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The role of compatibility in predicting business intelligence and analytics use intentions
16 references·16 citing·26 second hopsampled
The role of compatibility in predicting business intelligence and analytics use intentions (2018)The role of compatibility in predicting b…Common Method Bias in PLS-SEM (2015)Common Method Bias in PLS-SEMConsumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology1 (2012)Consumer Acceptance and Use o…Business Intelligence and Analytics: From Big Data to Big Impact (2012)Business Intelligence and Ana…\nThe use of partial least squares path modeling in international marketing (2009)\nThe use of partial least sq…Technology Acceptance Model 3 and a Research Agenda on Interventions (2008)Technology Acceptance Model 3…Designing and Conducting Mixed Methods Research (2007)Designing and Conducting Mixe…User Acceptance of Information Technology: Toward A Unified View1 (2003)User Acceptance of Informatio…Common method biases in behavioral research: A critical review of the literature and recommended remedies. (2003)Common method biases in behav…A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic-Mail Emotion/Adoption Study (2003)A Partial Least Squares Laten…A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies (2000)A Theoretical Extension of th…Use of partial least squares (PLS) in strategic management research: a review of four recent studies (1999)Use of partial least squares …Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation (1991)Development of an Instrument …User Acceptance of Computer Technology: A Comparison of Two Theoretical Models (1989)User Acceptance of Computer T…Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology (1989)Perceived Usefulness, Perceiv…Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models (1982)Asymptotic Confidence Interva…Evaluating Structural Equation Models with Unobservable Variables and Measurement Error (1981)Evaluating Structural Equatio…Understanding the acceptance of business intelligence from healthcare professionals’ perspective: an empirical study of healthcare organizations (2024)Understanding the acceptance …Out of the way, human! Understanding post-adoption of last-mile delivery robots (2024)Out of the way, human! Unders…The Role of Business Intelligence Tools in the Decision Making Process and Performance (2023)The Role of Business Intellig…Investigating the role of institutional pressures, technology compatibility, and green transformation in driving manufacturing industries toward green development (2023)Investigating the role of ins…Exploring the Determinants of Digital Transformation Adoption for SMEs in an Emerging Economy (2023)Exploring the Determinants of…Digital Culture, Knowledge, and Commitment to Digital Transformation and Its Impact on the Competitiveness of Portuguese Organizations (2023)Digital Culture, Knowledge, a…The impact of big data analytics talent capability on business intelligence infrastructure to achieve firm performance (2022)The impact of big data analyt…Predicting Critical Success Factors of Business Intelligence Implementation for Improving SMEs’ Performances: a Case Study of Lagos State, Nigeria (2022)Predicting Critical Success F…A meta-regression of task-technology fit in information systems research (2022)A meta-regression of task-tec…The impact of business analytics capability on data-driven culture and exploration: achieving a competitive advantage (2021)The impact of business analyt…Does marketing analytics capability boost firms' competitive marketing performance in data-rich business environment? (2021)Does marketing analytics capa…Business Intelligence and Business Value in Organisations: A Systematic Literature Review (2021)Business Intelligence and Bus…New challenges in sport entrepreneurship for value creation (2020)New challenges in sport entre…Modeling of Business Intelligence Systems Using the Potential Determinants and Theories with the Lens of Individual, Technological, Organizational, and Environmental Contexts-A Systematic Literature Review (2020)Modeling of Business Intellig…Business intelligence in academic libraries in Jordan: Opportunities and challenges (2020)Business intelligence in acad…Business intelligence and organizational performance (2020)Business intelligence and org…Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research (1975)Self-efficacy mechanism in human agency. (1982)A new criterion for assessing discriminant validity in variance-based structural equation modeling (2014)Understanding Attitudes and Predicting Social Behavior (1980)The theory of planned behavior (1991)Older Adults' Reasons for Using Technology while Aging in Place (2015)Diffusion of Innovations 1 (2019)Self-Reports in Organizational Research: Problems and Prospects (1986)Structural Equations with Latent Variables. (1991)Sources of Method Bias in Social Science Research and Recommendations on How to Control It (2011)Coefficient Alpha and the Internal Structure of Tests (1951)Structural equation modeling in practice: A review and recommended two-step approach. (1988)PLS-SEM: Indeed a Silver Bullet (2011)When to use and how to report the results of PLS-SEM (2018)Significance tests and goodness of fit in the analysis of covariance structures. (1980)On the Evaluation of Structural Equation Models (1988)Toward a Definition of Mixed Methods Research (2007)Bridging the Qualitative–Quantitative Divide: Guidelines for Conducting Mixed Methods Research in Information Systems1 (2013)A Concise Introduction to Mixed Methods Research (2021)Confidence Limits for the Indirect Effect: Distribution of the Product and Resampling Methods (2004)lavaan : An R Package for Structural Equation Modeling (2012)Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R (2021)Trust and TAM in Online Shopping: An Integrated Model1 (2003)Why Don’t Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior1 (2000)Unified Theory of Acceptance and Use of Technology: A Synthesis and the Road Ahead (2016)Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a Revised Theoretical Model (2017)
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References

  • 1981Evaluating Structural Equation Models with Unobservable Variables and Measurement Error108,884 cited
  • 2003Common method biases in behavioral research: A critical review of the literature and recommended remedies.81,863 cited
  • 1989Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology68,271 cited
  • 2003User Acceptance of Information Technology: Toward A Unified View144,945 cited
  • 1989User Acceptance of Computer Technology: A Comparison of Two Theoretical Models25,696 cited
  • 2007Designing and Conducting Mixed Methods Research23,260 cited
  • 2000A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies22,991 cited
  • 2012Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology115,720 cited
  • 1982Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models12,786 cited
  • 2009\nThe use of partial least squares path modeling in international marketing11,331 cited
  • 2015Common Method Bias in PLS-SEM10,154 cited
  • 1991Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation9,145 cited
  • 2008Technology Acceptance Model 3 and a Research Agenda on Interventions8,138 cited
  • 1999Use of partial least squares (PLS) in strategic management research: a review of four recent studies

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7,307 cited
  • 2003A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic-Mail Emotion/Adoption Study6,477 cited
  • 2012Business Intelligence and Analytics: From Big Data to Big Impact6,241 cited
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