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Quality function deployment (QFD) has been widely applied in new product development, but existing research on QFD has some limitations. Primarily, QFD lacks the capability to provide feedback on the satisfaction degree of customer requirements (CRs) according to the actual values of engineering characteristics (ECs). In addition, QFD does not quantitatively consider the interrelationships among ECs. Reverse QFD (R-QFD) was introduced to implement the feedback process. On this basis, this paper quantitatively considers the interrelationships among ECs in the R-QFD model and extends these relationships to encompass combinations of multiple ECs, aiming to improve the inference accuracy of the model.

A nonlinear regression model was established between CRs and ECs, aiming to infer the satisfaction degree of CRs based on the implementation status of ECs. This model considers the interdependencies among ECs and extends the consideration of pairwise EC correlations from every two to every fifteen. Lingo Software is utilized to seek solutions for this program. To facilitate the implementation of the program, a directive to simplify the solution has been proposed.

The experimental results indicate that the interrelationships among ECs significantly affect the inference accuracy of the R-QFD model, thereby verifying the necessity of considering higher-order interrelationships among ECs within the R-QFD framework. Based on the results from data experiments, this paper also proposes research recommendations pertaining to ECs hierarchy for varying quantities of ECs.

The outcomes of this study have further refined the R-QFD model, addressing its limitations of ignoring the interrelationships among ECs. This transformation elevates the R-QFD model from a relatively simple linear model to a nonlinear model formed through modeling, thereby enhancing its accuracy and applicability. In practical terms, this study provides case support for the application of the R-QFD model in manufacturing industry.

The study examines how process/organizational innovation and R&D spending mediate the relationship between financial performance and the resource dependence theory in Fintech, providing insights into effective innovation strategies for achieving sustainable financial performance.

Data from 191 financial firms in Taiwan was collected from annual reports using the Taiwan Economic Journal (TEJ), a financial information provider. Content analysis was used to measure innovation activities and financial performance, with process and organizational innovation defined. R&D expenditures were also collected and used in statistical analysis to explore the relationship between variables.

This study on the financial services industry shows that process innovation and R&D expenditure positively impact firm performance, while organizational innovation may have a negative short-term effect but could have long-term benefits.

Limitations of this study include vulnerability to spurious effects and the use of data from only listed financial service firms. Future research should use more short-term performance data and include unlisted firms in the financial services industry to extend the study’s coverage.

This study extends resource dependence theory to financial services and explores the effects of process and organizational innovation on firm performance. Results show that internal process management boosts performance, while external collaboration with startups enhances Fintech innovation and efficiency, with positive short-term effects. The study highlights the importance of interacting with external organizations to access resources and improve performance in financial services.

This study aims to present a novel topology optimization method for effectively minimizing the frequency response over a given frequency interval considering anisotropic features and fiber angles simultaneously.

The variable thickness sheet (VTS) method is used to obtain a free material distribution under the specified volume constraint. The anisotropic equivalent stiffness matrix based on the material fiber angles is considered in the orthotropic material properties model, which ensures a sufficiently large design space to minimize the frequency response. To lessen the computational burden, the quasi-static Ritz vector (QSRV) method is integrated to approximate the structural response.

Compared to considering only one element, the optimization process simultaneously considers the spatially-varying fiber angles and the material distribution, allowing for a broader design space to minimize the frequency response of additive manufacturing (AM) structures. The orthotropic properties play an important role in determining optimal material distribution of the structure. Moreover, the QSRV method makes the frequency response analysis more efficient.

The anisotropic stiffness and spatially-varying angles of the fiber materials induced by the layer-by-layer printing process of carbon fiber reinforced plastics (CFRP) are simultaneously considered to further minimize the frequency response of AM structures, which improves the performance of AM-CFRP structures.

In this study, suggestions on the protection and development of marine resources, sea area use and management, improvement of laws and regulations, monitoring of marine resources and impact assessment of marine environment are put forward.

Literature research method.

