925 resultados para Customer services quality, Hedonic service consumption, Perceived service quality, Retail environment, Retailing, Service convenience, Social servicescape


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During the past years, the industry has shifted position and moved towards “the luxury universe” whose customers are demanding, treating individuals as unique and valued customer for the business, offering vehicles produced with the state of the art technologies and implementing the highest finishing standards. Due to the competitive level in the market, car makers enable processes which equalizes customer services to E.R. management, being dealt with the maximum urgency that allows the comparison between both, car workshops and emergency rooms, where workshop bays or ramps will be equal to emergency boxes and skilled technicians are equivalent to the health care specialist, who will carry out tests and checks prior to afford any final operation, keeping the “patient” under control before it is back to normal utilization. This paper establishes a valid model for the automotive industry to estimate customer service demand forecasting under variable demand conditions using analogies with patient demand models used for the medical ER.

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During the past years, the industry has shifted position and moved towards “the luxury universe” whose customers are demanding, treating individuals as unique and valued customer for the business, offering vehicles produced with the state of the art technologies and implementing the highest finishing standards. Due to the competitive level in the market, motor makers enable processes which equalizes customer services to E.R. management, being dealt with the maximum urgency that allows the comparison between both, car workshops and emergency rooms, where workshop bays or ramps will be equal to emergency boxes and skilled technicians are equivalent to the health care specialist, who will carry out tests and checks prior to afford any final operation, keeping the “patient” under control before it is back to normal utilization. This paper ratify a valid model for the automotive industry to estimate customer service demand forecasting under variable demand conditions using analogies with patient demand models used for the medical ER

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La computación basada en servicios (Service-Oriented Computing, SOC) se estableció como un paradigma ampliamente aceptado para el desarollo de sistemas de software flexibles, distribuidos y adaptables, donde las composiciones de los servicios realizan las tareas más complejas o de nivel más alto, frecuentemente tareas inter-organizativas usando los servicios atómicos u otras composiciones de servicios. En tales sistemas, las propriedades de la calidad de servicio (Quality of Service, QoS), como la rapídez de procesamiento, coste, disponibilidad o seguridad, son críticas para la usabilidad de los servicios o sus composiciones en cualquier aplicación concreta. El análisis de estas propriedades se puede realizarse de una forma más precisa y rica en información si se utilizan las técnicas de análisis de programas, como el análisis de complejidad o de compartición de datos, que son capables de analizar simultáneamente tanto las estructuras de control como las de datos, dependencias y operaciones en una composición. El análisis de coste computacional para la composicion de servicios puede ayudar a una monitorización predictiva así como a una adaptación proactiva a través de una inferencia automática de coste computacional, usando los limites altos y bajos como funciones del valor o del tamaño de los mensajes de entrada. Tales funciones de coste se pueden usar para adaptación en la forma de selección de los candidatos entre los servicios que minimizan el coste total de la composición, basado en los datos reales que se pasan al servicio. Las funciones de coste también pueden ser combinadas con los parámetros extraídos empíricamente desde la infraestructura, para producir las funciones de los límites de QoS sobre los datos de entrada, cuales se pueden usar para previsar, en el momento de invocación, las violaciones de los compromisos al nivel de servicios (Service Level Agreements, SLA) potenciales or inminentes. En las composiciones críticas, una previsión continua de QoS bastante eficaz y precisa se puede basar en el modelado con restricciones de QoS desde la estructura de la composition, datos empiricos en tiempo de ejecución y (cuando estén disponibles) los resultados del análisis de complejidad. Este enfoque se puede aplicar a las orquestaciones de servicios con un control centralizado del flujo, así como a las coreografías con participantes multiples, siguiendo unas interacciones complejas que modifican su estado. El análisis del compartición de datos puede servir de apoyo para acciones de adaptación, como la paralelización, fragmentación y selección de los componentes, las cuales son basadas en dependencias funcionales y en el contenido de información en los mensajes, datos internos y las actividades de la composición, cuando se usan construcciones de control complejas, como bucles, bifurcaciones y flujos anidados. Tanto las dependencias funcionales como el contenido de información (descrito a través de algunos atributos definidos por el usuario) se pueden expresar usando una representación basada en la lógica de primer orden (claúsulas de Horn), y los resultados del análisis se pueden interpretar como modelos conceptuales basados en retículos. ABSTRACT Service-Oriented Computing (SOC) is a widely accepted paradigm for development of flexible, distributed and adaptable software systems, in which service compositions perform more complex, higher-level, often cross-organizational tasks using atomic services or other service compositions. In such systems, Quality of Service (QoS) properties, such as the performance, cost, availability or security, are critical for the usability of services and their compositions in concrete applications. Analysis of these properties can become more precise and richer in information, if it employs program analysis techniques, such as the complexity and sharing analyses, which are able to simultaneously take into account both the control and the data structures, dependencies, and operations in a composition. Computation cost analysis for service composition can support predictive monitoring and proactive adaptation by automatically inferring computation cost using the upper and lower bound functions of value or size of input messages. These cost functions can be used for adaptation by selecting service candidates that minimize total cost of the composition, based on the actual data that is passed to them. The cost functions can also be combined with the empirically collected infrastructural parameters to produce QoS bounds functions of input data that can be used to predict potential or imminent Service Level Agreement (SLA) violations at the moment of invocation. In mission-critical applications, an effective and accurate continuous QoS prediction, based on continuations, can be achieved by constraint modeling of composition QoS based on its structure, known data at runtime, and (when available) the results of complexity analysis. This approach can be applied to service orchestrations with centralized flow control, and choreographies with multiple participants with complex stateful interactions. Sharing analysis can support adaptation actions, such as parallelization, fragmentation, and component selection, which are based on functional dependencies and information content of the composition messages, internal data, and activities, in presence of complex control constructs, such as loops, branches, and sub-workflows. Both the functional dependencies and the information content (described using user-defined attributes) can be expressed using a first-order logic (Horn clause) representation, and the analysis results can be interpreted as a lattice-based conceptual models.

