About

Traci J. Hess is the Senior Associate Dean and Douglas & Diana Berthiaume Endowed Professor of Information Systems at the Isenberg School of Management, University of Massachusetts Amherst. She holds a PhD and MA in Information Systems from Virginia Tech's Pamplin School of Business, and a BS in Accounting from the University of Virginia's McIntire School of Commerce. Her professional experience includes senior roles in financial institutions such as Valley Financial Corporation and Bank of Hampton Roads, as well as a senior accountant position at Ernst & Young. Her academic career includes appointments as Professor and Associate Professor within the Operations & Information Management Department at UMass Amherst, where she has served as Chair of Graduate Faculty and as IS PhD Coordinator. She has also held positions at Washington State University and has been recognized with several honors, including the Isenberg Outstanding Teaching Award, the Isenberg Outstanding Research Award, and the Isenberg Research Excellence Award. Her research interests encompass human-computer interaction, decision-making and decision support systems, recommendation agents, electronic commerce, trust and signaling, and user evaluation and acceptance of information systems. She is actively involved in scholarly research, with recent publications examining online community participation, digital labor platforms, online review platforms, and online waiting experiences.

Research topics

• Computer Science
• Computer Security
• Internet privacy
• Mathematics
• World Wide Web
• Programming language

Selected publications

• Reconceptualizing Online Community Participation Behaviors with the Visibility–Cost Framework and Commitment

  Journal of Management Information Systems · 2026-04-03

  articleSenior author
  PublisherDOI

• The Psychology of paid reviewers: an experimental study of online reviewer needs and motivations

  European Journal of Information Systems · 2026-04-27

  articleOpen accessSenior author
  PublisherDOI

• Mixed Messages: An Examination of Reviewer Badges and Consumer Trust with Online Review Platforms

  AIS Transactions on Human-Computer Interaction · 2024-06-30 · 3 citations

  articleOpen access

  Online reviews play a critical role in online shopping platforms by helping consumers make efficient shopping decisions despite the limited experiential information that online shopping forums provide. While platforms provide incentives to encourage consumers to write online reviews, consumers need additional information or cues about reviewers to build consumer trust and meet disclosure requirements about using incentives. This paper examines such disclosures in the form of two reviewer badges—the verified badge and the incentive badge—to better understand how badges, individually and jointly together, influence trust. We draw on the elaboration likelihood model (ELM) to investigate badges as peripheral cues and online review quality as a central cue in an online shopping scenario. We conducted two experimental studies to examine the effect that badges, when presented individually and together, had on consumers’ trusting beliefs, trusting attitude, and behavioral intentions. The verified badge increased trusting beliefs and the incentive badge largely decreased trusting beliefs, with both cues moderating (decreasing) the effect of argument quality on trusting beliefs when badges were presented individually. When we presented these mixed cues together, study participants directed their attention back to argument quality to resolve the ambiguity from mixed cues. While benevolence, integrity, and competence trusting beliefs were all influenced by the two badges, competence beliefs predominantly influenced trusting attitude.

  PublisherDOI

• Confirmation and Disconfirmation: How do badges change motivation for eWOM?

  Americas Conference on Information Systems · 2021-01-01

  article1st authorCorresponding
  Publisher

• How Dual-Process Theories Provide Insights to Online Cues

  Journal of the Association for Information Systems · 2021-01-01

  articleSenior author

  Online activities now occupy more of our time than ever before, increasing our struggle with online information overload. Online cues, such as icons, images, and badges have gained importance as these cues can act as effective decision-making aids for overcoming information overload. While such cues may improve decision-making efficiency, psychological evidence suggests that decisions made with such cues can be shallow, irrational, and unconscious. This ERF paper addresses these conflicting outcomes, by conducting a literature review on cues used in online opinion platforms using dual-process decision-making theories. Through this review, cues and outcomes have been organized into categories, and research gaps and theoretical inconsistencies have been documented. Contributions include describing influential online cues based on context and theory and identifying specific research opportunities with the complicating roles of online cues and the relationships between cues and argument quality.

