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Artificial intelligence (AI) has received much attention due to its promethean-like powers to transform the management and delivery of public sector services. Due to the proliferation of research articles in this context, research to date is fragmented into research streams based on different types of AI technologies or a specific government function of the public sector (e.g. health, education). The purpose of this study is to synthesize this literature, identify challenges and opportunities, and offer a research agenda that guides future inquiry.

This paper aggregates this fragmented body of knowledge by conducting a systematic literature review of AI research in public sector organisations in the Chartered Association of Business Schools (CABS)-ranked journals between 2012 and 2023.

The search strategy resulted in the retrieval of 2,870 papers, of which 61 were identified as primary papers relevant to this research. These primary papers are mapped to the ten classifications of the functions of government as classified by the Organisation for Economic Co-operation and Development (OECD), and the reported challenges and benefits aggregated.

This study advances knowledge by providing a state-of-the-art of AI research based the OECD classifications of government functions, reporting of claimed benefits and challenges and providing a research agenda for future research.

Financial instability and economic crises are closely intertwined. There is no universally accepted definition. The term ‘stability’ or ‘instability’ refers to the behaviour of the system rather than to individual institutions. However, one cannot rule out that failure of a single financial institution can trigger significant financial turmoil as was happened in 2007–08 global financial crises. Like unstable equilibrium, instability implies inability to correct itself on its own. Instability, if it persists, turns into a crisis. In the above backdrop, the objective of this chapter is to investigate the financial crises and instability viewed both from economic and international political economy perspectives with a tale of four generation crisis models as it has been evolved over time to explain the phenomenon of different types of crises.

Stockbrokers’ frauds in India frequently occur, causing investors significant financial loss. This study aims to unfold the various dubious practices adopted by stock brokers in the recent past to defraud investors and the necessary corrective regulations passed by the market regulator to prevent and detect fraud.

The authors conduct exploratory research using a collective model of literature review, case studies and regulatory changes.

The authors find tightening the system’s loopholes and strengthening the regulatory system using technology helps in the early detection and prevention of fraud. Media activism and investors’ awareness play a role in reducing incidences of fraud.

This study unfolds the practices followed by stock brokers to defraud investors, indicative of regulatory gaps and enforcement lapses. Regulators are evolving a robust system to curb these practices and make them on par with international standards. But, it has a long way to go.

Robust fraud detection and prevention mechanism is desirable to restore investors’ confidence in the stock market. Regulators should focus on investors’ protection and education and whistleblowers’ protection. Compared to the market regulators worldwide, the Securities and Exchange Board of India has less power to identify, detect and punish fraudulent brokers and needs to be empowered.

Besides the regulatory changes, strict enforcement and investor campaigns are required to increase public awareness and restore trust in the stock market to combat the recurrence of fraud.

This paper can be helpful to regulators, investors and financial intermediaries like stock brokers and aid in strengthening the reliability of capital markets and restoring investors’ confidence.

This paper aims to investigate the heterogeneous effects of macroeconomic and financial factors across various distributions of financial deepening in 22 African countries over the past two decades (2000–2019).

The paper uses a recent method of moments quantile regression, which accounts for the often overlooked heterogeneity effects. The analysis focuses on the banking sector, which is predominant in Africa, using a broad range of macroeconomic and financial indicators.

The findings show that gross domestic product per capita positively and significantly impacts financing deepening with an increasing marginal benefit as depth increases. Trade openness positively and substantially affects only high financial deepening. Real interest rate, real exchange rate and inflations negatively and significantly affect financial deepening, especially at higher than lower levels. Financial stability positively and substantially influences financial deepening with an increasing marginal benefit as the depth increases. Bank lending interest rate, bank lending–deposit rate spread, bank concentration and return on equity negatively and substantially impact higher levels of financial deepening than lower levels.

These findings are crucial to policymakers and development partners, as promoting a favourable financial environment and stable macroeconomic policies based on the heterogeneity of financial depths can increase debt financing in Africa.

To the best of the authors’ knowledge, this paper is one of the first attempts to analyse the heterogeneous effects of macroeconomic and financial determinants on varying levels of financial depth in Africa.

This study aims to comprehensively address the challenge of delineating traffic scenarios in video footage captured by an embedded camera within an autonomous vehicle.

