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This paper aims to apply the developmental state theory to examine the institutional arrangements that support the widespread adoption of the property‐led urban economic growth model and generate risks on property investment in Chinese cities.

This paper conducts institutional analysis on the behaviour of the Chinese state and examines results from major interview programmes and field investigations on six cities in China.

The Chinese state deviates from other developmental states and is polymorphous, i.e. lacking an effective central state to maintain the standard of governance and regulate the behaviour of local states. The weak central state is responsible for failures to implement national policies on land supply and housing price inflation, to nurture the development of professions like valuation, and to formulate policy on commercial property. The local states, on the other hand, intensify risks in property investment by poor plan making and implementation that create chaos in urban development and intensive competition among projects, and by poor data services and legal support for market operations. Such risks, however, seem to be played down by Chinese property professionals.

This paper uses the summarised opinions of interviewees who have varied expertise on different issues in China. Further research could be conducted on a number of fronts, say risk perception by different professions such as valuers or investors.

This is the first paper to apply developmental state theory to examine the roles the Chinese central and local governments play in using the property‐led growth model on the generation and intensification of property investment risks.

Online social networks are increasingly important venues for businesses to promote their products and image. However, information propagation in online social networks is significantly more complicated compared to traditional transmission media such as newspaper, radio, and television. In this chapter, we will discuss research on modeling and forecasting diffusion of virally marketed content in social networks. Important aspects include the content and its presentation, the network topology, and transmission dynamics. Theoretical models, algorithms, and case studies of viral marketing will be explored.

As hybrid organizations become increasingly common, the authors observe that some hybrid forms are becoming institutionalized and legitimated. The authors explore the implications of the institutionalization of hybridity, addressing both the internal tensions that plague many hybrids and the external tensions stemming from evaluator assessments and stakeholder uncertainty. The authors propose that institutionalization can dampen internal tensions associated with hybridity and also facilitate legitimation and acceptance by external audiences. The authors present identity as a useful theoretical lens through which to examine these questions, as identities are born from, but also have the potential to modify, existing institutional arrangements. The authors present directions for future research at the juncture of identity, hybridity, and institutionalization, suggesting potential avenues of inquiry in this productive stream of research.

Introduction: Human resource management (HRM) is going through a transformation phase due to the pandemic. The COVID-19 crisis compelled the employees to work virtually. To mitigate the effects of COVID-19, several organisations heavily invested in artificial intelligence (AI) in the realm of HRM.

Purpose: With limited studies on the paradigm shift in HRM post-pandemic and the role of AI, the study investigates and proposes a conceptual framework for the paradigm shift in HRM practices post-COVID-19 pandemic and the significance of AI. Furthermore, the study investigates the outcomes of the use of AI in HRM for organisations and employees.

Methodology: A comprehensive review of the literature based on the guidelines of Tranfield, Denyer, and Smart (2003) and Crossan and Apaydin (2010) has been followed. A systematic literature review assisted in critically analysing, synthesising, and mapping the extant literature by identifying the broad themes involved.

Findings: COVID-19-related economic disruption has led to a paradigm shift in HRM practices. AI-enabled HRM practices are now centred around remote and contingent workforce management, mindfulness, social capital, increasing employee engagement, reskilling and upskilling towards new competencies, etc. AI is making remote work seamless through smooth recruitment and selection process, onboarding, career and development, tracking and managing the performance, facilitating learning, and talent management. Post-pandemic, AI-powered tools based on data mining (DM), predictive analytics, big data analytics, natural language processing (NLP), intelligent robots, machine learning (ML), virtual (VR)/augmented reality (AR), etc., have paved the way for managing the HRM practices effectively, thereby leading to enhanced organisational performance, employee well-being, automation, and reduced cost.

The study aims to investigate market reactions associated with the JUST 100 rankings published by JUST Capital, a non-profit organization, as well as differences in financial reporting quality and performance between selected firms and their industry peers.

This study uses a sample of 431 firms selected as the 100 America’s Most Just Companies between 2016 and 2020 by JUST Capital. This study performs both an event study to determine whether the rankings are useful to investors and cross-sectional regression analyses on the characteristics of selected firms compared to their peers.

