Background

The public and private industries are facing difficulties in the development of the construction of infrastructure. The focus should be given on providing effective public services such as electricity, water supply, transportation, education, and others.  The rapid growth of the nation depends on the development of the infrastructure within the country. The GDP of the nation can be improved and increased according to the efficiency of the infrastructure project development plan (Halil, Nasir, Hassan, Shukur, 2016). The evaluation of anomalies which are associated with the development of construction program helps in analysing the complexities, risks, and issues which are responsible for the project delay and overrunning of the cost. The development of agreement between the public and private authorities focuses on managing the balance between them so that the complexities and risks can be effectively managed between the two parties by allocating risks between them. The advantage of PPP project is that the risks can be transferred in public and private sector. The high quality infrastructure can be developed at lower price and cost with the utilization of high standard technologies provided by the private sector. The public sector is responsible for managing the fund amount for completing the given process within the given timeframe (Carbonara, Costantino, and Gunnigan, 2012). The allocation of the risks between the public and private sector helps in managing the complexities related to the settlement process of loan, financial inefficiency, political implications, social problems, lack of meeting supply and demand of resources, security and confidentiality issues, and others. The success of the project depends upon the capability of the business process, operations, and project manager ability in determining the risks associated with the projects. The identification of the risks at an early stage helps in providing new opportunities to the public and private sector by the risks allocation for managing them effectively and completes the project successfully. The effective risks allocation strategy should be adopted by the PPP projects so that the identified risks can be easily settle down. The potential opportunities which are associated with the projects are cope up with various risks. The value for money can be earned by the implementing the process of risks allocation. The purpose of this paper is to determine the risks associated with the construction project in Australia with its allocation by using the innovative methodology of Fuzzy theory.

Traditionally, the construction projects are facing problem of managing infrastructure design required for the project and the relevant cost associated with the project completion process. The complexity of the construction project increases by analysing the overrunning of time and cost factors. The development of the agreement and contract between the public and private authorities helps in managing the allocation of risks between them. For example, the complexities of design preparation for the construction of infrastructure can be managed by the private authorities and the financial risks which are associated with the project can be managed by the public sector by providing the financial fund and support at the time of demand (Hall, 2012). The quality standards for the project completion should be prepared by the active participation of the both sectors so that the level of satisfaction of the participating members can be achieved. The quality of the project is determined by the efforts put by the team members from public and private sectors, quality of the resources used by the company, providing funds, and others. The identification of the risks is the most important step for resolving the complexities associated with the project. The innovation processes are required for determining the risks and their allocation for mitigation. The innovative methods should be based on Fuzzy theory. The application of Fuzzy theory concept helps in managing the risks and issues effectively.

Problem Domain

The construction programs of the infrastructure projects in Australia are accompanied with the complexities of developing the construction design and managing funds to complete the process and operation effectively. The initialization of the public and private sector helps in resolving the risks and issues by dividing the tasks between the two parties. Traditionally, the construction of construction projects in Australia is equipped with various risks such as technology risks, financial risks, social risks, political risks, and others. The need and demand arises for the development of effective relationship between them. The innovative procedures are required for managing the risks and issues associated with the construction projects.

The aim of the undertaken research on the Australian construction project is to determine the optimum procedures which should be developed for risks allocation and transfer between the public and private partnership projects.

The objectives of the risks are as follow:

• Identification of significant risks associated with the construction projects in Australia
• Deployment of literature review program for identifying the procedures followed by the researchers in managing and transferring the risks associated with the construction industry in Australia
• Identification of Fuzzy logic approach for managing the risks associated with the project.

The research question which is designed for collecting data through the literature review on the risks identification and allocation procedures associated with the PPP projects are highlighted below:

• How the fuzzy theory is helps in risk allocation associated with the development of the PPP projects?

The literature review is the major source of data collected for the development of the thesis on risk allocation on PPP project with Fuzzy theory. The risks register  is prepared for risk allocation among the public and private sector.

The thesis is structured on enabling the findings of the research question prepared. The thesis starts with the construction of research aim, objectives, and questions. The description research methodology is opted for data collection through literature review. The selection of the literature should be according to the proposed agenda. The systematic development of the findings helps in analysing the efficiency of the research program. The thesis ends with the concluding remarks.

