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This review aims to provide an overview of research from different academic disciplines to chart some of the key developments in retail cryptocurrency trading against the backdrop of the wider trading landscape, and how it has evolved in recent years. The purpose of this review is to provide researchers with a broad perspective to highlight the complex range of factors that drive cryptocurrency trading among retail investors.

Peer-reviewed literature from the social sciences, economics, marketing and branding disciplines is synthesised to explicate influential factors among retail cryptocurrency investors.

Online retail trading communities can create narratives that ascribe value to cryptocurrencies leading to consumer herding behaviours. The principles that underpin emotional branding and Fear of Missing Out can promote trading behaviour driven by heuristic processing and cognitive biases. Concurrently, the tenets of controversial marketing and the anti-establishment nature of Bitcoin and other cryptocurrencies serve to bolster in-group out-group categorisations fostering continued investment and market volatility. Consequently, Bitcoin and cryptocurrency trading more broadly offer a powerful combination of excitement from risk-taking akin to gambling buffered by the sanctity of social inclusion.

A broader, unique perspective on retail cryptocurrency trading which assists in better understanding the complexities that underpin its appeal to retail investors.

In a rapidly shifting market, organizations seek more diverse and innovative employee development interventions. Yet, these initiatives may have limited impact without employees’ engagement. This conceptual paper aims to propose self-leadership as a value-added strategy for promoting both individual and organizational development.

The authors conducted a conceptual analysis with three case examples. The cases were purposefully selected, aiming to comprehend how the concept of self-leadership has been applied within organizations and to identify real-life examples where self-leadership has been adopted as an organizational strategy.

This study demonstrates that self-leadership plays a significant role in facilitating human resource development (HRD) initiatives. Specifically, the authors illustrate how self-leadership interventions in companies empower individuals to take charge of their development, aligning personal and organizational goals. When effectively applied, self-leadership strategies positively impact HRD practices in the areas of training and development, organization development and career development, yielding benefits for both employees and employers.

This study addresses knowledge gaps in the emerging field of self-leadership in HRD by providing three companies’ examples of how self-leadership can add value to HRD. The findings offer unique insights into the synergy between self-leadership and HRD, benefiting academics interested in this line of inquiry and HRD practitioners seeking innovative approaches to employee and organizational development.

Little is known about how individual differences play out in the process of authentic self-development (ASD) through workplace coaching. This article explores whether the Big Five personality traits and affective, behavioral, cognitive and desire (ABCDs) components of the Big Five personality traits were relevant to ASD, specifically examining the role of affect as a potential mediator.

In total, 176 clients' personality was assessed pre-coaching. Aspects of ASD (perceived competence, goal commitment, self-concordance and goal stability) were assessed post-coaching. Clients' affect balance (AB) scores were obtained post-session.

Multilevel path models showed that higher levels of mean AB (but not the slope) mediated the associations between personality and perceived competence and goal commitment. Personality predicted goal self-concordance, but these effects were not mediated by AB, neither personality nor AB predicted goal stability.

The authors encourage randomized controlled trials to further test findings of this study. Ruling out method variance is not possible completely. However, the authors put forth considerations to support the authors' claim that method variance did not overly influence our results.

These results suggest the necessity of an optimal experience of affect for ASD in workplace coaching and the understanding of how ABCDs, AB and ASD are related beyond coaching psychology.

A deeper understanding of personality processes is important for fostering ASD to meet the challenges of management development in the authors' volatility, uncertainty, complexity and ambiguity (VUCA) world.

This is the first study to test personality as a process in workplace coaching linking personality to one of the most valued leadership skills: authenticity.

The purpose of this study is to investigate the perceived effects between soft management practices, employee behaviours and the implementation of digital technologies in manufacturing plants, as well as how these relate to the emergence of digital waste.

This paper uses case-based research. Data was collected in two large manufacturing companies based in Norway and Sweden through semi-structured interviews with two management representatives and four shop-floor employees. The data was used to evaluate 29 variables describing lean- and total quality management (TQM)-associated employee behaviours and soft management practices, in light of digital transformation.

