A FORMATIVE MODEL FOR MEASURING CUSTOMER SATISFACTION WITH A DEGREE COURSE

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1 A FORMATIVE MODEL FOR MEASURING CUSTOMER SATISFACTION WITH A DEGREE COURSE GIOVANNA NICOLINI FRANCESCA DE BATTISTI Woring Paper n Settembre Dipartimento di Economia Politica e Aziendale Università degli Studi di Milano via Conservatorio, Milano tel. ++39/02/ fax ++39/02/ E Mail: dipeco@unimi.it Pubblicazione depositata presso gli Uffici Stampa della Procura della Repubblica e della Prefettura di Milano

2 A Formative Model for Measuring Customer Satisfaction with a Degree Course Giovanna Nicolini - Francesca De Battisti Dipartimento di Economia Politica e Aziendale Università degli Studi di Milano giovanna.nicolini@unimi.it francesca.debattisti@unimi.it. Introduction Customer satisfaction with a service/product (p/s) can be measured through a survey of the actual perception of the users or otherwise comparing their actual perception with their expectations. More appropriately in the first case quality is considered, in the second customer satisfaction (CS) (Cronin et al.992,994). Therefore to measure the CS we have to compare the evaluations of the user with his expectations connected to an ideal p/s. For some inds of p/s such expectations are typically subjective, they have to be gathered ad hoc; for others they can be suggested by the provider the p/s referring to an optimum p/s; in this way the expectations are collected in an objective way. This paper proposes an index founded on objective expectations, with the aim of measuring the CS of a service such as a university degree course (DC) provided by the Italian universities. In fact the quality of university teaching has been tested for many years now submitting a questionnaire to the students attending the courses and present at the end of each course; the questionnaire is divided into four dimensions: particular organisation of the teaching, characteristics of the teaching, characteristics of the exercises, general organisation of the teaching within the overall degree course. A different number of attributes are associated to each dimension, with a different question lined to each attribute, and the student answers using an item scale. Afterwards we substitute items for scores, with m as the minimum value and M the maximum, the same for all the questions. By means of an item scale the student tells his personal satisfaction, while the expected satisfaction will be considered objectively the same for all the questions and equal to the maximum value M on the same scale. It follows that the level of satisfaction, for each question, can be defined by a function measuring the differences between the scores observed and the maximum M. The function chosen G is similar to that proposed by Minowsy with parameter. And since such a function is concerned with a single question, we have to use a model to combine them in an overall CS measure. To this end formative models are proposed; SERVQUAL is an example, it is a global measure obtained by the weighted mean of the dimension indexes, which are simple means of the differences between the scores observed and those expected by each

3 individual. In SERVQUAL the problem of weighting is concerned only with the dimensions and is often solved by asing the interviewed to give a weight to the dimensions themselves (with the constraint that the sum of weights is equal to one). The index proposed in this paper is within the logic of the formative models, but nonetheless presents some particulars regarding: a) a second level of aggregation, b) a different number of respondents. In fact, in this case the means of the dimensions do not lead to a CS global measure (as in SERVQUAL), but only to a partial measure regarding the teaching; it is the combination of these latter measures that lead to the overall CS index for DC. Lastly the different teaching courses are attended by a different number of students and moreover often item non-response is verified. While point a) is easily solved, point b) requires careful examination to establish opportune weights for the different levels. In paragraph 2 the index G is briefly set out, in paragraph 3 the method for calculating the overall index is shown and lastly, in paragraph 4, the variability within and between the intermediate levels (dimensions and teaching) is analysed to obtain the overall variability measure. 2. Distance Indexes G Let n be a population size of individuals giving their personal satisfaction with an attribute y of a service dimension; let y, with =,..., K ; m y M, a score on an evaluation scale and n, with n = n, the number of individuals choosing y. To obtain a function of the differences between the values y and the maximum value M we use the measures of distance proposed by Minowsi: G * K = n = y M n. () The index () can be normalised taing it to its maximum value (Fabbris, 2000): K * y M n K G * ( ( ) ) = G = = = y M f, (2) Max G M m n M m = where f = n n. We observe 0 G ; in fact, G is equal to zero when all the units of the population are gathered at the maximum value, it is equal to one when all the units are gathered at the maximum distance from the optimum and tae on increasing values because of their gap from the optimum. Moreover such an index can be used with any score scale and it is independent of the type of scale chosen (Fabbris, 2000). Taing in formula (2) = and = 2 we have the following indexes: 2

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