The research undertaken by different authors helps in collecting the details related to the public private partnership projects. The quality of service is the major credential for gaining the value for money from the undertaken construction project (Chan, Yeung,  Calvin, Wang, and Ke, 2014). The public and private sectors should focus on identifying the risks associated with the project. The Public private partnership projects are developed by signing the agreement between them to manage risks associated with the project and completing the project within given time frame (Effah, and Chan, 2014). The quality of the project delivery is depends upon the potential associated between the working parties of the project plan. The procurement methods are used for funding the projects for the long term management plan (GiHub, 2014). The government plays an active role in providing funds to complete the project without any complexities. The PPP projects are developed to follow the following principles:

• To gain value for money from the construction projects
• To develop best outcome of the project
• Meeting the quality standard of the project
• Minimising the risks associated with the project
• Initializing the risks transfer and allocation between the participating parties (Firmanzyah, Veronika, and Trigunarsyah, 2016)
• Managing project at lower cost
• Defining risks transfer procedures
• Managing drivers for value for money

Research Aim

The policies which are used in the traditional projects of developing construction are based on the concept of build-operate-transfer, build-own-operate, Build-own-operate-transfer, and lastly Design-build-operate-transfer. The risks allocation problems were faced in the deployment of BOT, BOOT, BOO, and DBOT. The evaluation of the PPP project helps in resolving the inappropriate procedures followed for managing the risks between the members. The value for money can be gained by giving emphasis on the procedures used for defining the parameters of managing risks allocation procedures (Firmanzyah, Veronika, and Trigunarsyah, 2016). The management, transfer, and allocation of the risks helps in managing the risks associated with the projects. The control structure should be laid down for increasing the efficiency of decision making policies in allocating the risks.

The identification of risks at an early stage of the PPP projects helps in allocating the risks between the public and private parties effectively. The proactive action plan results in minimising the cost associated with the project. The success of the project depends on three factors which are named as cost, time, and quality (Laufer, Takacs, Rudas, 2018). The efficiency of the project deliverables increases with the completion of the project within the time, cost and meeting the quality standard of the project. It depends on identifying, allocating, and managing the risks associated with the project. The following table shows the list of risks which are identified by literature review incorporated with the infrastructure project in Australia.

Identified Risks	Description
Technical risks	The adoption and implementation of the new technology within the working schedule of the project management in the construction project can be a failure due to the resistance placed by the working employees
Construction Design risks	The designing of the construction program was not efficiently done by the construction engineer to manage the cost and time
Financial Instability risks	The government is not able to provide the funds to the private sector on time so that they can complete their tasks and operation within the given period of time.
Political association	The government put obligation in the working process of the private sector which can affect their capacity planning and the breaking of communication plan. The opposition can put major hindrance in  completing the project on time.
Legislation risks	The changes done in the legislation and laws in regards to the construction program can affect the working of the PPP projects.
Operational plan and business risks	The operation plan and business risks are associated with the failure of completing the process in the direction of achieving the goal and objective of the company. The working process is selected for the completion of the project.
Environment management risks	The change in the location and operational plan of the project will affect the working of the PPP projects. The unavailability of the land and transportation are the major factors for environmental risks to occur (Hovy, 2015)
Disaster risks	There is no scope for managing the natural disaster. The focus should be given on identifying the natural disaster proactively so that effective management of risks can be identified.
Organization hierarchy risks	The inefficiency in managing the communication between the top executives of the public and private sector can create complexities in completing the tasks within the given time frame.
Process and procedure risks	The change in the process and procedures during the implementation of the project working plan can create the complexities in the working staff to finish the work with efficiencies. The settlement of the process and procedures if not in the direction of the project plan, goal, and objectives than the project will not  meet the quality standards (Ibrahim, 2014).
Role and responsibilities risks	The distribution of roles and adequate authorities to the public and private sector should be based on identifying the skills and capabilities of the team members of different sector. The change in the organization culture will affect the working capabilities of the team members which can directly or indirectly affect the project success
Employees risks	The resistance placed by the employees in adopting new technologies, policies, and business plan can affect the working procedures and operational plan of the project
Monitoring and control risks	The ineffective monitoring and control plan can affect the development of continuous improvement plan to get effective results and meeting the requirement of the stakeholders and end users. The inefficiency of decision making capability and placement of the key performance indicators will affect the monitoring program for the construction project (Hyari and Kandil, 2009).
Resource management risks	The failure of the contractor in managing the supply and demand of the resources, raw material, and equipment required for the completion of infrastructure. The supply and demand of the resources should be managed simultaneously so that the working of the construction activities will remain carry on.
Asset management risks	The management of the physical assets required for the project should be managed on the construction site. The inefficiency in the management of assets will create complexities in completing the construction program on time
Permission risks	The private sector should take legal permission from the public sector to complete the project. The in discrepancies in completing the legal procedures for permission can create the complexities (Bao, Chan, Chen, and Darko, 2018).
Land unavailability risks	The construction program undertaken by the private sector can equipped with the risks associated with the legal and political obligations associated with the land available. The pre-requisites procedures should be performed before making agreement with the public and private authorities.
Tax based risks	The tax paid by the government for completing the construction project is higher than the normal price
Failure of hardware, software, process, and procedures	The chance of project failure is associated with the failure of hardware, software, process, and procedures.
Corruption and bribery risks	The corruption and the bribery risks is the major common problems associated with the partnership between the public and private sector for completing the project in Australia which in turn increases the cost of the project
Public sector interruption risks	The periodic interruption and obligations from the public sector in the procedures and process followed by the private sector for completing the construction program
Government policies framework risks	The changes in the policies, principles, and legal laws developed by the government in favour of the construction industry in Australia
Third party management risks	The public sector provides the completion of infrastructure program development process to the private sector and management of resources and equipment to the contractor company. The disturbance and mismanagement between the two working parties increases the chance of risks occurrence
Increasing interest risks	The delay in the project plan increases the interest rate of the project
Failure of decision risks	The failure of the public and private top executives in taking effective decision for the benefit of the construction project
Market analysis risks	The private sector fails in managing the effective analysis of the market competitors in the field of construction program
Market change risks	The technological improvement and changes in the construction development process will affect the working structure of the construction program because the upcoming of the new trends and technologies in the market will affect the level of satisfaction of the end users.
Demand Change risks	The failure of the contractor in managing the supply and demand of the resources, raw material, and equipment required for the completion of infrastructure. The supply and demand of the resources should be managed simultaneously so that the working of the construction activities will remain carry on.
Competition risks	The technological improvement and changes in the construction development process will affect the working structure of the construction program because the upcoming of the new trends and technologies in the market will affect the level of satisfaction of the end users (Prasad, Reddy, Kumar, Reddy, 2012).
Re-settlement of the public risks	The resistance exerted by the local people for re-settlement due to the deployment of the infrastructure construction program in Australia

