Discrete Element Analysis on the Correlation between Marketing Means and Economic Benefits of Island Ecotourism

Mo, Jianghong; Ren, Fei

doi:10.2112/si103-216.1

Cited by 6 publications

(5 citation statements)

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“…I ij is the standardized value of the j -th evaluation index of the I-type livelihood capital. In this paper, the calculation of the overall livelihood capital of farmers is to take the average value of various livelihood capital and then use the weight and the proportion of the quantitative treatment [ 13 – 15 ].…”

Section: Methodsmentioning

confidence: 99%

Difference of Farmers’ Livelihood Capital before and after Rural Tourism Development

Xiao

Xixi

Lü

2022

Computational Intelligence and Neuroscience

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Purpose. To compare the differences in rural household livelihood capital before and after the development of rural tourism to derive factors that affect rural household livelihood capital. Methodology. This study establishes a household livelihood capital index system to determine the total livelihood capital owned by rural households. Findings. After the development of rural tourism, regardless of farmers participating in rural tourism or not participating in rural tourism, their livelihood capital has increased, but the growth rate of livelihood capital of farmers participating in rural tourism is significantly higher than that of non-participating farmers, especially social capital and financial capital. Originality. This study is based on the sustainable livelihood analysis framework developed by DFID, analyzes the characteristics of farmers’ livelihood capital and livelihood activities, and discusses the differences of farmers’ livelihood capital before and after rural tourism development.

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Section: Methodsmentioning

confidence: 99%

Difference of Farmers’ Livelihood Capital before and after Rural Tourism Development

Xiao

Xixi

Lü

2022

Computational Intelligence and Neuroscience

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“…In order to better describe users' interests, it is necessary to analyze them quantitatively and assign different weights to different interests to measure them more accurately. erefore, in order to build the interest graph of social commerce users, this paper adopts the segmentation tree vector space model (a modified vector space model (VSM)) [28][29][30][31][32][33]. is model can classify and assign weights to different interests of users, that is, expressing users' interests in the form of text, then extracting interest keywords from them for classification, and then calculating the interest distribution by weights.…”

Section: User Interest Representationmentioning

confidence: 99%

Clustering Merchants and Accurate Marketing of Products Using the Segmentation Tree Vector Space Model

Ding

2022

Mathematical Problems in Engineering

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Using social commerce users as the data source, a reasonable and effective interest expression mechanism is used to construct an interest graph of sample users to achieve the purpose of clustering merchants and users as well as realizing accurate marketing of products. By introducing an improved vector space model, the segmentation tree vector space model, to express the interests of the target user group and, on this basis, using the complex network analysis tool Gephi to construct an interest graph, based on the user interest graph, we use Python to implement the K-means algorithm and the users of the sample set according to interest topics for community discovery. The experimental results show that the interests of the sample users are carefully divided, each user is divided into different thematic communities according to different interests, and the constructed interest graph is more satisfactory. The research design of the social commerce user interest mapping scheme is highly feasible, reasonable, and effective and provides new ideas for the research of interest graph, and the boundaries of thematic communities based on interests are clear.

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“…The geographical elements are always interdependent, interrelated, and mutually restricted. Correlation analysis is a universal method to study the relationship among these geographical elements, which includes two parts: Correlation direction and correlation degree (Mo & Ren, 2020).…”

Section: Correlation Analysismentioning

confidence: 99%

Spatiotemporal Evolution of NPP in Sandy Land of China's Seasonal Freezing-Thawing Typical Region

Wang

2022

International Journal of Agricultural and Environmental Information Systems

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Based on the data set of AVHRR GIMMS, TERRA/AQUA MODIS NDVI, and climate data from 1982 to 2018, CASA model, GIS spatial analysis, and mathematical statistics were used to study the changing law in the category of time and space, spatial distribution, and the correlativity between the NPP and meteorological factors in the sandy land of China's Seasonal Freezing-Thawing Typical Region. The results showed that the average annual NPP value of vegetation in the growing season of the sandy land from 1982 to 2018 fluctuated between 217.65-356.61 gC/m2a, showing an obvious seasonality and a significant increase. The spatial distribution of NPP in the sandy land in the near 37a is significantly different. There are significant seasonal differences in vegetation responses to temperature, precipitation, wind speed, evaporation, and other meteorological factors in different regions. The increase of vegetation cover in sandy land of China's Seasonal Freezing-Thawing Typical Region is controlled by regional atmospheric circulation and human dynamics.

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Discrete Element Analysis on the Correlation between Marketing Means and Economic Benefits of Island Ecotourism

Cited by 6 publications

References 0 publications

Difference of Farmers’ Livelihood Capital before and after Rural Tourism Development

Difference of Farmers’ Livelihood Capital before and after Rural Tourism Development

Clustering Merchants and Accurate Marketing of Products Using the Segmentation Tree Vector Space Model

Spatiotemporal Evolution of NPP in Sandy Land of China's Seasonal Freezing-Thawing Typical Region

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