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Consistency and consensus are two important research issues in group decision-making (GDM). Considering some drawbacks associated with these two issues in existing GDM methods with intuitionistic multiplicative preference relations (IMPRs), a new GDM method with complete IMPRs (CIMPRs) and incomplete IMPRs (ICIMPRs) is proposed in this paper.

A mathematically programming model is constructed to judge the consistency of CIMPRs. For the unacceptably consistent CIMPRs, a consistency-driven optimization model is constructed to improve the consistency level. Meanwhile, a consistency-driven optimization model is constructed to supplement the missing values and improve the consistency level of the ICIMPRs. As to GDM with CIMPRs, first, a mathematically programming model is built to obtain the experts' weights, after that a consensus-driven optimization model is constructed to improve the consensus level of CIMPRs, and finally, the group priority weights of alternatives are obtained by an intuitionistic fuzzy programming model.

The case analysis of the international exchange doctoral student selection problem shows the effectiveness and applicability of this GDM method with CIMPRs and ICIMPRs.

First, a novel consistency definition of CIMPRs is presented. Then, a consistency-driven optimization model is constructed, which supplements the missing values and improves the consistency level of ICIMPRs simultaneously. Therefore, this model greatly improves the efficiency of consistency improving. Experts' weights determination method considering the subjective and objective information is proposed. The priority weights of alternatives are determined by an intuitionistic fuzzy (IF) programming model considering the risk preference of experts, so the method determining priority weights is more flexible and agile. Based on the above theoretical basis, a new GDM method with CIMPRs and ICIMPRs is proposed in this paper.

This paper aims to investigate whether a complementary effect exists between government R&D subsidies (GRSs) and intellectual property rights (IPR) protection on innovation performance in the pharmaceutical manufacturing industry in China. This paper also attempts to understand whether this complementary effect is significantly different across China’s eastern, central and western regions.

The study sample comprised 28 provinces involved in the pharmaceutical manufacturing industry in China from 2003 to 2014. Ordinary least squares was used to test the complementary effects of GRSs and IPR protection on innovation performance. The seemingly unrelated estimation test was also applied to ascertain whether differences existed between the eastern and western regions.

A complementary effect between GRSs and IPR protection in terms of improving the innovation of pharmaceutical manufacturers was found to exist only in eastern and western regions. There was no significant difference in the complementary effect between GRSs and IPR protection in terms of improving innovation among the three regions. Without considering the interaction effect of GRSs and IPR protection, the GRSs were negatively associated with innovation in the eastern region, but positively related to the innovation in central region.

This study contributes to the literature on government policies and innovation by incorporating the interaction effect of GRSs and IPR protection on innovation in the context of a high-tech industry (pharmaceutical manufacturing) in an emerging economy (China). It also explores the internal differences in the influence of this complementary effect on innovation in an emerging economy, enriching the institution-based view.

In recent years, Malaysia has seen a dramatic change in the landscape of financial transactions due to the fast growth of mobile payment systems. This study aims to examine the technological, organisational and environmental (TOE) factors of merchants’ adoption intention to use mobile payment platforms essential for the continuing development and profitability of these cutting-edge payment options.

The research model was developed from the TOE framework and tested with the data collected from 120 merchants in Malaysia. The partial least squares structural equation modelling technique was used in analysing the collected data.

Technology readiness and competitor pressure were directly related to merchants' mobile payment adoption intention and indirectly through perceived strategic value. Also, perceived ease of use and perceived strategic value were significant predictors of the adoption intention of mobile payment.

This model demonstrates the relevance of TOE in explaining merchants' mobile payment adoption intention, with implications for policy and strategy to support the broader adoption of mobile payment platforms in Malaysia.

Abundant studies of outpatient visits apply traditional recurrent neural network (RNN) approaches; more recent methods, such as the deep long short-term memory (DLSTM) model, have yet to be implemented in efforts to forecast key hospital data. Therefore, the current study aims to reports on an application of the DLSTM model to forecast multiple streams of healthcare data.

As the most advanced machine learning (ML) method, static and dynamic DLSTM models aim to forecast time-series data, such as daily patient visits. With a comparative analysis conducted in a high-level, urban Chinese hospital, this study tests the proposed DLSTM model against several widely used time-series analyses as reference models.

The empirical results show that the static DLSTM approach outperforms seasonal autoregressive integrated moving averages (SARIMA), single and multiple RNN, deep gated recurrent units (DGRU), traditional long short-term memory (LSTM) and dynamic DLSTM, with smaller mean absolute, root mean square, mean absolute percentage and root mean square percentage errors (RMSPE). In particular, static DLSTM outperforms all other models for predicting daily patient visits, the number of daily medical examinations and prescriptions.

