New Jersey State Policy Lab: From Emergency to Routine: Evaluating the Implementation of Technology for Government after COVID-19

April 5, 2022

by Leonor Camarena, PhD and Federica Fusi, PhD for New Jersey State Policy Lab

New Jersey was one of the first states to recognize the significance that technological advancements can have on the workforce and larger community. In October 2018, Governor Murphy issued Executive Order 41, which focused on examining how technology would affect New Jersey employees, local businesses, and the overall community. While much of the conversation on policy regarding technological advancements is largely on understanding technological infrastructure and economic opportunities, a less studied aspect of technology is its use in the workplace and how it impacts the social, psychological, and mental well-being of employees in public organizations.

COVID-19 and Technology Adoption in the Workplace

The coronavirus pandemic (COVID-19) forced many public organizations around the world to quickly integrate technology into workplace practices regardless of their locale, size, or role in order to continue to provide public service while guaranteeing safety for both public employees and citizens. For example, New Jersey began issuing emergency adoptions in March 2020 allowing previous work that was typically required to be completed in person to be conducted through online platforms (CITE 52 N.J. 1275). Even in the instances where public employees were still required to be largely in person, communication between government agencies and citizens was moved to various technological platforms (e.g., Zoom, webchats) that may not have been in existence prior to the start of the pandemic.

While these technologies helped public organizations to navigate a sudden emergency like the pandemic, public organizations should now evaluate their impact on work outcomes such as workload, stress, and sense of inclusion of public employees as well as on how local communities are able to use or access the technology. Our review of current research found evidence that information and communications technology (ICT) use can lead employees to work longer hours (Tarafdar et al., 2007) and feel overwhelmed from the increased number of demands (Barley et al., 2010; Bucher et al., 2013; González & Mark, 2004), all of which increase workplace dissatisfaction, fatigue, and anxiety while decreasing commitment and productivity (Hwang & Cha, 2018; Ragu-Nathan et al., 2008; Tarafdar et al., 2015). However, studies also show that organizational interventions – IT support, leadership – can mitigate the negative effects of technology use (Spagnoli et al., 2020; Suh & Lee, 2017; Tarafdar et al., 2015). Our prior work finds that public organizations providing guidance on technology use through best practices and policies help to reduce these negative effects (Camarena & Fusi, 2022; Fusi & Feeney, 2018).

Project Focus

The next steps in this project include speaking with employees in state government agencies to understand how the adoption and integration of technology through government services following COVID-19 has impacted both work outcomes and interactions with the public. Through this project we aim to:

  • Help government agencies to adopt technology into their work practices by informing organizational policies surrounding technology use
  • Identify a set of best practices for advancing the implementation of technology in government agencies
  • Assess potential barriers and needs of local communities with regards to technology use and access
  • Provide inputs and an overview regarding the interaction between the state government and communities through the use of and access to online technology

Barley, Stephen R., Debra E. Meyerson, and Stine Grodal. 2010. ‘E-Mail as a Source and Symbol of Stress’. Organization Science 22(4):887–906. doi: 10.1287/orsc.1100.0573.

Bucher, Eliane, Christian Fieseler, and Anne Suphan. 2013. ‘The Stress Potential of Social Media in the Workplace’. Information, Communication & Society 16(10):1639–67. doi: 10.1080/1369118X.2012.710245.

Camarena, Leonor, and Federica Fusi. 2022. ‘Always Connected: Technology Use Increases Technostress Among Public Managers’. The American Review of Public Administration 52(2):154–68. doi: 10.1177/02750740211050387.

Fusi, Federica, and Mary K. Feeney. 2016. ‘Social Media in the Workplace Information Exchange, Productivity, or Waste?’ The American Review of Public Administration 0275074016675722. doi: 10.1177/0275074016675722.

González, Victor M., and Gloria Mark. 2004. ‘“Constant, Constant, Multi-Tasking Craziness”: Managing Multiple Working Spheres’. Pp. 113–20 in Proceedings of the SIGCHI Conference on Human Factors in Computing SystemsCHI ’04. Vienna, Austria: Association for Computing Machinery.

Hwang, Inho, and Oona Cha. 2018. ‘Examining Technostress Creators and Role Stress as Potential Threats to Employees’ Information Security Compliance’. Computers in Human Behavior 81:282–93. doi: 10.1016/j.chb.2017.12.022.

Ragu-Nathan, T. S., Monideepa Tarafdar, Bhanu S. Ragu-Nathan, and Qiang Tu. 2008. ‘The Consequences of Technostress for End Users in Organizations: Conceptual Development and Empirical Validation’. Information Systems Research. doi: 10.1287/isre.1070.0165.

Spagnoli, Paola, Monica Molino, Danila Molinaro, Maria Luisa Giancaspro, Amelia Manuti, and Chiara Ghislieri. 2020. ‘Workaholism and Technostress During the COVID-19 Emergency: The Crucial Role of the Leaders on Remote Working’. Frontiers in Psychology 11. doi: 10.3389/fpsyg.2020.620310.

Suh, Ayoung, and Jumin Lee. 2017. ‘Understanding Teleworkers’ Technostress and Its Influence on Job Satisfaction’. Internet Research 27(1):140–59. doi: 10.1108/IntR-06-2015-0181.

Tarafdar, Monideepa, Ellen Bolman Pullins, and T. S. Ragu‐Nathan. 2015. ‘Technostress: Negative Effect on Performance and Possible Mitigations’. Information Systems Journal 25(2):103–32. doi: 10.1111/isj.12042.

Tarafdar, Monideepa, Qiang Tu, Bhanu S. Ragu-Nathan, and T. S. Ragu-Nathan. 2007. ‘The Impact of Technostress on Role Stress and Productivity’. Journal of Management Information Systems 24(1):301–28. doi: 10.2753/MIS0742-1222240109.

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