How does relationship quality sustain the rich world’s poorest businesses?

Hani, Umme; Akter, Shahriar; Wickramasinghe, Ananda; Kattiyapornpong, Uraiporn

doi:10.1016/j.jbusres.2021.04.065

Cited by 11 publications

(28 citation statements)

References 127 publications

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“…We define trustworthy offerings as big data that captures data for delivering credible, customized, and caring offerings for microfinance customers. Our findings align with Hani et al, ( 2021a , 2021b )’s earlier research. According to the systematic literature review and interviews from the microfinance managers, the study finds that trustworthy offerings consist of credibility, caring and customization.…”

Section: Proposed Modelsupporting

confidence: 93%

“…Data can allow us to identify the most needed customer and assists us in offering the services to help those customers ( Interviewee # 5) The qualitative research studies showed that credibility, caring, and customization can be used to predict different types of trust among microfinance customers using big data analytics. Also, the previous qualitative study exhibited that microfinance customers mentioned the importance of customization, caring, and credibility when describing trust (Hani et al, 2021a , 2021b ). The notion of trust has been postulated as being the basis of quality interpersonal interactions and a source of competitive advantage for businesses (Tan & Lim, 2009 ).…”

Section: Proposed Modelmentioning

confidence: 99%

“…Customers seek credibility when information or promises become pertinent for actions or decisions yet unknown from personal experience(Wanner & Janiesch, 2019 ). In microfinance, the bank’s credibility is indicated by the fact that it is expected not to make any false claim or charge higher interest to their vulnerable customers (Hani et al, 2021a , 2021b , p. 300). For example, big data analytics can provide up-to-date and real-time data using the bulk amount of text, data, and analysis of customers' responses from online and offline feedback or opinions (Wanner & Janiesch, 2019 ).…”

Section: Proposed Modelmentioning

confidence: 99%

“…Understanding the importance and urgency of this need, BRAC introduced a customized product, “CIP,” a digital financial service (DFS) guaranteeing an end-to-end digital operation process in which customers can directly receive the loan, pay installments and save money through bKsah or cash (BRAC, 2021 ). In microfinance, we define customization as the bank's ability to tailor products and services to meet the specific demands of each customer (Hani et al, 2021a , 2021b ). The importance of big-data analytics in customized service offerings is reflected in the following quote: Data allow us to identify trends and patterns concerning current loan information and future loan offerings.…”

Section: Proposed Modelmentioning

confidence: 99%

“…Caring for microfinance customers is critical because they are vulnerable and encounter various challenging environments (Hani et al, 2021a , 2021b ). Customer’s trust in microfinance is embedded in the caring attitude that prioritizes the customers' well-being over the organization’s interests (Ganesan, 1994 ).…”

Section: Proposed Modelmentioning

confidence: 99%

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The future of data-driven relationship innovation in the microfinance industry

2022

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Data-driven innovation (DDI) initiatives by microfinance institutes have transformed the global poverty alleviation landscape. Despite the fact that relationship building is one of the primary goals of DDI initiatives in microfinance operations, there has been little research on the dimensions of relationship quality. This study examines how DDI initiatives recognize and incorporate relational dimensions in their service offerings to alleviate poverty. Drawing on a systematic literature review, thematic analysis and interviews with 20 microfinance managers, this research explores the relationship quality parameters that need to be leveraged. Grounded in the resource-based theory, the findings of this study confirm trust and commitment as two key relationship capabilities. The findings contribute to a better understanding of how microfinance institutes can use DDI to achieve sustainable competitive advantage.

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Section: Proposed Modelsupporting

confidence: 93%

Section: Proposed Modelmentioning

confidence: 99%

Section: Proposed Modelmentioning

confidence: 99%

Section: Proposed Modelmentioning

confidence: 99%

Section: Proposed Modelmentioning

confidence: 99%

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The future of data-driven relationship innovation in the microfinance industry

2022

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Gamification in financial service apps to enhance customer experience and engagement

Raza,

Rehmat,

Ishaq

et al. 2023

J of Consumer Behaviour

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The purpose of this research is twofold: (1) to examine the impact of gamification on user experiences, customer engagement, and purchase intentions in the financial industry and (2) to examine how immediate rewards vs. delayed rewards prompt different consumer behaviors in Pakistan's mobile banking (m‐banking) industry. The data for study 1 was collected from 340 m‐banking customers using a structured, survey‐based questionnaire, while study 2 collected data from 161 customers using an experimental‐based study. The structural equation modeling results show that gamification elements are positively related to user experiences and customer engagement, and customer engagement mediates the relationship between gamification and purchase intentions. Moreover, the results of the experimental‐based study show that immediate rewards more strongly influence user experiences, customer engagement, and purchase intentions. For theoretical implications, this study extends the scant literature on gamification in the m‐banking industry. For managerial implications, this research highlights the essential elements of gamification to increase customer engagement and purchase intentions in the m‐banking sector.

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