Skip to main content
Springer Nature Link
Log in

What could possibly go wrong? A multi-panel Delphi study of organizational social media risk

  • Published:
Information Systems Frontiers Aims and scope Submit manuscript

Abstract

The growth of social media has crossed the boundary from individual to organizational use, bringing with it a set of benefits and risks. To mitigate these risks and ensure the benefits of social media use are realized, organizations have developed a host of new policies, procedures, and hiring practices. However, research to date has yet to provide a comprehensive view on the nature of risk associated with the use of social media by organizations. Using a multi-panel Delphi approach consisting of new entrants to the workforce, certified human resource professionals, and certified Information Technology auditors, this study seeks to understand organizational social media risk. The results of the Delphi panels are compared against a textual analysis of 40 social media policies to provide a comprehensive view of the current state of social media policy development. We conclude with directions for future research that may guide researchers interested in exploring social media risk in organizations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Notes

  1. http://mashable.com/2011/02/16/red-cross-tweet/ (Accessed 05/15/2016)

  2. https://www.fbi.gov/about-us/investigate/counterintelligence/internet-social-networking-risks (Accessed 05/15/2016)

  3. https://www.zerofox.com/blog/top-9-social-media-threats-2015/ (Accessed 05/15/2016)

  4. https://www.sec.gov/News/PressRelease/Detail/PressRelease/1365171513574 (Accessed 05/15/2016)

References

  • Alter, S., & Sherer, S. A. (2004). A general, but readily adaptable model of information system risk. Communications of the Association for Information Systems, 14(1–28), 1.

    Google Scholar 

  • Argenti, P. A., & Druckenbiller, B. (2004). Reputation and the corporate brand. Corporate Reputation Review, 6(4), 368–374.

    Article  Google Scholar 

  • Aula, P. (2010). Social media, reputation risk, and ambient publicity management. Strategy & Leadership, 38(6), 43–49.

    Article  Google Scholar 

  • Barton, B. F., & Barton, M. S. (1984). User-friendly password methods for computer-mediated information systems. Computers & Security, 3(3), 186–195.

    Article  Google Scholar 

  • Baskerville, R., Park, E. H., & Kim, J. (2014). An emote opportunity model of computer abuse. [article]. Information Technology & People, 27(2), 155–181. doi:10.1108/itp-11-2011-0068.

    Article  Google Scholar 

  • Baur, A. W. (Forthcoming). Harnessing the social web to enhance insights into people’s opinions in business, government and public administration. Information Systems Frontiers, 1–21.

  • Bernoff, J., & Schadler, T. (2010). Empowered. Harvard Business Review, 88(July–August), 95–101.

    Google Scholar 

  • Best, R. (1974). An experiment in delphi estimation in marketing decision making. Journal of Marketing Research, 11, 448–452.

    Article  Google Scholar 

  • Bharati, P., Zhang, C., & Chaudhury, A. (2014). Social media assimilation in firms: investigating the roles of absorptive capacity and institutional pressures. Information Systems Frontiers, 16(2), 257–272.

    Article  Google Scholar 

  • Boje, D., & Murninghan, J. (1982). Group confidence pressures in iterative decisions. Management Science, 28, 1187–1196.

    Article  Google Scholar 

  • Boyatzis, R. E. (1998). Transforming qualitative information: Thematic analysis and code development. Chicago: Sage.

    Google Scholar 

  • Boyd, D. (2008). Facebook’s privacy trainwreck: exposure, invasion, and social convergence. Convergence: The International Journal of Research into New Media Technologies, 14(1), 13–20.

    Article  Google Scholar 

  • Brancheau, J. C., & Wetherbe, J. C. (1987). Key issues in information systems management. MIS Quarterly, 11(1), 22.

    Article  Google Scholar 

  • Brancheau, J. C., & Wetherbe, J. C. (1990). The adoption of spreadsheet software: testing innovation diffusion theory in the context of end-user computing. Information Systems Research, 1(2), 115–143.

    Article  Google Scholar 

  • Brockhoff, K. (2002). The performance of forecasting groups in computer dialogue and face-to-face discussion. In M. Turoff, & H. A. Linestone (Eds.), The Delphi Method: Techniques and Applications. Addison-Wesley Publishing Co.

