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ANTECEDENTS OF DECISION MAKING ERRORS IN PUBLIC SECTOR

Nadeem I Kureshi, Center for Advanced Studies in Engineering, Islamabad, Pakistan. nadeemk@case.edu.pk.

Ammar Asghar, Center for Advanced Studies in Engineering, Islamabad, Pakistan.

Citation: Kureshi N and Asghar A, (2015). Antecedents of Decision Making errors in public sector, Journal of Strategy and Performance Management, 3(4), 159-177.

ABSTRACT Decision-making  is becoming increasingly challenging with increased  span of control of decision makers and reduced time to make decisions. This time can be few minutes or much lesser in high profile decision making situations. Complexity of this problem increases due to the limited information available on which the decisions have to be based. If more information is sought or attempts are made to solicit more information, decisions are delayed and opportunities can be lost. The problem is more pronounced in public sector due to a general lack of formal decision-making related training and budgetary constraints that impose deadlines and thus force decision-making using sub-optimal conditions. The purpose of this study is to propose a model whereby antecedents that may lead to ineffective decision-making are identified and addressed, thus increasing the probability of optimal decision-making. Detailed interviews with 55 Aviation industry officials from three different companies working for three different projects in the areas of Integration, Research & Development and Maintenance within Public Sector, formed the research base of this paper. The questionnaires designed were on the basis of previous researches and PMCD framework. The results have been established on the basis of various iterations of answers from outcomes of the questionnaire fed to the panel of expertise and analyzed in SPSS v 17.0. This research identifies the gaps and proposes an improved process map incorporating the techniques of Analytic Hierarchy Process (AHP) and Multiple Criteria Decision Making (MCDM). Implications derived from this study can be highly beneficial in development of effective decision making process map in public sector organizations.

Keywords: Decision Making, Biases and limitations, improved process maps, AHP, MCDM

INTRODUCTION Public sector organizations have not traditionally been associated with quality decision making. Several theories have been used to demystify the antecedents leading to the quality of decision making in public sector such as Agency Theory (Jensen and Meckling, 1976; Fama,1880; Eisenhardt, 1989), Contingency

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Theory (Beach & Mitchell, 1978; Tarter & Hoy, 1998) and a plethora or other theories in context of organizational management, economics, social sciences, education management inter alia. With the ever increasing challenges of reduced time and limited information available for decisions coupled with increased pressure of the public sector organizations for managing resource efficiently amid shrinking resources, this challenge os expected to increase further. Such pressures are forcing the public sector to look for working models used by the private sector.

This research is designed to investigate different challenges encountered by public sector decision makers when in situations requiring decisions with high impact. Decisions can fail because the most appropriate alternatives are not viable enough at the outset or the vital factors are not measured as integral part of the whole process. This is avoided when problem-solving and decision-making strategies are brought together to clarify your understanding towards a particular problem. A logical and ordered process always helps to address all of the critical elements needed for a successful outcome.

LITERATURE REVIEW Successful organizations decide their preferences in three ways at least: they make better-quality decisions; the decisions they make are faster; and they make sure almost all the decisions they make are implemented well. Simon (1960) projected a three phase model of the decision process including all the activities of perceived Intelligence, Design and Choice. Intelligence includes identifying and detecting the need for a decision. Design actually begins when a need to make a decision is identified and determines when a choice is ready to be made. (McLaughlin 1995).

Weick (1979) expresses the design phase as mobilizing from an ineffectual scheme of reality to a workable version of reality. The latest choice phase defines the actions and activity of choosing the most suitable mode and course of action. Decision Analysis (Keeney, 1982) and the Analytic Hierarchy Process (Saaty, 1980) are two well-known examples of this approach. Such approaches tend to adopt a one size fits all approach, to make unreasonable assumptions about decision maker rationality and are not always cognizant of the different environments which constrain the decision making process. The impact of these constraints is such that many (e.g. Nutt, 1993) have rejected the more normative approaches for decision support, and have turned their attention to descriptive approaches which take account of real-world constraints. Rather than requiring decision makers to behave in certain prescription, descriptive approaches starts with how decisions are actually made and from there seek to improve these processes (Dillon 2002).

Dillon (2002) has proposed a simple, non-directive, process-based definition: Decision structuring is the process by which a decision situation is transformed into a form enabling choice. The decision making process in public sector is quite simple. It constitutes of three fundamental elements. These factors to be precise are aims that ultimately turn into goals, standards, human personality and the prevailing environment. As per these three concepts, the decision makers in the public sector choose these steps to be followed. Some of the DM

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processes are far more important and yield better outcome than others. Kahalas, 1976).

