Although it seems intuitive for firms to leverage social connections and interactions to influence consumers’ goal attainment and spending, the authors present a caveat of such strategies. Using two large-scale data sets with more than 5 million people-day observations from online gaming markets, Studies 1 and 2 show consistently nonlinear effects. Although some social connections and interactions boost goal attainment and spending (positive linear term), after a certain point too many of them have a diminished marginal effect (negative squared term). The results are robust to a wide array of modeling techniques addressing self-selection, unobserved individual heterogeneity, and endogeneity. In addition, novices can benefit more from greater social connections and interactions, yet also suffer more from the diminishing effects. Regarding the underlying mechanism, the follow-up experiment Study 3 shows that consistent with the information processing theory, some social connections and interactions can provide information support for goal attainment, but too many of them can introduce an information overload problem and, thus, hamper goal attainment intention. Together, these findings refute a simple, linear view of the effects of social connections and interactions and provide pivotal theoretical and practical implications.
AlbaJoseph W., and Wesley HutchinsonJ. (1987), “Dimensions of Consumer Expertise,”Journal of Consumer Research, 13(4), 411–54.
3.
AndrewsMichelle, LuoXueming, FangZheng, and GhoseAnindya (2016), “Mobile Ad Effectiveness: Hyper-Contextual Targeting with Crowdedness,”Marketing Science, 35(2), 218–33.
4.
AralSinan, and WalkerDylan (2011), “Creating Social Contagion through Viral Product Design: A Randomized Trial of Peer Influence in Networks,”Management Science, 57(9), 1623–39.
5.
ArgoJennifer J., DahlDarren W., and ManchandaRajesh V. (2005), “The Influence of a Mere Social Presence in a Retail Context,”Journal of Consumer Research, 32(2), 207–12.
6.
AustinPeter C. (2011), “An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies,”Multivariate Behavioral Research, 46(3), 399–424.
7.
BainbridgeWilliam S. (2007), “The Scientific Research Potential of Virtual Worlds,”Science, 317(5837), 472–76.
8.
BakerAndy, AmesBarry, and RennoLucio R. (2006), “Social Context and Campaign Volatility in New Democracies: Networks and Neighborhoods in Brazil's 2002 Elections,”American Journal of Political Science, 50(2), 382–99.
9.
BanduraAlbert (1988), “Perceived Self-Efficacy: Exercise of Control Through Self-Belief,”Annual Series of European Research in Behavior Therapy, 2, 27–59.
10.
BanduraAlbert, and LockeEdwin A. (2003), “Negative Self-Efficacy and Goal Effects Revisited,”Journal of Applied Psychology, 88(1), 87–99.
11.
BartoliniStefano, BilanciniEnnio, and PugnoMaurizio (2013), “Did the Decline in Social Connections Depress Americans’ Happiness?”Social Indicators Research, 110(3), 1033–59.
12.
BettmanJames R. (1979), Information Processing Theory of Consumer Choice.Boston: Addison Wesley.
13.
BondRobert M., FarissChristopher J., JonesJason J., KramerAdam D., MarlowCameron, SettleJaime E. (2012), “A 61-Million-Person Experiment in Social Interactions and Political Mobilization,”Nature, 489(7415), 295–98.
14.
BorboraZoheb, SrivastavaJaideep, HsuKuo W., and WilliamsDmitri (2011), “Churn Prediction in MMORPGs Using Player Motivation Theories and Ensemble Approach,”2011 IEEE Third International Conference on Social Computing (SocialCom), 157–64.
15.
BrightLaura F., KleiserSusan B., and GrauStacy L. (2015), “Too Much Facebook? An Exploratory Examination of Social Media Fatigue,”Computers in Human Behavior, 44(March), 148–55.
16.
BucklinRandolph E., and SismeiroCatarina (2003), “A Model of Web Site Browsing Behavior Estimated on Clickstream Data,”Journal of Marketing Research, 40(3), 249–67.
17.
BurgerJerry M., SorokaShelley, GonzagoKatrina, MurphyEmily, and SomerwellEmily (2001), “The Effect of Fleeting Attraction on Compliance Request,”Personality and Social Psychology Bulletin, 27(12), 1578–86.
18.
BurnkrantRobert E., and CousineauAlain (1975), “Informational and Normative Social Interactions in Buyer Behavior,”Journal of Consumer Research, 2 (3), 206–15.
19.
