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The purpose of the study is to investigate the impact of artificial intelligence (AI), machine learning (ML), and data science (DS) on unemployment rates across ten high-income economies from 2015 to 2023.

This study takes a unique approach by employing a dynamic panel data (DPD) model with a generalised method of moments (GMM) estimator to address potential biases. The methodology includes extensive validation through Sargan, Hansen, and Arellano-Bond tests, ensuring the robustness of the results and adding a novel perspective to the field of AI and unemployment dynamics.

The study’s findings are paramount, challenging prevailing concerns in AI, ML, and DS, demonstrating an insignificant impact on unemployment and contradicting common fears of job loss due to these technologies. The analysis also reveals a positive correlation (0.298) between larger government size and higher unemployment, suggesting bureaucratic inefficiencies that may hinder job growth. Conversely, a negative correlation (−0.201) between increased labour productivity and unemployment suggests that technological advancements can promote job creation by enhancing efficiency. These results refute the notion that technology inherently leads to job losses, positioning AI and related technologies as drivers of innovation and expansion within the labour market.

The study’s findings suggest a promising outlook, positioning AI as a catalyst for the expansion and metamorphosis of employment rather than solely a catalyst for automation and job displacement. This insight presents a significant opportunity for AI and related technologies to improve labour markets and strategically mitigate unemployment. To harness the benefits of technological progress effectively, authorities and enterprises must carefully evaluate the balance between government spending and its impact on unemployment. This proposed strategy can potentially reinvent governmental initiatives and stimulate investment in AI, thereby bolstering economic and labour market reliability.

The results provide significant perspectives for policymakers and direct further investigations on the influence of AI on labour markets. The analysis results contradict the common belief of technology job loss. The study’s results are shown to be reliable by the Sargan, Hansen, and Arellano-Bond tests. It adds to the discussion on the role of AI in the future of work, proposing a detailed effect of AI on employment and promoting a strategic method for integrating AI into the labour market.

This paper aims to add further evidence to adoption criteria for “revolutionary” business techniques.

Adoption criteria for business techniques with a high degree of novelty have been developed earlier. The case of exchange-traded funds supports the earlier findings. The methodology applied is explicative.

The analysis supports findings that an effective response to a problem, the availability of a controllable procedure, the means to apply the procedure easily and the hardware jointly explain adopting “revolutionary” business techniques.

The results of case studies, in general, do not permit induction. More research might identify additional adoption criteria or falsify the presently obtained results. Therefore, further research is invited.

Managers seeking or being introduced to new techniques in business administration might use the criteria outlined here for their evaluation.

The author believes this paper corroborates earlier findings on adopting “revolutionary” business techniques that draw on theoretically developed technologies.

The intent of this practice briefing is to provide clarity on the role of market cycles in influencing property valuations at specific points in time. Market cycles are important to the valuation function as real estate cycles have been a critical underlying reason for the financial successes and failures of real estate investments throughout history.

This practice briefing is an overview of the role of the valuer/appraiser in decanting out market information and expectations from market comparables.

This briefing is a review of property valuation and proffers that connecting market cycles to valuation will capture a more expansive and inclusive world view that explicitly incorporates consideration of multiple factors that are reflected in market value.

Important implication of this research is that valuers be aware of how profoundly market cycles concepts and circumstances influence property values – and implement that knowledge in property valuation assignments.

This briefing considers the implications of using market cycles knowledge as a core resource for the property valuer. All involved in the property discipline must recognise that market cycles dramatically influence property values at any one point in time.

Societies, cultures, governments, business and places depend upon and have major stake in competent, responsible, informed decisions about properties and property interest. This research contributes to superior property practice – and therefore supports the interests of societies, cultures, governments, business and places.

This briefing provides guidance on how to interpret markets, market cycles and market information that feed into property pricing and market value.

The purpose is to stimulate scholarship in the strategic management field that accounts for conditions implied by projected impacts of climate change.

