Please wait a minute...
Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (4): 29-37    DOI: 10.11925/infotech.2096-3467.2017.1250
Orginal Article Current Issue | Archive | Adv Search |
The Influences of Technological Factors and Perceived Values on Continuance Intention of Social Commerce: An Empirical Study
Gan Chunmei1(), Huang Kai1, Xu Jiayi1, Lin Tiantian2
1School of Information Management, Sun Yat-Sen University, Guangzhou 510006, China
2Business School, Sun Yat-Sen University, Guangzhou 510006, China
Download: PDF (613 KB)   HTML ( 6
Export: BibTeX | EndNote (RIS)      
Abstract  

[Objective] This study aims to find the reasons of continuously using social commerce sites. [Methods] We developed a theoretical model for continuance intention to use social commerce sites based on the S-O-R model as well as the technology factors and perceived values. A total of 330 valid samples were collected via an online questionnaire, which were analyzed by PLS-SEM. [Results] We found that interactivity significantly affected perceived hedonic values, personalization significantly impacted perceived utilitarian values, sociability had a significant effect on perceived values, and recommendation significantly influenced perceived utilitarian and hedonic values. Meanwhile, perceived utilitarian and hedonic values significantly affected continuance intention to use social commerce sites. [Limitations] First, this study only focuses on the effects of beneficial values rather than the risks. Second, our data was collected from young users. Third, social commerce sites might lead to different browsing behaviors. [Conclusions] Technological factors and perceived values pose some effect to continuance intention to use social commerce sites. This study provides references and guidelines for related service providers.

Key wordsSocial Commerce      S-O-R Model      Perceived Values      Technological Factors      Continuance Intention     
Received: 11 December 2017      Published: 11 May 2018
ZTFLH:  G354  

Cite this article:

Gan Chunmei,Huang Kai,Xu Jiayi,Lin Tiantian. The Influences of Technological Factors and Perceived Values on Continuance Intention of Social Commerce: An Empirical Study. Data Analysis and Knowledge Discovery, 2018, 2(4): 29-37.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.1250     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2018/V2/I4/29

题项 频率 百分比(%)
性别 204 61.82
126 38.18
年龄 18以下 4 1.21
18-24 215 65.15
25-29 45 13.64
30-34 11 3.33
35-39 11 3.33
40及以上 44 13.33
使用时间 ≤1个月 10 3.03
1-3个月 11 3.33
3-6个月 9 2.73
6-12个月 21 6.36
12-24个月 45 13.64
≥24个月 234 70.91
使用频率 一周多次 224 67.88
一周一次 36 10.91
两周一次 21 6.36
一个月一次 30 9.09
三个月一次 3 0.91
三个月以上一次 16 4.85
变量 测度项 因子载荷 AVE CR Cronbach’s α
交互性(IA) IA1 0.890 0.745 0.897 0.828
IA2 0.884
IA3 0.813
个性化(PL) PL1 0.884 0.722 0.912 0.872
PL2 0.872
PL3 0.836
PL4 0.806
社交性(SC) SC1 0.804 0.753 0.924 0.890
SC2 0.915
SC3 0.878
SC4 0.871
推荐性(RC) RC1 0.915 0.795 0.921 0.871
RC2 0.881
RC3 0.879
功利性价值(PUV) PUV1 0.800 0.760 0.927 0.894
PUV2 0.894
PUV3 0.909
PUV4 0.880
享乐性价值(PHV) PHV1 0.906 0.854 0.946 0.914
PHV2 0.936
PHV3 0.930
社交性价值(PSV) PSV1 0.893 0.825 0.950 0.929
PSV2 0.917
PSV3 0.897
PSV4 0.925
持续意愿(CI) CI1 0.898 0.766 0.907 0.846
CI2 0.804
CI3 0.919
IA PL SC RC PUV PHV PSV CI
IA 0.863
PL 0.252 0.850
SC 0.463 0.487 0.868
RC 0.160 0.560 0.304 0.892
PUV 0.151 0.511 0.353 0.445 0.872
PHV 0.370 0.423 0.486 0.410 0.461 0.924
PSV 0.369 0.422 0.725 0.251 0.365 0.502 0.908
CI 0.306 0.357 0.317 0.394 0.462 0.666 0.297 0.875
[1] Liang T P, Turban E.Introduction to the Special Issue Social Commerce: A Research Framework for Social Commerce[J]. International Journal of Electronic Commerce, 2011, 16(2): 5-13.
