Quantifying the Dynamic Effects of Service Recovery on Customer Satisfaction

Mais informações

Aims and Objectives

por franco wong

Computational Journalism

por Lluis Codina

Visual metaphors

por J M

Dropbox

por Dussadee Leesan

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