With these results, hospitals can achieve more precise predictions of outpatient visits, medical examinations and prescriptions, which can inform hospitals' construction plans and increase the efficiency with which the hospitals manage relevant information.

To address a persistent gap in smart hospital and ML literature, this study offers evidence of the best forecasting models with a comparative analysis. The study extends predictive methods for forecasting patient visits, medical examinations and prescriptions and advances insights into smart hospitals by testing a state-of-the-art, deep learning neural network method.

The purpose of this paper is to examine the underlying mediating mechanism and contextual conditions in the relationship between dynamic capabilities and novelty-centered business model design (NCBMD).

Using data from 146 firms in China and the process conditional modeling, the authors acquire evidence supporting the hypothesized moderated mediation.

The authors find that interfunctional coordination plays a crucial mediator role in the relationship between dynamic capabilities and NCBMD. Environmental dynamism positively moderates the mediating effect of interfunctional coordination on the relationship of dynamic capabilities and NCBMD.

First, the research setting focuses on a specific intermediary mechanism of dynamic capabilities on NCBMD. Second, dynamic capabilities are considered as an integrative construct in the study. Future research could further examine the effect mechanism of dynamic capabilities' sub-dimensions, which might provide more theoretical findings. Third, the impact of public policies, an important source of environmental dynamism, on NCBMD needs a fine-grained analysis. Fourth, the sample data restricts the popularity of the conclusion.

First, firms should be aware of the irreplaceable role of dynamic capabilities in the process of designing a novel business model. Second, firms promoting the design of business models should pay more attention to interfunctional coordination. Third, the significant moderating mediation effect reveals that the importance of interfunctional coordination for the relationship between dynamic capabilities and NCBMD under a highly dynamic environment.

First, the authors reveal how a firm's dynamic capabilities can promote NCBMD. By focusing on the influence of dynamic capabilities on NCBMD, the authors elucidate the source of value creation from the perspective of organizational capability. Second, the analysis of mediating effect delineates the bridging mechanism of dynamic capabilities and NCBMD. These findings emphasize the important role of interfunctional coordination in designing a novel business model. Third, given the context of this research, the results present implications for the role of a dynamic environment. For the methodology of theoretical research, the different findings indicate that scholars could further refine the manipulation of moderators, which contributes to elucidate new conclusions ignored in the past studies. Accordingly, this research extends both theoretical research and methodology.

A successful process of design concept evaluation has positive influence on subsequent processes. This study aims to consider the evaluation information at multiple stages and the interaction among evaluators and improve the credibility of evaluation results.

This paper proposes a multi-stage approach for design concept evaluation based on complex network and bounded confidence. First, a network is constructed according to the evaluation data. Depending on the consensus degree of evaluation opinions, the number of evaluation rounds is determined. Then, bounded confidence rules are applied for the modification of preference information. Last, a planning function is constructed to calculate the weight of each stage and aggregate information at multiple evaluation stages.

The results indicate that the opinions of the evaluators tend to be consistent after multiple stages of interactive adjustment, and the ordering of design concept alternatives tends to be stable with the progress of the evaluation.

Updating preferences according to the bounded confidence rules, only the opinions within the trust threshold are considered. The attribute information of the node itself is inadequately considered.

This method addresses the need for considering the evaluation information at each stage and minimizes the impact of disagreements within the evaluation group on the evaluation results.

Polyethylene terephthalate (PET) as a fiber molding polymer is widely used in aerospace, electrical and electronic, clothing and other fields. The purpose of this study is to improve the thermal insulation performance of polyethylene terephthalate (PET), the SiO₂ aerogel/PET composites slices and fibers were prepared, and the effects of the SiO₂ aerogel on the morphology, structure, crystallization property and thermal conductivity of the SiO₂ aerogel/PET composites slices and their fibers were systematically investigated.

The mass ratio of purified terephthalic acid and ethylene glycol was selected as 1:1.5, which was premixed with Sb₂O₃ and the corresponding mass of SiO₂ aerogel, and SiO₂ aerogel/PET composites were prepared by direct esterification and in-situ polymerization. The SiO₂ aerogel/PET composite fibers were prepared by melt-spinning method.

The results showed that the SiO₂ aerogel was uniformly dispersed in the PET matrix. The thermal insulation coefficient of PET was significantly reduced by the addition of SiO₂ aerogel, and the thermal conductivity of the 1.0 Wt.% SiO₂ aerogel/PET composites was reduced by 75.74 mW/(m · K) compared to the pure PET. The thermal conductivity of the 0.8 Wt.% SiO₂ aerogel/PET composite fiber was reduced by 46.06% compared to the pure PET fiber. The crystallinity and flame-retardant coefficient of the SiO₂ aerogel/PET composite fibers showed an increasing trend with the addition of SiO₂ aerogel.