Contextual constraints and influences play significant roles in structuring public sector decisions. Because of the constrained nature of decisions made in this environment, human behavioral aspects have less influence. Another obvious point of difference with the public sector model is sequentially of process; only public sector senior managers were able to describe activities that had any form of sequential process. Given that disagreement about ends or goals is a feature of the public sector, beginning with objective definition is not surprising. Furthermore, the need at this sector demands transparency and importance of clearness of goals. Alternatives are produced and information is gathered only after goals have been identified. The alternative generating process and collecting information are activities to be performed simultaneously. The character and nature of information collected is strongly affected by the requirements and criteria of the sector and the exacting decision situation. Typically public sector decision making generally emerges from inside the organization that may be the bottom-up, surprising and therefore unpredictable (Bozeman & Pandey 2004).

Research in social psychology and behavioral economics has continuously shown that managers are quite irrational when it comes to decision making. Every day in organizations high authorities are inundated with decisions big or small. There are several factors that influence their decisions. Understanding of the factors, biases and errors which occur while DM, is of vital importance to improve the process of decision making. Literature abounds on investigations on biases in decision making such as Cognitive Bias (Kahneman & Tversky 1996), Confirmation Bias (Nickerson, 1998; Kahneman, 2011), Stability Bias (Kornell & Bjork, 2009; Kornell et al, 2011), Action-Oriented Bias(Sibony, 2011),Anchoring, Over-confidence bias(Lovallo, 2011) and the like.

Some of the decision Making tools to overcome biases, suggested in literature are discussed below:

Decision Analysis: Previous studies have revealed some techniques which are designed to manage the cause of biases in DM process. Out of the common techniques one of the most common is Decision Making Analysis. It is defined as an organized, quantitative and illustrative approach to estimate and evaluate important options and choices faced by businesses. Decision analysis is a tool which consumes a variety of tactics and tools to evaluate all applicable, relevant information to aid DM process. A graphical depiction of alternatives and choices, as well as disputes and doubts, can be carved on a decision tree or an influence diagram. This term, decision analysis, was originated back in 1964. (Ronald A. Howard, Professor of Management Science and Engineering at Stanford University, 1964).

Analytic Hierarchy Process: Analytic Hierarchy Process (AHP) is considered to be the most popular and widely accepted multi attribute decision aid method. The top leadership needs to compare the possibilities utilizing a decision problem with an inherent character of trade off between certain criteria in order to make best use of this tool. AHP is a multi-criteria decision making technique

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which directly relates to diversity of situations with quite reasonable results. This technique can enable decision making authorities to a comprehensive, rational and productive framework for structuring and dealing with a decision problem to represent and quantify its elements for making a relation among those eminent elements. It also helps in evaluating alternatives that could help the managers in managing their tasks according to the priority drafted on a prior basis.

The strengths of AHP comprises of the probability to evaluate not only the quantitative but also the qualitative criteria taking alternatives on the same scale, a verbal one. As a matter of fact, the use of verbal response is using one or the other more users friendly, appealing and quite common in our daily lives. In order to deduce the priorities the comparisons must be converted and turned into numerical ones. Anyhow the entered comparisons are not totally unique. They are totally dependent on the decision-maker ("The Journal of the Operational Research Society, Vol. 62, No. 4 (April 2011), pp. 700-710”)

The Journal of the Operational Research Society has reported several successful applications in different areas: including Information System, Supply Chain Management, Communication Management, Human Resource Management, Public Services, and Strategic Manufacturing. There are use one or the other surveys on the success of Analytic Hierarchy Process. AHP aids the decision makers in finding one best solution that suits their goal and the understanding of the stated problem. (The Journal of the Operational Research Society, Vol. 62,(April 2011), pp. 700-710)

Multiple Criteria Decision Making: The Multiple Criteria Decision Making (MCDM) model presumes that when a decision is to be made, DM authority defines a fixed set of criteria which is offered with a vibrant picture of all the alternatives available. The task is then reduced to calculating the score for each of the alternatives. Thus, it includes constructing a ranking and selecting the one with maximized value. Most decisions in the real world, made by the top leadership take place in an environment which is vibrant and dynamic, where the final choice is made only at the end of a tentative process. Investigation of the dilemma is often valuable, it may unveil beforehand unthinking alternatives or criteria. This technique of MCDM is inculcated in a decision making process in order to enhance the productivity of decision making process by the managers. This technique is imperative for decision making authorities to learn, as it is based on allocation of criteria with fixed parameters, which lessens the chances of missing out the important tasks. If the manager or any DM authoritative figure learns to adopt the technique of MCDM in their daily decisions, it would aid them to handle complex problems well and allowing for multiple criteria, will lead to better and well informed decisions. (Journal -of Management Information Systems, Vol. 1, No. 4 (Spring, 1985), pp. 24-43).

