Why people use social networking sites: An empirical study integrating network externalities and motivation theory
TL;DR: It is shown that enjoyment is the most influential factor in people's continued use of SNS, followed by number of peers, and usefulness, and the findings suggest that gender difference also produces different influences.
About: This article is published in Computers in Human Behavior.The article was published on 2011-05-01. It has received 1472 citations till now. The article focuses on the topics: Social network & Personal network.
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01 Sep 2016
TL;DR: Information and communications technologies ICTs have enabled the rise of so-called "Collaborative Consumption" CC: the peer-to-peer-based activity of obtaining, giving, or sharing the access to go...
Abstract: Information and communications technologies ICTs have enabled the rise of so-called "Collaborative Consumption" CC: the peer-to-peer-based activity of obtaining, giving, or sharing the access to goods and services, coordinated through community-based online services. CC has been expected to alleviate societal problems such as hyper-consumption, pollution, and poverty by lowering the cost of economic coordination within communities. However, beyond anecdotal evidence, there is a dearth of understanding why people participate in CC. Therefore, in this article we investigate people's motivations to participate in CC. The study employs survey data N=168 gathered from people registered onto a CC site. The results show that participation in CC is motivated by many factors such as its sustainability, enjoyment of the activity as well as economic gains. An interesting detail in the result is that sustainability is not directly associated with participation unless it is at the same time also associated with positive attitudes towards CC. This suggests that sustainability might only be an important factor for those people for whom ecological consumption is important. Furthermore, the results suggest that in CC an attitude-behavior gap might exist; people perceive the activity positively and say good things about it, but this good attitude does not necessary translate into action.
2,051 citations
TL;DR: In this article, the authors analyzed 355 brand posts from 11 international brands spread across six product categories and found that vivid and interactive brand post characteristics enhance the number of likes and positive comments on a brand post.
1,621 citations
TL;DR: The results show that participation in CC is motivated by many factors such as its sustainability, enjoyment of the activity as well as economic gains, and suggest that in CC an attitude‐behavior gap might exist; people perceive the activity positively and say good things about it, but this good attitude does not necessary translate into action.
Abstract: Information and communications technologies (ICTs) have enabled the rise of so-called “Collaborative Consumption” (CC): the peer-to-peer-based activity of obtaining, giving, or sharing the access to goods and services, coordinated through community-based online services. CC has been expected to alleviate societal problems such as hyper-consumption, pollution, and poverty by lowering the cost of economic coordination within communities. However, beyond anecdotal evidence, there is a dearth of understanding why people participate in CC. Therefore, in this article we investigate people’s motivations to participate in CC. The study employs survey data (N = 168) gathered from people registered onto a CC site. The results show that participation in CC is motivated by many factors such as its sustainability, enjoyment of the activity as well as economic gains. An interesting detail in the result is that sustainability is not directly associated with participation unless it is at the same time also associated with positive attitudes towards CC. This suggests that sustainability might only be an important factor for those people for whom ecological consumption is important. Furthermore, the results suggest that in CC an attitudebehavior gap might exist; people perceive the activity positively and say good things about it, but this good attitude does not necessary translate into action.
1,496 citations
Cites background from "Why people use social networking si..."
...Instead, the development is led by social dynamics, such as enjoyment and self-marketing of a community (Lin and Lu, 2011; Wasko & Faraj, 2000)....
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...A study on the continued use of social networking services established that enjoyment is a primary factor, followed by the number of peers and usefulness (Lin & Lu, 2011)....
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TL;DR: The results of an empirical analysis based on a sample of 371 s-commerce users indicate that all the characteristics of s-commerce had significant effects on trust and that trust hadsignificant effects on purchase and WOM intentions.
725 citations
TL;DR: The results indicate that perceived enjoyment and usefulness of the gamification decline with use, suggesting that users might experience novelty effects from the service.
634 citations
References
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TL;DR: In this paper, the statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined, and a drawback of the commonly applied chi square test, in additit...
Abstract: The statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined. A drawback of the commonly applied chi square test, in addit...
56,555 citations
"Why people use social networking si..." refers background or methods in this paper
...In discriminant validity, as Fornell and Larcker (1981) suggested, the AVE of construct should exceed other correlation coefficients of the construct....
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...…the three standards recommended by Bagozzi and Yi (1988) to assess the measuring model: (1) all indicator factor loadings should exceed 0.5 (Hair et al., 1998); (2) CR should be above 0.7; and (3) the average variance extracted, AVE, of every construct should exceed 0.5 (Fornell & Larcker, 1981)....
