Publications Database
Welcome to the new Schulich Peer-Reviewed Publication Database!
The database is currently in beta-testing and will be updated with more features as time goes on. In the meantime, stakeholders are free to explore our faculty’s numerous works. The left-hand panel affords the ability to search by the following:
- Faculty Member’s Name;
- Area of Expertise;
- Whether the Publication is Open-Access (free for public download);
- Journal Name; and
- Date Range.
At present, the database covers publications from 2012 to 2020, but will extend further back in the future. In addition to listing publications, the database includes two types of impact metrics: Altmetrics and Plum. The database will be updated annually with most recent publications from our faculty.
If you have any questions or input, please don’t hesitate to get in touch.
Search Results
Danuvasin Charoen, Guangrui Li, Warut Khern-am-nuai (2026). "Preparing Technology Managers for the Postconsumer Reviews Era", IEEE Engineering Management Review, 54(2), 14–20.
Abstract
Online consumer reviews have long been instrumental in shaping user behavior and guiding product development. However, their credibility, and thus their utility, is in steep decline due to threats, such as malicious reviews, incentivized reviews, and AI-generated reviews. As synthetic content becomes indistinguishable from genuine feedback and bad actors exploit platforms to manipulate perceptions, the foundational trust in user-generated reviews is rapidly eroding. This article explores the critical challenges facing review ecosystems and argues that technology managers must prepare for a transition beyond traditional reviews. It examines how alternative mechanisms, such as question-and-answer systems, expert editorial content, and synthetically generated summaries from aggregated sources, can provide more trustworthy, actionable insights. These alternatives emphasize verified engagement, structured expertise, and scalable synthesis, offering resilient feedback models. This article calls for a rethinking of how platforms collect, interpret, and present user reviews, outlining practical steps for managers to sustain trust and transparency in digital marketplaces.Marchanda, P., Packard, G. and Pattabhiramaiah, A. (2015). "Social Dollars: The Economic Impact of Consumer Participation in a Firm-Sponsored Online Customer Community", Marketing Science, 34(3), 367-387.
Abstract
Many firms operate customer communities online. This is motivated by the belief that customers who join the community become more engaged with the firm and/or its products, and as a result, increase their economic activity with the firm. We describe this potential economic benefit as “social dollars.” This paper contributes evidence for the existence and source of social dollars using data from a multichannel entertainment products retailer that launched a customer community online. We find a significant increase in customer expenditures attributable to customers joining the firm’s community. While self-selection is a concern with field data, we rule out multiple alternative explanations. Social dollars persist over the time period observed and arose primarily in the online channel. To assess the source of the social dollar, we hypothesize and test whether it is moderated by participation behaviors conceptually linked to common attributes of customer communities. Our results reveal that posters (versus lurkers) of community content and those with more (versus fewer) social ties in the community generated more (fewer) social dollars. We found a null effect for our measure of the informational advantage expected to accrue to products that differentially benefit from content posted by like-minded community members. This overall pattern of results suggests a stronger social than informational source of economic benefits for firm operators of customer communities. Several implications for firms considering investments in and/or managing online customer communities are discussed.Chen, Y., Fischer, E. and Smith, A. (2012). "How Does Brand-Related User-Generated Content Differ Across YouTube, Facebook, and Twitter?", Journal of Interactive Marketing, 26, 102–113.