BurtRonald S. (1992), Structural Holes.Cambridge, MA: Harvard University Press.
20.
CacioppoJohn T., and PatrickWilliam (2008), Loneliness: Human Nature and the Need for Social Connection.New York: W.W. Norton.
21.
CapizziMichael T., and FergusonRick (2005), “Loyalty Trends for the Twenty-First Century,”Journal of Consumer Marketing, 22(2), 72–80.
22.
ChamberlainGary (1982), “Multivariate Regression Models for Panel Data,”Journal of Econometrics, 18(1), 5–46.
23.
ChanTat Y., LiJia, and PierceLamar (2014), “Learning from Peers: Knowledge Transfer and Sales Force Productivity Growth,”Marketing Science, 33(4), 463–84.
24.
ChappellDarren, EatoughVirginia, DaviesMark N., and GriffithsMark (2006), “‘EverQuest'—It's Just a Computer Game Right? An Interpretative Phenomenological Analysis of Online Gaming Addiction,”International Journal of Mental Health and Addiction, 4(3), 205–16.
25.
DolinskiDariusz, NawratMagdalena, and RudakIzabela (2001), “Dialogue Involvement as a Social interactions Technique,”Personality and Social Psychology Bulletin, 27(11), 1395–406.
26.
DyManuel B.Jr. (1994), Contemporary Social Philosophy.Quezon City, Philippines: JMC Press.
EpplerMartin J., and MengisJeanne (2004), “The Concept of Information Overload: A Review of Literature from Organization Science, Accounting, Marketing, MIS, and Related Disciplines,”Information Society, 20(5), 325–44.
29.
FalkArmin, FischbacherUrs, and GächterSimon (2013), “Living in Two Neighborhoods – Social Interaction Effects in the Laboratory,”Economic Inquiry, 51(1), 563–78.
30.
FeigenbergBenjamin, FieldErica, and PandeRohini (2013), “The Economic Returns to Social Interaction: Experimental Evidence from Microfinance,”Review of Economic Studies, 80(4), 1459–83.
31.
FinkelsteinStacy R., and FishbachAyelet (2012), “Tell Me What I Did Wrong: Experts Seek and Respond to Negative Feedback,”Journal of Consumer Research, 39(1), 22–38.
32.
FreemanLinton C., Kimball RomneyA., and FreemanSue C. (1987), “Cognitive Structure and Informant Accuracy,”American Anthropologist, 89, 310–25.
33.
FunderDavid C., and ColvinRandall C. (1988), “Friends and Strangers: Acquaintanceship, Agreement, and the Accuracy of Personality Judgment,”Journal of Personality and Social Psychology, 55(1), 149–58.
GrantAdam M. (2003), “The Impact of Life Coaching on Goal Attainment, Metacognition and Mental Health,”Social Behavior & Personality An International Journal, 31(3), 253–63.
37.
GrantAdam M., and SchwartzBarry (2011), “Too Much of a Good Thing: The Challenge and Opportunity of the Inverted-U,”Perspectives on Psychological Science, 6(1), 61–76.
HallMarshall (1976), The Theory of Groups.Providence, RI: American Mathematical Society.
40.
HeckmanJames J. (1979), “Sample Selection Bias as a Specification Error,”Econometrica, 47(1), 153–61.
41.
HoD., ImaiK., KingG., and StuartE. (2011), “MatchIt: Non-parametric Preprocessing for Parametric Causal Inference,”Journal of Statistical Software, 42(8), 1–28.
42.
HoViolet T., and LevesqueLaurie L. (2005), “With a Little Help from My Friends (and Substitutes): Social Referents and Influence in Psychological Contract Fulfillment,”Organization Science, 16(3), 275–89.
43.
HofackerCharles F., de RuyterKo, LurieNicholas H., ManchandaPuneet, and DonaldsonJeff (2016), “Gamification and Mobile Marketing Effectiveness,”Journal of Interactive Marketing, 34(May), 25–36.
44.
HsuChin L., and LinJudy C. (2008), “Acceptance of Blog Usage: The Roles of Technology Acceptance, Social Influence and Knowledge Sharing Motivation,”Information & Management, 45(1), 65–74.
45.
HsuChin L., and LuHsi P. (2007), “Consumer Behavior in Online Game Community: A Motivational Factor Perspective,”Computers in Human Behavior, 23(3), 1642–59.
46.
ImbensGuido W., and LemieuxThomas (2008), “Regression Discontinuity Designs: A Guide to Practice,”Journal of Econometrics, 142(2), 615–35.
