article

Social Networking Services and Social Trust in Social Commerce: : A PLS-SEM Approach

Author:

Osama SohaibAuthors Info & Claims

Journal of Global Information Management (JGIM), Volume 29, Issue 2

Pages 23 - 44

https://doi.org/10.4018/JGIM.2021030102

Published: 01 March 2021 Publication History

Abstract

This study researches the mediating consequence of social trust (identification-based trust and information-based trust) on the relationship between social networking services (SNS) use and social commerce intention. The study also explores whether and how gender differences impact the use of SNS on endogenous constructs. The proposed research model is empirically examined using a sample of 170 consumers who have had a prior online shopping experience. The statistical analysis employs partial least squares structural equation modelling (PLS-SEM) methods such as PLS algorithm, model assessments, PLS predict, PLS goodness-of-fit, invariance assessment and multi-group analysis, and importance-performance map analysis. The study provides empirical insights into the effects of SNS on social trust towards s-commerce intention. Also, men and woman consumers are found to exhibit different emphases in using SNS to trust the s-commerce.

References

[1]

Bandura, A. (2002). Social Cognitive Theory in Cultural Context . Applied Psychology, 51(2), 269–290.

[2]

Bandura, A. (2004). Social Cognitive Thoery for Personal and Social Change by Enabling Media. Entertainment-education and social change: History, research, and practice, 75-95.

[3]

Chen, J., & Shen, X.-L. (2015). Consumers’ decisions in social commerce context: An empirical investigation . Decision Support Systems, 79, 55–64.

Digital Library

[4]

Chen, J., Xu, H., & Whinston, A. B. (2011). Moderated Online Communities and Quality of User-Generated Content . Journal of Management Information Systems, 28(2), 237–268.

Digital Library

[5]

ChengX.ChengX.FuS.BianY.YanX. (2017). Investigating the Relationship among Characteristics of Social Commerce, Consumers’ Trust and Trust Performance. Proceedings of the 50th Hawaii International Conference on System Sciences, 1182-1191. 10.24251/HICSS.2017.140

[6]

ChinW. (2003). A permutation procedure for multi-group comparison of PLS models. Proceedings of the PLS’03 International Symposium, 33-43.

[7]

Chin, W. W., & Dibbern, J. (2010). An Introduction to a Permutation Based Procedure for Multi-Group PLS Analysis: Results of Tests of Differences on Simulated Data and a Cross Cultural Analysis of the Sourcing of Information System Services Between Germany and the USA. In Handbook of Partial Least Squares: Concepts, Methods and Applications. Springer.

[8]

Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a monte carlo simulation study and an electronic-mail emotion/adoption study . Information Systems Research, 14(2), 189–217.

Digital Library

[9]

Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error . JMR, Journal of Marketing Research, 18(1), 39–50.

[10]

Füller, J., Mühlbacher, H., Matzler, K., & Jawecki, G. (2009). Consumer Empowerment Through Internet-Based Co-creation . Journal of Management Information Systems, 26(3), 71–102.

Digital Library

[11]

Gefen, D., & Straub, D. W. (2004). Consumer trust in B2C e-Commerce and the importance of social presence: Experiments in e-Products and e-Services . Omega, 32(6), 407–424.

[12]

Grabner-Kräuter, S. (2009). Web 2.0 Social Networks: The Role of Trust . Journal of Business Ethics, 90(4), 505–522.

[13]

Gu, B., Park, J., & Konana, P. (2012). Research note—the impact of external word-of- mouth sources on retailer sales of high-involvement products. Information System Research, 23(1), 182–196.

Digital Library

[14]

Ha, H.-Y., John, J., & Chung, Y.-K. (2016). Temporal effects of information from social networks on online behavior . Internet Research, 26(1), 213–235.

[15]

Haenlein, M., & Kaplan, A. M. (2004). A Beginner’s Guide to Partial Least Squares Analysis . Understanding Statistics, 3(4), 283–297.