Some limitations in Decision Making are discussed below:

Prospect Theory: This theory is regarded as psychologically realistic alternative in contrast to expected Utility Theory (Kahneman & Tversky, 1979). Managers while making decision are subjected to dominance of risk associated with the decision, keeping the gains aside and thus the decision made, turns out to be

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unfounded. This leads to irrationality where losses tend to dominate human minds.

Span of Control: A span of control is defined as the employees in number prevailing under certain management or control at one time. Ideas regarding span of control keep changing. Once it was envisaged that fundamental human capacity determined the appropriate number of employees working under a certain command and control (Zealous hunters, 2009). It is not an easy task to determine the ideal span of control but history is evident due to pressures prevailing in terms of increased span of control, the process of decision making has faced a lot of issues. It may vary from nature of work and deadlines allotted to certain tasks. Sometimes the pressure due to increased span of control also affects the quality of decision so severely that it crashes up the whole dimension. With craftsmen this number can be possibly quite small because the level of direction needed is high. Talking about mass production, the span of control can be possibly many times more because each employee has a defined task to complete, needing little habitual oversight. (The Economist Guide to Management Ideas and Gurus, 2009). Views regarding ideal span of control have timely changed as regard to Public sector. For decades back in 20th century, talking about the first 60 years, the top leadership followed a well structured management style with little authority to each of the employees. The charge was taken up by only one or two in organizations to make decisions. Flatter, not having too many levels, less hierarchical and loosely structured organizations obscured larger spans of control. The mutual consent to an ideal span of control with time has risen to about 11-15 employees. According to GE's guideline no managers should have charge of more than 10 to 15 people reporting them directly. (Jack Welch, 2009).

Limited Information: Decisions which are based on complete knowledge and perfect reasoning can lead the organization to prosperity in the longer run. On the other hand decisions which are made on the ambiguities, hunches, defective logic, emotions, or information that is incomplete can rapidly put a business in the border of failure. As a matter of fact, weak decisions can cripple big, rich, in capital corporations over time. Ultimately, the thing that drives success of an organization is basically the high quality decisions made and implemented. A good business is nothing more but a mere reflection of good decisions. Managers make decisions on the basis of rationality but limited information available may force the managers to rely on hunches, intuition and gut feelings. This often affects the rationality of decision making process. Fair processes in decision making in public sector require adequate information based on justifiable and reliable sources. (Organization Theory and Design, 1992).

Personal Competencies: The process of decision making is influenced by personal competencies. There are two types of personalities. Type A and Type B, both have different attitude while a decision is to be made. Some decision makers are proactive, who not only make timely decisions but also foresee the factors that could affect their decisions through various dimensions. Apart from variance in personalities the skills and competencies in different managers, according to the grooming they have been through in the organization and in their academic experience. (Marsh, & Hanlon, 2007; Nestler. & vons Collani, 2008; Stanovich & West, 2008; see also West et al., 2008). With the passage of

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time the world has transformed into a paradigm having multiple options and technical props to solve and deal with everything, yet human abilities, personality and individual differences do play an important role in some of the very vital processes of business. Decision making is believed to be a reflection of one’s judgment that comes straight from human mind and psyche, the information gathered and perceived. To make a decision is dependent on personal vision to view things. Acevedo and Krueger (2004) inspected individuals’ voting patterns, and they concluded that people tend to vote more willingly when they believe in their opinion. Thus managers believe what they decide is important and it matters, they are more keenly indulged in decision making (Reed, Mikels, & Simon, 2008).

Research GapDecision making is an essential part of daily routine activities in all organizations. Many biases affect the quality of decisions. Aviation managers while making decisions get victimized to above mentioned biases which have been narrated in many theories; but no research until now has addressed such errors with regards to defense organizations in Public sector of Pakistan. This research will identify the biases affecting the DM process for aviation managers in defense organizations, in Public sector of Pakistan, at all stages of decision making, at all levels of management; and will propose a better DM process and approach by keeping aforementioned tools of decision making under consideration.