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Research has shown that more than half of attempted recovery efforts fail, producing a ‘double deviation’ effect. Surprisingly, these double deviation effects have received little attention in marketing literature. This paper examines what happens after these critical encounters, which behavior or set of behaviors the customers are prone to follow and how customers’ perceptions of the firm’s recovery efforts influence these behaviors. For the analysis of choice of the type of response (complaining, exit, complaining and exit, and no-switching), we estimate multinomial Logit models with random coefficients (RCL). The results of our study show that magnitude of service failure, explanations, apologies, perceived justice, angry and frustration felt by the customer, and satisfaction with service recovery have a significant effect on customers’ choice of the type of response. Implications from the findings are offered.

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Mode of access: Internet.

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In small-service settings, how do owner satisfaction, front-line employee satisfaction, and customer satisfaction relate to one another? The authors use generalized exchange theory (GET) to examine how satisfaction levels of these three constituents are reciprocated. The authors examine a European franchise system comprising 50 outlets, 933 employees, and 20,742 customers. Their results show two important findings. First, the effect of owner-franchisee's satisfaction on customer satisfaction is fully mediated by front-line employee satisfaction. Thus, managers of a service outlet can strongly impact the satisfaction and behavioral intentions of their customer base, even without direct contact with them. Second, the link between customer satisfaction and purchase intention is moderated by employee satisfaction at an outlet. The link between customer satisfaction and customer purchase intentions is almost twice as strong when employees are satisfied than when they are not. Thus, there is a "doublepositive effect:" not only does higher employee satisfaction at an outlet directly lead to higher customer satisfaction but it also indirectly strengthens the association between customer satisfaction and their repurchase intentions.

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Price increases seem to be an adequate way to improve the earnings of companies. This fact becomes especially crucial because of increased price competition in many markets. Price increases might lead to negative customer reactions, such as a lower perceived utility or a lower loyalty intention. Therefore, the question for managers remains how prices can be increased without losing customers. Results of our experimental study suggest that customers of energy suppliers rate the perceived utility of the offer relatively better when the price increase is combined with an additional modification of the product or accompanied by a new service. It becomes clear that intensifying service relations can offset the negative effects of price increases.

