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This applies, for example, to commonly used linear regression models. The possibility of prediction is also reduced due to the requirements imposed on the form of individual variables. This does not always allow for a clear and immediate assessment. In many analyses, customer satisfaction is defined as a quantitative variable, most often expressed as a percentage. The most popular method in literature is SERVQUAL or six sigma tools. They can be used to make corrections and streamline processes carried out. Methods aimed at studying or measuring the achieved quality of services play an important role in the process of developing high standards of customer service and its accompanying elements.
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The lack of quantifiable measures and limited availability of empirical data are also not conducive to its analysis, which is why some research in this area are simulation studies. It is, however, a result of numerous elements, often difficult to measure, sometimes even to identify.
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The high quality of services provided is of key importance for maintaining a proper level of customer satisfaction and increasing the revenues of each company. The research showed which of them (and how strongly) affect the dependent variable, which allowed for modification of strategy and implementation of new solutions increasing the number of satisfied customers. From among the possible ones, regressors whose influence was statistically significant and whose modification was possible were selected. The dichotomous form of the predictor taking two values - late and on-time delivery - was determined. The quality of service assessment was considered from the point of view of delivery time. As the most profitable group of customers are local car repair shops, it was this group that was subject to analysis. The research was conducted on the basis of a distribution and trade company dealing with the supply of automotive spare parts. This article proposes logistic regression. There are different methods for such an analysis. Maintaining the already held position and further expansion requires adjusting the level of services provided to the needs and requirements of customers, as well as continuous surveying, monitoring and adjusting the implemented strategy. 2022.Īll rights reserved.Transport companies operate in a dynamically developing and competitive market. In reference cell coding, the first category acts as aīaseline, and you can interpret the other coefficients as an increase or decrease in the log odds ratio over the baseline category.
#FOUR PARAMETER LOGISTIC REGRESSION WITH POLYMATH SOFTWARE CODE#
There are different ways to code the predictors for a categorical variable, the most common method in logistic regression is called reference cell coding or dummy coding. For each term involving a categorical variable, a number of dummy predictor variables are created to predict the effect of each different level. When the model contains categorical variables, the interpretation of the coefficients is more complex. Interval for each parameter shows the uncertainty in the estimate. A positive sign indicates that the explanatory variable increases the probability of the outcome, while a negative sign indicates that the variable decreases the probability of that outcome.
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The unknown model parameters are estimated using maximum-likelihood estimation.Ī coefficient describes the size of the contribution of that predictor a large coefficient indicates that the variable strongly influences the probability of that outcome, while a near-zero coefficient indicates that variable has little influence on the probability of that outcome. One-unit change of the predictor, all other predictors being held constant. Parameter estimates (also called coefficients) are the log odds ratio associated with a