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This study examines how corporate litigation, both securities-related and not, is affected by hedge fund (HF) activism.

We use a difference-in-differences (DiD) method, along with propensity score matching and firm fixed effects and a comparison of HF and non-HF activists for identification.

We find that companies that are targeted by HFs face operation-related lawsuits, mainly from stakeholders or competitors. This effect does not seem to be caused by targets' higher tendency to settle the cases. Our evidence shows that HF activists increase firm value for the target firms that are prone to litigation.

Therefore, our evidence supports the idea that the higher operation litigation risks are unintended consequences of improving firm efficiency through cost savings or restructuring of target firms by the activists.

This study aims to examine the effects of payment methods used in mergers and acquisitions (M&A) conducted by UK companies spanning the period from 2007 to 2019.

The study used the estimated expected returns method to identify abnormal returns during the deal announcement period, applying event study analysis with both univariate and multivariate regression models to detect cumulative abnormal returns around the announcement timeframe.

The results show a short-term positive return increase for acquiring firms, controlling for deal-specific characteristics like target firm location and payment methods. The authors observed a preference for cash financing across domestic and cross-border transactions. Multivariate analysis revealed insignificance between payment methods and deal characteristics like cross-border acquisitions and diversification.

The study’s focus on publicly traded firms in the UK and the absence of a comparative analysis across different regions and markets limits the sample size and may impact the generalizability of findings.

The study proposes three practical implications. Firstly, firms should tailor payment methods to each transaction, aligning with strategic goals to optimize value and mitigate risks. Secondly, decision-makers must prioritize comprehensive due diligence and strategic alignment throughout M&A processes to enhance success and maximize synergies. Finally, analysing broader strategic contexts and regulatory landscapes when structuring transactions enables goal attainment, such as market expansion or value creation.

The study’s findings can promote transparency and accountability among corporate decision-makers in M&A transactions. Stakeholders can advocate for transparent decision-making processes, enhancing trust in corporate governance.

This study provides valuable insights into the impact of payment methods on shareholder value in M&A transactions involving UK companies, informing strategic decision-making and contributing to the understanding of corporate finance dynamics.

This study explores whether targeted microcredit can effectively alleviate households’ multidimensional relative poverty (MdRP) in rural China in the new era following the poverty elimination campaign and discusses it from a gendered perspective.

This study applies a fixed-effects model, propensity score matching (PSM) and two-stage instrumental variable method to two-period panel data collected from 611 households in rural western China in 2018 and 2021 to explore the effects, mechanisms and heterogenous performance of targeted microcredit on households’ MdRP in the new era.

(i) Targeted microcredit can alleviate MdRP among rural households in the new era, mainly by reducing income and opportunity inequality. (ii) Targeted microcredit can promote women’s empowerment, mainly by enhancing their social participation, thereby helping alleviate households’ MdRP. The effect of the targeted microcredit on MdRP is more significant in medium-educated women households and non-left-behind women households. (iii) The MdRP alleviation effect is stronger in villages with a high degree of digitalization.

Learn from the experience of targeted microcredit. Accurately identify poor groups and integrate loan design into financial health and women empowerment. Particularly, pay attention to less-educated and left-behind women households and strengthen coordination between targeted microcredit and digital village strategies.

This study clarifies the effect of targeted microcredit on women’s empowerment and households’ MdRP alleviation in the new era. It also explores its various effects on households with different female characteristics and regional digitalization levels, providing ideas for optimizing microcredit.

Small-scale farmers are highly heterogeneous with regard to their types of farming, levels of technology adoption, degree of commercialization and many other factors. Such heterogeneous types, respectively groups of small-scale farming systems require different forms of government interventions. This paper applies a machine learning approach to analyze the typologies of small-scale farmers in South Africa based on a wide range of objective variables regarding their personal, farm and context characteristics, which support an effective, target-group-specific design and communication of policies.

