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The present study assesses the commercial bank profit efficiency and its relationship to banking sector competition in a rapidly growing emerging economy, India from 2009 to 2019 using stochastic frontier analysis (SFA).

Lerner indices, conventional and efficiency-adjusted, quantify competition. Two SFA models are employed to calculate alternative profit efficiency (inefficiency) scores: the two-step time-decay approach proposed by Battese and Coelli (1992) and the recently developed single-step pairwise difference estimator (PDE) by Belotti and Ilardi (2018). In the first step of the BC92 framework, profit inefficiency is calculated, and in the second step, Tobit and Fractional Regression Model (FRM) are utilized to evaluate profit inefficiency correlates. PDE concurrently solves the frontier and inefficiency equations using the maximum likelihood process.

The results suggest that foreign banks are less profit efficient than domestic equivalents, supporting the “home-field advantage” hypothesis in India. Further, increasing competition drives bank managers to make riskier lending and investment choices, decreasing bank profit efficiency. However, this effect varies depending on bank ownership and size.

Literature on the competition bank efficiency link is conspicuously scant, with a focus on technical and cost efficiency. Less is known regarding the influence of competition on bank profit efficiency. The article is one of the first to examine commercial bank profit efficiency and its relationship to banking sector competition. Additionally, the study work represents one of the first applications of the FRM presented by Papke and Wooldridge (1996) and the PDE provided by Belotti and Ilardi (2018).

This empirical study aims to explore how actors in specific human resource practices (HRPs) such as line managers (LMs) impact employee productivity measures in the context of financial institutions (FI) banks.

This cross-country study adopted a qualitative methodology. It employed semi-structured interviews to collect data from purposefully selected 12 business facing directors (BFDs) working in the top 10 banks in Nigeria and the UK. The data collected were analysed with the help of the trans-positional cognition approach (TPCA) phenomenological method.

The findings of a TPCA analytical process imply that in the UK and Nigeria’s FIs, the BFDs line managers’ human resources practices (LMHRPs) resulted in a highly regulated workplace, knowledge gap, service operations challenges and subjective quantitatively driven key performance indicators, considered service productivity paradoxical elements. Although the practices in the UK and Nigerian FIs had similar labels, their aggregates were underpinned by different contextual issues.

To support LMs in better understanding and managing FIs BFDs productivity measures and outcomes, we propose the Managerial Employee Productivity Operational Definition framework as part of their toolkit. This study will be helpful for banking sectors, their regulators, policymakers, other FIs’ industry stakeholders and future researchers in the field.

Within the context of the UK and Nigeria’s FIs, this study is the first attempt to understand how LMHRPs impact BFDs productivity in this manner. It confirms that LMHRPs result in service productivity paradoxical elements with perceived or lost productivity implications.

This study aims to propose a research model integrating technology acceptance model 3 (TAM3) constructs and human aspects of humanoid service robots (HSRs), measured by the Godspeed questionnaire series and tested across two hotel properties in Japan and the USA.

Potential participants were approached randomly by email invitation. A final sample size of 395 across two hotels, one in Japan and the other in the USA, was obtained, and the data were analysed using structural equation modelling.

The results confirm that perceived usefulness, driven by subjective norms and output quality, and perceived ease of use, driven by perceived enjoyment and absence of anxiety, are the immediate direct determinants of users’ re-patronage intentions for HSRs. Results also showed that users prefer anthropomorphism, perceived intelligence and the safety of an HSR for reusing it.

The findings have practical implications for the hospitality industry, suggesting multiple attributes of an HSRs that managers need to consider before deploying them in their properties.

The current study proposes an integrated model determining factors that affect the re-patronage of HSRs in hotels.

This research is aimed at preparing landslide susceptibility using spatial analysis and soft computing machine learning techniques based on convolutional neural networks (CNNs), artificial neural networks (ANNs) and logistic regression (LR) models.

Using the Geographical Information System (GIS), a spatial database including topographic, hydrologic, geological and landuse data is created for the study area. The data are randomly divided between a training set (70%), a validation (10%) and a test set (20%).

The validation findings demonstrate that the CNN model (has an 89% success rate and an 84% prediction rate). The ANN model (with an 84% success rate and an 81% prediction rate) predicts landslides better than the LR model (with a success rate of 82% and a prediction rate of 79%). In comparison, the CNN proves to be more accurate than the logistic regression and is utilized for final susceptibility.

