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Information systems and strategy-as-practice in the digital era: an artificial neural network model for SMEs

Author

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  • Maria Kamariotou

    (University of Macedonia)

  • Fotis Kitsios

    (University of Macedonia)

Abstract

Improving small and medium-sized enterprises’ (SMEs’) operations requires a combination of digital transformation and IS. Every business is working harder than ever to obtain a competitive edge and boost consumer satisfaction as the global economy heats up. Therefore, picking the right IS results in a competitive edge, faster communication, the ability to store and retrieve more accurate data, decreased costs, and greater customer value. Prior researchers have ignored the importance of IS strategizing in selecting and implementing appropriate IS as per situation, instead focusing on the impact of digital transformation practices on SMEs’ performance and critical factors that impact IS adoption. Given the lack of formal processes and strategic planning, the application of strategy-as-practice is fruitless. This prevents management from gaining a long-term competitive advantage through IS planning. In this study, we investigate how strategic processes and practices affect IS success. Data was obtained from 294 information technology managers from Greek SMEs. Both the Artificial Neural Network model and the Structural Equation Model (SEM) were used to examine the data. The study's findings indicate that top-level management should be educated on the strategic application of IS planning to boost competitive advantage. Additionally, the manager is in charge of selecting the right IT infrastructure in order to harmonize the organization's strategy and structure. The results help managers prioritize duties and understand the value of IS planning in this area.

Suggested Citation

  • Maria Kamariotou & Fotis Kitsios, 2024. "Information systems and strategy-as-practice in the digital era: an artificial neural network model for SMEs," Operational Research, Springer, vol. 24(3), pages 1-20, September.
  • Handle: RePEc:spr:operea:v:24:y:2024:i:3:d:10.1007_s12351-024-00842-9
    DOI: 10.1007/s12351-024-00842-9
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