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The European Union (EU) Medical Device Regulations (MDR) 2017/745 entered into force on May 2021 with changes related to strengthening the clinical evaluation requirements, particularly for high-risk devices. This study aims to investigate the impact of these strengthened requirements on medical device manufacturers by investigating the challenges they encounter while generating an MDR-compliant clinical evaluation report.

A systematic literature review was carried out using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses method of peer-reviewed literature and various government jurisdictional reports and legislation.

The findings from the study understanding what constitutes sufficient clinical evidence poses the biggest challenge to the generation of an MDR-compliant clinical evaluation report. Resulting from the challenges they are facing, manufacturers of certain CE-marked medical devices are planning to remove (and have removed) devices from the EU market upon expiration of their certificate, and in the case of new and innovative devices, some manufacturers are planning to launch in other markets ahead of the EU. These challenges will lead to a potential shortage of certain medical devices in the EU and a delay in access to new devices, thereby negatively impacting patients’ quality of life.

This study provides a unique insight into the challenges currently experienced by medical device manufacturers as they transition to the MDR clinical evaluation requirements and the subsequent impact on the continued availability of medical devices in the EU. A limitation is the lack of literature analysing the regulations and their effects.

This study has both theoretical contributions in that, to the best of the authors’ knowledge, it is the first detailed and systematic review of the new MDR Regulations and has implications for practice as manufacturers and policymakers can leverage it alike to understand the challenges of the new MDR.

Security assurance evaluation (SAE) is a well-established approach for assessing the effectiveness of security measures in systems. However, one aspect that is often overlooked in these evaluations is the assurance context in which they are conducted. This paper aims to explore the role of assurance context in system SAEs and proposes a conceptual model to integrate the assurance context into the evaluation process.

The conceptual model highlights the interrelationships between the various elements of the assurance context, including system boundaries, stakeholders, security concerns, regulatory compliance and assurance assumptions and regulatory compliance.

By introducing the proposed conceptual model, this research provides a framework for incorporating the assurance context into SAEs and offers insights into how it can influence the evaluation outcomes.

By delving into the concept of assurance context, this research seeks to shed light on how it influences the scope, methodologies and outcomes of assurance evaluations, ultimately enabling organizations to strengthen their system security postures and mitigate risks effectively.

The purpose of this study is to establish a grey-entropy-catastrophe progression method (CPM) model to assess the photovoltaic (PV) industry chain resilience of Jiangsu Province in China.

First, we designed the resilience evaluation index system of such a chain from two aspects: the external environment and internal conditions. We then constructed a PV industry chain resilience evaluation model based on the grey-entropy-CPM. Finally, the feasibility and applicability of the proposed model were verified via an empirical case study analysis of Jiangsu Province in China.

As of the end of 2022, the resilience level of its PV industry chain is medium-high resilience, which indicates a high degree of adaptability to the current unpredictable and competitive market, and can respond to the uncertain impact of changes in conditions effectively and in a timely manner.

The construction of this model can provide reference ideas for related enterprises in the PV industry to analyze the resilience level of the industrial chain and solve the problem of industrial chain resilience.

Firstly, an analysis of the entire industrial chain structure of the PV industry, combined with its unique characteristics is needed to design a PV industry chain resilience evaluation index system. Second, grey relational analysis (GRA) and the entropy method were adopted to improve the importance of ranking the indicators in the evaluation of the CPM, and a resilience evaluation model based on grey-entropy-CPM was constructed.

This research examines the effects of physical proximity (close vs distant) of retailers’ private label brands (PLBs) relative to national brands (NBs) and brand display orientation (horizontal [brands occupy the same shelf] vs vertical [brands occupy different shelves]) on consumers’ PLB quality perceptions and PLB evaluations.

Two experiments involving real brands in different product categories tested the hypotheses.

A PLB positioned close (vs distant) to a NB is evaluated more favorably and this effect is mediated by increased PLB quality perceptions, but only in a horizontal brand display. In a vertical brand display, a PLB positioned close (vs distant) to a NB is evaluated less favorably and this effect is mediated by decreased PLB quality perceptions.

The findings suggest that to enhance consumers’ PLB quality perceptions and evaluations, PLBs be positioned next to (rather than on separate shelves) and close to (rather than distant from) NBs in the same product category.

Although the literature suggests that the best shelf position for PLBs is close to NBs, there is a lack of empirical research on the effects of relative shelf positioning on consumers’ quality perceptions and subsequent PLB evaluations. This research finds that both physical proximity and brand display orientation play an important role.

Conspicuously absent from the branding literature is research on the brand-to-brand (Br2Br) interface enabled by social media. The author proposes how networked brands-as-actors integrate their resources as Br2Br interactions that co-create consumer–brand value. As a secondary contribution, the author provides an empirical baseline exploration of the value co-creating impact of Br2Br interactions on consumer–brand evaluations and social media engagement.

Three streams of research aid in conceptualizing the value co-creating process of Br2Br interactions. A follow-up exploratory study uses a controlled Br2Br interaction stimulus in a 2 × 2 × 2 between-subjects design, where brand familiarity and product category complementarity are manipulated, and interaction spillover effects are analyzed using structural equation modeling.

The author finds Br2Br interactions positively affect consumer–brand evaluations and social media engagement likelihood. Spillover effects of these interactions are symmetric for consumer–brand evaluations for both brands. However, brand familiarity moderates the effects of Br2Br interactions on consumer–brand evaluations.

The author lays the groundwork for future research on the complexities of Br2Br interactions – including brand personality conflict, interaction duration and paratextual language – and the boundary conditions for Br2Br and brand-to-consumer relationships.

