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This study aims to determine the key indicators affecting the resilience of the construction supply chain to flooding and calculate the resilience of the urban construction supply chain in three cases city.

This study combines expert opinions and literature review to determine key indicators and establish a fuzzy EWM-GRA-TOPSIS evaluation model. The index weight was calculated using the entropy weight method, and GRA-TOPSIS was used for comprehensive evaluation.

The results of the study show that the three cities are ranked from the high to low in order of Hangzhou, Hefei and Zhengzhou.

The innovative method adopted in this study comprising EWM-GRA-TOPSIS reduced the influence of subjectivity, fully extracted and utilized data, in a way that respects objective reality. Further, this approach enabled the absolute and relative level of urban construction supply chain resilience to be identified, allowing improvements in the comprehensiveness of decision-making. The method is relatively simple, reasonable, understandable, and computationally efficient. Within the approach, the entropy weight method was used to assign different index weights, and the GRA-TOPSIS was used to rank the resilience of the construction supply chain in three urban cities. The development of resilience provides a robust decision-making basis and theoretical reference, further enriching research methods, and having strong practical value. The study serves to improve risk awareness and resilience, which in turn helps to reduce losses. It also provides enhanced awareness regarding the future enhancement of supply chain resilience for urban construction.

Effectuation, which articulates the process of entrepreneurial action based on nonpredictive control logic, is receiving extensive scholarly attention. What drives the effectual entrepreneurship is featured with high complexity. However, existing studies ignored the complex driving forces underlying entrepreneurial decision-making. Building on a configurational perspective, the purpose of this study was to examine the combinative effects of environmental uncertainty and entrepreneurs’ means on effectual entrepreneurship.

Drawing on 54 entrepreneurs who are launching new ventures in China, this study adopts a fuzzy-set Qualitative Comparative Analysis (fsQCA) to investigate two sets of antecedent conditions and how they form different combinations for a highly effectual entrepreneurship.

Our findings disclose four highly effectual entrepreneurship paths involving novice–specialist effectual entrepreneurship in a highly uncertain environment, socialite–specialist effectual entrepreneurship in a highly uncertain environment, pure-specialist effectual entrepreneurship and resourceful effectual entrepreneurship, and one path of barefoot noneffectual entrepreneurship in a highly uncertain environment, which reveals the complex nature of environmental uncertainty and entrepreneurs’ means in driving entrepreneurs to adopt effectuation.

Our study makes the following contributions. First, by taking a configurational perspective, we are able to obtain an elaborate view of the combined effects of environmental uncertainty and entrepreneurs’ means on effectual entrepreneurship. Second, we expand prior thinking on the relationship between environmental uncertainty and effectuation. Third, our study offers a more delicate understanding of entrepreneurs’ means in driving effectuation by splitting means into three separate factors.

The purpose of this paper is to solve new pricing issues faced by low-carbon companies in the Yellow River Basin, which is caused by the change of key pricing factors in the mixed appliance background of Big Data and blockchain, such as product quality and carbon-emission reduction CER level (hereafter, CER level).

We choose a low-carbon supply chain with a low-carbon manufacturer and a retailer as our research object. Then, we propose that using the ineffective effect of the CER level and the quality and safety level to reflect the relationships among the CER level, the quality and safety level and the market demand is more suitable in the new environment. Based on these, we revise the demand equation. Afterwards, by using Stackelberg game, four cost-sharing situations and their pricing rules are analyzed.

Results indicated that in the four cost-sharing situations, the change trends and the magnitudes of the best retail prices were not affected by the changes of the inputs of the demand information and the traceability services costs (hereafter, DITS costs), the proportion about retailer's DITS costs undertaken by the manufacturer, the ineffective effect coefficient of the CER level and the quality and safety level and the cost optimization coefficient. However, the cost-sharing situations could affect the change magnitudes of the best revenues.

This paper has two main contributions. First, this paper proposes a demand function that is more suitable for the mixed appliance background of Big Data and blockchain. Secondly, this paper improves the cost-sharing model and finds that demand information sharing and traceability service sharing have different impacts on key pricing factors of low-carbon product. In addition, this research provides a theoretical reference for low-carbon supply chain members to formulate pricing strategies in the new background.

Mixed fermentation with Saccharomyces cerevisiae and non-Saccharomyces yeasts has become an oenlogical tool to improve wines’ organoleptic properties. However, the maximum utilization of this method is dependent upon understanding the influence of mixed cultures on the physiology of S.cerevisiae and non-Saccharomyces yeasts.