  • Buckley, J. L. (1974). Family Educational Rights and Privacy Act (FERPA). In U. S. Congress (Ed.), (Vol. 20 U.S.C. § 1232 g; 34 CFR Part 99). Washington, D. C.: United States Congress.

  • Byrd, S. (2012). Hi fans! Tell us your story!: incorporating a stewardship-based social media strategy to maintain brand reputation during a crisis. Corporate Communications: An International Journal, 17(3), 241–254.

    Article  Google Scholar 

  • Chou, W.-Y. S., Hunt, Y. M., Beckjord, E. B., Moser, R. P., & Hesse, B. W. (2009). Social media use in the United States: implications for health communication. Journal of Medical Internet Research, 11(4), e48.

    Article  Google Scholar 

  • Choudhary, A., Hendrix, W., Lee, K., Palsetia, D., & Liao, W.-K. (2012). Social media evolution of the Egyptian revolution. Communications of the ACM, 55(5), 74–80.

    Article  Google Scholar 

  • Committee of Sponsoring Organizations of the Treadway Commission (COSO) (2004). Enterprise risk management - integrated framework. New York, NY: Committee of Sponsoring Organizations of the Treadway Commission.

    Google Scholar 

  • Culnan, M. J., McHugh, P. J., & Zubillaga, J. I. (2010). How large U.S. companies can use twitter and other social media to gain business value. MIS Quarterly Executive, 9(4), 243–259.

    Google Scholar 

  • Dahlander, L., & Piezunka, H. (2014). Open to suggestions: how organizations elicit suggestions through proactive and reactive attention. Research Policy, 43, 812–827.

    Article  Google Scholar 

  • Deans, P. C. (2011). The impact of social media on C-level roles. MIS Quarterly Executive, 10(4), 187–200.

    Google Scholar 

  • Delbecq, A., Van de Ven, A., & Gustafson, D. (1975). Group techniques for program planning: A guide to nominal group and delphi processes. Glenview, IL: Scott, Foresman, and Company.

    Google Scholar 

  • Dhillon, G., & Torkzadeh, G. (2006). Value-focused assessment of information system security in organizations. [article]. Information Systems Journal, 16(3), 293–314. doi:10.1111/j.1365-2575.2006.00219.x.

    Article  Google Scholar 

  • Di Gangi, P. M., & Wasko, M. (2009). Steal my idea! Organizational adoption of user innovations from a user innovation community: a case study of Dell IdeaStorm. Decision Support Systems, 48(1), 303–312.

    Article  Google Scholar 

  • Di Gangi, P. M., Wasko, M., & Hooker, R. E. (2010). Getting customers’ ideas to work for you: learning from Dell how to succeed with online user innovation communities. MIS Quarterly Executive, 9(4), 213–228.

    Google Scholar 

  • Dickinson, G. W., Leitheiser, R. L., Wetherbe, J. C., & Nechis, M. (1984). Key information systems issues for the 1980’s. MIS Quarterly, 8(3), 24.

    Google Scholar 

  • Dijkmans, C., Kerkhof, P., & Beukeboom, C. J. (2015). A stage to engage: social media use and corporate reputation. Tourism Management, 47(April), 58–67.

    Article  Google Scholar 

  • El-Gayar, O. F., & Fritz, B. D. (2010). A web-based multi-perspective decision support system for information security planning. [article]. Decision Support Systems, 50(1), 43–54. doi:10.1016/j.dss.2010.07.001.

    Article  Google Scholar 

  • Gaines-Ross, L. (2013). Get social: a mandate for new CEOs. MIT Sloan Management Review, 54(3), 1–5.

    Google Scholar 

  • Gallaugher, J., & Ransbotham, S. (2010). Social media and customer dialog management at Starbucks. MIS Quarterly Executive, 9(4), 197–212.

    Google Scholar 

  • Goel, S., & Chengalur-Smith, I. (2010). Metrics for characterizing the form of security policies. Journal of Strategic Information Systems, 19, 281–295.

    Article  Google Scholar 

  • Goh, S. H., & Di Gangi, P. M. (2016). A framework for understanding risk perceptions in cooperatives. The Cooperative Accountant, LXIV(Summer), Article 2.

  • Goodhue, D. L., & Straub, D. (1991). Security concerns of system users: a study of perceptions of the adequacy of security. Information Management, 20(1), 13–27.

