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The emergence of Internet product sales platform has not only greatly enriched consumers' choices and facilitated their purchasing behavior but also provided space for counterfeit products and relevant fraudulent signal strategies in China, which damage the consumer's rights and interests and further disrupt the normal order of the e-commerce market. However, effective empirical study on the long-term and dynamic influence mechanism of fraudulent signals of counterfeit products and the seller incentive mechanism is still unavailable in academic circles, especially in the Chinese market, where government regulation is deemed to be lacking. For the purpose of this paper, an empirical study has been conducted by virtue of Internet e-commerce platform data based on data capture technology to analyze the dynamic performance effect mechanism of e-commerce fraudulent signals of counterfeit products under multiple game conditions. The study results show that selling of counterfeit products by using fraudulent signals can improve the current sales performance, but it will cause a long-term performance decline consequently. Additionally, from the perspective of the pricing mechanism, this paper analyzes the said seller incentive mechanism of counterfeit products. Finally, this paper puts forward relevant management suggestions based on the empirical study findings. [ABSTRACT FROM AUTHOR]

Currently, the global consumer market is moving toward digitalization, and cross-border e-commerce enterprises are no exception and have to make adjustments in their operational strategies. Digitalization brings complexity, dynamism, and fragmentation in sales channels, media environment, and consumer behavior, requiring cross-border e-commerce enterprises to react more quickly and timely, and the need for intelligent operations is becoming more and more urgent. In this paper, through the problem of predicting the e-commerce user behavior process, the model usually needs to focus on both long-term preferences and short-term preferences of e-commerce users in the current behavior sequence; otherwise, the behavior prediction will be much less effective. Specifically, through a comprehensive analysis of typical cases, the strategies and problems in the intelligent operation process of China's cross-border e-commerce enterprises at the present stage are discussed, and corresponding suggestions are put forward, so as to promote the rapid development of China's cross-border e-commerce enterprises. [ABSTRACT FROM AUTHOR]

In the era of the rise of big data, if insurance companies can effectively and reasonably use existing data to tap more potential information, it can not only improve work efficiency but also achieve precise marketing to customers, thereby saving costs. At the same time, China pays more and more attention to financial insurance, so it is of great significance to use customer information to explore the purchase behavior of financial insurance. This paper mainly analyzes the factors that affect the purchase of financial insurance from the aspects of individuals and families and provides references for insurance marketing. This paper selects the results of the China Comprehensive Social Survey in 2020 as the empirical sample data of this paper and sets whether to purchase financial insurance as the target variable. The characteristic variables were screened, and the 10 variables selected after screening were finally used to build the model. Next, the data are divided into training set and test set, and a decision tree learning model is established on the two data sets at the same time. The classification results of the model are evaluated according to the classification evaluation indicators. Finally, the decision tree analysis results provide suggestions and strategies for the construction of insurance marketing recommendation methods. [ABSTRACT FROM AUTHOR]

Based on the close relationship between real estate and capital financing, this paper specifically discusses the impact of interest rate changes in China on real estate market transactions. Housing price regulation has been a hot and focused topic of economics research. It is important to explore the effect of interest rate on real estate market transactions, for the interest rate is an important tool for the government to carry out macrocontrol of the real estate market and affects residents' consumption choices of goods. Currently, most scholars believe that interest rate changes have a significant impact on house prices, but their studies are often based on empirical analysis of macro data, making it difficult to exclude the effects of economic differences, geographic characteristics, and other factors. Also, some scholars believe that it is difficult for interest rates to have a long-term impact on real estate prices. This paper applies the experimental economics method to simulate real estate transactions in the real market and control the irrelevant variables to study the movements of housing prices, transaction volumes, consumer transaction intentions and bubble indices under different deposit and lending rates. The results show that: (1) The level of deposit interest rate has a significant inhibitory effect on housing price and a significant promoting effect on real estate market transaction volume and traders' house-buying behavior. The higher the level of deposit interest rate is, the better the degree of regulating house prices deviating from the theoretical price is and the better the effect of inhibiting market bubbles. (2) The level of lending rate has a significant inhibiting effect on the volume of real estate transactions and a significant promoting effect on the house-buying behavior of traders, but its effect on housing prices and market bubbles is not significant. The higher the level of lending rate is, the better the degree of regulating housing prices deviating from the theoretical price is. (3) The effect of deposit interest rate and lending rate policies on the house selling behavior of market traders is not significant. [ABSTRACT FROM AUTHOR]

Shared manufacturing is the application innovation of the digital economy in the field of manufacturing and brings new opportunities for the transformation and upgrading of China and even the global manufacturing industry. In order to explore the strategy selection of enterprises on the shared manufacturing platform, this study constructs a two-party evolutionary game model and analyzes the dynamic relationship between manufacturing enterprise A and manufacturing enterprise B. Furthermore, in order to explore the influence of consumers' strategies of manufacturing enterprises on the platform, the study constructs a tripartite evolutionary game model of manufacturing enterprise A, manufacturing enterprise B, and consumers. Based on the principles of system dynamics, the paper uses Matlab to simulate the evolutionary game process dynamically and discusses the influence of parameter changes on resource-sharing enthusiasm and strategy selection. The research shows that in the two-party game, manufacturing enterprises are more inclined to adopt the strategy of sharing manufacturing resources. In the tripartite game, consumers' decision-making will affect the strategic choice of manufacturing enterprises. Consumers tend to establish strong dependence on shared-manufacturing products in the process of sharing manufacturing resources. [ABSTRACT FROM AUTHOR]

