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Digital technologies, such as big data, the Internet, and artificial intelligence, are rapidly advancing. Photovoltaic building materials enterprises (PBMEs) have been leveraging digital transformation to enhance their technological innovation capabilities and gain a competitive edge. In the global context of transitioning towards a low-carbon economy, the deep integration of digital technology offers a new solution for the green transformation of PBMEs. The synergy between green traction digitalization and digitalization enables green practices, making collaborative integration crucial for the far-reaching development of PBMEs. Within the framework of China's "double carbon" policy, domestic PBMEs are experiencing exponential growth, where digital green innovation (DGI) has become their primary objective. In this DGI context, selecting the right partners is the first step that significantly impacts the efficiency and effectiveness of DGI implementation. Therefore, the purpose of this study is to assist PBMEs in selecting high-quality partners, promoting the DGI process, enhancing technological innovation capabilities, and gaining a competitive advantage. To achieve this, the paper proposes constructing a theoretical framework for evaluating the DGI cooperation ability of PBMEs using the theory of ecological reciprocity. Based on this framework, an evaluation index system is established to assess the DGI cooperation ability of potential partners The interval intuitionistic fuzzy evaluation method, combined with a double combination weighting approach, is employed to evaluate the DGI ability of selected partners. Furthermore, by applying field theory, a dynamic selection model for strategic alliance partners is developed to aid PBMEs in selecting high-quality partners for DGI and facilitating the DGI process. The research findings indicate that: i) The evaluation standard framework for DGI cooperation ability of PBMEs encompasses "symbiosis," "mutualism," and "regeneration," along with the crucial environmental element of mutual trust. ii) The evaluation method based on double combination weighting effectively assesses the comprehensive DGI capabilities of selected PBME partners. The application of field theory enables scientific and effective dynamic partner selection for PBMEs through resource complementarity. iii) The proposed framework and partner selection model can be employed in real partner selection scenarios for PBMEs, allowing them to choose high-quality partners, enhance their DGI capabilities, and attain practical selection outcomes. This paper presents novel partner selection model that integrates decision rules and resource complementarity, enabling PBMEs to efficiently select DGI partners from a pool of potential candidates and improve their innovation efficiency. The utilization of the double combination weighting method and field theory in the partner selection paradigm of D extends the theoretical foundation, while the establishment of the DGI capability evaluation index system for PBME partners contributes to empirical applications. [ABSTRACT FROM AUTHOR]

As China's economic and social development enters a new stage, the role of innovation and entrepreneurship is becoming increasingly prominent, and its importance is also being emphasized. As the main force for future employment and national economic construction, college students naturally become the new force for innovation and entrepreneurship. Therefore, it is imperative for universities to carry out in-depth innovation and entrepreneurship education (IEE) for college students. Then, with the continuous development of social development needs and the professional growth needs of college students, the "innovation and entrepreneurship" education for college students should also be adjusted in a timely manner in terms of educational concepts, models, and methods. The IEE environment evaluation in universities under the background of " Double Innovation" is looked as multiple attribute decision-making (MADM). In this paper, the information entropy model is employed to calculate the objective weight of the evaluation attribute. Then, interval-valued intuitionistic fuzzy Combined Compromise Solution (IVIF-CoCoSo) is built based on the Hamming distance and Euclid distance to cope with MADM under interval-valued intuitionistic fuzzy sets (IVIFSs). The new MADM method is proposed for IEE environment evaluation in universities under the background of " Double Innovation". Finally, the IVIF-CoCoSo approach is compared with existing methods to verify the effectiveness of IVIF-CoCoSo algorithm. The main contributions of this constructed paper are: (1) the IVIF-CoCoSo method is built based on the Hamming distance and Euclid distance. (2) the information entropy model is employed to calculate the objective weight of the evaluation attribute. (3) The new MADM method is proposed for IEE environment evaluation in universities under the background of " Double Innovation" based on IVIF-CoCoSo. (4) The IVIF-CoCoSo model is compared with existing methods to verify the effectiveness of the IVIF-CoCoSo algorithm. [ABSTRACT FROM AUTHOR]

This paper aims to analyze the coupling coordination degree of technology, economy, social responsibility, and ethic of technological innovation in high-tech enterprises, and provide basis for the optimization of technological innovation system structure in high-tech enterprises. Using data of high-tech enterprises in China Statistical Yearbook and China Statistical Yearbook of Science and Technology in 2018, the authors applied Cloud model to index transformation, consistent fuzzy preference relations to determine index weights, coupling degree model to measure the coupling degree of responsible innovation system of high-tech enterprises in China. Research results show that the responsible innovation system of China's high-tech enterprises in 2018 is in a low degree of coordination and coupling stage, and the high-tech enterprises in China invest relatively little in technical level, social development, and ethical innovation. This research contributes to the literature on responsible innovation, ethical responsibility in the high-tech enterprises, which is conducive to improving the quality of innovation activities. However, this research collected data from a single country at a single point in time. This paper studies from the perspective of responsible innovation and measures the coupling degree between innovation and ethical responsibility of high-tech enterprises. The establishment of coupling analysis model can not only effectively calculate the coupling degree of technological innovation system, but also deeply analyze the shortcomings of each subsystem of technological innovation system, and provide a basis for the formulation of promotion strategy. [ABSTRACT FROM AUTHOR]

