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The purpose of this paper is to address the opposing views of the relationship between directors’ and officers’ liability insurance (D&O insurance) and stock price crash risk in a major Asian emerging stock market.

This paper finds an endogenous relationship between D&O insurance and stock price crash risk. Hence, the two-stage least squares regression analysis is used to address the endogeneity issue when the relationship is examined. Moreover, this paper further controls the quality of other corporate governance mechanisms to investigate whether D&O insurance still has an effect on stock price crash risk.

The effect of D&O insurance coverage is significantly negatively related to firm-specific stock price crash risk in Taiwan. More importantly, even when the quality of other corporate governance mechanisms is controlled, the negative relationship between D&O insurance coverage and firm-specific stock price crash risk remains significant. The evidence supports that D&O insurance serves as an effective external monitoring mechanism, strengthens corporate governance, and thus reduces stock price crash risk.

Emerging Asian markets suffer a dearth of research on the relationship of D&O insurance coverage and the firm-specific stock price crash risk. Investigating the relationship in Taiwan, the present study fills the research void. The findings show that D&O insurance plays an important role in reducing stock price crash risk of Taiwanese firms even when other corporate governance mechanisms are in place.

Doxing refers to the intentional public release by a third party of personal data without consent, often with the intent to humiliate, intimidate, harass, or punish the individual concerned. Intuitively, it is tempting to condemn doxing as a crude form of cyber violence that weaponizes personal data. When it is used as a strategy of resistance by the powerless to hold the powerful accountable, however, a more nuanced understanding is called for. This chapter focuses on the doxing phenomenon in Hong Kong, where doxing incidents against police officers and their family members have skyrocketed since 2019 (a 75-fold increase over 2018). It contends that doxing for political purposes is closely related to digital vigilantism, signifying a loss of confidence in the ruling authority and a yearning for an alternative form of justice. The chapter therefore argues that public interest should be recognized as a legal defense in doxing cases when those discharging or entrusted with public duty are the targets. Equally, it is important to confine the categories of personal data disclosed to information necessary to reveal the alleged wrongdoer or wrongdoing. Only in this way can a fair balance be struck between privacy, freedom of expression, and public interest.

Library intelligence institutions, which are a kind of traditional knowledge management organization, are at the frontline of the big data revolution, in which the use of unstructured data has become a modern knowledge management resource. The paper aims to discuss this issue.

This research combined theme logic structure (TLS), artificial neural network (ANN), and ensemble empirical mode decomposition (EEMD) to transform unstructured data into a signal-wave to examine the research characteristics.

Research characteristics have a vital effect on knowledge management activities and management behavior through concentration and relaxation, and ultimately form a quasi-periodic evolution. Knowledge management should actively control the evolution of the research characteristics because the natural development of six to nine years was found to be difficult to plot.

Periodic evaluation using TLS-ANN-EEMD gives insights into journal evolution and allows journal managers and contributors to follow the intrinsic mode functions and predict the journal research characteristics tendencies.

The link between supply chain agility (SCA) and performance has been tested in previous research with different samples and results. The present paper quantitatively analyses and summarises the impact of SCA on performance found in previous empirical papers and determines the influence of several identified moderators.

Using a meta-analysis approach based on a systematic literature review, a total of 63 empirical papers comprising a sample of 14,469 firms were meta-analysed to consider substantive (type of performance and SCA operationalisation) and extrinsic (economic region and industry) moderators.

Results confirm a significantly large, positive correlation between SCA and performance. None of the analysed moderators has enabled the identification of any significant differences between the SCA and performance correlations by subgroup. However, high heterogeneity in total variance, both in the full sample and the subgroups by moderator, demands further rigorously reported empirical research on this topic with clearly conceptualised variables and frameworks and the use of validated scales.

Several research gaps and best practice recommendations have been indicated to improve future empirical research on this topic.

Practitioners in different economic regions and industries will find consistent evidence of improvements in performance through SCA.

No meta-analysis has been found in previous research to estimate the value of the correlation between SCA and performance and the influence of moderating variables.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.