ARID ZONE JOURNAL OF ENGINEERING, TECHNOLOGY & ENVIRONMENT AZOJETE September 2023. Vol. 19(3):573-584 Published by the Faculty of Engineering, University of Maiduguri, Maiduguri, Nigeria. Print ISSN: 1596-2490, Electronic ISSN: 2545-5818 www.azojete.com.ng Corresponding author’s e-mail address: yamusajf@yahoo.com 573 ORIGINAL RESEARCH ARTICLE TECHNOLOGY AWARENESS OF ARTIFICIAL INTELLIGENCE (AI) APPLICATION FOR PUBLIC PROCUREMENT PROCESS IN NIGERIA M. A. Yamusa1,2*, H. S. Lawal2, M. Abdullahi1,2 and Z. H. Ishaq3 1Public Procurement Research Centre, Ahmadu Bello University Zaria, Kaduna, Nigeria. 2Department of Quantity Surveying, Ahmadu Bello University, Zaria, Kaduna, Nigeria 3Department of Building, Ahmadu Bello University, Zaria, Kaduna, Nigeria *Corresponding author’s email address: yamusajf@yahoo.com 1.0 Introduction The public procurement process of acquiring goods, works and services has been noted to be suffering from inefficiencies such as corruption, absence of transparency, faulty procedures, and dysfunctional bureaucratic ties (Yap et al., 1994). This led to several calls for transition from the manual paper-based approach to a digitised method (Expert Group Meeting Report; EGMR, 2011). The transition came along with numerous positive feedbacks. These include reduced procurement expenses, expanded aptitude as well as transparency, abridged corruption and enhanced accountability (EGMR, 2011; eTEG, 2012). Several efforts have been made to transit from the manual paper-based procurement method towards digitising the procurement approach. This started with the development of one-way ARTICLE INFORMATION ABSTRACT The public procurement process of acquiring goods, works and services has been observed to be suffering from inefficiencies in the forms of corruption cases, absence of transparency, faulty procedures, and dysfunctional bureaucratic ties. In Nigeria, it was discovered that the public procurement process has the potential of reaping the benefits of Artificial Intelligence (AI). However, the level of awareness of the public procurement practitioners of the significance of incorporating AI in procurement is yet to be studied. This study assessed the awareness of Artificial Intelligence application for public procurement processes in Nigeria. Data was collected using questionnaire survey. The questionnaire was distributed to public procurement practitioners with at least 5 years of experience in procurement. Data was analysed using Mean, Standard Deviation, and Relative importance index. Analysis of variance and Independent t-test was then used to ascertain the level of awareness of the respondents based on their attributes. The study discovered information about Artificial intelligence is quite vast as the parameter ‘I have heard about AI’ got the highest ranking with mean score of 3.63 and RII of 72.58%, while ‘I use AI for procurement processes’ to be the lowest ranking attribute with mean score of 1.50 and RII of 30.00% meaning even though information is available, the usage of AI for procurement is quite low. Additionally, the results show that while AI is a popular concept within procurement organisations, majority of the procurement practitioners have little knowledge of its application in public procurement. The research recommends that, public procurement organisations should develop the capacity of their employees on the utilisation of AI in procurement process. © 2023 Faculty of Engineering, University of Maiduguri, Nigeria. All rights reserved. Submitted 14 May, 2023 Revised 12 July, 2023 Accepted 20 July, 2023 Keywords: public procurement artificial intelligence awareness process Nigeria http://www.azojete.com.ng/ mailto:yamusajf@yahoo.com mailto:yamusajf@yahoo.com Arid Zone Journal of Engineering, Technology and Environment, Sept, 2023; Vol. 19(3):573-584. ISSN 1596-2490; e-ISSN 2545-5818; www.azojete.com.ng Corresponding author’s e-mail address: yamusajf@yahoo.com 574 information systems that digitise only tender advertisement. This was followed with more encompassing systems which were developed to digitise the entire front-end and back-end procedures of the procurement system (Betts et al., 2006). Studies were carried out to address different aspects of the systems development. They include design and implementation (Lai et al., 2007); interoperability and integration across manifold platforms (Noor et al., 2003); legal and security requirements (Du et al., 2004a.b; Betts et al., 2006); and tender evaluation through decision support system (Padumansa and Rehan, 2009; Noor and Man, 2010; and Noor and Mohemmad, 2010); and e-Tendering research in Africa (Adebiyi et al., 2010; Muchiri et al., 2015; and Afolabi et al., 2017). More recently, Artificial Intelligence (AI) is being used to automate procurement processes. This is because the procurement lifecycle generates tonnes of data, and AI is heavily reliant on data. Studies have been conducted where AI has been applied to different procurement processes including analysis of spend (Domingos et al., 