Integrating Organizational Reputation Mechanism to Decision-Making Processes: Facebook Case

Abstract

Facebook, one of the most widespread social media networks across the world, suffered from a serious decline in the share value of the company in the wake of the unauthorized data sharing scandal that occurred in 2018.This survey conducted in the wake of the news of the scandal attempts to determine whether the people would continue to use their social media accounts or not by utilizing the perceived reputation scale. Facebook is an international platform, but the sample of this study consists only of the users in Turkey. The fact that social media is a dynamic agenda-setting tool by nature has revealed the need to respond quickly to the problem. For this reason, the number of the sample was limited to 663, and 72 participants were excluded from the study as they were found to be invalid within the model. The analysis was done through Decision Trees Technique and the rules that affect the perception of the participants and their preferences are revealed. Participants' reputation perceptions are mapped and the probability value of each decision is calculated by the Naive Bayes algorithm. In the decision tree diagram, thirteen rules were obtained. Then, the probability values of each decision made by the Bayesian classifier were calculated and the output of the decision tree diagram was tested. In the research, when the model which is composed of the answers given to the decision variable was tested with the ROC curve, an average of %97, 9 model classification success was achieved. In the decision tree diagram 13 rules were obtained. Then, the probability values of each decision made by the Bayesian classifier were calculated and the output of the decision tree diagram was tested. As a result, each rule obtained from the Decision Tree Diagram has the same result as the Bayes probability values.

Organizational Legitimacy: An In-Depth Overview Through The Lens of Institutional Theory

“…Having raised great concern especially in management research, organizational legitimacy has been regarded as an abstract, a multidimensional and, essential phenomenon in organization studies (Ruef and Scott, 1998 ;Suchman, 1995). Similar to the way organizational reputation is embraced (Yüncü and Fidan, 2019) organizational legitimacy is often referred to as vital for the survival of organizations (Díez-Martín, Prado-Roman and Blanco-González, 2013;Meyer and Rowan, 1977;Zimmerman and Zeitz, 2002). Therefore, researchers have gone for conceptualizing this multilevel phenomenon to achieve a better understanding of how organizations gain and manage it.…”

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“…Accordingly, the present study extends the prevailing views regarding the relationship between organizational silence and organizational support by applying decision trees learning -a data mining technique -to explore the hidden patterns or relationships that prior studies haven't been able to reveal. Decision trees algorithm is a technique that is utilized in classifying and obtaining rules and the algorithm seeks for the best ranking to guess target variables (Yüncü & Fidan, 2019). Hence, the study primarily offers a novel and idiosyncratic perspective for both theoretical frameworks by utilizing the distinct advantages of using decision trees in classification and prediction applications (Kotu & Deshpande, 2015) to form a unique predictive model.…”