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With the deep cross-border integration of tourism and big data, the personalized demand of tourist groups is increasingly strong. Precision marketing has become a new marketing mode that the tourism industry needs to pay close attention to and explore. Based on the advantages of big data platform and location-based service, starting from the precise marketing demand of tourism, we design data flow mining technology framework for user’s mobile behavior trajectory based on location services in mobile e-commerce environment to get user track data that incorporates location information, consumption information, and social information. Data mining clustering technology is used to analyze the characteristics of users’ mobile behavior trajectories, and the precise recommendation system of tourism is constructed to provide support for tourism decision making. It can target the tourist group for precise marketing and make tourists travel smarter.

As the global warming crisis is increasing daily, it is crucial to find ways to reduce the carbon footprint generated by activities like the production, consumption, and distribution of goods and services. This empirical study has looked at one approach through which environment-friendly production and consumption can be encouraged. The developed model has studied the relationship between retailers’ access to green finance and consumer purchase intention of green products by incorporating the role of environmental, status, and future consciousness. Theoretical foundations for this model have been taken from the theory of planned behaviour (TPB) and theory of reasoned action (TRA), which have extensively discussed the role of consciousness and societal norms while making purchase intentions. To gain insights about the purchasing behaviour of consumers, this study collected data from the Jiangsu province of China, where a non-probability convenience sampling technique was used to distribute a questionnaire to 400 respondents between February 2022 and August 2022. The collected data was analysed using Structural Equation Modeling (SEM) in SmartPLS in order to study the relationship between independent and dependent variables. Results of this study show that retailers’ access to green finance positively impacts consumer purchase intention towards green products, and adding a consciousness perspective in the model strengthens this relationship. Moreover, the theory of planned behaviour and the theory of reasoned action were validated through this study, providing insights for policymakers on the importance of promoting green finance to influence green product purchase intention. Overall, this study shows that policymakers should give green financing to retailers and environmental and future awareness to consumers to encourage environment-friendly behaviour.

China is one of the largest sources of outbound tourists coming to the United States. We used data from a choice experiment to determine whether Chinese tourists are interested and willing to pay for agritourism tour packages in which the U.S. state of Oklahoma is the rural destination. Our research is important because agritourism is a growing source of farm revenue, international tourists have potential to accelerate this growth, and China is the largest market for international tourism. Results suggest that, from various agritourism packages offered to them, Chinese travelers are price conscious but willing to pay significant amounts for packages that provide more local foods, that allow them to visit more event and recreation sites, and stay in cabins rather than farmstead accommodations. We also find evidence of significant heterogeneity in Chinese willingness to pay for agritourism attributes.