Articles
Journal of Modelling in Management (17465672)19(6)pp. 1827-1848
Purpose: This paper aims to simulate vital corrective actions (CAs) affecting system availability through a system dynamics approach based on the results obtained by analyzing the causal relationships among failure modes and effects analysis elements. Design/methodology/approach: A stock and flow diagram has been developed to simulate system behaviors during a timeframe. Some improvement scenarios regarding the most necessary CAs according to their strategic priority and the possibility of eliminating root causes of critical failure modes in a roller-transmission system have been simulated and analyzed to choose the most effective one(s) for the system availability. The proposed approach has been examined in a steel-manufacturing company. Findings: Results indicated the most effective CAs to remove or diminish critical failure causes that led to the less reliability of the system. It illustrated the impacts of the selected CAs on eliminating or decreasing root causes of the critical failure modes, lessening the system’s failure rate and increasing the system availability more effectively. Research limitations/implications: Results allow managers and decision-makers to consider different maintenance scenarios without wasting time and more cost, choosing the most appropriate option according to system conditions. Originality/value: This study innovation would be the dynamic analysis of interactions among failure modes, effects and causes over time to predict the system behavior and improve availability by choosing the most effective CAs through improvement scenario simulation via VENSIM software. © 2024, Emerald Publishing Limited.
Journal of Simulation (17477778)17(4)pp. 477-498
Smart tourism destinations can be considered as a system consisting of a complex set of variables. Developing sustainable destinations through smart technologies requires effective policies to be identified prior to any investment decision making. So, System Dynamics is a good method to see how a set of complex and dynamic variables influence eachother and shape the behaviour of the system and its components over time. In this research a dynamic model is devised to simulate developing smart tourism destinations via smart technologies. The results suggest that about 10 million tourists would be expected to come by 2025 if existing situation persists. The results of this study help to make strategic decisions by policymakers by predicting the behaviour of variables of different subsystems. This study provides a reilable tool to evaluate different policies for realizing tourism sustainability. © Operational Research Society 2022.
Information Technology and Tourism (10983058)24(4)pp. 511-546
The smart tourism concept emerged from smart city development and is a particular application area within smart city initiatives. Smart tourism is broadly applied as a strategic tool to enhance the competitiveness of tourism destinations. This study creates a framework to identify, explore, and rate the effective factors of developing smart tourism destinations. The effective factors were identified through a review of the research literature and by surveying experts. The identified factors were rated using an interpretative-structural modelling approach. A Cross-impact matrix multiplication applied to classification (MICMAC) analysis was used to determine the power and dependence of these factors. The findings show 20 indexes at ten levels. Financial resources, government support, and smart tourism policies were identified as the most important factors in modelling smart tourism development. By identifying effective factors for developing smart tourism destinations, the policymakers can encourage innovation of smart destinations, support smart tourism and highlight the multi-faceted contribution of smart destinations to sustainable development. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
International Journal of Quality and Reliability Management (0265671X)39(8)pp. 1977-1995
Purpose: This paper aims to develop a system dynamics (SD) model to identify causal relationships among the elements of failure modes and effects analysis (FMEA), i.e. failure modes, effects and causes. Design/methodology/approach: A causal loop diagram (CLD) has been developed based on the results obtained from interdependencies and correlations analysis among the FMEA elements through applying the integrated approach of FMEA-quality function deployment (QFD) developed by Shaker et al. (2019). The proposed model was examined in a steel manufacturing company to identify and model the causes and effects relationships among failure modes, effects and causes of a roller-transmission system. Findings: Findings indicated interactions among the most significant failure modes, effects and causes. Moreover, corrective actions defined to eliminate or relieve critical failure causes. Consequently, production costs decreased, and the production rate increased due to eliminated/decreased failure modes. Practical implications: The application of CLD illustrates causal relationships among FMEA elements in a more effective way and results in a more precise recognition of the root causes of the potential failure modes and their easy elimination/decrease. Therefore, applying the proposed approach leads to a better analysis of the interactions among FMEA elements, decreased system's failure rate and increased system availability. Originality/value: The literature review indicated a few studies on the application of SD methodology in the maintenance area, and no study was performed on the causal interactions among FMEA elements through an FMEA-QFD based SD approach. Although the interactions of these elements are significant and helpful in risks ranking, researchers fail to investigate them sufficiently. © 2021, Emerald Publishing Limited.
