Competitive strategies are an essential tool for sustainable competitive advantage. Particularly in the service industry, strategy has its significance as it plays a vital role in achieving customer satisfaction. This study investigates alignment of four service characteristics i.e. servicescape, service quality, quality and value with the firms’ strategy and how this alignment achieves customer satisfaction. A set of hypotheses were formulated to portray the significance of each of the four service characteristics and customer satisfaction in accordance with the firms’ competitive strategy. The investigations were done particularly within the fast-food industry, comparing two well-known fast-food chain restaurants namely, McDonalds and Max. A survey questionnaire covering the four service characteristics was prepared and distributed among the possible respondents. The analysis of the results was done with the help of SPSS. The results do not show any significant difference in McDonald’s or Max’s strategy in alignment of the four service characteristics. This thesis helps to understand the strategy dynamics of the service industry firms and what is or is not significant to them when customer satisfaction is to achieved; particularly for the fast-food industry.

Le secteur des services revêt une importance croissante dans toute économie. La croissance de la productivité et celle de l'emploi sont étroitement liées au succès des industries de services, et les services sont depuis récemment, de puissants moteurs de croissance économique dans nombre d'économies. Mais malgré son importance économique, le secteur des services a reçu relativement peu d’attention jusqu’ici dans les travaux d’analyse et d’enquête. Ce manque d’intérêt est attribuable à une vision négative entretenue longtemps par la réflexionEconomique sur le rôle des services.La place grandissante des services et l’accroissement de la concurrence dans le secteur tertiaire soulèvent de nombreuses questions parmi lesquelles la gestion du processus de production des services, la mesure de la productivité et de la qualité des activités de service etL’évaluation de la valeur ajoutée par le client.Dans le cadre de cette thèse, nous essayerons de mettre en valeur la position axiale qu’occupent les services dans l’espace économique grâce notamment à leurs propriétés et caractéristiques intrinsèques ainsi qu’à l’évolution des approches économiques s’y rapportant. L’étude proposée passe aussi par la recherche des caractéristiques communes aux biens et aux services afin d’établir une typologie des systèmes de production puis par l’analyse des modèles de gestion propres aux biens et au service afin de réutiliser les éléments congruents de chacun pour la proposition de modèles de gestion de chacun des types identifiés. Une analyse sectorielle de terrain nous permettra par la suite d’étudier la concordance des approches théoriques avec la réalité du terrain, afin de confirmer ou d’infirmer nos hypothèses de départ, ce qui nous aidera à mettre en place notre modèle conceptuel des services. Deux secteurs en particulier retiendront notre attention: la Santé et l'enseignement supérieur. / Abstract

In future service markets a selection of functionally equal services is omnipresent. The evolving challenge, finding the best-fit service, requires a distinction between the non-functional service characteristics (e.g., response time, price, availability). Service providers commonly capture those quality characteristics in so-called Service Level Agreements (SLAs). However, a service selection based on SLAs is inadequate, because the static SLAs generally do not consider the dynamic service behaviors and quality changes in a service-oriented environment. Furthermore, the profit-oriented service providers tend to embellish their SLAs by flexibly handling their correctness. Within the SOC (Service Oriented Computing) research project of the Karlsruhe University of Applied Sciences and the Linnaeus University of Sweden, a service broker framework for an optimized web service selection is introduced. Instead of relying on the providers’ quality assertions, a distributed knowledge is developed by automatically monitoring and measuring the service quality during each service consumption. The broker aims at optimizing the service selection based on the past real service performances and the defined quality preferences of a unique consumer.This thesis work concerns the design, implementation and evaluation of appropriate machine learning methods with focus on the broker’s best-fit web service selection. Within the time-critical service optimization the performance and scalability of the broker’s machine learning plays an important role. Therefore, high- performance algorithms for predicting the future non-functional service characteristics within a continuous machine learning process were implemented. The introduced so-called foreground-/background-model enables to separate the real-time request for a best-fit service selection from the time-consuming machine learning. The best-fit services for certain consumer call contexts (e.g., call location and time, quality preferences) are continuously pre-determined within the asynchronous background-model. Through this any performance issues within the critical path from the service request up to the best-fit service recommendation are eliminated. For evaluating the implemented best-fit service selection a sophisticated test data scenario with real-world characteristics was created showing services with different volatile performances, cyclic performance behaviors and performance changes in the course of time. Besides the significantly improved performance, the new implementation achieved an overall high selection accuracy. It was possible to determine in 70% of all service optimizations the actual best-fit service and in 94% of all service optimizations the actual two best-fit services.