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EN
Purpose: The aim of this paper is to present a new model for risk assessment of unfavorable interorganizational relationships, among other things, in ventures classified as corporate social responsibility (CSR) projects. Design/methodology/approach: Scenario analysis, brainstorm sessions, literature study and own observations of interorganizational projects were used to develop a list of unwanted events and factors determining their occurrence. In the proposed risk assessment model, fault tree analysis and fuzzy logic were applied for qualitative and quantitative risk analysis. Thanks to applying the elements of fuzzy sets theory, it was possible to decrease the uncertainty and lack of precision in obtaining crisp values of the basic events’ probability. Findings: In this work 13 basic events and 41 risk factors determining occurrence of unfavorable interorganizational relationships in ventures were identified and described. The proposed model enabled to carry out qualitative and quantitative risk assessment of unfavorable interorganizational relationships projects. Its practical application was shown in an example of interorganizational CSR project concerning the organization of a mass event, considering its logistics aspects. Research limitations/implications: It is necessary to involve experts in risk assessment. This could be overcome by applying machine learning in future research. Practical implications: The application of the proposed model allows to effectively identify the critical risks, which should be of particular attention during the risk treatment stage. It aims to give a helping hand to all managers and practitioners who want to deliver attainable and successful interorganizational projects, supporting meeting the expectation of the engaged stakeholders. Social implications: Socially responsible activities contribute to solving and counteracting social problems. Originality/value: A novel risk assessment model of unfavorable interorganizational relationships in which 13 basic events and 41 risk determinants were considered. The model was presented at ventures classified as Corporate Social Responsibility projects.
EN
Horizontal Directional Drilling (HDD) is a very complex technology. Although the installation of pipelines by means of this technology is often successful, examples of unsuccessful projects are also known. Due to the complexity of the technology, with the interaction of multiple processes, risks related to uncertainties in these processes play important role. These risks are related to the variability of underground strata, changing natural environment, changes in economic environment, as well as limitations of the equipment, technical disruptions and human factors. This paper describes the risk evaluation results of the FMEA and a Pareto– Lorenz analysis for 14 external risk factors (8 natural or environmental risk factors as well as 6 economic risk factors) in HDD technology. In the proposed approach not only the probability of the external risk factor occurrence was considered, but also its consequences and the ability to detect faults, which were not plainly separated and taken into account in the literature so far. Such an approach has shown the relationship between occurrence, severity and detection for the analysed external failures. Moreover, 40 detection possibilities for the external risks in HDD technology were identified. The calculated risk priority numbers enabled ranking HDD external failures and identified the most critical risks for which the suggested detection options were unsatisfactory and insufficient, and therefore other types of risk response actions need to be explored.
EN
Horizontal Directional Drilling (HDD) technology is a highly complex process connected with high risk and uncertainty due the high variability underground strata, often limited access to specialised equipment, dynamic natural environment, technical disruptions, human factor and changes in economic environment that further complicate the gathering of reliable information and data. This work presents a new risk evaluation model tailored for HDD technology, in which failure mode and effect analysis (FMEA) modelling were applied. This paper focuses on 15 human risk factors and 9 equipment risk factors in HDD technology. The proposed approach takes into account not only the probability of the risk factor occurrence, but also its severity and the possibility of detecting faults, which were not clearly separated and analyzed in the previous works. Application of the proposed model shows the relationship between occurrence, severity and detection for the analyzed failures. Moreover, many detection possibilities for the identified failures were presented. The calculated risk priority numbers allowed to rank HDD failures and identify the most critical risks for which one should look for risk treatment possibilities beyond risk cause reduction, such as risk effect reduction, risk transfer, risk elimination or active risk retention.
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