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Although organizations regularly execute projects to improve their performance, there is still no agreement in the literature on how to evaluate their eventual success. As a result, scholars end up using different scales to measure the same outcome variable of project success, thereby causing inconsistency in research results. Existing project success evaluation models suffer from their inability to apply to all project types and lack of separation of project success measurement from that of project individuals’ performance (for e.g., of the project manager). Through two longitudinal studies based on the satisficing theory, this paper develops, validates, and illustrates generic scales to measure the success of any project, as well as the performance of its two key leaders. This results in three distinct project success dimensions: 1) Project management success—evaluates the performance of the project manager in achieving the project plan; 2) Project ownership success—evaluates the performance of the project owner in realizing the business case; and 3) Project investment success—evaluates the investment performance of the project for its funder. This paper contributes to the literature by offering a theoretically robust, multidimensional evaluation model that will enhance performance evaluation of both projects and their leaders. [ABSTRACT FROM AUTHOR]

With the growing economic pressure, one lever for companies to be competitive is to efficiently monitor projects. To this goal, the different processes involved in the project must be carefully supervised and the project manager needs to be well-informed on their state and progress to take the best decisions thanks to accurate performances of indicators, process, and project. Another key factor of successful decision-making in engineering projects beyond taking into account information from the project manager on the project management (PM) is to consider information from the systems engineer on the product development. This paper proposes a process to monitor engineering projects relying on a set of project performance indicators that integrate the views of both project manager and systems engineer. This process includes three main activities: 1) defining project performance indicators related to the processes described by international guides and standards; 2) valuating and weighting these indicators by consulting project managers and systems engineers; and 3) constructing a hierarchical framework of indexes to support project monitoring. This proposal thus refers to the practices described in PM and systems engineering norms and improves them by involving project managers and systems engineers into decision-making, with the goal to take more coherent decisions. [ABSTRACT FROM AUTHOR]

Large dam projects (i.e., those exceeding 15 m) often make headlines for their poor performance and their negative social and environmental impacts. The world register characterizes dams by height, purpose (e.g., irrigation), and type (e.g., rock-fill). Thus, large dams differ in many technical ways, but because practitioners still lack a framework to sort them into different types for management purposes, they tend to manage them in a one-size-fits-all manner. Shenhar and Dvir's NTCP (novelty, technology, complexity, and pace) model (2007) may be a good fit as large dams experience high unforeseen technological uncertainty. In this paper, through observations, a case study, a qualitative analysis of 42 interviews with project managers, and a quantitative analysis, we examined 30 large dam projects in Africa and sorted them into different categories according to the NTCP model. Going beyond the rather static NTCP, we identified their underlying NTCP characteristics and the variety of roles that their project managers played throughout the lifecycle, and highlighted the dynamic fit between the roles and NTCP characteristics. Since different characteristics and project manager's roles are prominent at different phases, project managers should sort dams into different types based on the NTCP model at different phases, and tailor their roles accordingly for more success. [ABSTRACT FROM AUTHOR]