47.
JettenJolanda, HaslamCatherine, HaslamAlexander S., DingleGenevieve, and JonesJanelle M. (2014), “How Groups Affect Our Health and Wellbeing: The Path from Theory to Policy,”Social Issues and Policy Review, 8(1), 103–30.
48.
JoffeMarshall M., and RosenbaumPaul R. (1999), “Invited Commentary: Propensity Scores,”American Journal of Epidemiology, 150(4), 327–33.
49.
KarlanDean S. (2007), “Social Connections and Group Banking,”Economic Journal, 117(517), 52–84.
50.
KelmanHerbert C. (2006), “Interests, Relationships, Identities: Three Central Issues for Individuals and Groups in Negotiating Their Social Environment,”Annual Review of Psychology, 57, 1–26.
51.
KimKihyun H., and KumarV. (2017), “The Relative Influence of Economic and Relational Direct Marketing Communications on Buying Behavior in B2B Markets,”Journal of Marketing Research (published electronically March 20), DOI: 10.1509/jmr.16.0283
52.
KooMinjung, and FishbachAyelet (2012), “The Small-Area Hypothesis: Effects of Progress Monitoring on Goal Adherence,”Journal of Consumer Research, 39(3), 493–509.
53.
KumarV., SriramS., LuoAnita, and ChintaguntaPradeep K. (2011), “Assessing the Effect of Marketing Investments in a Business Marketing Context,”Marketing Science, 30(5), 924–40.
54.
KurtDidem, InmanJeffrey J., and ArgoJennifer J. (2011), “The Influence of Friends on Consumer Spending: The Role of Agency–Communion Orientation and Self-Monitoring,”Journal of Marketing Research, 48(4), 741–54.
55.
LeeMatthew K., ShiNa, CheungChristy M., LimKai H., and SiaChoon L. (2011), “Consumer's Decision to Shop Online: The Moderating Role of Positive Informational Social Influence,”Information & Management, 48(6), 185–91.
56.
LiChenxi, LuoXueming, ZhangCheng, and WangXiaoyi (2017), “Sunny, Rainy, and Cloudy with a Chance of Mobile Promotion Effectiveness,”Marketing Science (published electronically June 20), DOI: 10.1287/mksc.2017.1044.
57.
LinMingfeng, LucasHenry C., and ShmueliGalit (2013), “Too Big to Fail: Large Samples and the p-Value Problem,”Information Systems Research, 24(4), 906–17.
58.
LordKenneth R., LeeMyung-Soo, and ChoongPeggy (2001), “Differences in Normative and Informational Social Interactions,”Advances in Consumer Research, Vol. 28, GillyMary C., and Meyers-LevyJoan, eds. Valdosta, GA: Association for Consumer Research, 280–85.
59.
LordKenneth R., and PutrevuSanjay (1993), “Advertising and Publicity: An Information Processing Perspective,”Journal of Economic Psychology, 14(1), 57–84.
60.
LuoXueming (2005), “How Does Shopping with Others Influence Impulsive Purchasing?”Journal of Consumer Psychology, 15(4), 288–94.
61.
LuoXueming (2007), “Consumer Negative Voice and Firm-Idiosyncratic Stock Returns,”Journal of Marketing, 71(3), 75–88.
LuoXueming, AndrewsMichelle, SongYiping, and AsparaJaakko (2014), “Group-Buying Deal Popularity,”Journal of Marketing, 78(2), 20–33.
64.
MacoursKaren, and VakisRenos (2014), “Changing Households’ Investment Behaviour Through Social Interactions with Local Leaders: Evidence from a Randomised Transfer Programme,”Economic Journal, 576(124), 607–33.
65.
MaierChristian, LaumerSven, EckhardtAndreas, and WeitzelTim (2015), “Giving Too Much Social Support: Social Overload on Social Networking Sites,”European Journal of Information Systems, 24(5), 447–64.
66.
ManchandaPuneet, PackardGrant, and PattabhiramaiahAdithya (2015), “Social Dollars: The Economic Impact of Customer Participation in a Firm-Sponsored Online Customer Community,”Marketing Science, 34(3), 367–87.
MillerGeorge A., GalanterEugence, and PribramKarl H. (1960), Plans and the Structure of Behavior.New York: Holt, Rinehart & Winston.
69.
