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This study aims to explore the influence of health-care service quality on customers’ perceived value, satisfaction, effectiveness and behavioural intention concerning district health centres (DHCs) in Hong Kong. This research also intends to assess customers’ perception of the subsidy scheme and its influence on the relationships amongst the aforementioned constructs.

The convenience and snowball sampling approaches were adopted, and the self-administered questionnaire was sent to 309 customers of DHCs.

Service quality attributes in terms of staffing and procedures positively increased customers’ perceived value and staffing, procedures and operations. Physical facilities positively promoted customers’ satisfaction, consequently improving DHCs’ effectiveness and behavioural intention. However, core treatments and services of DHCs did not impact customers’ perceived value and satisfaction. Furthermore, customers receiving subsidies exhibited a more positive perception than those without subsidies.

Health-care organisations are advised to strategically allocate resources (staffing, facilities and procedures and operations management) to optimise overall performance outcomes. DHC operators could reinforce the core services of DHCs and health-care voucher subsidies to local citizens so as to enhance the effectiveness of DHCs and behavioural intention of customers.

This study integrates the input–process–output approach in measuring the effectiveness of and customers’ behavioural intention towards newly established DHCs.

This study aims to examine the effect of application architecture and application efficiency on the intention to continue using Islamic bank with data security as a moderator. The investigation was situated within the framework of a hacker attack that compromised the security of customer data at one of Indonesia’s largest Islamic bank.

A survey questionnaire method was used, and the sample population comprised users of Islamic bank in Indonesia. The respondents were then selected purposively with the criteria of individuals who were using mobile banking services. Furthermore, data collection in this study was carried out by distributing questionnaires online. To validate the questionnaire, consultation and validation were conducted by engaging four experts and conducting a pilot study. Hypothesis testing was performed using the structural equation modeling method based on partial least squares.

The results of the partial least square structural model assessment showed that application efficiency and data security positively influenced the intention to continue using Islamic bank, while application architecture had no effect. Furthermore, data security could not moderate the relationship between application architecture and efficiency toward the intention to continue using Islamic bank.

The results of this study suggested that Islamic banking practitioners must prioritize the enhancement of digital banking services, with a specific focus on improving application efficiency and ensuring robust data security. These two dimensions were critical determinants influencing the intention to continue using Islamic bank.

This study addressed the issue of data security as a moderator, particularly in the context of hacker attacks targeting a major Islamic bank in Indonesia. Furthermore, this current report expounded on the study conducted by Mir et al. (2022) by introducing novel dimensions to the e-service quality of internet banking.

The present research investigates the effects of green supply chain management (GSCM) practices on customer behavioural intentions (e.g. word of mouth [WOM], willingness to pay [WTP] and revisit intention [RI]) and the mediating role of customer satisfaction (CS) in the hospitality industry in Bangladesh.

The authors applied a convenience sampling approach to distribute questionnaires and collect opinions from 404 customers who stayed in Bangladesh's five- and four-star hotels. SmartPLS was applied to examine the proposed hypothesised model.

GSCM practices have positive and significant impacts on CS and behavioural intentions of customers' WOM, WTP and RI. Additionally, CS mediates the association between GSCM practices and three behavioural intentions.

To boost their hotel's financial performance, hoteliers should allocate more resources to improving environmental sustainability practices in supply chain management.

This study's novel contribution to the literature rests in the findings regarding the mediating effect of CS. This adds value to the theory of planned behaviour. Another unique contribution of this study is that it combines three behavioural intentions (willingness to pay, RI and WOM).

This paper explores the Adoption of Technological Innovation (ATI) in the healthcare industry. It investigates how the literature has evolved, and what are the emerging innovation dimensions in the healthcare industry adoption studies.

We followed a mixed-method approach combining bibliometric methods and topic modeling, with 57 papers being deeply analyzed.

Our results identify three latent topics. The first one is related to the digitalization in healthcare with a specific focus on the COVID-19 pandemic. The second one groups up the word combinations dealing with the research models and their constructs. The third one refers to the healthcare systems/professionals and their resistance to ATI.

The study’s sample selection focused on scientific journals included in the Academic Journal Guide and in the FT Research Rank. However, the paper identifies trends that offer managerial insights for stakeholders in the healthcare industry.

ATI has the potential to revolutionize the health service delivery system and to decentralize services traditionally provided in hospitals or medical centers. All this would contribute to a reduction in waiting lists and the provision of proximity services.