[16]

Hair, F., Marko, J. S., Lucas, H., & Volker, G. K. (2014). Partial least squares structural equation modeling (PLS-SEM) An emerging tool in business research . European Business Review, 26(2), 106–121.

[17]

Hair, J. F.Jr, Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: Updated guidelines on which method to use . International Journal of Multivariate Data Analysis, 1(2), 107–123.

[18]

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a Silver Bullet. Journal of Marketing Theory and Practice, 19(2), 139-151.

[19]

Hajli, M. (2013). A research framework for social commerce adoption . Information Management & Computer Security, 21(3), 144–154.

[20]

HajliM.HajliM.KhaniF. (2013). Establishing trust in social commerce through social word of mouth. 7th International Conference on e-Commerce in Developing Countries:with focus on e-Security, 1-22. 10.1109/ECDC.2013.6556738

[21]

Hajli, N. (2015). Social commerce constructs and consumer’s intention to buy . International Journal of Information Management, 35(2), 183–191.

Digital Library

[22]

Hajli, N., & Lin, X. (2016). Exploring the Security of Information Sharing on Social Networking Sites: The Role of Perceived Control of Information . Journal of Business Ethics, 133(1), 111–123.

[23]

Hajli, N., Lin, X., Featherman, M. S. & Wang, Y. (2014). Social Word of Mouth: How Trust Develops in the Market. International Journal of Market Research, 56(5), 673–689.

[24]

Hajli, N., & Sims, J. (2015). Social commerce: The transfer of power from sellers to buyers . Technological Forecasting and Social Change, 94, 350–358.

[25]

Henseler, J. (2017). Bridging design and behavioral research with variance-based structural equation modeling . Journal of Advertising, 46(1), 178–192.

[26]

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling . Journal of the Academy of Marketing Science, 43(1), 115–135.

[27]

Henseler, J., Ringle, C. M., & Sarstedt, M. (2016). Testing Measurement Invariance of Composites Using Partial Least Squares. International Marketing Review, 33(3), 405–431.

[28]

Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing . New Challenges to International Marketing, 20, 277–319.

[29]

Henseler, J., & Sarstedt, M. (2013). Goodness-of-fit indices for partial least squares path modeling . Computational Statistics, 28(2), 565–580.

[30]

Hock, C., Ringle, C. & Sarstedt, M. (2010). Management of Multi-Purpose Stadiums: Importance and Performance Measurement of Service Interfaces. Academic Press.

[31]

Hsu, M.-H., Chang, C.-M., & Yen, C.-H. (2011). Exploring the antecedents of trust in virtual communities . Behaviour & Information Technology, 30(5), 587–601.

Digital Library

[32]

Hu, N., Bose, I., Koh, S. N., & Liu, L. (2012). Manipulation of online reviews: An analysis of ratings, readability, and sentiments . Decision Support Systems, 52(3), 674–684.

Digital Library

[33]

Huang, Z., & Benyoucef, M. (2013). From e-commerce to social commerce: A close look at design features . Electronic Commerce Research and Applications, 12(4), 246–259.

[34]

Indvik, L. (2013). The 7 Species of Social Commerce. Retrieved from: https://mashable.com/2013/05/10/social-commerce-definition/

[35]

Jones, K., & Leonard, L. N. K. (2008). Trust in consumer-to-consumer electronic commerce . Information & Management, 45(2), 88–95.

Digital Library

[36]

Jörg, H. (2016). Testing measurement invariance of composites using partial least squares . International Marketing Review, 33(3), 405–431.

[37]

Keil, M., Bernard, C. Y. T., Wei, K.-K., Saarinen, T., Tuunainen, V., & Wassenaar, A. (2000). A Cross-Cultural Study on Escalation of Commitment Behavior in Software Projects . Management Information Systems Quarterly, 24(2), 299–325.

Digital Library

[38]

Khang, H., Han, E.-K., & Ki, E.-J. (2014). Exploring influential social cognitive determinants of social media use . Computers in Human Behavior, 36, 48–55.

