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
Grant Packard, Yang Li, Jonah Berger (2024). "When Language Matters", Journal of Consumer Research, 51(3), 634–653.
Abstract
Text analysis is increasingly used for consumer and marketing insight. But while work has shed light on what firms should say to customers, when to say those things (e.g., within an advertisement or sales interaction) is less clear. Service employees, for example, could adopt a certain speaking style at a conversation's start, end, or throughout. When might specific language features be beneficial? This article introduces a novel approach to address this question. To demonstrate its potential, we apply it to warm and competent language. Prior research suggests that an affective (i.e., warm) speaking approach leads customers to think employees are less competent, so a cognitive (competent) style should be prioritized. In contrast, our theorizing, analysis of hundreds of real service conversations from two firms across thousands of conversational moments (N = 23,958), and four experiments (total N = 1,589) offer a more nuanced perspective. Customers are more satisfied when employees use both cognitive and affective language but at separate, specific times. Ancillary analyses show how this method can be applied to other language features. Taken together, this work offers a method to explore when language matters, sheds new light on the warmth/competence trade-off, and highlights ways to improve the customer experience.Matten, D. and Moon, J. (2020). "The Meaning and Dynamics of Corporate Social Responsibility, Academy of Management Review", Academy of Management Review, 45(1), 7-28.