Risk Management Impact Assessment on the Success of Strategic Investment Projects: Benchmarking Among Different Sector Companies :

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Vol.7, No.3, pp.55-94


Filip Jovanović1 , Nenad Milijić2 , Makedonka Dimitrova3 , Ivan Mihajlović2 1 Faculty of Project and Innovation Management, Boze Jankovica 14, 11000 Belgrade, Serbia 2 University of Belgrade, Technical Faculty in Bor, Management Department, Vojske Jugoslavije 12, 19210 Bor, Serbia 3 University American College Skopje, Faculty of Business Economics and Management, Blvd. Treta makedonska brigada no.60, Skopje 1000, Macedonia filip.jovanovic@mozzartbet.com, nmilijic@tf.bor.ac.rs, dimitrova@uacs.edu.mk, imihajlovic@tf.bor.ac.rs



Abstract: The paper explores the impact of the main elements of the strategic investment projects management process in South East Europe (SEE), on achieving project objectives. The impact of different projects elements on the project’s risk management process was also addressed. The initial hypotheses are based on literature review in the field. The proposed hypotheses were tested by the SEM (Structural Equation Modeling) methodology on a sample of 311 strategic investment projects in Serbia, Bosnia and Herzegovina as well as Macedonia. The strategic projects were analyzed in companies across various business sectors thus the obtained results represent a benchmark of risk factors’ significance according to the project team members and managers. The benchmarking of risk factors significance was conducted by using the PROMETHEE – GAIA methodology. The results verify the adequacy of the hypothetical framework. Keywords: risk management; strategic investment projects; project objectives


1 Introduction:

 Strategic projects (SP) are of great significance for organizations, as they enable environment for realization of strategic objectives. The SP may vary from major investment projects, such as, construction of a new factory or plant, introduction of modern technology, improvement of energy efficiency etc., to somewhat smaller projects such as information system introduction, development and implementation of a new organizational structure, quality system introduction or similar. Asrilhant et al. suggested that the strategic projects are necessary when an organization strives to achieve its long-term objectives and development [1]. In this respect, Schoemaker defines the strategic projects as a manner of implementation and realization of a sound organizational vision [2]. Moreover, SPs are connected to the main investments of the companies and often bear considerable risk and uncertainty, intangible benefits and enable attractive longterm financial benefit [3, 4]. The strategic project management process helps achieve the projects’ successful implementation, including the financial and the non-financial outcomes, as well as, the benefits. Strategic project management includes two primary phases: the evaluation phase and the monitoring phase [5]. The evaluation phase includes development, planning and the evaluation of the strategic projects as well as the project approval. The strategic projects’ monitoring phase envisages the project management, the control and possible adaptation processes in case of necessity [1]. Efficient strategic project management may be achieved if the responsible project manager and the project team perform in accordance with the evaluation and monitoring phase requirements; all based on the predefined influence elements [6]. The process involves application of contemporary methods and techniques necessary to achieve efficient management of the strategic projects [7]. In practice, strategic investment projects most frequently apply the following techniques for their evaluation and monitoring: the return on investment, the net present value, the internal rate of return, the repayment period, the cost benefit analysis, the sensitivity analysis, the decision tree, the risk analysis, the forecasting methods, the game theory, the simulation etc. [1]. Selection process of the methods and techniques to be used in the strategic project management process involves prior analysis and assessment to which extend certain methods and techniques would be applied, if applicable at all [8]. The evaluation and the forecasting of future undertakings, processes and activities are accompanied by uncertainty and risk. Some future project settings might bear risk that could lead to negative and in rare cases positive impact on the project implementation [9]. This is the reason that the project management process entails appropriate project risk management. According to Kerzner, the risk management is an action or an exercise for dealing with risk [10]. The project risk management includes several related actions, such as the risk planning, the identification and analysis of risk events, the development of strategies for risk handling and monitoring, all oriented towards the project success [11]. Successful risk control and management in the strategic investment projects may lead towards the successful projects’ implementation. The level of success may be estimated by application of an appropriate criterion [12].

