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This paper aims to consolidate empirical studies between 2013 and 2022 to investigate the impact of artificial intelligence (AI) in higher education. It aims to examine published research characteristics and provide insights into the promises and challenges of AI integration in academia.

A systematic literature review was conducted, encompassing 44 empirical studies published as peer-reviewed journal papers. The review focused on identifying trends, categorizing research types and analysing the evidence-based applications of AI in higher education.

The review indicates a recent surge in publications concerning AI in higher education. However, a significant proportion of these publications primarily propose theoretical and conceptual AI interventions. Areas with empirical evidence supporting AI applications in academia are delineated.

The prevalence of theoretical proposals may limit generalizability. Further research is encouraged to validate and expand upon the identified empirical applications of AI in higher education.

This review outlines imperative implications for future research and the implementation of evidence-based AI interventions in higher education, facilitating informed decision-making for academia and stakeholders.

This paper contributes a comprehensive synthesis of empirical studies, highlighting the evolving landscape of AI integration in higher education and emphasizing the need for evidence-based approaches.

Emphasizing the increasing role of talent management (TM) as a global phenomenon and a source of sustainable competitive advantage for organizations, this study aims to present a scoping review of empirical literature on TM, examining the transition of TM from a phenomenon-driven to a theory-driven field.

Using a scoping review, this study analyzed 200 empirical studies published between 2010 and 2023 on TM.

The results indicate that TM is extensively studied in nationally operated, large, private, engineering-led organizations in Anglo-Saxon countries. The study highlights the necessity for more empirical studies and statistically robust evidence to establish the effectiveness of TM.

This review intends to provide a vision and direction for future researchers, guiding TM towards becoming a theory-driven field characterized by widely accepted theoretical frameworks and research designs.

The findings of this study may not be generalizable to other types of organizations or cultural contexts, as it primarily focused on large private engineering-led organizations in Anglo-Saxon countries.

This paper offers a comprehensive view of the definitions, contextualization, conceptualization, frameworks, practices, processes and under-explored areas of TM, which are essential for its development as a discipline.

While scholars have researched the impact of specific total quality management (TQM) aspects on innovation performance (INP), empirical evidence on how the former, as a composite construct, influences the latter is rare. To add, empirical evidence on the mechanism through which TQM passes to affect innovative behaviour (INB) and, then, INP is limited. Essentially, scholars have requested that future research look at the boundary conditions that support the adoption of TQM activities in businesses. Although the banking sector has experienced a number of transformations, there is still a need to raise the standard of service provided to bank customers. This research sheds more light on this subject.

This research tests the hypotheses in Ahinful et al.’s (2023) conceptual model using responses from 260 top- and middle-level bank managers by applying Smart PLS. Organisational support and team member exchange were used as potential control variables for the mediator, while slack resources and bank size were applied to the target endogenous latent construct. Mediation and moderation effects were estimated using the variance accounted for (VAF) and product indicator approaches, respectively. Sig. level was set at 5%.

This study found that TQM and INP had a positive and significant connection (ß = 0.303, p = 0.000), and INB partially mediated this connection (VAF = 40.92%). However, government regulation (GOV; ß = 0.055, p = 0.365), market dynamism (MKD; ß = 0.063, p = 0.434), competitive intensity (CMP; ß = 0.069, p = 0.297) and technological turbulence (TUR; ß = 0.011, p = 0.865) all failed to moderate the TQM–INB connection, although the expected positive directions of these moderation relationships were established.

This research provides empirical evidence on the TQM–INP connection, how this connection may be mediated and how the TQM–INB connection may be activated. It also sheds light on novel ways in which service quality in the banking sector may be improved. Upcoming research may explore other control variables in their research. Since the moderating relationships were unsupported, this avenue is open for further research, particularly in other banking settings across the globe.

Practical lessons for bank consultants, regulators, customers, employees and managers are deliberated.

