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This study aims to describe and examine the effectiveness of the mathematics-based learning method, called Accountamatics (Accounting from Mathematics perspective). The Accountamatics method is rooted in the principles of double-entry bookkeeping and the rules of debits and credits, which were initially documented by Luca Pacioli, a Mathematics Professor, in a mathematics book.

This study uses a quasi-experimental design, spanning a duration of one semester, to examine its research objectives. The participants included 230 students from the Faculty of Economics and Business in Indonesia, who were accredited by AACSB. Control variables, including gender, majors and study backgrounds, were taken into consideration. The data was analyzed using a linear regression test, followed by a comparative t-test.

The study findings show a significant positive impact of the Accountamatics method on student performance when compared to traditional learning approaches. Furthermore, the analysis indicates that the control variables examined in the study did not have a significant effect on student performance. Thus, it can be inferred that the implementation of the Accountamatics method has a beneficial effect on the academic performance of college students.

The study findings provide valuable insights for faculty members in higher education institutions, highlighting the potential benefits of incorporating mathematics-based teaching in accounting as an alternative approach for business students. These findings contribute to the existing knowledge on innovative teaching methods that can enhance the study of accounting within the business curriculum.

Over the span of around 25 years, extensive research has been conducted to compare traditional teaching methods with innovative approaches. However, the results have not consistently shown that the innovative methods outperform their traditional counterparts. In response to this, the Accountamatics method has been developed, building upon the fundamental knowledge in accounting that has been used since 1494. Despite its historical significance, this method is sometimes regarded as limited to technical knowledge in the modern era.

The study presents various barriers to adopt big data analytics (BDA) for sustainable manufacturing operations (SMOs) post-coronavirus disease (COVID-19) pandemics. In this study, 17 barriers are identified through extensive literature review and experts’ opinions for investing in BDA implementation. A questionnaire-based survey is conducted to collect responses from experts. The identified barriers are grouped into three categories with the help of factor analysis. These are organizational barriers, data management barriers and human barriers. For the quantification of barriers, the graph theory matrix approach (GTMA) is applied.

The study presents various barriers to adopt BDA for the SMOs post-COVID-19 pandemic. In this study, 17 barriers are identified through extensive literature review and experts’ opinions for investing in BDA implementation. A questionnaire-based survey is conducted to collect responses from experts. The identified barriers are grouped into three categories with the help of factor analysis. These are organizational barriers, data management barriers and human barriers. For the quantification of barriers, the GTMA is applied.

The study identifies barriers to investment in BDA implementation. It categorizes the barriers based on factor analysis and computes the intensity for each category of a barrier for BDA investment for SMOs. It is observed that the organizational barriers have the highest intensity whereas the human barriers have the smallest intensity.

This study may help organizations to take strategic decisions for investing in BDA applications for achieving one of the sustainable development goals. Organizations should prioritize their efforts first to counter the barriers under the category of organizational barriers followed by barriers in data management and human barriers.

The novelty of this paper is that barriers to BDA investment for SMOs in the context of Indian manufacturing organizations have been analyzed. The findings of the study will assist the professionals and practitioners in formulating policies based on the actual nature and intensity of the barriers.

This paper aims to provide a conceptual framework containing SERVQUAL original dimensions and add two additional dimensions: patient satisfaction and loyalty in the hospital SQ model that demonstrates the relationship between hospital service quality, patient satisfaction and loyalty from patients’ perspective.

This research conducted a thorough literature review using specific keywords and electronic databases, adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Through analysis, the key dimensions of service quality in Indian hospitals were identified, with the addition of patient satisfaction and loyalty as variables. Of 1,000 initially downloaded papers, 497 were included.

While many researchers rely on the SERVQUAL model, some introduce new or modified dimensions, often renaming existing ones. This study identifies the RATER factors as the main dimensions patients use to evaluate hospital services. This study finds a positive relationship between service quality, patient satisfaction and loyalty.

An understanding of how health-care service quality dimensions, directly and indirectly, affect patient satisfaction and loyalty is important for hospital marketing managers. This study helps them take action to improve patient satisfaction, which encourages patients to be loyal.

This research provides a comprehensive framework for measuring health-care service quality, combining SERVQUAL dimensions and new variables. This study offers useful insights for academics and health-care professionals, promoting more accurate measurement and enhancement of service quality. The use of PRISMA in this context is also innovative, as it is less common in administrative health-care research.