Adoption of mobile banking in rural China: Impact of information dissemination channel

Zhu, Qianyu; Lyu, Zhongyao; Yan, Long; Wachenheim, Cheryl J.

doi:10.1016/j.seps.2021.101011

Cited by 43 publications

(32 citation statements)

References 22 publications

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“…Distance has no significant effect on the use of the type of information media. This finding contradicts the study of Steffes and Burgee [81], who claimed that distance had an impact on technology use. The further away the person's home from the market, the more likely they are to use digital media.…”

Section: Word-of-mouth or Digital Media In Agricultural Smescontrasting

confidence: 93%

“…This is because they easily learn and understand the benefits of digital media [20,79]. In other research, Zhu et al [81] and Mumporeze and Prieler [82] argue that lower levels of education are still a major barrier for non-digital media users. They prefer to communicate face-to-face with other people [77].…”

Section: Word-of-mouth or Digital Media In Agricultural Smesmentioning

confidence: 99%

“…Almost the same as young people, educated people are also interested and involved in using digital media [80]. There are many assumptions that educated people are more willing to accept technology and have an expanded ability to understand it [81]. This is because they easily learn and understand the benefits of digital media [20,79].…”

Section: Word-of-mouth or Digital Media In Agricultural Smesmentioning

confidence: 99%

See 2 more Smart Citations

Word of Mouth, Digital Media, and Open Innovation at the Agricultural SMEs

Wicaksono

Nugroho

Lakner

et al. 2021

Journal of Open Innovation: Technology, Market, and Complexity

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Small and medium enterprises (SMEs) must continue to combine technology and market adaptation or open innovation to sustain their business. One of these ways is to promote their products and services extensively. This study investigated the best media to promote SMEs in the local agricultural markets of Hungary. This study uses an approach of asking consumers where they receive information about SMEs and their determinants. Research questionnaires were distributed to 156 consumers who purchased agricultural products on the Budapest Central Market Hall. The data were analyzed using a binary logistic model. The studies showed that consumers obtain market information through word-of-mouth and digital media. Older consumers tend to receive information through word-of-mouth, while consumers who rarely interact with others or who are educated or foreign choose digital media. Therefore, SMEs in Hungary’s local agricultural markets have yet to focus on developing promotional activities through these two media. For the future, recommendations are given to SMEs in Hungary to maintain the quality of products and services and to develop two-way communication in digital media (e-WOM).

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Section: Word-of-mouth or Digital Media In Agricultural Smescontrasting

confidence: 93%

Section: Word-of-mouth or Digital Media In Agricultural Smesmentioning

confidence: 99%

Section: Word-of-mouth or Digital Media In Agricultural Smesmentioning

confidence: 99%

See 1 more Smart Citation

Word of Mouth, Digital Media, and Open Innovation at the Agricultural SMEs

Wicaksono

Nugroho

Lakner

et al. 2021

Journal of Open Innovation: Technology, Market, and Complexity

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“…With respect to the conduct of banking transactions, m-banking cannot be taken as a facility that has reached a global point of development and has a low rate of acceptance and diffusion, particularly in developing countries (Cruz et al, 2010;Hassan & Wood, 2020;Tran & Corner, 2016;Zhu et al, 2021). The Indian banking industry can benefit from other key indicators, such as the government's decision to promote cashless transactions and the idea of digital India.…”

Section: Literature Review and Development Of Hypothesismentioning

confidence: 99%

Examining the Impact of Customers’ Awareness, Risk and Trust in M-Banking Adoption

Tiwari

Gupta

2021

FIIB Business Review

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Mobile banking services have been a significant breakthrough in the electronic banking system and have many potential demands for online banking services to connect with consumers. Although there has been a rapid expansion of information technology (IT) in banking, which offers multiple opportunities in the global market, massive growth has not been seen in India’s m-banking adoption. Several kinds of research on m-banking adoption have been conducted in various countries, and it has been observed that India has great potential for m-banking. Nonetheless, users are not quite sure about its use for a few reasons. The present study extends the applicability of technology acceptance model (TAM) constructs in connection with customers’ awareness, perceived risk and perceived trust to investigate the user’s behavioural intention of m-banking adoption. The authors tested the proposed framework by using regression analysis in SPSS 23 and collected a sample of 311 mobile banking users by using convenience sampling. In support of the previous studies, findings revealed that perceived usefulness, perceived ease of use, customer awareness, perceived risk and perceived trust significantly adopted m-banking services in the Indian context.

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“…Ouma et al [30] also discovered that m-Banking has a similar saving potential. According to Zhu et al [31], m-banking has enormous potential in rural development.…”

Section: M-banking and Its Evolutionmentioning

confidence: 99%

An integrated fuzzy model for evaluation and selection of mobile banking (m-banking) applications using new fuzzy-BWM and fuzzy-TOPSIS

Roy

Shaw

2021

Complex Intell. Syst.

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Mobile technology has revolutionised various business processes. Banking is one of them. Traditional banking operations are gradually changing with the introduction of efficient mobile technologies. Mobile banking (m-banking) has recently emerged as an innovative banking channel that provides continuous real-time customer service. It is expected that the market for m-banking will expand in the near future. There are currently various types of m-banking applications in the market. However, ranking and selecting efficient applications is difficult due to the involvement of multiple factors. As of now, very few studies have reported the m-banking application selection framework, left scope for further research. The current study proposes an m-banking application selection model based on a combined fuzzy best–worst method (fuzzy-BWM) and fuzzy Technique for Order of Preference by Similarity to Ideal Solution (fuzzy-TOPSIS). The research was carried out in several stages, beginning with the identification of potential factors and progressing to pair-wise comparisons and the final ranking of the applications. The fuzzy set theory was applied to handle the ambiguity of the decision maker. In the first stage, fuzzy-BWM was used to determine the weight of the factors. Further, fuzzy-TOPSIS was applied to rank the m-banking applications. The present study has adopted a new fuzzy BWM, which differs significantly from the existing fuzzy-BWM, to solve the nonlinearity problem of optimisation. The applicability of the proposed model has been demonstrated through a real-life case study. The efficacy of the model has been further examined by performing a sensitivity analysis. The study observed application functionality, convenience, and performance expectancy as significant factors in selecting an m-banking application, followed by performance quality, security, and compatibility. The proposed model can assist financial institutions and customers to overcome the challenges of choosing an appropriate m-banking application. The proposed model can be used to benchmark the m-banking applications in the market.

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Adoption of mobile banking in rural China: Impact of information dissemination channel

Cited by 43 publications

References 22 publications

Word of Mouth, Digital Media, and Open Innovation at the Agricultural SMEs

Word of Mouth, Digital Media, and Open Innovation at the Agricultural SMEs

Examining the Impact of Customers’ Awareness, Risk and Trust in M-Banking Adoption

An integrated fuzzy model for evaluation and selection of mobile banking (m-banking) applications using new fuzzy-BWM and fuzzy-TOPSIS

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