Yazar "Tomaskova, Hana" seçeneğine göre listele

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    Business process optimization for trauma planning
    (Elsevier Science Inc, 2023) Tomaskova, Hana; Tirkolaee, Erfan Babaee; Raut, Rakesh Dulichand
    Managers play a critical role in considering their organization's needs, goals, and objectives when making decisions. However, most written material is produced before or after the issue it addresses, requiring managers to have prior knowledge to apply it correctly. We contend that fundamental business process analysis and straightforward reengineering can be used to the procedures outlined in the documentation to improve decision-making processes. This approach is illustrated through a study focusing on trauma planning. Process models were created from the trauma planning documentation to assess the effectiveness of the time process. Procedures were then redesigned, increasing efficiency while maintaining the time for partial activities. By using this approach, managers can ensure that their organization's objectives are met while improving efficiency and productivity. Our study emphasizes the importance of considering the effectiveness of existing procedures and reengineering them where necessary.
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    An integrated decision-making approach for green supplier selection in an agri-food supply chain: threshold of robustness worthiness
    (MDPI, 2021) Tirkolaee, Erfan Babaee; Dashtian, Zahra; Weber, Gerhard-Wilhelm; Tomaskova, Hana; Soltani, Mehdi; Mousavi, Nasim Sadat
    Along with the increased competition in production and service areas, many organizations attempt to provide their products at a lower price and higher quality. On the other hand, consideration of environmental criteria in the conventional supplier selection methodologies is required for companies trying to promote green supply chain management (GSCM). In this regard, a multi-criteria decision-making (MCDM) technique based on analytic hierarchy process (AHP) and fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) is used to evaluate and rate the suppliers. Then, considering the resource constraint, weight of criteria and a rank of suppliers are taken into account in a multi-objective mixed-integer linear programming (MOMILP) to determine the optimum order quantity of each supplier under uncertain conditions. To deal with the uncertain multi-objectiveness of the proposed model, a robust goal programming (RGP) approach based on Shannon entropy is applied. The offered methodology is applied to a real case study from a green service food manufacturing company in Iran in order to verify its applicability with a sensitivity analysis performed on different uncertainty levels. Furthermore, the threshold of robustness worthiness (TRW) is studied by applying different budgets of uncertainty for the green service food manufacturing company. Finally, a discussion and conclusion on the applicability of the methodology is provided, and an outlook to future research projects is given.
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    An integrated multi-criteria decision-making approach to optimize the number of leagile-sustainable suppliers in supply chains
    (Springer, 2022) Darvazeh, Saeid Sadeghi; Mooseloo, Farzaneh Mansoori; Vandchali, Hadi Rezaei; Tomaskova, Hana; Tirkolaee, Erfan Babaee
    Global supply chains are increasingly becoming complex by having numerous suppliers around the world. To manage this complexity, organizations must identify the optimum number of suppliers. There have been many examples in the literature that used diferent approaches to solve this problem. Despite the importance of this issue, less attention has been paid to it and managers of the companies do not know how, and based on which approach and criteria, they should determine the optimal number of suppliers which leads to lower cost and higher reliability of the production line. Therefore, in this study, a hybrid methodology is proposed to expose the process of this problem which helps managers to learn how they can determine the optimal number of suppliers. We address this gap by developing an integrated approach based on multi-criteria decision-making (MCDM) comprising best-worst method (BWM), simple additive weighting (SAW), and technique for order preference by similarity to ideal solution (TOPSIS), and simulation to determine the optimal number of suppliers. This study utilizes a comprehensive approach based on leagile and environmentally sustainable criteria to determine the optimal number of suppliers. To examine the efciency of the proposed approach, an empirical case study is conducted in an Iranian oil company. The fnal results represent that the scenario with a 1-1-1 arrangement (one supplier for each type of equipment) is the best possible scenario to determine the optimal number of leagile-sustainable suppliers. To examine the reliability and robustness of the obtained results, a sensitivity analysis based on the three most important criteria is conducted. Finally, discussions on the fndings as well as theoretical and managerial implications are presented.
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    An integrated multi-criteria decision-making approach to optimize the number of leagile-sustainable suppliers in supply chains (Jun, 10.1007/s11356-022-20214-0, 2022)
    (SPRINGER HEIDELBERG, 2022) Darvazeh, Saeid Sadeghi; Mooseloo, Farzaneh Mansoori; Vandchali, Hadi Rezaei; Tomaskova, Hana; Tirkolaee, Erfan Babaee
    No Abstract Available.
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    A novel approach for group decision making based on the best–worst method (G-bwm): application to supply chain management
    (MDPI AG, 2021) Haseli, Gholamreza; Sheikh, Reza; Wang, Jianqiang; Tomaskova, Hana; Tirkolaee, Erfan Babaee
    Metrics Funding details Abstract Due to the complexity of real-world multi-criteria decision-making (MCDM) issues, an-alyzing different opinions from a group of decision makers needs to ensure appropriate decision making. The group decision-making methods collect preferences of the decision makers and present the best preferences using mathematical equations. The best–worst method (BWM) is one of the recently introduced MCDM methods that requires fewer pairwise comparisons to obtain the criteria weights than the other MCDM methods. In this research, we develop a novel approach to group decision-making problems based on the BWM called G-BWM. This approach helps us to analyze the preferences of decision makers to carry out democratic decision making using the BWM structure. In order to assess the applicability of the proposed methodology and represent its novelty, two numerical examples from the literature with the application to supply chain management (SCM) (i.e., green supplier selection and supplier development/segmentation) are examined and discussed. The results demonstrate the performance of our proposed G-BWM for group decision making in terms of a large number of decision makers, ease of use and achieving democratic decisions in the decision-making process.
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    Sport performance analysis with a focus on racket sports: A review
    (MDPI, 2021) Krizkova, Sarka; Tomaskova, Hana; Tirkolaee, Erfan Babaee
    Athletes, both professional and amateur, are always looking for ways to improve their performance. With the introduction and increasing availability of modern technologies and smart devices arose the need to measure and analyze performance, but likewise, the use of these innovations as a competitive advantage also arose. Scientific publications reflect the wide range of available approaches and technologies, as well as the growing interest in various sports. As a result, we concentrated on a systematic review of publications that presented performance analysis tools and methods in all sports, with a final focus on racket sports. Clarivate Analytics’ Web of Science (WoS) and Elsevier Inc.’s SCOPUS databases were searched for 1147 studies that conducted performance analysis and sports research and were published in English. The data in the systematic review are current, up until 18 May 2021. A general review was performed on 759 items, and then 65 racket sports publications were thoroughly scrutinized. We concentrated on performance data, data collection and analysis tools, performance analysis methods, and software. We also talked about performance prediction. In performance research, we have identified specific approaches for specific sports as well as key countries. We are also considering expanding performance analysis in to E-sports in the future.
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    Using a process approach to pandemic planning: a case study
    (MDPI AG, 2021) Tomaskova, Hana; Tirkolaee, Erfan Babaee
    The purpose of this article was to demonstrate the difference between a pandemic plan’s textual prescription and its effective processing using graphical notation. Before creating a case study of the Business Process Model and Notation (BPMN) of the Czech Republic’s pandemic plan, we conducted a systematic review of the process approach in pandemic planning and a document analysis of relevant public documents. The authors emphasized the opacity of hundreds of pages of text records in an explanatory case study and demonstrated the effectiveness of the process approach in reengineering and improving the response to such a critical situation. A potential extension to the automation and involvement of SMART technologies or process optimization through process mining techniques is presented as a future research topic.