Digital Library

[39]

Kim, S., & Park, H. (2013). Effects of various characteristics of social commerce (s-commerce) on consumers’ trust and trust performance . International Journal of Information Management, 33(2), 318–332.

[40]

Kock, N. (2015). Common Method Bias in PLS-SEM: A Full Collinearity Assessment Approach . International Journal of e-Collaboration, 11(4), 1–10.

Digital Library

[41]

Lange, P. A. M. V. (2015). Generalized Trust . Current Directions in Psychological Science, 24(1), 71–76.

[42]

LaRose, R., & Eastin, M. S. (2004). A Social Cognitive Theory of Internet Uses and Gratifications: Toward a New Model of Media Attendance . Journal of Broadcasting & Electronic Media, 48(3), 358–377.

[43]

Lee, M. K. O., Shi, N., Cheung, C. M. K., Lim, K. H., & Sia, C. L. (2011). Consumer’s decision to shop online: The moderating role of positive informational social influence . Information & Management, 48(6), 185–191.

Digital Library

[44]

Li, F., & Du, T. C. (2011). Who is talking? An ontology-based opinion leader identification framework for word-of-mouth marketing in online social blogs . Decision Support Systems, 51(1), 190–197.

Digital Library

[45]

Liang, T.-P., Ho, Y.-T., Li, Y.-W., & Turban, E. (2011). What Drives Social Commerce: The Role of Social Support and Relationship Quality . International Journal of Electronic Commerce, 16(2), 69–90.

Digital Library

[46]

Liang, T.-P., & Turban, E. (2011). Introduction to the Special Issue Social Commerce: A Research Framework for Social Commerce . International Journal of Electronic Commerce, 16(2), 5–14.

Digital Library

[47]

Lu, B., Fan, W., & Zhou, M. (2016). Social presence, trust, and social commerce purchase intention: An empirical research . Computers in Human Behavior, 56, 225–237.

Digital Library

[48]

Lu, Y., Zhao, L., & Wang, B. (2010). From virtual community members to C2C e-commerce buyers: Trust in virtual communities and its effect on consumers’ purchase intention . Electronic Commerce Research and Applications, 9(4), 346–360.

Digital Library

[49]

McKnight, D. H., Carter, M., Thatcher, J. B., & Clay, P. F. (2011). Trust in a specific technology: An investigation of its components and measures . ACM Transactions on Management Information Systems, 2(2), 12.

[50]

McKnight, D. H., & Chervany, N. L. (2001). Trust and distrust definitions: One bite at a time. In Trust in Cyber-societies, 27–54.

[51]

McKnight, D. H., Choudhury, V., & Kacmar, C. (2000). Trust in e-commerce vendors: a two-stage model. ICIS 2000 Proceedings, 54.

[52]

McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-commerce: An integrative typology . Information Systems Research, 13(3), 334–359.

Digital Library

[53]

Ng, C. S.-P. (2013). Intention to purchase on social commerce websites across cultures: A cross-regional study . Information & Management, 50(8), 609–620.

Digital Library

[54]

Parasuraman, A., & Colby, C. L. (2015). An Updated and Streamlined Technology Readiness Index . Journal of Service Research, 18(1), 59–74.

[55]

Reinartz, W., Haenlein, M., & Henseler, J. (2009). An empirical comparison of the efficacy of covariance-based and variance-based SEM . International Journal of Research in Marketing, 26(4), 332–344.

[56]

Ringle, C. M., & Sarstedt, M. (2016). Gain more insight from your PLS-SEM results: The importance-performance map analysis . Industrial Management & Data Systems, 116(9), 1865–1886.

[57]

Ringle, C. M., Sarstedt, M., & Straub, D. W. (2012). Editor’s comments: A critical look at the use of PLS-SEM in MIS quarterly . Management Information Systems Quarterly, 36(1), iii–xiv.