In this study, the supernatants from 48 h mixed-culture fermentation were added to the pure cultures of Issatchenkia orientalis and Saccharomyces, respectively. And the authors used RNA sequencing to determine the transcriptome change of I.orientalis and S.cerevisiae in a mixed culture.

The results showed that multiple genes associated with cell growth and death were differentially expressed. Genes related to biosynthesis of amino acids were enriched among those upregulated in the mixed-fermentation supernatant. Meanwhile, the differential expression level of genes encoding enzymes essential for formation of aroma compounds was found in the single and in the mixed fermentation. The high expression level of molecular chaperones Hsp70, Hsp90 and Hsp110 suggests that metabolites of mixed-culture fermentation may lead to aggregation of misfolded proteins. Moreover, upregulation of ethanol dehydrogenase I ADH1 in the mixed-culture fermentations was highlighted.

This is the first time that RNA-seq was used to analyze changes in the transcriptome of mixed cultures. According to the results the authors’ manuscript provided, an integrated view into the adaptive responses of S.cerevisiae and non-Saccharomyces yeasts to the mixed-culture fermentation is benefit for the potential application of S.cerevisiae and non-Saccharomyces yeasts in fruit wine brewing.

This paper aims to deal with the coordination problem of the supply chain through cost sharing of corporate social responsibility (CSR) and government subsidy.

With respect to the coordination problem of the supply chain with CSR, this paper constructs a three-stage game model consisting of a dominant retailer, n suppliers and government. From the perspective of cost sharing and government subsidies, this paper discussed the decentralized and centralized decision-making, respectively. On this basis, this paper designed a coordination mechanism considering both cost sharing and government subsidies and explore the impact of cost sharing rate and government subsidy rate on CSR efforts, members’ profits and social welfare.

CSR can improve the profits of supply chain members and the overall performance of the supply chain. Then the profits of supply chain nodal enterprises will be affected by the fulfillment level of CSR of their partners. Furthermore, excessive CSR will erode the supply chain profits and cause resource waste. High CSR costs often make retailers low CSR effort level, while a high CSR cost sharing rate can reduce the profits of suppliers and the supply chain. In addition, excessive government subsidies will lead to the decline of social welfare. Excessive government subsidies will cause the dependence of enterprises and affect their operating efficiency.

The proposed coordination mechanism can effectively do with the coordination problem of the supply chain.

The proposed coordination mechanism considering cost sharing and government subsidies simultaneously can effectively deal with conflict problems and guarantee the supply chain members and the supply chain to maximize their profits and social welfare.

The purpose of this study is to gather insights into digital consumer behaviour related to Chinese restaurents by examining visual contents on Tripadvisor platform.

Using the deep learning approach, this research assessed consumer-posted online content of dining experiences by implementing image analysis and clustering. Text mining using word cloud analysis revealed the most frequently repeated keywords.

First, 4,000 photos of nine Chinese restaurants posted on Tripadvisor’s website were analyzed using image recognition via Inception V3 and Google’s deep learning network; this revealed 12 hierarchical image clusters. Then, an open-questionnaire survey of 125 Chinese respondents investigated consumers’ information needs before visiting a restaurant and after purchasing behavior (motives to share).

This study contributes to culinary marketing development by introducing a new analysis methodology and demonstrating its application by exploring a wide range of keywords and visual images published on the internet.

This research extends and contributes to the literature regarding visual user-generated content in culinary tourism.

The purpose of this study is investigating the effect of using multi-phase nanofluids, Rayleigh number and baffle arrangement simultaneously on the heat transfer rate and Predict the optimal arrangement type of baffles in the differentiation of Rayleigh number in a 3D enclosure.

Simulations were performed on the base of the L25 Taguchi orthogonal array, and each test was conducted under different height and baffle arrangement. The multi-phase thermal lattice Boltzmann based on the D3Q19 method was used for modeling fluid flow and temperature fields.

Streamlines, isotherms, nanofluid volume fraction distribution and Nusselt number along the wall surface for 104 < Ra < 108 have been demonstrated. Signal-to-noise ratios have been analyzed to predict optimal conditions of maximize and minimize the heat transfer rate. The results show that by choosing the appropriate height and arrangement of the baffles, the average Nusselt number can be changed by more than 57 per cent.

The value of this paper is surveying three-dimensional and two-phase simulation for nanofluid. Also using the Taguchi method for Predicting the optimal arrangement type of baffles in a multi-part enclosure. Finally statistical analysis of the results by using of two maximum and minimum target Function heat transfer rates.

