Online serendipity: A contextual differentiation of antecedents and outcomes

Abstract

Critics worry that algorithmic filtering could lead to overly polished, homogeneous web experiences. “Serendipity,” in turn, has been touted as an antidote. Yet, the desirability of serendipity could vary by context, as users may be more or less receptive depending on the services they employ. We propose a nomological model of online serendipity experiences, conceptualizing both cognitive and behavioral antecedents. Based on a survey of 1,173 German Internet users, we conduct structural equation modeling and multigroup analyses to differentiate the antecedents and effects of serendipity across three distinct contexts: online shopping, information services, and social networking sites. Our findings confirm that antecedents and outcomes of digital serendipity vary by context, with serendipity only being associated with user satisfaction in the context of social network sites.

Examining Serendipitous Encounters and Self-Determination in Twitter-Enabled Innovation

“…e Twitter-enabled innovation scale was adjusted from the task innovation scale by Torkzadeh and Doll [9], which we adjusted to the context of Twitter use. We chose the online serendipity scale by Lutz et al [18], because of its emphasis on the unexpected encounter of information. Moreover, consistent with our chosen conceptualization of serendipity, it also includes the extent to which individuals find that particular information useful.…”

“…Two related views have emerged suggesting it is necessary to extend the conceptual understanding of serendipity beyond chance and luck. e first view describes serendipity as an unexpected discovery of insights and ideas that an individual evaluates as useful [11,18]. is view holds that a serendipitous encounter is subjectively evaluated and that serendipity occurs as the individual identifies the usefulness of the unexpected insight for themselves.…”

“…For example, research has focused on innovation processes [26], spontaneous encounters [27], and social awareness [28] in collocated work environments. Some studies have posited that physical and digital environments enable access to various information and engage interactions of diverse minds to achieve noticeable benefits in task innovation [29], thus increasing chances for serendipity to occur [18,30].…”

“…Building on the prior work covered in Section 2, our model posits that information and social serendipity encounters in Twitter help satisfy the three needs. Fortunate discoveries of information are known to encourage individuals [8,18]. When users identify new insights or contacts that are beneficial and relevant to their work, their doubts are relieved in regard to the benefits of carrying out the activity, such as using Twitter for ongoing work tasks [8,50].…”

From Chance to Serendipity: Knowledge Workers’ Experiences of Serendipitous Social Encounters

“…Serendipitous experiences triggered or initiated by physical and digital objects, agents, or environments have been termed artificial serendipity [14]. e concept also appears in the literature where it is called controlled [37] and online serendipity [38,39]. In contrast to its natural counterpart, which is entirely unpredictable and nondeterministic, artificial serendipity happens only when necessary conditions occur.…”