Interactions and consequences of inertia and switching costs
Abstract
Purpose: Service research typically relates switching costs to customer loyalty, and portrays them as effective switching deterrents that engender harmful word‐of‐mouth (WOM). Rather than to customer loyalty, this paper aims to relate switching costs to consumer inertia, and show that while switching costs may result in customer retention, they can engender positive and negative WOM. This depends on whether the inertia stems from satisfaction or indifference. Design/methodology/approach: A mall‐intercept survey investigated 518 customers' perceptions of their mobile phone service providers. Structural equation modelling fitted the data to the conceptual model. Findings: Switching costs deterred switching and engendered negative WOM, but only with low‐inertia customers. With high‐inertia customers, retention and WOM behaviours depended on whether the inertia stemmed from satisfaction or indifference. Satisfied customers with high switching costs tended to stay, gave more positive and less negative WOM. With indifferent customers, switching costs were unrelated to retention or WOM behaviours. Research limitations/implications: While they may be perceived negatively, switching costs can engender PWOM. Hence, research should not consider switching costs alone without considering the context that produces them. Practical implications: Service providers should segment their customers into low‐inertia, high‐inertia/satisfied and high‐inertia/indifferent, and target each segment differently. By converting customers into the high‐inertia/satisfied segment, service providers can make the best use of switching costs – not only in the traditional sense as a barrier to defection, but also as a way of generating positive WOM. Originality/value: This study is the first to consider the role of inertia with switching costs, positive WOM, and negative WOM. The findings suggest that past studies portraying switching costs as negative impediments that evoke only negative WOM might be misleading.
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Inertia leads to customer retention but influences positive or negative word of mouth.
“Lee and Neale (2012) related switching costs to customer inertia. They found that while inertia led to customer retention, it influenced positive or negative word of mouth.”
From Health insurance policy renewal: an exploration of reputation, performance, and affect to understand customer inertia (2022) · cites this paper as Lee and Neale (2012)
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- Authors
- Lee, R., & Neale, L.
- Affiliations
- University of South Australia (AU)
- Queensland University of Technology (AU)
- Venue
- Journal of Services Marketing
- Publisher
- Emerald
- Published
- 2012-07-27
- Volume
- 26
- Issue
- 5
- Pages
- 365-374
- ISSN
- 0887-6045 (ISSN-L)
- OpenAlex
- W67102468
- Cited by
- 78
- References
- 41
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 7 · 2023: 8 · 2022: 6 · 2021: 6 · 2020: 5 · 2019: 4 · 2018: 10 · 2017: 7 · 2016: 4 · 2015: 6 · 2014: 5 · 2013: 1
- FWCI
- 7.77
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Services Marketing (publishedVersion)
- QUT Business School
- Topics
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Customer Service Quality and Loyalty
- Social Sciences › Business, Management and Accounting › Marketing › Customer churn and segmentation
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Market Behavior and Pricing
- Keywords
- switching costs, consumer inertia, customer loyalty, word of mouth, positive word of mouth, negative word-of-mouth, customer retention, customer satisfaction, mobile operators, customer segmentation, service switching
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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