PLS Path Modeling for Causal Detection of Project Management Skills: a research field in National Research Council in Italy


Framework of this paper is the causal detection of Project Management (PM) competencies in the world of science and research. Activation of hard and soft skills of Principal Investigators in public research organizations becomes crucial to improve the management of research projects toward efficiency and effectiveness. How important is the awareness of project goals?
What is the impact of leadership competencies with respect to other soft skills in PM? A conceptual model with theoretical constructs and latent variables is introduced to analyze the causal detection among different types of variables, including the activation of hard and soft PM skills of Principal Investigators in public organizations. Partial Least Squares Path Modeling is suitably defined and applied in a research field in the largest public research organization in Italy, namely the National Research Council (CNR)

DOI Code: 10.1285/i20705948v11n2p516

Keywords: soft skills; structural model; measurement model; model assessment; path estimation


AIPM (2008). Professional competency standards for project management. australian institute of project management.

Aria, M. (2015). PLS-SEM Matlab Toolbox.

Association, I. P. M. et al. (2006). Icb-ipma competence baseline version 3.0. International Project Management Association, Nijkerk.

Atkinson, R., Crawford, L., and Ward, S. (2006). Fundamental uncertainties in projects and the scope of project management. International journal of project management, 24(8):687–698.

Barnes, T., Pashby, I., and Gibbons, A. (2002). Effective university–industry interaction:: A multi-case evaluation of collaborative r&d projects. European Management Journal, 20(3):272–285.

Bass, B. M. and Avolio, B. J. (1994). Transformational leadership and organizational culture. The International Journal of Public Administration, 17(3-4):541–554.

Bassi, F., Clerci, R., and Aquario, D. (1978). Studentsevaluation of teaching at a large italian university: measurement scale validation. Electronic Journal Of Applied Sta- tistical Analysis, 10(1):93 – 117.

Bernardini Papalia, R. and Ciavolino, E. (2011). Gme estimation of spatial structural equations models. Journal of classification, 28(1):126–141.

Blake, S. P. (1978). Managing for responsive research and development. WH Freeman.

Bonner, N. A. (2010). Predicting leadership success in agile environments: An inquir- ing systems approach. Journal of Management Information and Decision Sciences, 13(2):83.

Bourini, I. F. and Bourini, F. A. R. (2016). Using sem-pls and fuzzy logic to determine the influence of uncertainty avoidance and accreditation cost on strategic intention. Electronic Journal Of Applied Statistical Analysis, 9(3):454 – 468.

Carpita, M. and Ciavolino, E. (2017). A generalized maximum entropy estimator to simple linear measurement error model with a composite indicator. Advances in Data Analysis and Classification, 11(1):139–158.

Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2):295–336.

Ciavolino, E. (2017). General distress as second order latent variable estimated through pls-pm approach. Electronic Journal Of Applied Statistical Analysis, 5(3):458–464.

Ciavolino, E. and Al-Nasser, A. (2009). Comparing generalized maximum entropy and partial least squares methods for structural equation models. Journal of Nonparametric Statistics, 21(8):1017–1036.

Ciavolino, E. and Carpita, M. (2015). The gme estimator for the regression model with a composite indicator as explanatory variable. Quality and Quantity, 49(3):955–965.

Ciavolino, E., Carpita, M., and Al-Nasser, A. (2015). Modeling the quality of work in the italian social co-operatives combining npca-rsm and sem-gme approaches. Journal of Applied Statistics, 42(1):161–179.

Ciavolino, E. and Dahlgaard, J. (2009). Simultaneous equation model based on gener- alized maximum entropy for studying the effect of the managements factors on the enterprise performances. Journal of Applied Statistics, 36(7):801–815.

Ciavolino, E., Redd, R., Evrinomy, A., Falcone, M., Fini, V., Kadianaki, I., Kullasepp, K., Mannarini, T., Matsopoulos, A., Mossi, P., Rochira, A., Santarpia, A., Sammut, G., Valsiner, J., Veltri, G., and Salvatore, S. (2017). Views of context. an instrument for the analysis of the cultural milieu. a first validation study. Electronic Journal Of Applied Statistical Analysis, 10(2):599 – 628.

Conboy, K. and Coyle, S. (2010). People over process: key people challenges in agile development. IEEE Software, 99(1):47–57.

Crawford, L. (2005). Senior management perceptions of project management competence. International journal of project management, 23(1):7–16.