The success of the PPP projects can be achieved by deploying the methodology for the risk allocation procedures. The success is defined as meeting the requirement of the project within the given time and cost. The allocation of the risks between the public and private sector authorities helps in managing the balance between the working parties. The flow of information between the communicating parties should be maintained. The commitment and the requirement of the project participants should be fulfilled (Monnappa, 2017). The risks analysis can be carried out  by undergoing the factor analysis theorem, use of fuzzy sets, and process of fuzzy synthetic evaluation. The fuzzy algorithms are implemented for identifying the overrunning of time and costs associated with the project. The fuzzy theorems are applicable for managing the dependency of risks between the working process and procedures (Muller and Oppe, 2012). The risks occurrence probability can be effectively reduced by implementing the Fuzzy theorem functions. The risks allocation procedures follow the following principles for the effective distribution of risks among the participating sectors:

• Controlling the risks within the project boundaries
• Managing the risks transfer process for gaining economic benefit
• Increasing value for money associated with the projects
• Increasing the working efficiency and capabilities of the stakeholders (Shastri, 2012)
• Evaluating the validity of risks
• Evaluating the risks impact on the PPP projects
• Increasing rate of risks transfer between the member participants
• Minimizing the loss of information
• Managing control over the risks allocation process (Raz, Shenhar, and Dvir, 2011)
• Setting priority to the risks

Research Objectives

The working process of private and public sector can be resolved by managing the risks associated between the private and public sector. The consequences of the risks should be forecasted so that the relevant information to the demanding parties be available (LLveskoski, 2014). The framework given below helps in defining the risks allocation procedure associated with the PPP projects.

Figure 1: Risk allocation framework

(Source: Bao, Chan,  Chen,  and Darko, 2018). Review of public private partnership literature from a project lifecycle perspectives)