A major factor contributing to the decline in fishery resources is excessive fishing. At present, there are many problems to be solved in the exploitation and utilization of marine mineral resources in China. The pollution problem of marine tourism resources is becoming increasingly serious. Overmining of coastal sea resources has led to planning and management failures.

This paper discusses the current situation of marine resource exploitation and protection in China and analyzes the reasons for excessive resource exploitation from three aspects of marine concept, laws and regulations and marine management.

This study empirically examined four value attributes (e.g. conditional value, functional value, epistemic value and price consciousness) influencing young customers’ attitudes, word-of-mouth (WOM) and continuous usage intentions. Subjective norm was positioned as the moderator, while WOM was identified as the mediator.

This study collected data from 252 Chinese young customers using purposive sampling technique and utilized PLS-SEM to examine the interrelationships among variables.

The findings confirmed that the four value attributes (i.e. conditional value, functional value, epistemic value and price consciousness) significantly influence young consumers' attitudes toward pre-made dishes (PMDs). Additionally, attitudes and WOM positively influence continuous usage intention, with WOM acting as a mediator between attitudes and continuous usage intentions. Furthermore, subjective norm partially moderates the value-attitude-behavior (VAB) model.

PMDs manufacturers should take into account the consumption values and price consciousness of young customers when developing marketing campaigns. Subjective norm and WOM continue to be key factors in enhancing continuous intention.

This study expands the applicability of the VAB model, the theory of consumption value (TCV), and the theory of planned behavior (TPB), enriching the literature on PMDs by examining four value attributes and moderating factors influencing continuous usage intention.

Integrating the Chat Generative Pre-Trained Transformer-type (ChatGPT-type) model with government services has great development prospects. Applying this model improves service efficiency but has certain risks, thus having a dual impact on the public. For a responsible and democratic government, it is necessary to fully understand the factors influencing public acceptance and their causal relationships to truly encourage the public to accept and use government ChatGPT-type services.

This study used the Latent Dirichlet allocation (LDA) model to analyze comment texts and summarize 15 factors that affect public acceptance. Multiple-related matrices were established using the grey decision-making trial and evaluation laboratory (grey-DEMATEL) method to reveal causal relationships among factors. From the two opposite extraction rules of result priority and cause priority, the authors obtained an antagonistic topological model with comprehensive influence values using the total adversarial interpretive structure model (TAISM).

Fifteen factors were categorized in terms of cause and effect, and the antagonistic topological model with comprehensive influence values was also analyzed. The analysis showed that perceived risk, trust and meeting demand were the three most critical factors of public acceptance. Meanwhile, perceived risk and trust directly affected public acceptance and were affected by other factors. Supervision and accountability had the highest driving power and acted as the causal factor to influence other factors.

This study identified the factors affecting public acceptance of integrating the ChatGPT-type model with government services. It analyzed the relationship between the factors to provide a reference for decision-makers. This study introduced TAISM to form the LDA-grey-DEMATEL-TAISM method to provide an analytical paradigm for studying similar influencing factors.

The paper proposes a two-level closed-loop supply chain (CLSC) dynamic competitive model based on different competitive cooperation situations, and explores the impact of competitive cooperation methods on the pricing strategies, recycling and remanufacturing strategies and competitive model selection strategies of supply chain firms.

This paper establishes a CLSC game consisting of a manufacturer and two retailers. Firstly, five CLSC models are established in both horizontal and vertical dimensions, each of which competes with one another. Secondly, the recycling and remanufacturing pricing strategies are analyzed under different competition or cooperation models. Finally, the results are verified through numerical analysis.

The overall profitability of the CLSC is highest when the manufacturer–retailer partnership alliance is in place. The relationship between retailers and manufacturers is also found to be the best way to achieve overall optimization of the CLSC.

The paper investigates the relationship between the competitive partnership and the total profit of the CLSC, taking into account how to optimize the overall benefit, and focusing on how to optimize the individual interests of each participating enterprise. The results can provide basis and guidance for managers' pricing decision and competition cooperation.

The present study aims to test the impact of workplace incivility and violence on doctors' turnover intentions. Besides, the present study also tested the mediating role of employees' burnout.

