IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/w69yh.html
   My bibliography  Save this paper

Behavioral Intentions to use Artificial Intelligence Among Managers in Small and Medium Enterprises

Author

Listed:
  • Jameel, Alaa S.

    (Cihan University-Erbil)

  • Harjan, Sinan Abdullah
  • Ahmad, Abd Rahman

Abstract

The purpose of this study is to examine the measure the Behavioral intentions (BI) to use artificial intelligence (AI) among managers in small and medium enterprises. the targets population of this study was the SMEs managers in Baghdad City after ensuring that the managers were using some form of AI. 184 valid questionnaires have been analyzed by Smart-PLS. The results indicated that performance expectancy (PE), Social influence (SI), Facilitating Conditions (FC), and Top management support (TMS) have a positive and significant impact on behavioral intention to use AI among the managers in SMEs; on the other hand, the effort expectancy (EE) has an insignificant impact on behavioral intention to use AI among the managers.

Suggested Citation

  • Jameel, Alaa S. & Harjan, Sinan Abdullah & Ahmad, Abd Rahman, 2023. "Behavioral Intentions to use Artificial Intelligence Among Managers in Small and Medium Enterprises," OSF Preprints w69yh, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:w69yh
    DOI: 10.31219/osf.io/w69yh
    as

    Download full text from publisher

    File URL: https://osf.io/download/650ac530cf3dc926f1ad1949/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/w69yh?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Chatterjee, Sheshadri & Chaudhuri, Ranjan & Vrontis, Demetris & Thrassou, Alkis & Ghosh, Soumya Kanti, 2021. "Adoption of artificial intelligence-integrated CRM systems in agile organizations in India," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    2. Duan, Yanqing & Edwards, John S. & Dwivedi, Yogesh K, 2019. "Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda," International Journal of Information Management, Elsevier, vol. 48(C), pages 63-71.
    3. Gansser, Oliver Alexander & Reich, Christina Stefanie, 2021. "A new acceptance model for artificial intelligence with extensions to UTAUT2: An empirical study in three segments of application," Technology in Society, Elsevier, vol. 65(C).
    4. Juan-Pedro Cabrera-Sánchez & Iviane Ramos-de-Luna & Elena Carvajal-Trujillo & Ángel F. Villarejo-Ramos, 2020. "Online Recommendation Systems: Factors Influencing Use in E-Commerce," Sustainability, MDPI, vol. 12(21), pages 1-15, October.
    5. Grewal, Dhruv & Guha, Abhijit & Satornino, Cinthia B. & Schweiger, Elisa B., 2021. "Artificial intelligence: The light and the darkness," Journal of Business Research, Elsevier, vol. 136(C), pages 229-236.
    6. Cao, Guangming & Duan, Yanqing & Edwards, John S. & Dwivedi, Yogesh K., 2021. "Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making," Technovation, Elsevier, vol. 106(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Badghish, Saeed & Shaik, Aqueeb Sohail & Sahore, Nidhi & Srivastava, Shalini & Masood, Ayesha, 2024. "Can transactional use of AI-controlled voice assistants for service delivery pickup pace in the near future? A social learning theory (SLT) perspective," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    2. Dhiman, Neeraj & Jamwal, Mohit & Kumar, Ajay, 2023. "Enhancing value in customer journey by considering the (ad)option of artificial intelligence tools," Journal of Business Research, Elsevier, vol. 167(C).
    3. Haili Yang & Yueyue Luo & Yunhua Qiu & Jiantao Zou & Mohammad Masukujjaman & Abdullah Mohammed Ibrahim, 2023. "Modeling the Enablers of Consumers’ E-Shopping Behavior: A Multi-Analytic Approach," Sustainability, MDPI, vol. 15(8), pages 1-28, April.
    4. Pervaiz Akhtar & Arsalan Mujahid Ghouri & Haseeb Ur Rehman Khan & Mirza Amin ul Haq & Usama Awan & Nadia Zahoor & Zaheer Khan & Aniqa Ashraf, 2023. "Detecting fake news and disinformation using artificial intelligence and machine learning to avoid supply chain disruptions," Annals of Operations Research, Springer, vol. 327(2), pages 633-657, August.
