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What Determines Intentions to Use Mobile Fitness Apps? The Independent and Joint Influence of Social Norms
16 references·7 citing·36 second hop
What Determines Intentions to Use Mobile Fitness Apps? The Independent and Joint Influence of Social Norms (2022)What Determines Intentions to Use Mobile …Expanding the Technology Acceptance Model with the Inclusion of Trust, Social Influence, and Health Valuation to Determine the Predictors of German Users’ Willingness to Continue using a Fitness App: A Structural Equation Modeling Approach (2017)Expanding the Technology Acce…Keep Using My Health Apps: Discover Users' Perception of Health and Fitness Apps with the UTAUT2 Model (2015)Keep Using My Health Apps: Di…“Working out for likes”: An empirical study on social influence in exercise gamification (2015)“Working out for likes”: An e…The theory of planned behaviour is alive and well, and not ready to retire: a commentary on Sniehotta, Presseau, and Araújo-Soares (2014)The theory of planned behavio…Why people keep coming back to Facebook: Explaining and predicting continuance participation from an extended theory of planned behaviour perspective (2013)Why people keep coming back t…The Challenges of Building Theory by Combining Lenses (2011)The Challenges of Building Th…Predicting and Changing Behavior (2011)Predicting and Changing Behav…Predicting adolescents’ use of social networking sites from an extended theory of planned behaviour perspective (2010)Predicting adolescents’ use o…Social influence in the theory of planned behaviour: The role of descriptive, injunctive, and in‐group norms (2008)Social influence in the theor…Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology (2005)Personal innovativeness, soci…How Behaviors are Influenced by Perceived Norms (2005)How Behaviors are Influenced …Understanding Information Systems Continuance: An Expectation-Confirmation Model1 (2001)Understanding Information Sys…Efficacy of the Theory of Planned Behaviour: A meta‐analytic review (2001)Efficacy of the Theory of Pla…The theory of planned behavior (1991)The theory of planned behaviorPredicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior (1991)Predicting User Intentions: C…From Intentions to Actions: A Theory of Planned Behavior (1985)From Intentions to Actions: A…What Drives Users to Recommend Mobile Fitness Apps? A Three-Stage Analysis Using PLS-SEM, Machine Learning, and fsQCA (2024)What Drives Users to Recommen…The Mediation Role of Convenience in Mobile Wallet Adoption (2024)The Mediation Role of Conveni…Impact of artificial intelligence-enabled service quality on user consumption value and continuous intention to use mobile fitness applications: Evidence from China (2024)Impact of artificial intellig…The Mediating Role of e-Lifestyles to Use the Fitness Center App (2023)The Mediating Role of e-Lifes…Role of Privacy Concerns and Trust in Consumers’ Intention to Use Buy-Now, Pay-Later (BNPL): An Extended TPB Model (2023)Role of Privacy Concerns and …Assessing the Behavioral Intention of Individuals to Use an AI Doctor at the Primary, Secondary, and Tertiary Care Levels (2023)Assessing the Behavioral Inte…A systematic review of intention to use fitness apps (2020–2023) (2023)A systematic review of intent…Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research (1975)Self-efficacy: Toward a unifying theory of behavioral change. (1977)Self-efficacy: Toward a unifying theory of behavioral change. (1977)Understanding Information Technology Usage: A Test of Competing Models (1995)Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology (1989)User Acceptance of Information Technology: Toward A Unified View1 (2003)Usage, barriers and measurement of social media marketing: An exploratory investigation of small and medium B2B brands (2011)Extending the understanding of mobile banking adoption: When UTAUT meets TTF and ITM (2014)Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT model (2017)Understanding Attitudes and Predicting Social Behavior (1980)A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies (2000)Predicting and Changing Behavior: The Reasoned Action Approach (2009)How well does the theory of planned behaviour predict alcohol consumption? A systematic review and meta-analysis (2014)How Effective are Behavior Change Interventions Based on the Theory of Planned Behavior? (2016)Canadian teachers’ attitudes toward change, efficacy, and burnout during the COVID-19 pandemic (2020)Coefficient Alpha and the Internal Structure of Tests (1951)Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology1 (2012)Evaluating Structural Equation Models with Unobservable Variables and Measurement Error (1981)Common Method Variance in IS Research: A Comparison of Alternative Approaches and a Reanalysis of Past Research (2006)Technology Acceptance Model 3 and a Research Agenda on Interventions (2008)Diffusion of Innovations 1 (2019)Social Learning Theory. (1978)The effects of subjective norms on behaviour in the theory of planned behaviour: A meta‐analysis (2009)PRISM: A Planned Risk Information Seeking Model (2010)A Re-Explication of Social Norms, Ten Years Later (2015)A power primer. (1992)Self-Efficacy: The Exercise of Control (1999)Nature and Operation of Attitudes (2001)Perceived Behavioral Control, Self‐Efficacy, Locus of Control, and the Theory of Planned Behavior 1 (2002)The theory of planned behaviour: Reactions and reflections (2011)Advancing the social identity approach to health and well‐being: Progressing the social cure research agenda (2017)Gender norms and social norms: differences, similarities and why they matter in prevention science (2019)Social Influence and Group Identity (2020)The Handbook of Behavior Change (2020)Cashless Transactions: A Study on Intention and Adoption of e-Wallets (2021)Consumers’ purchase behaviour and green marketing: A synthesis, review and agenda (2021)
this work references cited by second hop