    Article  Google Scholar 

  • Gramm, P., Leach, J., & Bliley, T. J. Jr. (1999). Gramm-Leach-Bliley Act. In t. U. S. Congress (Ed.), (Vol. Public Law 106–102). Washington, D. C.: United States Congress.

  • Gray, P., & Hovav, A. (2014). Using scenarios to understand the frontiers of IS. Information Systems Frontiers, 16, 337–345.

    Article  Google Scholar 

  • Gregor, S. (2006). The nature of theory in information systems. MIS Quarterly, 611–642.

  • Guitierrez, F. J., Ochoa, S. F., Zurita, G., & Baloian, N. (2016). Understanding student participation in undergraduate course communities: a case study. Information Systems Frontiers, 18(1), 7–21.

    Article  Google Scholar 

  • Hanna, R., Rohm, A., & Crittenden, V. L. (2011). We’re all connected: the power of the social media ecosystem. Business Horizons, 54(3), 265–273.

    Article  Google Scholar 

  • Helm, C., & Jones, R. (2010). Brand governance: the new agenda in brand management. Brand Management, 17, 545–547.

    Article  Google Scholar 

  • Hogben, G. (2007). Security issues and recommendations for online social networks. ENISA position paper (1).

  • Hsu, L., & Lawrence, B. (2015). The role of social media and brand equity during a product recall crisis: a shareholder value perspective. International Journal of Research in Marketing, 33(1), 59–77.

    Article  Google Scholar 

  • Hunton, J. E., Wright, A. M., & Wright, S. (2004). Are financial auditors overconfident in their ability to assess risks associated with enterprise resource planning systems? Journal of Information Systems, 18(2), 7–28.

    Article  Google Scholar 

  • Ifinedo, P. (2011). An exploratory study of the relationships between selected contextual factors and information security concerns in global financial services institutions. Journal of Privacy & Security, 7(1), 25–49.

    Article  Google Scholar 

  • IT Governance Institute (ITGI) (2005). COBIT 5. Rolling Meadows, IL: IT Governance Institute.

    Google Scholar 

  • Jenkins, C. (2012). Towards ‘social’ security. Computer Fraud & Security, 2012(8), 18–20. doi:10.1016/s1361-3723(12)70084-2.

    Article  Google Scholar 

  • Johnston, A. C., & Warkentin, M. (2010). Fear appeals and information security behaviors: an empirical study. MIS Quarterly, 34(3), 549–566.

    Article  Google Scholar 

  • Johnston, A. C., Worrell, J. L., Di Gangi, P. M., & Wasko, M. (2013). Online health communities: an assessment of the influence of participation on patient empowerment outcomes. Information Technology & People, 26(2), 213–235.

    Article  Google Scholar 

  • Johnston, A. C., Warkentin, M., & Siponen, M. (2015). An enhanced fear appeal rhetorical framework: leveraging threats to the human asset through sanctioning rhetoric. MIS Quarterly, 39(1), 113–134.

    Article  Google Scholar 

  • Kallinikos, J., & Tempini, N. (2014). Patient data as medical facts: social media practices as a foundation for medical knowledge creation. Information Systems Research, 25(4), 817–833.

    Article  Google Scholar 

  • Kane, G. C. (2015a). Can you really let employees loose on social media? MIT Sloan Management Review, 56(2), 1–9.

    Google Scholar 

  • Kane, G. C. (2015b). Enterprise social media: Current capabilities and future possibilities. MIS Quarterly Executive, 14(1), 1–16.

    Google Scholar 

  • Kane, G. C., Fichman, R. G., Gallaugher, J., & Glaser, J. (2009). Community relations 2.0. Harvard Business Review, November.

  • Kane, G. C., Alavi, M., Labianca, G., & Borgatti, S. P. (2014). What’s different about social media networks? A framework and research agenda. MIS Quarterly, 38(1), 275–304.

    Article  Google Scholar 

  • Kankanhalli, A., Teo, H.-H., Tan, B. C. Y., & Wei, K.-K. (2003). An integrative study of information systems security effectiveness. International Journal of Information Management, 23, 139–154.

    Article  Google Scholar 

  • Kaplan, A. M., & Haenlein, M. (2010). Users of the world unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59–68.

    Article  Google Scholar 

  • Kennedy, E., & Kassebaum, N. (1996). Health Insurance Portability and Accountability Act (HIPPA) of 1996. In t. U. S. Congress (Ed.), (Vol. Public Law 104–191). Washington, D. C.: United States Congress.

