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Cell phone banking: predictors of adoption in South Africa—an exploratory study
4 references·16 citing·42 second hopsampled
Cell phone banking: predictors of adoption in South Africa—an exploratory study (2003)Cell phone banking: predictors of adoptio…Developing and Validating Trust Measures for e-Commerce: An Integrative Typology (2002)Developing and Validating Tru…Factors Influencing the Adoption of Internet Banking (2000)Factors Influencing the Adopt…The Role of Innovation Characteristics and Perceived Voluntariness in the Acceptance of Information Technologies (1997)The Role of Innovation Charac…Understanding Information Technology Usage: A Test of Competing Models (1995)Understanding Information Tec…Factors affecting the behavioral intention to adopt mobile banking: An international comparison (2020)Factors affecting the behavio…Integrating cognitive antecedents into TAM to explain mobile banking behavioral intention: A SEM-neural network modeling (2017)Integrating cognitive anteced…Adoption of 3D-printing technologies in manufacturing: A survey analysis (2016)Adoption of 3D-printing techn…The effects of product-related, personal-related factors and attractiveness of alternatives on consumer adoption of NFC-based mobile payments (2015)The effects of product-relate…M-Banking in Metropolitan Bangkok and a Comparison with other Countries (2015)M-Banking in Metropolitan Ban…Acceptance of mobile banking framework in Pakistan (2015)Acceptance of mobile banking …Exploring consumer adoption of proximity mobile payments (2014)Exploring consumer adoption o…An investigation of users’ continuance intention towards mobile banking in China (2014)An investigation of users’ co…Perceived risk, usage frequency of mobile banking services (2013)Perceived risk, usage frequen…The role of information in mobile banking resistance (2010)The role of information in mo…Mobile banking rollout in emerging markets: evidence from Brazil (2010)Mobile banking rollout in eme…Personality traits and concern for privacy: an empirical study in the context of location-based services (2008)Personality traits and concer…Mobile commerce user acceptance study in China: A revised UTAUT model (2008)Mobile commerce user acceptan…Mobile banking innovators and early adopters: How they differ from other online users? (2008)Mobile banking innovators and…What do we know about mobile Internet adopters? A cluster analysis (2005)What do we know about mobile …Consumer value creation in mobile banking services (2005)Consumer value creation in mo…Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research (1975)From Intentions to Actions: A Theory of Planned Behavior (1985)Understanding Information Systems Continuance: An Expectation-Confirmation Model1 (2001)Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit (2008)Diffusion of Innovations 1 (2019)BUSINESS RESEARCH METHODS (PHƯƠNG PHÁP NGHIÊN CỨU TRONG KINH DOANH) (2023)The theory of planned behavior (1991)Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives (1999)Common method biases in behavioral research: A critical review of the literature and recommended remedies. (2003)Understanding the impact of m-banking on individual performance: DeLone & McLean and TTF perspective (2016)A meta-analysis of antecedents and consequences of trust in mobile commerce (2019)Understanding consumer acceptance of healthcare wearable devices: An integrated model of UTAUT and TTF (2020)Evaluating Structural Equation Models with Unobservable Variables and Measurement Error (1981)Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology (1989)A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies (2000)The DeLone and McLean Model of Information Systems Success: A Ten-Year Update (2003)User Acceptance of Information Technology: Toward A Unified View1 (2003)Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology1 (2012)The battle of Brain vs. Heart: A literature review and meta-analysis of “hedonic motivation” use in UTAUT2 (2019)Digital payment and banking adoption research in Gulf countries: A systematic literature review (2020)Point of adoption and beyond. Initial trust and mobile-payment continuation intention (2020)Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence (1988)A Multistage Model of Customers' Assessments of Service Quality and Value (1991)Consumer perceived value: The development of a multiple item scale (2001)Adoption of digital payment systems in the era of demonetization in India (2018)Mobile-banking adoption: empirical evidence from the banking sector in Pakistan (2018)User Acceptance of Computer Technology: A Comparison of Two Theoretical Models (1989)THE BIG FIVE PERSONALITY DIMENSIONS AND JOB PERFORMANCE: A META‐ANALYSIS (1991)A very brief measure of the Big-Five personality domains (2003)Research Note —Effects of Individual Self-Protection, Industry Self-Regulation, and Government Regulation on Privacy Concerns: A Study of Location-Based Services (2012)Theories in online information privacy research: A critical review and an integrated framework (2012)Location information disclosure in location-based social network services: Privacy calculus, benefit structure, and gender differences (2015)Structural equation modeling in practice: A review and recommended two-step approach. (1988)Trust and TAM in Online Shopping: An Integrated Model1 (2003)Validation Guidelines for IS Positivist Research (2004)Understanding knowledge sharing in virtual communities: An integration of social capital and social cognitive theories (2006)NFC mobile credit card: The next frontier of mobile payment? (2013)Online shopping drivers and barriers for older adults: Age and gender differences (2014)An empirical study on trust in mobile banking: A developing country perspective (2015)Modeling users’ acceptance of mobile services (2012)An extended UTAUT model to explain the adoption of mobile banking (2015)The Unified Theory of Acceptance and Use of Technology (2020)
this work references cited by second hop· second hop is a sample of the most-cited connections

References

  • 1995Understanding Information Technology Usage: A Test of Competing Models8,810 cited
  • 2002Developing and Validating Trust Measures for e-Commerce: An Integrative Typology5,540 cited
  • 2000Factors Influencing the Adoption of Internet Banking1,712 cited
  • 1997The Role of Innovation Characteristics and Perceived Voluntariness in the Acceptance of Information Technologies1,669 cited

Cited by

  • 2015Acceptance of mobile banking framework in Pakistan376 cited
  • 2008Personality traits and concern for privacy: an empirical study in the context of location-based services373 cited
  • 2005Consumer value creation in mobile banking services355 cited
  • 2014Exploring consumer adoption of proximity mobile payments352 cited
  • 2010Mobile banking rollout in emerging markets: evidence from Brazil347 cited
  • 2008Mobile commerce user acceptance study in China: A revised UTAUT model346 cited
  • 2014An investigation of users’ continuance intention towards mobile banking in China342 cited
  • 2010The role of information in mobile banking resistance297 cited
  • 2015The effects of product-related, personal-related factors and attractiveness of alternatives on consumer adoption of NFC-based mobile payments278 cited
  • 2020Factors affecting the behavioral intention to adopt mobile banking: An international comparison

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270 cited
  • 2013Perceived risk, usage frequency of mobile banking services266 cited
  • 2008Mobile banking innovators and early adopters: How they differ from other online users?262 cited
  • 2005What do we know about mobile Internet adopters? A cluster analysis260 cited
  • 2016Adoption of 3D-printing technologies in manufacturing: A survey analysis249 cited
  • 2015M-Banking in Metropolitan Bangkok and a Comparison with other Countries229 cited
  • 2017Integrating cognitive antecedents into TAM to explain mobile banking behavioral intention: A SEM-neural network modeling225 cited