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Does brand personality affect consumer satisfaction? An application of text mining to restaurants


Does brand personality affect consumer satisfaction? An application of text mining to restaurants

Rahemi, Hooman (2021) Does brand personality affect consumer satisfaction? An application of text mining to restaurants. Masters thesis, Concordia University.

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Brand personality is a fundamental marketing construct that may be leveraged for competitive advantage. Researchers and market research firms often measure brand personality in consumer surveys. This approach is expensive, unscalable, and inefficient for tracking perceptions that constantly change over time. This research thus explores an alternative to the tracking of consumers’ brand personality perceptions. Online reviews offer textual data that can be extracted for marketing research. This research captures consumers’ brand personality and brand attribute (e.g., perceived price and perceived quality) perceptions of 40 restaurants, as reflected in 4,000 online reviews, using a deep-learning algorithm. It then investigates the effect of brand personality dimensions and brand attributes on consumer satisfaction. Findings indicate a strong and independent effect of sincere, exciting, and sophisticated brand personalities on consumer satisfaction while competence and ruggedness dimensions do not influence satisfaction. In addition, this study found support for an effect of additional brand attributes (i.e., perceived price, perceived quality, interpersonal service quality, psychic cost, time/effort cost) on satisfaction, with psychic cost perceptions having the greatest impact on consumer satisfaction.

Divisions:Concordia University > John Molson School of Business > Marketing
Item Type:Thesis (Masters)
Authors:Rahemi, Hooman
Institution:Concordia University
Degree Name:M. Sc.
Program:Business Administration (Marketing specialization)
Date:8 December 2021
Thesis Supervisor(s):Grohmann, Bianca
Keywords:brand personality, text mining, consumer satisfaction, user-generated content, natural language processing
ID Code:990027
Deposited By: Hooman Rahemi
Deposited On:16 Jun 2022 15:14
Last Modified:16 Jun 2022 15:14


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