This research paper focuses on the strategic investment projects’ (SIP) management processes in the companies from the industrial and the non-industrial sectors in South-Eastern Europe (SEE), in particular from Serbia, Macedonia and Bosnia and Herzegovina. Research results from all three countries were analyzed simultaneously. We can explain this decision based on the similarity of all three countries. Namely, not long ago they were Member States of one country, Yugoslavia. Even today, political, economic, social and technological factors do not differ much in all three environments and therefore, we assumed that there should not be much differences in the responses. This research endeavor targets the risk management process, primarily in terms of understanding the effective management process at SIP. Therefore, the objective of this paper is to analyze the impact of the main elements of the risk management processes at SIP in SEE on the achievement of the project goals as well as the impact of the project elements on the risk management process. The importance of the risk factors, were determined, by benchmarking, in accordance with the opinion of the project managers and team members operating across different sectors.


2 Theoretical Framework and Research Hypotheses :

The research framework of this work was preceded by extensive analysis of the available literature in the field of SIP risk management. Numerous recently published research papers pointed out to the relationship between the appropriate methods for the risks analysis and assessment based on the factors of significance for the decision makers, for evaluation of the overall success of SIP [13, 14, and 15]. Therefore, we have defined the first research hypothesis of this paper as follows: H1: The application of the methods for risk analysis and assessment is directly related to the risk factors significant for the success of the company’s projects Given the significant relationship between the methods used for the analysis and assessment of risks and the risk factors that are primarily manageable [16, 17, 18], we have defined the second research hypothesis as follows: H2: The application of methods for risk analysis and assessment is directly related to risk factors of significance for project risk management The contemporary literature dealing with project risk management identifies that the analysis of risk factors is significant for the project’s success and their relationship with the risk management success [19, 20, 21]. The following hypothesis is based on the previous findings: H3: The risk factors of significance for the success of a company’s projects influence the risk management results Analysis of the factors significant for risk management and their relationship with the success of risk management is featured in a many research publications as well [22, 23, 24]. Based on results of the authors of the aforementioned papers, the following hypothesis is proposed as: H4: The factors of significance for project risk management affect the risk management results On the other hand, some of the latest papers dealing with the correlation of elements of significance to SIP control, and the applied methods for project management [25, 26, 27], have led to the proposal of the following hypothesis: H5: The elements of significance for the control of the strategic investment project are directly correlated to the methods for strategic investment project management Apart from that, numerous authors emphasize that the applied methods for SIP management are directly related to a significant criteria for measuring the project success [28, 29, 30]. Therefore, the following hypothesis is further defined as: H6: The methods for strategic investment project management are directly correlated to the main criteria for measuring project success In addition to the six research hypotheses, the following statements would be considered axioms, since they are widely accepted in theory and practice [9, 31, 32, 33]. A1: The results of the project risk management affect the results of the strategic investment project management A2: The main criteria for measuring the project success affect the results of the strategic investment project management.


3 Sample and the Data Collection:

 The research objective of this paper is to understand the extent to which the risk management process of SIP may be characterized by a set of elements, set forth by the project managers as the most significant ones and which are in accordance with the wide range of data available in the literature related to the topic. The identified elements of significance were then grouped in several groups of research questions. The data collection in this particular research used the questionnaire based methodology [1, 31]. The questionnaire consisted of two parts. The first part consisted of 10 (ten) control questions of a demographic character relevant to the surveyed sample (project-oriented companies, respondents and projects). The second part of the questionnaire featured 42 questions in the field of risk management and significant factors for SIP management, all divided into appropriate groups defined in accordance to proposed hypothesis, as presented in the Appendix 1. Based on the questionnaire, the opinions of the project managers on the importance of the methods for analysis and assessment of project risk were reviewed (1st group of questions – G1), along with risk factors having the greatest impact on the projects’ success (2nd group of questions – G2), then the most significant factors for the project risk management (3rd group of questions – G3), the elements significant in the process of SIP control (4th group of questions – G4), the methods for the evaluation and control of SIPs (5th group of questions – G5), as well as the main criteria for measuring the success of SIPs (6th group of questions – G6). The impact of each of these groups of factors on the achieved results of project risk management (Key Question 1 – Q1), as well as the success of management of SIPs of the investigated companies (Key Question 2 – Q2) were then analyzed. The Likert scale was used to measure the different levels of significance, where 1 represents the lowest significance (I absolutely disagree) and 5 represent the highest significance (I absolutely agree). Also, certain questions were of a dichotomous character (yes/no). In order to collect relevant data, project managers and project team members were sampled, in particular those in charge for SIP management or those involved with SIP on frequent basis. A total of 400 questionnaires were sent to potential respondents, 311 of which, were fully completed within the stipulated deadline from Serbia, Bosnia and Herzegovina and Macedonia. A relatively high response rate was achieved, owing to the persistence and the direct contact between the researchers of this paper and the surveyed managers and employees. Employees–non-managers were also included in the research, with the condition that they were engaged in the project teams of the company. Detailed demographic indicators of the companies.