Following conceptual logic, the article analyses how changes in the strategic environment brought about by climate change may challenge current strategic management theory. It develops avenues for theory development based on expanding the field’s scope and extending its limits of applicability.

The article highlights the extent to which the strategy field has evolved in a stable empirical context, despite its attention to dynamism and hence is less well aligned with potentially pervasive new pressures and impacts. It sets out a rationale for moving beyond symbolic environmentalism, possibilities to harness cognitive and behavioural insights, dilemmas in strategic innovation and the empirical potential of non-mainstream contexts.

Firms and organisations can expect widespread systemic effects from climate change that challenge established ways of operating. The article explores how strategic management could better support strategists in navigating these shifts such that firms can continue to thrive.

The article approaches the issue of climate change specifically from the perspective of strategic management of firms rather than as policy or social advocacy. It focuses on pressures and characteristics that distinguish climate change from other environmental and social impacts on firms.

The applications of Artificial Intelligence (AI) in various areas of professional and knowledge work are growing. Emotions play an important role in how users incorporate a technology into their work practices. The current study draws on work in the areas of AI-powered technologies adaptation, emotions, and the future of work, to investigate how knowledge workers feel about adopting AI in their work.

We gathered 107,111 tweets about the new AI programmer, GitHub Copilot, launched by GitHub and analysed the data in three stages. First, after cleaning and filtering the data, we applied the topic modelling method to analyse 16,130 tweets posted by 10,301 software programmers to identify the emotions they expressed. Then, we analysed the outcome topics qualitatively to understand the stimulus characteristics driving those emotions. Finally, we analysed a sample of tweets to explore how emotional responses changed over time.

We found six categories of emotions among software programmers: challenge, achievement, loss, deterrence, scepticism, and apathy. In addition, we found these emotions were driven by four stimulus characteristics: AI development, AI functionality, identity work, and AI engagement. We also examined the change in emotions over time. The results indicate that negative emotions changed to more positive emotions once software programmers redirected their attention to the AI programmer's capabilities and functionalities, and related that to their identity work.

Overall, as organisations start adopting AI-powered technologies in their software development practices, our research offers practical guidance to managers by identifying factors that can change negative emotions to positive emotions.

Our study makes a timely contribution to the discussions on AI and the future of work through the lens of emotions. In contrast to nascent discussions on the role of AI in high-skilled jobs that show knowledge workers' general ambivalence towards AI, we find knowledge workers show more positive emotions over time and as they engage more with AI. In addition, this study unveils the role of professional identity in leading to more positive emotions towards AI, as knowledge workers view such technology as a means of expanding their identity rather than as a threat to it.

This interview study examines Hungarian journalists' and copywriters' expectations of generative AI’s impact on their professions and factors influencing these views during a period of hype.

While acknowledging the specialized knowledge of journalists and copywriters relative to the general public, the study employs the sociology of expectations framework to interpret their anticipations not as objective forecasts of the future, but rather as phenomena shaped by diverse influences. The research comprises 30 semi-structured interviews conducted in spring 2023 to explore these expectations and their contributing factors.

Results reveal ChatGPT’s media coverage as pivotal, encouraging the professionals interviewed to experiment with AI, reassess their roles, and cause a shift in their job expectations. At the same time, this shift was limited. Skepticism about hyperbolic media formulations, their own experiences with ChatGPT and projecting its constraints into the future, contextual factors, and optimism bias contributed to moderating their expectations. They perceived AI as an enhancer of efficiency and quality, not as a radical disruptor. Copywriters were more open to integrating AI in their work, than journalists.

The results underscore the importance of further research to explore subjective experiences associated with technological change, particularly considering their complex social, psychological, and cultural influences.

The study uniquely contributes to the sociology of expectations by highlighting how a complex interplay of factors can shape professionals' anticipation of the impact of AI on their careers, including optimism bias and media hype.