  • Kietzmann, J. H., Hermkens, K., McCarthy, I. P., & Silvestre, B. S. (2011). Social media? Get serious! Understanding the functional building blocks of social media. Business Horizons, 54(3), 241–251.

    Article  Google Scholar 

  • Kotulic, A. G., & Clark, J. G. (2004). Why there aren’t more information security research studies. Information Management, 41(5), 597–607.

    Article  Google Scholar 

  • Krasnova, H., Günther, O., Spiekermann, S., & Koroleva, K. (2009). Privacy concerns and identity in online social networks. Identity in the Information Society, 2, 39–63.

    Article  Google Scholar 

  • Krasnova, H., Widjaja, T., Buxmann, P., Wenninger, H., & Benbasat, I. (2015). Why following friends can hurt you: an exploratory investigation of the effects of envy on social networking sites among college-age users. Information Systems Research, 26(3), 585–605.

    Article  Google Scholar 

  • Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174.

    Article  Google Scholar 

  • Leidner, D., Koch, H., & Gonzalez, E. (2010). Assimilating generation Y IT new hires into USAA’s workforce: the role of an enterprise 2.0 system. MIS Quarterly Executive, 9(4), 229–242.

    Google Scholar 

  • Leonardi, P. M., Huysman, M., & Steinfield, C. (2013). Enterprise social media: definition, history, and prospects for the study of social technologies in organizations. Journal of Computer-Mediated Communication, 19(1), 1–19.

    Article  Google Scholar 

  • Levy, M., Leusner, A., & Wasti, K. (2015). Putting the squeeze on social media: understanding social media regulation, and its associated risks, is key to helping protect the organization from potential harm. Internal Auditor, 72(1), 36–42.

    Google Scholar 

  • Li, H., Sarathy, R., Zhang, J., & Luo, X. (2014). Exploring the effects of organizational justice, personal ethics and sanction on internet use policy compliance. Information Systems Journal, 24(6), 479–502.

    Article  Google Scholar 

  • Linestone, H. A., & Turoff, M. (2002). The Delphi method: techniques and applications. Reading: Addison-Wesley Publishing Co.

  • Lundmark, L. W., Oh, C., & Verhaal, J. C. (Forthcoming). A little birdie told me: social media, organizational legitimacy, and underpricing in initial public offerings. Information Systems Frontiers, 1–16. doi:10.1007/s10796-016-9654-x.

  • Miller-Merrell, J. (2012). The workplace engagement economy where HR, social, mobile, and tech collide. Employment Relations Today, 39(2), 1–9.

    Article  Google Scholar 

  • Mooney, J. L., Wright Jr., H. R., & Higgins, L. N. (2010). Gen Y’s addiction to Web 2.0: problem or strategy? The Journal of Corporate Accounting & Finance, 22(1), 63–73.

  • Ng, B. Y., & Feng, A. E. (2006). An exploratory study on managerial security concerns in technology start-ups. In 10th Pacific Asia Conference on Information Systems, Kuala Lumpur, Malaysia, pp. 189–196.

  • Paliwoda, S. (1983). Predicting the future using Delphi. Management Decision, 21(1), 31–38.

    Article  Google Scholar 

  • Reich, B. H., & Benbasat, I. (2000). Factors that influence the social dimension of alignment between business and information technology objectives. MIS Quarterly, 24(1), 81–113.

  • Rhee, H.-S., Ryu, Y. U., & Kim, C.-T. (2012). Unrealistic optimism on information security management. Computers & Security, 31, 221–232.

    Article  Google Scholar 

  • Sarasohn-Kahn, J. (2008). The wisdom of patients: Health care meets online social media. Oakland, CA: California HealthCare Foundation.

    Google Scholar 

  • Saridakis, G., Benson, V., Ezingeard, J. N., & Tennakoon, H. (2016). Individual information security, user behavior and cyber victimisation: an empirical study of social networking users. Technological Forecasting and Social Change, 102(C), 320–330.

    Article  Google Scholar 

  • Schmidt, R. (1997). Managing delphi surveys using nonparametric statistical techniques. Decision Sciences, 28(3), 763–774.

    Article  Google Scholar 

  • Schmidt, R., Lyytinen, K., Keil, M., & Cule, P. (2001). Identifying software project risks: an international delphi study. Journal of Management Information Systems, 17(4), 5–35.

