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This study aims to model collaborative product development (CPD) among a focal firm (FF) and a fairness-concerned external partner (EP). The model is used to explore the impact of fairness concerns on revenue distributing contract and innovation efforts. The study also examines the role of follow-up sales in product development decisions.

A sequential game-theoretic model is developed to analyze product development decisions between the two parties, where participants exert innovation efforts to promote the product value and a revenue-sharing contract is used to distribute the revenue.

Fairness concern of EP has significant impacts on decisions. FF has incentives to change the contract in that fairness concerns might decrease his profit. Conditions and results change when the contract is endogenously decided. First, FF tends to develop the product independently. Second, FF may share a smaller revenue fraction with EP, as FF relies more on his own efforts during CPD. Third, FF cannot benefit from fairness concerns, as his profit is not higher than that in the benchmark. Finally, the existence of follow-up sales does not change FF’s decision about whether to collaborate with EP.

This study incorporates fairness preference into CPD decisions. Besides, a new concept of fairness called “effort-related fairness” is proposed.

This paper aims to report on a study that used the practice theory lens to understand how Chinese ethnic culture influences restaurant workers' learning through engagement in everyday work practices.

A multiple case study approach was used. Data were collected from semi-structured interviews and site observations. Thematic analysis was conducted to identify how workers learnt the sayings, doings and relatings in their workplaces.

The findings show that the ethnic culture of the participants influences and enriches their learning in practice settings such as small Chinese restaurants.

The understandings presented here need to be verified through more research in different regions and nations. In addition, cross-cultural studies on other ethnic restaurants may contribute to deeper understandings of the influences of ethnic culture on practice-based learning.

The research contributes to understanding the influence of ethnic culture on practice-based learning.

The understandings gained from the findings of this study form a useful basis for curriculum development and instructional design of training programmes for practice-based as well as work-integrated-learning components of vocational curriculum. Furthermore, awareness of the strengths of the ethnic culture is of interest to owner/managers of small Chinese restaurants to afford supportive learning environments for workers.

Considers TQM from a cultural perspective using the influence of Confucian work dynamism and Chinese cultural beliefs on Hong Kong companies. Asks if these cultural beliefs conflict with modern quality management philosophy and presents the findings of research covering Chinese literature, experts in Chinese philosophy and Hong Kong TQM experts. Outlines research methods and concludes that there are relevant principles which can be used when implementing TQM.

Failure of the materials occurs once the stress intensity factor (SIF) overtakes the material fracture toughness. At this level, the crack will grow rapidly resulting in unstable crack growth until a complete fracture happens. The SIF calculation of the materials can be conducted by experimental, theoretical and numerical techniques. Prediction of SIF is crucial to ensure safety life from the material failure. The aim of the simulation study is to evaluate the accuracy of SIF prediction using finite element analysis.

The bootstrap resampling method is employed in S-version finite element model (S-FEM) to generate the random variables in this simulation analysis. The SIF analysis studies are promoted by bootstrap S-version Finite Element Model (BootstrapS-FEM). Virtual crack closure-integral method (VCCM) is an important concept to compute the energy release rate and SIF. The semielliptical crack shape is applied with different crack shape aspect ratio in this simulation analysis. The BootstrapS-FEM produces the prediction of SIFs for tension model.

The mean of BootstrapS-FEM is calculated from 100 samples by the resampling method. The bounds are computed based on the lower and upper bounds of the hundred samples of BootstrapS-FEM. The prediction of SIFs is validated with Newman–Raju solution and deterministic S-FEM within 95 percent confidence bounds. All possible values of SIF estimation by BootstrapS-FEM are plotted in a graph. The mean of the BootstrapS-FEM is referred to as point estimation. The Newman–Raju solution and deterministic S-FEM values are within the 95 percent confidence bounds. Thus, the BootstrapS-FEM is considered valid for the prediction with less than 6 percent of percentage error.

The bootstrap resampling method is employed in S-FEM to generate the random variables in this simulation analysis.