Crawford, L. and Pollack, J. (2004). Hard and soft projects: a framework for analysis. International Journal of Project Management, 22(8):645–653.

Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. psychometrika, 16(3):297–334.

Dewulf, A., Franc ̧ois, G., Pahl-Wostl, C., and Taillieu, T. (2007). A framing approach to cross-disciplinary research collaboration: experiences from a large-scale research project on adaptive water management. Ecology and Society, 12(2):14.

Diamantopoulos, A. and Winklhofer, H. M. (2001). Index construction with forma- tive indicators: An alternative to scale development. Journal of marketing research, 38(2):269–277.

Dibbern, J., Goles, T., Hirschheim, R., and Jayatilaka, B. (2004). Information systems outsourcing: a survey and analysis of the literature. ACM Sigmis Database, 35(4):6– 102.

Dijkstra, T. K. and Henseler, J. (2015). Consistent and asymptotically normal pls estimators for linear structural equations. Computational statistics & data analysis, 81:10–23.

Dionne, S. D., Yammarino, F. J., Atwater, L. E., and Spangler, W. D. (2004). Trans- formational leadership and team performance. Journal of organizational change man- agement, 17(2):177–193.

DuBrin, A. J. (2004). Applying psychology: Individual and organizational effectiveness. prentice Hall.

Ernø-Kjølhede, E. et al. (2000). Project management theory and the management of research projects. Technical report.

Esposito Vinzi, V., Ringle, C., Squillacciotti, S., and Trinchera, L. (2007). Capturing and treating unobserved heterogeneity by response based segmentation in pls path mod- eling. a comparison of alternative methods by computational experiments. Technical report, ESSEC Research Center, ESSEC Business School.

Esposito Vinzi, V., Trinchera, L., and Amato, S. (2010). Pls path modeling: From foundation to recent developments and open issues form model assessment and improvement. volume 10, pages 47–82.

Fisher, E. (2011). What practitioners consider to be the skills and behaviours of an effec- tive people project manager. International Journal of Project Management, 29(8):994– 1002.

Fornell, C. and Larcker, D. F. (1981). Structural equation models with unobservable vari- ables and measurement error: Algebra and statistics. Journal of marketing research, pages 382–388.

Fornell, C. and Robinson, W. T. (1983). Industrial organization and consumer satisfac- tion/dissatisfaction. Journal of Consumer Research, 9(4):403–412.

Gefen, D., Straub, D., and Boudreau, M.-C. (2000). Structural equation modeling andregression: Guidelines for research practice. Communications of the association for information systems, 4(1):7.

Gustavsson, T. K. and Hallin, A. (2014). Rethinking dichotomization: A critical per- spective on the use of hard and soft in project management research. International Journal of Project Management, 32(4):568–577.

Henseler, J., Hubona, G., and Ray, P. A. (2016). Using pls path modeling in new technology research: updated guidelines. Industrial management & data systems, 116(1):2–20.

Higgins, C. A., Duxbury, L. E., and Irving, R. H. (1992). Work-family conflict in the dual-career family. Organizational Behavior and Human Decision Processes, 51(1):51– 75.

Higgs, M. and Dulewicz, S. (2003). The design of a new instrument to assess leadership dimensions and styles. Henley Working Paper Series HWP2003/11.

Hulland, J. (1999). Use of partial least squares (pls) in strategic management research: A review of four recent studies. Strategic management journal, pages 195–204.

Huutoniemi, K., Klein, J. T., Bruun, H., and Hukkinen, J. (2010). Analyzing interdis- ciplinarity: Typology and indicators. Research Policy, 39(1):79–88.

Ingusci, E., Callea, A., Chirumbolo, A., and Urbini, F. (2016). Job crafting and job sat- isfaction in a sample of italian teachers: the mediating role of perceived organizational support. Electronic Journal Of Applied Statistical Analysis, 9(4):675 – 687.

Jarvis, C. B., MacKenzie, S. B., and Podsakoff, P. M. (2003). A critical review of con- struct indicators and measurement model misspecification in marketing and consumer research. Journal of consumer research, 30(2):199–218.

J ̈oreskog, K. and S ̈orbom, D. (1989). Lisrel vii: A guide to the program and applications. chicago: Spss.

J ̈oreskog, K. G. (1978). Structural analysis of covariance and correlation matrices. Psychometrika, 43(4):443–477.

Kaplan, D. (2008). Structural equation modeling: Foundations and extensions. Sage Publications.