doi: 10.2753/JEC1086-4415160201
[2] Busalim A H, Hussin A R C. Understanding Social Commerce: A Systematic Literature Review and Directions for Further Research[J]. International Journal of Information Management, 2016, 36(6): 1075-1088.
doi: 10.1016/j.ijinfomgt.2016.06.005
[3] Hajli N.Social Commerce Constructs and Consumer’s Intention to Buy[J]. International Journal of Information Management, 2015, 35(2): 183-191.
doi: 10.1016/j.ijinfomgt.2014.12.005
[4] Lin X, Li Y, Wang X.Social Commerce Research: Definition, Research Themes and the Trends[J]. International Journal of Information Management, 2017, 37(3): 190-201.
doi: 10.1016/j.ijinfomgt.2016.06.006
[5] Zhang H, Lu Y, Gupta S, et al.What Motivates Customers to Participate in Social Commerce? The Impact of Technological Environments and Virtual Customer Experiences[J]. Information & Management, 2014, 51(8): 1017-1030.
doi: 10.1016/j.im.2014.07.005
[6] Xiao B, Benbasat I.E-Commerce Product Recommendation Agents: Use, Characteristics, and Impact[J]. MIS Quarterly, 2007, 31(1): 137-209.
doi: 10.2307/25148784
[7] Bhattacherjee A.Understanding Information Systems Continuance: An Expectation-Confirmation Model[J]. MIS Quarterly, 2001, 25(3): 351-370.
doi: 10.2307/3250921
[8] Wang C, Zhang P.The Evolution of Social Commerce: The People, Business, Technology, and Information Dimensions[J]. Communications of the Association for Information Systems, 2012, 31(5):105-127.
[9] Hajli N, Shanmugam M, Powell P, et al.A Study on the Continuance Participation in On-Line Communities with Social Commerce Perspective[J]. Technological Forecasting & Social Change, 2015, 96:232-241.
doi: 10.1016/j.techfore.2015.03.014
[10] Chen H, Papazafeiropoulou A, Chen T K, et al.Exploring the Commercial Value of Social Networks: Enhancing Consumers’ Brand Experience Through Facebook Pages[J]. Journal of Enterprise Information Management, 2014, 27(5): 576-598.
doi: 10.1108/JEIM-05-2013-0019
[11] Zhang H, Lu Y, Gupta S, et al.Understanding Group-Buying Websites Continuance: An Extension of Expectation Confirmation Model[J]. Internet Research, 2015, 25(5): 767-793.
doi: 10.1108/IntR-05-2014-0127
[12] Pöyry E, Parvinen P, Malmivaara T.Can We Get from Liking to Buying? Behavioral Differences in Hedonic and Utilitarian Facebook Usage[J]. Electronic Commerce Research & Applications, 2013, 12(4): 224-235.
doi: 10.1016/j.elerap.2013.01.003
[13] Mehrabian A, Russell J A.An Approach to Environmental Psychology[M]. Cambridge: MIT, 1974: 38-39.
[14] Xiang L, Zheng X, Lee M K O, et al. Exploring Consumers’ Impulse Buying Behavior on Social Commerce Platform: The Role of Parasocial Interaction[J]. International Journal of Information Management, 2016, 36(3): 333-347.
doi: 10.1016/j.ijinfomgt.2015.11.002
[15] Liu H, Chu H, Huang Q, et al.Enhancing the Flow Experience of Consumers in China Through Interpersonal Interaction in Social Commerce[J]. Computers in Human Behavior, 2016, 58(C): 306-314.
doi: 10.1016/j.chb.2016.01.012
[16] Hu X, Huang Q, Zhong X, et al.The Influence of Peer Characteristics and Technical Features of a Social Shopping Website on a Consumer’s Purchase Intention[J]. International Journal of Information Management, 2016, 36(6): 1218-1230.
doi: 10.1016/j.ijinfomgt.2016.08.005
[17] Lin J, Yan Y, Chen S, et al.Understanding the Impact of Social Commerce Website Technical Features on Repurchase Intention: A Chinese Guanxi Perspective[J]. Journal of Electronic Commerce Research, 2017, 18(3): 225-244.
