{"title":"基于PLS-SEM的方法:通过Facebook的大数据分析Z世代的购买意愿","authors":"Vikas Kumar;Preeti;Shaiku Shahida Saheb;Sunil Kumari;Kanishka Pathak;Jai Kishan Chandel;Neeraj Varshney;Ankit Kumar","doi":"10.26599/BDMA.2022.9020033","DOIUrl":null,"url":null,"abstract":"The objective of this paper is to provide a better rendition of Generation Z purchase intentions of retail products through Facebook. The study gyrated around the favorable attitude formation of Generation Z translating into intentions to purchase retail products through Facebook. The role of antecedents of attitude, namely enjoyment, credibility, and peer communication was also explored. The main purpose was to analyze the F-commerce pervasiveness (retail purchases through Facebook) among Generation Z in India and how could it be materialized effectively. A conceptual façade was proposed after trotting out germane and urbane literature. The study focused exclusively on Generation Z population. The data were statistically analyzed using partial least squares structural equation modelling. The study found the proposed conceptual model had a high prediction power of Generation Z intentions to purchase retail products through Facebook verifying the materialization of F-commerce. Enjoyment, credibility, and peer communication were proved to be good predictors of attitude (R\n<sup>2</sup>\n=0.589) and furthermore attitude was found to be a stellar antecedent to purchase intentions (R\n<sup>2</sup>\n=0.540).","PeriodicalId":52355,"journal":{"name":"Big Data Mining and Analytics","volume":"6 4","pages":"491-503"},"PeriodicalIF":7.7000,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8254253/10233239/10233245.pdf","citationCount":"0","resultStr":"{\"title\":\"A PLS-SEM Based Approach: Analyzing Generation Z Purchase Intention Through Facebook's Big Data\",\"authors\":\"Vikas Kumar;Preeti;Shaiku Shahida Saheb;Sunil Kumari;Kanishka Pathak;Jai Kishan Chandel;Neeraj Varshney;Ankit Kumar\",\"doi\":\"10.26599/BDMA.2022.9020033\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The objective of this paper is to provide a better rendition of Generation Z purchase intentions of retail products through Facebook. The study gyrated around the favorable attitude formation of Generation Z translating into intentions to purchase retail products through Facebook. The role of antecedents of attitude, namely enjoyment, credibility, and peer communication was also explored. The main purpose was to analyze the F-commerce pervasiveness (retail purchases through Facebook) among Generation Z in India and how could it be materialized effectively. A conceptual façade was proposed after trotting out germane and urbane literature. The study focused exclusively on Generation Z population. The data were statistically analyzed using partial least squares structural equation modelling. The study found the proposed conceptual model had a high prediction power of Generation Z intentions to purchase retail products through Facebook verifying the materialization of F-commerce. Enjoyment, credibility, and peer communication were proved to be good predictors of attitude (R\\n<sup>2</sup>\\n=0.589) and furthermore attitude was found to be a stellar antecedent to purchase intentions (R\\n<sup>2</sup>\\n=0.540).\",\"PeriodicalId\":52355,\"journal\":{\"name\":\"Big Data Mining and Analytics\",\"volume\":\"6 4\",\"pages\":\"491-503\"},\"PeriodicalIF\":7.7000,\"publicationDate\":\"2023-08-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/iel7/8254253/10233239/10233245.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Big Data Mining and Analytics\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10233245/\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Big Data Mining and Analytics","FirstCategoryId":"1093","ListUrlMain":"https://ieeexplore.ieee.org/document/10233245/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
A PLS-SEM Based Approach: Analyzing Generation Z Purchase Intention Through Facebook's Big Data
The objective of this paper is to provide a better rendition of Generation Z purchase intentions of retail products through Facebook. The study gyrated around the favorable attitude formation of Generation Z translating into intentions to purchase retail products through Facebook. The role of antecedents of attitude, namely enjoyment, credibility, and peer communication was also explored. The main purpose was to analyze the F-commerce pervasiveness (retail purchases through Facebook) among Generation Z in India and how could it be materialized effectively. A conceptual façade was proposed after trotting out germane and urbane literature. The study focused exclusively on Generation Z population. The data were statistically analyzed using partial least squares structural equation modelling. The study found the proposed conceptual model had a high prediction power of Generation Z intentions to purchase retail products through Facebook verifying the materialization of F-commerce. Enjoyment, credibility, and peer communication were proved to be good predictors of attitude (R
2
=0.589) and furthermore attitude was found to be a stellar antecedent to purchase intentions (R
2
=0.540).
期刊介绍:
Big Data Mining and Analytics, a publication by Tsinghua University Press, presents groundbreaking research in the field of big data research and its applications. This comprehensive book delves into the exploration and analysis of vast amounts of data from diverse sources to uncover hidden patterns, correlations, insights, and knowledge.
Featuring the latest developments, research issues, and solutions, this book offers valuable insights into the world of big data. It provides a deep understanding of data mining techniques, data analytics, and their practical applications.
Big Data Mining and Analytics has gained significant recognition and is indexed and abstracted in esteemed platforms such as ESCI, EI, Scopus, DBLP Computer Science, Google Scholar, INSPEC, CSCD, DOAJ, CNKI, and more.
With its wealth of information and its ability to transform the way we perceive and utilize data, this book is a must-read for researchers, professionals, and anyone interested in the field of big data analytics.