Impact of Strategic Alignment on Company Performance: An approach based on performance indicators system design

Azzouz, Mahdia; Boukhedouma, Saida; Alimazghi, Zaia

doi:10.1109/icacsis51025.2020.9263216

Cited by 4 publications

(3 citation statements)

References 16 publications

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“…Reference [36] shows that AI can help to construct a good marketing strategy by giving information to the decisionmaker. The study in [37] also confirms this, showing that AI can construct a strategy to retain customers by analyzing past data. The study in [38] justified it by showing how AI is utilized to analyze data to help construct and align IT-Business strategy.…”

Section: ) Strategy Alignmentsupporting

confidence: 64%

“…Finally, AI can also be utilized in the Check stage of IT Governance [40], which shows that after it gives product recommendations to the customer, it can also evaluate the effectiveness of those recommendations to find ways to improve. Reference [37] also shows the same thing with customer retention strategy: how AI is used to help analyze data to help strategy construction and can also be used to evaluate the strategy. The study in [43] shows AI being used to analyze and evaluate the organizational business model and business process to see if there is a problem with the process and/or model.…”

Section: ) Strategy Alignmentmentioning

confidence: 99%

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Implementations of Artificial Intelligence in Various Domains of IT Governance: A Systematic Literature Review

Hariyanti,

Janeswari,

Moningka

et al. 2023

J. Inf. Syst. Eng. Bus. Intell.

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Background: Artificial intelligence (AI) has become increasingly prevalent in various industries, including IT governance. By integrating AI into the governance environment, organizations can benefit from the consolidation of frameworks and best practices. However, the adoption of AI across different stages of the governance process is unevenly distributed. Objective: The primary objective of this study is to perform a systematic literature review on applying artificial intelligence (AI) in IT governance processes, explicitly focusing on the Deming cycle. This study overlooks the specific details of the AI methods used in the various stages of IT governance processes. Methods: The search approach acquires relevant papers from Elsevier, Emerald, Google Scholar, Springer, and IEEE Xplore. The obtained results were then filtered using predefined inclusion and exclusion criteria to ensure the selection of relevant studies. Results: The search yielded 359 papers. Following our inclusion and exclusion criteria, we pinpointed 42 primary studies that discuss how AI is implemented in every domain of IT Governance related to the Deming cycle. Conclusion: We found that AI implementation is more dominant in the plan, do, and check stages of the Deming cycle, with a particular emphasis on domains such as risk management, strategy alignment, and performance measurement since most AI applications are not able to perform well in different contexts as well as the other usage driven by its unique capabilities. Keywords: Artificial Intelligence, Deming cycle, Governance, IT Governance domain, Systematic literature review

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Section: ) Strategy Alignmentsupporting

confidence: 64%

Section: ) Strategy Alignmentmentioning

confidence: 99%

Implementations of Artificial Intelligence in Various Domains of IT Governance: A Systematic Literature Review

Hariyanti,

Janeswari,

Moningka

et al. 2023

J. Inf. Syst. Eng. Bus. Intell.

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“…Azzouz et al [20] proposed a generic approach for designing, implementing and exploiting a performance indicator system based on the concept of alignment. The authors use the definition of the Performance Indicators System as an essential element used in business management to fulfill this process.…”

mentioning

confidence: 99%

Industrial Performance Measurement Systems Coherence: A Comparative Analysis of Current Methodologies, Validation and Introduction to Key Activity Indicators

2022

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This paper discusses and integrates the concept of complexity in the industrial performance measurement and management systems (PMM) theory, providing a comprehensive overview of the different methodologies used within the decision systems research area. It also discusses the importance of introducing Key Activity Indicators (KAI) within PMM, specifically related to the Operations and Supply Chain management research and industrial areas. Moreover, it provides validation of the methodology through a case study concerning the production environment of a multinational pharmaceutical company. The main research objective is to design appropriate industrial PMM systems with the aim of increasing the industrial efficiency and effectiveness of manufacturing and service organizations. An analysis of the central industrial performance measurement systems design methods is conducted, classifying them into macro-categories and conducting a comparative study. Based on the analysis of the different proposed methods, organisations will be able to choose the best one based on their needs to design effective decision systems. The research work allows organisations to evaluate, assess, and design effective industrial performance measurement systems. Moreover, the proposed methodology can be easily integrated within an Industry 4.0 context, and benefit from the digitalization environment to obtain continuous feedback on the effectiveness of the industrial PMM.

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Objective Key Results and Their Role in Modern Performance Management: A Critical Analysis of Benefits, Challenges, and Integration with Traditional Tools

Fantozzi,

Di Luozzo,

Schiraldi

2024

Lecture Notes in Production Engineering

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Impact of Strategic Alignment on Company Performance: An approach based on performance indicators system design

Cited by 4 publications

References 16 publications

Implementations of Artificial Intelligence in Various Domains of IT Governance: A Systematic Literature Review

Implementations of Artificial Intelligence in Various Domains of IT Governance: A Systematic Literature Review

Industrial Performance Measurement Systems Coherence: A Comparative Analysis of Current Methodologies, Validation and Introduction to Key Activity Indicators

Objective Key Results and Their Role in Modern Performance Management: A Critical Analysis of Benefits, Challenges, and Integration with Traditional Tools

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