With the continuous development of China's social economy, the competitiveness of brand market is gradually increasing. In order to improve their own level in brand building, major enterprises gradually explore and study visual communication design. Brand visual design has also received more and more attention. Building a complete and rich visual design system can improve the brand level and attract users to consume. Based on the abovementioned situation, this paper proposes to use collaborative filtering algorithm to analyze and study brand visual design. Firstly, a solution is proposed to solve the problem of low accuracy of general recommendation algorithm in brand goods. Collaborative filtering algorithm is used to analyze the visual communication design process of enterprise brand. Research on personalized image design according to consumers' trust and recognition of brand design is conducted. In traditional craft brand visual design, we mainly study the impact of image design on consumer behavior. The brand loyalty model is used to predict and analyze the visual design effect. Also, the user's evaluation coefficient is taken as the expression of brand visual design recognition. Finally, the collaborative filtering algorithm is optimized to improve the consumer similarity based on the original algorithm. The results show that the brand visual design using collaborative filtering algorithm can help enterprises obtain greater benefits in their own brand construction. It provides effective data help in the development of traditional craft brands. [ABSTRACT FROM AUTHOR]

China has become the world's largest luxury goods consumer market due to its population base. In view of the bright prospects of the luxury consumer market, major companies have entered and want to get a share. For the luxury goods industry, traditional mass marketing methods are not able to serve corporate sales and marketing strategies more effectively, and targeted marketing is clearly much more efficient than randomized marketing. Therefore, in this paper, based on consumer buying habits and characteristics data of luxury goods, the paper uses a machine learning algorithm to build a personalized marketing strategy model. And the paper uses historical data to model and form deductions to predict the purchase demand of each consumer and evaluate the possibility of customers buying different goods, including cosmetics, jewelry, and clothing. [ABSTRACT FROM AUTHOR]

Although the clarification of property rights for agricultural land has the potential to enhance agricultural production efficiency and support its sustainable growth, this goal may not always be met in reality. As a result, the emphasis of this study is on the elements that affect agricultural output. It also examines how the stability of land rights affects agricultural production efficiency and, most importantly, how the heterogeneity of farmers' perspectives affects this process. Through the empirical test using the data of farmers in Henan Province, the largest wheat area in China, the results show that: (1) The farmland confirmation policy significantly promotes the improvement of the pure technical efficiency of agricultural production, a series of robustness tests, and the treatment of endogenous problems, which also confirmed the robustness of the results. (2) In the allocation of factors, agricultural investment and credit acquisition have been proved to be important influencing mechanisms, while labor and land transfer have not played a mechanistic role. (3) Heterogeneity analysis shows that the self-service of farmers choosing to purchase agricultural machinery is more efficient than purchasing outsourcing services; The agricultural production of farmer households without hired workers has a significant technical efficiency, but the impact on farmer households with hired workers is not significant; for farmer households with agricultural insurance purchase behavior, purchase willingness, and planting and breeding advantages, the farmland ownership confirmation policy can play a more important role in promoting the pure technical efficiency of agricultural production; The promotion effect of the farmland right confirmation policy on the pure technical efficiency of agricultural output is strongest when there is a smaller level of farmers operating on a part-time basis and when more farmers prioritize profit maximization as the production goal. Corresponding policy recommendations are made at the conclusion of the study in light of the conclusions mentioned. [ABSTRACT FROM AUTHOR]

As passengers are proved to be preference heterogeneous in air travel, this paper tries to model the air ticket purchase behavior incorporating market segmentation. In the research, a latent-NL model, established on the latent class structure and the nested logit model, integrates the personal features as well as the purchase preferences into the forecast of segment-specific purchase probability. In order to calibrate the model, a stated preference survey is designed with the choice profiles using real service information, and the survey is conducted in four cities in China for data collection. The results show that the proposed model provides an effective approach for predicting the air travel demand in particular for air ticket pricing, and the estimation results outperforms the traditional-nested logit model with higher goodness-of-fit. Besides, the model is then adopted to test the efficiency of different pricing strategies, showing its advantages in improving the flight revenues. [ABSTRACT FROM AUTHOR]

To assist filtering and sorting massive review messages, this paper attempts to examine the determinants of review attraction and helpfulness. Our analysis divides consumers’ reading process into “notice stage” and “comprehend stage” and considers the impact of “explicit information” and “implicit information” of review attraction and review helpfulness. 633 online product reviews were collected from Amazon China. A mixed-method approach is employed to test the conceptual model proposed for examining the influencing factors of review attraction and helpfulness. The empirical results show that reviews with negative extremity, more words, and higher reviewer rank easily gain more attraction and reviews with negative extremity, higher reviewer rank, mixed subjective property, and mixed sentiment seem to be more helpful. The research findings provide some important insights, which will help online businesses to encourage consumers to write good quality reviews and take more active actions to maximise the value of online reviews. [ABSTRACT FROM AUTHOR]

