IDEAS home Printed from https://ideas.repec.org/a/spr/joiaen/v12y2023i1d10.1186_s13731-023-00323-x.html
   My bibliography  Save this article

Determinants of consumers’ purchase intention on digital business model platform: evidence from Ethiopia using partial least square structural equation model (PLS-SEM) technique

Author

Listed:
  • Mulatu Tilahun

    (Addis Ababa Institute of Technology, Addis Ababa University)

  • Eshetie Berhan

    (Addis Ababa Institute of Technology, Addis Ababa University)

  • Gezahegn Tesfaye

    (Addis Ababa Institute of Technology, Addis Ababa University)

Abstract

Online digital market platform business model designers, marketers, and retailers can further expand their marketing strategies to draw in and keep customers to gain a competitive edge globally if they are aware of the elements influencing consumers' purchasing intentions. The purpose of this research is to identify the crucial variables impacting Addis Ababa University, Graduating Engineering Students’ desire to purchase on online digital market platforms, and narrow the research gap on determinants of online purchase intention of Ethiopian consumers. This study adopted a descriptive and inferential survey design, epistemology assumption, and employed the positivism research philosophy approach to test the research hypotheses. The primary study technique used to collect relevant data was a closed-ended 5-point Likert scale questionnaire. The information was gathered from 100 Ethiopian, Addis Ababa University, graduating engineering students. With the use of SPSS version 23 and SmartPLS version 3.0 software, the data were examined using descriptive statistics and the inferential partial least square structural equation modeling (PLS-SEM) technique. The results of this study highlighted five useful decision-making elements that have an impact on the selected consumers' intention to buy on online digital market platforms including Website Design, Perceived Usefulness, Perceived Ease of Use, Trust, and Subjective Norms. The Practical Implication of this research is that with a clear understanding of the key determinants of consumers’ purchase intention on online digital market platforms; manufacturers, online marketers, and retailers can create effective market strategies, enhance technology, and make smart marketing choices that will help them gain global competitive advantage. This study is unique in that it uses a new conceptual research framework and the partial least square structural equation modeling (PLS-SEM) technique to analyze relationships between determinant variables and consumers’ intention to purchase on online digital market platforms. The major finding of this research provides empirical evidence towards the key determinant variables of consumers’ purchase intention on online digital market platforms. The small sample size is one of the limitations to generalize the finding of this research. Future studies should focus on enlarging the sample size and assessing more determinant variables to get a generalizable result.