A cluster analysis is performed based on a comprehensive quantitative and qualitative survey among 212 small-scale farmers, which was conducted in 2019 in the Limpopo Province of South Africa. An unsupervised machine learning approach, namely Partitioning Around Medoids (PAM), is applied to the survey data. Subsequently, the farmers' risk perceptions between the different clusters are analyzed and compared.

According to the results of the cluster analysis, the small-scale farmers of the investigated sample can be grouped into four types: subsistence-oriented farmers, semi-subsistence livestock-oriented farmers, semi-subsistence crop-oriented farmers and market-oriented farmers. The subsequently analyzed risk perceptions and attitudes differ considerably between these types.

This is the first typologisation of small-scale farmers based on a comprehensive collection of quantitative and qualitative variables, which can all be considered in the analysis through the application of an unsupervised machine learning approach, namely PAM. Such typologisation is a pre-requisite for the design of more target-group-specific and suitable policy interventions.

The study aims to investigate the characteristics of the current situation of library programs and explore the possible reasons behind the low participation in Hong Kong. It focuses on the development of library programs in the era of digital technology, which can lead to discussion and reflections on the further development of library programs with innovative technology services.

This study applied a mixed-method research approach to investigate the current situation of library programming and the reasons for low participation in Hong Kong. The first part analyzes the characteristics of library programs offered by the Hong Kong Public Libraries (HKPL) through data collection from the HKPL website. The second part of this study investigated the reasons behind the low participation in library programs through quantitative research through an online survey.

The findings show that current library programs were dominated by reading activities and children's programs to a great extent, which both users and non-users are not very interested in. Further, most respondents expressed more interest in cultural and leisure events and hands-on activities (especially new technologies related) than traditional library programming. Many lapsed and non-users chose not to attend the library programs for boredom and uselessness. As a result, there is a need for HKPL to adjust its services to stay relevant to the needs and interests of local communities.

Scant studies explored the reasons behind non-users of public library programs, especially in Asia. This research contributes to the literature by analyzing and proposing the characteristics of the current situation of library programs and exploring the possible reasons behind the low participation in Hong Kong.

This paper aims to propose a methodology for assessing an optimal portfolio of investment instruments that minimise the social costs of decarbonising economic activity while improving the environmental objectives proposed in EU legislation.

The methodology defines the net social cost of decarbonisation related to a portfolio of four instruments: installation of solar PV and wind generation, thermal insulation of households and deployment of heat pumps. The social cost is minimised by restricting it to the minimum level of the targets proposed in the Spanish National Energy and Climate Plan to reduce greenhouse gas emissions, increase generation from renewable sources and reduce energy consumption. The empirical approach also includes differences between regions according to the expected effect for instruments.

The application of this methodology to the environmental objectives defined in the current Spanish National Energy and Climate Plan for 2030 concludes that it is clearly possible to reduce the social cost of decarbonisation while improving environmental performance through a reorientation of investment instruments. In this case, such a reorientation would be based on a minimisation of efforts in thermal insulation of households and a maximisation of measures aimed at the installation of heat pumps.

The paper proposes a novel methodology for a social cost assessment that improves the allocation of a portfolio of environmental instruments. This portfolio could be extended in further work to include instruments related to transport or support for industrial decarbonisation, such as the deployment of renewable hydrogen, among others.

This paper examines how different configurations of societal impact are pursued by purpose-driven organizations (PDOs) and how these configurations align with the application of varying supply chain design (SCD) practices.

This multi-method study uses quantitative data from 1588 B Corps and qualitative data from 316 B Corps to examine how PDOs align SCD with the pursuit of diverse types of societal impact. The authors first conduct a cluster analysis to group organizations based on the impact they create. Second, qualitative content analysis connects impact with enabling SCD elements.

The analysis of the five identified clusters provides detailed empirical insights on influencers, design decisions and building blocks adopted by PDOs to drive a range of societal impacts. Specifically, the nature of the impact pursued affects (1) whether a PDO will be more influenced by a need in the political environment or an opportunity in the industry environment, (2) the relative importance of the design of social flows versus material flows and (3) the need to develop new relational resources with beneficiaries versus leveraging existing capabilities to manage inter-firm processes.

