Produktentwicklung mit Lieferanten

Digital Transformation in Public Sector: Case Study on Licensing Services to Start a Business in Pekalongan City

“…Theoretically, this study suspects several factors that influenced the process of digital transformation, those were strategy factor, leadership factor, HR capacity factor, digital culture factor, and user focus factor. The factors were consistent with the results of research conducted by Eggers and Bellman (2015).…”

“…The influence of strategic factors, digital cultural factors, leadership factors, the role of the central government organization, and HR capacity factors were different from the results of research conducted by Eggers & Bellman (2015). Five differences were identified between the results of this study with Eggers and Bellman's research (2015).…”

“…This study did not find any data and information that showed the influence of user focus factors, but data and information showed the Digital Government? influence of new factors which was not mentioned by Eggers and Bellman (2015) in their research, namely the role of the central government organization.…”

“…Research on e-government implementation was found more than research on digital transformation, especially in the context of the public sector. Research conducted by Eggers and Bellman (2015), Martin and Goggins (2016) Research conducted by Martin and Goggin (2016) focused on the impact of digital transformation in the public sector, while Eggers and Bellman (2015), Benjamin and Potts (2018), Mergel et al (2019), and Jonathan (Jonathan, 2019) focused on analyzing the factors that influenced the process of digital transformation. The results of the study can be seen in table 2.…”

The Transformation Risk-Benefit Model of Artificial Intelligence: Balancing Risks and Benefits Through Practical Solutions and Use Cases

“…This research builds upon 8 AI challenge categories proposed in a public sector model, used to organize the risks: 1) societal; 2) economic; 3) political, legal and policy; 4) environmental; 4) ethical; 5) data; 6) technological and implementation; and 8) organizational and managerial [13]. Public organization adoption of AI and data science presents numerous known challenges ranging from employee path dependency on embedded processes and norms, information silos, and a lack of resources, collaborative culture and technical capacities [25][26] [27]. AI systems have had some harmful side effects on communities, through effects on employment and inequality [28], privacy and safety-injury, property loss and workplace hazards [14], addictive behavior [29], fairness, bias and discrimination [30][31], human rights [12] and polarization, extremism, manipulative practices and conflict [32][33][34] [18].…”