[18] Park M S, Shin J K, Ju Y.Social Networking Atmosphere and Online Retailing[J]. Journal of Global Scholars of Marketing Science, 2014, 24(1): 89-107.
doi: 10.1080/21639159.2013.867681
[19] Kim J B.The Mediating Role of Presence on Consumer Intention to Participate in a Social Commerce Site[J]. Journal of Internet Commerce, 2015, 14(4): 425-454.
doi: 10.1080/15332861.2015.1092067
[20] Rintamäki T, Kanto A, Kuusela H, et al.Decomposing the Value of Department Store Shopping into Utilitarian, Hedonic and Social Dimensions: Evidence from Finland[J]. International Journal of Retail & Distribution Management, 2006, 34(1): 6-24.
doi: 10.1108/09590550610642792
[21] Steuer J.Defining Virtual Reality: Dimensions Determining Telepresence[J]. Journal of Communication, 1992, 42(4): 73-93.
doi: 10.1111/j.1460-2466.1992.tb00812.x
[22] Komiak S Y X, Benbasat I. The Effects of Personalization and Familiarity on Trust and Adoption of Recommendation Agents[J]. MIS Quarterly, 2006, 30(4): 941-960.
doi: 10.1080/14639230600991726
[23] Preece J.Sociability and Usability in Online Communities: Determining and Measuring Success[J]. Behaviour & Information Technology, 2001, 20(5): 347-356.
[24] Hsiao K, Lin J C, Wang X, et al.Antecedents and Consequences of Trust in Online Product Recommendations[J]. Online Information Review, 2010, 34(6): 935-953.
doi: 10.1108/14684521011099414
[25] Zeithaml V A.Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence[J]. Journal of Marketing, 1988, 52(3): 2-22.
doi: 10.2307/1251446
[26] Overby J W, Lee E J.The Effects of Utilitarian and Hedonic Online Shopping Value on Consumer Preference and Intentions[J]. Journal of Business Research, 2006, 59(10): 1160-1166.
doi: 10.1016/j.jbusres.2006.03.008
[27] Hsu C L, Lin C C.Effect of Perceived Value and Social Influences on Mobile App Stickiness and In-App Purchase Intention[J]. Technological Forecasting & Social Change, 2016, 108: 42-53.
doi: 10.1016/j.techfore.2016.04.012
[28] Hoffman D L, Novak T P.Marketing in Hypermedia Computer-Mediated Environments: Conceptual Foundations[J]. Journal of Marketing, 1996, 60(3): 50-68.
doi: 10.2307/1251841
[29] Kleijnen M, Ruyter K D, Wetzels M.An Assessment of Value Creation in Mobile Service Delivery and the Moderating Role of Time Consciousness[J]. Journal of Retailing, 2007, 83(1): 33-46.
doi: 10.1016/j.jretai.2006.10.004
[30] Fiore A M, Jin H J, Kim J.For Fun and Profit: Hedonic Value from Image Interactivity and Responses Toward an Online Store[J]. Psychology & Marketing, 2005, 22(8): 669-694.
doi: 10.1002/mar.20079
[31] Animesh A, Pinsonneault A, Yang S B, et al.An Odyssey into Virtual Worlds: Exploring the Impacts of Technological and Spatial Environments on Intention to Purchase Virtual Products[J]. MIS Quarterly, 2011, 35(3): 789-810.
doi: 10.2307/23042809
[32] Babin B J, Darden W R, Griffin M.Work and/or Fun: Measuring Hedonic and Utilitarian Shopping Value[J]. Journal of Consumer Research, 1994, 20(4): 644-656.
doi: 10.1086/jcr.1994.20.issue-4
[33] Alpert S R, Karat J, Karat C M, et al.User Attitudes Regarding a User-Adaptive eCommerce Web Site[J]. User Modeling and User-Adapted Interaction, 2003, 13(4): 373-396.
doi: 10.1023/A:1026201108015
[34] Tam K Y, Ho S Y.Web Personalization as a Persuasion Strategy: An Elaboration Likelihood Model Perspective[J]. Information Systems Research, 2005, 16(3): 271-291.
doi: 10.1287/isre.1050.0058
[35] Benlian A.Web Personalization Cues and Their Differential Effects on User Assessments of Website Value[J]. Journal of Management Information Systems, 2015, 32(1): 225-260.
doi: 10.1080/07421222.2015.1029394
[36] Kim C, Li W, Kim D J.An Empirical Analysis of Factors Influencing M-Shopping Use[J]. International Journal of Human-Computer Interaction, 2015, 31(12): 974-994.
