Restricted accessResearch articleFirst published online 2023
Influential Factors in the Implementation of an Educational Blockchain System in the Democratic Republic of the Congo: Case of Higher Education Institutions
Blockchain has gained significant attention and use beyond its initial purpose. It is recognized as a disruptive technology in many domains, including education. Its interest in education has grown due to its ability to prevent fraud in academic documents. This research aimed to identify influential factors in implementing a Blockchain system in DR Congo higher education using the combination of Technology Acceptance Model & Technology-Organization-Environment. Data was collected through an online survey of 355 respondents from public and private institutions of the country. The findings provide insight into the factors influencing Blockchain adoption and highlight its importance in addressing the issue.
AlammaryA.AlhazmiS.AlmasriM.GillaniS. (2019). Blockchain-based applications in education: A systematic review. Applied Sciences, 9(12), 2400. https://doi.org/10.3390/app9122400
2.
AlbrechtS.ReichertS.SchmidJ.StrükerJ.NeumannD.FridgenG. (2018). Dynamics of blockchain implementation: A case study from the energy sector. In Proceedings of the 51st Hawaii International Conference on System Sciences, Hilton Waikoloa Village, HI, USA, 3–6 January 2018.
3.
AndersonJ. C.GerbingD. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103, 411–423.
AslamaJ.SaleemaA.Tariq KhanbN.KimB. Y. (2021). Factors influencing Blockchain adoption in supply chain management practices: A study based on the oil industry. Journal of Innovation & Knowledge, 6, 124–134. https://doi.org/10.1016/j.jik.2021.01.002
6.
AttaranM. (2022). Blockchain technology in healthcare: Challenges and opportunities. International Journal of Healthcare Management, 15(1), 70–83. https://doi.org/10.1080/20479700.2020.1843887
7.
BahramiM.MovahedianA.DeldariA. (2020). A comprehensive blockchain-based solution for academic certificates management using smart contracts. In 2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) (pp. 573–578). IEEE.
8.
BentlerP. M.BonettD. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606. https://doi.org/10.1037/0033-2909.88.3.588
9.
BrowneM. W.CudeckR. (1993). Alternative ways of assessing model fit. In BollenK. A.LongJ. S. (Eds.), Testing tructural equation models (pp. 136–162). Sage.
10.
BentlerP. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107, 238–246. 10.1037/0033-2909.107.2.238
DavisF. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
13.
EducationG.CitizenshipG. (2022). 4 ‘Education is the Most Powerful Weapon Which You Can Use to Change the World’(Mandela). Challenges in Early Years and Primary Education: Employing critical thinking skills during turbulent times.
14.
EtshimR. (2017). Collaboration between higher education and labor market in Kinshasa, DR Congo. Journal of International Education and Leadership, 7(1), n1.
15.
FolkinshteynD.LennonM. (2016). Braving bitcoin: A technology acceptance model (TAM) analysis. Journal of Information Technology Case and Application Research, 18(4), 220–249. https://doi.org/10.1080/15228053.2016.1275242
16.
FornellC.LarckerD. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312
17.
GholamiZ.AbdekhodaM.GavganiV. Z. (2018). Determinant factors in adopting mobile technology-based services by academic librarians. DESIDOC Journal of Library & Information Technology, 38(4), 271–277.
18.
GreschJ.RodriguesB. B.ScheidE. J.KanhereS. S.StillerB. (2018). The proposal of a Blockchain-based architecture for transparent certificate handling. In Business information systems (pp. 185–196). Springer.
19.
JrHairFJ.. (1998). Multivariate data analysis with readings. Prentice-Hall.
20.
HairJ. F.BlackW. C.BabinB. J.AndersonR. E.TathamR. L. (2009). Multivariate data analysis (7th ed.). Pearson Education Limited.
21.
HairJ. F.SarstedtM.MatthewsL. M.RingleC. M. (2016). Identifying and treating unobserved heterogeneity with FIMIX-PLS: Part I – method. European Business Review, 28(1), 63–76.
22.
HintonP. R.BrownlowC.McMurraryI.CozensB. (2004). SPSS explained. Routledge Inc.
23.
IftikharW.VistroD. M.MahmoodZ. (2021). Blockchain technology adoption by Malaysian higher education institutes: A perspective of integrated TAM model and TOE framework. Atlantis Highlights in Computer Sciences, 4. https://doi.org/10.2991/ahis.k.210913.077
24.
JaoudeJ. A.SaadeR. (2017). Blockchain factors for consumer acceptance. International Journal of Business Management Technology, 10(10), 16–29.
JoreskogK. G.SorbomD. (1984). Advances in factor analysis and structural equation models. Rowman & Littlefield Publishers.
27.
KamarulzamanM. S.HassanN. H.BakarN. A. A.MaaropN.SamyG. A.-L. N.AzizN. (2021). Factors influencing blockchain adoption in government organization: A proposed framework. International Conference on Computer & Information Sciences. pp. 366–371. https://doi.org/10.1109/ICCOINS49721.2021.9497196
28.
KambleS.GunasekaranA.ArhaH. (2019). Understanding the Blockchain technology adoption in supply chains-Indian context. International Journal of Production Research, 57, 2009–2033.
29.
