Effects of Entrepreneurship Education Components on Entrepreneurial Intentions in Oman Norizan Mohd Kassim, Abdallah Alshukaili, Mohamed Zain, Anju Ravi, Mohammed Muneerali, et al. Entrepreneurship Education and Pedagogy, 2025 Despite the many studies on entrepreneurship education programs to date, their findings have mainly reported on the changes in attitudes and intentions toward entrepreneurship without answering the questions of what precisely caused these changes. Little has been written and elaborated on the specific effects of entrepreneurship education components. This study integrates Johannisson’s four components of entrepreneurship education into Azjen’s Theory of Planned Behavior model. The model was conveniently tested among undergraduate students in higher education institutions in Oman through an online survey. The results show that the best-fit structural model supports the notion that the systematic entrepreneurship education components are interrelated, and they in fact drive the three antecedent variables of the TPB and entrepreneurial intentions. In addition, the findings also support the assertion that students’ entrepreneurship education (i.e., know-what) solely influences their entrepreneurial intentions. Practical implications of the findings and suggestions for future research are also discussed.
Unveiling the secrets: decoding the factors influencing MSMEs' accounting process and strategic debtors' management in Oman Maha Ali Alalawi, Mohammed Muneerali Thottoli, Aisha Hamed Al-Shukaili, Fatema Khamis Al-Amri Management and Sustainability, 2025 PurposeThis study investigates determinant factors (influence of the third party (ITP), credit policy (CP) and follow-up process (FP)) of micro, small and medium enterprises' (MSMEs) accounting processes (APs) and strategic debtors' management.Design/methodology/approachThe study employed a sequential mixed-method approach, combining quantitative and qualitative methods for comprehensive data analysis. Phase I involved purposively selecting and interviewing 10 MSME owners or accountants to gain insights into debtors' management. In Phase II, a quantitative approach was used for collecting survey data from 72 MSME owners or accountants. Structural equation modeling-partial least squares (SEM-PLS) are the statistical tools that validated the study's proposed hypotheses.FindingsThe findings indicate that determinant factors (ITP, CP and FP) positively affect MSMEs' AP, significantly influencing strategic debtors' management. As a result, sole proprietors can use this study's findings to create value through systematic management of their debtors, guaranteeing sustainable firm growth and profitability.Practical implicationsThe sample has restricted to MSMEs in Oman, where the findings may not be generalized to other companies. Overall, the findings suggest that it requires considering the proposed determinant factor of MSMEs' AP to manage their debtors or accounts receivable (AR) to be more profitable.Originality/valueMSMEs play an essential role in the growth of any country's economy. However, the dearth of comprehensive research on influential factors of MSMEs' debtors’ management studies justifies the significance of the current study.
Unlocking the potential of smart learning: exploring the impact of students' technological factors on remote access Mohammed Muneerali Thottoli, K.V. Thomas Journal of Applied Research in Higher Education, 2024 PurposeThe primary objective of this study is to examine how students' technological factors affect remote access (RA) in smart learning (SL) environments. Additionally, the paper explores the moderating effect of students' technical skills (TS) on RA and SL.Design/methodology/approachThe study applied a quantitative research approach and collected 125 valid questionnaires from students in Oman's higher education institutions (HEIs). A structural equation model (SEM) was employed for data analysis using the Smart PLS 4 version to examine the influence of technological factors on RA in SL environments.FindingsIt was found that the use of cloud-based RA in SL is influenced by students' use of technology, technology competitiveness and the availability of institutional software (IS). Moreover, students' TS were found to play a crucial role in moderating RA and SL, as well as technical knowledge (TK) and SL. These findings highlight the importance of technical competencies and software availability in shaping students' RA experiences.Research limitations/implicationsThe study's findings should be interpreted with caution due to the limited sample size, which may restrict the generalizability of the results.Practical implicationsThe study suggests the technological learning capabilities of HEIs, which significantly improved by prioritizing critical technical factors, including knowledge and use of technology, availability of institutional software and RA antecedents in SL environments.Originality/valueThis paper offers practical and actionable directions for HEIs, universities, colleges and educators looking to incorporate technology into their practices in the dynamic and ever-evolving Fourth Industrial Era.
