Abstract
Research on operations analytics has focused on the design and execution of processes and projects. For projects in particular, the emphasis is on factors such as plans, stakeholders, and uncertainty; and their effects on the outcomes of projects. Little attention is paid to a variable of considerable importance: ethical behaviour, particularly corruption in large projects. This matters because studies of corruption have shown that corruption inflates project budgets (by sometimes 30%) and thus imposes an unproductive tax. This chapter builds on an original dataset of 38 very large government projects in Nigeria to demonstrate that corruption not only inflates project budgets but also distorts decisions, rendering other project management success drivers less effective. The chapter demonstrates that corruption has negative interactions with the positive effect of project success drivers and illustrates on a detailed case example what these interactions look like in practice.
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Notes
- 1.
The average completion probability of our 38 projects is, of course, 50%, because that is how the sample was constructed. However, as our regression is not linear, the success probability of the average parameter values is not the same as the average success probability; it is slightly offset.
References
Abimbola A (2015) About 12,000 federal projects abandoned across Nigeria. Premium Times, 16 November 2015 http://www.premiumtimesng.com/news/108450-about-12000-federal-projects-abandoned-across-nigeria.html
Adeyemo AA, Amade B (2016) Corruption and construction projects in Nigeria: manifestations and solutions. PM World J V(X):1–14
Alli-Balogun G (1988) Soviet technical assistance and Nigeria’s steel complex. J Mod Afr Stud 26(4):623–637
Amzat A (2018) How Nigerian government, Indians wreck multi-billion-dollar Delta Steel Company, rip off host communities and tax payers. The Guardian Nigeria, 12 February, downloaded from https://guardian.ng/features/how-nigerian-government-indians-wreck-multi-billion-dollar-delta-steel-company-rip-off-host-communities-and-tax-payers/
Cohen MA, Lee HL (1989) Resource deployment analysis of global manufacturing and distribution networks. J Manuf Oper Manag 2:81–104
Elinoff E (2017) Concrete and corruption: materialising power and politics in the Thai Capital. CITY 21(5):587–596. https://doi.org/10.1080/13604813.2017.1374778
Flyvbjerg B (2007) Policy and planning for large-infrastructure projects: problems, causes, cures. Environ Plann B: Plann Des 34:578–597
Flyvbjerg B (2014) What you should know about megaprojects and why: an overview. Proj Manag J 45(2):6–19
Hausman WH, Lee HL, Subramanian U (2013) The impact of logistics performance on trade. Prod Oper Manag 22(2):236–252
Jimoh IF, Loch CH, Sengupta K (2022) How very large government projects are damaging Nigeria and need reform. Palgrave MacMillan, Berlin
Kenny C (2006) Measuring and reducing the impact of corruption in infrastructure. World Bank Policy Research Working Paper 4099, December
Kenny C, Søreide T (2008) Grand corruption in utilities. Public Research Working Paper 4805, World Bank Economics Division, December
Locatelli G, Mariani G, Sainati T, Greco M (2017) Corruption in public projects and megaprojects: there is an elephant in the room! Int J Proj Manag 35:252–268
Loosemore M, Lim B (2015) Interorganizational unfairness in the construction industry. Constr Manag Econ 33(4):310–326
Matusevich M (2003) No easy row for a Russian Hoe: ideology and pragmatism in Nigerian-Soviet Relations, 1960–1991. Africa World Press, Trenton
Okafor P (2016) Ajaokuta Mines: concession back to GHNL, 8 years after without reparation. Vanguard, 11 August, downloaded from https://www.vanguardngr.com/2016/08/ajaokuta-mines-concession-back-to-ghnl-8-years-after-without-reparation/
Olatunji OA (2018) Causations of failure in megaprojects: a case study of the Ajaokuta Steel Plant Project. Front Eng Manag 5(3):334–346
Olawale A (2013) Renationalisation: the taking of Nigeria’s Ajaokuta Steel Company from GINL. Lagos Business School Case Study 213-056-1
Olken B (2006) Corruption perceptions vs. corruption reality. NBER Working Paper 12428
Oyeyinka O, Adeloye O (1988) Technological change and project execution in a develo** economy: evolution of Ajaokuta Steel Plant in Nigeria. Manuscript Report 187e, International Development Research Centre (IDRC), Canada, April
Reinikka R, Svensson J (2006) Using micro-surveys to measure and explain corruption. World Dev 34(2):359–370
Shleifer A, Vishny RW (1993) Corruption. Q J Econ 108:599–617
Tabish SZS, Jha KN (2011) Analyses and evaluation of irregularities in public procurement in India. Constr Manag Econ 29(3):261–274
Treisman D (2007) What have we learned about the causes of corruption from ten years of cross-national empirical research? Annu Rev Polit Sci 10(1):211–244
Udo B (2017) Ajaokuta belongs to Nigerian Government Despite Concession Dispute – Official. Premium Times, 16 November, downloaded from https://www.premiumtimesng.com/news/headlines/249555-ajaokuta-belongs-nigerian-govt-despite-concession-dispute-official.html
Unongo P (1980) Steel development and Nigeria’s power status. Lecture delivered by Paul Unongo at the Nigerian Institute of International Affairs, Victoria Island, Lagos on Thursday 24 July. The Institute, Issue 35 of Lecture Series, ISSN 0331–6262
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Appendices
Appendix 1: Project sample
Appendix 2: Questionnaire
Numerical questions were asked about planned and actual start and completion dates and planned and actual budgets. All other questions (except Q2a, which has a text answer) are answered in 7-point Likert scales.