    5. Cano-Marin, Enrique & Mora-Cantallops, Marçal & Sánchez-Alonso, Salvador, 2023. "Twitter as a predictive system: A systematic literature review," Journal of Business Research, Elsevier, vol. 157(C).
    6. Qian, Lixian & Yin, Juelin & Huang, Youlin & Liang, Ya, 2023. "The role of values and ethics in influencing consumers’ intention to use autonomous vehicle hailing services," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    7. Latinovic, Zoran & Chatterjee, Sharmila C., 2022. "Achieving the promise of AI and ML in delivering economic and relational customer value in B2B," Journal of Business Research, Elsevier, vol. 144(C), pages 966-974.
    8. Mahmud, Hasan & Islam, A.K.M. Najmul & Ahmed, Syed Ishtiaque & Smolander, Kari, 2022. "What influences algorithmic decision-making? A systematic literature review on algorithm aversion," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    9. Zhang, Weidong & Zuo, Na & He, Wu & Li, Songtao & Yu, Lu, 2021. "Factors influencing the use of artificial intelligence in government: Evidence from China," Technology in Society, Elsevier, vol. 66(C).
    10. Taiga Saito & Shivam Gupta, 2022. "Big data applications with theoretical models and social media in financial management," CARF F-Series CARF-F-550, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    11. Ying, Ying & Wang, Shixiang & Liu, Yang, 2022. "Make bricks without straw: Eco-innovation for resource-constrained firms in emerging markets," Technovation, Elsevier, vol. 114(C).
    12. Jung-Chieh Lee & Yuyin Tang & SiQi Jiang, 2023. "Understanding continuance intention of artificial intelligence (AI)-enabled mobile banking applications: an extension of AI characteristics to an expectation confirmation model," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
    13. Dydrov, Artur (Дыдров, Артур), 2023. "Artificial Intelligence: Mythologies Of Western Scientific Content [Искусственный Интеллект: Мифологемы Западного Научного Контента]," Sotsium i vlast / Society and power, Russian Presidential Academy of National Economy and Public Administration, pages 16-25.
    14. Chatterjee, Sheshadri & Chaudhuri, Ranjan & Vrontis, Demetris & Dana, Léo-Paul & Kabbara, Diala, 2024. "Developing resilience of MNEs: From global value chain (GVC) capability and performance perspectives," Journal of Business Research, Elsevier, vol. 172(C).
    15. Chatterjee, Sheshadri & Chaudhuri, Ranjan & Vrontis, Demetris & Pereira, Vijay, 2022. "Examining the industrial buying behavior in Indian market: From behavior and cultural perspective for B2B buyers and suppliers," Journal of Business Research, Elsevier, vol. 151(C), pages 86-99.
    16. Zhiyuan Yu & Doudou Jin, 2021. "Determinants of Users’ Attitude and Intention to Intelligent Connected Vehicle Infotainment in the 5G-V2X Mobile Ecosystem," IJERPH, MDPI, vol. 18(19), pages 1-19, September.
    17. Yuan, Chunlin & Zhang, Chenlei & Wang, Shuman, 2022. "Social anxiety as a moderator in consumer willingness to accept AI assistants based on utilitarian and hedonic values," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    18. Jeon, Yongwoog Andrew, 2022. "Let me transfer you to our AI-based manager: Impact of manager-level job titles assigned to AI-based agents on marketing outcomes," Journal of Business Research, Elsevier, vol. 145(C), pages 892-904.
    19. Fawwaz Tawfiq Awamleh & Ala Nihad Bustami, 2022. "Examine the Mediating Role of the Information Technology Capabilities on the Relationship Between Artificial Intelligence and Competitive Advantage During the COVID-19 Pandemic," SAGE Open, , vol. 12(3), pages 21582440221, August.
    20. Sullivan, Yulia & Fosso Wamba, Samuel, 2024. "Artificial intelligence and adaptive response to market changes: A strategy to enhance firm performance and innovation," Journal of Business Research, Elsevier, vol. 174(C).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:osfxxx:w69yh. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.