Avaliação da Qualidade do Transporte Colectivo Urbano, na Cidade da Praia, e a Satisfação dos Utentes

A qualidade nas organizações de serviço tem-se tornado num tópico de muita importância, sendo reconhecida como uma variável estratégica para aumentar a sua eficácia e eficiência, ganhar vantagem competitiva e conduzir à satisfação dos seus clientes. Promover uma escala apropriada, que reflicta convenientemente as percepções e as expectativas dos clientes, deve ser uma preocupação tanto dos gestores de empresas como das agências governativas. O presente estudo empírico desenvolve e analisa uma escala de medição da qualidade de serviço, através da aplicação do modelo SERVQUAL, desenvolvido por Parasuraman et al. (1985, 1988, 1991), e adaptado para o serviço de transporte colectivo urbano de passageiros (TCUP). O procedimento levado a efeito na presente investigação apresenta 4 fases e 9 etapas, com a combinação do paradigma de Churchill (1979) e entrevistas focus group. A escala final SERVQUAL adaptada, com 23 itens, e as dimensões obtidas indicam que a mesma é altamente fiável (0,891) e válida, demonstrando assim que o procedimento seguido é aplicável e que os seus itens foram desenhados de acordo com as condições do sector. A pesquisa exploratória foi conduzida em Cabo Verde, na cidade da Praia, em Setembro de 2008, com 230 utentes regulares do serviço de TCUP. Os dados confirmam a existência de gaps, encontrando-se a maioria dos inquiridos (67%) insatisfeita com esse serviço. A análise factorial confirmou a existência de cinco dimensões, que determinam a qualidade de serviço no TCUP, na Praia, pela seguinte ordem de importância: “aparência física dos veículos/conforto”, “atenção personalizada/desempenho dos colaboradores”, “empatia”, “conveniência do serviço”, e, por último, “equipamento tangível”. Service quality has become a topic of great importance and it is recognized as a strategic variable to increase its efficiency and effectiveness in getting competitive advantage and leading to customer satisfaction. To seek a proper scale that can reflect perceptions and customers’ expectations accurately should be a concern for business managers as well as government agencies. Present empirical study develops and analyzes a measurement scale of quality service, through the application of SERVQUAL model developed by Parasuraman et al. (1985, 1988, 1991) and adapted for the urban passenger transportation. The procedure followed in present research indicates four phases and nine steps in connection to Churchill paradigm (1979) and focus group interview. The adapted final SERVQUAL scale, with 23 items, and the dimensions obtained indicated that it is highly reliable (0.891) and valid, showing this way that the procedure followed is applicable and their items were drawn according to the sector conditions. This exploratory research was performed in Cape Verde, at Praia in September 2008 with 230 regular’s users of bus service. The data confirms the existence of gaps and that the majority of the inquired are not pleased (67%) with their bus service. The factorial analysis confirms the existence of five dimensions, which determines the service quality in the bus service at Praia according to the following order of importance : “physical appearance of the bus/confort”, “personalized attention/results from the collaborators”, “empathy”, “service convenience” and lastly “tangible equipment”.

One-sided tolerance interval in a two-way balanced nested model with mixed effects

In many research areas (such as public health, environmental contamination, and others) one deals with the necessity of using data to infer whether some proportion (%) of a population of interest is (or one wants it to be) below and/or over some threshold, through the computation of tolerance interval. The idea is, once a threshold is given, one computes the tolerance interval or limit (which might be one or two - sided bounded) and then to check if it satisfies the given threshold. Since in this work we deal with the computation of one - sided tolerance interval, for the two-sided case we recomend, for instance, Krishnamoorthy and Mathew [5]. Krishnamoorthy and Mathew [4] performed the computation of upper tolerance limit in balanced and unbalanced one-way random effects models, whereas Fonseca et al [3] performed it based in a similar ideas but in a tow-way nested mixed or random effects model. In case of random effects model, Fonseca et al [3] performed the computation of such interval only for the balanced data, whereas in the mixed effects case they dit it only for the unbalanced data. For the computation of twosided tolerance interval in models with mixed and/or random effects we recomend, for instance, Sharma and Mathew [7]. The purpose of this paper is the computation of upper and lower tolerance interval in a two-way nested mixed effects models in balanced data. For the case of unbalanced data, as mentioned above, Fonseca et al [3] have already computed upper tolerance interval. Hence, using the notions persented in Fonseca et al [3] and Krishnamoorthy and Mathew [4], we present some results on the construction of one-sided tolerance interval for the balanced case. Thus, in order to do so at first instance we perform the construction for the upper case, and then the construction for the lower case.