Land cover data and geological data are limited in largescale, making it challenging to develop accurate and comprehensive susceptibility maps.

It helps to identify areas with a higher likelihood of experiencing landslides. This information is crucial for assessing the risk posed to human lives, infrastructure and properties in these areas. It allows authorities and stakeholders to prioritize risk management efforts and allocate resources more effectively.

The social implications of a landslide susceptibility map are profound, as it provides vital information for disaster preparedness, risk mitigation and landuse planning. Communities can utilize these maps to identify vulnerable areas, implement zoning regulations and develop evacuation plans, ultimately safeguarding lives and property. Additionally, access to such information promotes public awareness and education about landslide risks, fostering a proactive approach to disaster management. However, reliance solely on these maps may also create a false sense of security, necessitating continuous updates and integration with other risk assessment measures to ensure effective disaster resilience strategies are in place.

Landslide susceptibility mapping provides a proactive approach to identifying areas at higher risk of landslides before any significant events occur. Researchers continually explore new data sources, modeling techniques and validation approaches, leading to a better understanding of landslide dynamics and susceptibility factors.

This study aimed to evaluate the potential of artificial intelligence (AI) as a tool for knowledge synthesis, the production of written content and the delivery of coaching conversations.

The research employed the use of experts to evaluate the outputs from ChatGPT's AI tool in blind tests to review the accuracy and value of outcomes for written content and for coaching conversations.

The results from these tasks indicate that there is a significant gap between comparative search tools such as Google Scholar, specialist online discovery tools (EBSCO and PsycNet) and GPT-4's performance. GPT-4 lacks the accuracy and detail which can be found through other tools, although the material produced has strong face validity. It argues organisations, academic institutions and training providers should put in place policies regarding the use of such tools, and professional bodies should amend ethical codes of practice to reduce the risks of false claims being used in published work.

This is the first research paper to evaluate the current potential of generative AI tools for research, knowledge curation and coaching conversations.

Prior research has extensively examined how bringing technology from work into the non-work life domain creates conflict, yet the reverse pathway has rarely been studied. The purpose of this study is to bridge this gap and examine how the non-work use of smartphones in the workplace affects work–life conflict.

Drawing from three literature streams: technostress, work–life conflict and role boundary theory, the authors theorise on how limiting employees' ability to integrate the personal life domain into work, by means of technology use policy, contributes to stress and work–life conflict. To test this model, the authors employ a natural experiment in a company that changed its policy from fully restricting to open smartphone access for non-work purposes in the workplace. The insights gained from the experiment were explored further through qualitative interviews.

Work–life conflict declines when a ban on using smartphones for non-work purposes in the workplace is revoked. This study's results show that the relationship between smartphone use in the workplace and work–life conflict is mediated by sensed stress. Additionally, a post-hoc analysis reveals that work performance was unchanged when the smartphone ban was revoked.

First, this study advances the authors' understanding of how smartphone use policies in the workplace spill over to affect non-work life. Second, this work contributes to the technostress literature by revealing how, in specific situations, engagement with ICT can reduce distress and strain.

The aim of this study is to empirically explore and analyze the concrete tasks of output measurement and the inherent challenges related to these tasks in a traditional and autonomous professional public work setting – the judicial system.

The analysis of the tasks is based on a categorization of general performance measurement motives (control-motivate-learn) and main stakeholder levels (society-organization-professionals). The analysis is exploratory and conducted as an empirical content analysis on materials and reports produced in two performance improvement projects conducted in European justice organizations.

The identified main tasks in the different categories are related to managing resources, controlling performance deviations, and encouraging improvement and development of performance. Based on the results, key improvement areas connected to output measurement in professional public organizations are connected to the improvement of objectivity and fairness in budgeting and work allocation practices, improvement of output measures' versatility and informativeness to highlight motivational and learning purposes, improvement of professional self-management in setting output targets and producing outputs, as well as improvement of organizational learning from the output measurement.

The paper presents empirically founded practical examples of challenges and improvement opportunities related to the tasks of output measurement in professional public organization.

This paper fulfils an identified need to study how general performance management motives realize as concrete tasks of output measurement in justice organizations.

This research paper aims to investigate the effects of internal audit’s (IA) use of data analytics and the performance of consulting activities on perceived IA quality.

