通过社交媒体网络积累社会资本:来自随机场实验和个人水平面板数据的证据

MIS Q. Pub Date : 2022-05-24 DOI:10.25300/misq/2022/16451
Michael Weiler, Simon Stolz, Andreas Lanz, Christian Schlereth, O. Hinz
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引用次数: 8

摘要

与工作相关的社交媒体网络(smn),如LinkedIn,引入了新的网络机会和功能,承诺帮助个人建立、扩展和维持社会资本(SC)。通常,与工作相关的短信只向高级用户提供高级网络功能,以鼓励基本用户成为付费会员。然而,对于这些高级网络功能是否会对SC积累产生因果影响,我们知之甚少。为了缩小这一研究差距,我们进行了一项随机现场实验,招募了215名自由职业者参加一个免费的、与工作相关的SMN。在这些被招募的参与者中,超过70人收到了一张随机分配的12个月免费高级会员券。我们观察到,个人并不一定会从他们访问高级网络功能的能力中积累更多的SC,因为接受治疗的自由职业者不会自动改变他们的在线网络参与。只有在个人积极主动地参与社交活动的情况下,这些功能才能充分发挥其效用。我们发现,使用高级网络功能的自由职业者在战略网络行为量表上每增加一个单位,他们的SC增加了4.609%。我们在另一项研究中证实了这一发现,该研究利用了第二个个人层面的面板数据集,涵盖了52,392名自由职业者。我们还研究了主动与被动特征在SC积累中的动态作用。基于这些发现,我们引入了“有目的的特征利用理论”:从本质上讲,个体不仅要拥有有效的“网络武器”——他们还需要“射击”它的意图。
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Social Capital Accumulation through Social Media Networks: Evidence from a Randomized Field Experiment and Individual-Level Panel Data
Work-related social media networks (SMNs) like LinkedIn introduce novel networking opportunities and features that promise to help individuals establish, extend, and maintain social capital (SC). Typically, work-related SMNs offer access to advanced networking features exclusively to premium users in order to encourage basic users to become paying members. Yet little is known about whether access to these advanced networking features has a causal impact on the accumulation of SC. To close this research gap, we conducted a randomized field experiment and recruited 215 freelancers in a freemium, work-related SMN. Of these recruited participants, more than 70 received a randomly assigned voucher for a free 12- month premium membership. We observe that individuals do not necessarily accumulate more SC from their ability to access advanced networking features, as the treated freelancers did not automatically change their online networking engagement. Those features only reveal their full utility if individuals are motivated to proactively engage in networking. We found that freelancers who had access to advanced networking features increased their SC by 4.609% for each unit increase on the strategic networking behavior scale. We confirmed this finding in another study utilizing a second, individual-level panel dataset covering 52,392 freelancers. We also investigated the dynamics that active vs. passive features play in SC accumulation. Based on these findings, we introduce the “theory of purposeful feature utilization”: essentially, individuals must not only possess an efficacious “networking weapon”—they also need the intent to “shoot” it.
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