The SiO₂ aerogel/PET composite slices and their fibers have good thermal insulation properties and exhibit good potential for application in the field of thermal insulation, such as warm clothes. In today’s society where the energy crisis is becoming increasingly serious, improving the thermal insulation performance of PET to reduce energy loss will be of great significance to alleviate the energy crisis.

In this study, SiO₂ aerogel/PET composite slices and their fibers were prepared by an in situ polymerization process, which solved the problem of difficult dispersion of nanoparticles in the matrix and the thermal conductivity of PET significantly reduced.

The purpose of this study is to improve the mechanical properties, thermal insulation properties and flame retardant properties of polyethylene terephthalate (PET), the organic montmorillonite (OMMT)/SiO₂ aerogel/PET composites and fibers were prepared, and the effects of the OMMT/SiO₂ aerogel on the structure, thermal conductivity and flame retardance of the OMMT/SiO₂ aerogel/PET composites and their fibers were systematically investigated.

The OMMT/SiO₂ aerogel/PET composites and fibers were prepared by in-situ polymerization and melt spinning using SiO₂ aerogel as thermal insulation filler and OMMT (DK2) as comodified filler.

The experimental results showed that OMMT improved the crystallization properties of PET. Compared with the crystallinity of SiO₂ aerogel/PET composites (34.8%), SiO₂ aerogel/PET composites and their fibers reached 45.1% and 49.2%, respectively. The breaking strength of the OMMT/SiO₂ aerogel/PET composite fibers were gradually increased with the OMMT content. When the content of OMMT was 0.8 wt.%, the fracture strength of the composite fibers reached 4.40 cN/dtex, which was 54% higher than that of the SiO₂ aerogel/PET fiber. In addition, the thermal insulation properties of the composites and their fibers were improved by addition of fillers, and at the same time reached the flame retardant level. The thermal conductivity of the 0.8 wt.% OMMT/SiO₂ aerogel/PET composites was 101.78 mW/(m·K), which was 49.3% and 58.8% lower than that of the SiO₂ aerogel/PET composites and the pure PET, respectively. The thermal conductivity of the fiber fabrics woven from the 0.8 wt.% OMMT/SiO₂ aerogel/PET composites was 28.18 mW/(m·K), which was 29.0% and 44.6% lower than that of the SiO₂ aerogel/PET composite fiber fabrics and PET fiber fabrics. The flame retardancy of the composites was improved, with an limiting oxygen index value of 29.2% for the 0.8 wt.% OMMT/SiO₂ aerogel/PET composites, which was 4.1% higher compared to the SiO₂ aerogel/PET composites, and achieved the flame retardant level.

The SiO₂ aerogel/PET composites and their fibers have good mechanical properties, flame retardant properties and thermal insulation properties, exhibited good potential for application in the field of thermal insulation, such as warm clothing. Nowadays, as the energy crisis is becoming more and more serious, it is very important to improve the thermal insulation properties of PET to reduce energy losses and mitigate the energy crisis.

In this study, PET based composites and their fibers with excellent mechanical properties, thermal insulation properties and flame retardant property were obtained by using three-dimensional network porous silica aerogel with low density and low thermal conductivity as the thermal insulation functional filler and two-dimensional layered OMMT as the synergetic modified filler.

The innovation process demands an interaction between environment agents, knowledge generators and policies of incentive for innovation and not only development by companies. Universities have gradually become the core of the knowledge production system and, therefore, their role regarding innovation has become more important and diversified. This study is aimed at identifying the mechanisms of university–industry (U–I) collaboration, as well as the operationalization steps of the U–I collaboration process.

This study is aimed at identifying, based on a systematic literature review, the mechanisms of university–industry (U–I) collaboration, as well as the operationalization steps of the U–I collaboration process.

The analysis of the 72 selected articles enabled identifying 15 mechanisms of U–I collaboration, proposing a new classification for such mechanisms and developing a framework presenting the operationalization steps of the interaction process.

In this paper, the authors screened nearly 1,500 papers and analyzed in detail 86 papers addressing U–I collaboration, mechanisms of U–I collaboration and operationalization steps of the U–I collaboration process. This paper provides a new classification for such mechanisms and developing a framework presenting the operationalization steps of the interaction process. This research contributes to both theory and practice by highlighting managerial aspects and stimulating academic research on such timely topic.