This research is novel. It is the first to test the hypotheses in Ahinful et al.’s (2023) conceptual model. This study advances the theoretical frameworks and existing knowledge within the TQM, innovation and performance management fields.

Service innovation (SI) is crucial for social and economic development. However, most of the studies about innovation relate to product/manufacturing. Aimed at enhancing the academic debate about SI, this paper intends to (1) assess the factors applied in empirical studies about SI from 2006 to 2020, (2) evaluate if researchers differentiate innovation in services from innovation in manufacturing, (3) evaluate if researchers differentiate innovation among distinct service segments within the heterogeneous service industry and (4) propose a categorization model for the factors that influence SI.

Our study employs a five-step approach for a systematic literature review of 99 relevant empirical papers from 2006 to 2020.

Our findings demonstrate a persistent lack of conceptual consolidation in the area, adding value to the ongoing dispute between opposite views on current SI's maturity level. Our results also evidence the non-observance of differentiation of innovation factors between service and manufacturing empirical papers. In addition, our paper shows an even higher lack of differentiation in the use of innovation factors among different service segments.

This paper provides the first more systematic verification of the lack of service differentiation within the empirical innovation study field. In addition, despite the abundance of factors that influence SI, the proposed categorization model offers the possibility to promote an area's conceptual consolidation. Our findings and categorization also support the debate about pathways for the field's development and help researchers in their future study designs and analyses.

This study examines how compliance with government and firm's own policy and reverse logistics practices relate with firm environmental performance.

This study draws on insights from stakeholder theory, and follows a two-phase research approach. The first phase utilized an extended literature review that seeks to provide a qualitative and comprehensive understanding of the research problem. The 2001–2023 data was collected from the Web of Science and Scopus databases, complemented with Google Scholar. The second phase involved an empirical study—adopting a quantitative cross-sectional survey design with a self-administered questionnaire to validate the theoretical conceptualizations deriving from the literature review. The empirical data were collected from 203 food and beverages manufacturing firms in Uganda and analysed using the partial least squares structural equation modelling (PLS-SEM) approach.

The study findings suggest that compliance with government policy positively influences firm environmental performance, both directly, and indirectly through fostering reverse logistics practices, and that the relationship between compliance with government policy and reverse logistics practices is contingent upon compliance with the focal firm's own policy.

The study findings will enhance the theoretical and conceptual development of the ideas that underpin stakeholder theory and applications. The Ugandan government will come up with better mechanisms for enforcing compliance with policy regulating the application of reverse logistics practices. In addition, the study advances the use of multi-method approaches in investigating interesting research aspects requiring in-depth examination. However, considering the fact that the empirical study was conducted in a single country context, and focused on firms more or less from the same sub-sector, the findings of the study might not be generalizable globally.

This study provides useful insights to logistics and supply chain managers involved in reverse logistics activities in food and beverages manufacturing firms. These managers can know how to leverage reverse logistics practices to enhance environmental performance of firms amidst environmental policies in the industry where they operate.

This study contributes to the built body of knowledge in operations, logistics and supply chain management literature; understanding about reverse logistics practices as a mechanism through which compliance with government policy influences environmental performance of firms. The interaction between compliance with government policy and compliance with firm policy is essential in explaining the performance effects of reverse logistics practices. In addition, the study advances the use of multi-method approaches in investigating interesting research aspects requiring in-depth examination. Complementing extended literature review with and empirical research to investigate reverse logistics practices influences on firm environmental performance, and incorporating the role of policy in explaining this relationship should make considerable contribution. Besides, the study highlights important areas for future research.

This paper discusses whether institutional investors change the shareholding ratio of listed companies through research meeting, and whether this active investment mode can really improve the investment efficiency of institutional investors.

Using empirical research method, this study designs and conducts an empirical research according to empirical research's basic norms. Thus, we acquire needed and credible empirical data. This study analyzes whether institutional investors seek their private interest in researched companies by analyzing their research meetings and the shareholding ratios of different types of institutional investors using Shenzhen Stock Exchange data on listed firms from 2014 to 2018.

