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The purpose of this paper is to explore and evaluate the current legal position on the admissibility and exclusion of illegally obtained evidence in money laundering cases.

A thorough exploratory analytical analysis signifies that such illegally obtained evidence from money laundering offences is admissible, provided it does not undermine the administration of justice or the right to a fair trial.

By virtue of the lack of written or codified rules governing the admissibility and exclusion of illegally obtained evidence in cases involving money laundering, the rule of admissibility remains the primary foundational principle for the governance of the admissibility and exclusion of illegally obtained evidence in money laundering cases.

The Malaysian Criminal Justice System has historically relied on the long-standing admissibility principles to admit and exclude illegally obtained evidence. For decades, courts have used their discretion to admit illegally obtained evidence based on the relevancy test, and they have further demonstrated to use the same discretion to exclude gravely prejudicial evidence. Evidence obtained illegally but if relevant to the matter in issue is deemed admissible. Evidence derived from an act associated with unlawful activities or a predicate offence in money laundering may be obtained illegally, which may influence the prosecution case and conversely, defend the accused’s rights to a fair trial.

Given the significant role played by valuers and the evidence of a lack of independence in some property valuation industries, particularly in emerging markets, this study analyses the issue of client influence in property valuation by providing a valuer-client perspective and measuring the interrelationships between the clients' influence factors to identify causal factors of prominence, which can assist in developing solutions to address the clients' influence issue.

The study used a mixed-method approach. Firstly, interviews were conducted with ten property valuers and five financial institution staff in Nigeria, and the data were subject to thematic analysis using Nvivo 12 software. A matrix questionnaire survey was administered to the valuers, and the responses were analysed using the fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) method.

The results indicate that institutional clients, loan-seeking customers, property valuers and the perception of corruption within the Nigerian environment fuelled the issue of clients' influence. Based on the measurement of the interrelationship between the 14 identified client influence factors, the type of company, perception the public has of the industry, size of the firm, relationship with the client, type of client and regulatory framework were the factors of prominence.

The findings of this study bear huge implications for Nigeria and other similar structured property markets facing the issue of clients' influence in property valuation. With the prominent factors bearing root in a mix of client, valuer and environmental factors such as the valuation structure, process and public perception, there is a need for solutions that level the playing field between institutional clients and valuers, reinforce transparency and establish excellent regulatory standards to address the issue of clients' influence.

This study is the first to measure the interrelationships between the clients' influence factors to identify the prominent causal factors. Accordingly, considering the multi-factors, the research is novel as it focusses on those factors that would likely lead to other factors, thereby providing opportunities to develop solutions that focus on those factors of prominence. Secondly, the study deviates from the narrative on clients' influence in property valuation, which pits it as solely a client or valuer factor, by showing how the interplay of the stakeholders' interests and the environment promotes the issue in a non-transparent property market.

This study aims to delve into the varying impacts of different types of emotions conveyed through retailers' review request texts on consumers' intention to write a review.

To verify the relationships between these variables, two laboratory experiments were conducted in this study.

The findings indicate that when accompanied by an objective statement, texts that evoke empathy and favor have a positive influence on consumers' inclination to write a review. Moreover, by examining the underlying mechanism, this study uncovers two interconnected mediators, namely persuasive intent and cognitive (affective) resistance, along with empathy and helping intention. Additionally, the study explores the moderating role of customer satisfaction with the product, shedding light on the contextual factors that influence the effects of emotional cues in review texts.

This research contributes to the literature and practice by focusing on the process of retailers' generating online reviews. This is one of the first studies to systematically examine the effects of emotional text in retailers' review request on consumers' reviewing intention from the perspective of emotional evocation. The experimental findings and the underlying mechanisms emphasize the impact of different types of emotions in retailers' review requests texts on consumers' reviewing intentions. It can help retailers better understand the psychological reactions of consumers when they ask reviews, which provide theoretical support for retailers to design more reasonable asking texts.

Artificial intelligence (AI) can enhance human resource resiliency (HRR) by providing the insights and resources needed to adapt to unexpected changes and disruptions. Therefore, the present research attempts to develop a framework for future researchers to gain insights into the actions of AI to enable HRR.

The present study used a systematic literature review, bibliometric analysis, and network analysis followed by content analysis. In doing so, we reviewed the literature to explore the present state of research in AI and HRR. A total of 98 articles were included, extracted from the Scopus database in the selected field of research.

The authors found that AI or AI-associated techniques help deliver various HRR-oriented outcomes, such as enhancing employee competency, performance management and risk management; enhancing leadership competencies and employee well-being measures; and developing effective compensation and reward management.

The present research has certain implications, such as increasing the HR team's proficiency, addressing the problem of job loss and how to fix it, improving working conditions and improving decision-making in HR.

The present research explores the role of AI in HRR following the COVID-19 pandemic, which has not been explored extensively.

This study aims to investigate the factors that lead to the failure of some rewards to induce knowledge sharing behavior among employees, with much focus on employees’ attitudes and leadership’s knowledge of employees’ preferences, and presents a model that depicts the linkages.

To investigate why the provision of some rewards fails to induce knowledge sharing behavior among employees, this study uses the preferred reporting items for systematic reviews and meta-analyses framework to identify and analyze 56 articles published from 2000 to 2021.

Knowledge sharing is positively linked to organizational performance. Further, employees’ negative attitudes toward a reward system negatively relate to knowledge sharing behavior. Furthermore, management’s lack of knowledge of employees’ preferences regarding rewards leads to the provision of incorrect rewards that do not enhance knowledge sharing behavior. Finally, a conceptual model depicting the linkages among the variables under consideration has been presented.

Through the present study, employees’ attitudes toward rewards and leadership’s knowledge of employees’ preferences have been presented as critical factors that can lead to the failure of some rewards to induce knowledge sharing behavior. Further, the conceptual framework that can guide managers and leaders in strategizing on how best to develop and implement correct reward systems has been presented.

The present study is a significant contribution to the literature by focusing on the negative side of rewards toward knowledge sharing behavior with a focus on employees’ attitudes and leadership’s awareness of employees’ preferences regarding rewards.

Previous research has analyzed the consequence of network stability; however, little is known about how partner type diversity influence network stability in R&D network. Based on knowledge-based view and social network theory, the purpose of this paper is to unravel the internal mechanisms between partner type diversity and network stability through the mediating role of knowledge recombination in R&D network.

The authors collected an unbalanced panel patent data set from information communication technology industry for the period 1994–2016. Then, the authors tested the different dimensions of partner type variety and its relevance in the R&D network and the mediating role of knowledge recombination through adopting the multiple linear regression.

Results indicate an inverted U-shaped relationship between partner type diversity (variety and relevance) and network stability, whereas knowledge recombination partially mediate these relationships.

From the perspective of R&D networks, this paper explores that there are the under-researched phenomena the antecedent of network stability through nodal attributes (i.e. partner type variety and partner type relevance). Moreover, this paper empirically examined the mediating role of knowledge recombination in the partner type diversity–network stability relationships. The novel perspective allows focal firm to recognize importance of nodal attributes, which are critical to fully excavate the potential capabilities of cooperating partners in R&D network.