KaramchandaniA.SrivastavaS. K.SrivastavaR. K. (2020). Perception-based model for analyzing the impact of enterprise blockchain adoption on Scm in the Indian service industry. International Journal of Information Management, 52, 102019.
30.
KhaledM. (2021). Blockchain traceability to ensure the veracity of diplomas. International Journal of Intelligent Information Systems, 10, 60–68. https://doi.org/10.11648/j.ijiis.20211004.14
31.
KnauerF.MannA. (2019). What is in it for me? Identifying drivers of Blockchain acceptance among German consumers. The Journal of the British Blockchain Association, 3(1), 1–16. https://doi.org/10.31585/jbba-3-1-(1)2020
32.
KrasnovaH.WidjajaT.BuxmannP.WenningerH.BenbasatI. (2015). Research note—why following friends can hurt you: An exploratory investigation of the effects of envy on social networking sites among vollege-age users. Information Systems Research, 26(3), 585–605. https://doi.org/10.1287/isre.2015.0588
LiX.LaiP. L.YangC. C.YuenK. F. (2021). Determinants of blockchain adoption in the aviation industry: Empirical evidence from Korea. Journal of Air Transport Management, 97, 102139.
35.
LiaoC.TsouC.HuangM. (2007). Factors influencing the usage of 3G mobile services in Taiwan. Online Information Review, 31(6), 759–774. https://doi.org/10.1108/14684520710841757
36.
MalikS.ChadharM.VatanasakdakulS.ChettyM. (2021). Factors affecting the organizational adoption of blockchain technology: Extending the technology–organization–environment (TOE) framework in the Australian context. Sustainability, 13, 9404. https://doi.org/10.3390/su13169404
MokonziG.KadongoM. (2010). Democratic Republic of the Congo: Effective Delivery of public services in the education sector. Open Society Institute. A study of AfriMAP and the Open Society Initiative for Southern Africa. Retrieved from http://www.afrimap.org/english/images/report/AfriMAP_DRC_Edn_full_EN.pdf
40.
MuthénB., & Kaplan, (1985). A comparison of some methodologies for the factor analysis of non-normal Likert variables. British Journal of Mathematical and Statistical Psychology, 38, 171–189.
41.
MuseeN. M. (2015). An Academic Certification Verification System Based on Cloud Computing Environment [PhD thesis]. University of Nairobi.
42.
NuryyevG.WangY.-P.AchyldurdyyevaJ.JawB.-S.YehY.-S.LinH.-T.WuL.-F. (2020). Blockchain technology adoption behavior and sustainability of the business in tourism and hospitality SMEs: An empirical study.Sustainability, 12(3), 1256. https://doi.org/10.3390/su12031256
43.
PsaillaG.WagnerR. (2007). E-commerce and web technologies. Springer.
44.
PorterC. E.DonthuN., 2006. Using the technology acceptance model to explain how attitudes determine Internet usage: The role of perceived access barriers and demographics. Journal of Business Research, 59, 999–1007.
45.
RaimundoR.RosárioA. (2021). Blockchain system in higher education. European Journal of Investigation in Health, Psychology and Education, 11(1), 276–293. https://doi.org/10.3390/ejihpe11010021
46.
ReinartzW.HaenleinM.HenselerJ. (2009). An empirical comparison of the efficacy of covariance-based and variance-based SEM. International Journal of Research in Marketing, 26, 332–344.
SciarelliM.PriscoA.GheithM. H.MutoV. (2021). Factors affecting the adoption of Blockchain technology in innovative Italian companies: An extended TAM approach. Journal of Strategy and Management, ahead-of-print(ahead-of-print). https://doi.org/10.1108/JSMA-02-2021-0054
49.
SpirtesP.ScheinesR.GlymourC. (1990). Simulation studies of the reliability of computer-aided model specification using the TETRAD II, EQS, and LISREL programs. Sociological Methods & Research, 19(3), 3–66.
50.
TashkandiA. N.Al-JabriI. M. (2015). Cloud computing adoption by higher education institutions in Saudi Arabia: Analysis based on TOE. Cluster Computing, 18(4), 1527–1537. https://doi.org/10.1007/s10586-015-0490-4
51.
TeferraD.AltbachP. G. (2004). African higher education: Challenges for the 21st century. Higher Education Journal, 61(1). Retrieved from http://www.jstor.org/stable/4151555
WilliamsB.OnsmanA.BrownT. (2010). Exploratory factor analysis: A five-step guide for novices. Australasian Journal of Paramedicine, 8, 1–13. https://doi.org/10.33151/ajp.8.3.93
57.
World Bank. (2005). Education in the democratic Republic of Congo: Priorities and options for regeneration. The World Bank Journal. https://doi.org/10.1596/978-0-8213-6121-4
58.
World Bank Report No 127 (2008). Governance, Management, and Accountability in Secondary Education in Sub-Saharan Africa. Africa Human Development Series. The International Bank for Reconstruction and Development. The World Bank.
59.
ZainudinA. (2012). A handbook on SEM: Structural equation model- ling using amos graphics (4th ed.). University Technology MARA Press.
60.
ZhaoF.Sajid KhanM. (2013). An empirical study of E-government service adoption: Culture and behavioral intention. International Journal of Public Administration, 36(10), 710–722. https://doi.org/10.1080/01900692.2013.791314