This methodology involves systematically elucidating the traffic context by leveraging data from the object recognition subsystem embedded in vehicular road infrastructure. A knowledge base containing production rules and logical inference mechanism was developed. These components enable real-time procedures for describing traffic situations.

The production rule system focuses on semantically modeling entities that are categorized as traffic lights and road signs. The effectiveness of the methodology was tested experimentally using diverse image datasets representing various meteorological conditions. A thorough analysis of the results was conducted, which opens avenues for future research.

Originality lies in the potential integration of the developed methodology into an autonomous vehicle’s control system, working alongside other procedures that analyze the current situation. These applications extend to driver assistance systems, harmonized with augmented reality technology, and enhance human decision-making processes.

Mindfulness is the human ability to be fully present, aware of where we are and what we're doing. This study explores on the impact of mindfulness on different elements of knowledge management, knowledge creation, knowledge sharing and knowledge hiding.

The authors undertake an inductive reasoning approach whereby they try to generate themes from specific observations and conceptualize the theory of mindfulness and knowledge transfer.

This study finds out that mindfulness critically facilitates an open environment and enhances the clarity of thought which aids in effective knowledge creation. Such a realistic understanding about the present scenario encourages employees to share knowledge and equips them to collaborate and effectively work in teams. Surprisingly, this study also finds that mindfulness increases the result orientation to the extent that employees tried to hide knowledge from their co-workers targeting certain self-desired outcomes. In other words, similar to knowledge creation and knowledge sharing, mindfulness increases agenda-based knowledge hiding.

The theory of mindfulness and knowledge transfer states that mindfulness increases knowledge creation, knowledge sharing and agenda-based knowledge hiding.

Due to the global labor shortage, the labor-heavy and high turnover hospitality industry is now recruiting from nontraditional sources. This study aims to investigate the views of people in the hotel industry to better understand how people with disabilities can obtain jobs in the hotel industry and how they are treated.

The study used a constructivist approach to grounded theory. Interviews were conducted with senior managers, middle managers and line-level employees at both internationally branded and locally branded hotels and who worked at upscale and midscale hotels to tell their perspectives about recruiting and working with people with disabilities.

Senior managers showed positive attitudes toward hiring people with disabilities but lacked pragmatic considerations about their integration into teams. Middle managers were the most hesitant, primarily due to practical concerns about accommodating their workplace needs. Line-level staff at midscale hotels were more open to working with colleagues with disabilities compared to those at high-end properties.

Limited research has been conducted on the broad perspectives regarding workers with disabilities in the hospitality industry. The study reveals not only the impact of managerial level on managers’ perspectives, but also how hotel class influenced the views of the coworkers and potential coworkers of people with disabilities. These distinctions not only help to advance our theoretical understanding of careers and hospitality labor markets but also inform operators on how to best integrate and recruit people with disabilities.

The participation of females in economic activity remains a challenge, and received a lot of attention for a better labor policy discourse. The empirical research focused widely on the relationship between female labor force participation (FLFP) and economic development, called the feminization U-shape hypothesis. However, the linear/nonlinear relationship has been questioned due to empirical and methodological anomalies. Hence, this study aims to extend the previous work by reexamining this relationship in Pakistan.

The annual data from 1980 to 2021, the unit root tests augmented Dickey–Fuller and Phillips and Perron, the conventional autoregressive distributed lag bound test approach by including the quadratic-term of GDP per capita and the novel Sasabuchi–Lind–Mehlum (SLM) U test (2010) used for empirical estimation.

The findings revealed the prospects of a long-run nonlinear association between FLFP and economic development in Pakistan. However, an inverse U-shape exists between the female labor force participation rate (FLFPR) and GDP per capita, predicting that FLFP may decline in the future.

The traditional feminization U-shape hypothesis has little empirical support in the case of Pakistan. Therefore, the Government of Pakistan should enhance the enabling environment for females through the provision of better job opportunities, technical skills, on-the-job training and social security benefits during all phases of economic development.

The conventional approach of testing U-shape is insufficient. To the best of the authors’ knowledge, therefore, this study incorporated a wider data set in a time series that is less evident, an advanced methodology SLM U test (2010), to validate the feminization U-shape hypothesis in Pakistan for the first time.