Purpose -The purpose of this study is to propose an integrated model that examines the impact of three elements of foodservice quality dimensions (physical environment, food, and service) on restaurant image, customer perceived value, customer satisfaction, and behavioral intentions. Design/methodology/approach -Data were collected from customers at an authentic upscale Chinese restaurant located in a Southeastern state in the USA via a self-administered questionnaire. Anderson and Gerbing's two-step approach was used to assess the measurement and structural models. Findings -Structural equation modeling shows that the quality of the physical environment, food, and service were significant determinants of restaurant image. Also, the quality of the physical environment and food were significant predictors of customer perceived value. The restaurant image was also found to be a significant antecedent of customer perceived value. In addition, the results reinforced that customer perceived value is indeed a significant determinant of customer satisfaction, and customer satisfaction is a significant predictor of behavioral intentions.Research limitations/implications -The proposed model and study findings will greatly help researchers and practitioners understand the complex relationships among foodservice quality (physical environment, food, and service), restaurant image, customer perceived value, customer satisfaction, and behavioral intentions in the restaurant industry. Originality/value -This study is the first to develop an integrated model that explicitly accounts for the influence of three restaurant service quality factors on restaurant image and customer perceived value. Using structural equation modeling, this study empirically confirms that the model with the causality from quality, in particular three dimensions of foodservice quality in this study, to restaurant image is superior to the one with causality from image to quality in the context of restaurant.

Purpose -Structural equation modeling (SEM) depicts one of the most salient research methods across a variety of disciplines, including hospitality management. Although for many researchers, SEM is equivalent to carrying out covariance-based SEM, recent research advocates the use of partial least squares structural equation modeling (PLS-SEM) as an attractive alternative. The purpose of this paper is to systematically examine how PLS-SEM has been applied in major hospitality research journals with the aim of providing important guidance and, if necessary, opportunities for realignment in future applications. Because PLS-SEM in hospitality research is still in an early stage of development, critically examining its use holds considerable promise to counteract misapplications which otherwise might reinforce over time.Design/methodology/approach -All PLS-SEM studies published in the six SSCI-indexed hospitality management journals between 2001 and 2015 were reviewed. Tying in with the prior studies in the field, the review covers reasons for using PLS-SEM, data characteristics, model characteristics, the evaluation of the measurement models, the evaluation of the structural model, reporting and use of advanced analyses.Findings -Compared to other fields, the results show that several reporting practices are clearly above standard but still leave room for improvement, particularly regarding the consideration of state-of-the art metrics for measurement and structural model assessment. Furthermore, hospitality researchers seem to be unaware of the recent extensions of the PLS-SEM method, which clearly extend the scope of the analyses and Even though this research does not explicitly refer to the use of the SmartPLS software (www. smartpls.com), Ringle acknowledges a financial interest in SmartPLS.

This research aims to examine the relationships among three components of the physical environment (i.e., décor and artifacts, spatial layout, and ambient conditions), price perception, customer satisfaction, and customer loyalty in the restaurant industry. A total of 279 cases from a survey were used to assess overall fit of the proposed model and test hypotheses using structural equation modeling. The three factors of the physical environment strongly influenced how customers perceived price, and this price perception, in turn, enhanced customer satisfaction level and directly/indirectly influenced customer loyalty. Décor and artifacts were the most significant predictors of price perception among the three components of the physical environment. Furthermore, both price perception and customer satisfaction played significant partial/complete mediating roles in the proposed model. The paper provides potential ways for restaurateurs to increase customer loyalty by improving their understanding of the roles of physical environment, price perception, and customer satisfaction.

This study examined the relationships between three determinants of quality dimensions (predictors: food, service, and physical environment), price (moderator), and satisfaction and behavioral intention (criterion) in quick-casual restaurants. Despite the importance of foodservice quality, academics and managers know relatively little about how the combined effects of quality (food, service, and physical environment) elicit customer satisfaction which, in turn, affects behavioral intention. Hierarchical multiple regression analysis with interactions showed that quality of food, service, and physical environment were all significant determinants of customer satisfaction. In addition, perceived price acted as a moderator in the satisfaction formation process. Finally, the results indicated that customer satisfaction is indeed a significant predictor of behavioral intention. The findings may provide restaurateurs with a guideline for enhancing customer satisfaction and behavioral intention level.

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This research built a conceptual model to show how customers’ perceptions of dining environments influence behavioral intentions through emotions in the upscale restaurant setting. An environmental psychology model was proposed to explore the linkages between customers’ perceptions and emotions (pleasure and arousal) and between customers’ emotional states and behavioral intentions. A structural equation modeling analysis revealed that facility aesthetics, ambience, and employees had significant effects on the level of customer pleasure while ambience and employees significantly influenced the level of arousal. In addition, pleasure and arousal had significant impacts on behavioral intentions, and pleasure appeared to be the more influential emotion of the two. Implications for restaurateurs and academic researchers are also discussed.

PurposeThe paper aims to examine the relationships among hedonic and utilitarian values, customer satisfaction and behavioral intentions in the fast‐casual restaurant industry.Design/methodology/approachThe measures were developed based on a thorough review of the previous literature. Questionnaires were collected in classroom settings at a mid‐western university in the USA. Anderson and Gerbing's two‐step approach was employed to assess the measurement and structural models.FindingsThe findings indicate that hedonic and utilitarian values significantly influence customer satisfaction, and customer satisfaction has a significant influence on behavioral intentions. Utilitarian value shows a greater influence on both customer satisfaction and behavioral intention than does hedonic value. This study also reveals that customer satisfaction acts as a partial mediator in the link between hedonic/utilitarian value and behavioral intentions.Research limitations/implicationsStudy findings will greatly help hospitality researchers and practitioners understand the roles of hedonic and utilitarian values in customer satisfaction and behavioral intentions in the fast‐casual restaurant industry.Originality/valueThe paper is the first to explore the relationships among hedonic and utilitarian values and their effect on customer satisfaction and behavioral intentions in the fast‐casual restaurant industry using Babin et al.'s two‐dimensional measure of consumer value.

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