An Application of Covariance Analysis to Capacity Expansion at an Intermodal Blending Plant

Analysis of covariance (ANCOVA) integrates analysis of variance (ANOVA) and regression. The basic advantages of ANCOVA over ANOVA are: (1) generally greater power, and (2) reduction in bias caused by differences between groups that exist before experimental treatments are administered. ANCOVA has numerous possible applications in the evaluation of simulation output, especially where the values of covariates are not known until after the simulation experiment is completed. These covariates are uncontrolled experimental variables that influence the response but are themselves unaffected by the experimental factors. This paper provides an application of multiple analysis of covariance (MANCOVA) to a simulation experiment to determine whether an intermodal transfer and blending facility should add commodity handling and storage capacity. A discrete simulation model of the plant generated cash flows from several proposed capital projects. These cash flows indicated that capacity expansion was a prudent decision. However, when the treatment means for the various combinations of additional capacity were adjusted by MANCOVA for the same levels of operating volume and scheduling performance, the adjusted cash flows produced unacceptable financial returns. In this example, the increased precision of the MANCOVA model suggested that plant management should not invest in additional storage and commodity handling capacity.     

Peer effects and intentional entrepreneurial behaviour: A systematic literature review and research agenda

What role peers play in individuals’ decisions to become entrepreneurs and to what extent peer effects play a role in influencing behaviours at the various stages of business venturing are important questions for scholars and policymakers. This systematic review takes stock of the recent additions to the literature around the phenomenon of peer influence in entrepreneurship. The review identified 2894 documents which were then narrowed down through three consecutive filtering stages. We thematically analysed the final sample of 27 empirical studies that shed light on how individual peers influence the process and outcomes of these individuals’ entrepreneurial intentions and behaviour, allowing for critical analysis. We propose a conceptual schema of social influence that occurs in interactions among entrepreneurial individuals within business venturing and across the three stages of pre-formation, formation and growth. Our framework reconciles the conceptual classification around discovering, evaluating and exploiting entrepreneurial opportunities with the mechanisms of social influence affecting entrepreneurial behaviours. Grounded in the findings of the literature review, this framework synthesizes peer influence in entrepreneurship with the tripartite distinction of the behavioural motives recognized in contemporary theories of social influence. We suggest promising directions for further research on how interactions with peers might affect individuals’ entrepreneurial behaviours.