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Different channels for different services: information sources for services with search, experience and credence attributes

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  • Raquel Chocarro
  • Monica Cortinas
  • Maria Luisa Villanueva

Abstract

A first step in many decision-making processes is a search for information. This paper focuses on the means consumers use to access information prior to contracting services. It uses two different theoretical perspectives, namely, the economic approach and the psychological approach), and the specific aim is to compare consumers’ choice of source when seeking information prior to contracting services with different levels of search, experience or credence attributes. The modelling technique is mixed regression models, which allow the use of standard errors robust to within-group correlation. Our review of the data from a sample of 492 consumers and nine different services (three for each attribute category) shows that consumers use fewer information sources and show less search intensity when the purchase involves a service with search attributes than when it involves either of the other types. The highest levels of information search intensity and online media usage are found in relation to services with experience attributes. Fewer sources are consulted for purchases involving services with credence qualities than for those involving the other types, but the information obtained has a greater impact on decision making. The information sources most commonly-used are personal contacts and offline media.

Suggested Citation

  • Raquel Chocarro & Monica Cortinas & Maria Luisa Villanueva, 2021. "Different channels for different services: information sources for services with search, experience and credence attributes," The Service Industries Journal, Taylor & Francis Journals, vol. 41(3-4), pages 261-284, February.
  • Handle: RePEc:taf:servic:v:41:y:2021:i:3-4:p:261-284
    DOI: 10.1080/02642069.2018.1508457
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    Cited by:

    1. Pei-Ju Wu, 2023. "O2O switching determinants and successful drivers in omnichannel retailing services," Service Business, Springer;Pan-Pacific Business Association, vol. 17(3), pages 771-788, September.
    2. Yao, Qi & Hu, Chao & Zhou, Wenkai, 2024. "The impact of customer privacy concerns on service robot adoption intentions: A credence/experience service typology perspective," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    3. Jan-Peter Kucklick & Jennifer Priefer & Daniel Beverungen & Oliver Müller, 2023. "Elucidating the Predictive Power of Search and Experience Qualities for Pricing of Complex Goods – A Machine Learning-based Study on Real Estate Appraisal," Working Papers Dissertations 112, Paderborn University, Faculty of Business Administration and Economics.
    4. Chen, Zhongwei & Cui, Ruijie & Tang, Can & Wang, Zihan, 2024. "Can digital literacy improve individuals' incomes and narrow the income gap?," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    5. Liu, Yun & Wang, Xingyuan & Wang, Shuyang, 2022. "Research on service robot adoption under different service scenarios," Technology in Society, Elsevier, vol. 68(C).

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