Abstract
Abstract This study examines the influence of individual factors (self-monitoring, temporal orientation) on social networking, and their relationship with unethical decision-making. The study used surveys to measure the unethical intentions and social network data of 129 professionals. Data were analyzed using confirmatory factor analysis and structural equation modeling. The findings provided evidence that individual factors influence the development of social networks and, along with self-monitoring, the likelihood of unethical decision-making. In particular, being in positions of lower network centrality increased individuals' risk of unethical intention. One explanation stems from the need for high situation control to reduce risk and ensure the success of an event, which only a closed network can provide. However, ethical low self-monitor women were also found to have low centrality, so social networks alone do not explain ethical decision-making. This research represents a step forward in our understanding of ethical decision-making through the adoption of multiple and simultaneous factors, proposing an integrated theory of individual and situational factors influencing unethical options.
Highlights
Over the past several decades, fraud and corruption have received increasing attention worldwide by both policymakers and academics
Self-monitoring was used in its continuous form in the main analyses (CFA and structural equation modeling (SEM)), but we introduced a dichotomized selfmonitoring in the text to offer additional analyses
The objective of this study was to analyze the mutual interplay of individual factors and social situations in the choice of unethical intentions, focusing on social networks and two individual factors – self-monitoring and temporal orientation
Summary
Over the past several decades, fraud and corruption have received increasing attention worldwide by both policymakers and academics. This attention has been due in part to the surfeit of high-profile cases reported in the popular press (e.g., Enron, WorldCom, Parmalat, Siemens, Petrobras) as well as the vast sums of money involved. As attitudes and values regarding unethical behavior are not formed in isolation (Gunia, Wang, Huang, Wang, & Murnighan, 2012; Martin, Cullen, Johnson, & Parboteeah, 2007) and corruption typically involves the complicity of other parties (Ayios, Jeurissen, Manning, & Spence, 2014; Brass, Butterfield, & Skaggs, 1998; Nielsen, 2003), a key element in understanding the emergence and perpetuation of corruption is relational networks. To understand and manage unethical behavior within and between organizations, it is necessary to focus on individuals’ networks
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