Weiyin Hong

Information Systems and Management · 2002–2014

A researcher in the Science corpus: 6 papers; trusts 57 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

Whom Weiyin Hong trusts overall

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

  1. V. Venkatesh
  2. Fred D. Davis
  3. Anol Bhattacherjee
  4. Kevin Zhu
  5. Naresh K. Malhotra
  6. Craig Van Slyke
  7. Michael G. Morris
  8. Jonathan W. Palmer
  9. Tamara Dinev
  10. P. Lachenbruch

Who trusts Weiyin Hong overall

  1. V. Venkatesh
  2. Do-Hyung Park
  3. Hartmut Hoehle
  4. Maria F. O. Martins
  5. Timothy Teo
  6. Yi-Shun Wang
  7. Tiago Oliveira
  8. Yili Kevin Hong
  9. M. Shamil
  10. Jumin Lee

Papers from Weiyin Hong's perspective

Ordered by how strongly the researchers Weiyin Hong 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. Common method biases in behavioral research: a critical review of the literature and recommended remedies. (Journal of Applied Psychology)
  3. Why Don't Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior (MIS Q.)
  4. User Acceptance of Information Technology: Toward a Unified View (MIS Q.)
  5. Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model (Information systems research)
  6. Time Flies When You're Having Fun: Cognitive Absorption and Beliefs About Information Technology Usage (MIS Q.)
  7. Multidimensional Constructs in Organizational Behavior Research: An Integrative Analytical Framework
  8. Understanding Information Systems Continuance: An Expectation-Confirmation Model (MIS Q.)
  9. Internet Users' Information Privacy Concerns (IUIPC): The Construct, the Scale, and a Causal Model (Information systems research)
  10. Structural Equation Modeling and Regression: Guidelines for Research Practice (Communications of the Association for Information Systems)

Their papers