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Customer satisfaction (CS) has become an important issue for commercial and public service organisations. Companies win or lose based on what percentage of their customers…
Customer satisfaction (CS) has become an important issue for commercial and public service organisations. Companies win or lose based on what percentage of their customers they can keep. Success is largely about retention of customers, which again depends on CS level. It would be a great help to be able to comprehensively measure the quality of product and service, by relating the measures of quality to real customer behaviour. Some companies get feedback about CS through the percentage of complaints, some through non‐systematic surveys, again some do not measure CS at all, because “the system would not add anything useful and is very time‐consuming”. Give three managers in the same company the same objective: to improve CS, however it may be measured, and they will come up with three distinctly different and incompatible plans. CS requires a number of ingredients, all of which need to be considered. Aims to develop and simplify measurement systems by using a general formula that makes quantitative measurement of CS possible. Considers four important aspects that have a negative or positive influence on profitability related to CS.
The paper aims to develop an evaluation model of the customer satisfaction index (CSI) in an R&D organization. A conceptual framework on customer satisfaction with a…
The paper aims to develop an evaluation model of the customer satisfaction index (CSI) in an R&D organization. A conceptual framework on customer satisfaction with a probabilistic approach has been attempted based on customer requirements and expectations in compliance with the clauses of ISO 9001:2008.
A survey through a well‐designed customer feedback data sheet has been used as an effective tool for the measurement of CSI. The questionnaire was framed on the basis of the requirements of a quality management system with advice to the customer for allotting grade points on a given scale to the quality parameters. The research model has been analyzed based on a fault‐tree approach and the probability of failure of each quality parameter has been assigned on the basis of grade point average. Data analysis for the estimation of the probability of failure at a customer satisfaction level (CSL) was carried out based on the probability of failure of each quality element graded by the customers. The data were also tested through statistical inference of whether customer‐to‐customer satisfaction level differs or not.
As a result of case study analysis, 88 percent of customers are fully satisfied. This gives significant information to the management process as well as providing a guiding tool for future improvements. The analysis was carried out based on a framed questionnaire graded by the customer and the result reveals that there is no significant difference between customer satisfaction levels.
This model can be used by any organization, irrespective of the number of customers participating, as well as the number of quality parameters being assigned in the customer feedback analysis.
A literature review found that there are various approaches for evaluating a CSI. The paper describes how a newly‐applied conceptual model based on the failure of CSL in the form of a fault‐tree approach was designed and how the probability of failure of each element/parameters was assigned on the basis of a grade point average to evaluate the CSI, as well as the variation in satisfaction levels between customers being analyzed.