This study finds that the research meetings of institutional investors provide participants with reliable information which supports the decision of institutional investors to change their shareholding ratio. The stock price growth rate strengthens the positive correlation between the research meetings of institutional investors and the shareholding ratio of institutional investors. Additionally, transactional institutional investors increase the shareholding ratio, while holding institutional investors do not.

This paper combines the behavior of institutional investors with the holding status of institutional investors, and discusses the impact of institutional investors' behavior on investment decisions. At the same time, it classifies the institutional investors and discusses the attitude of different types of institutional investors towards this active investment mode.

This study aims at presenting deeper insights regarding the understanding and application of the quality costs (CoQ) in the automotive manufacturing industry. The empirical research included three general determinants: reasons for, difficulties during and benefits from implementing quality costs, as well as two specific determinants: measuring and evaluating quality cost elements.

The empirical research methodology employs the expert evaluation method – the Delphi method, using a survey questionnaire comprising a total of 200 questions, and answered by 9 companies.

The survey results showed that companies do recognize the reasons for implementing quality costs as a need arising from the quality management standards, the lack of knowledge of quality costs by employees and management as the biggest difficulty while the biggest benefit includes the quality costs enhance the company competitiveness. The costs competence and qualification, the quality management system costs, the costs for improvement, the production control costs, the input control costs, the new measuring and control equipment calibration costs, the costs related to scrap, repairs and product finishing are the most significant elements of the quality costs.

This study is limited by the small number of surveyed companies from the automotive cluster.

The proposed quality costs model provides to the management to conceive CoQ elements as possible drivers in the improvement process of product quality. The structure and the nature of the CoQ elements is expected to advance the process of detailing the quality costs elements.

The novelty of this paper refers to development of a generic quality cost model, whose relevance is confirmed by the structuring of the model with elements published in literature and validating in research companies.

This paper aims to investigate the determinants that contribute to the financial stability and banking sector of Palestinian banks listed on the Palestine Stock Exchange (PEX) by using yearly data for the years 2012–2022.

Pooled ordinary least squares (OLS) and two-stage least squares (2SLS) were used to identify the variables and factors affecting the financial stability and banking sector of Palestinian banks. The study’s data were collected from the banks listed on PEX and from the yearly reports posted on the Palestine Monetary Authority’s (PMA) webpage over the years from 2012–2022. According to this research’s analysis, SMEs loans and capital sufficiency have a statistically significant positive impact on the stability of Palestinian banks. Unobserved heterogeneity, simultaneity and dynamic endogeneity are taken into account when using the 2SLS regression approach to adjust for the study endogeneity factor.

The study’s findings show that some factors and determinants might have both good and negative effects on financial stability and banking sector. Loans to small and medium-sized businesses (SMEs) and enough capital are two characteristics that statistically have a major favourable impact on the stability of Palestinian banks since they help the banks withstand deficits. A further potential discovery relates to the favourable effects of financial inclusion (FI) and digital financial services (DFS) on the stability of banks.

This research has faced some limitations, such as the lack of a defined index from the regulatory organizations, this research is based on information from bank annual accounts. It has mostly relied on self-developed or World Bank indexes. Furthermore, the research solely used information from the supply side (banks); demand-side data were not taken into consideration.

This paper has managerial implications for stability of banking sector. The Palestine Monetary Authority, as the central bank, must increase the percentage of bank loans directed to small and medium-sized companies and oblige bank management to adhere to adequate capital standards, which contributes to strengthening the Palestinian banking sector and increasing its profits. The study findings advise banks that are enjoying financial stability to speed up the pace of FI and DFSs because most of these reliable banks have relatively low FI ratios. PMA is responsible for preserving the stability of the financial system. PMA, decision makers and banks management must retain adequate liquidity in their institutions and raise client collateral expectations to raise credit conditions.

