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.

Qualidade de Serviço numa unidade Hoteleira em São Vicente

A satisfação dos clientes é uma forma das empresas se manterem no mercado a partir da conquista dos seus parceiros comerciais, por isso o tema satisfação ganhou maior importância no contexto da administração de empresas. Dado o crescente fenómeno competitivo da indústria hoteleira, o objectivo deste estudo foi aumentar a compreensão das percepções sobre a qualidade do serviço de um hotel, da perspectiva dos seus consumidores. Além disso, este estudo também pretendeu explorar a relação entre a satisfação global e nove factores de qualidade num serviço sendo eles: “higiene e limpeza”, “decoração”, “conforto”, “funcionários”, “alimentação”, “animação”, “serviços de apoio”, “quarto”, e “relação qualidade/preço”. Esta pesquisa acedeu as percepções da qualidade do serviço no hotel através da aplicação de um questionário abrangendo uma amostra de 16 respondentes (hospedes que de livre vontade responderam ao questionário). Os dados recolhidos foram analisados em SPSS (Statistical Package for Social Sciences). Verificamos os seguintes resultados: São o conforto (primeiro lugar), a higiene e limpeza (em segundo) e os serviços de apoio (em terceiro) que mais influenciam a satisfação global no hotel. Costumer’s satisfaction is one way for companies to keep in the market by the conquest of its trading partners; hence, the theme of satisfaction gained greater importance in the context of business administration lately. Given the increasing competitive phenomenon in the touristic industry, the aim of this study was to increase the comprehension of perceptions towards hotel service quality from the hotel customer’s perspective. Besides, this study also intended to explore the relationship between the overall satisfaction and nine service quality factors, namely: “cleanness”, “decoration”, “comfort”, “staff”, and “food/beverage”, “entertainment” “support services”, “rooms and “relation quality/price”. This research assessed the ‘perceptions of service quality’ by applying a questionnaire comprising a sample of 16 guests that responded it correctly. Data collected was analyzed using SPSS - (Statistical Package for Social Sciences). The results indicated the following: comfort (in the first place), cleanness (in the second) and support services (in the third) are the factors that most influence the overall satisfaction in a hotel.