilities of the owner, additional work orders, delayed payment, lack of comprehensive project plans between parties and incomplete project design, rising material prices, ineffective project schedules, and cost management, rising market prices and devaluation of the currency.

The scope of this study confined to public projects in Ethiopia. It suggests that further research needs to consider public and private construction from a comprehensive perspective in the developing countries.

It provides practitioners with information and guidance on the factors that affect the performance of construction projects.

It provides inclusive evidence related to many factors that affect the performance of public construction projects.

The number of construction dispute cases has maintained a high growth trend in recent years. The effective exploration and management of construction contract risk can directly promote the overall performance of the project life cycle. The miss of clauses may result in a failure to match with standard contracts. If the contract, modified by the owner, omits key clauses, potential disputes may lead to contractors paying substantial compensation. Therefore, the identification of construction project contract missing clauses has heavily relied on the manual review technique, which is inefficient and highly restricted by personnel experience. The existing intelligent means only work for the contract query and storage. It is urgent to raise the level of intelligence for contract clause management. Therefore, this paper aims to propose an intelligent method to detect construction project contract missing clauses based on Natural Language Processing (NLP) and deep learning technology.

A complete classification scheme of contract clauses is designed based on NLP. First, construction contract texts are pre-processed and converted from unstructured natural language into structured digital vector form. Following the initial categorization, a multi-label classification of long text construction contract clauses is designed to preliminary identify whether the clause labels are missing. After the multi-label clause missing detection, the authors implement a clause similarity algorithm by creatively integrating the image detection thought, MatchPyramid model, with BERT to identify missing substantial content in the contract clauses.

1,322 construction project contracts were tested. Results showed that the accuracy of multi-label classification could reach 93%, the accuracy of similarity matching can reach 83%, and the recall rate and F1 mean of both can reach more than 0.7. The experimental results verify the feasibility of intelligently detecting contract risk through the NLP-based method to some extent.

NLP is adept at recognizing textual content and has shown promising results in some contract processing applications. However, the mostly used approaches of its utilization for risk detection in construction contract clauses predominantly are rule-based, which encounter challenges when handling intricate and lengthy engineering contracts. This paper introduces an NLP technique based on deep learning which reduces manual intervention and can autonomously identify and tag types of contractual deficiencies, aligning with the evolving complexities anticipated in future construction contracts. Moreover, this method achieves the recognition of extended contract clause texts. Ultimately, this approach boasts versatility; users simply need to adjust parameters such as segmentation based on language categories to detect omissions in contract clauses of diverse languages.

In the process of cold rolled strip, there is tight coupling between flatness control and gauge control. The variation of the roll gap caused by the change of bending force will lead to the change of rolling force. Furthermore, it can cause a deep impact on the control accuracy of strip exit thickness and exit crown. The purpose of this paper is to improve the accuracy of the bending force preset value for cold rolled strip.

In this paper, the bending force preset control strategy with considering of rolling force was proposed for the first time and the preset objective function of bending force was established on the basis of the two-objective optimization of bending force and rolling force. Meanwhile, the multi-objective intelligent algorithm – INSGA-II – was used to solve the objective function.

The proposed bending force multi-objective preset model has been tested in a 1,450 mm tandem cold rolling line. The analyzed results of field data show that the deviations of strip exit thickness and exit crown are reduced effectively by using the improved model, and at the same time, more reasonable bending force preset values are obtained, which can enhance the accuracy of flatness preset control.

A preset model of bending force with considering flatness and gauge is proposed in this paper and the multi-objective function of bending force preset is established on the basis of the two-objective optimization of bending force and rolling force. The value lies in proposing a new decoupling method of rolling force and bending force.

Two types of institutional constraints, namely, institutional voids and policy uncertainty, have been recognised and elaborated, including their influence on new venture performance. However, not enough attention has been paid to the multidimensional attribute of institutional transformation. By hinting at a relatively underexplored third type of institutional constraints, i.e. institutional fragility, this paper aims to build a comprehensive framework of institutional constraints to analyse how innovative start-up performance is influenced by institutional constraints.

Using Chinese manufacturing firms as the empirical sample, the authors use an econometric method to test the relationship between institutional constraints and the performance of innovative start-ups.

On the basis of a uniquely constructed database from 2005 to 2007, the authors find that institutional constraints are negatively associated with innovative start-up performance proxied by return on assets, sales growth and new product sales.

The study offers researchers and practitioners a detailed view of institutional constraints and innovative start-up performance.