Suggested Citation

  • Mulatu Tilahun & Eshetie Berhan & Gezahegn Tesfaye, 2023. "Determinants of consumers’ purchase intention on digital business model platform: evidence from Ethiopia using partial least square structural equation model (PLS-SEM) technique," Journal of Innovation and Entrepreneurship, Springer, vol. 12(1), pages 1-28, December.
  • Handle: RePEc:spr:joiaen:v:12:y:2023:i:1:d:10.1186_s13731-023-00323-x
    DOI: 10.1186/s13731-023-00323-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1186/s13731-023-00323-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1186/s13731-023-00323-x?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. David J. Teece & Greg Linden, 2017. "Business models, value capture, and the digital enterprise," Journal of Organization Design, Springer;Organizational Design Community, vol. 6(1), pages 1-14, December.
    2. Thi Mai Anh Nguyen & Thi Hue Nguyen & Hieu Hoc Le, 2022. "Online Shopping in Relationship with Perception, Attitude, and Subjective Norm during COVID-19 Outbreak: The Case of Vietnam," Sustainability, MDPI, vol. 14(22), pages 1-11, November.
    3. Maxwell Olokundun & Mercy Ejovwokeoghene Ogbari & Hezekiah Falola & Ayodotun Stephen Ibidunni, 2022. "Leveraging 5G network for digital innovation in small and medium enterprises: a conceptual review," Journal of Innovation and Entrepreneurship, Springer, vol. 11(1), pages 1-10, December.
    4. Lee Cronbach, 1951. "Coefficient alpha and the internal structure of tests," Psychometrika, Springer;The Psychometric Society, vol. 16(3), pages 297-334, September.
    5. Nagy K. Hanna, 2020. "Assessing the digital economy: aims, frameworks, pilots, results, and lessons," Journal of Innovation and Entrepreneurship, Springer, vol. 9(1), pages 1-16, December.
    6. Issariya Woraphiphat & Pattama Roopsuwankun, 2023. "The impact of online design thinking-based learning on entrepreneurial intention: the case of vocational college," Journal of Innovation and Entrepreneurship, Springer, vol. 12(1), pages 1-18, December.
    7. Daniel Ofori & Christina Appiah-Nimo, 2019. "Determinants of online shopping among tertiary students in Ghana: An extended technology acceptance model," Cogent Business & Management, Taylor & Francis Journals, vol. 6(1), pages 1644715-164, January.
    8. Jayani Chamarika Athapaththu & D. Kulathunga, 2018. "Factors Affecting Online Purchase Intention: Effects of Technology and Social Commerce," International Business Research, Canadian Center of Science and Education, vol. 11(10), pages 111-128, October.
    9. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    10. Navitha Singh Sewpersadh, 2023. "Disruptive business value models in the digital era," Journal of Innovation and Entrepreneurship, Springer, vol. 12(1), pages 1-27, December.
    11. Aldo Alvarez-Risco & Liliana Quipuzco-Chicata & Carlos Escudero-Cipriani, 2022. "Determinants of Online Repurchase Intention in Covid-19 Times: Evidence From an Emerging Economy," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 96, pages 101-143, January-J.
    12. Elizabeth Emperatriz García-Salirrosas & Ángel Acevedo-Duque & Viviana Marin Chaves & Paula Andrea Mejía Henao & Juan Carlos Olaya Molano, 2022. "Purchase Intention and Satisfaction of Online Shop Users in Developing Countries during the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(10), pages 1-14, May.
    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. Sepasgozar, Samad M.E., 2022. "Immersive on-the-job training module development and modeling users’ behavior using parametric multi-group analysis: A modified educational technology acceptance model," Technology in Society, Elsevier, vol. 68(C).
    2. Chen Wei, 2021. "The influence of Consumers’ Purchase intention on Smart Wearable Device: A study of Consumers in East China," International Journal of Science and Business, IJSAB International, vol. 5(8), pages 46-72.
    3. Mohammad Tipu Sultan & Farzana Sharmin & Alina Badulescu & Darie Gavrilut & Ke Xue, 2021. "Social Media-Based Content towards Image Formation: A New Approach to the Selection of Sustainable Destinations," Sustainability, MDPI, vol. 13(8), pages 1-22, April.
    4. Seok Chan Jeong & Beom-Jin Choi, 2022. "Moderating Effects of Consumers’ Personal Innovativeness on the Adoption and Purchase Intention of Wearable Devices," SAGE Open, , vol. 12(4), pages 21582440221, November.
