Kategoriak: All - models - data - strategies - recovery

arabera Jorge Gnecco 5 years ago

279

Quantifying the Dynamic Effects of Service Recovery on Customer Satisfaction

This document explores the impact of service recovery strategies on customer satisfaction through various dynamic models and hypotheses. It delves into the use of a Vector Autoregressive Model to analyze the buildup and decay of customer satisfaction over time, employing Bayesian methods for parameter estimation.

Quantifying the Dynamic Effects of Service Recovery on Customer Satisfaction

Quantifying the Dynamic Effects of Service Recovery on Customer Satisfaction

Models

Modeling Short or Long Decay and Buildup Intensity
Estimating Parameters: Bayesian Method
Modeling the Marketing Dynamics: Vector Autoregressive Model

Data and Measures

Data Stationarity and Granger Casuality Tests
Controls to Rule Out Alternative Explanations to the Results
Measures
Data Setting

Dynamic Effects of Service Recovery on Customer Satisfaction

Hypotheses on the Dynamic Effects of Service Recovery
Service Recovery Strategies

Results

Results on Buildup and Decay
VAR Model Results

Managerial Implications for the Role of Service Recovery in Regaining Customer Satisfaction

Required Service Recovery Efforts to Regain Customer Satisfaction to 95%
Sources of Regained Customer Satisfaction

Research Implications and Conclusions

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