Although building enterprises are actively developing towards the direction of an integrated building supply chain (IBSC), they still face many difficulties in digital green innovation (DGI) activities. The purpose of this study is to reveal the interaction mechanism between the digital integration degree, green knowledge collaboration ability, and the DGI performance of IBSC enterprises in DGI activities under the influence of environmental characteristics of the integrated supply chain. In this study, firstly, a hierarchical regression method and a structural equation model are used to empirically study the static mechanism of DGI among enterprises in the IBSC. Secondly, this study adopts a complex system theory to construct a logistic dynamic analysis model to explore a dynamic evolution mechanism. The results of the study are as follows. (i) The digital integration degree and green knowledge synergy ability of the IBSC are conducive to improvements in digital green innovation performance among the enterprises involved in this chain. The digital integration degree of this chain is the dominant factor affecting the performance of digital green innovation among these enterprises. (ii) The digital network capability of this chain has a significant impact on its digital integration degree but has no significant effect on green knowledge synergy ability. The quality of digital relationships in the IBSC affects both the digital integration degree and green knowledge synergy ability. It has a higher impact on the digital integration degree than on the synergy ability of green knowledge. The resilience of the IBSC can effectively promote the improvement of digital integration and green knowledge synergy ability, but has no significant effect on digital green innovation performance. (iii) In the early stage of an IBSC, the effect of the digital integration degree on DGI performance is more obvious. Over the long term, under the effect of different digital relationship qualities of the IBSC, green knowledge collaboration ability plays a pivotal role. Improving this ability is conducive to the continuous improvement of DGI performance.
In the context of carbon peak and carbon neutrality, digital green innovation development is becoming more and more important for enterprises. In order to effectively improve green competitiveness and increase profits, photovoltaic building materials enterprises must choose digital green innovation projects for investment. The purpose of this study is to build a reasonable investment project selection framework system and propose appropriate methods for photovoltaic building materials enterprises to help them correctly choose digital green innovation investment projects. This study firstly combines relevant theories and digital green innovation characteristics of target investment projects to build a framework system for photovoltaic building materials enterprises to select investment projects. Secondly, this study innovatively proposes a dynamic intuitionistic fuzzy multi-attribute group decision-making method considering the interaction between attributes. Finally, this study takes Yingli Group as the research object and conducts an empirical study on it to verify the scientific nature and reliability of the framework system and method selection. The results show that the framework system includes four aspects: external support system, commercialization expectation, project operation ability and project operation resources. Yingli Group should choose project A3 for cooperation. The framework system and method proposed in this study are feasible and can help Yingli Group correctly choose digital green innovation investment projects. At the same time, this study also brings positive enlightenment to other photovoltaic building materials enterprises in the world when choosing digital green innovation investment projects.
Digital green innovation management activities are the core of low-carbon intelligent development of prefabricated construction enterprises (PCEs) for sustainable urban development. PCEs have to seek joint venture partners to avoid the financial risk of digital green innovation projects. The purpose of this study is to develop a conceptual partner selection framework for the digital green innovation management of prefabricated construction towards urban building 5.0. In this study, first, symbiosis theory and six analysis methods were integrated to innovatively build a 3W1H-P framework system for the joint venture capital partner selection of digital green innovation projects. Second, the dual combination weighting method was innovatively proposed to avoid subjective and objective deviation in attribute weight and time weight. Finally, empirical research was carried out to verify the scientific nature, reliability, and practicability of the framework system and selection model. The results of this study show that the framework system and selection model proposed can be used to assist PCEs to select joint investment partners of digital green and innovative projects for sustainable urban development.
BackgroundDuring the COVID-19 pandemic, universities around the world had to find a balance between the need to resume classes and prevent the spread of the virus by ensuring the health of students. The purpose of our study was to effectively assess the overall risk of universities reopening during the COVID-19 epidemic.Design and methodsUsing the pressure–state–response model, we designed a risk evaluation method from a disaster management perspective. First, we performed a literature review to find the main factors affecting the virus spread. Second, we used the pressure–state–response to represent how the considered hazards acts and interacts before grouping them as disaster and vulnerability factors. Third, we assigned to all factors a risk function ranging from 1 to 4. Fourth, we modeled the risk indexes of disaster and of system vulnerability through simple and appropriate weights and combined them in an overall risk for the university resumption. Finally, we showed how the method works by evaluating the reopening of the Hebei Province University in 2022 and highlighted the resulting advice for reducing related risks.ResultsOur model included 20 risk factors, six representing exogenous hazards (disaster factors) that university can only monitor and 14 related to system vulnerability that can also control. Disaster factors included epidemic risk level of students' residence and the school's location, means of transportation back to school, size of the university population, the number of migrants on and off campus and express carrier infection. Vulnerability factors included student behaviors, routine campus activities and all the other actions the university can take to control the virus spread. The university of Baoding city (Hebei Province) showed a disaster risk of 1.880 and a vulnerability of 1.666 which combined provided a low risk of school resumption.ConclusionOur study judged the risks involved in resuming school and put forward specific countermeasures for reducing the risk levels. This not only protects public health security but also has some practical implications for improving the evaluation and rational decision-making abilities of all parties.
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