    5. Pei Yee Chin & Nina Evans & Charles Zhechao Liu & Kim-Kwang Raymond Choo, 2020. "Understanding Factors Influencing Employees’ Consumptive and Contributive Use of Enterprise Social Networks," Information Systems Frontiers, Springer, vol. 22(6), pages 1357-1376, December.
    6. Pei Yee Chin & Nina Evans & Charles Zhechao Liu & Kim-Kwang Raymond Choo, 0. "Understanding Factors Influencing Employees’ Consumptive and Contributive Use of Enterprise Social Networks," Information Systems Frontiers, Springer, vol. 0, pages 1-20.
    7. Peng Gu & Hao Zhang & Zeheng Liang & Dazhi Zhang, 2022. "Impact of Public Risk Perception in China on the Intention to Use Sports APPs during COVID-19 Pandemic," IJERPH, MDPI, vol. 19(19), pages 1-12, September.
    8. Radoslaw Macik & Dorota Macik, 2011. "Physical vs. Virtual Information Search and Purchase in the Buying Behavior of Polish Young Consumers," MIC 2011: Managing Sustainability? Proceedings of the 12th International Conference, Portorož, 23–26 November 2011 [Selected Papers],, University of Primorska, Faculty of Management Koper.
    9. Ohiomah, Alhassan & Andreev, Pavel & Benyoucef, Morad & Hood, David, 2019. "The role of lead management systems in inside sales performance," Journal of Business Research, Elsevier, vol. 102(C), pages 163-177.
    10. Mohd Azhar & Ruksar Ali & Sheeba Hamid & Mohd Junaid Akhtar & Mohd Nayyer Rahman, 2022. "Demystifying the effect of social media eWOM on revisit intention post-COVID-19: an extension of theory of planned behavior," Future Business Journal, Springer, vol. 8(1), pages 1-16, December.
    11. Susmita Chatterjee & Bibek Ray Chaudhuri & Debabrata Dutta, 2019. "Determinants of Adoption of New Technology in Telecom Sector: A Structural Equation Modeling Approach," Global Business Review, International Management Institute, vol. 20(1), pages 166-178, February.
    12. Allam, Hesham & Bliemel, Michael & Spiteri, Louise & Blustein, James & Ali-Hassan, Hossam, 2019. "Applying a multi-dimensional hedonic concept of intrinsic motivation on social tagging tools: A theoretical model and empirical validation," International Journal of Information Management, Elsevier, vol. 45(C), pages 211-222.
    13. Fernández-Bonilla, Fernando & Gijón, Covadonga & De la Vega, Bárbara, 2022. "E-commerce in Spain: Determining factors and the importance of the e-trust," Telecommunications Policy, Elsevier, vol. 46(1).
    14. Cristina Gallego-Gómez & Carmen De-Pablos-Heredero & José Luis Montes-Botella, 2021. "Change of Processes in the COVID-19 Scenario: From Face-to-Face to Remote Teaching-Learning Systems," Sustainability, MDPI, vol. 13(19), pages 1-11, September.
    15. Baqar Ali Zardari & Zahid Hussain & Aijaz Ahmed Arain & Wajid H. Rizvi & Muhammad Saleem Vighio, 2021. "Development and Validation of User Experience-Based E-Learning Acceptance Model for Sustainable Higher Education," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
    16. Mütterlein, Joschka & Kunz, Reinhard E. & Baier, Daniel, 2019. "Effects of lead-usership on the acceptance of media innovations: A mobile augmented reality case," Technological Forecasting and Social Change, Elsevier, vol. 145(C), pages 113-124.
    17. Higueras-Castillo, Elena & Kalinic, Zoran & Marinkovic, Veljko & Liébana-Cabanillas, Francisco J., 2020. "A mixed analysis of perceptions of electric and hybrid vehicles," Energy Policy, Elsevier, vol. 136(C).
    18. Reineke, Nicolas, 2016. "The Implementation of integrated Management Information Systems in the Human Resource Management: An empirical Study of Success Factors," Journal of Applied Leadership and Management, Hochschule Kempten - University of Applied Sciences, Professional School of Business & Technology, vol. 4, pages 67-81.
    19. Darrell Carpenter & Alexander McLeod & Chelsea Hicks & Michele Maasberg, 0. "Privacy and biometrics: An empirical examination of employee concerns," Information Systems Frontiers, Springer, vol. 0, pages 1-20.
    20. Smith, Carlo D. & Mentzer, John T., 2010. "Forecasting task-technology fit: The influence of individuals, systems and procedures on forecast performance," International Journal of Forecasting, Elsevier, vol. 26(1), pages 144-161, January.

    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:spr:joiaen:v:12:y:2023:i:1:d:10.1186_s13731-023-00323-x. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.