Organizational design, quality management and competitive advantage in hotels

Purpose – The aim of this study is to examine the relationship between practices of quality management (QM) and the characteristics of organizational design, and QM and competitive advantage. Design/methodology/approach – The study uses a partial least squares approach to test these relationships in 350 hotels in Spain. Findings – The findings show that QM influences specialization, formalization and interdepartmental interactions, and that QM practices influence both cost and differentiation competitive advantage. The results also indicate the importance of QM strategic and operational systems as practices that have a key impact on the characteristics of organizational design. Similarly, the QM operational system is key in the relationship between QM and cost competitive advantage. Finally, the QM operational, information and strategic systems positively influence differentiation competitive advantage. Practical implications – When hotels adopt QM practices, there will be significant changes in a number of organizational variables, including specialization, formalization and interdepartmental interactions. This paper provides empirical evidence that QM practices improve both cost and differentiation competitive advantage in the hotel industry. Originality/value – There has been little research on the effects of QM on organizational design in the hotel industry. The contribution of this paper is that analyze the effects of QM on organizational design and competitive advantage, extending knowledge about these issues in a specific sector.

Quality Management, Environmental Management and Organizational Design in the Hotel Industry: A Qualitative Study

The purpose of this paper is twofold. First, the paper analyzes the relationship between quality management and environmental management and their effects on hotel performance. Second, the article examines the relationship between these two management systems and organizational design. The paper uses an exploratory, qualitative approach based on interviews with managers and experts in the hotel industry. Based on a content analysis of interviews, the results lead to several propositions. Specifically, quality and environmental management influence hotel performance through mediating variables. Moreover, the implementation of quality management facilitates the implementation of environmental management. Furthermore, the implementation of these two management systems is associated with an increase of formalization and decentralization. The paper contributes to the analysis of quality management, environmental management, organizational design and performance in a joint manner, which has not been attempted before in the hotel industry. In addition, it helps extend the findings about these links in manufacturing and service organizations to the hotel industry.

Cloud agile manufacturing

This paper proposes a new manufacturing paradigm, we call Cloud Agile Manufacturing, and whose principal objective is to offer industrial production systems as a service. Thus users can access any functionality available in the cloud of manufacturing (process design, production, management, business integration, factories virtualization, etc.) without knowledge — or at least without having to be experts — in managing the required resources. The proposal takes advantage of many of the benefits that can offer technologies and models like: Business Process Management (BPM), Cloud Computing, Service Oriented Architectures (SOA) and Ontologies. To develop the proposal has been taken as a starting point the Semantic Industrial Machinery as a Service (SIMaaS) proposed in previous work. This proposal facilitates the effective integration of industrial machinery in a computing environment, offering it as a network service. The work also includes an analysis of the benefits and disadvantages of the proposal.

Rigorous Design of Complex Distillation Columns Using Process Simulators and the Particle Swarm Optimization Algorithm

We present a derivative-free optimization algorithm coupled with a chemical process simulator for the optimal design of individual and complex distillation processes using a rigorous tray-by-tray model. The proposed approach serves as an alternative tool to the various models based on nonlinear programming (NLP) or mixed-integer nonlinear programming (MINLP) . This is accomplished by combining the advantages of using a commercial process simulator (Aspen Hysys), including especially suited numerical methods developed for the convergence of distillation columns, with the benefits of the particle swarm optimization (PSO) metaheuristic algorithm, which does not require gradient information and has the ability to escape from local optima. Our method inherits the superstructure developed in Yeomans, H.; Grossmann, I. E.Optimal design of complex distillation columns using rigorous tray-by-tray disjunctive programming models. Ind. Eng. Chem. Res.2000, 39 (11), 4326–4335, in which the nonexisting trays are considered as simple bypasses of liquid and vapor flows. The implemented tool provides the optimal configuration of distillation column systems, which includes continuous and discrete variables, through the minimization of the total annual cost (TAC). The robustness and flexibility of the method is proven through the successful design and synthesis of three distillation systems of increasing complexity.