In the process of intelligent system operation fault diagnosis and decision making, the multi-source, heterogeneous, complex, and fuzzy characteristics of information make the conflict, uncertainty, and validity problems appear in the process of information fusion, which has not been solved. In this study, we analyze the credibility and variation of conflict among evidence from the perspective of conflict credibility weight and propose an improved model of multi-source information fusion based on Dempster-Shafer theory (DST). From the perspectives of the weighting strategy and Euclidean distance strategy, we process the basic probability assignment (BPA) of evidence and assign the credible weight of conflict between evidence to achieve the extraction of credible conflicts and the adoption of credible conflicts in the process of evidence fusion. The improved algorithm weakens the problem of uncertainty and ambiguity caused by conflicts in the information fusion process, and reduces the impact of information complexity on analysis results. And it carries a practical application out with the fault diagnosis of wind turbine system to analyze the operation status of wind turbines in a wind farm to verify the effectiveness of the proposed algorithm. The result shows that under the conditions of improved distance metric evidence discrepancy and credible conflict quantification, the algorithm better shows the conflict and correlation among the evidence. It improves the accuracy of system operation reliability analysis, improves the utilization rate of wind energy resources, and has practical implication value.
PurposeThe social media expands the scope of museum marketing. Through the social media marketing, visitors get a rich and colorful visual experience, and the museum can quickly and effectively convey various information to visitors. At present, the research on social media in the museum industry mainly focuses on the level of technology use, while the research on the marketing application of social media is relatively scarce, especially from the empirical perspective. This study constructs a conceptual model to identify the impact of SMMAs on visitor experience in the context of the museum industry through the empirical analysis.Design/methodology/approachA survey is conducted with a total of 538 visitors who follow the fan page of the Palace Museum Weibo. The collected data are analyzed via structural equation modeling.FindingsThe results show that SMMAs have significant effects on social presence and social support, which in turn significantly affect flow state. Moreover, the results demonstrate that social presence and social support partially mediates the relationships between SMMAs and flow state.Originality/valueThe contribution of this study is twofold. First, from a theoretical perspective, it offers new insights into the conceptualization of social media marketing. Second, from a pragmatic perspective, the results are helpful to guide museums how to carry out social media marketing activities.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-12-2020-0564
Green product certification (GPC) is an important means of eliminating the asymmetry of information between consumers and manufacturers in the context of sustainable development. This study examined the critical risk factors in GPC and provided relevant suggestions for managers to reduce risk and ensure the correctness of the process. First, 18 risk factors were summarized along four dimensions: the certification institution, the entrusting enterprise, the certification business, and the implementation of the certification. Second, the Delphi method was used to determine the formal research framework, and the decision-making trial and evaluation laboratory (DEMATEL) method was applied to analyze the causal relationships among the risk factors to identify the ones driving risk and those representing the outcomes of GPC. This was used to construct a causality diagram of the risks related to green certification. Finally, the analytic network process (ANP) method was used to calculate the weight of each risk factor, and the weighted prominence of each is calculated to identify the critical factors. The results showed that the working life and experience of the certification institution were the critical driving risk factors in GPC. Corresponding countermeasures were also proposed to mitigate these risk factors.
The low-carbon economy and sustainable development have become a widespread consensus. Chain supermarkets should pay attention to path optimization in the process of distribution to reduce carbon emissions. This study takes chain supermarkets as the research object, focusing on the optimization of the vehicle routing problem (VRP) in supermarket store distribution. Firstly, based on the concept of cost-effectiveness, we constructed a green and low-carbon distribution route optimization model with the lowest cost. With cost minimization as the objective function, the total distribution cost in the vehicle delivery process includes fixed cost, transportation cost, and carbon emission cost. The carbon emission cost is calculated using the carbon tax mechanism. Secondly, through integrating the Floyd algorithm, the nearest neighbor algorithm, and the insertion algorithm, a fusion heuristic algorithm was proposed for model solving, and an empirical study was conducted using the W chain supermarket in Wuhan as an example. The experimental results show that optimizing distribution routes considering carbon emission cost can effectively reduce carbon emissions. At the same time, it can also reduce the total costs of enterprises and society, thereby achieving greater social benefits at lower costs. The research results provide effective suggestions for chain supermarkets to control carbon emissions during the distribution process.
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