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The purpose of this paper is to examine how crowding without violating personal space influences consumers’ channel selection and the underlying mechanism of this process. Crowded environment is ubiquitous and affects consumers’ behaviors. However, less attention has been paid to whether and how crowding influences consumers’ preference for purchasing channels.

There were three studies to test the validity of the theorized model, including two laboratory experiments and a field study. The variance analyses and mediation analyses were used to give more insights into the analytical process.

This study proposes that crowding makes consumers lose their perceived control, leading them to form certain compensatory behavior through the conversion between online and offline purchasing channels – the type of goods moderates the process of compensatory behavior.

The results of this study are helpful for retailers to design effective strategies to allocate resources into online or offline channels and to choose the appropriate types of product to promote.

Environmental clues have been widely studied in previous marketing research. Crowding, as a common environmental clue, has only been noticed in recent years. This study examines the impact of crowding on consumers’ channel preference. The results of three studies have confirmed that consumers have higher preference for offline shopping when they are in a crowded environment and found the intrinsic mechanism and the marginal scenario of this process.

This paper mainly explores the relationship between digital inclusive finance and financing constraints of technological-based SMEs, and how digital inclusive finance affects the financing constraints of technology-based SMEs. This paper empirically analyzes the relationship between them through the OLS model, and then further verifies the relationship between them through robust regression and heterogeneity analysis. At the same time, it uses the mechanism test to explore how digital inclusive finance affects the financing constraints of technology-based SMEs. This paper aims to address these issues.

This paper aims to explain the relationship between digital inclusive finance and financing constraints of technological-based SMEs. Technology-based SMEs always face the difficult problem of “financing difficulty” and “financing expensive” in the development process, which hinders the survival and development of enterprises to some extent. Digital inclusive finance development policy vigorously promoted by the state has alleviated the financing constraints of technology-based SMEs and brought opportunities for their development.

The results show that the role of digital inclusive finance in alleviating the financing constraints of technology-based SMEs, and incremental supplement and alleviating information asymmetry are the main reasons for digital inclusive finance to alleviate the financing constraints of technology-based SMEs. In view of the availability of digital inclusive financial data, this paper only uses the data from 2014 to 2019.

The authors’ research clearly found that the development of digital inclusive finance alleviates the financing of technology-based SMEs from the two aspects of “incremental supplement” and alleviating information asymmetry, so as to provide corresponding reference basis for the government to formulate a series of plans to support the development of technology-based SMEs.

This study investigated four different economic level areas of China (Shanghai, Shandong, Shaanxi, and Guizhou) to analyze the eastern and western urban and rural media service status at different development stages. This set of data comes from the comparison of regional urban and rural areas and indicates the various aspects of differences in the survey area, including the media use habits, media resources, media consumer demand, evaluation of media services, the role of media in public life, public knowledge level, and so on. On analyzing data comprehensively, one thing can be found that there is a positive correlation between the public media contact degree and the public knowledge level. The media plays an extremely important role in public life and regional public knowledge gap between urban and rural areas exists. Furthermore, this gap is positively correlated to the media resources and media exposure. The trend of media using on mobile phone and computer in urban areas increases significantly greater than in rural areas. Then, how to narrow the urban–rural and regional public knowledge gap and reduce the negative impact of the digital divide will be an important urgent task.

The purpose of this paper is to apply grey statistical model to identify and classify live fault rupture.

Based on grey statistical mode, this paper uses eight faults' ripping speed observation data from 1997 to 2001, according to the grey statistics method for analysis, and recognizes active fault rupture situation. Using the conventional methods, namely taking all faults monitoring stations' average dislocation rate to analysis and make judgment, the average results are obtained.

The results show that the results are closer to reality because the grey statistical evaluation method has considered dislocation rate and other discrete factors.

The method exposed in the paper can be used to monitor and recognize live fault rupture in earthquake prediction.

According to the fault dislocation rate, this paper advances active fault rupture identification and classification method based on grey statistical model.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

In the past decades, artificial intelligence (AI)-based hybrid methods have been increasingly applied in construction risk management practices. The purpose of this paper is to review and compile the current AI methods used for cost-risk assessment in the construction management domain in order to capture complexity and risk interdependencies under high uncertainty.

This paper makes a content analysis, based on a comprehensive literature review of articles published in high-quality journals from the years 2008 to 2018. Fuzzy hybrid methods, such as fuzzy-analytical network processing, fuzzy-artificial neural network and fuzzy-simulation, have been widely used and dominated in the literature due to their ability to measure the complexity and uncertainty of the system.

The findings of this review article suggest that due to the limitation of subjective risk data and complex computation, the applications of these AI methods are limited in order to address cost overrun issues under high uncertainty. It is suggested that a hybrid approach of fuzzy logic and extended form of Bayesian belief network (BBN) can be applied in cost-risk assessment to better capture complexity-risk interdependencies under uncertainty.

This study only focuses on the subjective risk assessment methods applied in construction management to overcome cost overrun problem. Therefore, future research can be extended to interpret the input data required to deal with uncertainties, rather than relying solely on subjective judgments in risk assessment analysis.