[58]

Ringle, C. M., Wende, S., & Becker, J.-M. (2014). Smartpls 3. SmartPLS.

[59]

Rönkkö, M., & Evermann, J. (2013). A Critical Examination of Common Beliefs About Partial Least Squares Path Modeling . Organizational Research Methods, 16(3), 425–448.

[60]

Royo‐Vela, M., & Casamassima, P. (2011). The influence of belonging to virtual brand communities on consumers’ affective commitment, satisfaction and word‐of‐mouth advertising: The ZARA case . Online Information Review, 35(4), 517–542.

[61]

Sarstedt, M., & Hair, J. F. (2017). Partial least squares structural equation modeling. Handbook of Market Research, 1-40.

[62]

Sarstedt, M., Hair, J. F., Ringle, C. M., Thiele, K. O., & Gudergan, S. P. (2016). Estimation issues with PLS and CBSEM: Where the bias lies! Journal of Business Research, 69(10), 3998–4010.

[63]

Sarstedt, M., Henseler, J., & Ringle, C. M. (2011). Multigroup Analysis in Partial Least Squares (PLS) Path Modeling: Alternative Methods and Empirical Results. Measurement and Research Methods in International Marketing.

[64]

Shi, S., & Chow, W. S. (2015). Trust development and transfer in social commerce: Prior experience as moderator . Industrial Management & Data Systems, 115(7), 1182–1203.

[65]

Shin, D.-H. (2013). User experience in social commerce: In friends we trust . Behaviour & Information Technology, 32(1), 52–67.

[66]

Shmueli, G., Ray, S., Velasquez Estrada, J. M., & Chatla, S. B. (2016). The elephant in the room: Predictive performance of PLS models . Journal of Business Research, 69(10), 4552–4564.

[67]

SohaibO.KangK. (2015a). Individual Level Culture Effects on Multi-Perspective iTrust in B2C E-commerce. 26th Australasian Conference on Information Systems, 1-11.

[68]

Sohaib, O., & Kang, K. (2015b). Individual Level Culture Influence on Online Consumer iTrust Aspects Towards Purchase Intention Across Cultures: A S-O-R Model . International Journal of Electronic Business, 12(2), 142–161.

[69]

Te’eni, D. (2001). A Cognitive–Affective Model of Organizational Communication for Designing IT . Management Information Systems Quarterly, 25(2), 251–312.

[70]

Weisberg, J., Te’eni, D., & Arman, L. (2011). Past purchase and intention to purchase in e‐commerce: The mediation of social presence and trust . Internet Research, 21(1), 82–96.

[71]

Wood, R., & Bandura, A. (1989). Social Cognitive Theory of Organizational Management . Academy of Management Review, 14(3), 361–384.

[72]

Yadav, M. S., de Valck, K., Hennig-Thurau, T., Hoffman, D. L., & Spann, M. (2013). Social Commerce: A Contingency Framework for Assessing Marketing Potential . Journal of Interactive Marketing, 27(4), 311–323.

[73]

Zhang, H., Lu, Y., Gupta, S., & Zhao, L. (2014). What motivates customers to participate in social commerce? The impact of technological environments and virtual customer experiences . Information & Management, 51(8), 1017–1030.

Digital Library

[74]

Zhang, T., Agarwal, R., & Lucas, H. C. (2011). The value of IT-enabled retailer learning: Personalized product recommendations and customer store loyalty in electronic markets . Management Information Systems Quarterly, 35(4), 859–882.

Digital Library

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Social Networking Services and Social Trust in Social Commerce: A PLS-SEM Approach

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cover image Journal of Global Information Management

Journal of Global Information Management Volume 29, Issue 2

Mar 2021

221 pages

ISSN:1062-7375

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United States

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Published: 01 March 2021

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Peng LWang SJiang HWang KLi G(2024)Directive vs. Commissive Illocutionary Acts?Journal of Global Information Management10.4018/JGIM.34996132:1(1-24)Online publication date: 7-Aug-2024
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