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Evaluating the Effect of Human Factors on Big Data Analytics and Cloud of Things Adoption in the Manufacturing Micro, Small, and Medium Enterprises
16 references·0 citing·53 second hopsampled
Evaluating the Effect of Human Factors on Big Data Analytics and Cloud of Things Adoption in the Manufacturing Micro, Small, and Medium Enterprises (2022)Evaluating the Effect of Human Factors on…The role of IT-based technologies on the management of human resources in the COVID-19 era (2021)The role of IT-based technolo…Big data analytics: Implementation challenges in Indian manufacturing supply chains (2020)Big data analytics: Implement…Big data analytics adoption model for small and medium enterprises (2020)Big data analytics adoption m…Investigating the adoption of big data analytics in healthcare: the moderating role of resistance to change (2019)Investigating the adoption of…Big data adoption: State of the art and research challenges (2019)Big data adoption: State of t…Understanding the determinants of big data analytics (BDA) adoption in logistics and supply chain management (2018)Understanding the determinant…Understanding the Determinants of Big Data Adoption in India (2018)Understanding the Determinant…Influence of big data adoption on manufacturing companies' performance: An integrated DEMATEL-ANFIS approach (2018)Influence of big data adoptio…Analyzing the factors influencing cloud computing adoption using three stage hybrid SEM-ANN-ISM (SEANIS) approach (2018)Analyzing the factors influen…Knowledge-based human resource management practices, intellectual capital and innovation (2017)Knowledge-based human resourc…Understanding the Factors Affecting the Organizational Adoption of Big Data (2016)Understanding the Factors Aff…A DEMATEL method to evaluate the causal relations among the criteria in auto spare parts industry (2011)A DEMATEL method to evaluate …The association among project manager's leadership style, teamwork and project success (2010)The association among project…Evaluating performance criteria of Employment Service Outreach Program personnel by DEMATEL method (2009)Evaluating performance criter…Promise and peril in implementing pay‐for‐performance (2004)Promise and peril in implemen…Extrinsic and Intrinsic Motivation to Use Computers in the Workplace 1 (1992)Extrinsic and Intrinsic Motiv…Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research (1975)Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology (1989)User Acceptance of Computer Technology: A Comparison of Two Theoretical Models (1989)Understanding Information Technology Usage: A Test of Competing Models (1995)A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies (2000)User Acceptance of Information Technology: Toward A Unified View1 (2003)Prospect Theory: An Analysis of Decision under Risk (1979)Intrinsic Motivation and Self-Determination in Human Behavior (1985)Prospect theory: An analysis of decision under risk (1988)What monetary rewards can and cannot do: How to show employees the money (2013)Let the evidence speak again! 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(1988)Firm Resources and Sustained Competitive Advantage (1991)Firm resources and sustained competitive advantage (2004)Malaysian SMEs m-commerce adoption: TAM 3, UTAUT 2 and TOE approach (2021)Intelligent automation implementation and corporate sustainability performance: The enabling role of corporate social responsibility strategy (2023)Big data analytics and firm performance: Effects of dynamic capabilities (2016)Teleworking in the Context of the Covid-19 Crisis (2020)The digitalization and public crisis responses of small and medium enterprises: Implications from a COVID-19 survey (2020)Mapping the Sustainable Human-Resource Challenges in Southeast Asia’s FinTech Sector (2022)Analyzing the impact of artificial intelligence on employee productivity: the mediating effect of knowledge sharing and well‐being (2023)Understanding consumer behavior toward adoption of e-wallet with the moderating role of pandemic risk: an integrative perspective (2023)Maneuvering through the stormy seas of digital transformation: the impact of empowering leadership on the AI readiness of enterprises (2021)The Assessment of Big Data Adoption Readiness with a Technology–Organization–Environment Framework: A Perspective towards Healthcare Employees (2021)Role of perceived ease of use, usefulness, and financial strength on the adoption of health information systems: the moderating role of hospital size (2024)
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References

  • 1992Extrinsic and Intrinsic Motivation to Use Computers in the Workplace 16,231 cited
  • 2017Knowledge-based human resource management practices, intellectual capital and innovation795 cited
  • 2010The association among project manager's leadership style, teamwork and project success446 cited
  • 2018Understanding the determinants of big data analytics (BDA) adoption in logistics and supply chain management343 cited
  • 2016Understanding the Factors Affecting the Organizational Adoption of Big Data306 cited
  • 2004Promise and peril in implementing pay‐for‐performance205 cited
  • 2019Investigating the adoption of big data analytics in healthcare: the moderating role of resistance to change200 cited
  • 2021The role of IT-based technologies on the management of human resources in the COVID-19 era196 cited
  • 2019Big data adoption: State of the art and research challenges187 cited
  • 2020Big data analytics adoption model for small and medium enterprises164 cited
  • 2018Influence of big data adoption on manufacturing companies' performance: An integrated DEMATEL-ANFIS approach158 cited
  • 2018Analyzing the factors influencing cloud computing adoption using three stage hybrid SEM-ANN-ISM (SEANIS) approach156 cited
  • 2009Evaluating performance criteria of Employment Service Outreach Program personnel by DEMATEL method125 cited
  • 2018

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Understanding the Determinants of Big Data Adoption in India
107 cited
  • 2020Big data analytics: Implementation challenges in Indian manufacturing supply chains96 cited
  • 2011A DEMATEL method to evaluate the causal relations among the criteria in auto spare parts industry86 cited
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