Factors influencing the intention to use of mobile value‐added services by women‐owned microenterprises in <scp>F</scp>iji

Sathye, Suneeta; Prasad, Biman C.; Sharma, Dharmendra; Sharma, Parmendra; Sathye, Milind

doi:10.1002/isd2.12016

Cited by 27 publications

(16 citation statements)

References 50 publications

(79 reference statements)

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“…The hypothesis is retained because the path coefficient indicated that social influence is a predicator for perceived usefulness. Previous researches similar to this study such as those of Venkatesh and Davis in [35], Lu et al in [72], Jaradat in [66] and Sathye, in [73] The findings of this study showed that computer self efficacy has a significant positive effect on perceived ease of use (H 10 : β = 0.529, p ˂ 0.001). This path coefficient indicated that computer self efficacy is a predicator for perceived ease of use, hence the hypothesis is retained.…”

Section: A) Hypothesis Hsupporting

confidence: 81%

Factors Determining the Intention to Use Electronic Health Records: An Extension of the Technology Acceptance Model

Okediran

Wahab

Oyediran

2020

JSRR

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This paper details an empirical investigation of the factors that determine the intention of adopting and using electronic health records (EHR). The paper’s goal is a study aimed at examining the possibilities and intents towards EHR amongst healthcare professionals in Nigeria. In this study, an extended Technology Acceptance Model (TAM) that incorporates Subjective norm, Social influence, Result demonstrability, Computer self-efficacy and System quality to the original TAM constructs was proposed. The proposed model was empirically tested using data collected from a sample of 126 healthcare professionals across 14 healthcare delivery institutions in Oyo State, Southwestern, Nigeria by applying structural equation modeling (SEM). These data were collected by administering a questionnaire containing 30 items. The results of the evaluation showed that all constructs have significant effect on healthcare professionals’ behavioural intention to use EHR.

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Section: A) Hypothesis Hsupporting

confidence: 81%

Factors Determining the Intention to Use Electronic Health Records: An Extension of the Technology Acceptance Model

Okediran

Wahab

Oyediran

2020

JSRR

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“…The result also shows that SN is significantly associated with PU, similar to previous studies ( Aji et al, 2020b , Koenig-Lewis et al, 2015 ). Sathye et al (2018) found that PU mediates the influence of SN on BI. Following Sathye’s analysis, we argue that if Hungarian family members and friends adopt a mobile payment system, this will add value to the mobile payment system’s spread as they will influence others to use it.…”

Section: Discussionmentioning

confidence: 99%

FinTech payments in the era of COVID-19: Factors influencing behavioral intentions of “Generation X” in Hungary to use mobile payment

Daragmeh

Lentner

Sági

2021

Journal of Behavioral and Experimental Finance

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Organizations, such as the World Health Organization, encouraged consumers to use contactless payment methods instead of payment methods such as cash, which can be carriers of the SARS-2 virus. This study aims to evaluate factors that influence Hungarian Generation X’s behavioral intentions to use mobile payment services during the pandemic. We conducted an electronic questionnaire-based survey among 1120 Generation X individuals. Using structural equation modeling to analyze the study’s conceptual model, our results confirm that perceived COVID-19 risk, perceived usefulness, and subjective norms significantly influence Hungarian Generation X’s behavioral intentions to use mobile payment services. Moreover, perceived usefulness mediates the relationship between perceived ease of use and behavioral intention to use mobile payment systems. Overall, our results show that the model of perceived COVID-19 risk, perceived usefulness, subjective norms, and perceived ease of use explains 62.9% of the variance in intention to use mobile payment systems. Our study contributes to the technology acceptance model and highlights its effectiveness in explaining the behavioral intention to adopt mobile payments during the COVID-19 pandemic.

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“…Social influence involves users gaining willingness to try new technologies from others, including friends, colleagues, and families. The social influence has a positive effect on the user's intentions to use new technologies [34][35][36]. Thus, this determinant can determine the user's intention of continued use of the FDA.…”

Section: Hypothesis 2 (H2) Effort Expectancy (Ee) Positively Affects Behavioral Intention To Use (Biu)mentioning

confidence: 99%

Factors Determining the Behavioral Intention of Using Food Delivery Apps during COVID-19 Pandemics

Muangmee

Kot

Meekaewkunchorn

et al. 2021

JTAER

149

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The purpose of this study was to investigate the factors determining the behavioral intention of using food delivery apps (FDAs) during COVID-19 pandemics, under a case study of Bangkok, Thailand. The study was necessitated by the increased use of FDAs during the lockdown; online transactions were considered important in preventing the spread of the virus. The study used quantitative techniques involving structural equation model (SEM) to evaluate the effects of exogenous variables on endogenous variables. Primary data were collected from people who had installed and used FDAs. The findings indicated that performance expectancy, effort expectancy, social influence, timeliness, task technology fit, perceived trust, and perceived safety significantly influence the behavioral intention to use (BIU) to use food delivery apps during the COVID-19 pandemic. To this end, effort should be intensified to study and understand FDAs as it pertains to safety and usage.

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Factors influencing the intention to use of mobile value‐added services by women‐owned microenterprises in Fiji

Cited by 27 publications

References 50 publications

Factors Determining the Intention to Use Electronic Health Records: An Extension of the Technology Acceptance Model

Factors Determining the Intention to Use Electronic Health Records: An Extension of the Technology Acceptance Model

FinTech payments in the era of COVID-19: Factors influencing behavioral intentions of “Generation X” in Hungary to use mobile payment

Factors Determining the Behavioral Intention of Using Food Delivery Apps during COVID-19 Pandemics

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