The purpose of this study is to advance a novel evaluation index system and evaluation approach for ability of older adults in China.

This study constructed a comprehensive older adult ability evaluation index system with 4 primary indicators and 17 secondary indicators. Grey clustering analysis and entropy weight method are combined into a robust evaluation model for the ability of older adults.

The result demonstrates that the proposed grey clustering model is readily available to calculate the disability level of elderly individuals. The constructed index system more comprehensively considers all aspects of the disability of the elderly.

This study provides a quantitative method and a more reasonable index system for the determination of the disability level of the elderly.

This study researched the effects on the perceptual evaluations of participants for the physical environmental factors of cafés using curvilinear, rectilinear, and mixed forms to provide for the spatial states of belonging, to increase the pleasures, and to extend the periods of remaining in the space.

This study used virtual reality (VR) technology to model the cafés designed by using curvilinear, rectilinear and mixed forms as an experimental environment. After experiencing the virtual images of the experimental spaces, participants filled out a “spatial perception” questionnaire. Perceptual evaluations of 415 participants regarding the environmental factors of cafés designed using curvilinear, linear and mixed forms were analyzed in a computer environment.

According to the analysis of the questionnaire data, the cafés using mixed forms were perceived as more positive for the factors of appeal (inviting, restful, warm and sincere), planning (well-planned) and space freedom (roomy, uncluttered, uncrowded, large, wide and free space) compared with the cafés using curvilinear and rectilinear forms. Furthermore, the cafés using curvilinear forms were perceived as more positive for all elements compared with the cafés using rectilinear forms. However, there was a more negative approach in the perceptual evaluations of participants connected to increases in level of education.

The research results clearly demonstrated that the different interior and furniture forms frequently encountered in cafés cause significant effects on users’ perceptual evaluations.

The purpose of this study is to determine the competency characteristics required for the employment of master’s degree students in educational technology.

A combined qualitative and quantitative method was used to consult multiple experts through a modified Delphi method. Competency characteristics were extracted from Chinese recruitment apps, national recruitment websites and university training programs. Ten senior teacher experts who teach educational technology master’s students were consulted through a questionnaire consultation to validate the proposed competency model. The weights of competency characteristics were determined through a combination of the analytic hierarchy process and entropy method.

The results show that when recruiting educational technology master’s students, more emphasis is placed on operational skills. The majority of companies tend to assess practical abilities rather than theoretical knowledge. Relevant knowledge of educational technology, psychology, computer science and education is considered to be the basic knowledge components of educational technology master’s students, while professional skills are the core skills required for their positions. Therefore, universities need to focus on training, educational technology graduate students in these areas of competence. The study also found that professional qualities (such as physical and mental fitness) and personality traits (interpersonal communication and interaction) receive more attention from companies and are essential competencies for educational technology master’s students.

A competence model for educational technology master’s students is proposed, which includes aspects such as knowledge, personal skills/abilities, professional qualities and personality traits. The competence elements included in this model can serve as reference indicators for universities to cultivate the competence of educational technology master’s students, as well as reference points for recruiting units to help them select talents. This represents a new dimension in research related to the employment of educational technology master’s students. The study enriches the research objects and competence dictionary in the field of competence research.

This research extends self-congruity theory and assesses the predictive validity of the triad personality congruence among brand, brand-related sustainability initiatives (BSI) and self-concept (BSSC: brand-sustainability-self-congruence) on consumers’ brand evaluation.

Three studies assessed BSSC using the brand personality scale (BPS) and the direct congruence measure (DCM). Through moderated mediation analyses, BSSC effects were examined on consumers’ behavioral intention, behavior and subjective well-being (SWB). The mediating role of brand trust and the moderating role of brand/BSI types and consumer characteristics were also assessed.

BSSC increased consumers’ brand trust, behavioral intention, behavior and SWB. Data based on BPS revealed impactful attributes that increase/decrease BSSC levels across brand-BSI combinations and the moderating role of sustainability involvement and income to enhance BSSC effects. BSSC was particularly effective, according to DCM.

For BSI planning, strategic consideration of BSSC based on both BPS and DCM is recommended. Thus, managers may predict the psychological impact of BSI and align its attributes to increase consumers’ brand evaluation.

In the sustainable marketing context, this research discusses BSSC – triad personality congruence – based on BPS and DCM and its predictive effects on consumers’ short-term brand evaluation, their actual behavior and SWB, a long-term life evaluation. The results imply a possible variation in consumers’ information processing according to the congruence measurement approach. Thus, it is relevant to the research on self-congruity, sustainability, marketing, consumer psychology/behavior and well-being.

Since the introduction of the outstanding web AI chat system, ChatGPT, it has caused a significant impact in both academia and the business world. Many studies have started to explore its potential applications in various fields. However, there is a lack of research from the perspective of user experience. To fill this theoretical gap and provide a theoretical basis for the operation and design of related services, this study plans to develop a set of evaluation scales for AI chat system user experience and explore the relationship between various factors and user satisfaction.

This study obtained 41 evaluation indicators through literature review and user research. Subsequently, these indicators were used as questionnaire items, combined with satisfaction metrics. A total of 515 questionnaires were distributed, and factor analysis and linear regression were employed to determine the specific elements influencing user experience and the user satisfaction model.

This study found that the factors influencing user experience are usefulness, accuracy, logical inference, interactivity, growth, anthropomorphism, convenience, credibility, ease of use, creativity, and security. Among these factors, only accuracy, anthropomorphism, creativity, and security indirectly influence satisfaction through usefulness, while the rest of the factors have a direct positive impact on user satisfaction.

This study provides constructive suggestions for the design and operation of related services and serves as a reference for future theoretical research in this area.