MoitalMiguel (2006), “An Evaluation of the Factors Influencing the Adoption of Ecommerce in the Purchasing of Leisure Travel by the Residents of Cascais,” doctoral thesis, Bournemouth University.
MundlakYair (1978), “On the Pooling of Time Series and Cross Section Data,”Econometrica, 46(1), 69–85.
72.
NewellAllen, and SimonHerbert A. (1972), Human Problem Solving.Englewood Cliffs, NJ: Prentice Hall.
73.
OnnelaJukka P., and Reed-TsochasFelix (2010), “The Spontaneous Emergence of Social Influence in Online Systems,”Proceedings of the National Academy of Sciences of the United States of America, 107(43), 18375–80.
74.
PriceLinda L., and ArnouldEric J. (1999), “Commercial Friendships: Service Provider-Client Relationships in Context,”Journal of Marketing, 63(4), 38–56.
75.
RanaweeraChatura, and JayawardhenaChanaka (2014), “Talk Up or Criticize? Customer Responses to WOM About Competitors During Social Interactions,”Journal of Business Research, 67(2), 2645–56.
76.
RatnerRebecca (2013), “Consumer Goal Pursuit,”Journal of Consumer Research, 40(2), vi–viii.
77.
RaudenbushStephen W., and BrykAnthony S. (2002), Hierarchical Linear Models: Applications and Data Analysis Methods, 2nd ed.Thousand Oaks, CA: Sage Publications.
78.
ReisbergBarry, FranssenEmile H., SourenLiduin E.M., AuerStefanie R., AkramImran, and KenowskySunnie (2002), “Evidence and Mechanisms of Retrogenesis in Alzheimer's and other Dementias: Management and Treatment Import,”American Journal of Alzheimer's Disease and Other Dementias, 17(4), 202–12.
79.
RosenbaumPaul R., and RubinDonald B. (1983), “The Central Role of the Propensity Score in Observational Studies for Causal Effects,”Biometrika, 70(1), 41–55.
80.
RubinDonald B., and WatermanRichard P. (2006), “Estimating the Causal Effects of Marketing Interventions Using Propensity Score Methodology,”Statistical Science, 21(2), 206–22.
81.
ShimKyong J., PathakNishith, AhmadMuhammad A., DeLongColin, BorboraZoheb, MahapatraAmogh (2011), “Analyzing Human Behavior from Multiplayer Online Game Logs: A Knowledge Discovery Approach,”IEEE Intelligent Systems, 26(1), 85–89.
StinsonLinda, and IckesWilliam (1992), “Empathic Accuracy in the Interactions of Male Friends and Male Strangers,”Journal of Personality and Social Psychology, 62(5), 787–97.
84.
StuartElizabeth A. (2010), “Matching Methods for Causal Inference: A Review and a Look Forward,”Statistical Science, 25(1), 1–21.
85.
SunYacheng, DongXiaojing, and McIntyreShelby (2017), “Motivation of User-Generated Content: Social Connectedness Moderates the Effects of Monetary Rewards,”Marketing Science, 36(3), 329–37.
86.
SykesTracy A., VenkateshViswanath, and GosainSanjay (2009), “Model of Acceptance with Peer Support: A Social Network Perspective to Understand Employees’ System Use,”Management Information Systems Quarterly, 33(2), 371–93.
87.
TaylorT.L. (2003), “Multiple Pleasures Women and Online Gaming,”Convergence, 9 (1), 21–46.
88.
ThompsonDebora V., HamiltonRebecca W., and RustRoland T. (2005), “Feature Fatigue: When Product Capabilities Become Too Much of a Good Thing,”Journal of Marketing Research, 42(6), 431–42.
89.
UrbanyJoel E., DicksonPeter R., and WilkieWilliam L. (1989), “Buyer Uncertainty and Information Search,”Journal of Consumer Research, 16(2), 208–15.
90.
VenkateshViswanath (2000), “Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model,”Information Systems Research, 11(4), 342–65.
91.
VerbekeGeert, and MolenberghsGeert (2000), Linear Mixed Models for Longitudinal Data.New York: Springer.
92.
WeinerBernard (1995), Judgments of Responsibility: A Foundation for a Theory of Social Conduct.New York: Guilford Press.
93.
WeinerBernard (2000), “Attributional Thoughts About Consumer Behavior,”Journal of Consumer Research, 27(3), 382–87.
YeeNick (2006), “Motivations for Play in Online Games,”Cyberpsychology & Behavior, 9(6), 772–75.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