RESEARCH METHODOLOGY Research design for this study is causal as we want to examine the relation between biases and DM at different stages. It also helps in analyzing biases in detail at different stages of decision making in public sector. The instrument used for conducting research is questionnaire developed from former studies and framework described in Likert Scale. The questionnaire is used to measure following dimensions of biases in decision making:

- Psychological bias- Limited Information bias- Bias/error due to increased span of control

Biases in decision making are regarded as independent variable, whereas decision making is categorized as dependent variable. The 10 item questionnaires were answered by the managers of aviation industry public sector. Questions were divided in three types of major biases. First six questions measured the effect of psychological bias on decision making. Second set of questions (7-12) measured effect of bias / error due to limited information regarding DM. Last set of question (13-19) measured the impact of increased span of control on decision making which could serve as the root cause of biases. A five-point Likert scale was employed ranging from 1 (strongly disagree) to 5 (strongly agree). The questionnaire was synthesized by taking help from previous research. The software used during this research is SPSS.

Following demographic information was solicited in the beginning of questionnaire:

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- Service cadre (Defense service or Civilian)- Employment type (Permanent or Contractual)- Employment in Public Sector (Initially or Converted from other fields)- Designation in office (Senior Manager, Middle Manager, Lower Manager)- Academic Experience (Degree)- Tenure in current organization (Years)- Gender

In the second part of the questionnaire, variables extracted from the previous studies were included to measure the theoretical construct of the biases in decision making. Previous studies showed that the three major biases/limitations that could affect DM in Public sector are: Psychological Bias, Limited Information and Increased span of control. A total of 19 questions were asked, divided into three types of biases / limitations. Psychological bias (6 questions), Limited Information Bias (6 questions), and Biases due to increased span of control (7 questions). The questionnaire was designed on Likert scale format to get the agreement of respondent with each item on five pointer scale.

- Psychological Bias: PS- Limited Information Bias: LIS- Bias/limitation of increased span of control: ISC

Variable Description

PS1 Before making a decision I evaluate risk associated with it.

PS2 I try to determine the real problem before starting decision making process.

PS3 I focus more on cause of problem rather than the process adopted to solve a problem.

PS 5 I practice a well-defined process to structure my decisions.

PS 5 I decide the factors most significant to the decision, and then use those factors to make my decision.

PS 6 I prioritize the decisions to be made and then make one by one.

LIB 1 After I narrate my decision, I face difficulty in making an implementation plan.

LIB 2 If I have doubts about the decision I made, I recheck my assumptions and entire process.

LIB 3 I consider my past experience before reaching to final decision.

LIB 4 I think that including many stakeholders to create solutions can make the process more complex.

LIB 5 Once I make decision I do not consider it final and make changes till the end.

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Convenience sampling was used to examine the relationship between decision making and various biases effecting the entire process.The advantage this technique offers is quick responses. 55 respondents belonging to aviation sector in ICT region of Pakistan formed the sample. The unit of analysis is individual manager of public sector from defense having aviation background.

RESULTS The psychological Bias (PS) , limited information bias (LIB) and biases due to increased span of control (ISC) have an overall mean of 3.24. 58% biases in decision making are psychological, where as 30% of the biases are due to increased span of control and 12 % are because of limited information available.

LIB 6 I usually have a strong "gut feeling" about problems, and I rely on my intuition while making a decision.

ISC 1 I include my justification and reasoning when communicating my decision.

ISC 2 I am surprised by the factual consequences of decisions I make.

ISC 3 I manage time well and take my time to choose the best decision making tool for specific decision.

ISC 4 I like to make decisions on my own and then let other people know what I have decided.

ISC 5 I solely depend on my own experience to chase potential solutions to a problem.

ISC 6 Some of the alternatives that I have chosen often become more difficult to implement than I had anticipated.

ISC 7 It is always easy for me to work in a team while making decision.

Variable Description

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psychological LimitedInfo IncreasedSpanofControl

Percen

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DimensionofBiases

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The Psychological bias is most common in senior managers. Highest level of psychological bias 48% is found in high level managers. 31% of the bias intervenes at middle level and only 21% of the bias hits at the low level. Limited information bias is highest in low level managers, occupying 56% of the total bias. 23% of this bias is occurred at middle level management and only 21% of this bias affects the managers at high level. The bias due to increased span of control is highest in high level managers because of large network concentrated into conventional rigid hierarchy. 30% of the total bias affects the middle level management and only 12% of the total bias affects the low level managers.

