The effects of corruption in urban development and urban affairs management in several south Asian countries are examined through a series of specific, distinctive, and provocative cases for which the data is more readily available. The stories and themes provide a starting point for analyzing corruption as a symptom and factor of underdevelopment, affecting efforts to use and allocate scarce resources for a higher quality of life in cities. It shows how corruption stifles imaginative and creative solutions to urban challenges while increasing future revenue sources. 3Ps has provided a chance for the public section to look at various funding expertise and options from the business sector to prepare the public infrastructure. On the other hand, governments in the source of budget limitations and other competing demands for state sources can’t supply each citizenry’s infrastructure. Besides, the private sector has been considered a better resource manager, and the government should concentrate on policymaking. Where P3s are put to fair use, the advantages are immense. Unfortunately, vulnerable to bribery. This is the case; whatever benefits 3P offers in reducing the urban infrastructure deficit may be eroded due to corruption, which could lead to an increase in construction or facility costs.’ rehabilitation. Secondly, a PPP process marred by corruption could lead to inferior construction substances. One of the fund’s big chunks will be diverted to the public officials’ bribing via the project company. Thirdly, a corrupt process could compromise officials’ integrity that has been charged with accountability for inspecting and approving construction works.
Farazmand A. Globalization and public administration. 1999. p. 509–22.
2.
Hodge G. Public private partnerships and legitimacy. University of New South Wales Law Journal Forum. 2006;12(2):43–8.
3.
Mörth U. The market turn in EU governance—the emergence of public–private collaboration. Governance. 2009;22(1):99–120.
4.
Kwak YH, Chih Y, Ibbs CW. Towards a comprehensive understanding of public private partnerships for infrastructure development. California management review. 2009;51(2):51–78.
5.
Hodge G, Greve C. Public‐private partnerships: governance scheme or language game? Australian journal of public administration. 2010;69:8–22.
6.
Hodge GA, Greve C. Public–private partnerships: an international performance review. Public administration review. 2007;67(3):545–58.
7.
Sclar E. You don’t always get what you pay for: The economics of privatization. 2001.
8.
Baizakov S. Guidebook on promoting good governance in public-private partnership. 2008.
9.
Caiden GE, Caiden NJ. Administrative corruption. In: Classics of administrative ethics. 2018. p. 177–90.
10.
Arnim HH, Heiny R, Ittner S. Korruption. 2006.
11.
Anderson MB, Petrie M, Alier MM, Cangiano MM, Hemming MR. Public-private partnerships, government guarantees, and fiscal risk. 2006.
12.
Iossa E, Martimort D. Corruption in Public-Private Partnerships, Incentives and Contract Incompleteness. CESifo DICE Report. 2014;12(3):14–6.
13.
Alkan RM, Erol S, Ozulu IM, Ilci V. Accuracy comparison of post-processed PPP and real-time absolute positioning techniques. Geomatics, Natural Hazards and Risk. 2020;11(1):178–90.
14.
Ho W, Xu X, Dey PK. Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of operational research. 2010;202(1):16–24.
15.
Chai J, Liu JN, Ngai EW. Application of decision-making techniques in supplier selection: A systematic review of literature. Expert systems with applications. 2013;40(10):3872–85.
16.
Ghodsypour SH, O’brien C. The total cost of logistics in supplier selection, under conditions of multiple sourcing, multiple criteria and capacity constraint. International journal of production economics. 2001;73(1):15–27.
17.
Chen CT, Lin CT, Huang SF. A fuzzy approach for supplier evaluation and selection in supply chain management. International journal of production economics. 2006;102(2):289–301.
18.
Dickson GW. An analysis of vendor selection systems and decisions. Journal of purchasing. 1966;2(1):5–17.
19.
Lahdelma R, Salminen P. SMAA-2: Stochastic multicriteria acceptability analysis for group decision making. Operations research. 2001;49(3):444–54.
20.
Lahdelma R, Hokkanen J, Salminen P. SMAA-stochastic multi-objective acceptability analysis. European Journal of Operational Research. 1998;106(1):137–43.
