Search results

This study aims to examine the determinants of ethical decision-making (EDM) of professional accountants in Sri Lanka, drawing on Rest’s (1986) four-component EDM model. The level of corporate collapses and fraud, coupled with the high level of corruption in Sri Lanka, has highlighted the importance and the timely nature of this research in the EDM processes of Sri Lankan accountants.

Data was collected from a sample of 315 accountants through a questionnaire survey that included four written ethical vignettes and was analysed using partial least square-structural equation modelling techniques.

The findings revealed a significant relationship between ethical awareness and ethical judgement, providing support for Rest’s model. However, the study does not support Rest’s model on the direct relationship between ethical judgement and ethical intention. Intrinsic religiosity and moral intensity significantly influenced the ethical awareness of accountants. Several determinants including accountants’ age, education, intrinsic religiosity, organisational ethical culture, familiarity with the professional ethical code and moral intensity influenced ethical judgement. However, the findings did not report any significant relationships between the study’s variables and ethical intention.

The study adds to the existing literature by providing a bigger picture of how various determinants work together in one EDM model and demonstrating that the EDM of accountants is multifaceted. The new finding on an insignificant relationship between ethical judgement and ethical intention implies that the Rest’s EDM process may be mediated and moderated by other constraints blocking accountants’ intention to act due to various pressures in a corrupt society, Sri Lanka, where accountants operate.

This study investigates to what extent the values perceived by tourists throughout cultural tours impact their overall satisfaction levels and behavioral intentions related to the destination. This study further examines the moderating role of tour guide competency in the relationship patterns concerned.

Empirical data were collected via a survey from 420 foreign tourists who visited Cappadocia and participated in guided cultural tours. Partial least squares-structural equation modeling was used for data analysis.

Study results reveal that the effects of quality, emotional, monetary and social value perceptions of tourists gained through cultural tour experiences on their overall satisfaction levels and the effects of overall satisfaction on recommendation and revisit intention are positive and significant. Furthermore, the moderating role of tour guide competency is significant and positive in the relationships between quality value and satisfaction and between satisfaction and revisit intention.

This study offers a critical analysis of discoveries concerning the pivotal role of tour guide competency within the cultural tour experience.

This paper aims to examine project management segments based on customer satisfaction drivers and loyalty rather than traditional demographic or behavioural variables.

Data were gathered over 18 consecutive months, and 3,129 surveys were completed using a questionnaire. The statistical methods included partial least squares (PLS) structural equation modelling, finite mixture segmentation, prediction-oriented segmentation (PLS-POS) and multi-group analysis (PLS-MGA).

The findings indicate the existence of three segments among system delivery project customers based on the differences in the strengths of the path coefficients in the customer-centric structural model. In Segment 1, satisfaction based on the proposal was crucial for loyalty, with the value-for-money construct negatively impacting the repurchase intent construct. Segment 2 had a solid value-for-money orientation. In Segment 3, the critical path indicated that satisfaction drove repurchase intention, with satisfaction based mainly on the installation.

The research contributes to the segmentation theory by introducing a new way to segment the systems delivery projects customers based on the perceived strength of the relationships in a customer-centric structural model, which aligns with traditional segmentation theory in a way that most segmentation analyses do not. A new segmentation approach to the domain of project management theory is presented. Based on the results, treating the system delivery project customer base as a single homogenous group can lead to managerially misleading conclusions.

Partial least squares structural equation modeling (PLS-SEM) has become an established social sciences multivariate analysis technique. Since quality management researchers also increasingly using PLS-SEM, this growing interest calls for guidance.

Based on established guidelines for applying PLS-SEM and evaluating the results, this research reviews 107 articles applying the method and published in eight leading quality management journals.

The use of PLS-SEM in quality management often only draws on limited information and analysis results. The discipline would benefit from the method's more comprehensive use by following established guidelines. Specifically, the use of predictive model assessment and more advanced PLS-SEM analyses harbors the potential to provide more detailed findings and conclusions when applying the method.

This research provides first insights into PLS-SEM's use in quality management. Future research should identify the key areas and the core quality management models that best support the method's capabilities and researchers' goals.

The results of this analysis guide researchers who use the PLS-SEM method for their quality management studies.

This is the first article to systematically review the use of PLS-SEM in the quality management discipline.

This paper aims to test a contingency-based path model that concurrently links the role of management accountants (MA) and advanced manufacturing technologies (AMTs) to cost system sophistication (CSS), as well as linking the latter to improvements in organisational performance through improving cost management and product planning decisions.

This paper used the questionnaire survey strategy to collect data from 373 medium and large manufacturing business units based in the UK, then subjected the data to structural equation modelling analysis to test a contingency-based path model.

The results show that the role of MAs and AMTs positively influence CSS. Moreover, it was found that the latter is positively associated with improvements in cost management decisions which, in turn, lead to improvements in organisational performance. However, no support was found for the association between the level of CSS and improvements in product planning decisions, although the latter was found to be positively associated with organisational performance. These results confirm the theory and empirical findings regarding the role that MAs and AMTs play in designing the cost accounting system, and support the argument that adopting sophisticated cost systems does not lead directly to improvements in organisational performance, unless the benefits of such systems, in terms of improved decision-making and cost applications, are used.

This research contributes to the literature by testing a contingency-based path model that incorporates hitherto underexamined contextual factors, namely, the role of MAs and AMTs; examining the effect of CSS on a critical output, organisational performance and the mechanisms of this effect; and considering the complexity of the business environments through the concurrent testing of the relationships involved in the research model.

