| The popularity and development of the Internet has driven the rapid development of e-commerce,and online shopping has become a consumption mode that consumers are increasingly relying on.In recent years,with the rapid development of cold chain logistics,fresh agricultural products have gradually become online hot products.The new crown epidemic that broke out earlier this year has accelerated the growth of online sales of fresh agricultural products.As an important channel for consumers to purchase fresh agricultural products online,e-commerce platforms have also accumulated more and more online reviews.While providing important references for consumers to make purchasing decisions,they also provide e-commerce companies with an understanding of consumers,Optimize the data foundation of product supply strategy.In view of this,this article takes experiential goods-fresh agricultural products as research objects,analyzes the impact of online reviews on online sales of fresh agricultural products,focuses on structured data and unstructured data of online reviews,and reviews text dimensions.Literature combing,model construction,review text mining,and empirical analysis.This article mainly wants to answer the following three questions:(1)Which of the total cumulative reviews,scores,and review texts has a more significant impact on online sales?(2)What is the mechanism of the effect of the online review text information on product sales?(3)Fresh e-commerce stores should pay more attention to which dimension to carry out marketing promotion: First,promote high-quality reviews after purchase to attract potential consumers to buy;Second,guide consumers to conduct post-purchase through combined marketing strategies High scores,persuade potential consumers;Third,optimize product supply strategies through online reviews,and attract consumers to buy products by improving consumer satisfaction.This paper focuses on the above issues,including literature review,model construction,review text mining,and empirical analysis.First,in the literature research: This article starts by sorting out online reviews,characteristics of fresh agricultural products,and related concepts and research status of online product sales.It is found that online reviews are a form of online word of mouth and a way of information dissemination.The main characteristic is fragile and perishable,and freshness is an important indicator to determine its value.In the online shopping process of fresh agricultural products,information related to product quality(freshness),store packaging logistics and service quality in online review texts will have an important impact on consumers' purchasing decisions.Therefore,based on cognitive effort theory,persuasion and persuasion effects,and consumer attitude models,assuming that each consumer is a rational person,this article divides online reviews into structured data and unstructured data-review text dimensions.These dimensions are subdivided into six aspects,such as the cumulative number of reviews,ratings,text positive sentiment,product quality,packaging logistics,and service quality.In addition,according to research,the perceived usefulness of consumers to online reviews also affects product sales.Because fresh produce is extremely prone to loss in the country of origin,logistics,transportation and distribution,purchased consumers will comment on the freshness of the product,and potential consumers will psychologically perceive the usefulness of the relevant product information in online reviews,affecting Its purchase decision,which in turn affects store network sales.Second,model construction: Through combing the literature and combining with the actual situation,this paper uses perceived usefulness as an intermediary variable in online reviews to product sales relations,builds the research model of this article and proposes hypotheses.Third,comment text mining: This article selects JD.com's fresh produce from the comprehensive e-commerce platform as the research object,and uses text mining technology to crawl comment data from JD website fresh shops.Collected 95,428 real reviews of 298 fresh agricultural products from October 1,2019 to February 20,2020,using ROST text mining tools to analyze text features to build a network,and mining fresh agricultural products that consumers are concerned about in the review text Purchase related review factors.By calculating the ratio of keywords and total word frequency related to the product purchased by consumers and constructing a text emotional polarity model,the product quality,packaging logistics,service quality average,and emotional tendency average of 298 fresh agricultural products were obtained,plus crawling Data,such as sales rankings,cumulativereviews,and average ratings,are used as the basis for empirical analysis.Fourth,empirical analysis: This paper first uses statistical software SPSS19.0 to perform descriptive statistics and correlation analysis on the survey samples to explain the basic situation of the sample data and the applicability of the samples,and then use model regression analysis to perform hypothesis testing and Intermediate effect test.The following conclusions are obtained through research:(1)Structured data of online reviews: The number and ratings of reviews have a direct positive impact on the online sales of fresh produce.(2)Review texts of online reviews: Product quality,packaging logistics,and textual sentiment have a direct positive impact on product sales.Commentary texts have positive sentiment to persuade potential consumers,and through the text,consumers pay attention to products when they purchase products.Factors such as quality,packaging and logistics affect consumer purchase decisions and directly affect product sales.(3)Service quality indirectly affects online sales of fresh agricultural products through the mediating role of perceived usefulness.According to the research conclusions,this article proposes an optimization strategy for increasing the sales of fresh food products,that is,fresh food e-commerce stores should pay more attention to constantly improving the online review incentive mechanism,and actively guide consumers to write post-purchase ratings and write high-quality review content.Develop online reviews to optimize product supply strategies and increase consumer satisfaction through online reviews to attract potential consumers to buy. |
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