The artificial neural network model is extensively used for managing the network of information through the concept of leaning fundamentals. The fuzzy logics are based on probability theory. Therefore, in the identification and allocation of the risks associated with the project it is mostly used. The outcome of the fuzzy logic functions are based on fuzzy logic input values. It helps in finding out the reasons for the uncertainties associated with the fuzzy variables (Jin, 2014). The scope and limitation of the risks can be effectively identified with the help of fuzzy functions and algorithms. The implementation of the fuzzy logic helps in identifying the linguistic variables which defines the complexities and risks in the logical manner. The non-linear distribution of information results in increasing the decision making process of the participants. The fuzzy logics are created for risks modelling and risks assessment tasks which are used for resolving the operational risks associated with the projects (Kolodiziev, Tyschenko, Azizova, 2017). The risks assessment procedures should be laid down for building the interpretation of the results. The risks matrix should be developed for modifying the analytical hierarchy process. The Fuzzy logic helps in optimizing the risks associated with the projects like financial risks, social risks, strategic risks, and operational risks. The fuzzy logics help in setting out the project boundaries for designing and analysing the operation between the linguistic variables. The member function should be developed for managing association between the risks identified (Mansfield community, 2013). The fuzzy logics helps in developing the risks matrix for analysing the risks impact on the construction program. The severity, ranking, and likelihood of risks should be determined for managing the risks matrix. The analysis of the risks in the development of project activities depends on evaluating the impact of three questions which are as follows:

• What is the result of risks?
• What is the likelihood of the risks?
• What are the consequences of the risks?

The quantification of the risks can be effectively minimised by developing the risks matrix by making use of Fuzzy logic functions (Sastoque, Arboleda, and Ponz, 2016). The certainty of the potential losses associated with project development process should be analysed. The risks assessment database is prepared on the basis of linguistic variables. The severity and the likelihood of the risks is depend upon the fuzzy input given to the member function (Kharaiweish, 2013). The risks score of the member functions helps in determining the risks impact on the development and allocation of risks associated with the public and private parties. The risks mapping procedures are deployed with the help of fuzzy logic member function.  The following diagram shows the risks mapping to show the occurrence of the risks likelihood in the construction projects.

Research Questions

Figure 2: Risks mapping

(Source: Hovy, P. (2015). Risk allocation in public-private partnership: Maximising value for money)

The preparation of the two dimensional chart help in analysing the likelihood and impact of risks based on risks severity. The emphasis should be given on analysing the occurrence of risks associated with the project.

The coordination should be developed for managing the risks likelihood and risks severity plotted in the graph to analyse the risks space. The following matrix shows the interrelationship between the likelihood and severity of the risks associated with the project (Li and Zhou, 2014). The categories of the risks are divided on the basis of risks score which are classified as 1 for low, 2 for medium, 3 for medium high, and 4 for high. The risks severity can be categorised as 1 for negligible, 2 for low, 3 for moderate, 4 for high, and 5 for catastrophic (Eriksson,  and Furuskold, 2014). The risks likelihood are categorised as 1 for very low, 2 for low, 3 for moderate, 4 for high, and 5 for very high. The following diagram shows the risks matrix based on risks likelihood and risks severity:

Figure 3: Risk matrix

(Source: Hovy, P. (2015). Risk allocation in public-private partnership: Maximising value for money)

Some rules have to be followed for developing the risks matrix which are categorised as below:

• The correspondent value of risk is Medium high if the value of likelihood is very low and severity of the risks is calculated as catastrophic (Lee, and at.el, 2012)
• The correspondent value of risk is low if the value of likelihood is low and severity of the risks is calculated as low (Mouraveiv, 2012)
• The correspondent value of risk is Medium if the value of likelihood is low and severity of the risks is calculated as moderate

The member functions are used for calculating the risks index on the basis of likelihood and severity measurement. The risks variables are used for determining the vague decision based on the values represented in the risks matrix. The member functions of the Fuzzy logics are used for creating the relationship between the severity, likelihood, and risks impact. The input and output given to the Member functions of the fuzzy logic helps in defining the impact of the risks associated with the project (Jethwa, Bhavsar, and Malek, 2017). The triangular matrix can be prepared given on the values of risks severity, risks likelihood, and risks impact. The following figure shows the demonstration of the relationship between the likelihood, severity, and impact.

Figure 4: Demonstration of relationship between the likelihood, severity and impact 

(Laufer, E., Takacs, M., Rudas, E. (2018). Fuzzy logic based risk assessment framework to evaluate physiological parameters

Analytical hierarchy process is used for identifying the modification in the Fuzzy logic. The risks factors should be determined for evaluating the linguistic variables associated with the system. The development of the risks matrix to prepare a pair wise comparison between the risks severity and risks likelihood helps in analysing the risks impact on the complete work breakdown structure of the project. The Fuzzy analytical hierarchy process is used identifying the subjective decision associated with the project improvement process (Kavishe, 2018). The FAHP model helps in analysing the qualitative quantitative risks associated with the project. The priority should be allocated to the risks so that they can effectively manageable. The hierarchical structure should be followed for improving the decision making efficiency of the project. The evaluation of the criteria should be done at second level to determine the best alternative to choose.

