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The increasing number of M‐internet subscribers and the fast growing revenue proves the great potential of M‐internet as well as the enormous business opportunity in Korea. The success in this business is dependent on understanding the concerns of customers and identifying the factors that promote the use of M‐internet. Thus, this paper aims to examine the human motivations underlying individual behavioral intention to use M‐internet in Korea.

Employs TAM (technology acceptance model) as the base model and develops a more comprehensive version of TAM to better reflect M‐internet context. The model employs perceived playfulness, contents quality, system quality, internet experience and perceived price level, in addition to perceived usefulness and ease of use. Investigates the causal relationships among the constructs used in this revised TAM and identifies the direct and indirect causal role of the constructs in developing the intention to use M‐internet.

Finds that attitude toward M‐internet is the most significant factor in predicting the behavioral intention to use M‐internet. Also identifies the positive role of the perceived playfulness and the negative role of perceived price level in developing the attitude as well as the intention. The positive causal relationships of “perceived contents quality – perceived usefulness”, “perceived system quality– perceived usefulness” and “internet experience–perceived ease of use” were also witnessed.

Considering the explosive growth of the M‐internet market, well‐established business strategy in M‐internet will deliver great success to the mobile operators. Thus, understanding comprehensive causal relationship among the constructs used in this revised TAM would help managers to better implement the strategic ramifications in promoting M‐internet.

Develops a more comprehensive version of TAM to better reflect M‐internet context in Korea, adding five new constructs and identifies the role of the construct in promoting the use of M‐internet.

This literature review aims to portray the thematic landscape of the Pacific Accounting Review (PAR) from 2013 to 2023. This paper also synthesises the special issues in PAR and identifies the main research streams that facilitate contemplating the dialogic interactions between PAR and real-world challenges. Furthermore, this paper aligns these streams with the emerging concerns in Sustainable Development Goals (SDGs) and technological disruptions to propose impactful future directions for publications in PAR.

This review adopts bibliometric analysis to establish the main research streams and objective measures for directing future publications. This paper acquires the data of 310 PAR articles from the Web of Science and ensure the data integrity before the analysis. Based on this technique, this paper also analyses PAR’s productivity, authorship and local and global impacts.

Our bibliometric analysis reveals three key research streams: (1) ESG practices and disclosures, (2) informal institutions in accounting and (3) accounting in transition. This finding affirms PAR’s relevance to real-world accounting challenges. Using a thematic map, this paper portrays the current state of PAR’s topics to identify potential directions for future publications. Further, this paper proposes three future paths for PAR: (1) the research agenda for non-financial reporting, (2) research relating to and from diverse countries considering both formal and informal contemporary contextual factors and (3) the future of the evolving accounting profession.

This study adds value to the existing PAR reviews by extending our knowledge with the latest publications, demonstrating an objective and replicable approach, and offering future directions for PAR publications.

This study aimed to analyse user experiences and perceptions of eRupee banking applications in India, focussing on understanding the key factors driving user satisfaction and dissatisfaction.

A comprehensive text-mining approach was employed to analyse 5,176 user reviews collected from the Google Play Store. Sentiment analysis and latent Dirichlet allocation (LDA) were used to classify reviews and uncover prevailing themes.

The analysis revealed that positive reviews highlighted the themes of usefulness, convenience, satisfaction, app attributes, and ease of use. Negative reviews emphasise issues related to lack of trust, faulty updates, unreliability, security concerns, and inadequate customer support. The Logistic Regression model demonstrated superior performance in predicting user sentiments, achieving an AUC of 0.7926 and an accuracy rate of 77.90%.

This study was limited to reviews from a single-platform source. Future research could incorporate data from multiple online sources and employ qualitative methods to gain deeper insight. Additionally, longitudinal studies and cross-cultural analyses are recommended to capture evolving user sentiments and global perspectives.

The findings provide actionable insights for bank managers, app developers and policymakers to enhance eRupee applications by addressing identified issues and leveraging positive aspects to improve overall user experience and satisfaction.

This study makes a novel contribution to the literature on digital currency and advanced text-mining techniques using machine-learning models to analyse user feedback in the context of an emerging economy. The proposed conceptual model and practical recommendations serve as the foundation for future research and practical development in digital financial services.