1. Régimen jurídico del monopolio
2.2. Formas de gestión de los servicios de telecomunicaciones
2.2.2. Gestión en libre competencia
Financial Management module is the highest ranked with score of 3.94, and the lowest is Portfolio Selection and Analytics module with score of 3.24. Beside the average value for Portfolio Selection Analytics module, only Business Intelligence module also has the average value below the total average value of all modules.
Portfolio Selection and Analytics and Business Intelligence and Reporting modules have the highest standard deviation (table 1). The key reason is that employees don‟t know or don‟t understand the usage of these two modules in organizations.
Table 1. Influences of the project management web modules on project management success
Project Management Modules Average Standard
Deviation
Variance
Project and Resource Center 3.71 0.78 0.61
Time and Schedule Management 3.78 1.01 1.01
Financial Management 3.94 0.76 0.58
Business Intelligence and Reporting 3.29 1.19 1.41
Collaboration 3.78 0.88 0.77
Portfolio Selection and Analytics 3.24 1.19 1.42
Risk Management 3.65 0.87 0.75
Dominant results are indicative for Public sector (table 2). For Public sector highest value is related with time and schedule management, which means that employees in public sector appreciate most the time, but on the other hand conclusion for this module can be related that working time is different according to sector, and with many others criteria (e.g. conditions, job security, advancement, growth, power, affiliation, esteem, decision-making processes, rewarding systems, task-related rules as well as social rules, like punctuality in task completion, agreed time to read and respond to messages, respect of consensus decisions, honesty, truth, preparation for and attendance to meetings, punctuality on meetings, etc).
Also, Business Intelligence and Reporting module in Public Sector has the lowest value, which could be consequentially related with time management and critical success factors (table 3). The implementation of business intelligence and reporting does not always result in expected outcomes. This problem, called paradox of productivity (delays in the observation of an increase of productivity, poor management of business intelligence and reporting, poor qualified workforce, or the difficulty to estimate, by means of an accounting treatment, the result (profit/loss) of an investment in Business Intelligence and Reporting. Raffo, (2005) emphasize „forward-looking‟ decision support framework that integrates up-to-date metrics data with simulation models of the software development process in order to support the software project management control function, considering the focus on the overall decision framework using outcome based control limits, utility functions and financial performance measures (e.g. return on investment, net present value, break even point and others) which is new.
Table 2. The average value of responses regarding to the Influence of the various web modules on project
management success by sectors
Influences of the various web modules on project management success:
Public
Sector Non-profit Sector Profit Sector
Project and Resource Center 3.2 3.75 3.76
Time and Schedule Management 4.2 3.5 3.76
Financial Management 4 3.25 4
Business Intelligence and Reporting 2.4 4 3.33
Collaboration 3.4 3.75 3.83
Portfolio Selection and Analytics 3.6 3.75 3.14
Risk Management 3.4 3.75 3.67
Table 3. The average value of critical success factors and the average value of influences of the various web
modules on project management success
How often are critical success factors defined in
the projects via web platform?
Influences of the various web modules on project management
success
Public Sector 4 3.46
Non-profit Sector 4.25 3.68
Project management software packages generally facilitate the integration of project data, the interaction with enterprise systems and the interoperability with business intelligence and reporting systems. Besides optimizing the productivity of the teams, the system allows to make better decisions, to maintain a competitive advantage and to implement an effective project management. This type of software consists of subsystems developed to treat various aspects of project management: procurement, construction, cost control and analysis, planning, quality insurance, etc.
4. CONCLUSION
Successful project management information system implementation in organizations depends on the following criteria: business process definition, maturity level of the company, number of employees, budget, number of projects, number of specific requests, etc. Difference between profit, non-profit organizations and organizations in public sector about project management system implementation could be noted in two modules - Portfolio Selection and Analytics and Business Intelligence and Reporting modules. Future consideration will include agile methodology and its application on software projects. Clients are seen to have matured in their understanding of IT projects, because maturity reveals itself in a greater understanding of the complex issues that confront IT projects and, therefore, a deep skepticism about the ability of IT departments and suppliers alone to deliver value.