The population of the present study was doctors working in 20 public sector hospitals. Where 250 doctors working in emergency departments participated, the sample size was calculated through Krejcie and Morgan's table. The data analysis was conducted through SPSS and Smart-PLS.

Results of the present study supported all the relationships except the relationship between workplace violence and turnover intentions. More specifically, relationship between workplace incivility and turnover intentions was confirmed, and mediation effect of doctors' burnout was also confirmed.

This present study is novel in a way that this study framed the study model using conservative resource theory and social cognitive theory covering both employees cognitive and external factors. Further, the nexus “workplace incivility → workplace violence → job burnout → turnover intentions” was tested for the first time, hence making a valuable addition to the body of literature. Further this study is a contribution to healthcare literature in context of incivility, violence, burnout, and turnover. Burnout is first time explored as moderator with workplace incivility which is another contribution.

In the field of digital entrepreneurship, achieving high growth in digital start-ups is crucial. This paper aims to explore how causal conditions at the individual, organizational and environmental levels interact in the growth process of digital start-ups. Furthermore, it uses a configurational approach to conduct a holistic analysis of the cross-level interaction mechanisms that enable digital start-ups to achieve high growth.

Based on a holistic perspective, the data collection included 57 representative cases of digital start-ups in China in the past decade (2014–2023). A fuzzy set qualitative comparative analysis was conducted to explore the cross-level interaction mechanism of the three-dimensional causal conditions of the environment, organization and individual entrepreneurs on high growth among digital start-ups.

This study found three models for digital start-ups to achieve high growth. These models − the resource network orchestration model, the innovation resource development model and the entrepreneurial spirit coherence model, respectively, reflect the multiple paths of high growth achieved by various digital start-ups based on their entrepreneurial environment, organizational capability and the personality of the founder. This reflects that digital start-ups face different conditions and entrepreneurial situations, with differing cross-level interaction mechanisms for achieving high growth.

First, digital start-ups should focus on strengthening their digital resource integration capabilities to lay the foundation for their subsequent high-growth path selection. Second, entrepreneurs need to adopt a holistic perspective to change or strengthen the causal conditions required to achieve high growth. Third, emphasis should be placed on the coherence between the entrepreneur’s need for achievement and the internal entrepreneurial culture.

First, this study contributes to the literature on high growth among digital start-ups by introducing a cross-level interaction mechanism comprising environmental, organizational and entrepreneurial causal conditions. Second, it reveals that individual factors at the environmental, organizational and entrepreneurial levels are not necessary conditions for high entrepreneurial growth and that digital resource integration capabilities play a more universal role in achieving high digital start-up growth. Finally, the study provides a cross-level holistic explanation of how digital start-ups can achieve high growth and reveals various configuration models conducive to high growth, thus offering practical insights for businesses.

This paper aims to explore augmented reality (AR) applications in construction safety academic literature and propose possible improvements for future scholarly works. The paper explicitly focuses on AR integration with Construction 4.0 technologies as an effective solution to safety concerns in the construction industry.

This study applied a systematic review approach. In total, 387 potentially relevant articles from databases were identified. Once filtering criteria were applied, 29 eligible papers where selected. The inclusion criteria were being directly associated with construction safety focused on an AR application and AR interactions associated with the Construction 4.0 technologies.

This study investigated the structure of AR applications in construction safety. To this end, the authors studied the safety purposes of AR applications in construction safety: pre-event (intelligent operation, training, safety inspection and hazard alerting), during-event (pinpointing hazard) and post-event (safety estimation) applications. Then, the integration of AR with Construction 4.0 technologies was elaborated. The systematic review also revealed that the AR integration has contributed to developing several technical aspects of AR technology: display, tracking and human–computer interaction. The study results indicate that AR integration with construction is effective in mitigating safety concerns; however, further research studies are required to support this statement.

This study contributes to exploring applications and integrations of AR into construction safety in order to facilitate the leverage of this technology. This review can help encourage practitioners and researchers to conduct further academic investigations into AR application in construction safety.