Impulse buying has been the focus of attention in the marketing. With the rise of online shopping, online impulse buying phenomenon becomes increasingly serious. Whereas, the impulse buying behavior in an online environment is rarely discussed in relevant literature. The purpose of this paper is to explore the impact of the type of product and time pressure on consumer online impulse buying intention; this is a relatively new issue of marketing academia in China.

In this paper, the experimental methodology was adopted to explore the impact of consumer online impulse buying tendencies, the departure from the type of product and the time pressure.

Results show that low-involvement feeling products stimulate consumer online impulse buying tendencies. Simultaneously, there is an interaction effect between time pressure and product type, which is, under the influence of time pressure, the enhancement of low-involvement feeling products on consumer online impulse buying tendency is more significant.

This study discusses the interaction between time pressure and product type on consumers’ online impulse buying tendency, which has not been studied before. While discussing the impact of product types on consumers’ impulse buying tendency on the internet, this paper considers the impact of time pressure on consumers’ impulsive buying tendency, and applies the term of time pressure, a psychological research term, to the field of marketing research, so as to make the cross-links between disciplines closer.

The purpose of this study is to analyze the current situation of the competitiveness development of China’s marine industrial clusters, reveal the existing problems and challenges, provide theoretical support and practical guidance for improving the competitiveness of China’s marine industrial clusters so as to promote industrial upgrading and high-quality development and help China realize the strategic transformation from a marine power to a marine power.

This report first provides a detailed review of the current development status and existing issues of marine industry clusters in China. Second, it constructs an evaluation index system for the competitiveness development of China’s marine industry clusters and conducts competitiveness analysis and evaluation of typical marine industry clusters in China. Third, it explores the development trends and prospects of typical marine industry clusters in China. Finally, the report proposes countermeasures and suggestions for enhancing the competitiveness of marine industry clusters in China, focusing on resource optimization, cluster structure and cluster efficiency.

(1) Significant competitiveness of marine shipbuilding and ocean engineering equipment clusters: Through technological innovation and policy support, the marine shipbuilding and ocean engineering equipment clusters have shown a marked improvement in competitiveness, advancing toward high-quality development despite facing macroeconomic fluctuations. (2) Continuous improvement in marine energy and offshore wind power clusters: The competitiveness of marine energy and offshore wind power clusters has been continuously enhanced under supportive policies. However, there is still a need to optimize resource allocation and strengthen innovation stability to meet market challenges. (3) Strong growth potential of desalination and comprehensive utilization clusters: The desalination and comprehensive utilization clusters demonstrate robust growth potential in technological innovation and regional collaborative development. Future efforts should focus on the application of environmentally friendly and energy-saving technologies to ensure a balance between economic and ecological benefits.

By strengthening the competitiveness of industrial clusters, China can effectively respond to international competition, accelerate the transformation and upgrading of the marine industry and support its transition from a maritime power to a strong maritime nation. Hence, this study will focus on analyzing the competitiveness development of China’s marine industry clusters, identifying existing problems and challenges and providing theoretical support and practical guidance for enhancing the competitiveness of China’s marine industry clusters.

Community question answering (CQA) platforms play a significant role in knowledge dissemination and information retrieval. Expert recommendation can assist users by helping them find valuable answers efficiently. Existing works mainly use content and user behavioural features for expert recommendation, and fail to effectively leverage the correlation across multi-dimensional features.

To address the above issue, this work proposes a multi-dimensional feature fusion-based method for expert recommendation, aiming to integrate features of question–answerer pairs from three dimensions, including network features, content features and user behaviour features. Specifically, network features are extracted by first learning user and tag representations using network representation learning methods and then calculating questioner–answerer similarities and answerer–tag similarities. Secondly, content features are extracted from textual contents of questions and answerer generated contents using text representation models. Thirdly, user behaviour features are extracted from user actions observed in CQA platforms, such as following and likes. Finally, given a question–answerer pair, the three dimensional features are fused and used to predict the probability of the candidate expert answering the given question.

The proposed method is evaluated on a data set collected from a publicly available CQA platform. Results show that the proposed method is effective compared with baseline methods. Ablation study shows that network features is the most important dimensional features among all three dimensional features.

This work identifies three dimensional features for expert recommendation in CQA platforms and conducts a comprehensive investigation into the importance of features for the performance of expert recommendation. The results suggest that network features are the most important features among three-dimensional features, which indicates that the performance of expert recommendation in CQA platforms is likely to get improved by further mining network features using advanced techniques, such as graph neural networks. One broader implication is that it is always important to include multi-dimensional features for expert recommendation and conduct systematic investigation to identify the most important features for finding directions for improvement.

This work proposes three-dimensional features given that existing works mostly focus on one or two-dimensional features and demonstrate the effectiveness of the newly proposed features.