This study aims to minimize the pressure drop across wavy microchannels using secondary branches without compromising its capacity to transfer the heat. The impact of secondary flows on the pressure drop and heat transfer capabilities at different Reynolds numbers are investigated numerically for different wavy microchannels. Finally, different channels are evaluated using performance evaluation criteria to determine their effectiveness.

To investigate the flow and heat transfer capabilities in wavy microchannels having secondary branches, a 3D conjugate heat transfer model based on finite volume method is used. In conventional wavy microchannel, secondary branches are introduced at crest and trough locations. For the numerical simulation, a single symmetrical channel is used to minimize computational time and resources and the flow within the channels remains single-phase and laminar.

The findings indicate that the suggested secondary channels notably improve heat transfer and decrease pressure drop within the channels. At lower flow rates, the secondary channels demonstrate superior performance in terms of heat transfer. However, the performance declines as the flow rate increased. With the same amplitude and wavelength, the introduction of secondary channels reduces the pressure drop compared with conventional wavy channels. Due to the presence of secondary channels, the flow splits from the main channel, and part of the core flow gets diverted into the secondary channel as the flow takes the path of minimum resistance. Due to this flow split, the core velocity is reduced. An increase in flow area helps in reducing pressure drop.

Many complex and intricate microchannels are proposed by the researchers to augment heat dissipation. There are challenges in the fabrication of microchannels, such as surface finish and achieving the required dimensions. However, due to the recent developments in metal additive manufacturing and microfabrication techniques, the complex shapes proposed in this paper are feasible to fabricate.

Wavy channels are widely used in heat transfer and micro-fluidics applications. The proposed wavy microchannels with secondary channels are different when compared to conventional wavy channels and can be used practically to solve thermal challenges. They help achieve a lower pressure drop in wavy microchannels without compromising heat transfer performance.

This paper aims to overcome the inability of both comparing loss costs and accounting for production resource losses of Overall Equipment Effectiveness (OEE)-related approaches.

The authors conducted a literature review about the studies focusing on approaches combining OEE with monetary units and/or resource issues. The authors developed an approach based on Overall Equipment Cost Loss (OECL), introducing a component for the production resource consumption of a machine. A real case study about a smart multicenter three-spindle machine is used to test the applicability of the approach.

The paper proposes Resource Overall Equipment Cost Loss (ROECL), i.e. a new KPI expressed in monetary units that represents the total cost of losses (including production resource ones) caused by inefficiencies and deviations of the machine or equipment from its optimal operating status occurring over a specific time period. ROECL enables to quantify the variation of the product cost occurring when a machine or equipment changes its health status and to determine the actual product cost for a given production order. In the analysed case study, the most critical production orders showed an actual production cost about 60% higher than the minimal cost possible under the most efficient operating conditions.

The proposed approach may support both production and cost accounting managers during the identification of areas requiring attention and representing opportunities for improvement in terms of availability, performance, quality, and resource losses.

This author reflects on her academic career spanning three decades as a Black woman in higher education. Ironically, the elders' sayings she heard and detested as a child resonated throughout her career. While in eighth grade, her grandmother admonished her for being deceptive and trying “to pull one over” on her and said that this author would need “to get up ‘fore day in the mornin’” to accomplish that feat. “Fore day in the mornin” must have been the time before her grandmother was fully alert, astute, and had the most clarity. For Black women to succeed in the academy, we must remain alert and recognize when faculty, administrators, and students attempt to pull one over with microaggressions and other forms of resistance. Microaggressions and resistance were perpetrated across race and gender lines, and occasionally by those who look like her. Having been reared in urban and low-income communities, the author acknowledged the investments she received throughout her schooling and career from both members of the academy and from Black communities. Consequently, her mission to improve outcomes in schools and communities, much like those in which she grew up, has not changed in 33 years. Understanding race and culture in self-definition and identity are discussed, followed by embracing opportunities and return on investments. There are increased calls for reciprocal and culturally responsive mentor–protégé relationships and successful strategies for tenure and promotion. The author makes meaning of both successful and challenging critical incidents in the academy.