The results suggest that several variables were positively influenced by the digital transformation process. These were top management leadership, middle management involvement, employee education, corporate social responsibility focus, innovation, knowledge sharing, work-family balance, psychological capital, job satisfaction and career commitment. Training employees, creativity, discretionary effort, turnover intention and proactivity appear to be negatively influenced by digital transformation The findings also indicate that several soft management practices and employee behaviours were not only influenced by manufacturing digitalization but also themselves influenced the process. The potential for digital waste creation was also detected in several variables, including reward and recognition and training employees.

Managers, practitioners and academics may learn about the importance of certain managerial practices and employees’ behavioural needs during the digital transformation process. The findings may help in prioritizing TQM and soft lean management practices and certain employee behaviours during the digital transformation and in creating awareness of digital waste.

This study builds on several existing studies discussing the impact of digital transformation on soft management practices and employee behaviours. It provides insights from a lean and TQM angle and offers a means of prioritizing certain practices and behaviours during a digital transformation. This study also highlights the significance of digital waste.

Good quality input data is critical to developing a robust machine learning model for identifying possible money laundering transactions. McKinsey, during one of the conferences of ACAMS, attributed data quality as one of the reasons for struggling artificial intelligence use cases in compliance to data. There were often use concerns raised on data quality of predictors such as wrong transaction codes, industry classification, etc. However, there has not been much discussion on the most critical variable of machine learning, the definition of an event, i.e. the date on which the suspicious activity reports (SAR) is filed.

The team analyzed the transaction behavior of four major banks spread across Asia and Europe. Based on the findings, the team created a synthetic database comprising 2,000 SAR customers mimicking the time of investigation and case closure. In this paper, the authors focused on one very specific area of data quality, the definition of an event, i.e. the SAR/suspicious transaction report.

The analysis of few of the banks in Asia and Europe suggests that this itself can improve the effectiveness of model and reduce the prediction span, i.e. the time lag between money laundering transaction done and prediction of money laundering as an alert for investigation

The analysis was done with existing experience of all situations where the time duration between alert and case closure is high (anywhere between 15 days till 10 months). Team could not quantify the impact of this finding due to lack of such actual case observed so far.

The key finding from paper suggests that the money launderers typically either increase their level of activity or reduce their activity in the recent quarter. This is not true in terms of real behavior. They typically show a spike in activity through various means during money laundering. This in turn impacts the quality of insights that the model should be trained on. The authors believe that once the financial institutions start speeding up investigations on high risk cases, the scatter plot of SAR behavior will change significantly and will lead to better capture of money laundering behavior and a faster and more precise “catch” rate.

Since previous literature provides fragmented and conflicting results about the use of digital data for product innovation, the article aims to comprehensively explore and shed light on how agri-food firms utilise external and internal digital data sources when dealing with different product innovations, such as incremental, architecture and radical innovation.

This paper adopts an exploratory multiple-case study and a theory-building process, focussing on the agri-food industry. We collected primary and secondary data from eight manufacturing companies.

The findings of this research show an empirical framework of six agri-food firms’ digital data utilisation behaviours: the supervisor, the passive supervisor, the developer, the passive developer, the pathfinder and the conjunction behaviour. These digital data utilisation behaviours vary according to a combination of data sources, such as internal data related to inside phenomenon measures (e.g. data generated by sensors installed in the production plan) or external data (e.g., market trends, overall sector sales), and innovation purposes.

This article offers guiding principles that assist agri-food companies when utilising internal and external digital data sources for specific product innovation outcomes such as incremental, architectural and radical innovation.

The significance of external and internal data sources in stimulating product innovation has garnered substantial attention within academic discussions, highlighting the critical importance of analysing digital data for driving such innovation. Nonetheless, the predominant approach is to study a single innovation outcome through the lens of digital technology. In contrast, our study stands out by adopting a fundamental perspective on data sources, enabling a more nuanced explanation of the overall product innovation outcomes within the agri-food sector.

Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a profound influence on the dissemination of information among participants in stock markets. Consequently, this present study delves into the ramifications of post-pandemic dynamics on stock market behavior. It also examines the relationship between investors' sentiments, underlying behavioral drivers and their collective impact on global stock markets.

Drawing upon data spanning from 2012 to 2023 and encompassing major world indices classified by Morgan Stanley Capital International’s (MSCI) market and regional taxonomy, this study employs a threshold regression model. This model effectively distinguishes the thresholds within these influential factors. To evaluate the statistical significance of variances across these thresholds, a Wald coefficient analysis was applied.

