Over the past decade Service Quality Measurement (SQM) has been receiving more attention worldwide and taking a more central role as a measurement of success. The notion of Service Quality is found well documented throughout the literature and describes the interactive process between the customer and the service provider. In general, the SQM is a powerful technique to monitor customer satisfaction, helping to focus on key areas of improvement in order to establish a new baseline to the current service quality rating.
The importance for service organisations is twofold: firstly, in the implications entailed in how to choose the most appropriate technique of service quality measurement, and secondly, in how service organisations can influence the perceptions of an individual customer/user in relation to the service encounter he/she is participating in. Empirically, this involves moving away from a standardised model of the same service for everybody to an approach where the best way of achieving excellent performance lies in addressing the subjective needs of an individual customer, providing precisely the specific service that reflects customers/ individuals’ perceptions.
In other words, service is not so much what the business does, per se, but what the customer experiences (Martin 1999i).
Contents :
i. Abstract
1.0 Introduction
2.0 Part A - Questionnaire “Palavrion Corporation”
2.1 Comments - Strengths & Weaknesses
2.2 Probability Based Sampling Strategy
2.3 Non-Probability Based Sampling Strategy
3.0 Part B: Service Quality Satisfaction Survey - ADMECO AG
3.1 Introduction
3.1.1 Overview of ADMECO AG
3.2 Problem Description & Objectives of Survey
3.3 Definition of Population & Sampling Process
3.3.1 Population
3.3.2 Sampling; Consideration & Process
3.4 Questionnaire Design
3.4.1 Procedure & Guiding Principle
3.4.2 Guiding Principle
3.4.3 Design & Layout
3.4.4 Pre-test the Questionnaire
3.5 Result of Survey
3.5.1 Response Rate
3.5.2 Overview of Answers
3.5.3 Personal Interaction - Analysis of Section
3.5.4 Business Savvy - Analysis of Section
3.5.5 Added Value - Analysis of Section
3.6 Conclusion
4.0 Part C: Middling Records - Data Analysis
4.1 Introduction
4.2 Presentation of Data
4.3 Retrospective Analysis
4.3.1 Model Validation
4.3.1.1 Multiple R
4.3. 1.2 Correlation Coefficient (R )
4.3.1.3 Confidence Interval (CI)
4.3.1.4 Outliers
4.4 Regression Model of CQSI - Forecasting 4 th Quarter
4.5 Comparison between Outlets - Impact on Sampling Strategy/Forecast
5.0 Part D - Reflection
5.1 Sampling Process/Questionnaire
5.2 Data Analysis
6.0 Appendices
6.1 Palavrion Corporation Survey Form
6.2 Service Quality Satisfaction Survey - ADMECO AG
6.3 Middling Records Data Tables
7.0 References
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