2016), prequalification and selection of contractor/supplier (Khosrowshahi, 1999; Lam et al., 2000; Lam et al., 2001; Elazouni, 2006; and Zhang et al., 2016), evaluation and classification of tender (Kim, et al., 2018; Ovsyanniko and Domashova, 2020) as well as in contract management (Hassan and Le, 2020). In Nigeria, several efforts have been made to digitise the public procurement lifecycle (Adebiyi et al., 2010; Afolabi et al., 2017; and Abdullahi et al., 2022, 2020, 2019). Yamusa et al. (2020) found that the public procurement process in Nigeria has the potential of reaping the benefits of AI. This was further confirmed by studies who modelled requirements and developed machine learning models for a web-based e-procurement system for Nigerian public procuring entities (Abdullahi et al., 2024; Yamusa et al., 2023). However, the level of awareness of the public procurement practitioners of the significance of incorporating AI in the conduct of their daily procurement tasks is yet to be studied. It is important to establish whether public procurement users are aware of how to use AI in various public procurement processes. Hence, this study aims to determine the level of awareness of procurement practitioners of using AI for procurement processes. This study will reveal to public procuring entities the benefits of AI methods in carrying out procurement processes effectively. 2.0 Methodology A quantitative research approach was adopted for this study, where questionnaire survey was used. Thirteen statements regarding awareness level of AI are established (Basaif et al., 2020) and used in designing the questionnaire for data collection. The questionnaire was distributed purposively to public procurement practitioner with at least 5 years of experience involved in the procurement of goods, works and services. A Likert scale (5-point) was adopted for gauging the variables of the questionnaire where 1 represents “Totally Disagree” and 5 represents “Totally Agree”. The sample size was determined using the Krejcie and Morgan (1970)’s formula in equation 1: 𝑆 = 𝑍2𝑁𝑃(1−𝑃) 𝑑2(𝑁−1)+𝑋2𝑃(1−𝑃) (1) file:///C:/user/Downloads/azojete143/www.azojete.com.ng mailto:yamusajf@yahoo.com Yamusa et al: Technology Awareness of Artificial Intelligence (AI) Application for Public Procurement Process in Nigeria. AZOJETE, 19(3):573- 584. ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng Corresponding author’s e-mail address: yamusajf@yahoo.com 575 Where: S = required sample size X2 = table of value of chi-square for 1 degree of freedom at the desired confidence level (3.841) N = the population size P = the population proportion (assumed to be 0.50) d = degree of accuracy expressed as a proportion (0.05) A minimum sample size of 186 was determined. The questionnaires were sent via online using e- mails and social media platforms. 62 valid responses amounting to approximately 32% of the total distributed were retrieved and found to be adequate for analysis. This is because Moser and Kalton (1979) noted that amount of feedback is fitting as it yields a return percentage of 30-40%. Data collected was analysed using SPSS (Statistical Package for the Social Sciences) Version 23 (IBM). Firstly, the frequencies, measures of central tendency (the Mean), measurements of dispersion based on the Mean (Standard Deviation), and Relative Important Index (RII) were determined. The RII was used in ranking the variables according to the retrieved responses to the level of awareness on AI. The RII was calculated using the Field (2013) formula in equation 2: 𝑅𝐼𝐼 = Σ𝑊 𝐴∗𝑁 (2) Where: RII = Relative Important Index W = the weight of each factor as obtained by the respondents (1 to 5). A = the highest weight (5 in this questionnaire). N = the overall number of respondents. The RII has a range of 0 to 1, where 0 was not included, and the variables are presented with the highest on top and the lowest at the bottom. The natural value of RII was determined and the total average RII of the awareness attributes/statements was compared against the neutral RII to make decision on the level of awareness of the practitioners. Total average RII of the awareness attributes ≥ the neutral RII implies high awareness while total average RII of awareness variables < the neutral RII implies low awareness. This method can be found in similar studies by Enhassi et al. (2019) and Basaif et al. (2020). Inferential statistical analysis using analysis of variance (ANOVA) (for attributes with three groups) and Independent t-test (for attributes with two groups) was further conducted to ascertain the level of awareness of the respondents based on their various attributes. http://www.azojete.com.ng/ mailto:yamusajf@yahoo.com mailto:yamusajf@yahoo.com Arid Zone Journal of Engineering, Technology and Environment, Sept, 2023; Vol. 19(3):573-584. ISSN 1596-2490; e-ISSN 2545-5818; www.azojete.com.ng Corresponding author’s e-mail address: yamusajf@yahoo.com 576 3.0 Results and Discussion 3.1 Demographic Information of Respondents Table 1 presents us