21.
Lahdelma R, Salminen P, Hokkanen J. Locating a waste treatment facility by using stochastic multicriteria acceptability analysis with ordinal criteria. European Journal of Operational Research. 2002;142(2):345–56.
22.
Durbach I. A simulation-based test of stochastic multicriteria acceptability analysis using achievement functions. European Journal of Operational Research. 2006;170(3):923–34.
23.
Lahdelma R, Salminen P. Classifying efficient alternatives in SMAA using cross confidence factors. European Journal of Operational Research. 2006;170(1):228–40.
24.
Lahdelma R, Salminen P. Stochastic multicriteria acceptability analysis using the data envelopment model. European journal of operational research. 2006;170(1):241–52.
25.
Lahdelma R, Makkonen S, Salminen P. Multivariate Gaussian criteria in SMAA. European Journal of Operational Research. 2006;170(3):957–70.
26.
Lahdelma R, Makkonen S, Salminen P. Two ways to handle dependent uncertainties in multi-criteria decision problems. Omega. 2009;37(1):79–92.
27.
Tervonen T, Lahdelma R. Implementing stochastic multicriteria acceptability analysis. European Journal of Operational Research. 2007;178(2):500–13.
28.
Corrente S, Figueira JR, Greco S. The smaa-promethee method. European Journal of Operational Research. 2014;239(2):514–22.
29.
Angilella S, Corrente S, Greco S. Stochastic multi-objective acceptability analysis for the Choquet integral preference model and the scale construction problem. European Journal of Operational Research. 2015;240(1):172–82.
30.
Angilella S, Corrente S, Greco S, Słowiński R. Robust Ordinal Regression and Stochastic Multi-objective Acceptability Analysis in multiple criteria hierarchy process for the Choquet integral preference model. Omega. 2016;63:154–69.
31.
Zhang Q, Lai KK, Yen J. Multicriteria supplier selection using acceptability analysis. Advances in Mechanical Engineering. 2019;11(10):1687814019883716.
32.
Durbach I. On the estimation of a satisficing model of choice using stochastic multicriteria acceptability analysis. Omega. 2009;37(3):497–509.
33.
Tervonen T, Figueira JR. A survey on stochastic multicriteria acceptability analysis methods. Journal of Multi‐Criteria Decision Analysis. 2008;15(1‐2):1–14.
34.
Babalos V, Philippas N, Doumpos M, Zopounidis C. Mutual funds performance appraisal using stochastic multicriteria acceptability analysis. Applied Mathematics and Computation. 2012;218(9):5693–703.
35.
Xiaohu Z, Heydari M, Lai KK, Yuxi Z. Analysis and modeling of corruption among entrepreneurs. REICE: Revista Electrónica de Investigación en Ciencias Económicas. 2020;8(16):262–311.
36.
Heydari MD, Lai KK. The Effect Employee Commitment on Service Performance through a Mediating Function of Organizational Citizenship Behaviour Using Servqual and Collaborative Filtering Modeling: Evidence From China’s Hospitality Industry. J Tour Hosp. 2019;8:2167–0269.
37.
Heydari M, Lai KK, Xiaohu Z. Risk Management in Public-Private Partnerships. 2020.
38.
Heydari M, Lai KK, Xiaohu Z. Corruption, Infrastructure Management and Public–Private Partnership: Optimizing through Mathematical Models. 2021.
39.
Heydari M, Xiaohu Z, Keung LK, Shang Y. Entrepreneurial intentions and behaviour as the creation of business: based on the theory of planned behaviour extension evidence from Polish universities and entrepreneurs. Propósitos y representaciones. 2020;8(2):46.
40.
Heydari M, Xiaohu Z, Lai KK, Wang SB. Social-Psychology and Situational Elements Affecting Individual Social Behavior. J Hotel Bus Manage. 2019;8(196):2169–0286.
41.
