Sachin S. Kamble

Management Information Systems · 2018–2021

A researcher in the Science corpus: 11 papers; trusts 35 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

Whom Sachin S. Kamble trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. V. Venkatesh
  2. Joseph F. Hair
  3. Fred D. Davis
  4. Angappa Gunasekaran
  5. Henry C. Lucas Jr.
  6. E. Wolf
  7. Lida Xu
  8. David Gefen
  9. S.A.S.P. Abeyratne
  10. P. Shrout

Who trusts Sachin S. Kamble overall

  1. Angappa Gunasekaran
  2. Sven Winkelhaus
  3. Shuchih Ernest Chang
  4. Lai-Wan Wong
  5. Maciel Manoel de Queiroz
  6. Samuel Fosso Wamba
  7. Abhijeet Ghadge
  8. Rakesh D. Raut
  9. Eric H. Grosse
  10. Assunta Di Vaio

Papers from Sachin S. Kamble's perspective

Ordered by how strongly the researchers Sachin S. Kamble trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology
  2. A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies (Management Sciences)
  3. Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model (Information systems research)
  4. Time Flies When You're Having Fun: Cognitive Absorption and Beliefs About Information Technology Usage (MIS Q.)
  5. Multivariate Data Analysis (Technometrics)
  6. Common method biases in behavioral research: a critical review of the literature and recommended remedies. (Journal of Applied Psychology)
  7. User Acceptance of Information Technology: Toward a Unified View (MIS Q.)
  8. Structural Equation Modeling and Regression: Guidelines for Research Practice (Communications of the Association for Information Systems)
  9. Why Don't Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior (MIS Q.)
  10. Reinforcement Learning: An Introduction

Their papers