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Service-based systems are applications built by composing pre-existing services. During design time and according to the specifications, a set of services is selected. Both, service providers and consumers exist in a service market that is constantly changing. Service providers continuously change their quality of services (QoS), and service consumers can update their specifications according to what the market is offering. Therefore, during runtime, the services are periodically and manually checked to verify if they still satisfy the specifications. Unfortunately, humans are overwhelmed with the degree of changes exhibited by the service market. Consequently, verification of the compliance specification and execution of the corresponding adaptations when deviations are detected cannot be carried out in a manual fashion. In this work, we propose a framework to enable online awareness of changes in the service market in both consumers and providers by representing them as active software agents. At runtime, consumer agents concretize QoS specifications according to the available market knowledge. Services agents are collectively aware of themselves and of the consumers' requests. Moreover, they can create and maintain virtual organizations to react actively to demands that come from the market. In this paper we show preliminary results that allow us to conclude that the creation and adaptation of service-based systems can be carried out by a self-organized service market system. © 2012 IEEE.

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Manufacturing companies have passed from selling uniquely tangible products to adopting a service-oriented approach to generate steady and continuous revenue streams. Nowadays, equipment and machine manufacturers possess technologies to track and analyze product-related data for obtaining relevant information from customers’ use towards the product after it is sold. The Internet of Things on Industrial environments will allow manufacturers to leverage lifecycle product traceability for innovating towards an information-driven services approach, commonly referred as “Smart Services”, for achieving improvements in support, maintenance and usage processes. The aim of this study is to conduct a literature review and empirical analysis to present a framework that describes a customer-oriented approach for developing information-driven services leveraged by the Internet of Things in manufacturing companies. The empirical study employed tools for the assessment of customer needs for analyzing the case company in terms of information requirements and digital needs. The literature review supported the empirical analysis with a deep research on product lifecycle traceability and digitalization of product-related services within manufacturing value chains. As well as the role of simulation-based technologies on supporting the “Smart Service” development process. The results obtained from the case company analysis show that the customers mainly demand information that allow them to monitor machine conditions, machine behavior on different geographical conditions, machine-implement interactions, and resource and energy consumption. Put simply, information outputs that allow them to increase machine productivity for maximizing yields, save time and optimize resources in the most sustainable way. Based on customer needs assessment, this study presents a framework to describe the initial phases of a “Smart Service” development process, considering the requirements of Smart Engineering methodologies.

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Traditionally, service encounters have included an interpersonal interaction between the service provider and the customer. The introduction ofself-service technologies to the service encounter, however, is reducing and in some cases, eliminating this interpersonal interaction. Self-se rvice technology is where the customer delivers the service themselves using a technological interface. This CIM funded research programme investigates the effect of self-service technology on the service encounter, and in turn on consumer satisfaction and consumer commitment. This paper reviews the literature relevant to the current study and outlines the constructs of interest in this study. The resear ch hypotheses and conceptual model are also introduced.Finally, the agenda for future research is presented.

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Australian and international governments are increasingly adopting social marketing as a social change management tool to deal with complex social problems. Government decision makers typically need to balance the use of business models and management theories whilst maintaining the integrity of government policy. In taking this approach, decision makers experience management tensions between a social mission to equitably deliver social services and the accountability and affordability of providing quality social and health services to citizens. This is a significant challenge as the nature of the ‘social product’ in government is often more service-oriented than goods-based. In this paper the authors examine value creation in government social marketing services. The contribution of this paper is a value creation process model, which considers the nature of governments to create social good. This is particularly important for governments where consumers still expect value and quality in the service delivered, despite that offering being ‘free’.

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Objective: To identify service providers’ and community organisations’ perceptions of the resources available to support people with mental illness and the unmet needs of this client group in rural Queensland. Design: An exploratory study was undertaken involving focus group interviews across the study sites. Setting: Five regional towns in rural Queensland. Participants: Ten to 14 members were recruited for each of the five focus groups. The groups represented a diverse mix of participants including health and community service providers and representatives from community organisations. Results: Participants identified gaps in services in relation to health, employment and education, housing and accommodation, transport and social inclusion and health promotion. Inter-service communication and inappropriate funding models were themes affecting service delivery. Conclusions: Specific service issues of housing and transport were identified to be particularly problematic for people with mental illness across all towns. Intersectoral communication and funding models require further research.