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1.
The project had a well-defined supervision structure (e.g. a combination of clear oversight by a government body with an external execution supervisor).
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2.
Outline the decision hierarchy structure (e.g. “minister–project officer–supervising consultant–main contractor”). Likert: The composition of the supervision structure remained stable throughout.
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3.
The supervision structure provided oversight on a regular basis throughout the project.
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4.
The supervision structure provided clear guidance when it came to grey areas.
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5.
All key decisions were approved by the supervision structure.
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6.
The supervision structure was regularly kept informed of key aspects of the project.
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7.
The supervision structure met regularly.
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8.
The credentials of the members were subject to due diligence prior to membership.
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9.
The supervision structure regularly uncovered difficulties in the project.
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10.
The supervision structure regularly uncovered irregularities in the project.
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11.
The supervision structure provided adequate guidance for resolving problematic aspects of the project.
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12.
Significant gratification in any form was present in this project.
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13.
The primary contractor was selected through a selection process appropriate for projects of this scale.
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14.
The selection process was rigorous and open.
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15.
The selection process considered contractors’ demonstrated experience in similar projects elsewhere.
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16.
Details regarding planning for the project received wide visibility, for example, through a website.
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17.
The public were able to ask questions regarding the project.
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18.
Key stakeholders outside the narrow decision circle had visibility and input before the approval processes of the project.
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19.
The goals of the project were clearly understood by all parties.
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20.
The goals were clearly measurable.
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21.
The prioritization among the most important goals was clear.
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22.
The project was created with a demonstrated business case defining the goals and public benefits.
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23.
The benefits of the project to the economy or society were clear and measurable at the start of the project.
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24.
The project goals and business case were subject to risk scenarios to capture the risks of outcomes.
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25.
The primary contractor had strong capability to deliver a project of similar characteristics and scale.
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26.
The primary contractor had strong prior experience in similar projects with a track record of successful delivery of similar projects.
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27.
The primary contractor and the supervising party had clearly defined roles.
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28.
The primary contractor and the government’s assigned project supervisor (see Question 2) worked together constructively when problems occurred in the execution.
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29.
Sub-contractors: Taken together, the sub-contractors had strong capability to deliver a project of similar characteristics and scale.
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30.
The project had formal plans for managing stakeholders outside the project.
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31.
The plans were actively used to positively influence stakeholders.
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32.
Stakeholder views were used to make changes that improved the viability of the project.
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33.
The project was adequately resourced (in terms of funds) for its initial size.
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34.
The project funding was renewed/maintained when the project needed the funds to proceed.
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35.
The project had an adequate supply of skilled staff on the government side.
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36.
The project had adequate logistical support, for example, for delivery of materials or personnel.
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37.
The timeline of the project plan was realistic.
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38.
The project had a well-defined risk plan.
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39.
The risk plan was comprehensive in the management of risks that did occur.
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40.
The quality of the risk plan was consistent with similar plans used in projects of this magnitude worldwide.
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Ibrahim, J., Loch, C., Sengupta, K. (2022). Corruption in Large Government Projects Not Only Inflates the Budget But Reduces Managerial Effectiveness. In: Lee, H., Ernst, R., Huchzermeier, A., Cui, S. (eds) Creating Values with Operations and Analytics. Springer Series in Supply Chain Management, vol 19. Springer, Cham. https://doi.org/10.1007/978-3-031-08871-1_7
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