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Expectations, Exit, and Voice: Big Data Evidence on Service Quality, Customer Segmentation, and Platform Response

Sadeghi, Amir Hossein | 2025

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 58218 (44)
  4. University: Sharif University of Technology
  5. Department: Management and Economics
  6. Advisor(s): Ansari, Mahdi; Ibrahim Haidar, Jamal
  7. Abstract:
  8. The growing availability of big data enables researchers to go beyond surveys and experiments to observe actual customer behavior in real-time. Understanding customer reactions to service quality is also vital for businesses. Using big data from a courier service company, covering about 70 million package deliveries, we examine how service quality influences customer behavior and how the company responds. We analyze the effect of service quality on demand, differentiating between new and returning customers. We develop a habit formation model and demonstrate that customers form expectations based on their past interactions with the company. Their sensitivity to service quality depends on the difference between the received service quality and their expectations. When service quality falls below expectations, it significantly reduces future demand. New customers are more likely to churn, while returning customers decrease their demand. We further explore whether dissatisfied customers exit or voice complaints. An increase in average delivery time does not significantly affect complaints on social media, but it raises the customer churn rate. Finally, we demonstrate that the company improves its performance by increasing delivery speed in response to customer churn
  9. Keywords:
  10. Big Data ; Customer Segmentation ; Service Quality ; Protest ; Customers Exit ; Expectations Formation

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