The Privacy Concerns On Social Networks Impacting Behavior Intention

In this empirical study,we provide an explanation of behavioral intention as well as privacy concerns in the context of the LinkedIn social network.In the present study,we build on and extend the current literature on social network and information management studies.A detailed and critical review of literature has identified privacy concerns as being potentially valuable for explaining the behavioral intention of social network users.The aim of our study is to raise understanding of the influence of privacy concern on users"behaviors of Social networks(SNW).By examining privacy concern factors and their relationship to the behavioral intention we aim to determine which factors should companies aim at managing that would translate into optimal user behavior.Furthermore,we will assess the perceived usefulness variable and its impact on behavioral intention.General privacy concern,transactional privacy concern,perceived usefulness,and behavioral intention relationships are tested in our model.The research is cross-sectional,which means that the study and related data acquisition were done during a specific time.The basic positivist approach was adopted,allowing the author to identify fundamental factors affecting the information sharing on LinkedIn.The paper relies on the prior studies,deriving from an extensive literature review,identifying key variables that can affect privacy concerns and help to identify the policy and managerial implications,which were then used as relevant variables in the construction of the research model.A quantitative method of study was preferred in the design to express all variables and elements in the research model numerically.The questionnaire was uploaded to SurveyMonkey,an online data collection tool.The link was distributed to people fitting the profile of LinkedIn users.Convenience sampling method was used.Such sample choice was made in order to secure a higher response rate.After a month-long process of data collection enough that had been sourced and the analysis process started.The scales were adopted from prior studies.All the scales exhibited a sufficient level of reliability exceeding the level of 0.7 in all the studies that the scales were taken from.Each item was measured on a seven-point Likert scale where 1 refers to "strongly agree" and 7 means "strongly disagree."Empirical study was conducted on the sample of 154 LinkedIn social network users,in order to get a better insight into the relevant data such as age,sex,work experience,and purchasing power and willingness to disclose personal information in order to get connected.The collected data was examined after being imported into SPSS Statistics software,which enabled us to make reliability,normality,and validity analysis.SEM analysis test was performed as well,which leads us to decide whether the hypotheses would b e accepted or rejected.This study was done following two-step analytical strategy to test the hypothesized model recommended by Anderson and Gerbing(1988).Accordingly,the measurement model was tested independently before the testing and evaluation of the full structural model.Consequently,the confirmatory factor analysis was firstly performed,followed by testing of the structural model using SEM.After initial confirmatory factor analysis the model was improved by adding covariances based on Modification Indices.Improved measurement model was tested again and it achieved a good model fit(x2/df=1.281;CFI=0.985;SRMR=0.053;RMSEA=0.044).Taking into account the obtained results,it can be concluded that unstandardized estimates are all statistically significant,given C.R.values are above the recommended threshold(1.96).Namely,it was demonstrated that transactional privacy concern has a negative impact on Behavioral intention.while general privacy concern has no moderating effect on transactional privacy concern-behavioral intention relationship in the context of the social network.Lastly,perceived usefulness was found to have a positive impact on Behavioral intention.We sought to explain the different roles of general privacy concerns and transactional privacy concerns in affecting individuals' behavioral intention on LinkedIn.We establish that general privacy concerns powerfully influence users'transactional privacy concerns,which in turn,influences their intention on how to use the social network.Therefore,the research answered the questions on factors impacting behavioral intention of users on LinkedIn,as well as identifying the relationship between privacy concern,perceived usefulness and behavioral intention.The study has implications both for theory and practice and is therefore valuable.The implications of this study provide a conceptual framework that can be used by management scholars and business executives to formulate social network features that can help them increase the trust and decrease privacy concerns of network users.Apart from its academic significance,our study has reached important empirical suggestions.Operators of Social Network Websites(SNW)can benefit from the findings of the study to have a deep understanding of the way privacy concern may influence users' consent of a specific SNW.First,the weak influence of privacy concern on the willingness to use SNWs may explain the reason that users keep using specific SNWs(e.g.LinkedIn)even with the release of privacy violations reports.