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To propose an evaluation model for the quality implementations in higher education through an analysis of quality systems and program evaluation using a systems approach.

Theoretical background, research and practice of the quality systems in higher education and program evaluation are analysed in conjunction with the concepts of systems approach. The analysis leads to a systems approach‐based program‐evaluation model for quality implementation in higher education.

The three concepts, quality systems in higher education, program evaluation and systems approach, are found to be consistent and compatible with one another with regard to the goals and organizational structure of the higher education institutions. The proposed evaluation model provides a new perspective for higher education management for the effective and efficient implementation of the quality systems and program improvement.

The implementation of the model in a real university setting is necessary for the clarification of the processes.

The study provides a constructive analysis of higher‐education‐related concepts, and a new dimension of quality systems and program evaluation is developed in the model. The approach comprises three subsystems; “social system”, “technical systems”, and “managerial system”. The evaluation of quality in higher education requires inquiry of the components of the systems.

This paper proposes an innovative evaluation model integrating the systems approach into quality tools. The model is claimed to be the first in integrating the three approaches.

Recognizing Gigerenzer’s (1991) dictum that scientists’ tools are not neutral (tools-in-use influence theory formulation as well as data interpretation), this chapter reports theory and examines data in ways that transcend the dominant logics for variable-based and case-based analyses. The theory and data analysis tests key propositions in complexity theory: (1) no single antecedent condition is a sufficient or necessary indicator of a high score in an outcome condition; (2) a few of many available complex configurations of antecedent conditions are sufficient indicators of high scores in an outcome condition; (3) contrarian cases occur, that is, low scores in a single antecedent condition associates with both high and low scores for an outcome condition for different cases; (4) causal asymmetry occurs, that is, accurate causal models for high scores for an outcome condition are not the mirror opposites of causal models for low scores for the same outcome condition. The study tests and supports these propositions in the context of customer assessments (n = 436) of service facets and service-outcome evaluations for assisted temporary-transformations of self via beauty salon and spa treatments. The findings contribute to advancing a nuanced theory of how customers’ service evaluations relate to their assessments of overall service quality and intentions to use the service. The findings support the need for service managers to be vigilant in fine-tuning service facets and service enactment to achieve the objective of high customer retention.

This paper aims to develop a quality evaluation model for artificial intelligence (AI)-based products/services that is applicable to startups utilizing AI technology. Although AI-based service has risen dramatically and replaced many service offerings, in reality, startups are rarely to develop and evaluate AI services. The features of AI service are fundamentally different from the properties of existing services and have a great influence on the customer's service selection.

This paper reviews startups' development process, existing quality evaluation models and characteristics of services utilizing AI technology, and develops a quality evaluation model for AI-based services. A detailed analysis of a survey (application of the model) on customer satisfaction for AI speakers is provided.

This paper provides seven key features and 24 evaluation items for evaluating AI-based services.

This paper contributes to the growing need for methodologies that reflect the new era of AI-based products/services in quality evaluation research.

This paper aims to define a hierarchical and multi-criteria framework based on pillars of the Modernization of Higher Education to evaluate European Accounting Doctoral Programmes (EADE-Model).

The authors applied a quali-quantitative methodology based on the analytic hierarchy process and the survey approach. The authors conducted an extensive literature and regulation review to identify the dimensions affecting the quality of Doctoral Programmes, choosing accounting as the relevant and pivotal field. The authors also used the survey to select the most critical quality dimensions and derive their weight to build EADE Model. The validity of the proposed model has been tested through the application to the Italian scenario.

The findings provide a critical extension of accounting ranking studies constructing a multi-criteria, hierarchical and updated evaluation model recognizing the role of doctoral training in the knowledge-based society. The results shed new light on weak areas apt to be improved and propose potential amendments to enhance the quality standard of ADE.

Theoretical and practical implications of this paper are directed to academics, policymakers and PhD programmes administrators.

The research is original in drafting a hierarchical multi-criteria framework for evaluating ADE in the Higher Education System. This model may be extended to other fields.

This study aims to propose a service quality evaluation model for health-care services.

In this study, a service quality evaluation model is proposed based on the service quality measurement (SERVQUAL) scale and machine learning algorithm. Primarily, items that affect the quality of service are determined based on the SERVQUAL scale. Subsequently, a service quality assessment model is generated to manage the resources that are allocated to improve the activities efficiently. Following this phase, a sample of classification model is conducted. Machine learning algorithms are used to establish the classification model.

The proposed evaluation model addresses the following questions: What are the potential impact levels of service quality dimensions on the quality of service practically? What should be prioritization among the service quality dimensions and Which dimensions of service quality should be improved primarily? A real-life case study in a public hospital is carried out to reveal how the proposed model works. The results that have been obtained from the case study show that the proposed model can be conducted easily in practice. It is also found that there is a remarkably high-service gap in the public hospital, in which the case study has been conducted, regarding the general physical conditions and food services.