  Publisher

• Internet Privacy Concerns: A Replication and Parsimonious Extension

  Americas Conference on Information Systems · 2020

  Senior authorCorresponding
  • Computer Science
  • Computer Security
  • Computer Science

  Privacy concerns is a widely used construct in Information Systems research. Several different conceptualizations and taxonomies have been proposed but the Internet Privacy Concerns construct by Hong & Thong (2013) offers a more comprehensive approach to integrate previous research. The Internet Privacy Concerns construct is operationalized by an 18-item scale with six sub-dimensions. The present study aims to replicate and validate the best fitting model previously identified as a third-order construct with two second-order constructs, and six first-order dimensions. In addition, this research proposes a more parsimonious three-item criterion measure of internet privacy concerns which can offer researchers a more participant-friendly approach to measuring this relevant construct in IS research. Preliminary results are presented which confirm the original model and support the new criterion measures for internet privacy concerns, called hereafter Parsimonious Internet Privacy Concerns (PIPC) scale.

  Publisher

• Motivation to Use IS: A Literature Review

  Americas Conference on Information Systems · 2020

  1st authorCorresponding
  • Computer Science
  • Computer Science
  Publisher

• Biased but Credible: An Experimental Study of Online Reviews

  International Conference on Information Systems · 2020

  1st authorCorresponding
  • Computer Science
  • Computer Science
  Publisher

• When Do Likes Create Bias

  Journal of the Association for Information Systems · 2020-01-01

  articleSenior author

  The rise of online communities has ushered in a new era of content sharing with platforms that serve many functions and overcome the geographic and synchronous limitations of traditional word-of-mouth communications. Community-based question answering sites (CQA) have emerged as convenient platforms for users to exchange knowledge and opinions with others. Research on CQA has primarily focused on engaging members to voluntarily contribute to these communities. Helpfulness ratings and “likes” are one mechanism platforms can use to engage members, but these subjective evaluations can also create bias. In this ERF paper, the elaboration likelihood model is applied to better understand when bias can occur with these platforms. An experimental design and a planned data collection are reported.

  Publisher

• A Review of Knowledge Contribution Measurement in Online Communities

  Journal of the Association for Information Systems · 2019-01-01

  review

  Scholars have long studied the genesis of knowledge in organizations and communities. These entities are increasingly being superseded by virtual counterparts, leading to the emergence of online communities. While the information systems (IS) literature covers many aspects of how and why online community members contribute knowledge, less attention has been paid to the nature and rigor of its measurement. In response, this study reviews the empirical literature on knowledge contribution in online communities with the aim of assessing the current state of its measurement. Insights into direct and indirect measurement approaches are evaluated and three primary categories of measures are identified—volume, quality, and other. A typology of online communities is proposed to investigate measurement differences between community types. We find evidence that different theoretical perspectives inform measurement in different types of online communities. The paper concludes by outlining limitations and future research directions.

  Publisher

Frequent coauthors

• Joseph S. Valacich

  University of Arizona

  9 shared

• Anna Lazárová McNab

  Niagara University

  8 shared

• John D. Wells

  University of Massachusetts Amherst

  6 shared

• Mark A. Fuller

  St. Francis Xavier University

  5 shared

• David Agogo

  Florida International University

  5 shared

• John Mathew

  Sultan Qaboos University

  4 shared

• Loren Paul Rees

  Virginia Tech

  4 shared

• Óscar García

  IDEO (United States)

  3 shared

Education

• Ph.D., Business Administration

  University of Massachusetts Amherst

  2000

• M.S., Business Administration

  University of Massachusetts Amherst

  1996

• B.S., Business Administration

  University of Massachusetts Amherst

  1994

Awards & honors

• Association for Information Systems (AIS) Distinguished Memb…
• Isenberg Outstanding Teaching Award, UMass Amherst (2014-201…
• Isenberg Outstanding Research Award, UMass Amherst (2012)
• Isenberg Research Excellence Award, UMass Amherst (2011)
• Transactions on Human-Computer Interaction, Best Paper Award…