Product recommendation agents (RAs) assist online firms to adapt their suggested offers to users’ preferences, thereby lowering users’ decision effort. The concept of effort is central in decision-making, yet it remains unclear whether it should be regarded as a cost or as a benefit improving the odds of a better decision. Building on Social Exchange theory, we suggest that interactions between users and RAs are driven by the concepts of perceived interdependence and reciprocity. We suggest that perceived user effort decreases the perceived RA quality, whereas RA effort increases the perceived RA quality. We conducted two experimental studies across different contexts. We found that users evaluate RAs based on their own expended effort, in relation to how much effort they perceived the RA has put into the process of generating recommendations. Such an effect is attenuated by users’ familiarity with the product context. Our findings offer important insights into how online firms can improve the use of their RAs.

Many important findings and discoveries in science and everyday life are the result of serendipity, that is, the unanticipated occurrence of happy events such as the finding of valuable information. Consumers are increasingly seeking serendipity in online shopping, where information clutter and preprogramed recommendation systems can make product choice frustrating or mundane. However, it is notoriously difficult to design online shopping environments that induce it. In this study, we explore how social media affordances such as obtaining access to peer-generated content and being connected to online friends can help create the right conditions for serendipity in online shopping. We supplement this analysis with an account of two individual factors that are also likely to be instrumental in a shopping context, namely, the intensity of shoppers’ information search and their aversion to risk when faced with a product choice. Our investigation relies on a conceptualization of serendipity that has two defining elements: unexpectedness and informational value . The results of an experimental study in which we manipulated an online product search environment reveal the superiority of designs that incorporate online friendships, and these results support the positive effects of search effort and risk aversion on serendipity. This study contributes by developing a theoretical framework for the analysis of serendipity and by explaining how social commerce , that is, the integration of social media and electronic commerce , can cultivate serendipity.

This paper challenges a long-held assumption of prior research – that online word-of-mouth is anonymous and impersonal – by examining shoppers’ opinion seeking in the context of using a product review website connected to a digital social network (SN). Motivated by the need to account for the idiosyncratic resources available in each shopper’s SN, we distinguish between two types of opinion-seeking behaviours: (i) exploiting, seeking peers’ opinions in one’s core network (ie, online friends), and (ii) exploring, seeking peers’ opinions from one’s extended network (ie, strangers). Using SN theory, we specify what drives these behaviours, and how they influence shoppers’ utilitarian and hedonic experiences in an online product selection task. A free-simulation study, conducted with a restaurant review website connected to the Facebook SN, provided three key insights: (1) Exploitation has a stronger beneficial effect on shoppers’ utilitarian and hedonic experiences than exploration, (2) there is a strong positive influence of social capital (both structural and relational) on shoppers’ propensity to engage in exploitation, and (3) high social capital does not induce the expected extensive substitution of exploration with exploitation. Overall, this study enhances our understanding of online shoppers’ opinion seeking in the increasingly prevalent SN-enabled settings.

Insider threat is a “wicked” contemporary organizational problem. It poses significant threats to organizational operations and information security. This article reviews insider threat research and outlines key propositions to conceptualize the interpretation of dynamic human information behavior in an organizational setting, which represent an integration of trustworthiness and human sensors’ attribution in close relationships. These propositions posit that when a focal individual violates integrity‐based trust, the group can collectively attribute a shift in trustworthiness, triggering a natural peer attribution process that assigns cause to observed behavior. Group communication can thus reflect subtle changes in a focal individual's perceived trustworthiness. The ability to understand group‐based computer‐mediated communication patterns over time may become essential in safeguarding information assets and the “digital well‐being” of today's organizations. This article contributes a novel theoretical lens to examine dynamic insights on insider threat detection.

Language as a symbolic medium plays an important role in virtual communications. In a primarily linguistic environment such as cyberspace, words are an expressed form of intent and actions. We investigate the functions of words and actions in identifying behavioral anomalies of social actors to safeguard the virtual organization. Social actors are likened to “sensors” as they observe changes in a focal individual's behavior during computer‐mediated communications. Based on social psychology theories and pragmatic views of words and actions in online communications, we theorize a dyadic attribution model that helps make sense of anomalous behavior in creative online experiments. This model is then tested in an experiment. Findings show that observation of the behavioral differences between words and actions, based on either external or internal causality, can offer increased ability to detect the compromised trustworthiness of observed individuals—possibly leading to early detection of insider threat potential. The dyadic attribution model developed in this sociotechnical study can function to detect behavioral anomalies in cyberspace, and protect the operations of a virtual organization.