A Change Management Approach with the Support of the Balanced Scorecard and the Utilization of Artificial Neural Networks

Alkinoos Psarras, Theodoros Anagnostopoulos, Ioannis Salmon, Yannis Psaromiligkos and Lazaros Vryzidis
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Alkinoos Psarras: Department of Business Administration, University of West Attica, 12243 Athens, Greece
Theodoros Anagnostopoulos: Department of Business Administration, University of West Attica, 12243 Athens, Greece
Ioannis Salmon: Department of Business Administration, University of West Attica, 12243 Athens, Greece
Yannis Psaromiligkos: Department of Business Administration, University of West Attica, 12243 Athens, Greece
Lazaros Vryzidis: Department of Business Administration, University of West Attica, 12243 Athens, Greece

Administrative Sciences, 2022, vol. 12, issue 2, 1-15

Abstract: Artificial Intelligence (AI) has revolutionized the way organizations face decision-making issues. One of these crucial elements is the implementation of organizational changes. There has been a wide-spread adoption of AI techniques in the private sector, whereas in the public sector their use has been recently extended. One of the greatest challenges that European governments have to face is the implementation of a wide variety of European Union (EU) funding programs which have evolved in the context of the EU long-term budget. In the current study, the Balanced Scorecard (BSC) and Artificial Neural Networks (ANNs) are intertwined with forecasting the outcomes of a co-financed EU program by means of its impact on the non-financial measures of the government body that materialized it. The predictive accuracy of the present model advanced in this research study takes into account all the complexities of the business environment, within which the provided dataset is produced. The outcomes of the study showed that the measures taken to enhance customer satisfaction allows for further improvement. The utilization of the proposed model could facilitate the decision-making process and initiate changes to the administrational issues of the available funding programs.

Keywords: change management; Balanced Scorecard; Artificial Neural Networks; project performance (search for similar items in EconPapers)
JEL-codes: L M M0 M1 M10 M11 M12 M14 M15 M16 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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