Leveraging information communication technology (ICT) and artificial intelligence (AI) to enhance auditing practices Mohammed Muneerali Thottoli Accounting Research Journal, 2024 Purpose In the fourth industrial revolution, where business accounting integrates with automation through artificial intelligence (AI) and information communication technology (ICT), auditors must be able to access and analyze vast data and information to identify potential risks and issues. Using data analytics and AI to study significant amounts of data linked to audits, this study aims to investigate auditing practices by leveraging ICT and AI to enhance the audit process. Design/methodology/approach Bibliometric and quantitative research techniques have been used in the study’s mixed-method process. The theoretical underpinnings of AI have been investigated using the bibliometric research method, and the challenge of implementing ICT-enabled auditing practices among auditing professionals has been studied using the quantitative research method. Surveys, interviews and bibliometric analysis have all been used as data-gathering techniques. Findings Research in AI and auditing has a broad worldwide scope, involving developed and developing nations. ICT perceived benefits have no direct effect on auditing practices. However, ICT training has a mediating effect on the relationship between ICT perceived benefits and auditing practices. ICT adoption has no moderating effect on the relationship between ICT training and auditing practices. Research limitations/implications Findings have significance for lead auditors, policymakers and the Institute of Chartered Accountants of India (ICAI), who are keenly interested in upgrading the auditing practice of accounting professionals in India by incorporating AI and ICT determinants. Practical implications This research makes a significant contribution by offering a thorough framework for improving the knowledge management of practising auditors regarding ICT adoption, training and perceived benefits, a crucial component of auditing practices in the digital age. In addition, it provides insightful information about how AI affects accounting practices, which may point the way for further study in this area. Originality/value This research has significant implications for auditing firms in India. It can inform ICAI, policymakers and regulators in their attempts to foster the incorporation of AI and ICTs in auditing practice.
The tactician role of FinTech in the accounting and auditing field: a bibliometric analysis Mohammed Muneerali Thottoli Qualitative Research in Financial Markets, 2024 Purpose This study aims to know the tactician role of financial technology (FinTech) in the field of accounting and auditing through contextualized systematic literature review by using bibliometric analysis. Design/methodology/approach The qualitative bibliometric analysis includes studies from 2017 to 2021 using the Scopus and Web of Science databases, which yielded 277 published papers with the keywords, FinTech accounting and auditing. The contextualized systematic literature review greatly helped in clarifying the content within each cluster. Findings The study identified the tactician role of fintech primarily in the accounting and auditing professional field. Fintech is still in its inception, with continual development and implementation taking place especially, in the auditing field. The findings also confirm that FinTech can produce a confluence between various research areas, including accounting, auditing, business finance, economics, management and business field. Research limitations/implications The study describes the tactician role of FinTech and its huge possibility for future study in the accounting and auditing field among professionals, academics and regulators. Practical implications This study be able to help accounting professionals, policymakers and government regulators to establish policy development, as this research emphasizes the tactician role of FinTech in the accounting and auditing field. Social implications FinTech in accounting and auditing might add to the existing field of FinTech in the IR4.0 era that give benefits to different players such as policymakers, governments, researchers, FinTech entrepreneurs and practicing professionals. Originality/value To the best of the author’s knowledge, little focus has been given about FinTech in the accounting and auditing field using bibliometric analysis. The insights of systematic literature review provide researchers on FinTech among practicing professionals and offer opportunities for further scientific endeavours.
Factors Influencing Students’ Satisfaction at Higher Educational Institutions in Oman A.N.A. Al Wardi, E.N.A. Al Wardi, M.M. Thottoli Review of Business and Economics Studies, 2024 Purpose: Higher education is becoming increasingly critical for a nation’s socioeconomic and technical innovation, and the quality of education these institutions provide directly affects how well a country does. Hence, this study examines factors influencing student satisfaction at Oman’s higher educational institutions (HEIs). Methodology: Following scale development, the bootstrapping approach tested the research hypothesis. A survey was undertaken to gauge student satisfaction at various higher education institutions in Oman. Software for structural equation modeling (SEM PLS) has been used to examine the results to determine the relationships between the variables. Findings: The result of this study revealed that lectures and university resources positively correlated with student satisfaction, while technology showed no significant impact on student satisfaction.
Predicting Engineering Students’ Employability using Data Mining Classification Techniques Maria Elisa Linda Taeza-Cruz, Mohammed Muneerali, Badria Hamed Al Ruqishi, Bernard Guzman Cruz 2024 IEEE 3rd Conference on Information Technology and Data Science Citds 2024 Proceedings, 2024 Higher education institutions in Oman emphasize the employability of their students as one of their top priorities. Hence, the primary objective of this study is to construct a model to predict engineering students' employability using data mining classification techniques. It also investigates relevant factors to improve the prediction model. The study applied a technique known as Knowledge Discovery in Databases (KDD), which utilized 250 engineering students' records stored in the University of Nizwa database from the Spring Semester of the Academic Year 2020–2021. WEKA-Waikato Environment for Knowledge Analysis- was used to create the research classifiers. The InfoGainAttributeEval and the Ranker search methods were used to identify the most significant attributes of student employability. After the testing phase, 10-fold cross-validation was carried out. The prediction models J48 and RepTree outperformed Random Tree in accuracy metrics and tree size. J48 showed the highest Kappa value, lower error rates, and compactness, making it the top choice. Attributes like internship mark, credit hours, department, and specialization heavily influenced model performance, with J48 exhibiting superior accuracy and interpretability over RepTree. Using the most accurate data mining classification algorithm, a prediction model was developed as a subsequent stage of the data mining technique. The study suggested recommendations to improve the student's employability by emphasizing skills and competencies related to employment.