This paper adds some contributions to the literature. To adjust for discrepancies between various types of banks, the authors concentrate on conventional and Islamic banks, which enables us to use a homogenous data set as opposed to depending on dichotomous variables. The authors used Z-scores, which have recently been used in research, to measure stability and FI at the level of specific institutions. This research contributes in some key aspects that no prior research has addressed. Conventional banks are different from Islamic banks, and a number of issues might impact their stability. To evaluate the connection between FI and DFSs, it is important to consider the actions of bank regulators.

This study focuses on (re-)introducing computer simulation as a part of the research paradigm. Simulation is a widely applied research method in supply chain and operations management. However, leading journals, such as the International Journal of Operations and Production Management, have often been reluctant to accept simulation studies. This study provides guidelines on how to conduct simulation research that advances theory, is relevant, and matters.

This study pooled the viewpoints of the editorial team of the International Journal of Operations and Production Management and authors of simulation studies. The authors debated their views and outlined why simulation is important and what a compelling simulation should look like.

There is an increasing importance of considering uncertainty, an increasing interest in dynamic phenomena, such as the transient response(s) to disruptions, and an increasing need to consider complementary outcomes, such as sustainability, which many researchers believe can be tackled by big data and modern analytical tools. But building, elaborating, and testing theory by purposeful experimentation is the strength of computer simulation. The authors therefore argue that simulation should play an important role in supply chain and operations management research, but for this, it also has to evolve away from simply generating and analyzing data. Four types of simulation research with much promise are outlined: empirical grounded simulation, simulation that establishes causality, simulation that supplements machine learning, artificial intelligence and analytics and simulation for sensitive environments.

This study identifies reasons why simulation is important for understanding and responding to today's business and societal challenges, it provides some guidance on how to design good simulation studies in this context and it links simulation to empirical research and theory going beyond multimethod studies.

Following the surge of documents laying out organizations' ethical principles for their use of artificial intelligence (AI), there is a growing demand for translating ethical principles to practice through AI governance (AIG). AIG has emerged as a rapidly growing, yet fragmented, research area. This paper synthesizes the organizational AIG literature by outlining research themes and knowledge gaps as well as putting forward future agendas.

The authors undertake a systematic literature review on AIG, addressing the current state of its conceptualization and suggesting future directions for AIG scholarship and practice. The review protocol was developed following recommended guidelines for systematic reviews and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).

The results of the authors’ review confirmed the assumption that AIG is an emerging research topic with few explicit definitions. Moreover, the authors’ review identified four themes in the AIG literature: technology, stakeholders and context, regulation and processes. The central knowledge gaps revealed were the limited understanding of AIG implementation, lack of attention to the AIG context, uncertain effectiveness of ethical principles and regulation, and insufficient operationalization of AIG processes. To address these gaps, the authors present four future AIG agendas: technical, stakeholder and contextual, regulatory, and process. Going forward, the authors propose focused empirical research on organizational AIG processes, the establishment of an AI oversight unit and collaborative governance as a research approach.

To address the identified knowledge gaps, the authors present the following working definition of AIG: AI governance is a system of rules, practices and processes employed to ensure an organization's use of AI technologies aligns with its strategies, objectives, and values, complete with legal requirements, ethical principles and the requirements set by stakeholders. Going forward, the authors propose focused empirical research on organizational AIG processes, the establishment of an AI oversight unit and collaborative governance as a research approach.

For practitioners, the authors highlight training and awareness, stakeholder management and the crucial role of organizational culture, including senior management commitment.

For society, the authors review elucidates the multitude of stakeholders involved in AI governance activities and complexities related to balancing the needs of different stakeholders.

By delineating the AIG concept and the associated research themes, knowledge gaps and future agendas, the authors review builds a foundation for organizational AIG research, calling for broad contextual investigations and a deep understanding of AIG mechanisms. For practitioners, the authors highlight training and awareness, stakeholder management and the crucial role of organizational culture, including senior management commitment.