The authors conduct a 2 × 2 between-subjects experiment among upper and middle managers where the use of data analytics and the performance of consulting activities by internal auditors are manipulated.

Results highlight the importance of internal auditor use of data analytics and performance of consulting activities to improve perceived IA quality. First, managers perceive internal auditors as more competent when the auditors use data analytics. Second, managers perceive internal auditors’ recommendations as more relevant when the auditors perform consulting activities. Finally, managers perceive an improvement in the quality of relationships with internal auditors when auditors perform consulting activities, which is strengthened when internal auditors combine the use of data analytics and the performance of consulting activities.

From a theoretical perspective, this research builds on the IA quality framework by considering digitalization as a contextual factor. This research focused on the perceptions of one major stakeholder of the IA function: senior management. Future research should investigate the perceptions of other stakeholders and other contextual factors.

This research suggests that internal auditors should prioritize the development of the consulting role in their function and develop their digital expertise, especially expertise in data analytics, to improve perceived IA quality.

This research tests the impacts of the use of data analytics and the performance of consulting activities on perceived IA quality holistically, by testing Trotman and Duncan’s (2018) framework using an experiment.

Prior research has emphasised the importance of the early phases of construction projects, as well as the difficulties of procuring engineering services – especially due to the uncertainties. Despite that, studies on the public procurement of engineering services are scarce. Although scholars have shown that uncertainty may affect the choice of control modes, the level of uncertainty that characterises services is not addressed by the two task characteristics: knowledge of the transformation process and output measurability. The purpose is to investigate organisational control in public procurement of engineering services.

The existing control model was adjusted in this study by conceptually adding uncertainty as a third aspect to the two task characteristics. A single case study of the Swedish Transport Administration was used. The empirical data, comprising 14 interviews with managers from the client and engineering consulting companies, were analysed using flexible pattern matching and visual mapping approaches and then illustrated using the model.

The public client did not base its choice of control modes on uncertainty, but rather on the other two task characteristics. Consequently, the service providers argued that the chosen control modes reduced their creativity, increased their financial risks and caused unclear responsibilities. This study therefore shows that uncertainty is an important factor to consider in the choice of control modes, both from a theoretical perspective and from the service providers' point of view. The developed model may therefore be useful for researchers as well as practitioners.

This study is the first attempt to add uncertainty as a task characteristic when choosing control modes. The results contribute to the scarce control literature regarding the procurement of engineering services for construction projects and the procurement of other services with high uncertainty.

Improving the quality of madrasah in the digital era is a must. This can be committed by strengthening aspects of madrasah governance through implementing management strategies that refer more to the integration of technology and Islamic education. This research focuses on madrasah management strategies through the Madrasah Reform program.

This research uses a case study research design that focuses attention on strategic aspects of developing madrasah through the Madrasah Reform program. The informants in this study were 18 people consisting of three madrasah heads from Madrasah Ibtidaiyah (MI), Madrasah Tsanawiyah (MTs) and Madrasah Aliyah (MA), five teachers and 10 students. Data collection in this study used in-depth and semi-structured interviews with madrasah heads and teachers regarding the implementation of the Madrasah Reform program and also regarding madrasah management strategies at three levels of education.

This study shows that the strategy of managing madrasahs through the Madrasah Reform program in three madrasahs in Indonesia has had a positive impact on improving the quality of madrasahs, although there are still aspects that require development.

This research implies that the quality of madrasah in the digital era is determined by management strategies based on the use of educational technology.

This program has implications for the development of the quality of human resources in educational institutions, especially in relation to digital literacy among students and teaching staff. The use of digital technology, which is one of the main projections of the Madrasah Reform program, is continuously able to change the face of education in a more modern direction, both in terms of governance and the learning process, so that the output of this program, especially what occurs at Madrasah Madani, is significant development in the aspects of digital literacy and technology. Which is the main criterion in facing a digital-based educational context.

For a policy aspect, the success of the Madrasah Reform program at Madrasah Madani can be used as a blueprint or model for implementing this program in Islamic educational institutions, specifically Madrasas in South Sulawesi and in general at Madrasas throughout Indonesia.

This proves that Madrasah Reform program is a program that can be implemented in madrasahs to improve the quality of madrasah management in the digital era while continuing to carry out simultaneous improvements and evaluations of the program.