Despite the current rapid growth of organic agriculture, the problem of low demand for organic agricultural products persists in China, and the consumption space warrants improvement. Exploring consumers' preferences for organic agricultural products and increasing their purchase intentions are of utmost significance to promote organic agricultural production. Thus, this study takes organic milk, which accounts for 58% of China's organic processed agricultural products in sales, as the research object, and uses a choice experiment to investigate the influence of consumers on the purchase intention of organic milk under the intervention of environmental protection information and quality and safety information. The main research results revealed that both environmental protection information and quality and safety information have significantly increased consumers' willingness to purchase and that quality and safety information has increased more than environmental protection information. [ABSTRACT FROM AUTHOR]

Attracting more consumers through mobile online platforms has become the most important thing for luxury brands. However, few studies have explored how cultural context, as exemplified by face consciousness and source credibility, influences the online luxury consumption and promotion of mobile users. To fill that research gap, this study constructed a research model of Chinese consumers to examine the effect of source credibility on the online luxury purchase and recommendation intentions of mobile consumers, and the moderating effects of face consciousness were examined. A structural equation model was also employed in our study. Furthermore, a field survey with 168 mobile online shopping customers was conducted to test the research model and hypotheses. The empirical results confirm the following: (1) the source credibility of online reviews had a positive effect on the online luxury purchase intentions of mobile customers but increased their intention to recommend the shopping site even more in a luxury environment; (2) face consciousness had a negative moderating effect between source credibility and the online luxury purchase intention of mobile consumers; and (3) face consciousness had a negative moderating effect between source credibility and the luxury recommendation intention of mobile consumers. The implications for theory and practice and suggestions for future research were also discussed. [ABSTRACT FROM AUTHOR]

Recently, IoV-based services and vehicles have come to the forefront as part of the growing market for the automobile industry. Since IoV-based services and vehicles were introduced, they have been expected to grow rapidly. However, contrary to optimistic expectations for future market growth, the IoV-based services and vehicles market has appeared to hit a roadblock and remains at an early market stage. Therefore, research of the determinants leading to consumers' intention to accept and purchase IoV-based services and vehicles is significant for either academics or practitioners. Drawing upon the extended unified theory of acceptance and use of technology acceptance model (UTAUT2), the perceived risk theory, and the initial trust model, we developed an integrated conceptual model and explored what and how various determinant antecedent conditions fit together on consumer intention to accept IoV-based services and vehicles. The proposed model and hypotheses were assessed by both symmetric (partial least square structural equation modeling, PLS-SEM) and asymmetric (fsQCA) approaches using online survey datasets with 362 Chinese consumers. The findings suggest that PLS-SEM and fsQCA are complementary analytical techniques providing comparable results. PLS-SEM results indicate that performance expectancy, price value, habit, and initial trust have significant effects on behavioral intention to accept IoV services. Despite other determinants, e.g., effort expectancy, social influence, facilitating conditions, hedonic motivation, and perceived risk, have no significant effect. FsQCA results reveal twelve different configurations of determinants resulting in a high level of behavioral intention to accept IoV services, and eight causal paths equifinally leading to the negation of behavioral intention to accept IoV services. These findings suggest that several conditions that were not significant in PLS-SEM are sufficient conditions when combined with other conditions. This study enriches relevant research studies on IoV-based services acceptance and provides relevant insights and marketing suggestions for incentivizing consumers to accept the IoV-based services. [ABSTRACT FROM AUTHOR]

Background and Aims This study was designed to investigate the sensory attributes that relate to Chinese consumer liking responses to red wines and determine whether they differ from those of Australian consumers in a cross-cultural study. Methods and Results A set of Australian and international wines was profiled by a sensory descriptive analysis panel. A subset of 14 wines was assessed for hedonic liking by 310 consumers in China. These results were compared with findings of an Australian test using 216 consumers. For the Chinese sample, liking was most strongly positively associated with 'red fruit', 'sweetness' and 'fruity aftertaste' attributes. Two consumer clusters (80% of the consumers) preferred sweeter wines and had low acceptance to wines with strong acidity, with differences between the two clusters in their response to bitterness, 'bruised fruit' and 'fresh green' attributes. The third cluster liked wines with higher purple colour, 'dark fruit', 'viscosity' and 'black pepper', and had a lower liking score for wines with higher astringency. Two clusters of the Australian consumers were found with similar sensory attribute drivers of liking compared with those identified in China, but with different proportions. Conclusions The consumers from the two countries, while having broadly similar preferences, differed in both the size of cluster groups and in the importance of certain attributes. Significance of the Study The study provides an insight into differences in drivers of preference between an established Western wine consumer market and a developing Asian market. [ABSTRACT FROM AUTHOR]