The originality of the paper lies in the combination of two methods: bibliometric analysis and topic modeling. This approach allowed us to understand the ATI evolutions in the healthcare industry.

This study aims to explore the effect of whistleblowing and interpretation among practitioners in the Nigerian economy. The research puts a premium on understanding the relevance and critical issues in its practices and developing an improved model for the effective practice of whistleblowing and interpretation in Nigeria.

This study adopted a conceptual approach, relying on extant literature to understand the management of whistleblowing incidents and identify the managers’ and other stakeholders’ responsibility in the whistleblowing process. It applied systems dynamics conceptual modelling and presented an improvement approach to addressing the complexities associated with whistleblowing and interpretation among Nigerian organizations.

This study contributed to the extant literature by developing a model for proper management of whistleblowing in the Nigerian context and enhancing the robust practice of whistleblowing and interpretation in Nigeria. The findings highlighted critical factors such as managers’ skills development, legal system support, institutional stakeholders’ function and ethical balance as key factors to effective whistleblowing management and interpretation. This implies that the act of identifying and developing responses to an emerging case of whistleblowing requires a process of developing underpinning assumptions, engagement and consideration of stakeholders’ interests while driving the sustenance of organizational focus.

This study emphasized the departure from absolute best practice to developing idea approaches that reflect stakeholders’ interests and the context of whistleblowing and interpretation. While the study acknowledges limitations in the sole focus on the Nigerian private sector and the Nigerian economic background, it recommends further exploration of whistleblowing and its interpretation on a comparative approach, to improving the current understanding of the topic.

This paper aims to investigate the effect of product offering and other service quality (SQ) dimensions on the satisfaction of the customers of both Islamic and conventional banks, using evidence from an oil-based economy that is based on a prolonged SERVQUAL model with 11 dimensions and other statistical analysis methods.

The data were collected from 461 Islamic and conventional bank customers in Qatar via a survey and several tests were used to test certain hypotheses. Component analysis, factor analysis and gap and ascendency analysis were used in this study. Afterward, a correlation analysis and regression model were used to examine the hypotheses and validate the instruments used.

The results show that regardless of the type of bank, customers always have greater expectations of the services than they had perceived. A customer’s expectation of the product on offer is the only dimension that is significantly different in relation to the two types of banks. However, reliability, competence, responsiveness, credibility and empathy dimensions are significantly different of the two types of banks in customers’ perception of quality. In addition, the results suggest that both types of banks need to concentrate their efforts on the product offering, competence and courtesy dimensions.

The size of our sample of Islamic and conventional banks is unequally balanced. Future studies might therefore choose an equally balanced sample.

Bank managers in both types of banks need to continue improving the quality of their service including product offering and to adopt advanced methods to enhance customer satisfaction (CS) and reduce the gaps in quality in the dimensions used. Furthermore, managers in both types of banks need to put more emphasis on product offering, competence, courtesy and communication if they wish to improve SQ. Moreover, Islamic banks must guarantee that they possess competent, highly trained personnel who are familiar with Islamic finance products, so as to enhance the quality of service and attract customers.

To the best of the author’s knowledge, this is the first study to investigate the effect of product offering and other dimensions of SQ on CS in both Islamic and conventional banks by using 11 dimensions of SQ. In addition, it provides evidence of gaps in SQ, at the dimensions level, for both types of banks in an oil-based economy. The results of this study are valuable in helping decision-makers and bank managers who wish to raise the level of SQ and improve CS and in validating the results from other countries with a dual financial system.

This study aims to investigate the influence of ChatGPT, an AI-based chatbot, on the digital learning experience of students at Mzumbe University.

This study adopted a qualitative research design to gather in-depth insights from participants. Semi-structured interviews and an analysis of previous chat content were used as primary sources of data. Thematic analysis was used to analyze the qualitative data, allowing for the exploration of participants’ perspectives, experiences and opinions regarding the integration of ChatGPT into the learning process.

The results of the study demonstrated that ChatGPT is widely used in educational contexts and has a positive influence on students’ study habits, academic performance, and understanding of course material. Students appreciated the system’s simplicity, tailored instructions, and the promptness and accuracy of the responses. Despite the possibility of isolated mistakes.

It is important to recognize the limitations of this study. First, the sample size was small, limiting the broad application of the results. Second, this study’s narrow emphasis on students at Mzumbe University limits its applicability in other situations. Furthermore, depending on self-reported experiences, biases, such as individual interpretation or recollection bias, can occur.