The empirical results highlighted the substantive role that investors' sentiments and behavioral determinants play in shaping the predictability of returns on a global scale. However, their influence on developed economies and the continents of America appears comparatively lower compared with the Asia–Pacific markets. Similarly, the regions characterized by a more pronounced influence of behavioral factors seem to reduce their reliance on these factors in the post-pandemic landscape and vice versa. Interestingly, the post COVID-19 technological advancements also appear to exert a lesser impact on developed nations.

This study pioneers the investigation of these contextual dissimilarities, thereby charting new avenues for subsequent research studies. These insights shed valuable light on the contextualized nexus between technology, societal dynamics, behavioral biases and their collective impact on stock markets. Furthermore, the study's revelations offer a unique vantage point for addressing market inefficiencies by pinpointing the pivotal factors driving such behavioral patterns.

The purpose of this study is to discover the learning mechanisms and temporal dynamics of implementing systems (Six Sigma) as it unfolds over time.

The data come from a European engineering company that was implementing a Six Sigma-based quality management system (QMS) over a seven-year period. The analysis is based on an event-sequence reconstruction of the implementation process as it unfolded over time and discovers four different learning mechanisms that emerged: programmatic, persistent, adaptive and dialectical learning mechanisms. The research follows a process design study, where the authors study how the process unfolds over time.

Much of the literature on implementing management systems suggests that implementation follows a prescribed sequence of “turn-key” steps. However, the findings show that only 40% of all events were driven by prescribed “turn-key” generic practices, while 56% of events required constructing new practices via adaptive and dialectical learning. Moreover, the implementation process did not proceed in a linear programmatic fashion, but instead followed a punctuated equilibrium pattern, which alternated between periods of incremental change and major organizational change. The study also found that implementation required changing many complementary organizational structures and practices that were interdependent with the management system (i.e. Six Sigma). By understanding the implementation process, managers can better assess the time and effort involved, better adapt the system to their situated context and predict critical junctures where implementation could break down.

This research complements the few studies that have examined the process of implementing management systems. Most studies examine factors or conditions that result in implementation success (the what of implementing systems), but few examine the process of implementation and the learning that takes place during implementation (the how of implementing systems), which is a complex nonlinear process that involves different modes of learning.

In the scope of the immense growth of corporate frauds and scandals, reporting unethical practices could be considered as an important mechanism to control them and ultimately improve organizational quality. To this end, this study proposes the conceptual framework comprising the enablers impacting employees' tendencies and behaviors to reporting misdemeanor in the workplace.

Systematic review of literature has been carried out. To understand the complexities among various enablers and to analyze their driving power and contingencies, a modified total interpretive structural modeling (TISM) approach has been adopted.

The findings indicate that enablers such as moral identity (MI) and job satisfaction (JS) having higher driving power (come at the bottom of the hierarchy) are relatively more important. Furthermore, perceived personal cost (PC), moral courage (MC), self-efficacy (SE) and anger have high dependent power of factors. Finally, the paper provides two paths that can lead to whistleblower's ethical decision.

A conceptual framework delivered in this paper requires to test against the field data. However, the conceptual understanding of driving enablers paves the way to top management in recruiting and hiring people in the workplace.

This study represents the first attempt to apply TISM for whistleblowing phenomenon. It provides a comprehensive conceptual framework in order to address the relative importance of various individual enablers in developing reporting tendencies against misdemeanors.

The primary objective of this investigation was to explore how employees’ utilization of social media for work-related purposes impacts their service innovation behavior, both directly and through the intermediary mechanisms of knowledge management and employees’ risk-taking.

In developing its conceptual framework, this study has drawn upon the stimulus-organism-response (SOR) theory. To test its hypotheses, this study has surveyed 241 financial analysts from ten Iranian financial companies and has employed variance-based structural equation modeling (specifically, PLS-SEM) with the assistance of “WarpPLS 8.0 software.”

The findings revealed that employees’ work-related use of social media positively influences their service innovation behavior using knowledge management, encompassing knowledge sharing and acquisition capability as well as employee risk-taking. However, this influence is not directly significant.

To the best of our knowledge, this study marks the first instance in which the effect of work-related use of social media on employee service innovation behavior directly and through the mediating roles of knowledge management and risk-taking has been investigated through the lens of the SOR paradigm, especially in the financial sector.