Research Methodology

The consistency and validity should be checked through the process of AHP prioritization (Kang, 2010). The implementation of the AHP process helps in increasing the decision making capability of the top executives of the public and private sector. The dependencies of the risks within the project management should be determined for managing the flow of hierarchy. It should be focused that the upper level of the management should not depends upon the decision given by the lower level (Ke, Wang,  albert, and Chan, 2014). The development of the pairwise matrix helps in taking effective decision for improving the flow of information between the participating parties. The consistency ratio is defined as the ratio between the consistency index and random index. The limitations which are associated with the AHP process are highlighted as criticism associated with the process, limitation of the AHP methodology, increasing parameters of uncertainty. The success and failure of the project depends on the aggregation method used for the development of the project. The AHP process results in defining the judgement based on fixed value of the project. The FAHP model is used for managing the dependencies of triangular fuzzy numbers to increase the efficiency of the decision making capability of the process. The focus should be given on identifying the fuzzy weights and scores. There are different models designed for determining the comparison matrix:

• Fuzzy Dataset: The fuzzy datasets are used for developing the comparison matrix to achieve the goal of the project success. The likelihood risks factors can be easily identified through the development of fuzzy matrix (Velasquez, 2014).
• The Van Laarhoven and Pedrycz model: The decision making capabilities of the project can be improved by defining the logarithmatic least square, managing fuzzy weights, improving the scores of the fuzzy performance, and improving fuzzy multiplication process (Velasquez, 2014).The limitation of this model is that the multiplication is based on formula, managing changes in the priority, normalizing the fuzzy weights, and uncertainty of the fuzzy comparison matrix.
• The Buckley FAHP model: The main characteristics of this model are to develop a trapezoidal extension of AHP to FAHP and geometrical mean should be determined by analysing the fuzzy weights and performance scores of the project. The limitation of the buckley model is that consistency of the matrix cannot effectively determined
• Change FAHP model: The change FAHP model is based on the trapezoidal extension of AHP to FAHP. The priority vector is used for defining the arithmetic mean of the proposed system. The ranking and priority should be determined for the fuzzy vectors.

The limitation of the AHP method is based on the normalization formula. The decision making capability of the project get affected by analysing the difference in the criteria and sub-criteria.

The literature review is the main source of data collection. The consideration is also given on the other online sources to know the efficiency of fuzzy logic in applying to the PPP projects for determining the risks identification and risks allocation for the successful completion of the project. The qualitative approach is deployed for analysing the various risks which can be the obstacles and hindrance in the project management program of PPP construction project in Australia. The Australia is a developed country, it make use of innovative technology for determining the risks associated with the project.

The descriptive methodology based on the literature review is undertaken for identifying  the risks associated with the PPP projects and the use of fuzzy logic in managing and distributing the risks associated with the projects. The parameters which are used for defining the risks severity and likelihood are very high, high, medium, and low with the value of 4, 3, 2, and 1. The risks ranking can be calculated by combining the effect of risks severity and risks likelihood. According to the risks ranking distribution of the risks and its associated allocation should be done between the public and private parties. The distribution of the risks is low, medium, high, and very high according to the combined effect of risks severity and likelihood. The risks impact are divided into three categories which are 1, 2 and 3 are low, 4 and 5 for medium, and 6, 7 and 8 for high.

Thesis Structure

The literature review is the method used of collecting the data from different online and offline sources. The contribution of the authors in constructing the research paper is given preference to analyse the complexities associated with the public private partnership projects. The focus should be given on analysing the efficiency of the project to determine the risks and complexities. The systematic arrangement of the risks in the matrix and applying the fuzzy logic principles, methods, and application helps in identifying the risks allocation procedures effectively.

Data Collection Question 1: How the fuzzy logic is useful for risks identification process associated with the PPP projects?

The Fuzzy logic helps in analysing the risks identification, risks severity, risks likelihood, and risks impact (Singh, 2017). The setting of priority to the risks helps in optimizing the process of risk allocation. The data collected with regards to the risks associated with the PPP projects from the literature review helps in identifying the risks priority and impact to allocate the risks between the public and private sector authorities.

Data Collection Question 2: How the uncertainties can be minimized associated with the Australian PPP projects?