Other Techniques used by Public SectorPareto Analysis: Pareto Analysis is used by defense officials in local public sector. On interviewing a high ranking key informant it was revealed that this technique is good at evaluating the performance but upholds less in putting the right decision on the table. This technique is used where decision making is involved at a larger scale and where too many decisions need to be implemented. This aids in prioritizing. It indicates which decisions should be made first by identifying which decisions will have the maximum overall impact.

T-Chart: The T-chart is used by weighing the pluses and minuses of the choices and options available. The T-chart ensures that all the positive and negative points and aspects are taken into consideration, when a decision is to be made. This is often used by the local officials when new equipment is to be purchased. One of the illustrations is mentioned below. Two of the three companies running the project of integration use this technique.

Decision Tree: On interviewing one of the senior officials in local aviation industry another process map of making decision was envisaged. A decision tree is often incorporated by the officials and other SMEs. This is a model or a graph that absorbs contemplating all options and the results of each. This method is often accompanied with statistical analysis to get the desired results.

Multi-voting: The technique of Multi-voting is considered when large number of people are involved in making a decision as reported during an in-depth interview session with a Program Manager in local public sector. It helps in whittling down a large catalog of options and aids in making a decision with all possible outcomes. Officials as public authorities frequently make administrative decisions as an integral part of conveying services to the public.  Most of the times, the decision-makers are required to exercise discretion while decisions are to be made. Most important role of decision maker is to make a judgment taking into account all relevant information.

Descriptive Analysis Demographics of the Respondents

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- Gender: Most of the respondents were male, which makes the percentage of 66 and 33 in number, whereas, female respondents are 17 in number and that makes a percentage of 34%.

- Service Cadre: The employees from defense were of 32%, whereas, civilian employees were 68%.

- Employment: Contractual and permanent employees were almost equally sample; at 52% and 48% respectively.

- Experience in Public Sector: As the experience increases employees tend to stay more at the organization as compared to less experienced employees. The data specifically shows that employees acquiring more than three years of experience rarely tend to leave the organization and formed 76% of the sample. Only 12% had an experience of 1 year or less.

- Qualification: PhD, M Phil, MS and Bachelor degree respondents were 8, 24, 66 and 2% respectively.

- Designation: Senior, Middle and Lower managers were 46, 18 and 36% respectively.

- Observed Variables: Following table shows the detailed data for observed variables.

Factor Analysis Factor Analysis was conducted for the research with following results:

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Following values were observed through KMO and Bartlett's Test:

- Kaiser Meyer Olkin Measure of Sampling Adequacy. .719

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- Bartlett's Test of Sphericity: Approx. Chi-Square 596.336, Df 171, Sig. .000

In the table below, Rotation Sums of Squared Loadings, shows only those factors that meet the cut-off criterion extraction method. (Eigen values = Load Factor) There are 5 factors with Eigen values greater than 1 whereas the “% of variance” shows how much of the total variability including all the variables together can be accounted for by each one of these summary scales. Factor 1 account for 20.418% of the variability in all 19 variables, and so on.

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Rotation Matrix Model: The Rotated Component Matrix shows the factor loadings for each variable. Highlighted the factor that each variable most strongly loaded on.

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Reliability: Cronbach’s alpha values for each construct are given below:

Similarly, the reliability and correlation data is given below:

PS LIB ISC

Cronbach’s alpha 0.837 0.799 0.861

Cronbach’s alpha (st items) 0.838 0.777 0.870

Items # 6 6 7

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DISCUSSION There are four broad classification of errors identified by experts, namely unreasonable assumptions, illogical interpretation, perceptual distortion and one size fits all approach. All of these errors are ineffective actions generated by human processing limitations.