Acknowledgments
This paper is a result of Strategic Project founded by Ministry of Education and Science of republic Serbia: Exploring modern trends of strategic management of the application of specialized management disciplines in the function of the competitiveness of Serbian economy, No 179081.
REFERENCES
Abbassi, M., Ashrafi, M., & Sharifi Tashnizi, E. (2014). Selecting balanced portfolios of R&D projects with interdependencies: A Cross-Entropy based methodology. Technovation, 34(1), 54–63. doi:10.1016/j.technovation.2013.09.001
Bowen, P., Edwards, P., Lingard, H., & Cattell, K. (2014). Occupational stress and job demand, control and support factors among construction project consultants. International Journal of Project Management. doi:10.1016/j.ijproman.2014.01.008
Halawa, W. S., Abdelalim, A. M. K., & Elrashed, I. A. (2013). Financial evaluation program for construction projects at the pre-investment phase in developing countries: A case study. International Journal of
Project Management, 31(6), 912–923. doi:10.1016/j.ijproman.2012.11.001
Hameri, A.-P., & Heikkilä, J. (2002). Improving efficiency: time-critical interfacing of project tasks.
International Journal of Project Management, 20(2), 143–153. doi:10.1016/S0263-7863(00)00044-2
Liu, J. Y.-C., Chen, V. J., Chan, C.-L., & Lie, T. (2008). The impact of software process standardization on software flexibility and project management performance: Control theory perspective. Information and
Software Technology, 50(9-10), 889–896. doi:10.1016/j.infsof.2008.01.002
Nikas, A., & Argyropoulou, M. (2014). Assessing the Impact of Collaborative Tasks on Individuals‟ Perceived Performance in ICT Enabled Project Teams. Procedia - Social and Behavioral Sciences, 119, 786–795. doi:10.1016/j.sbspro.2014.03.088
Obradovic, V., Jovanovic, P., Petrovic, D., Mihic, M., & Bjelica, D. (2014). Web-based Project Management Influence on Project Portfolio Managers‟ Technical Competencies. Procedia - Social and Behavioral
Sciences, 119, 387–396. doi:10.1016/j.sbspro.2014.03.044
Pinto, J. K., Dawood, S., & Pinto, M. B. (2014). Project management and burnout: Implications of the Demand–Control–Support model on project-based work. International Journal of Project Management,
32(4), 578–589. doi:10.1016/j.ijproman.2013.09.003
Raffo, D. M. (2005). Software project management using PROMPT: A hybrid metrics, modeling and utility framework. Information and Software Technology, 47(15), 1009–1017. doi:10.1016/j.infsof.2005.09.004 Salas-Morera, L., Arauzo-Azofra, A., García-Hernández, L., Palomo-Romero, J. M., & Hervás-Martínez, C. (2013). PpcProject: An educational tool for software project management. Computers & Education, 69, 181–188. doi:10.1016/j.compedu.2013.07.018
Sanchez, H., Robert, B., & Pellerin, R. (2008). A project portfolio risk-opportunity identification framework.
Project Management Journal, 39(3), 97–109. doi:10.1002/pmj.20072
Singh, A. (2014). Resource Constrained Multi-project Scheduling with Priority Rules & Analytic Hierarchy Process. Procedia Engineering, 69, 725–734. doi:10.1016/j.proeng.2014.03.048
Unger, B. N., Gemünden, H. G., & Aubry, M. (2012). The three roles of a project portfolio management office: Their impact on portfolio management execution and success. International Journal of Project
Management, 30(5), 608–620. doi:10.1016/j.ijproman.2012.01.015
Yaghootkar, K., & Gil, N. (2012). The effects of schedule-driven project management in multi-project
environments. International Journal of Project Management, 30(1), 127–140.