The identification of the risks allocation and distribution helps in minimizing the complexities associated with the Australian construction company. The major focus is given on analysing the various risks associated with the PPP projects. The systematic list of risks associated with the project helps in analysing the responsible parties for managing the risks effectively to minimize the complexities of the construction projects (Pribadi,  and Pageran, 2013). The Fuzzy logics are used for developing the matrix for the risks severity and likelihood to calculate the risks impact.

The risks allocation can be effectively done through the process of fuzzy optimization. The negative consequences get associated with the wrong estimation of the probability (Otieno, 2014). The unexpected results of the proposed model of fuzzy logic can create the complexities in determining the risks associated with the project. The risks allocation process is based on three steps which are categorised as risks identification, risks analysis, and risks evaluation. The risks allocation procedures is followed through the following flowchart:

Figure 5: Risk allocation procedures

(Raz,  Shenhar, and Dvir, (2011). Risk Management, project success, and technological uncertainty

The clear picture should be drawn for managing the uncertainties associated with the project. The probability of the risks can be identified through the wrong estimation of knowledge criteria (Patanakul, 2010).

Literature Review

The objective functions and constraints are defined for optimizing the fuzzy logic in the development procedures. The efficiency of the decision making process can be improved by maximising the risks impact associated with the risks severity and risks likelihood. The steps which are followed for analysing the risks associated with the project are described below:

• Development of the Fuzzy logic based on the objective function
• The feasibility of the project can be tested between the max value and the min value.
• The constraints associated with the project should be determined
• Identifying the constraints and objective functions associated with the optimal member function

The identification of the risks and setting of risks priority can be effectively drawn by giving consideration to the following step:

• Start collecting data and developing matrix for the indicators
• The indicator matrix should be based on scaling factors
• Applying fuzzy weights to the indicator matrix
• The linear process should be followed for applying weights to the risks associated with the projects
• Standard deviation of the matrix should be calculated for measuring the variation in the data
• The local density of the project score, severity, and likelihood should be calculated
• The associated objective function should be calculated after analysing the risks likelihood, severity, and impact on the developing process (Merrit, and Ricketts, 2012).
• The optimized project indicators are used for maximizing the risks impact associated with the project
• The AHP method is used for providing the ranking to the fuzzy matrix
• Risks ranking are calculated by analysing the combined effect of risks severity and risks likelihood.
• The Fuzzy optimization methods are used to solve the complication in the management of the risks allocation procedures

The identification of the risks, analysing the risks severity and risks likelihood, estimating the risks ranks, and analysing the risks impact for the risks allocation between public and private sector can be effectively done with the help of fuzzy logic optimization methods. The application of fuzzy theory helps in identifying the systematic review of the impact associated with the risks severity and likelihood. The ranking of the risks is provided by following the set of rules explained in the table below:

Table 1: Rules for ranking of risks

Probability	Impact of Severity depends on the probability
Frequent	Medium	High	Low
Likely	Low	Medium	High
Remote	Catastrophic	Medium	Low

Source: Prepared by the Author)

The allocation of the risks should be based on the principles and guidelines provided by the Australian government. The focus should be given on managing the communication between the public and private sectors to make availability of resources. The assessment of the risks helps in completing the project successfully. The planning of risks allocation procedures is used to follow the procedures for risks handover among the private and public sector. The table below shows the analysis of the risks in determining their impact on the assets with the deployment of Australian standard.

Table 2: Areas affected by risks

Risks	Areas Affected
Physical risks	Assessment of the site location Managing condition for latent Analysing of weather condition Act of god for natural disaster Variation in the quantity of resources used
Financial Risk	Stability and instability of the financial funding
Political risks	Management of grievances and conflicts between the public and private sectors
Performance risks	Defect in the work breakdown structure Occurrence of accidents Completion time for activities Growth and acceleration Managing competition in the managerial process Labour association Material management

((Source: Prepared by the Author)

The table below shows the results of risks identification, risks severity, risks likelihood, risks ranking, risks impact, and responsible parties associated with the PPP projects in Australia:

