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Learning Resource Centre Monthly Bulletin |
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Learning Resource Centre Monthly Bulletin |
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| New Books |
 Ebook: FN424 Central Bank Digital Currencies : The Future of Mo By Michael Lloyd |  Ebook: FN425 The Return of Inflation : Money and Capital in the By Paul Mattick |  Ebook: FN426 The Economic Theory of Fiscal Policy By Alan Peacock and G. K. Shaw |
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| Articles |
| Understanding mobile money adoption in rural subsistence markets: a construal-based perspective. By Carbonell, Pilar;Rodriguez Escudero, Ana Isabel International Journal of Bank Marketing. 2025, Vol. 43 Issue 7, p1413-1440. 28p. Abstract :Purpose: This study aims to advance understanding of mobile money adoption by examining the similarities and differences between the drivers of adoption intention and actual usage. It also seeks to address critical gaps in the literature by focusing on rural subsistence consumers, who are often underrepresented in mobile money research. Design/methodology/approach: The study employs a mixed-methods approach, combining quantitative survey data collected from 326 users and 130 non-users of mobile money in the Peruvian Amazon with qualitative insights from two focus group discussions involving key stakeholders in the mobile money ecosystem. Partial least squares structural equation modeling and multigroup analysis were used to examine relationships between key factors and to assess differences across the intention and usage stages. Findings: The study identifies significant similarities and differences in the drivers of mobile money adoption intention and use in rural subsistence markets. Perceived usefulness, ease of use and service accessibility are equally important for both stages. However, collective needs and perceived relative advantage have a stronger influence on adoption intention, while subjective norms, affordability, compatibility and perceived risk are more critical during the usage stage. Originality/value: This study makes a unique contribution by applying construal level theory to mobile money adoption, highlighting how psychological distance shapes decision-making at different stages of adoption. By focusing on the Peruvian Amazon – a region marked by high poverty levels and limited success in government-led efforts to promote mobile money adoption – this research provides novel insights into adoption behaviors in rural subsistence markets. | |||
| Understanding how banking channels grow and share customers. By Thorpe, David;Cohen, Justin;Tanusondjaja, Arry;Lockshin, Larry International Journal of Bank Marketing. 2025, Vol. 43 Issue 7, p1441-1467. 27p. Abstract :Purpose: Banks provide multiple channels for customers to use, but little is known about how these channels grow or share customers. This study investigates this by testing patterns known to empirically describe brand competition—Double Jeopardy (DJ), duplication of usage (DoU) and user profile homogeneity (UPH)—across banking channel contexts. Design/methodology/approach: 427 Australian customers self-reported their banking channel usage at each purchase process stage (i.e. information, acquisition and usage). DJ analysis examined the relationship between channel penetration and average usage frequency. DoU analysis examined the relationship between channel penetration and customer multichannel usage. Mean Absolute Deviation analysis measured UPH across channels. Findings: DJ is observed at the usage stage and aggregate level: larger channels have more customers, and those customers use the larger channels more frequently. DJ is not seen at the information or acquisition stages. DoU is observed across stages: channels share more customers with larger channels and fewer customers with smaller channels. UPH across channels was observed at the aggregate level: profiles of customers who use different channels are similar. There was lower homogeneity at the individual stages. Practical implications: DJ patterns imply that channel growth results from customer acquisition, rather than increasing usage frequency. DoU results imply that customer co-usage across channels is in line with channel size and any deviations should be investigated further to better understand and service customers. UPH suggests that category reach is a better-suited strategy over segmentation for channel growth. Originality/value: DJ, DoU and UPH patterns provide novel insights of banking channel growth and customer sharing. This informs more effective channel management strategies. | |||
| Advanced AI and big data techniques in E-finance: a comprehensive survey By Rihab Najem, Ayoub Bahnasse, Meryem Fakhouri Amr, Mohamed Talea Discover Artificial Intelligence; Istanbul Vol. 5, Iss. 1, (Dec 2025): 102. DOI:10.1007/s44163-025-00365-y Abstract :The finance sector is one of those that have had a dramatic change after the integration of technology and more so Artificial Intelligence, Big Data, Text Mining and Cloud computing which has also given way to the development of e-finance where electronic channels together with digital technologies are used to deliver financial services. E-finance takes advantage of these new technologies to provide easy, efficient, and innovative financial services to people. This makes it possible for DFI to reduce expenses, make data-informed decisions and improve their experience for clients but also opens access to financial services for people in emerging markets. Advances need to ensure data protection and secrecy for the well and confidence in financial industry as well: research will scrutinize effects due technological progress on AI plus Big Data, Text Mining or Cloud Computing within Finance. This paper attempts a comprehensive review of literature through scholarly articles and papers published over the past thirteen years (2013–2025) available through Google Scholar and SCOPUS. The research methodology proceeded by choosing and crossing keywords related to technology and fintech, based on a bibliometric analysis of the past and current literature of related fields, the frequency of citation, and usage in emerging AI, Big Data, Text Mining, and Cloud computing trends in finance. Wide coverage was pursued by considering expert-reviewed high-ranking keywords drawn from the core areas of the field. The results identify the top publishers and journals holding significant influence in the field of E-finance. Moreover, this paper will also shed light on the possible benefits of text mining in finance which include improving customer satisfaction as well as detecting and preventing fraudulent transactions and risks mitigation. Results underscore the co-dependence between Finance, Technology, AI, Big Data, Text Mining, Cloud. And how they fit with each other; it further proposed a new methodology that detailed using multi-source datasets. However, these findings form valuable insights into the growing importance of emerging technologies upon the finance industry and current key trends in this area. | |||
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| News |
| India`s Bajaj Finserv hikes customer target to 250 million By The Economic Times; 1st July 2025 |
| Indian financial system resilient amid global uncertainty: RBI report By Business Standard; 30th June 2025 |
| India for reforms in multilateral banks, fairer credit rating systems: FM By Financial Express; 1st July 2025 |
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