The aim of this study is to (1) construct a standard framework for assessing the capability of bioenergy enterprises' digital green innovation partners; (2) quantify the choice of partners for digital green innovation by bioenergy enterprises; (3) propose based on a dual combination empowerment niche digital green innovation field model.

Fuzzy set theory is combined into field theory to investigate resource complementarity. The successful application of the model to a real case illustrates how the model can be used to address the problem of digital green innovation partner selection. Finally, the standard framework and digital green innovation field model can be applied to the practical partner selection of bioenergy enterprises.

Digital green innovation technology of superposition of complementarity, mutual trust and resources makes the digital green innovation knowledge from partners to biofuels in the enterprise. The index rating system included eight target layers: digital technology innovation level, bioenergy technology innovation level, bioenergy green level, aggregated digital green innovation resource level, bioenergy technology market development ability, co-operation mutual trust and cooperation aggregation degree.

This study helps to (1) construct the evaluation standard framework of digital green innovation capability based on the dual combination empowerment theory; (2) develop a new digital green innovation domain model for bioenergy enterprises to select digital green innovation partners; (3) assist bioenergy enterprises in implementing digital green innovation practices.

This paper aims to explore students’ intention to use and actual use of the artificial intelligence (AI)-based chatbot such as ChatGPT or Google Bird in the field of higher education in an emerging economic context like Bangladesh.

The present study uses convenience sampling techniques to collect data from the respondents. It applies partial least squares structural equation modeling (PLS-SEM) for analyzing a total of 413 responses to examine the study’s measurement and structural model.

The results explore that perceived ease of use (PEOU) negatively affects intention to adopt AI-powered chatbots (IA), whereas university students’ perceived usefulness (PU) influences their IA positively but insignificantly. Furthermore, time-saving feature (TSF), academic self-efficacy (ASE) and electronic word-of-mouth (EWOM) have a positive and direct impact on their IA. The finding also reveals that students' IA positively and significantly affects their actual use of AI-based chatbot (AU). Precisely, out of the five constructs, the TSF has the strongest impact on students’ intentions to use chatbots.

Students who are not aware of the chatbot usage benefits might ignore these AI-powered language models. On the other hand, developers of chatbots may not be conscious of the crucial drawbacks of their product as per the perceptions of their multiple users. However, the findings transmit a clear message about advantages to users and drawbacks to developers. Therefore, the results will enhance the chatbots’ functionality and usage.

The findings of the study alert the teachers, students and policymakers of higher educational institutions to understand the positive outcomes and to accept AI-powered chatbots such as OpenAI’s ChatGPT. Outcomes also notify the AI-product developers to boost the chatbot’s quality in terms of timeliness, user-friendliness, accuracy and trustworthiness.

The prime purpose of the study is to analyse the effect of fintech adoption on the financial well-being of persons with disabilities (PWDs), considering the intervening role of financial behaviour, financial access and financial knowledge.

A self-administered survey schedule collected primary data on fintech adoption and financial well-being among 205 PWD, through snowball sampling from January to May 2023. Researchers used exploratory factor analysis to identify reliable factors and PLS-SEM for testing mediation and research hypotheses.

The study’s outcome found that fintech adoption does not directly impact the financial well-being of PWDs. Instead, the impact on financial well-being is explained by mediating factors like financial access, financial knowledge and financial behaviour. Financial access is the most significant among these mediating factors.

The study demonstrates the significance of mediating factors in comprehending the influence of fintech adoption on financial well-being. These results underpin existing literature on determinants of financial well-being.

Findings evidenced that developing disabled-friendly fintech tools can enhance financial access, reduce inequality and improve the financial well-being of PWDs, which would be helpful for public policymakers.

There has been no comprehensive study conducted on this topic, particularly among PWDs. In the current study, an effort is being made to examine the relative effects of fintech adoption on financial well-being directly and indirectly through mediating variables.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2023-0596

This research paper aims to explore the added value of knowledge management (KM) and its antecedents for innovation and organizational performance (OP) in marginal healthcare organizations.

Using insights from the resource-based view and knowledge-based theory of the firm, the model explains the effects of technology capabilities (TC) and organizational culture (OC) on the KM process, process innovation (PIN), administrative innovation (AIN) and OP. The authors used partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to analyze data collected from 168 healthcare practitioners in Cameroon using a survey.

The authors reveal that TC and OC positively impact some KM components. Knowledge sharing (KS), knowledge acquisition (KA) and responsiveness to knowledge (RK) influence PIN, while only PIN and KA influence OP. FsQCA provided several configurations that lead to high OP within healthcare centers. As a result, the results are adaptable to any healthcare center that wishes to set up one or more KM processes.

Given that the results will help the health workforce make concerted decisions about medical care, the authors contribute significantly to the definition and optimization of KM in healthcare by implementing various processes and policies to ensure the continued existence of high-quality and outstanding healthcare systems. The KM propositions will enable healthcare centers to: (1) improve the quality of patient care through collegiality in medical practice; (2) optimize processes in the patient care chain; and (3) leverage knowledge gained though knowledge sharing among the medical team. The propositions open up avenues for future research in addition to providing practical implications for healthcare center practitioners.

This study sheds new empirical light on the relationships between KM antecedents and processes, innovation and OP in healthcare centers. This research is one of the few to examine the relationship between TC, OC, KM processes, innovation and OP in developing countries. This paper aims to fill this gap and inform future research concerning KM in the healthcare sector. Further, this study goes beyond testing the PLS-SEM approach's hypotheses by applying fsQCA to provide practical and comprehensive knowledge on how to increase the efficiency of a healthcare center through KM.