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...Every CR scored above 0.8, which exceeded 0.7 suggested for CRs by Fornell and Larcker (1981), indicating good reliability and stability for the measurement items of each construct....
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01 Jan 1989
TL;DR: Regression analyses suggest that perceived ease of use may actually be a causal antecdent to perceived usefulness, as opposed to a parallel, direct determinant of system usage.
40,975 citations
"Why people use social networking si..." refers background or methods in this paper
...Davis (1989) defined usefulness as ‘‘the degree to which a person believes that using a particular system would enhance his or her job performance,’’ when the individual feels a system is useful, he or she thinks positively about it....
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...The scale for usefulness was adapted from Davis (1989) and Kwon and Wen (2010)....
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TL;DR: In this article, the authors developed and validated new scales for two specific variables, perceived usefulness and perceived ease of use, which are hypothesized to be fundamental determinants of user acceptance.
Abstract: Valid measurement scales for predicting user acceptance of computers are in short supply. Most subjective measures used in practice are unvalidated, and their relationship to system usage is unknown. The present research develops and validates new scales for two specific variables, perceived usefulness and perceived ease of use, which are hypothesized to be fundamental determinants of user acceptance. Definitions of these two variables were used to develop scale items that were pretested for content validity and then tested for reliability and construct validity in two studies involving a total of 152 users and four application programs. The measures were refined and streamlined, resulting in two six-item scales with reliabilities of .98 for usefulness and .94 for ease of use. The scales exhibited hgih convergent, discriminant, and factorial validity. Perceived usefulness was significnatly correlated with both self-reported current usage r = .63, Study 1) and self-predicted future usage r = .85, Study 2). Perceived ease of use was also significantly correlated with current usage r = .45, Study 1) and future usage r = .59, Study 2). In both studies, usefulness had a signficnatly greater correaltion with usage behavior than did ease of use. Regression analyses suggest that perceived ease of use may actually be a causal antecdent to perceived usefulness, as opposed to a parallel, direct determinant of system usage. Implications are drawn for future research on user acceptance.
40,720 citations
01 Jan 1973
TL;DR: In this paper, a six-step framework for organizing and discussing multivariate data analysis techniques with flowcharts for each is presented, focusing on the use of each technique, rather than its mathematical derivation.
Abstract: Offers an applications-oriented approach to multivariate data analysis, focusing on the use of each technique, rather than its mathematical derivation. The text introduces a six-step framework for organizing and discussing techniques with flowcharts for each.
Well-suited for the non-statistician, this applications-oriented introduction to multivariate analysis focuses on the fundamental concepts that affect the use of specific techniques rather than the mathematical derivation of the technique. Provides an overview of several techniques and approaches that are available to analysts today - e.g., data warehousing and data mining, neural networks and resampling/bootstrapping. Chapters are organized to provide a practical, logical progression of the phases of analysis and to group similar types of techniques applicable to most situations.
Table of Contents
1. Introduction.
I. PREPARING FOR A MULTIVARIATE ANALYSIS.
2. Examining Your Data.
3. Factor Analysis.
II. DEPENDENCE TECHNIQUES.
4. Multiple Regression.
5. Multiple Discriminant Analysis and Logistic Regression.
6. Multivariate Analysis of Variance.
7. Conjoint Analysis.
8. Canonical Correlation Analysis.
III. INTERDEPENDENCE TECHNIQUES.
9. Cluster Analysis.
10. Multidimensional Scaling.
IV. ADVANCED AND EMERGING TECHNIQUES.
11. Structural Equation Modeling.
12. Emerging Techniques in Multivariate Analysis.
Appendix A: Applications of Multivariate Data Analysis.
Index.
37,124 citations
TL;DR: In this paper, the authors provide guidance for substantive researchers on the use of structural equation modeling in practice for theory testing and development, and present a comprehensive, two-step modeling approach that employs a series of nested models and sequential chi-square difference tests.
Abstract: In this article, we provide guidance for substantive researchers on the use of structural equation modeling in practice for theory testing and development. We present a comprehensive, two-step modeling approach that employs a series of nested models and sequential chi-square difference tests. We discuss the comparative advantages of this approach over a one-step approach. Considerations in specification, assessment of fit, and respecification of measurement models using confirmatory factor analysis are reviewed. As background to the two-step approach, the distinction between exploratory and confirmatory analysis, the distinction between complementary approaches for theory testing versus predictive application, and some developments in estimation methods also are discussed.
34,720 citations
"Why people use social networking si..." refers methods in this paper
...Data analysis followed the two-step approach by Anderson and Gerbing (1988), to test convergent validity and discriminant validity of the measurement model, followed by testing the research hypotheses and structural model framework....
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