The primary contribution of this study is threefold. The proposed evaluation model determines the impact levels of service quality dimensions on the service quality in practice. The proposed evaluation model prioritizes service quality dimensions in terms of their significance. The proposed evaluation model finds out the answer to the question of which service quality dimensions should be improved primarily?

The five-factor model (FFM), a popular personality typology that identifies five key personality traits, has been used to predict use intention in various e-commerce applications, but the role of FFM in triggering certain evaluations of the various quality dimensions of e-commerce websites has not been examined, revealing a gap, i.e. the authors do not know how the five personality traits impact evaluations of the quality dimensions of e-commerce websites. The 3Q model—which comprises system quality (SysQ), information quality (IQ), and service quality (SQ), spanning 13 quality dimensions—is helpful for evaluating website quality, but the model neglects user characteristics and their impacts on quality evaluation, posing another gap, i.e. the authors do not know how user characteristics impact the user's evaluation of quality dimensions. Thus, the authors used the FFM to extend the 3Q model to explain how user personality predicts the evaluation of websites in the 13 quality dimensions.

The authors used an online survey to collect responses from 392 online shoppers. Structural equation modeling was used to test the hypotheses.

The authors found that openness in a shopper predicts their favorable evaluation of a website in the quality dimensions of format and flexibility; conscientiousness predicts favorable evaluation in terms of completeness, accuracy, currency, timeliness, and service reliability; neuroticism predicts unfavorable evaluation in terms of reliability, accessibility, and assurance; and extraversion predicts favorable evaluation in terms of responsiveness; while agreeableness did not predict empathy.

In sum, the authors successfully used the FFM to theoretically extend the 3Q model, which clarifies the usefulness and pathways of personality in formulating strategies for e-commerce success.

Evaluation is increasingly being regarded as a powerful tool to enhance the effectiveness of training. Three major approaches to training evaluation: quality ascription, quality assessment and quality control are highlighted. In order to enhance the effectiveness of training, evaluation should be integrated with organisational life. To ensure this, a model, “the quality assurance evaluation model”, is proposed. A description of an action‐researchoriented exploration of the model with 43 training co‐ordinators of manufacturing firms in Nigeria is given. Changes in the model, suggested by the research findings, are discussed, and the modified model presented. The need to test the modified model on reallife training programmes is emphasised.

The purpose of this paper is to establish an integrated model of Analytic Network Process (ANP) and Decision-Making Trial and Evaluation Laboratory (DEMATEL), to assist enterprises to process supplier quality performance rating and comparison and find the core improvement direction to create the value of all supply chain members.

This study used the integrated model to process supplier quality performance rating and comparison, which not only improved the order-winners and qualifiers and continued to increase supplier quality performance, but resolved the complex and difficult cause-effect relation issue to find out core improvement items. The cases of Taiwanese industrial computer manufacturers were used to describe the application and benefits of this methodology.

The results recommended that the improvement item of supplier A shall focus on design and quality conformance. The recommended improvement item and order for supplier B is design, delivery reliability and delivery speed. This study established ANP and DEMATEL evaluation models, and expanded the application field in the supplier performance evaluation.

The ANP model is used to calculate the importance of the evaluation criteria, and the DEMATEL method is introduced to consider the impact of the casual relationship of evaluation items and to adjust the importance of the evaluation item, and to solve the complex and difficult practical causation issue.

The purpose of this study is to analyze the efficiency of the service quality activity itself by using the DEA Model, in contrast to previous quality evaluation methods, as an attempt to evaluate the service quality activities of the distribution industry. Furthermore, by complementing the shortfalls of the weighted value of the DEA Model, it recommends a DEA/PS Model that is appropriate in the evaluation of service quality activities. Based on this model, the study proposes the SQAE Model, an evaluation tool to complement the traditional measuring method. According to the results of the analysis of 18 sample distribution businesses, there was a discrepancy by business in the results of the Traditional Scoring System and the Evaluation Measuring System. Therefore, it is most desirable to not only be active in service quality activities but also increase efficiency at the same time.

Effective measurement and analysis of service quality are an essential first step in its improvement. This paper discusses the development of neural network models for this purpose. A valid neural network model for service quality is initially developed. Customer data from a SERVQUAL survey at an auto‐dealership network in The Netherlands provide the basis for model development. Different definitions of service quality measurement are modelled using the neural network approach. The perception‐minus‐expectation model of service quality was found not to be as accurate as the perception‐only model in predicting service quality. While this is consistent with the literature, this study also shows that the more intuitively appealing but mathematically less convenient expectation‐minus‐perception model out‐performs all the other service quality measurement models. The study also provides an analytical basis for the importance of expectation in the measurement of service quality. However, the study demonstrates the need for further study before neural network models may be effectively used for sensitivity analyses involving specific dimensions of service quality.