Purpose This paper aims to focus on supply chain quality (SCQ) in the hospitality industry in China, and to stress the importance of the synergy of quality management (QM) and supply chain management (SCM). The authors have investigated the relationship among QM practices, SCM practices, SCQ and hotel performance, and examined the effect of contextual variables. Design/methodology/approach This study mainly uses a questionnaire survey to collect data relating to the research hypotheses. Structural equation model technique is suited for our research purposes, and the LISREL software is implemented to test the conceptual model. Findings The results show that QM practices and SCM practices are significantly correlated. QM practices/SCM practices are positively related to SCQ, and consequently influence hotel performance. SCQ has the mediating effect between QM/SCM practices and hotel performance. Contextual variables truly play a moderator between QM/SCM practices and SCQ. Research limitations/implications Hotel managers should look beyond their own hotels into supply chain to manage quality, highlight the importance of interdepartmental or external (i.e. customers or suppliers) connectedness, such as building close and long-term relationships with well-chosen suppliers, encouraging customer involvement and establishing an effective interface for accumulating information regarding customers’ needs and feedback. Hotel managers are also able to realize the influence of contextual variables (e.g. the new normal state of the Chinese economy), and further to gain chance of hotel’s survival. Originality/value This study focuses on SCQ and tries to fill a gap in the exiting literature on SCQ management in hospitality industry.

2002) Product design resources optimization using a non-linear fuzzy quality function deployment modelQuality Function Deployment (QFD) is a well-known customer-oriented methodology that is widely used to assist decision-making in product design and development in various types of production including highly customized One-of-a-Kind Production (OKP), batch production as well as continuous/ mass production. Determining how and to what extent (degree) certain characteristics/technical attributes (TA) of products are to be met with a view to gaining a higher level of overall customer satisfaction is a key to successful product design and development. Most of the existing approaches and models for QFD planning seldom consider the resource constraints in product design, nor do they normally take into account the impacts of the correlation among various TA. In other words, most of the existing QFD applications assume that the resources committed fully to attaining the design target for one TA have no impacts on those for other TA. Hence, the costs/resources required are usually worked out individually by linear formulation. In practice, design resource requirements should be expressed in fuzzy terms to accommodate the imprecision and uncertainties innate in the design process, such as ill-de®ned or incomplete understanding of the relationship between a given set of customer requirements (CR) and TA, the complexity of interdependence among TA, etc. A non-linear fuzzy model is proposed here to o er a more practical and e ective means of incorporating the resource factors in QFD planning. The impacts of the correlation among TA are also considered. In the model, the resources for achieving the design target for a certain TA are expressed in a non-linear formulation of its relationship, correlation as well as interdependence with other customer requirements or TA. The concepts of the achieved attainments and planned attainments for TA, and the corresponding primary costs, planned costs and actual costs are introduced. Solutions to the non-linear fuzzy model can be obtained using a parametric optimization method or a hybrid genetic algorithm. A case study is also given to illustrate how the proposed fuzzy model and the optimization routine can be applied to help decision-makers in a company deploy their design resources towards gaining better overall customer satisfaction.

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