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By incorporating the resource-based view with the dynamic capability view, this study aims to examine the link between corporate political networking strategy and firm performance in transition economies by focusing on the mediating role of corporate entrepreneurship and the moderating role of dysfunctional competition.

A large-scale questionnaire survey was conducted among 1,300 senior managers from 650 enterprises in China, and valid survey data were obtained from 401 enterprises.

Empirical results demonstrate that political networking strategy is positively related to firm performance and that this relationship is fully mediated by corporate entrepreneurship. Moderated path analysis indicates that dysfunctional competition strengthens the direct effect of political networking strategy on corporate entrepreneurship and its indirect effect on firm performance via corporate entrepreneurship.

This research is among the first to examine the mediating mechanism underlying the relationship between political networking strategy and firm performance in the context of transition economies. In addition, existing research has seldom discussed the effects on corporate entrepreneurship of external resource acquisition from government sources. This research fills this important gap and identifies the condition under which political networking benefits corporate entrepreneurship.

The purpose of this study is to introduce strategic flexibility as an important dynamic capability into the field of strategic human resource management (SHRM) and explore its mediating role between network-building HR practices for top management team (TMT) and firm performance. Moreover, based on the context of transition economy in China, the authors examine environmental uncertainty as a moderator in these relationships and empirically test the questions above.

The authors have conducted questionnaire surveys on 780 top managers in 390 companies mainly located in Beijing, Tianjin, Shanghai, Jiangsu and Zhejiang and finally received 241 valid samples.

The results show that network-building HR practices have positive effects on firm performance and strategic flexibility plays a fully mediating role between them. In addition, environmental uncertainty moderates the relationship between network-building HR practices for TMT and strategic flexibility, while it has no moderating effect in the relationship between strategic flexibility and firm performance.

These conclusions have important implications for the development and application of SHRM in dynamic environments. Theoretically, the authors enrich the functions of network-building HR practices for TMT and provide the evidence to advocate the development of the innovative HR practices in China. In terms of the practical implications of the study, it is argued that network-building HR practices for TMT and strategic flexibility can help firms to deal with uncertainty and achieve high performance, which provides constructive guidance in the development of enterprises in the China's transition economy.

Professor independent directors have been the subject of academic debate as to whether they can improve corporate innovation performance. Accordingly, this paper aims to investigate the relationship between professor independent directors, the marketization process and corporate innovation performance in China.

Using a sample of Chinese A-share listed companies from 2014 to 2017, this study examines how professor independent directors and the (low and high) marketization process affect corporate innovation performance.

The empirical analysis of this yields the following main results. First, enterprises with a higher proportion of professor independent directors outperform those with a low proportion of professor independent directors in terms of corporate innovation. Second, the study of introducing the marketization process finds that there is no “market failure”. Third, while professor independent directors have a significant association with innovation performance in the high-marketization group, this association is negligible in the low-marketization group, indicating that there is no “substitution effect”.

This research provides empirical evidence to support the hiring of professors with relevant backgrounds as independent directors who can contribute meaningfully to corporate governance and innovation while also fostering industrial transformation. This study also identifies that the role of professor independent directors in facilitating corporate innovation is more effective in regions with a high degree of marketization than in regions with a low degree of marketization, implying that increasing marketization benefits the role of professor independent directors in facilitating corporate innovation.

Environmental, social and governance (ESG) factors have become increasingly important in investment decisions, leading to a surge in ESG investing and the rise of sustainable investment assets. Nevertheless, challenges in ESG disclosure, such as quantifying unstructured data, lack of guidelines and comparability, rampantly exist. ESG rating agencies play a crucial role in assessing corporate ESG performance, but concerns over their credibility and reliability persist. To address these issues, researchers are increasingly utilizing machine learning (ML) tools to enhance ESG reporting and evaluation. By leveraging ML, accounting practitioners and researchers gain deeper insights into the relationship between ESG practices and financial performance, offering a more data-driven understanding of ESG impacts on business communities.

The authors review the current research on ESG disclosure and ESG performance disagreement, followed by the review of current ESG research with ML tools in three areas: connecting ML with ESG disclosures, integrating ML with ESG rating disagreement and employing ML with ESG in other settings. By comparing different research's ML applications in ESG research, the authors conclude the positive and negative sides of those research studies.

The practice of ESG reporting and assurance is on the rise, but still in its technical infancy. ML methods offer advantages over traditional approaches in accounting, efficiently handling large, unstructured data and capturing complex patterns, contributing to their superiority. ML methods excel in prediction accuracy, making them ideal for tasks like fraud detection and financial forecasting. Their adaptability and feature interaction capabilities make them well-suited for addressing diverse and evolving accounting problems, surpassing traditional methods in accuracy and insight.

The authors broadly review the accounting research with the ML method in ESG-related issues. By emphasizing the advantages of ML compared to traditional methods, the authors offer suggestions for future research in ML applications in ESG-related fields.

Collaboration in agricultural value chains (AVCs) has the potential to increase smallholders’ participation in international value chains and increase their benefits from participation. This scoping review explores existing collaboration models among stakeholders of AVCs in developing countries, examines enablers and constraints of collaboration and identifies policy gaps.

We systematically searched three databases, CAB Abstracts, Econlit (EBSCO) and Agricola, for studies published between 2005 and 2023 and included 59 relevant studies on AVC collaboration.

The primary motivations for collaboration are to enhance market access and improve product quality. Key outcomes of collaboration include improvements in farmers’ welfare, market participation and increased production; only a few studies consider improved risk management as an important outcome. Robust support from government and non-governmental entities is a primary enabler of collaboration. Conversely, conflicts of interest among stakeholders and resource limitations constrain collaboration possibilities. Collaboration involving high-value crops prioritizes income increases, whereas collaboration involving staple crops focuses on improving household food security.

This study may have publication bias as unsuccessful instances of collaboration are less likely to be published.

This study is unique in highlighting collaboration models’ characteristics and identifying AVC policy and programmatic areas where private firms, farmers’ groups, local governments and donor agencies can contribute.