4 Results and Discussion :

In the following text, the results of the data analysis are presented, in order to identify the relationship among elements of SIPs, as outlined in the initial hypothetical framework. Subsequent to the data entry into a database, we have proceeded to data analysis using the corresponding statistical analysis tools. The statistical analysis included the measurement of adequacy of the whole sample and the validation of the data structure. Then the analysis of the reliability of the risk management indicators of SIPs, placed within the appropriate factor groups, was performed along with testing the initial hypothetical frameworks through the application of structural equations modeling. The statistical analysis of the collected data was performed using the software packages SPSS 18.0 and LISREL 8.80.

4.1 Measures of the Sampling Adequacy and Structure Validation The measure of sampling adequacy analysis was performed by using the Kaiser– Meyer–Olkin (KMO) and Bartlett tests. Based on the recommendations of other authors, the minimum acceptable value of the Kaiser–Meyer–Olkin indicator is 0.6 [34]. The analysis showed that the coefficient of the Kaiser–Meyer–Olkin (KMO) sampling adequacy test, for the results of the questionnaire conducted in this research, is 0.738, indicating that the collected data is suitable for the application of factor analysis. Aside from that, the Bartlett test of sphericity shows the importance (χ 2 = 592.16, p < 0.000), indicating that there are acceptable correlations among items within the measuring instrument, and that the correlation matrix is not a unit matrix [35].


4.1.2 Factor Analysis The factor analysis was performed in order to extract questions that should be kept within the main factors of control and evaluation of SIPs, as well as the analysis and the management of project risks, placed in the groups G1-G6. The relationships between the measured variables are such that their regrouping into smaller sets of variables may be performed, representing a more concise and understandable structure of the examined field [35]. Based on the results of the factor analyses, it was concluded that, in almost all question groups, certain questions should be eliminated from the final model or further divided in the subgroups. Accordingly, for the group G1 – the analyses of the methods for the assessment and analysis of project risks (Appendix 1), the factor analysis revealed that questions 1.1-1.5 should remain in this factor group, while the questions 1.6. – 1.8 should be removed due to the low factor loadings. Similarly, only the questions 2.1, 2.2 and 2.3, from the group G2 – the results of the risk factors having impact on the project success, should remain in this factor group, while the questions 2.4, and 2.5, should be avoided from the following analysis. On the other hand, considering the large number of questions in the group G3, it should be divided into two factors (the subgroups G3.1 and G3.2), with the group G3.1 including the questions 3.1 – 3.3 and 3.5, and the group G3.2 including all other questions. Almost all the questions in the group G4 – elements of significance for SIP evaluation and control, are in the same factor, with the exception of the question 4.5. The questions in the group G5 – the methods of SIP evaluation and control are one-dimensional, as all of them should remain in just one factor, according to their high factor loadings. The questions in the group G6 – the criteria for measuring SIP success should all remain within one factor, except for the question 6.6, which should be removed from the further analysis. The accuracy of such segmentation of the questions, resulting after the factor analysis, was verified using the analysis of reliability of the listed grouped indicators of SIP risk management, presented in the following text.