with demographic information of the respondents of this study. Table 1: Respondents' Profile Attributes Classification Frequency Percentage Years of Existence of Procuring Entity 1-5 years 12 19.4 6-10 years 12 19.4 11-15 years 26 41.8 Above 15 years 12 19.4 Annual Turnover of PE 50-250 million 14 22.6 501-750 million 16 25.8 Above 750 million 32 51.6 Gender Female 12 19.4 Male 50 80.6 Academic Qualification Bachelor 22 35.5 Masters 32 51.6 Others 8 12.9 Rank Operational management level 14 22.6 Middle management level 30 48.4 Senior/strategic management 18 29 Years of Experience At least 5 years 30 48.4 6-10 years 14 22.6 11-15 years 12 19.4 Above 15 years 4 6.4 BPP Conversion Status No 14 22.6 Yes 48 77.4 Other Relevant Certification No 12 19.4 Yes 50 80.6 Status of Certification Fellow 8 12.9 Corporate member 24 38.7 Probationer member 4 6.4 Other 25 41.9 Source: Authors’ Analysis (2022) The result shows that, 41.8% of the PE have been in existence for about 11-15 years and 19.4 have been in existence for over 15 years hence, 61.2% of the procurement entities have been in existence for over 10 years which adds credibility to the findings of this study. Additionally, it was discovered that the PEs are engaged in procurement activities with 51.6% having an annual file:///C:/user/Downloads/azojete143/www.azojete.com.ng mailto:yamusajf@yahoo.com Yamusa et al: Technology Awareness of Artificial Intelligence (AI) Application for Public Procurement Process in Nigeria. AZOJETE, 19(3):573- 584. ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng Corresponding author’s e-mail address: yamusajf@yahoo.com 577 turnover above 750 million naira and 25. 8% having an annual turnover of 500 to 700 million naira. Results received from the respondents show that male respondents constitute 80.6% whereas the female was only at 19.4% which shows that the number of male procurement officers far outweighs that of female officers. Interestingly, 87.1% of the respondents are having a bachelor or master’s degree hence, majority of procurement officers are graduates. Middle level managers made up 48.4% of the respondents while strategic managers made 29% of the respondents, this implies that people with the desired information about procurement administration make majority of the respondents. which is further buttressed by the finding that 51.6% of the respondents have an experience above 5 years. Also, 77.4% have attended the conversion training offered by the Bureau of Public Procurement. However, 80.6% of the respondents hold other relevant certification, where 38.7% of them are corporate members and 12.9% of them are fellows. These qualifications and level of experience in terms of years, education and conversion training helped in shaping the level of accuracy of this study. 3.2 Level of Awareness of the Public Procurement Practitioners of Using AI for Procurement Processes This section assesses the level of awareness of AI by public procurement practitioners in Nigeria. The established set of 13 statements presented in the questionnaire were used in assessing the respondents’ level of awareness of using AI for procurement processes. Means, Standard Deviations, RII, were used to analyse the data and results are presented in Table 2. Table 2: Awareness of the Public Procurement Practitioners of Using AI for Procurement Processes Attributes/statements Mean SD RII (%) Rank I have heard about AI 3.63 1.462 72.58 1 I think AI can help and add value to my daily work 3.44 1.500 68.71 2 I have knowledge about the concept of AI technology 3.35 1.380 67.10 3 I think AI will be a useful tool for procurement processes 3.11 1.404 62.26 4 I know that AI technology is important for carrying out procurement processes in the Nigerian construction industry 3.05 1.431 60.97 5 I have read some research and studies about AI 2.95 1.498 59.03 6 I have knowledge on how to use AI technology tools 2.34 1.070 46.77 7 I practice AI in my job 1.94 1.158 38.71 8 People within my organisation are talking about using AI for procurement processes 1.74 .626 34.84 9 I have attended training on AI 1.69 .781 33.87 10 My Organisation provides formal training on AI including follow-up programs 1.65 .726 32.90 11 I have taken some courses about AI 1.60 .664 31.94 12 I use AI for procurement processes 1.50 .671 30.00 13 Total Average 2.46 49.21 http://www.azojete.com.ng/ mailto:yamusajf@yahoo.com mailto:yamusajf@yahoo.com Arid Zone Journal of Engineering, Technology and Environment, Sept, 2023; Vol. 19(3):573-584. ISSN 1596-2490; e-ISSN 2545-5818; www.azojete.com.ng Corresponding author’s e-mail address: yamusajf@yahoo.com 578 Source: Authors’ Analysis (2022) From Table 2, according to the mean score and relative importance index (RII) of the awareness attributes, ‘I have heard about AI, I think AI can help and add value to my daily work and I have Knowledge about the concept of AI technology are the top three attributes with mean score of 3.64, 3.44, 3.35 AND RII of 72.58, 68.71 and 67.1 respectively. The study also discovered