Contingency Theory: United States Small Business Predictive Performance with Project Management Using Partial Least Squares Structural Equation Modeling

Small business entrepreneurs (SBEs) within the United States in 2014 produced 47% of the national $17.5 trillion GDP and employed 48.5% of the national labor force. Detailed business planning was a theorized predictor of SBE performance and project, program, and portfolio management (P3M) as detailed managerial planning processes influenced by organizational theories. The specific problem was the failure of SBEs due to a lack of business management planning and the unknown generalizable U.S. SBE use of P3M as detailed managerial planning processes to enhance SBE performance. The purpose of this quantitative cross-sectional study was to statistically model U.S. SBE predictive P3M application to SBE Performance within a contingency theory framework using partial least squares structural equation modeling (PLS-SEM), hierarchical component modeling (HCM), and multi-group analysis (MGA-PLS) of subpopulations (growth orientation, number of employees, business age, business location, industry sector, legal form of organization, and P3M maturity). Random anonymous sampling among small business owners and chief managers was used to attain a representative sample by U.S. state using a web-based survey instrument. A sample of 179 was planned (R2 sensitivity of 0.1) and n =150 was attained (R2 sensitivity of 0.107). Sample size was representative of 93.1% of 28.9 million small business enterprises by U.S. state and the District of Columbia. Findings included an average performance efficiency of 59% among U.S. SMEs with room for improvement of 41%. P3M was identified as detailed planning and management processes with a 0.308 total effect on national SBE performance. A 1% improved adaptation of P3M managerial knowledge area processes predicted 18.17% SBE performance improvement. Limitations of the study included data collection barriers from internet service providers (ISPs) and email service providers (ESPs) in censoring and filtering emailed survey invitations contributing to a decreased response rate. Future research recommendations include expanding population ecology theory to identify predictive environmental factors that effect the 59% performance mean resulting in a population of SBEs failing or improving at various S-curve lifecycle stages