These results may assist in the management of cost overrun while addressing complexity and uncertainty to avoid chaos in a project. In addition, project managers, experts and practitioners should address the interrelationship between key complexity and risk factors in order to plan risk impact on project cost. The proposed hybrid method of fuzzy logic and BBN can better support the management implications in recent construction risk management practice.

This study addresses the applications of AI-based methods in complex construction projects. A proposed hybrid approach could better address the complexity-risk interdependencies which increase cost uncertainty in project.

The advent of globalization not only made the manufacturing sector highly competitive but also facilitated best-quality products. The trend is further augmented by e-Commerce which increases the penetration to the targeted customer with the easy availability of customized product. In this backdrop, Indian manufacturing industries are striving hard to seek out best systems which will yield maximum profitability. Time is ripe to realize the true potential of agile manufacturing system (AMS). Infusion of AMS in manufacturing industry will bring forth the elusive mix of customer needs and products at lowest possible cost. But adoption and implementation of AMS is a challenging task in itself. There are certain facilitators and criteria which not only facilitate the system but also help in the effective and smooth implementation of this system. The purpose of this paper is to identify the criteria to weightage and ranking to AMS facilitators. This study was carried out by different approaches, namely, entropy approach, multi-objective optimization on the basis of ratio analysis (MOORA) method, Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) analysis and a cross-sectional survey of manufacturing firms in India.

The criteria and facilitators are identified followed by the application of entropy approach, MOORA method and VIKOR analysis to study and analyze the criteria weight and provide the ranking to AMS facilitators.

The result of the entropy approach concludes that beneficiary and non-beneficiary criteria carry 48.43 and 51.56 percent weight, respectively. MOORA method and VIKOR analysis conclude that organization structure and virtual enterprise facilitators are carrying the first and second rank, respectively.

This study is completed on the basis of responses from few experts from industry and academicians who may not reflect the attitude of entire industry community.

This research is expected to facilitate policy makers in government and industries to frame policies for optimum utilization of resources and infrastructure for better performance. This paper helps the researcher to do a case study on the implementation of AMS and then finally helps to society in getting the high-quality product in an easy way.

Integration of entropy approach, MOORA method and VIKOR analysis with identification of AMS criteria weightage and ranking to AMS facilitators has been recommended for an industry which is an innovative effort for the execution of AMS.

The purpose of this paper is to introduce an interpreting schema and semantic description framework for a collection of images of Xilankapu, a traditional Chinese form of embroidered fabric and brocade artwork.

First, the authors interpret the artwork of Xilankapu through Gillian Rose’s “four site” theory by presenting how the brocades were made, how the patterns of Xilankapu are classified and the geometrical abstraction of visual images. To further describe the images of this type of brocade, this paper presents semantic descriptions that include objective–non-objective relations and a multi-layered semantic framework. Furthermore, the authors developed corresponding methods for scanning, storage and indexing images for retrieval.

As exploratory research on describing, preserving and indexing images of Xilankapu in the context of the preservation of cultural heritage, the authors collected 1,000+ images of traditional Xilankapu, classifying and storing some of the images in a database. They developed an index schema that combines concept- and content-based approaches according to the proposed semantic description framework. They found that the framework can describe, store and preserve semantic and non-semantic information of the same image. They relate the findings of this paper to future research directions for the digital preservation of traditional cultural heritages.

The framework has been designed especially for brocade, and it needs to be extended to other types of cultural image.

The semantic description framework can describe connotative semantic information on Xilankapu. It can also assist the later information retrieval work in organizing implicit information about culturally related visual materials.

This study aims to explore the success factors of tourism performing arts (TPA) programs by analyzing a large data set of online reviews.

A total of 195,230 reviews from Ctrip.com were collected and preprocessed. A deep learning method was leveraged to estimate the similarity between words. Then, regression analysis was conducted to determine success factors.

This study extracted four positive and two negative factors affecting tourist satisfaction with tourism performance arts. The results demonstrate that the tourists paid the most attention to the traditional Chinese cultural aspects, audiovisual effects and the actors’ performing enthusiasm.

Despite this study’s large data set, the focused was only on Chinese reviews. It would be useful and interesting to compare the success factors of tourism performance arts programs offered in different countries.

The study findings can contribute to the development of TPA programs to attract tourists to travel destinations.

This study demonstrates that analyzing online reviews of TPA through text mining technology is an effective method of understanding tourist satisfaction.

在线点评分析探析旅游演艺成功因素

本研究旨在通过分析大型在线评论数据集来探索旅游表演艺术项目的成功因素。

共收集和预处理来自携程网的 195,230 条评论。利用深度学习方法来估计单词之间的相似性。然后, 进行回归分析以确定成功因素。

本研究提取了影响游客对旅游表演艺术满意度的四个积极因素和两个消极因素。结果表明, 游客最关注中国传统文化方面、视听效果和演员的表演热情。

尽管我们的数据集很大, 但它只关注中文评论。比较不同国家提供的旅游表演艺术项目的成功因素将是有用和有趣的未来研究方向。

研究结果有助于发展旅游表演艺术项目, 以吸引游客前往旅游目的地。

研究表明, 通过文本挖掘技术分析旅游表演艺术的在线评论是了解游客满意度的有效方法。