    Article  Google Scholar 

  • Spears, J. L., & Barki, H. (2010). User participation in information systems security risk management. MIS Quarterly, 34(3), 503–522.

    Article  Google Scholar 

  • Straub, D. W., & Welke, R. J. (1998). Coping with systems risk: security planning models for management decision making. MIS Quarterly, 22(4), 441–469.

    Article  Google Scholar 

  • Tan, T., Ruighaver, T., & Ahmad, A. (2003). Incident handling: Where the need for planning is often not recognised. In 1st Australian Computer, Network & Information Forensics Conference, Perth, Western Australia.

  • Tapscott, D. (2008). Grown up digital: How the net generation is changing your world. New York: McGraw-Hill.

    Google Scholar 

  • Templier, M., & Paré, G. (2015). A framework for guiding and evaluating literature reviews. Communications of the Association for Information Systems, 37(Article 6), 112–137.

    Google Scholar 

  • Teo, T. S. H., Nishant, R., Goh, M., & Agarwal, S. (2011). Leveraging collaborative technologies to build a knowledge sharing culture at HP analytics. MIS Quarterly Executive, 10(1), 1–18.

    Google Scholar 

  • Tsui, T. C. (2013). Experience from the anti-monopoly law decision in China (Cost and Benefit of Rule of Law). The Network: Business at Berkeley Law(April/ May).

  • van Zyl, A. S. (2009). The impact of social networking 2.0 on organizations. The Electronic Library, 27, 906–918.

    Article  Google Scholar 

  • Viera, A. J., & Garrett, J. M. (2005). Understanding interobserver agreement: the Kappa statistic. Family Medicine, 37(5), 360–363.

    Google Scholar 

  • Vishwanath, A. (2015). Diffusion of deception in social media: social contagion effects and its antecedents. Information Systems Frontiers, 17, 1353–1367.

    Article  Google Scholar 

  • Wakunuma, K. J., & Stahl, B. C. (2014). Tomorrow’s ethics and today’s response: an investigation into the ways information systems professionals perceive and address emerging ethical issues. Information Systems Frontiers, 16, 383–397.

    Article  Google Scholar 

  • Weber, R. (2012). Evaluating and developing theories in the information systems discipline. Journal of the Association for Information Systems, 13(1), 1–30.

    Article  Google Scholar 

  • Wesch, M. (2008). An anthropological introduction to YouTube. In U. Library of Congress (Ed.).

  • Willison, R., & Backhouse, J. (2006). Opportunities for computer crime: considering systems risk from a criminological perspective. [article]. European Journal of Information Systems, 15(4), 403–414. doi:10.1057/palgrave.ejis.3000592.

    Article  Google Scholar 

  • Worrell, J. L., Di Gangi, P. M., & Bush, A. A. (2013). Exploring the use of the Delphi method in accounting information systems research. International Journal of Accounting Information Systems, 14(3), 193–208.

    Article  Google Scholar 

  • Yan, X., Wang, J., & Chau, M. (2015). Customer revist intention to restaurants: evidence from online reviews. Information Systems Frontiers, 17, 645–657.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Management, Information Systems, and Quantitative Methods, Collat School of Business, University of Alabama at Birmingham, 1150 10th Ave S., Birmingham, AL, 35294-4460, USA

    Paul M. Di Gangi, Allen C. Johnston & Samuel C. Thompson

  2. Department of Accounting and Finance, Collat School of Business, University of Alabama at Birmingham, 1150 10th Ave S., Birmingham, AL, 35294-4460, USA

    James L. Worrell

Authors
  1. Paul M. Di Gangi
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Allen C. Johnston
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. James L. Worrell
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Samuel C. Thompson
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Paul M. Di Gangi.

Appendix

Appendix

Item

Risk Domain (Source of Risk)

Definition

Literature Source

Intentional or unintentional violation of legal or regulatory requirements

Legal / Regulatory (Internal)

Inappropriate sharing of personal or professional information that is deemed confidential or privileged by government laws or other regulatory bodies.

(Kane et al. 2009; Levy et al. 2015)

Online content may facilitate discriminatory hiring practices

Legal / Regulatory (Internal)

Use of social media content that is typically deemed inappropriate, unethical, or illegal for the purposes of making hiring decisions or resource assignments.