This paper aims to provide a conceptual framework containing SERVQUAL original dimensions and add two additional dimensions: patient satisfaction and loyalty in the hospital SQ model that demonstrates the relationship between hospital service quality, patient satisfaction and loyalty from patients’ perspective.

This research conducted a thorough literature review using specific keywords and electronic databases, adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Through analysis, the key dimensions of service quality in Indian hospitals were identified, with the addition of patient satisfaction and loyalty as variables. Of 1,000 initially downloaded papers, 497 were included.

While many researchers rely on the SERVQUAL model, some introduce new or modified dimensions, often renaming existing ones. This study identifies the RATER factors as the main dimensions patients use to evaluate hospital services. This study finds a positive relationship between service quality, patient satisfaction and loyalty.

An understanding of how health-care service quality dimensions, directly and indirectly, affect patient satisfaction and loyalty is important for hospital marketing managers. This study helps them take action to improve patient satisfaction, which encourages patients to be loyal.

This research provides a comprehensive framework for measuring health-care service quality, combining SERVQUAL dimensions and new variables. This study offers useful insights for academics and health-care professionals, promoting more accurate measurement and enhancement of service quality. The use of PRISMA in this context is also innovative, as it is less common in administrative health-care research.

Identifying the flow regime is a prerequisite for accurately modeling two-phase flow. This paper aims to introduce a comprehensive data-driven workflow for flow regime identification.

A numerical two-phase flow model was validated against experimental data and was used to generate dynamic pressure signals for three different flow regimes. First, four distinct methods were used for feature extraction: discrete wavelet transform (DWT), empirical mode decomposition, power spectral density and the time series analysis method. Kernel Fisher discriminant analysis (KFDA) was used to simultaneously perform dimensionality reduction and machine learning (ML) classification for each set of features. Finally, the Shapley additive explanations (SHAP) method was applied to make the workflow explainable.

The results highlighted that the DWT + KFDA method exhibited the highest testing and training accuracy at 95.2% and 88.8%, respectively. Results also include a virtual flow regime map to facilitate the visualization of features in two dimension. Finally, SHAP analysis showed that minimum and maximum values extracted at the fourth and second signal decomposition levels of DWT are the best flow-distinguishing features.

This workflow can be applied to opaque pipes fitted with pressure sensors to achieve flow assurance and automatic monitoring of two-phase flow occurring in many process industries.

This paper presents a novel flow regime identification method by fusing dynamic pressure measurements with ML techniques. The authors’ novel DWT + KFDA method demonstrates superior performance for flow regime identification with explainability.

The purpose of this study is to explore the literature of healthcare service quality for identifying and analyzing the healthcare service quality models and dimensions and to present future research insights pertaining to the applications of these models and dimensions.

A literature review of healthcare service quality has been performed on 59 relevant studies after applying inclusion and exclusion criteria. Google Scholar and Scopus are the primary sources to find the relevant documents. Search was limited to keywords of “service quality,” “healthcare,” “models” and “dimensions.”

The results revealed that different models and dimensions have been evolved and developed after SERVQUAL in healthcare service quality literature. There is still a need to develop new models, add new contextual dimensions and items in existing models on different aspects of healthcare services. There is also a need to incorporate the perspective of service providers as respondents. Moreover, healthcare service quality models can be devolved or narrowed down at department and individual levels.

This study presents valuable research insights for the researchers and practitioners in ways that healthcare service quality models and dimensions can be developed, modified and tested further in different research contexts and settings. Besides, the literature on healthcare services can be enhanced and enriched.

The current study aims at developing a conceptual framework containing original dimensions of SERVQUAL and adding two modified dimensions: patient safety and medical professionalism in healthcare service quality (HSQ) model.

An extensive review of HSQ literature pertaining to its dimensions and models with respect to content analysis and bibliometric studies of service quality in healthcare and SERVQUAL in healthcare were performed on 47 relevant studies, 4,689 and 529 documents after applying inclusion and exclusion criteria. Google Scholar and Scopus were the primary sources to find the relevant documents.