that the factors with lowest mean score and RII are My organisation provides formal training on AI including follow up, I have taken some courses about AI and I use AI for procurement processes with low mean scores of 1.65, 1.60, 1.5 and low RII of 32.9, 31.94 and 30.00 respectively. This means that despite the fact that most procurement officers are aware of AI and its potential to make their work better, they receive very low support on training from their organisation and also do not make personal efforts to learn about AI hence, they barely use it in procurement process. The overall average mean scores of the 13 statements used to assess the respondents’ level of awareness of AI in procurement process is 2.46 which implies that the awareness of artificial intelligence in procurement is low, this is further buttressed by the average Relative importance index of 49.21 which is below the neutral RII of 60 The result agrees with Basaif et al. (2022) who found that, the awareness of AI is low in the Malaysian construction industry. Moreso, there is lack of knowledge of the application of AI among practitioners (Basaif et al., 2020). 3.3 Awareness of the Public Procurement Practitioners of Using AI for Procurement Processes Based on the Respondents’ Attributes This section assesses the differences in the level of awareness in the use of AI by public procurement practitioners in Nigeria based on their demographic classifications. The ANOVA test was used to check if there is significance difference in the level of awareness of the Procurement officers based on Years of Existence of the Procurement Entity, Annual Turnover of the Procurement entity, Academic Qualification, Rank and Years of Experience and Status of Certification. From Table 3, it can be seen that the attribute Years of Existence showed no significant difference in the respondents’ awareness of ‘I have taken some courses about AI’, ‘I have attended training on AI’ and ‘People within my organisation are talking about using AI for procurement processes’. For the other 10 factors, the result shows statistical significant difference in the awareness of the respondents as the significance level is less than 0.05. Based on the Annual Turnover of PE, six factors, including ‘I have knowledge about the concept of AI technology’, ‘I have read some research and studies about AI’, ‘I have taken some courses about AI’, ‘I have heard about AI’, ‘I think AI can help and add value to my daily work’ and ‘My Organisation provides formal training on AI including follow-up programs’ reveal statistical significance difference in the level of awareness of the respondents. The remaining 7 factors have no statistical significant difference. file:///C:/user/Downloads/azojete143/www.azojete.com.ng mailto:yamusajf@yahoo.com Yamusa et al: Technology Awareness of Artificial Intelligence (AI) Application for Public Procurement Process in Nigeria. AZOJETE, 19(3):573- 584. ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng Corresponding author’s e-mail address: yamusajf@yahoo.com 579 Table 3: Awareness of the Public Procurement Practitioners Using the Respondents’ Attributes Attributes/statements Years of Existence of PE Annual Turnover of PE Academic Qualification Rank Years of Experience BPP Conversion Status Status of Certification Sig. (.05) I have knowledge about the concept of AI technology 0.000 0.001 0.000 0.031 0.007 0.506 .584 I have read some research and studies about AI 0.000 0.000 0.001 0.481 0.703 0.004 .000 I have taken some courses about AI 0.061 0.022 0.000 0.029 0.000 0.001 .025 I have knowledge on how to use AI technology tools 0.008 0.161 0.004 0.003 0.095 0.044 .000 I know that AI technology is important for carrying out procurement processes in the Nigerian construction industry 0.000 0.233 0.001 0.608 0.225 0.012 .000 I have heard about AI 0.000 0.003 0.004 0.101 0.631 0.020 .000 I have attended training on AI 0.064 0.983 0.002 0.056 0.017 0.002 .208 I practice AI in my job 0.037 0.961 0.168 0.045 0.857 0.000 .185 I think AI can help and add value to my daily work 0.000 0.009 0.000 0.718 0.294 0.161 .000 My Organisation provides formal training on AI including follow-up programs 0.038 0.010 0.004 0.067 0.000 0.000 .114 I use AI for procurement processes 0.000 0.339 0.146 0.146 0.632 0.502 .004 People within my organisation are talking about using AI for procurement processes 0.086 0.191 0.044 0.007 0.340 0.946 .000 I think AI will be a useful tool for procurement processes 0.000 0.793 0.017 0.000 0.135 0.896 .028 Source: Authors’ Analysis (2022) Respondents’ Academic Qualification affects their level of awareness. This is obvious as eleven factors have been found to be significantly different. Only ‘I practice AI in my job’ and ‘I use AI http://www.azojete.com.ng/ mailto:yamusajf@yahoo.com mailto:yamusajf@yahoo.com Arid Zone Journal of Engineering, Technology and Environment, Sept, 2023; Vol. 19(3):573-584. ISSN 1596-2490; e-ISSN 2545-5818; www.azojete.com.ng Corresponding author’s e-mail address: yamusajf@yahoo.com 