Author generated – Expansion of legal/ regulatory requirements

Purposeful loss of competitive data or trade secrets

Legal / Regulatory (Internal)

Inappropriate sharing of professional information that is deemed confidential or privileged by a company or organization.

(boyd 2008; van Zyl 2009)

Minority Influence or amplification of events

Social (External)

Creation of a distorted sense of market opinion by increasing the visibility of a vocal and visible minority.

(Helm and Jones 2010)

Unintended exposure of information

Social (Internal)

Accidental transmission and disclosure of information to an unintended third party.

(boyd 2008; van Zyl 2009; Levy et al. 2015)

Social mobilization/ online activism

Social (External)

Ability of a distributed group of individuals or groups to coordinate expressing their opinions and/or interests.

(Kane et al. 2009; Choudhary et al. 2012)

Source of information for hackers/ social engineering

Social (External)

The use of information found on a social media platform to gain unauthorized access to personal or organizational resources.

(van Zyl 2009; Saridakis et al. 2016)

Decreased productivity

Social (Internal)

Reduction in worker efficiency and/or effectiveness due to social media usage for social or non-work purposes.

(van Zyl 2009)

Unreliable user-generated content

Social (External)

Creation of content (posts, images, etc.) by users which contains misinformation, errors, or other incorrect data.

(Kane et al. 2009; van Zyl 2009; Di Gangi et al. 2010; Levy et al. 2015)

Damage to reputation

Social (Internal)

Use of social media in a manner that diminishes how an organization is perceived by others.

(Argenti and Druckenbiller 2004; boyd 2008; Krasnova et al. 2009; van Zyl 2009; Aula 2010; Levy et al. 2015; Hsu and Lawrence 2015; Byrd 2012; Dijkmans et al. 2015; Wakunuma and Stahl 2014)

Employee views perceived as sanctioned/ approved by employer

Social (Internal)

Misperception by individuals, customers and others that a posting by an individual represents the views of their employer.

(Kane et al. 2009; Levy et al. 2015)

Online content may be stored or indexed

Social (External)

Property of social media posts and content that they can be easily searched and/or stored for future access or retrieval by an individual or organization.

(Krasnova et al. 2009; Levy et al. 2015)

Online content shared with unintended third parties for commercial purposes

Social (External)

Use or transmission of an organization’s content to a third party for an expected economic gain.

(Krasnova et al. 2009)

Online content shared with unintended third parties for non-commercial purposes

Social (External)

Use or transmission of organization’s content to a third party for reasons other than economic gain.

(Krasnova et al. 2009)

Perception of social media acceptance/adoption

Social (External)

Concern that an organization may not be adept or savvy at using social media.

(Mooney et al. 2010; Bharati et al. 2014)

Inconsistent branding

Social (Internal)

Image of an organization as portrayed via social media may be inconsistent with the image communicated through more traditional means.

(Kane et al. 2009; Levy et al. 2015)

Damage to consumer confidence

Social (Internal)

Information disseminated through social media may damage current and potential customers’ impressions of a company, its products and/or services.

(Argenti and Druckenbiller 2004; van Zyl 2009; Byrd 2012)

Damage to morale

Social (Internal)

Information disseminated through social media may damage the sense of well-being and faith that employees share regarding their employer.

Author generated – Extrapolation from damage to consumer confidence

Uncontrollable actions

Social (External)

Social media content that is shared or contributed about an organization in a manner that is not under the organization’s direct control.

(van Zyl 2009)

Hacks / unauthorized access to social media account

Technical (External)

Unauthorized use of an organization’s social media accounts by a third party with the intent to cause harm.

(Hogben 2007)

Inefficient use of employer network resources

Technical (Internal)

Negative effects on corporate servers, network bandwidth and other corporate IT resources of employees accessing social media sites.

(van Zyl 2009)

Service interruption

Technical (Internal)

Temporary inability to access social media applications or platforms.

Author generated – IT infrastructure risk

Malicious software (malware)

Technical (External)

Use of fake profiles, postings, blogs or other social media content to secretly install malicious software on a person’s computer without their consent.

(Hogben 2007)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Di Gangi, P.M., Johnston, A.C., Worrell, J.L. et al. What could possibly go wrong? A multi-panel Delphi study of organizational social media risk. Inf Syst Front 20, 1097–1116 (2018). https://doi.org/10.1007/s10796-016-9714-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10796-016-9714-2

Keywords