With the rapid development of "Internet plus" in our country, the scope of its influence is also constantly expanding. Especially in recent years, China puts forward "mass entrepreneurship and innovation", which makes the "cloud analysis" and "Internet plus" and "innovation" to start cross-border integration. Starting with the background, development stage, environment and other aspects of Internet-plus entrepreneurship and innovation under the cloud analysis, this paper analyzes the influence of various factors in the process of Internet plus entrepreneurship and innovation and the influence degree of various factors on entrepreneurship and innovation in depth, constructs the entrepreneurship and innovation evaluation index system based on the "Internet plus", and finally, combined with an example to verify the index system and fusion analysis method. The verification results show that the "Internet plus" entrepreneurship and innovation based on the perspective of cloud analysis in this paper can not only directly demonstrate the promoting factors of "entrepreneurship and innovation "under Internet plus", but also be scientific and effective when evaluating the "Internet plus" entrepreneurship and innovation activities from the perspective of cloud analysis. [ABSTRACT FROM AUTHOR]

At present, the development of China's economy is inseparable from the promotion of innovation and entrepreneurship. However, there are huge differences in the level of entrepreneurship in different regions, so it is urgent to analyze the influencing factors of entrepreneurship. This paper uses panel data of 31 provinces in 2008–2017 to test the impact of urban unemployment rate, regional financial development level, market scale, agglomeration effect, entrepreneurial cost, scientific and technological innovation level, government support and other factors on entrepreneurial level. To solve the issue of factors influencing the enterprises, we utilised an effective way of fuzzy logic along with decision estimation strategy. The empirical results show that regional financial development level, agglomeration effect, technological innovation ability, government support and so on have a positive role in promoting the level of entrepreneurship, while urban unemployment rate has no significant effect on the level of entrepreneurship. Based on the empirical conclusion, the paper puts forward some policy suggestions. [ABSTRACT FROM AUTHOR]

This paper takes the listed pharmaceutical manufacturing firms in China's A-share market from 2011 to 2017 as the research sample, from the perspective of top managers' pay gap, employs principal component analysis and general least square method to empirically investigate the effect of risk preference of top management team(TMT) on the re-innovation behavior after the failure of innovation. The study found that the risk preference of TMT is positively correlated with the re-innovation input and brand-new innovation after the failure of innovation, but not with the supplementary innovation. Besides, the pay gap not only has a positive moderating effect on the positive correlation between the risk preference of TMT and the re-innovation input, but also on the positive correlation between the risk preference of TMT and the brand-new innovation after the failure of innovation. The findings of this study contribute to: (1) through empirical research on the impact of TMT risk preference on re-innovation behavior after innovation failure, expand the relevant research content and research methods of TMT and innovation failure to make the research results more convincing; (2) by setting a reasonable executive compensation gap, TMT can avoid blindly choosing brand-new innovation behavior after innovation failure with the increase of risk preference innovation, ignoring the potential value of innovation failure projects without supplementary innovation, improving the re-innovation behavior of TMT after innovation failure and improving the re innovation success rate after innovation failure. [ABSTRACT FROM AUTHOR]

With the advent of green economy, it is of great significance to objectively calculate the green innovation efficiency of provincial industrial enterprises in China for achieving sustainable economic development. In this paper, the author analyzes the regional technological innovation and green economic efficiency based on DEA model and fuzzy evaluation. Based on the latest development of traditional efficiency and productivity analysis theory, this study calculates the green innovation efficiency of 30 provincial industrial enterprises by using SBM model, while considering the relaxation of economic input-output problem. The results show that the SBM model improves the accuracy and authenticity of the economic efficiency evaluation of green innovation. The efficiency of green economy in most provinces is on the rise. At the same time, the intensity of R&D and industrial structure play a positive role in improving the efficiency of green economy. Through cluster analysis, the differences and causes of green economic efficiency of regional industrial enterprises are analyzed. In addition, the provinces should also consider the factors affecting the green economic efficiency of industrial enterprises, implement the innovation-driven development strategy in an all-round way, and promote the development of green economy. [ABSTRACT FROM AUTHOR]

Since the 1990s, High-tech industries have become the most dynamic growth point of the world economy and the leading industry in promoting economic development. In the fierce competition of globalization, it is necessary to master high-tech industries for the sake of grasping the leadership of economic development. As a developing country, China should develop high-tech industries more positively, so as to promote the adjustment of industrial structures and the transformation of economic development patterns, so that the country's economy development will be healthy and orderly. At present, the development of China's high-tech industry has made some achievements. By the end of 2012, the number of firms of China's high-tech industry has reached 24636, which is 1.52 times in compared with 9758 in 2000; the number of employees has risen from 2000 in 3.9 million to 12.69 million; the main business achieved at 10.2284 trillion yuan with 681.6 billion yuan total profit obtained. Compared with developed countries, however, the intensity of investment and the level of output in China's high-tech industries are both low. In this paper, we investigate the multiple attribute decision making problems with picture fuzzy information. Then, we utilize Choquet integral to propose the picture fuzzy correlated averaging (PFCA) operators. The prominent characteristic of this proposed operator are studied. Then, we have utilized the picture fuzzy correlated averaging (PFCA) operator to deal with the picture fuzzy multiple attribute decision making problems. Finally, a practical example for technical innovation efficiency evaluation of high-tech industry is given to verify the developed approach. [ABSTRACT FROM AUTHOR]

Aiming to improve the algorithm of the classic fuzzy C-means model (FCM), a double fuzzy C-means model (DFCM) was presented in this paper. A new fuzzy cluster validity index (RWW) and the DFCM algorithm were proposed, simultaneously. Then, the double fuzzy C-means model was applied for the clustering analysis of the regional technology innovation level in China. The validity of the double fuzzy C-means model was tested using the wine data set of UCI. The comparison results of different cluster validity indexes validated the fuzzy cluster validity index (RWW) proposed in this paper. The application example and wine data set clustering results indicated that the DFCM model enhanced the intra-class compactness and inter-class separation, making the classification more accurate. [ABSTRACT FROM AUTHOR]