580 for procurement processes’ have shown no statistical significant difference in the level of awareness of the respondents. Based on the Rank of the respondents, 6 factors which include ‘I have knowledge about the concept of AI technology’, ‘I have taken some courses about AI’, ‘I have knowledge on how to use AI technology tools’, ‘I practice AI in my job’, ‘People within my organisation are talking about using AI for procurement processes’ and ‘I think AI will be a useful tool for procurement processes’ have been found to reveal statistical significance difference. The other factors have a significance level greater than 0.05. The Years of Experience of the respondents has shown little effect on the level awareness of the respondents with only four have statistically significantly different. ‘I have knowledge about the concept of AI technology’, ‘I have taken some courses about AI’, ‘I have attended training on AI’ and ‘My Organisation provides formal training on AI including follow-up programs’ have a significant level less than 0.05. The rest of the nine factors have a significance level above 0.05. The BPP Conversion Status of the respondents has shown a significant level of impact on the awareness of the respondents on the use of AI in public procurement process. Five factors including ‘I have knowledge about the concept of AI technology’, ‘I think AI can help and add value to my daily work’, ‘I use AI for procurement processes’, ‘People within my organisation are talking about using AI for procurement processes’ and ‘I think AI will be a useful tool for procurement processes’ have a significance level greater than 0.05. This indicates that there is no significant difference in the respondents’ awareness of these factors. However, there is high significance level of awareness by the respondents on the remaining eight factors with a significance level less than 0.05. ‘I have knowledge about the concept of AI technology’, ‘I have attended training on AI’, ‘I practice AI in my job’ and ‘My Organisation provides formal training on AI including follow-up programs’ have shown no statistical significant difference with a significance level higher than 0.05 for the Status of Certification attribute. The remaining nine factors have a significance level lower than 0.05. This shows that the awareness of the respondents in these factors are statistically significantly different. 4.0 Conclusion The result of the study indicates that most procurement officers have heard about AI, they believe AI can add value to their daily work and have knowledge about the concept of AI however procurement officers barely attend any training on AI, this is further buttressed by the finding of this study that indicates that organisations hardly provide formal training on AI also, procurement officers barely take courses on AI and its usage for procurement processes is very low. The study discovered that there is significant difference in the respondents level of awareness of artificial intelligence based on their Years of Existence, Academic Qualification, BPP Conversion, Status of Certification, Annual Turnover and Rank. On the contrary, the study found out that file:///C:/user/Downloads/azojete143/www.azojete.com.ng mailto:yamusajf@yahoo.com Yamusa et al: Technology Awareness of Artificial Intelligence (AI) Application for Public Procurement Process in Nigeria. AZOJETE, 19(3):573- 584. ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng Corresponding author’s e-mail address: yamusajf@yahoo.com 581 there was no significance difference on the awareness level based on Years of Experience of the respondents. The research concludes that the level of awareness of Application of Artificial intelligence in public procurement is low owing to the overall low mean score of 2.46 and a 49.21 score of relative importance., The analysis of variance also shows that there is a significant difference in the awareness level of application of AI in public procurement based on the difference in demographics of the procurement officers. The study recommends that, public procurement organisations as well as the government should demonstrate commitment to develop the capacity of their employees on the utilisation of AI in procurement process. Emphasis should be paid on the newly established public procurement organisations. Also, special attention should be given to public procurement professionals with low Academic Qualification and Status of Certification, as well as professionals with no BPP Conversion. Disclosure Statement No potential conflict of interest was reported by the authors. Acknowledgement This study was carried out under the Public Procurement Research Centre of Ahmadu Bello University, Zaria. References Abdullahi, B., Ibrahim, YM., Ibrahim, AD. and Bala, K. 2022. Development of web-based e- Tendering system for Nigerian public procuring entities. International Journal of Construction Management, 22(2): 278-291 DOI: 10.1080/15623599.2019.1620492. 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