doi: 10.1080/10447318.2015.1085717
[37] Zhang C B, Li Y N, Wu B, et al.How WeChat Can Retain Users: Roles of Network Externalities, Social Interaction Ties, and Perceived Values in Building Continuance Intention[J]. Computers in Human Behavior, 2017, 69: 284-293.
doi: 10.1016/j.chb.2016.11.069
[38] Junglas I, Goel L, Abraham C, et al.The Social Component of Information Systems - How Sociability Contributes to Technology Acceptance[J]. Journal of the Association for Information Systems, 2013, 14(10): 585-616.
doi: 10.3233/AIS-130235
[39] Li D C.Online Social Network Acceptance: A Social Perspective[J]. Internet Research, 2011, 21(5): 562-580.
doi: 10.1108/10662241111176371
[40] Yeh N, Lin J C, Lu H.The Moderating Effect of Social Roles on User Behaviour in Virtual Worlds[J]. Online Information Review, 2011, 35(5): 747-769.
doi: 10.1108/14684521111176480
[41] Xu J J, Benbasat I, Cenfetelli R T.The Nature and Consequences of Trade-Off Transparency in the Context of Recommendation Agents[J]. MIS Quarterly, 2014, 38(2): 379-406.
doi: 10.25300/MISQ/2014/38.2.03
[42] Huang L T.Exploring Utilitarian and Hedonic Antecedents for Adopting Information from a Recommendation Agent and Unplanned Purchase Behaviour[J]. New Review of Hypermedia & Multimedia, 2016, 22(1-2): 139-165.
doi: 10.1080/13614568.2015.1052098
[43] Baier D, Stüber E.Acceptance of Recommendations to Buy in Online Retailing[J]. Journal of Retailing & Consumer Services, 2010, 17(3): 173-180.
doi: 10.1016/j.jretconser.2010.03.005
[44] Gu S, Kim H.What Drives Customers to Use Retailers’ Facebook Pages? Predicting Consumers’ Motivations and Continuance Usage Intention[J]. Journal of Global Fashion Marketing, 2016, 7(1): 1-14.
doi: 10.1080/20932685.2015.1105111
[45] Hew J J, Lee V H, Ooi K B, et al.Mobile Social Commerce: The Booster for Brand Loyalty?[J]. Computers in Human Behavior, 2016, 59: 142-154.
doi: 10.1016/j.chb.2016.01.027
[46] Song P, Phang C W.Promoting Continuance Through Shaping Members’ Social Identity in Knowledge-Based Versus Support/ Advocacy Virtual Communities[J]. IEEE Transactions on Engineering Management, 2016, 63(1): 16-26.
doi: 10.1109/TEM.2015.2488698
[47] Kumar N, Benbasat I.Research Note: The Influence of Recommendations and Consumer Reviews on Evaluations of Websites[J]. Information Systems Research, 2006, 17(4): 425-439.
doi: 10.1287/isre.1060.0107
[48] Kim B, Han I.What Drives the Adoption of Mobile Data Services? An Approach from a Value Perspective[J]. Journal of Information Technology, 2009, 24(1): 35-45.
doi: 10.1057/jit.2008.28
[49] Chin W W.The Partial Least Squares Approach for Structural Equation Modeling[J]. MIS Quarterly, 1998, 22(1): 7-16.
[50] Fornell C, Larcker D F.Evaluating Structural Equation Models with Unobservable Variables and Measurement Error[J]. Journal of Marketing Research, 1981, 18(1): 39-50.
doi: 10.2307/3151312
[51] Chiu C M, Wang E T G, Fang Y H, et al. Understanding Customers’ Repeat Purchase Intentions in B2C E-Commerce: The Roles of Utilitarian Value, Hedonic Value and Perceived Risk[J]. Information Systems Journal, 2014, 24(1): 85-114.
doi: 10.1111/j.1365-2575.2012.00407.x
[52] Gan C, Wang W.The Influence of Perceived Value on Purchase Intention in Social Commerce Context[J]. Internet Research, 2017, 27(4): 772-785.
doi: 10.1108/IntR-06-2016-0164
[1] Wei Wu, Xie Xingzheng. The Determinants of Continuance Intention to Pay: Empirical Research from Online Knowledge Payment Users[J]. 数据分析与知识发现, 2020, 4(8): 119-129.
[2] Zhang Min,Luo Meifen,Nie Rui,Zhang Yan. Analyzing Continuance Intention of Health APP Users Based on Information Ecology[J]. 数据分析与知识发现, 2017, 1(4): 46-56.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn