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Does the “Like” Habit of Social Networking Services Lower the Psychological Barriers to Recommendation Intention in Surveys?

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  • Kato Takumi

    (Graduate School of Humanities and Social Sciences, Saitama University, Japan)

Abstract

Background: Companies often measure their customers’ recommendation intention using the loyalty index based on the idea that a customer who has high loyalty and is committed to a brand has the confidence to recommend it to others. The psychological barrier is higher for recommendation intention, which may influence the behavior of others than for satisfaction on an individual level. However, the action of recommending has become commonplace due to the spread of social networking services (SNS). Pushing the “like” button for posts by family, friends, and co-workers has become an ingrained practice for consumers. Therefore, it is thought that “like” habits in SNS may lower the psychological barriers to the recommendation. Objectives: In this study, it was hypothesized that the more people habitually like posts on SNS, the higher the score for their recommendation intention in a customer survey. Methods/Approach: Propensity score matching was used to investigate a causal effect between the likes and the recommendation intention in a customer survey. Results: Based on the results of an online survey of chocolate brands in Japan, the causal effect was verified by propensity score matching. Conclusions: The results suggest that not only in companies but also in academic research, a valid concern is that the causal effect cannot be accurately evaluated unless a survey design is performed in consideration of the effects.

Suggested Citation

  • Kato Takumi, 2021. "Does the “Like” Habit of Social Networking Services Lower the Psychological Barriers to Recommendation Intention in Surveys?," Business Systems Research, Sciendo, vol. 12(1), pages 216-227, May.
    • Handle: RePEc:bit:bsrysr:v:12:y:2021:i:1:p:216-227:n:11
    DOI: 10.2478/bsrj-2021-0014
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    References listed on IDEAS

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    1. Khalilzadeh, Jalayer & Tasci, Asli D.A., 2017. "Large sample size, significance level, and the effect size: Solutions to perils of using big data for academic research," Tourism Management, Elsevier, vol. 62(C), pages 89-96.
    2. Takumi Kato, 2019. "Loyalty management in durable consumer goods: trends in the influence of recommendation intention on repurchase intention by time after purchase," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(2), pages 76-83, June.
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    More about this item

    Keywords

    customer relationship management; loyalty; customer survey; social networking services;
    All these keywords.

    JEL classification:

    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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