Predicting Customer Satisfaction Towards Mobile Value-Added Services : An Application of Multiple Regression

The Mobile Value-Added Services (MVAS) make a significant share in non-voice revenue in the Indian telecom sector. The MVAS are considered as growth drivers, source of revenue and key differentiators at the time when the industry is facing a sluggish growth due to decline in minutes of use per connection per month, average revenue per user per month, intense competition, and fall in voice tariffs. The present study is an attempt to analyze customer satisfaction for MVAS by using parametric and non-parametric test procedures. M-Commerce, M-Education, M-Health and M-Entertainment have been identified as important determinants that affect customer satisfaction in MVAS. Multiple regression analysis has been used to predict the customer satisfaction and also examine the relative importance of each determinant in affecting the customer satisfaction. Validity, assumptions and generalization of results have also been examined so as to make inferences about the population