Table 3: Results of risks identification

Risks Identification	Risks Severity	Risks Likelihood	Risks Ranking	Risks Impact	Risk allocation
Technical risks	1	2	3	Low	Private
Construction Design risks	2	3	5	Medium	Private
Financial Instability risks	1	2	3	Low	Public
Political association	3	2	5	Medium	Public
Resource management risks	4	3	7	High	Private
Asset management risks	2	1	3	Low	Private
Permission risks	3	1	4	Medium	Public
Land unavailability risks	4	2	6	High	Public
Tax based risks	1	4	5	Medium	Public
Failure of hardware, software, process, and procedures	2	3	5	Medium	Private
Corruption and bribery risks	3	2	5	Medium	Public/ private
Public sector interruption risks	3	1	4	Medium	Public
Government policies framework risks	4	2	6	High	Public
Third party management risks	2	4	6	High	Private
Increasing interest risks	1	3	4	Medium	Public
Failure of decision risks	2	2	4	Medium	Private / Public
Market analysis risks	1	1	2	Low	Private
Market change risks	3	1	4	Medium	Public
Demand Change risks	2	2	4	Medium	Public
Competition risks	2	1	3	Low	Private
Re-settlement of the public risks	3	4	7	High	Private / Public

 (Source: Prepared by the Author)

The following table shows the comparative study of risk allocation between Australia and Hong Kong associated with the PPP projects in the detailed structure by applying the principle of Fuzzy logic.

Table 4: Different between Risks allocation procedures of Australia and Hong Kong

Risks	Hong Kong		Australia
	Rank	Impact	Rank	Impact
Technical risks	7	High	3	Low
Construction Design risks	4	Medium	5	Medium
Financial Instability risks	6	High	3	Low
Political association	5	Medium	5	Medium
Resource management risks	3	Low	7	High
Asset management risks	6	High	3	Low
Permission risks	4	Medium	4	Medium
Land unavailability risks	3	Low	6	High
Tax based risks	2	Low	5	Medium
Failure of hardware, software, process, and procedures	7	High	5	Medium
Corruption and bribery risks	8	High	5	Medium
Public sector interruption risks	1	Low	4	Medium
Government policies framework risks	2	Low	6	High
Third party management risks	3	Low	6	High
Increasing interest risks	5	Medium	4	Medium
Failure of decision risks	3	Low	4	Medium
Market analysis risks	8	High	2	Low
Market change risks	2	Low	4	Medium
Demand Change risks	1	Low	4	Medium
Competition risks	2	Low	3	Low
Re-settlement of the public risks	1	Low	7	High

((Source: Prepared by the Author)

The significance of the risks allocation procedures with the help of fuzzy logics between the government and private companies helps in minimizing the risks occurrence and their probability so as to complete the project successfully. From the study of literature review and the analysis and findings of the proposed research study to demonstrate the identification of risks and risks allocation by making use of fuzzy logic. The major criteria for the implementation of Fuzzy logic to distribute the risks allocation between the participating organization was to gain value for money and increase the GDP of the nation so as to attract the foreign investor to develop business partnership with the Australian government. It helps in increasing the economy and financial condition of the nation. The success of the Australian construction project improves by managing the risks transfer and allocation, effective utilization of resources and material, and managing innovation in the project management plan. The comparison of the cost spend on the public and private project separately and PPP projects helps in evaluating that the PPP projects are more cost effective and successfully manages within the given cost and program.

The proactive analysis of the risks identification helps significantly in managing the risks effectively within the project time so that time taken to complete the activities can be managed. The ranking of the risks can be drawn by applying the member function of the fuzzy logic theory. The various risks which are classified with the PPP projects are technical risks, financial risks, performance risks, supply and demand risks, market analysis and change risks. The objective functions and constraints are defined for optimizing the fuzzy logic in the development procedures. The efficiency of the decision making process can be improved by maximising the risks impact associated with the risks severity and risks likelihood. The fuzzy methods help in concentrate on the logical flow and management of risks between the participating public and private sector authorities so as to minimize the risks impact on the public and private authorities (Salah, and Moselhi, 2018). The conceptual model should be developed for managing the systematic organization and flow of risks identification and allocation according to the analysis of the risks rating and priority.

Figure 6: Conceptual Model

The success of the project depends on the management of the external, internal, and partnership success factors and criteria by giving emphasis to the risks management process. The allocation and management of risks effectively which are associated with the project helps in increasing the interest rate of project sponsors and investors in the PPP construction projects. The investment from the foreign investors helps in bringing financial stability to the PPP project which helps in overcoming the risks associated with the financial condition of the undertaken construction project. The Australian government give emphasis on the process and procedures should be laid down for managing and allocating the risks in the early stages of the project.