References

  • 1991The theory of planned behavior90,729 cited
  • 1985From Intentions to Actions: A Theory of Planned Behavior19,049 cited
  • 2001Efficacy of the Theory of Planned Behaviour: A meta‐analytic review9,964 cited
  • 2001Understanding Information Systems Continuance: An Expectation-Confirmation Model18,741 cited
  • 1991Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior4,215 cited
  • 2011Predicting and Changing Behavior2,802 cited
  • 2005Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology1,460 cited
  • 2005How Behaviors are Influenced by Perceived Norms927 cited
  • 2014The theory of planned behaviour is alive and well, and not ready to retire: a commentary on Sniehotta, Presseau, and Araújo-Soares704 cited
  • 2008Social influence in the theory of planned behaviour: The role of descriptive, injunctive, and in‐group norms525 cited
  • 2015“Working out for likes”: An empirical study on social influence in exercise gamification473 cited
  • 2017Expanding the Technology Acceptance Model with the Inclusion of Trust, Social Influence, and Health Valuation to Determine the Predictors of German Users’ Willingness to Continue using a Fitness App: A Structural Equation Modeling Approach405 cited
  • 2015Keep Using My Health Apps: Discover Users' Perception of Health and Fitness Apps with the UTAUT2 Model403 cited

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  • 2010Predicting adolescents’ use of social networking sites from an extended theory of planned behaviour perspective358 cited
  • 2013Why people keep coming back to Facebook: Explaining and predicting continuance participation from an extended theory of planned behaviour perspective356 cited
  • 2011The Challenges of Building Theory by Combining Lenses287 cited
  • Cited by

    • 2023A systematic review of intention to use fitness apps (2020–2023)40 cited
    • 2023Role of Privacy Concerns and Trust in Consumers’ Intention to Use Buy-Now, Pay-Later (BNPL): An Extended TPB Model37 cited
    • 2023Assessing the Behavioral Intention of Individuals to Use an AI Doctor at the Primary, Secondary, and Tertiary Care Levels18 cited
    • 2023The Mediating Role of e-Lifestyles to Use the Fitness Center App12 cited
    • 2024What Drives Users to Recommend Mobile Fitness Apps? A Three-Stage Analysis Using PLS-SEM, Machine Learning, and fsQCA9 cited
    • 2024Impact of artificial intelligence-enabled service quality on user consumption value and continuous intention to use mobile fitness applications: Evidence from China8 cited
    • 2024The Mediation Role of Convenience in Mobile Wallet Adoption7 cited