Dyadic attribution model: A mechanism to assess trustworthiness in virtual organizations

Abstract

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.

Trustworthiness attribution: Inquiry into insider threat detection

“…This framework contributes an alternative theoretical lens to evaluate insiders’ trustworthiness and detect behavioral changes before the occurrence of an anomaly that impacts the operations of an organization. To summarize, new perspectives on trustworthiness attribution can: Provide early warning insights of insider anomalous activity from socio‐psychological perspectives (e.g., Wall, ). Utilize humans’ distributed metacognitive abilities (Schwarz, ; Smith & Schwarz, ) to correlate complex observations in order to sense and filter subtle cues of a focal actor's trustworthiness in group communication (e.g., Ho & Benbasat, ). Incorporate collective group intelligence to process dynamic social interaction and communication rather than focusing on individual activities (e.g., Ho et al, ). Correlate observations and data collected from social media and computer‐mediated communication environments (e.g., Ho, Hancock, Booth, & Liu, ). Accommodate a panoramic view of the dynamics of insider activities (e.g., Ho & Warkentin, ). …”

“…From a theoretical perspective, the challenge of capturing a perpetrator's intent and behavioral changes is to move beyond “whistleblowing,” to early detection based on empirical evidence. Ho and Benbasat's () dyadic attribution model provides a theoretical foundation for analyzing the causal relationships underlying behavioral observations, as indicators of trustworthiness. Specifically, the dyadic attribution model can be used to explain the influence of an actor's information behavior (e.g., language‐action cues) based on the observer's perception of the actor's trustworthiness (or lack thereof).…”

“…Accordingly, we propose a contemporary perspective to evaluate trustworthiness by adapting the dyadic attribution mechanism (Ho & Benbasat, ) in group communication (Ho et al, ). The dyadic attribution model posits that (a) individuals signal their communicative intent and information behavior in words and actions, (b) members of close groups make attributions associated with trustworthiness of focal actors based on communication cues embedded in group exchange, and (c) these observations can lead to correct attributions of downward shifts in perceived trustworthiness when focal actors initiate in actual “betrayal activities” (Levine & McCornack, ).…”

“…A perception of lowered (or sustained) trustworthiness is usually based on attributing anomalies to internal or external causes. In group communication, when any actor engages in betrayal activities (i.e., observables of actual trustworthiness), this betrayal intent may be reflected and result in subtle changes of physical and informational communication behaviors (Ho & Benbasat, ).

Proposition 1 (P1): Insiders who engage in betrayal activities against their organization may unknowingly send signals in communication artifacts reflecting reduced trustworthiness .

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“…To continue the previous analogy, regardless of a trustee's (i.e., the focal actor's) actual motivation to betray, attribution theory argues that others observe the trustee's behavior over time, making inferences about causes behind changes in behavior that may signify something abnormal (Kelley, ). Ho and Benbasat () extended attribution theory, seeking to answer the specific question of “how the attribution mechanism works to signal a violation of trust based on the communicative language of social actors in a virtual organization,” and investigated how social actors’ trustworthiness can be attributed collectively by group members based on “language as symbolic action.” They noted that “in online communications, people must rely on fairly simple rudimentary evidence (e.g., words and actions) to decide whether to trust another party” (Ho & Benbasat, , p. 1). Consistent with earlier attribution theory, Ho and Benbasat () found support for the argument that coworkers often serve as “smart sensors,” who can make intelligent inference and dynamic trustworthiness attributions based on the interplay of words and actions.…”