This study responds to calls to disaggregate different dimensions of societal impact and examines the relationship between SCD and a breadth of sustainability impacts for different stakeholders. In doing so, the authors identify four SCD pathways organizations can follow to achieve specific societal impacts. This study is also the first to employ a supply chain perspective in the study of certified B Corps.

This study aims to analyze the knowledge transfer process for implementing a company-specific production system (XPS) from a subsidiary of a multinational corporation (MNC) to its local suppliers.

A case study approach was adopted and applied in an automotive supply chain. Empirical data were collected from interviews, observations and internal documents.

The literature shows that the successful XPS implementation depends on the ability to transfer XPS knowledge; the motivation of the source unit to share XPS knowledge; the value and nature of knowledge embedded in XPS; the effectiveness of individual, social and organizational transfer mechanisms; the motivation and absorptive capacity of the target unit and, the organizational, social and relational contexts in which XPS is transferred. Based on the research findings, we develop 12 propositions and presented them in a framework.

This paper expands and enriches the literature on the knowledge transfer process of XPS. The proposed framework establishes theoretical propositions and associations raised by qualitative analysis. However, these propositions are potentially testable on a larger scale for broader generalization.

Managers can recognize critical factors and relationships needed to improve the XPS implementation from an MNC subsidiary to its local suppliers.

The proposed framework provides a scheme to capture the essential critical factors affecting a successful XPS implementation between MNC subsidiaries and local suppliers. Moreover, we found relevant associations between pairs of critical factors that were not identified in the literature.

Wage employees enter self-employment either directly or in a staged manner and may subsequently undertake multiple stints at self-employment. Extant research on the relationship between entry modes and the persistence and outcomes of self-employment is inconclusive. This study investigates the relationship between wage employees’ initial mode of entry into self-employment and the duration of the subsequent first two stints of self-employment.

This study used a matched longitudinal sample of 9,550 employees who became majority owners of incorporated firms from 2005 to 2016.

The findings demonstrate that the initial mode of entry into self-employment matters for the first two stints at self-employment. Staged entry into self-employment was associated with a shorter first stint and became insignificant for the second stint. Staged entry into self-employment was positively related to the odds of becoming self-employed for the second time in the same firm.

Using a comprehensive and reliable dataset, the paper shifts focus from the aggregated onward journey of novice entrepreneurs (survival as the outcome) to the duration of their self-employment stints. By doing so, the paper offers insights into the process of becoming self-employed and the patterns associated with success/failure in entrepreneurship associated with self-employment duration.

This study leverages an integrated framework that uses the theory of planned behavior (TPB), risk perception and sustainable behavior to investigate the COVID-19 risk perception of a potentially powerful consumer group – generation Z – on decisions to participate in the domestic tourism stimulus campaign and their willingness to practice socially responsible behaviors.

Self-administered questionnaires were used to collect data. The study adopts partial least squares-structural equation modelling (PLS-SEM) to examine the data with the final sample of 422 generation Z in Thailand.

The COVID-19 perceived risk positively affects attitudes, perceived behavioral control and the intention to join domestic tourism campaign, affecting the desire to engage in sustainable behaviors when traveling. Attitude and perceived behavioral control mediated risk perception and the decision to join the campaign. Unlike other studies, generation Z is conscious of the situation but is not risk-averse to travel.

The study offers recommendations (and domestic tourism campaign's features) for government agencies and tourism partitioners, especially developing tourism destinations, to effectively launch domestic tourism campaigns to target generation Z during and after post-pandemic crises.

This study contributes to our limited understanding of generation Z's travel behaviors. It contributes to the extended use of TPB, risk perception and socially responsible conduct of such a specific generation. It is one of the first studies integrating the COVID-19 risk perception of generation Z and their intention to utilize the stimulus campaign.