Heydari M, Xiaohu Z, Lai KK, Yuxi Z. EVALUATION OF ORGANIZATIONAL PERFORMANCE STRATEGIES. Proceedings of National Aviation University. 2020;82(1).
42.
Heydari M, Xiaohu Z, Lai KK, Yuxi Z. How Might Entrepreneurial Activities Affect Behaviour and Emotions? Proceedings of the National Aviation University. 2021;87(2):65–77.
43.
Heydari M, Xiaohu Z, Saeidi M, Lai KK, Yuxi Z. Entrepreneurship Process As The Creation Of Business By Engaging Family Members: Based On The Perceived Emotion. REICE: Revista Electrónica de Investigación en Ciencias Económicas. 2020;8(15):210–41.
44.
Heydari M, Xiaohu Z, Saeidi M, Lai KK, Yuxi Z. Entrepreneurial Cognition and effect on Neuro entrepreneurship. Gelpat Caderno Suplementar. 2020;3.
45.
Heydari M, Xiaohu Z, Saeidi M, Lai KK, Shang Y, Yuxi Z. Analysis of the role of social support-cognitive psychology and emotional process approach. European Journal of Translational Myology. 2020;30(3).
46.
Heydari M. A Cognitive Basis Perceived Corruption and Attitudes Towards Entrepreneurial Intention. 2021.
47.
Yang F, Song S, Huang W, Xia Q. SMAA-PO: project portfolio optimization problems based on stochastic multicriteriasz acceptability analysis. Annals of Operations Research. 2015;233(1):535–47.
48.
Yang F, Ang S, Xia Q, Yang C. Ranking DMUs by using interval DEA cross efficiency matrix with acceptability analysis. European Journal of Operational Research. 2012;223(2):483–8.
49.
Ng WL. An efficient and simple model for multiple criteria supplier selection problem. European journal of operational research. 2008;186(3):1059–67.
50.
Barron FH, Barrett BE. Decision quality using ranked attribute weights. Management science. 1996;42(11):1515–23.
51.
Xia W, Wu Z. Supplier selection with multiple criteria in volume discount environments. Omega. 2007;35(5):494–504.
52.
Tervonen T. JSMAA: open source software for SMAA computations. International Journal of Systems Science. 2014;45(1):69–81.
53.
Durbach IN, Calder JM. Modelling uncertainty in stochastic multicriteria acceptability analysis. Omega. 2016;64:13–23.
54.
Priddat BP. Schwarze Löcher der Verantwortung: Korruption—Die negative Variante von Public-Private Partnership. In: Korruption. 2005. p. 85–101.
55.
Becker GS, Stigler GJ. Law enforcement, malfeasance, and compensation of enforcers. The Journal of Legal Studies. 1974;3(1):1–18.
56.
Durbach IN. The use of the SMAA acceptability index in descriptive decision analysis. European Journal of Operational Research. 2009;196(3):1229–37.
57.
Flyvbjerg B, Holm MS, Buhl S. Underestimating costs in public works projects: Error or lie? Journal of the American planning association. 2002;68(3):279–95.
58.
Kangas AS, Kangas J, Lahdelma R, Salminen P. Using SMAA-2 method with dependent uncertainties for strategic forest planning. Forest policy and economics. 2006;9(2):113–25.
Sack D. Public Private Partnership im „aktivierenden Staat “. In vhw Forum Wohneigentum Zeitschrift für Wohneigentum in der Stadtentwicklung und Immobilienwirtschaft. 2004;285–8.
61.
Schomaker RM. Conceptualizing corruption in public private partnerships. Public Organization Review. 2020;20(4):807–20.
62.
Sze BWP, Lai KK, Fu Y. Project Selection via Stochastic Multi-criteria Acceptability Analysis. In: Asia Pacific Industrial Engineering and Management Systems Conference. 2016.
Citation
Copyright
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The statements, opinions and data contained in the journal are solely those of the individual authors and contributors and not of the publisher and the editor(s). We stay neutral with regard to jurisdictional claims in published maps and institutional affiliations.
