Delivery risk analysis within the context of program management using fuzzy logic and DEA: A China case study

Action selection in risk assessment with fuzzy Fine-Kinney-based AHP-TOPSIS approach: a case study in gas plant

In this study, the hazards occurring in a medium-sized gas filling facility were defined, and the risk scores of these hazards were determined by the expert team according to the Fine-Kinney risk analysis method. However, since the same risk significance score is obtained in different combinations of scale values in the classical Fine-Kinney risk analysis method and the characteristics/constraints of the company applied in the risk analysis are not taken into account, the hazards were evaluated using fuzzy Fine-Kinney risk analysis, and the most critical hazards were determined. Action plans are defined for critical hazards determined as a result of fuzzy Fine-Kinney risk analysis. Among the actions that require company resources, the action selection was performed with the TOPSIS method, taking into account their relationship with the hazards by integrating the weights, which was calculated with the AHP method, of affected groups. The effect of operating constraints is included in the last step of the study to calculate the final weights. Calculating the results by including the risk-affected groups and company constraints and ranking the actions reveals that the study is an original, objective, and applicable study.

A model to reduce the risk of project selection utilizing data envelopment analysis

Purpose

Project selection management is a matter of challenge for project-oriented organizations, particularly, if the decision-makers are confronted with limited resources. One of the main concerns is selecting an optimal subset that can successfully satisfy the requirements of the organization providing enough resources to the best subset of the project. The projects for which there are not enough resources or those requiring whole resources of the organization will collapse soon after failed to success. Therefore, the issue is in the risk of choosing a set of projects so that can make a balance in investment versus on collective benefit.

Design/methodology/approach

A model is presented for project selection and has been tested on the 37 available projects. This model could increase the efficiency of the whole subset of the project significantly in comparison to the other model and it was because of choosing a diverse subset of projects.

Findings

Provides a general framework for project selection and a diverse and balanced subset of projects to increase the efficiency of the selected subset. Also, reduces the impact of uncertainty risk on the project selection process.

Research limitations/implications

For the purposes of project selection, any project whose results are uncertain is a risky project because, if the project fails, it will reduce combined project value. For example, a pharmaceutical company’s R&D project is affected by the uncertain results of a specific compound. If the company invests in different compounds, a failure with one will be offset by a good result on another. Therefore, with selecting a diverse set of projects, this paper will have a different set of risks.

Originality/value

This paper discusses the risk of selecting or being responsible for selecting a project under uncertainty. Most of the projects in the field of project selection generally consider the risks facing the projects or existing models that do not take into account the risk.

Monitoring and Control in Program Management as Effectiveness Drivers in Polish Energy Sector. Diagnosis and Directions of Improvement

The activity of enterprises in the energy sector is complicated by the complexity and capital intensity of the resources and processes used. In the current market conditions, an additional challenge is the implementation of sustainable development, including, in particular, environmental and social goals. These circumstances require efficient and effective management, and this is possible, inter alia, thanks to the use of the project management. However, this approach requires not only implementation, but also professional monitoring and control, which is considered and diagnosed in this article. The purpose of this article is to: (a) verify the programme management areas subject to the monitoring and control process; (b) identify and evaluate the effectiveness of the most frequently used methods in the process of monitoring and control of the programme implementation. A qualitative study using a structured interview was conducted among 21 experts involved in the implementation of programmes from the energy sector. The authors found that energy companies monitor and control programmes in key, but traditional areas such as lead times, costs, risks and benefits. They less often refer to ‘soft’ areas of management, such as: work, communication or quality. In terms of the monitoring and control methodology used, significant discrepancies were found between the methods considered effective and those that are most often used in practice. This requires decisive improvement actions. At the same time, it is worth emphasising that the majority of managers prefer compact and quantifiable forms of monitoring and control, such as: earned value method, Gantt chart and comparing plans to results in individual areas. The sector also lacks a systemic approach to programme management, which should be distinguished from single project management, which is why the authors presented their own approach to solving this problem.

Enablers for Organizational Project Management in the Chinese Context

This study aims at exploring the organizational enablers (OEs) for organizational project management (OPM) in the Chinese context. From the resource-based view of firms, we conceptualize OEs as important drivers for the business value creation processes in project-based organizations. The preliminary factor framework was constructed through literature review and expert interviews. Questionnaire surveys elicited 146 responses from Chinese project management practitioners; thereafter, factor analysis was performed to test the OE system empirically. The resulting final OE system contains 49 enablers in nine categories for three management hierarchies; this OE system, constructed by exploratory analysis and verified by confirmatory analysis, comprehensively clarifies the framework of OEs in the Chinese context; it facilitates further investigations into the interaction among OEs and their effects on organization performance. Firm managers may also find this system helpful in formulating identifiable, measurable, and manageable OE frameworks for their own firms, and enabling their organization's strategies with robust OEs.