[Retracted] Analysis of Nostalgia Emotional Experience, Rural Tourism Environment Cognition, and Consumption Willingness Based on Big Data Technology

Abstract

As the primary research vehicle, rural tourism is used in this paper to examine urban visitors’ “homesickness.” This research explores the effects of homesickness on tourists’ perceptions of travel destinations and consumption intentions through qualitative analysis, logistic empirical analysis, and questionnaire survey. This work also explores the behavioral traits of customers’ purchase intentions from the perspective of a “big data” environment, and it constructs the relevant consumption behavior model for rural visitors in accordance with those behavioral traits. Through questionnaire design and investigation, this paper makes statistical analysis on tourists’ basic information, expected value, and actual experience and explores the related factors that affect their consumption behavior, so as to understand the consumption behavior law of tourists in rural tourism consumption. The research shows that the MSE (mean squared error) of this algorithm is about 4.16, and the RMSE (root mean square error) of this algorithm is about 0.508. Finally, combining the influence of tourists’ consumption behavior, this paper tries to put forward some countermeasures and suggestions on rural tourism. This paper aims to study the development and planning of rural tourist destinations, and provide corresponding basis for the destination selection of tourists with homesickness.

Development Drivers of Rural Summer Health Tourism for the Urban Elderly: A Demand- and Supply-Based Framework

“…Rural tourism enables the elderly to relive past lives [58]. The rural lifestyle can arouse tourists' nostalgia [103], and rural scenes and objects can attract nostalgic elderly [104]. The RSHTUE destination lifestyle attracts the nostalgic elderly, whose arrival raises the RSHTUE demand.…”

Retracted: Analysis of Nostalgia Emotional Experience, Rural Tourism Environment Cognition, and Consumption Willingness Based on Big Data Technology

“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [ 1 ]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process: Discrepancies in scope Discrepancies in the description of the research reported Discrepancies between the availability of data and the research described Inappropriate citations Incoherent, meaningless and/or irrelevant content included in the article Peer-review manipulation …”

“…Tis article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. Tis investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”