The content analysis was conducted to group HSQ dimensions into seven themes. Co-occurrence analysis of author keywords was performed in VOSviewer to find the links between service quality, SERVQUAL and proposed dimensions. Organization and analysis of different HSQ models and dimensions emerged from the literature result in a comprehensive conceptual framework comprising modified dimensions of healthcare service quality – medical professionalism and patient safety.

SERVQUAL is a widely accepted, tested and validated model in perceiving HSQ from the lenses of patients. But it does not cover the complex nature of healthcare service, thus requiring modification and the addition of new contextual dimensions. Therefore, a comprehensive conceptual framework is developed to validate and test quantitatively.

The Internet of Things (IoT), as one of the new digital technologies, has created wide applications in various industries, and one of the most influential industries of this technology is the transportation industry. By integrating the IoT with the transportation industry, there will be dramatic changes in the industry, and it will provide many entrepreneurial opportunities for entrepreneurs to develop new businesses. Opportunity identification is at the heart of the entrepreneurial process, and entrepreneurs identify innovative goods or services to enter a new market by identifying, evaluating, and exploiting opportunities. Despite the desire of transportation managers to invest in the IoT and the increase in research in this area, limited research has focused on IoT-based entrepreneurial opportunities in the transportation industry. Therefore, the present study aims to identify IoT-based entrepreneurial opportunities in the transportation industry and examine their importance.

To achieve the research objective, the authors applied a mixed approach. First, adapting the lens of the industry value chain theory, a comprehensive literature review, besides a qualitative approach including semi-structured interviews with experts and thematic analysis, was conducted to identify the entrepreneurial opportunities. The identified opportunities were confirmed in the second stage using a quantitative survey method, including the Student t-test and factor analysis. Finally, the identified opportunities were weighted and ranked using the best worst method (BWM).

Entrepreneurial opportunities are classified into five main categories, including “smart vehicles”, “business partners/smart transportation supply side”, “supporting services”, “infrastructures”, and “smart transport management and control”. The infrastructures group of opportunities ranked the highest amongst the identified groups.

This study adds to the digital entrepreneurship opportunity recognition literature by addressing opportunities in a smart industry propelled by digital technologies, including developing new products or new applications of the available technologies. Additionally, inspired by the industry value chain theory, this article develops a framework including various digital entrepreneurial opportunity networks which are necessary to add value to any industry and, thus, could be applied by entrepreneurs to recognize opportunities for new intermediaries to enter other digital-based industries. Finally, the present study identifies the IoT-based entrepreneurial opportunities in the smart transportation industry and prioritizes them, providing practical insights regarding the creation of entrepreneurial ecosystems in the field of smart transportation for entrepreneurs and policymakers.

Based on the numerical research on the relationship between the flow pattern transition and the condensation heat transfer in circular microchannels, the purpose of this paper is to bring forward a concept of external separation circular microchannel to regulate and control the flow pattern for enhancing the condensation heat transfer.

The numerical research is based on the volume of fluid method and the vapor-liquid phase change model proposed by the present authors.

By numerical research on the condensation process of water in a general circular microchannel, it is discovered that, with the increase of the inlet velocity and the reduction of the temperature difference between the saturation temperature and the channel wall temperature, the bubble detachment frequency is raised and the water vapor condensation length is extended, representing an exponential growth. Therefore, for the condensation process with low temperature difference and high mass flow rate, it is in urgent need to regulate and control the flow pattern.

To prevent the flow pattern in the general circular microchannel converted from annular flow to slug flow and then to bubble flow, this paper brings forward a concept of external separation circular microchannel, which regulates and controls the flow pattern by discharging partial liquid from the annular wall opening. After regulation and control, the flow pattern is converted from original periodic annular flow/slug flow/bubble flow to current stable annular flow. Accordingly, the heat transfer performance is enhanced and the condensation length is lowered remarkably.