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An Empirical Study of the Volkswagen Crisis in China: Customers’ Information Processing and Behavioral Intentions

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  • Jiuchang Wei
  • Ming Zhao
  • Fei Wang
  • Peng Cheng
  • Dingtao Zhao

Abstract

Product‐harm crises usually lead to product recalls, which may cause consumers concern about the product quality and safety. This study systematically examines customers’ immediate responses to the Volkswagen product recall crisis in China. Particular attention was given to customers’ responses to the risk information influencing their behavioral intentions. By combining the protective action decision model and the heuristic‐systematic model, we constructed a hypothetical model to explore this issue. A questionnaire survey was conducted to collect data involving 467 participants drawn from the customers of Volkswagen. We used structural equation modeling to explore the model. The results show that customers’ product knowledge plays an important role in their responses to the crisis. Having more knowledge would make them perceive a lower risk, but they might need even more information, making them more likely to seek and process information, and subsequently increasing their positive behavioral intentions toward the firm (that is pro‐firm behavioral intentions). Risk perception increased customers’ information needs, information seeking, and information processing but decreased their pro‐firm behavioral intentions. In addition to promoting information seeking, information needed to also facilitate customers’ systematic processing and thus increase their behavioral intentions to take corrective action. Customers’ behavioral intentions were also spurred by systematic processing, but failed to be predicted by information seeking. In summary, theoretical and practical implications and suggestions for further research are also discussed.

Suggested Citation

  • Jiuchang Wei & Ming Zhao & Fei Wang & Peng Cheng & Dingtao Zhao, 2016. "An Empirical Study of the Volkswagen Crisis in China: Customers’ Information Processing and Behavioral Intentions," Risk Analysis, John Wiley & Sons, vol. 36(1), pages 114-129, January.
  • Handle: RePEc:wly:riskan:v:36:y:2016:i:1:p:114-129
    DOI: 10.1111/risa.12446
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    4. Vincenza Capone & Daniela Caso & Anna Rosa Donizzetti & Fortuna Procentese, 2020. "University Student Mental Well-Being during COVID-19 Outbreak: What Are the Relationships between Information Seeking, Perceived Risk and Personal Resources Related to the Academic Context?," Sustainability, MDPI, vol. 12(17), pages 1-17, August.
    5. Wang, Fei & Yuan, Yu & Lu, Liangdong, 2021. "Dynamical prediction model of consumers’ purchase intentions regarding anti-smog products during smog risk: Taking the information flow perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    6. Manoj Anand & Jagandeep Singh, 2018. "Impact of Automobile Regulations on Shareholders’ Wealth: Indian Empirical Evidence," Metamorphosis: A Journal of Management Research, , vol. 17(1), pages 28-40, June.
    7. Yaodong Yang & Huaqing Ren & Han Zhang, 2022. "Understanding Consumer Panic Buying Behaviors during the Strict Lockdown on Omicron Variant: A Risk Perception View," Sustainability, MDPI, vol. 14(24), pages 1-19, December.
    8. Jagandeep Singh, 2018. "Impact of Automobile Recalls on Stock Prices: A Study in the Indian Context," Global Business Review, International Management Institute, vol. 19(2), pages 407-423, April.
    9. Robert L. Heath & Jaesub Lee & Michael J. Palenchar & Laura L. Lemon, 2018. "Risk Communication Emergency Response Preparedness: Contextual Assessment of the Protective Action Decision Model," Risk Analysis, John Wiley & Sons, vol. 38(2), pages 333-344, February.
    10. Peng Cheng & Zhe Ouyang & Yang Liu, 2020. "The effect of information overload on the intention of consumers to adopt electric vehicles," Transportation, Springer, vol. 47(5), pages 2067-2086, October.
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