The Impact of Service Recovery Processes on Consumer Trust and Loyalty in Car Repair Services

ABSTRACT

Although researchers and managers are increasingly paying attention to customer satisfaction, trust, loyalty and service recovery, not much is known about how these constructs interrelate with one another. Previous research has examined the interrelationships among subsets of these constructs. The authors extend this previous research by developing and testing a conceptual framework, considering all of these constructs (complaint encounter-specific evaluations and relational constructs) within a business/consumer environment. The findings show that distributive and interactional justice perceptions of the service recovery impact the satisfaction with the way the complaint is handled, which, in turn, influences the consumer's level of trust. Finally, consumer loyalty is affected by satisfaction, trust and perceived value.

RESUMEN. A pesar del creciente interés demostrado por los investigadores y gerentes en la satisfacción, confianza lealtad y recuperación del servicio del cliente, es poco lo que se conoce sobre cómo estas condiciones se interrelacionan entre sí. Investigaciones anteriores examinaron la interrelación entre los subgrupos de estos elementos. Los autores ampliaron la investigación anterior, desarrollando y poniendo a prueba un marco conceptual, considerando todos estos elementos (las quejas tienen evaluaciones específicas y elementos relacionales) dentro del entorno negocio - consumidor. Los hallazgos muestras que las percepciones de la justicia distributiva e interreaccional de la recuperación del servicio, impactan la satisfacción debido a la forma en que se manipula la queja que, a su vez, influye sobre el nivel de confiabilidad del consumidor. Finalmente, la lealtad del consumidor también se ven afectados por el grado de satisfacción, confianza y el valor que ellos le atribuyen.

RESUMO. Embora pesquisadores e gerentes venham prestando cada vez mais atenção à satisfação, confiança e fidelidade dos clientes e à recuperação de serviço (Service Recovery), pouco se sabe sobre como esses construtos se inter-relacionam. Pesquisas anteriores examinaram as inter-relações entre subconjuntos desses construtos. Os autores estendem essas pesquisas anteriores, desenvolvendo e testando uma estrutura conceitual, considerando todos esses construtos (avaliações de reclamações específicas aos encontros e construtos relacionais) dentro de um ambiente empresa/consumidor. As descobertas mostram que as percepções da justiça distributiva e interacional da recuperação de serviço impactam a satisfação com a forma como a reclamação é manuseada, o que, por sua vez, influencia o nível de confiança do consumidor. Finalmente, a fidelidade dos consumidores é afetada pela satisfação, confiança e valor percebido.     

Estimation of default probabilities using incomplete contracts data

This paper develops a count data model for credit scoring which allows the estimation of default probabilities using incomplete contracts data. The main advantage of the proposed approach is that it permits a more efficient use of the data, including that for the most recent clients. Moreover, because the probability of default is specified as a function of the age of the contract, the model provides some information on the timing of the defaults. The model is based on the beta-binomial distribution, which is found to be particularly adequate for this purpose. A well-known dataset on personal loans is used to illustrate the application of the proposed model.     

Comparison of Classical and Bayesian Approaches for Intervention Analysis

Intervention analysis has been recently the subject of several studies, mainly because real time series present a wide variety of phenomena that are caused by external and/or unexpected events. In this work, transfer functions are used to model different forms of intervention to the mean level of a time series. This is performed in the framework of state-space models. Two canonical forms of intervention are considered: pulse and step functions. Static and dynamic explanation of the intervention effects, normal and non-normal time series, detection of intervention, and study of the effect of outliers are also discussed. The performance of the two approaches is compared in terms of point and interval estimation through Monte Carlo simulation. The methodology was applied to real time series and showed satisfactory results for the intervention models used.     

KEYNES' WAGE–PRICE DYNAMICS

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How Latin American Students Perceive American Advertising

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Women nascent entrepreneurs and social capital in the process of firm creation

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Export Productivity and Specialisation: A Disaggregated Analysis

The paper analyses export productivity and trade specialisation in China, Brazil, India and South Africa. The investigation calculates a time‐varying export productivity measure using highly disaggregated product categories. The modelling shows that export productivity is determined by real income and human capital endowments. But the empirical analysis also reveals significant differences in export productivity and specialisation for countries with comparable per capita income levels.     

The value of switching inputs in a biodiesel production plant

There has been a growing concern in recent years about the quality of the environment and dependence on fossil fuels to supply the world's energy needs, which has created an interest in the development of renewable and less polluting energy sources. One of these alternatives is the biodiesel fuel, which has many advantages over the fossil based diesel, or petro diesel. In this paper we use the real options approach to determine the value of the managerial flexibility embedded in a biodiesel plant that has the option to switch inputs among two different grain commodities. Our results indicate that the option to choose inputs has significant value if we assume that future prices follow stochastic processes such as Geometric Brownian Motion and Mean Reversion Models, and can be sufficient to recommend the use of input commodities that would not be optimal under traditional valuation methods. We also show that the choice of model and parameters has a significant impact on the valuation of this class of projects.     

The Role of Market Orientation In Business Dyadic Relationships: Testing an Integrator Model

Over the last decade market orientation and relationship marketing have been huo of the most outstanding fields of research within Marketing discipline. However, little at tention has been devoted towards the investigation of the interface existing between both concepts. The aim of this study is to overcome this deficiency. Thus, the paper begins with a review of the existing literature into relationship marketing and market orientation as well as their main constructs. The result of this analysis is the proposal of a theoretical causal model in which the cultural market orientation that buyer firms show appears as a conditioning factor of their loyalty towards a supplier. Next, the methodology followed as well as the empirical contrast of the model proposed are thoroughly presented. R e empirical data was obtained from huo personal surveys conducted on the same sample of 141 industrial companies. Finally, results, conclusions and practical implications are discussed. In this way, the research proves that a buyer firm’s cultural market orientation acts as an indirect antecedent to the degree of loyalty shown to its main supplier.     

On some properties of Markov chain Monte Carlo simulation methods based on the particle filter

Andrieu et al. (2010) prove that Markov chain Monte Carlo samplers still converge to the correct posterior distribution of the model parameters when the likelihood estimated by the particle filter (with a finite number of particles) is used instead of the likelihood. A critical issue for performance is the choice of the number of particles. We add the following contributions. First, we provide analytically derived, practical guidelines on the optimal number of particles to use. Second, we show that a fully adapted auxiliary particle filter is unbiased and can drastically decrease computing time compared to a standard particle filter. Third, we introduce a new estimator of the likelihood based on the output of the auxiliary particle filter and use the framework of Del Moral (2004) to provide a direct proof of the unbiasedness of the estimator. Fourth, we show that the results in the article apply more generally to Markov chain Monte Carlo sampling schemes with the likelihood estimated in an unbiased manner.