Kerzner, H. (1981). Project-management in the year 2000. Journal of Systems Manage- ment, 32(10):26–31.

Koontz, H. and Weihrich, H. (1990). Essential of management, international edition. Kuchta, D., G􏰖ladysz, B., Skowron, D., and Betta, J. (2017). R&d projects in the science sector. R&D Management, 47(1):88–110.

Lee, L., Petter, S., Fayard, D., and Robinson, S. (2011). On the use of partial least squares path modeling in accounting research. International Journal of Accounting Information Systems, 12(4):305–328.

Lenfle, S. (2008). Exploration and project management. International Journal of Project Management, 26(5):469–478.

Lohm ̈oller, J.-B. (1989). Predictive vs. structural modeling: Pls vs. ml. In Latent Variable Path Modeling with Partial Least Squares, pages 199–226. Springer.

Lounsbury, J. W., Foster, N., Patel, H., Carmody, P., Gibson, L. W., and Stairs, D. R. (2012). An investigation of the personality traits of scientists versus nonscientists and their relationship with career satisfaction. R&D Management, 42(1):47–59.

Monecke, A. and Leisch, F. (2012). sempls: Structural equation modeling using partial least squares. Journal of Statistical Software, 48(i03).

Mu ̈ller, R. and Turner, J. R. (2007). Matching the project managers leadership style to project type. International journal of project management, 25(1):21–32.

Nelson, K. M. and Cooprider, J. G. (1996). The contribution of shared knowledge to is group performance. MIS quarterly, pages 409–432.

Pant, I. and Baroudi, B. (2008). Project management education: The human skills imperative. International journal of project management, 26(2):124–128.

Pavlou, P. A. and Chai, L. (2002). What drives electronic commerce across cultures? across-cultural empirical investigation of the theory of planned behavior. J. Electron. Commerce Res., 3(4):240–253.

Pelagatti, M., Fattore, M., and Vittadini, G. (2017). Inconsistencies of the pls-pm approach to structural equation models with formative-reflective schemes. Electronic Journal Of Applied Statistical Analysis, 5(3):333 – 338.

Pinto, J. and Trailer, J. (1998). Leadership skills for project managers. Project Management Institute.

PMI (2007). Project management body of knowledge (pmbok). Project Management Institute.

Pollack, J. (2007). The changing paradigms of project management. International journal of project management, 25(3):266–274.

Reinartz, W., Krafft, M., and Hoyer, W. D. (2004). The customer relationship man- agement process: Its measurement and impact on performance. Journal of marketing research, 41(3):293–305.

Simonetto, A. (2017). Formative and reflective models: state of the art. Electronic Journal Of Applied Statistical Analysis, 5(3):452–457.

Takey, S. M. and de Carvalho, M. M. (2015). Competency mapping in project manage- ment: An action research study in an engineering company. International Journal of Project Management, 33(4):784–796.

Tenenhaus, M., Vinzi, V. E., Chatelin, Y.-M., and Lauro, C. (2005). Pls path modeling. Computational statistics & data analysis, 48(1):159–205.

Turner, J. R. and Cochrane, R. A. (1993). Goals-and-methods matrix: coping with projects with ill defined goals and/or methods of achieving them. International Journal of project management, 11(2):93–102.

Turner, J. R. and Payne, J. (1997). The problem of projects of differing size and skill mix. Project Management, 3(1):14–17.

Vom Brocke, J. and Lippe, S. (2015). Managing collaborative research projects: A synthesis of project management literature and directives for future research. International Journal of Project Management, 33(5):1022–1039.

Werts, C. E., Linn, R. L., and J ̈oreskog, K. G. (1974). Intraclass reliability esti- mates: Testing structural assumptions. Educational and Psychological measurement, 34(1):25–33.

Wright, S. (1921). Correlation and causation. Journal of agricultural research, 20(7):557– 585.

Yammarino, F. J., Spangler, W. D., and Dubinsky, A. J. (1998). Transformational and contingent reward leadership: Individual, dyad, and group levels of analysis. The Leadership Quarterly, 9(1):27–54.

Yang, L.-R., Huang, C.-F., and Wu, K.-S. (2011). The association among project man- ager’s leadership style, teamwork and project success. International journal of project management, 29(3):258–267.

Full Text: pdf

Creative Commons License
This work is licensed under a Creative Commons Attribuzione - Non commerciale - Non opere derivate 3.0 Italia License.