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There are many different views and opinions held about the value of training. Some people, of course, reach the top without any formal training whatsoever and expect others to do the same. This is all well and good if, presumably, you are able to train yourself. Most need the support of formally organized training courses or continuous learning, working on the assumption that there are always things to learn. It does not matter how old or experienced you are, there will always be a gap in your knowledge that requires attention. Beware the people who know it all as they will be the ones who have the blind spots and just cannot see trouble ahead. If these people are at the top of the organization and just happened to be in the right place at the right time, which could happen if an organization has been particluarly successful, then this could have disastrous consequences on the business. Business means change, and if you cannot cope or are not prepared to accept or adapt to this change, the end result is inevitable.

IN the middle of a January afternoon an audience which packed the National Film Theatre was held in thrall by a film. These people drawn from Government departments, trade unions, employers, technical colleges and local productivity committees were not wasting precious time watching the miming of famous film stars.

THE enlarged scale and more varied content of this year's Business Efficiency Exhibition recalls the importance of the office in modern business. So, too, do those vast, austere rectangular boxes whose modular construction makes them so depressingly alike. Those in London and other major cities can be matched exactly in Frankfurt or Brussels, Milan or Montreal. This is a natural consequence of the tendency for the number of manual workers to decline and of clerical ones to increase.

The advent of artificial intelligence (AI) in the accounting landscape marks a significant shift, promising gains in efficiency and accuracy but also eliciting concerns about job displacement (JD) and broader socio-economic implications. This study aims to provide an in-depth understanding of how AI’s integration in accounting contributes to JD, reshapes decision-making processes and reverberates across economic and social dimensions. It also offers evidence-based policy recommendations to mitigate adverse outcomes.

Leveraging a cross-sectional survey disseminated through Facebook, this research used snowball sampling to target a diverse cohort of accounting professionals. The collected data were subjected to meticulous analysis through descriptive and regression models, facilitated by SmartPLS 4 software.

The analysis revealed a significant correlation between AI’s increasing role in accounting and a heightened rate of JD. This study found that this displacement is not isolated; it has tangible repercussions on decision-making paradigms, economic well-being, professional work dynamics and social structures. These insights corroborate existing frameworks, including, but not limited to, theories of technological unemployment and behavioural adjustments.

Although providing valuable insights, this study acknowledges limitations such as the restricted sample size, the cross-sectional nature of the survey and the inherent biases of self-reported data. Future research could aim to extend these initial findings by adopting a longitudinal approach and potentially integrating external data sources.

As AI technology becomes increasingly ingrained in accounting practices, there is an urgent need for coordinated action among stakeholders. Policy recommendations include focused efforts on talent retention, investment in upskilling programs and the establishment of support mechanisms for those adversely affected by AI adoption.

By synthesising a range of theoretical perspectives, this study offers a comprehensive exploration of AI’s multi-dimensional impacts on the accounting profession. It stands out for its nuanced examination of JD and its economic and social implications, thereby contributing to both academic discourse and policy formulation. This work serves as an urgent call to action, highlighting the need for strategies that both exploit AI’s potential benefits and protect the workforce from its disruptive impact.

Research on the practice of child marriage has been extensive, with studies recommending local strategies that are peculiar to the countries involved. Rights-based literature also recommends stringent laws; portraying the girls involved as helpless victims needing external agencies to rescue them from parochial and oppressive cultural practices. This chapter, however, presents their resilience as they navigate through the challenges and trauma of demeaning marriage practices. Their ability to rise above the challenges of child marriage contradicts the stereotypical perception of being passive and unable to develop agency and empower themselves. The author also draw from the experiences of these young women to argue for restorative justice (RJ) to tackle child marriage issues. Indeed, a restorative process is likely to prove far more effective in achieving social discipline than the current reliance on punishment and sanctions. More so, harm as a result of child marriage is a violation against the victim and not necessarily the state. Hence, RJ, which is future-focussed with healing and prevention as key goals, would be more suitable.

Focusing on the social influence processes in the context of massively multiplayer online role-playing games (MMORPGs), this study aims to investigate the nomological network of social influence factors, a topic seldom explicitly articulated in the literature in this unique context.

This study adopts a mixed-methods approach to develop and test a context-specific model of social influence processes in MMORPGs. First, the authors conducted qualitative interviews with MMORPG players to identify the drivers shaping players' perceptions of social influences. Second, the authors formulated and tested a research model with quantitative data collected from 450 respondents of an online survey.

Through the qualitative study, the authors identify leader enthusiasm, social support and social presence as the critical drivers of social influence factors. The result of the quantitative study validates the influences of the critical drivers and demonstrates the impact of social influences on MMORPG players' we-intention to continue playing games.

This research extends the social influence theory by identifying contextualized drivers that shape MMORPG players' perception of social influences determining their we-intention to continue playing games. MMORPG service providers can draw on these drivers to leverage social influences to increase players' we-intention of continuance.

The emergence of distributed ledger technology (DLT) has transformed the way construction industries approach data management, ushering in an era of increased transparency, security and efficiency. The purpose of this study is to investigate the strategies to promote the adoption of DLT in the Nigerian construction sector. This was done to address the challenges that hinder the widespread adoption of DLT within the Nigerian construction sector.

A comprehensive literature review informed the design of a structured questionnaire for data collection. The questionnaire was distributed among diverse construction professionals to explore their perceptions of potential strategies. The collected data were analyzed using the Shapiro–Wilk test for data distribution, while mean values and standard deviations were used to facilitate the ranking of strategies. The Kruskal–Wallis H-test was used to assess opinion differences, and exploratory factor analysis was applied to uncover underlying dimensions.

The findings revealed the top five strategies for DLT adoption as conducting workshops and seminars to educate professionals, collaborating with universities for DLT courses, encouraging joint projects for shared insights, forming consortia for DLT standards and allocating funding for DLT research in construction. Through factor analysis, the strategies identified were categorized into four principal clusters: awareness and education advancements, government support and incentives, industry collaboration and standards and pilot projects and demonstrations.

While prior studies have identified barriers to DLT adoption and offering recommendations, this research advances the field by empirically investigating and assessing several of these strategies proposed in various studies. This approach provides valuable insights that go beyond existing research, offering a deeper understanding of the practical and contextual dynamics influencing DLT adoption in the construction sector.

Metamodeling is an effective method to approximate the relations between input and output parameters when significant efforts of experiments and simulations are required to collect the data to build the relations. This paper aims to develop a new sequential sampling method for adaptive metamodeling by using the data with highly nonlinear relation between input and output parameters.

In this method, the Latin hypercube sampling method is used to sample the initial data, and kriging method is used to construct the metamodel. In this work, input parameter values for collecting the next output data to update the currently achieved metamodel are determined based on qualities of data in both the input and output parameter spaces. Uniformity is used to evaluate data in the input parameter space. Leave-one-out errors and sensitivities are considered to evaluate data in the output parameter space.

This new method has been compared with the existing methods to demonstrate its effectiveness in approximation. This new method has also been compared with the existing methods in solving global optimization problems. An engineering case is used at last to verify the method further.

This paper provides an effective sequential sampling method for adaptive metamodeling to approximate highly nonlinear relations between input and output parameters.