REFERQUAL: A pilot study of a new service quality assessment instrument in the GP Exercise Referral scheme setting

Background The development of an instrument accurately assessing service quality in the GP Exercise Referral Scheme (ERS) industry could potentially inform scheme organisers of the factors that affect adherence rates leading to the implementation of strategic interventions aimed at reducing client drop-out. Methods A modified version of the SERVQUAL instrument was designed for use in the ERS setting and subsequently piloted amongst 27 ERS clients. Results Test re-test correlations were calculated via Pearson's 'r' or Spearman's 'rho', depending on whether the variables were Normally Distributed, to show a significant (mean r = 0.957, SD = 0.02, p < 0.05; mean rho = 0.934, SD = 0.03, p < 0.05) relationship between all items within the questionnaire. In addition, satisfactory internal consistency was demonstrated via Cronbach's 'α'. Furthermore, clients responded favourably towards the usability, wording and applicability of the instrument's items. Conclusion REFERQUAL is considered to represent promise as a suitable tool for future evaluation of service quality within the ERS community. Future research should further assess the validity and reliability of this instrument through the use of a confirmatory factor analysis to scrutinise the proposed dimensional structure

A Model of Dynamic Scheduling of Restaurant Operations Considering the Order and Timing of Serving Dishes

Part 5: Smart Production for Mass CustomizationInternational audienceJapanese and French restaurants provide dishes in an order specified by tradition; for example, from appetizers to desserts. On the other hand, customers in a Japanese-style bar or casual restaurant often order several dishes at one time. They may have implicit preferences as to the order and timing of serving the dishes according to the characteristics of the foods and their situations. For example, light meals that can be served quickly tend to be served first to cater to customer desires. This paper proposes a dynamic scheduling approach for restaurant service operations considering the order and timing of serving dishes. Customers specify their requests for the order of serving dishes to floor staff, and then a model configures cooking and serving schedules dynamically according to the customers’ requests. In this paper, three models are proposed. In the first model, cooked dishes are stocked in a storage space until the customers’ requirements for the order have been satisfied. The second model coordinates cooking schedules by considering the order sequence, cooking time, and lot assignment to adapt to customer requirements. The third model combines the first and second models

Service System Design Considering Employee Satisfaction Through Introducing Service Robots

Part 11: Gastronomic Service System DesignInternational audienceIn this paper, we perform a basic analysis on employee satisfaction and production planning by introducing a service robot which delivers dishes in restaurant service. As an example of a service robot introduced in a Japanese restaurant, we focus on the pantry staff, kitchen staff, and customer service staff, as well as production planning that individual employees implicitly plan and update in their heads. The service robots are used to deliver the dishes prepared at the kitchen to the customer service floor, where the worker specifies the destination and transports the dishes while patroling the restaurant. By analyzing the productivity and employee satisfaction before and after the introduction of the service robots into the categories of serving, cooking area, and customer service, how employees can identify and coordinate work between humans and machines and change process design. From December 2019 to January 2020, an analysis was conducted based on the results of employee questionnaires and interviews conducted at a restaurant

A threshold model for respondent heterogeneity

Threshold model, Mixture distribution, Service wait times, Drivers of service quality,