Neupane explored the potential of public e-procurement technologies to reduce corruption in the public
procurement process. It analyses the risk factors of corruption in the government procurement
processes such as in project planning, product design and documentation, tender process, contract
awards, and accounting and auditing. The results indicate that anti-corruption capabilities of public eprocurement, particularly the automation and audit trail capabilities can potentially increase the
transparency and accountability of the government procurement process.
Citation: Neupane, Soar, Vaidya, & Yong. (2012). ROLE OF PUBLIC E-PROCUREMENT TECHNOLOGY TO
REDUCE CORRUPTION IN GOVERNMENT PROCUREMENT. Retrieved September 9, 2023, from
https://research.usq.edu.au/item/q17y5/role-of-public-e-procurement-technology-to-reducecorruption-in-government-procurement
This study found that e-procurement can have a positive impact on organizational performance, such as
reducing costs, improving efficiency, and increasing transparency
Gardenal. (2013). A MODEL TO MEASURE E-PROCUREMENT IMPACTS ON ORGANIZATIONAL
PERFORMANCE. Journal of Public Procurement., Vol. 13(Issue 2), p215-242.
https://doi.org/10.1108/JOPP-13-02-2013-B003
Data cleaning and data wrangling were conducted to prepare the dataset for machine learning and
ensure more accurate clustering results. A well-prepared dataset speeds up data analysis and enhances
the accuracy of predictions and insights. Maharana (2022) demonstrated how the issue of overfitting
might be improved through the use of multiple data augmentation. Missing values were selectively
addressed to maintain both comprehensiveness and reliability for tasks like analysis and machine
learning. Using the median to fill in missing values provides a more reliable dataset, as it is less sensitive
to outliers than the mean. In the same study, Maharana the study showed the importance of data
preprocessing. Accordingly, if the data has more than 20% of data missing, simply eliminating the data
set would improve the model’s robustness.
Maharana, Mondal, & Nemade. (2022, June). A review: Data pre-processing and data augmentation
techniques. Global Transitions Proceedings, Volume 3(Issue 1), Pages 91-99.
https://doi.org/10.1016/j.gltp.2022.04.020
Clustering helps segment procurement activities into groups with similar characteristics, simplifying the
analysis. Nicolescu showed in this study that clustering highlighted specific barriers and enablers that
were deemed most significant by respondents. Targeted policy measures can be applied to specific
clusters for more effective results.
Simion, C.-P., Nicolescu, C., & Vrîncuț, M. (2019). Green Procurement in Romanian Construction Projects.
A Cluster Analysis of the Barriers and Enablers to Green Procurement in Construction Projects from the
Bucharest-Ilfov Region of Romania. Sustainability, 11(22), 6231. MDPI AG. Retrieved from
http://dx.doi.org/10.3390/su11226231
Pandey (2014) examined the effects of data visualization by defining the circumstances under which data
visualization can make a message more persuasive, propose hypotheses, and perform quantitative and
qualitative analyses on studies conducted to test these hypotheses.
A. V. Pandey, A. Manivannan, O. Nov, M. Satterthwaite and E. Bertini, "The Persuasive Power of Data
Visualization," in IEEE Transactions on Visualization and Computer Graphics, vol. 20, no. 12, pp. 22112220, 31 Dec. 2014, doi: 10.1109/TVCG.2014.2346419.