This study finds that investors react positively to selected firms around the time of the release of the JUST 100 rankings, suggesting that the rankings are decision-useful. This study also finds that selected firms exhibit higher accounting quality and financial performance than their peers.

Rankings may not be free from bias because of JUST Capital’s ownership of an exchange-traded fund.

The findings validate the rankings as well as the methodology used by JUST Capital, as they show market participants value firms that engage in socially responsible actions through their commitment to positively impact five key stakeholder groups: employees, customers, communities, environment and shareholders.

To the best of the authors’ knowledge, this is the first study that shows the importance of the JUST 100 rankings for investment decisions. Considering the growing push for companies to disclose environmental, social and governance (ESG) activities, this study provides evidence to support ESG disclosure regulations.

The paper examines the effect of language negativity of US financial analysts’ ancestral origins on their earnings forecast behavior.

The paper first developed a dictionary of the most emotionally negative words in 25 languages, based on the study by Dodds et al. (2015). The authors constructed firm-year analyst-level earnings forecast data and applied multivariate regression model along with a series of robustness tests to examine the research question.

The empirical results indicate that financial analysts with their ancestral countries characterized by a high level of language negativity tend to issue less optimistic earnings forecasts than other analysts. Additional evidence suggests that the effect of language negativity on analysts’ forecast is strengthened (1) during periods of financial crisis, (2) for firms with losses and a high level of earnings volatility and (3) for younger analysts and analysts working for small brokerage firms. Finally, we find evidence that higher levels of language negativity increase analysts’ forecast accuracy.

Collectively, the findings of this study support the conjecture that the level of negativity across languages can have a significant impact on capital market participants’ behavior. Thus, the study sheds light on how culturally inherited emotion can affect analysts’ earnings forecast properties.

Purpose – In order to explore how gender and sexual politics are played out in everyday practice within both the extreme right and jihadi-Salafist movements online, this chapter analyzes the content of two women’s only forums: The Women’s Forum on Stormfront.org and Women Dawah, a Turkish language pro-IS group chat on Telegram.

Methodology – The Women’s Forum and the Women Dawah data sets were analyzed using structural topic modeling to uncover the differences and similarities in salient topics between White Nationalist and Islamic State women-only forums.

Findings – The cross-ideological and multi-linguistic thematic analysis suggests that the safety of online spaces enables women to be more active, and serves digital support network for like-minding individuals. It also highlights that religion and ideology, whilst interwoven throughout posts on both platforms, they were more explicitly discussed within Women Dawah data.

Originality/Value – This research uses a unique data set which was collected over one year to conduct a cross-ideological and multi-linguistic thematic analysis, a relatively uncommon approach.

Biodiversity conservation is a major challenge globally. This global challenge exists due to the Scarcity of funds to preserve biodiversity. The need for more funds is the primary issue in managing biodiversity in this uncertain environment wherein different challenges emerge routinely. Thus, the main purpose of this study is to focus on the issues of biodiversity conservation and to examine alternative sources for biodiversity financing. Biodiversity is a multidimensional aspect covering several facets of the environment. It acts as a life support on earth and is a catalyst for human survival. However, biodiversity conservation is critical due to the Scarcity of biodiversity financing (Negacz, Petersson, Widerberg, Kok, & Pattberg, 2022). Thus, it is the need of the hour to overcome this issue by examining varied sources to generate more funds for preserving biodiversity. The study is based on a systematic review of past research wherein possible alternatives have been provided for generating necessary funds to mitigate biodiversity loss. It is revealed through past literature that though effort is made to combat the problem of funds, a very minimal effort is made at the individual level. More so framework lneeds to be not implemented globally. Therefore, the present study has proposed the practice of Green finance as an innovative financial mechanism to deal with biodiversity loss by emphasising environmental benefits. As laid down in this paper, a theoretical framework about biodiversity loss will encourage researchers to carry out various studies from varied outlooks to have a holistic approach towards this issue, hence ensuring environmental sustainability.