4.3 Structural Model:

 The Structural Equation Modeling (SEM) represents a multivariate statistical technique used to analyze the structural relations between the dependent and latent variables. Its greatest advantage is the possibility for multivariate analysis at one time. Two types of variables are identified in the analysis i.e. endogenous – variables determined by the system or variables deriving from the models (representing an equivalent to a dependent variable), and exogenous – variables outside the models, meaning that their values are accepted as given (representing the equivalent to an independent variable). SEM tests and evaluates the relationships in a model using a combination of statistical data and qualitative causal assumptions. It can be used for the verification or development of hypotheses, or for the confirmative or research purposes. One of the great strengths of this type of modeling is the ability to create latent variables, variables that may not be measured directly but are assessed in the model based on other measured variables. These variables are actually grouping factors of certain measured variables. In order to develop a model of structural equations, the grouping of the initial measured variables by application of, for example, factor analysis, is performed beforehand. Based on the conclusions drawn from the results of the statistical analysis, especially the factor analysis described in the previous text, and in order to verify the initial research hypotheses, the structural models for the analysis of risk in the examined SIPs were set. The models are presented in Figure 1. The following correlations have been verified through the structural equation model (Figure 1a): – The applied methods of the project risk assessment and analysis (G1) are positively related to the risk factors that affect SIP success (G2). The correlation level is 0.41. It may therefore be concluded that the research hypothesis H1 has been verified. – The applied methods of the project risk assessment and analysis (G1) are also positively related to the risk factors that affect SIP success (G3). The correlation level is 0.60. Verification of the hypothesis H2. – The risk factors affecting the overall project success (G2) are positively related to the achieved results of the project risk management (Q1). The correlation level is 0.32. Verification of the hypothesis H3. – The factors affecting the project risk management (G3) are also positively related to the achieved results of the project risk management (Q1). The correlation level is 0.37. Verification of the hypothesis H4. – The achieved results of the project risk management (Q1) are positively related to the success of SIP risk management (Q2). The correlation level is 0.74. Axiom A1. The following correlations have also been verified (Figure 1b): – The elements of the significance in the process of SIP control (G4) are positively related to the methods for evaluation and control of SIPs (G5), with the correlation level of 0.41. Verification of the hypothesis H5. – The methods for evaluation and control of SIPs (G5) are positively related to the criteria for the measuring of SIP success (G6), with 0.40 correlation. Verification of the hypothesis H6. – Finally, the criterion for measuring the success of SIPs (G6) is directly related to the success of SIP management (Q2), with correlation level of 0.59. Axiom A2.


Conclusion :

Strategic investment projects represent the very foundation of economic development and the development of Society, in general. Detailed analysis and approaches to the management of every single element of these types of projects is required given their level of significance. The potential risks and their adverse effects, represent a particularly weighty part of that process, especially the possibility to eliminate or minimize them or respond in a suitable way. The statistical analysis of the data collected through a survey of employees in 311 companies and organizations within the area of SEE, dealing with SIP management within their operations, leads to the following conclusions. The initial questions in the questionnaire, as well as the initial hypothetical framework of the research, have been defined based on the analysis of the available literature in the field. Accordingly, six research hypotheses were proposed based on the relation between application of the methods for risk analysis and identified risk factors influencing the SIPs success in SEE. Conducted factor analysis, according to the question groups in the initial questionnaire, indicated that subgroups should be formed within certain groups, whereas certain questions should be eliminated from the further analysis. The final groups of questions, classified by factors, were used to develop a structural model, used for verification of the previously set hypothetical framework.

Based on the formed structural model for risk analysis of SIPs, it can be concluded that the hypotheses have been verified. The obtained results could be of use for the risk analysis and the strategic project management, connecting the identified project risks with applicable methods for risk analysis, in the real life project management practice. Finally, the obtained results, presented in this paper, represent a solid foundation for the continuation of the research and the development of a final measurement instrument and model of SIP risk management. We suggest that future research should apply the GLM multivariate procedure and focus on the influence of the most significant demographic characteristics of the projects (project type, project duration, project budget and type of project management), as well as, the different methodologies for risk management of the projects, on the overall SIP success. Also, additional research endeavors should target new and larger samples of respondents.



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