A Study of Net Involvement, Self-Efficacy, and Addiction

碩士 === 開南大學 === 資訊管理學系 === 103 === With the rise of tablet PC in recent years and after smartphones were launched, internet-based devices have not been limited to desktop computers already. People can surf the Internet using their phones or tablet PC at any time and any place. Due to this change, th...

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Bibliographic Details
Main Authors: Wen De Yu, 温得鈺
Other Authors: Hsu Chi I
Format: Others
Language:zh-TW
Published: 2015
Online Access:http://ndltd.ncl.edu.tw/handle/07743962470318821661
Description
Summary:碩士 === 開南大學 === 資訊管理學系 === 103 === With the rise of tablet PC in recent years and after smartphones were launched, internet-based devices have not been limited to desktop computers already. People can surf the Internet using their phones or tablet PC at any time and any place. Due to this change, this research aims at discussing the relationship between internet using motivations of people with different background variables and their actual internet using behaviors, and then discussing that internet using behaviors affect internet involvement, and involvement has positive effects on internet self-efficacy, or its negative effects can cause internet addiction. It collects literature of related fields regarding the five constructs, i.e. internet using motivation, internet using behavior, internet involvement, internet self-efficacy and internet addiction and conducts a questionnaire survey. There are 263 respondents and the number of valid questionnaires is 230. The number of male and female respondents is 128 and 102 respectively and their age is between 19~35; undergraduates, graduate students and social beings are included. The statistical analysis methods it uses are descriptive statistics analysis, validity and reliability analysis, Pearson correlation analysis, regression analysis and analysis of variance (ANOVA). The results of ANOVA show in internet addiction, men outnumber women, and in self-efficacy, graduate students are superior to undergraduates. The results of correlation analysis show a positive moderate or high correlation between internet using motivation, internet using behavior, internet involvement, internet self-efficacy and internet addiction, but there is a low correlation between internet self-efficacy and internet addiction. The results of regression analysis show “Social Motivation”, “Instrumental Motivation” and “Entertainment Motivation” in Internet Using Motivation all have positive effects on internet using behaviors. “Information Learning”, “Leisure and Recreation” and “Communication and Making Friends” in Internet Using Behavior all have positive effects on internet involvement. Internet involvement has positive effects on “General Self-Efficacy”, “Self-Efficacy for Communication” and “Self-Efficacy for Internet Learning” in Internet Self-Efficacy. Internet involvement has positive effects on “compulsive internet use”, “Withdrawal from Internet Addiction”, “Tolerance of Internet Addiction”, “Time Management” and “Healthy Relationship Management” in Internet Addiction. This shows the overall regression model above is statistically significant.