Following explanations were offered by the respondents for occurrence ob the above mentioned errors, in order. Respondents were given standard definition of each:

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- Cognitive Bias- Monumentalizing the Trivial- Confirmation Bias- Stability Bias- Action-Oriented Bias- Anchoring- Overconfidence Bias- Psychological Bias- Limited Information Bias- Bias due to Increased Span of Control

All respondents were asked to outline the broad process followed by them while making decisions. They are then asked to identify the most influencing bias (Bias 1) and the second most influencing bias (Bias 2) which they expect to confront on each step. Broadly, following common process steps were identified by respondents, as their approach to decision making along with most and second most influencing bias:

Step Bias 1 Definitions Bias 2 Definitions

Problem Identification

Stability Influence/ acceptance of current state

Cognitive Illogical interpretation, perceptual distortion, subjective social reality

Information Gathering

Monumentalizing the trivial

Increase complexity of the matter

Action orientation

Action based on limited information

Alternatives Identification

Anchoring Jumping to conclusion

Confirmation Preferring options conforming to own beliefs

Ranking of Alternatives

Over confidence Exaggerated view of personal experience

Cognitive Illogical interpretation, perceptual distortion, subjective social reality

Decision Prospect theory Risk Aversion Over confidence Exaggerated view of personal experience

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THE PROPOSED MODEL Based on analysis of qualitative and quantitative data gathered and analyzed above, this paper proposes a 2 step approach to decision making in public sector.

The first part of the model consist of basic strategic steps of Decision Making process map that need to be made part of training of all the Aviation managers in Public sector. First 5 steps are extracted from the AHP model that needs to be inculcated in training of junior managers. Identifying the right problem at the right time leads to effective beginning of decision making process. Defining the problem and then relating it to achieve the goal is the right approach. The problem is then decomposed into a hierarchy of more easily comprehended sub-problems, each of which is then to be analyzed independently on the basis of criteria defined. This part of the DM process flow will eliminate the chance of psychological biases as defining criteria will confine the DM to think in right direction.

- Identify problem- Define problem- Formulate goal- Operationalize goal- Analyze available data- Define decision criteria and sub-criteria as appropriate- Predict performance and gain insight

The second part of decision making process consists of rational analysis of alternatives. The alternatives are to be measured on the basis of weights given according to defined criteria (Incorporating the techniques of AHP and MCDM). In this way, psychological bias is addressed which has the maximum percentage 58% to be precise among all the biases, which will automatically minimize the consequences faced by managers due to bias of increased span of control. Following are the broad steps:

- Define and examine alternatives- Choose preferred alternative(s)- Evaluate for missing and non-measurable aspects- Decide

CONCLUSION The study determined relation between decision making and factors like limited information available, increased span of control and personal competencies with biases acting as independent variable. The purpose of this research was to examine the biases at different stages of decision making process and then propose a better process map to eradicate such biases. The results exhibited significant relationships between these variables. The biases affect decision making at every stage and at all the levels of management. As the mean of psychological bias is quite high that’s why we can envisage that this is the most common error being committed by most of the decision makers in Public sector. The conclusions suggest that the biases do intervene when a decision is to be made in public sector, where no formal effective process maps are incorporated

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because of time pressure and other constraints, such as increased span of control. It does have a significant impact on the performance of the managers. If managers adopt a better framework to design effective process maps for making decision in public sector then the biases can be minimized. Mean of questions, measuring effect of psychological biases on decision making is 3.246, which is more than the other dimension of bias due to increased span of control. This shows that respondents are reasonably more affected by psychological bias when making a decision as compared to the burden of increased span of control. Result shows that this bias affects the decision makers of middle level managers because they have more power and authority but not high decision making skills thus they rely more on intuition and their past experience. This shows which level of management is affected by which particular bias while making a decision. Thus after the results of research, process maps are which needs to be adopted by different level managers to overcome biases.

RECOMMENDATIONS Top level managers should run training programs for their team to identify the biases in decision making process.

A formal effective process map for DM inculcating the techniques of AHP and MCDM should be made into practice with strictness to ensure follow up of a systemized DM process to curtail biases affecting DM.

In order to avoid psychological biases, team decision making should be encouraged. Making decisions within a group appears to be complicated but multiple parties reduces the limitation of limited information available and heightens the chance of access to different ideas, so conflict management should be made integral part of training of the managers.

Cost benefit analysis is always a rational approach to make decisions. Aviation managers should include the blend of T-chart, Decision Analysis and such techniques to make decisions with minimum chances of error.

FUTURE WORK Following areas can be explored in future researches:

- Numerous other dimensions of the biases and limitations not only in public but private sector can be studied for improved decision making process.

- Evaluating more projects based at different geographic locations worldwide may conclude different results.

- DM Improvement tools like AHP and MCDM were utilized in this research. There is a room to take into account numerous other tools.

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