Educators can maximize ChatGPT in the classroom by using study insights. Its advantages, such as effectiveness and enhanced performance, highlight the possibility for student-centered learning. Practitioners are guided by their awareness of problems, such as probable errors. Constant updates guarantee ChatGPT’s applicability and provide educators with useful advice.

Peer impact is highlighted in this study concerning social factors on the adoption of AI in education. Resolving issues preserves public confidence. Views influence public opinion and direct policymakers in discussions about safe AI use. It influences public attitudes while navigating the ethical integration of AI.

This study offers insightful information about the impact of ChatGPT on digital learning in Tanzania’s higher education. It makes innovative research contributions that enhance educational practices and emphasizes the advantages, difficulties and demands of responsible usage in the context of AI-based chatbots.

Although training is essential to continuous improvement, scant literature examines post-training facilitators for continuous improvement. The study aims to explore the relationship between training and continuous improvement, the mediating role of self-efficacy and the moderate role of training transfer climate.

This study utilizes the questionnaire survey of 455 Vietnamese employees to test the link between continuous improvement training and continuous improvement, the moderate role of the training transfer climate and the mediating role of self–efficacy.

Research results reveal that training positively influences continuous improvement. Furthermore, self-efficacy fully intervenes in the link between training and continuous improvement. Finally, the training transfer climate positively moderates this link.

Although the link between training and continuous improvement is suspicious, there is scant research on post-training facilitators of continuous improvement applications. To the best of the author's knowledge, this study is one of the first to explore the moderation role of transfer climate and the mediation role of self-efficacy in the relationship between training and continuous improvement.

With big data (BD), traditional supply chain is shifting to digital supply chain. This study aims to address the issues and challenges in the way toward the implementation of big data analytics (BDA) in sustainable supply chain management (SSCM).

The factors that affect the implementation of BDA in SSCM are identified through a widespread literature review. The PESTEL framework is used for this purpose as it covers all the political, economic, social, technological, environmental and legal factors. These factors are then finalized by means of experts' opinion and analyzed using structural equation modeling (SEM).

A total of 10 factors are finalized with 31 sub-factors, of which sustainable performance, competitive advantage, stakeholders' involvement and capabilities, lean and green practices and improvement in environmental performance are found to be the critical factors for the implementation of BDA in SSCM.

This research has taken up the case of Indian manufacturing industry. It can be diversified to other geographical areas and industry sectors. Further, the quantitative analysis may be undertaken with structured or semi-structured interviews for validation of the proposed model.

This research provides an insight to managers regarding the implementation of BDA in SSCM by identifying and examining the influencing factors. The results may be useful for managers for the implementation of BDA and budget allocation for BDA project.

The result includes green practices and environmental performance as critical factors for the implementation of BDA in SSCM. Thus the research establishes a positive relationship between BDA and sustainable manufacturing that ultimately benefits the environment and society.

This research addresses the challenges in the implementation of BDA in SSCM in Indian manufacturing sector, where such application is at its nascent stage. The use of PESTEL framework for identifying and categorizing the factors makes the study more worthwhile, as it covers full spectrum of the various factors that affect the strategic business decisions.

The huge Muslim population has increased the demand for halal tourism products and destination factors in this niche tourism segment. Despite the growing body of research conducted regarding ChatGPT’s revolutionary impact on the tourism industry, the use of such an artificial intelligence (AI) tool in halal tourism needs more attention. This study aims to provide a comprehensive an overview of using ChatGPT in the tourism industry, specifically in halal tourism, and offer an agenda for further essential research questions exploration.

Through the intensive examination of the tourism literature dealing with AI and halal tourism, this review identifies the implications related to the use of ChatGPT for Muslim travelers and future trends in halal tourism.

This paper identified the possible utilization of ChatGPT in assisting Muslim travelers across various stages of their journey, encompassing pre-trip, staying and post-trip phases. Subsequently, this paper identified the opportunities and challenges associated with implementing ChatGPT in the context of halal tourism. Finally, the paper delves into potential avenues for future research.

The findings serve as crucial implications, contributing to the theory of halal tourism development and the applications of ChatGPT in halal tourism.

This paper provides essential foundational knowledge for upcoming research on halal tourism theory, ChatGPT and the development of halal tourism sector.