The partnership with the private companies should be developed by signing the tender quotation at lowest price. The association of the bidding process helps in minimizing the risk impact by lowering down the structure and implication of risks severity and risks likelihood for the project. The successful allocation of the risks between the public and private parties helps in managing the risks effectively. The fuzzy logic theory and member functions for developing the consistency matrix for the risks should be identified so that the division of risks can be effectively done. The fuzzy logics help in setting out the project boundaries for designing and analysing the operation between the linguistic variables (Elkan, 2016). The member function should be developed for managing association between the risks identified (Mansfield community, 2013). The fuzzy logics help in developing the risks matrix for analysing the risks impact on the construction program. The severity, ranking, and likelihood of risks should be determined for managing the risks matrix. The following table shows the risk allocation between the participating parties and the method opted for managing the risks are described below:

Table 5: Risks allocation

Risks Identified	Risk allocation to Responsible parties	Methods for risks management
Technical risks	Private	The innovative technology should be implemented for carrying over the construction program. The older technologies should be replaced by the newer technologies. The organization of the training and development program should be arranged for the employees.
Construction Design risks	Private	The design of the infrastructure should be according to the requirement placed by the Australian government in the development of the construction project.
Financial Instability risks	Public	Attracting foreign investors for managing the financial stability
Political association	Public	Managing government policies and principles according to the demand and requirement
Resource management risks	Private	Managing resources for the effective development of the construction project
Asset management risks	Private	Managing assets for improving the process structure
Permission risks	Public	Taking legal permission from the public sectors
Land unavailability risks	Public	Managing availability of land to the private companies
Tax based risks	Public	Tax imposed on the project should be paid by the government authorities
Failure of hardware, software, process, and procedures	Private	Managing alternative medium for hardware and software requirement at the time of emergency and failure
Corruption and bribery risks	Public/ private	Rules and obligations should be imposed on the public and private authorities for taking bribes and doing corruption
Public sector interruption risks	Public	Meeting should be arranged after fixed interval of time between public and private sectors
Government policies framework risks	Public	Policies and procedures by the government should be designed
Third party management risks	Private	Managing resources with the help of third party association
Increasing interest risks	Public	Government should pay attention to manage the rising interest rate of the project
Failure of decision risks	Private / Public	Arrangement of training and development program to enhance decision making skills
Market analysis risks	Private	Managing key performance indicators for analysing the success criteria
Market change risks	Public	Managing key performance indicators for analysing the success criteria
Demand Change risks	Public	The communication flow should be managed between the management of supply and demand of resources
Competition risks	Private	Increasing competition
Re-settlement of the public risks	Private / Public	Proper planning for the re-settlement of the people

 (Source: Prepared by Author)

The deployment of the Fuzzy logic member functions helps in identifying the linguistic variables for defining the fuzzy values to the risks associated to the project. It helps in analysing the risks severity and risks likelihood which in turn helps in analysing the combined effect of the two to analyse the risks impact (Rajput, 2017). The uncertainties associated with the PPP projects can be effectively managed by applying the principles of fuzzy logic for the allocation of risks.

Conclusion

It can be concluded that evaluation of anomalies which are associated with the development of construction program helps in analysing the complexities, risks, and issues which are responsible for the project delay and overrunning of the cost. The development of agreement between the public and private authorities focuses on managing the balance between them so that the complexities and risks can be effectively managed between the two parties by allocating risks between them. The contribution of the authors in constructing the research paper is given preference to analyse the complexities associated with the public private partnership projects. The systematic arrangement of the risks in the matrix and applying the fuzzy logic principles, methods, and application helps in identifying the risks allocation procedures effectively. From the study of literature review and the analysis and findings of the proposed research study to demonstrate the identification of risks and risks allocation by making use of fuzzy logic. The major criteria for the implementation of Fuzzy logic to distribute the risks allocation between the participating organization was to gain value for money and increase the GDP of the nation so as to attract the foreign investor to develop business partnership with the Australian government. The allocation of the risks should be based on the principles and guidelines provided by the Australian government. The focus should be given on managing the communication between the public and private sectors to make availability of resources. The assessment of the risks helps in completing the project successfully. The handover of the risks during the project initialization helps in analysing the critical path of the project which should be followed for the accomplishment of given task within the given period of time and cost. The evaluation of the PPP project helps in resolving the inappropriate procedures followed for managing the risks between the members. The value for money can be gained by giving emphasis on the procedures used for defining the parameters of managing risks allocation procedures.

The limitation of the project is that the research study is based on the selected literary sources from online and offline media. The privilege is given to the work done and methodologies adopted by the different authors to carry out their research work. The future scope of the project is to deploy the quantitative approach on analysing the efficiency of the fuzzy logic in determining the risks and risks allocation among the participating public and private sectors. It is recommended that the proper format should be adopted for identifying the risks, risks analysis, and effective management and allocation of risks associated with the projects.

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