Authors: | Salmon, Ioannis Anagnostopoulos, Theodoros Psarras, Alkinoos Psycharis, Panagiotis Nikolaos Tagkouta, Eleni |
Issue Date: | 1-Jan-2023 |
Journal: | WSEAS Transactions on Business and Economics |
Volume: | 20 |
Keywords: | Artificial Intelligence, Artificial Neural Networks, Balanced Scorecard, Business plan, Business strategy, Change management, E-Business, Machine Learning, Product Success, Start-ups |
Abstract: | Machine Learning (ML) can be proved as an important tool in planning better business strategies. For the purposes of the present study, the prospect for the development of an electronic platform by a technology firm providing financial services is explored. The purpose of this article is to demonstrate the ways in which a start-up can predict the success of an online platform prior to its market launch. The prediction is achieved by applying Artificial Intelligence (AI) on Key Performance Indicators (KPIs) derived from the customers’ perspective, as shown in the Balanced Scorecard (BSC). The research methodology was quantitative and online questionnaires were used to collect empirical quantitative data related to bank loans. Subsequently, KPIs were created based on the collected data, to measure and assess the success of the platform. The effectiveness of the model was calculated up to 91.89%, and thus, it is estimated that the online platform will be of great success with 91.89% validity. In conclusion, prediction was found to be crucial for businesses to prevent a dire economic situation. Finally, the necessity for businesses to keep up with technological advances is highlighted. |
ISSN: | 22242899 11099526 |
DOI: | 10.37394/23207.2023.20.59 |
URI: | https://uniwacris.uniwa.gr/handle/3000/1576 |
Type: | Article |
Department: | Department of Business Administration |
School: | School of Administrative, Economics and Social Sciences |
Affiliation: | University of West Attica (UNIWA) |
Appears in Collections: | Articles / Άρθρα |
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