This paper decision analyctics the evolution of pro-poor development and research on pro-poor practices in China and India, taking rural poverty alleviation in both countries as an example. The research perspective is cast more towards the policy target groups and rural societies to gain a deeper understanding of the institutional and systemic factors that influence the choice and implementation of pro-poor policies, as well as the logic and interrelationships among different actors in the policy implementation network. The final conclusion is that the government should enter more into the life world of the poor, listen to their voices, understand at what level and to what extent their lives are affected by the implementation of pro-poor policies, and how the informal institutions of the vernacular society interact with the formal institutions in the process of policy implementation. This series of questions can help the government examine the theoretical and practical issues of rural poverty alleviation policies from a more comprehensive and historical perspective, which is important for promoting the practice of rural poverty alleviation policies.
{"title":"Public Intervention on Rural Poverty Alleviation: A Case Study Between China and India","authors":"Peiwen Jia","doi":"10.31181/jscda11202318","DOIUrl":"https://doi.org/10.31181/jscda11202318","url":null,"abstract":"This paper decision analyctics the evolution of pro-poor development and research on pro-poor practices in China and India, taking rural poverty alleviation in both countries as an example. The research perspective is cast more towards the policy target groups and rural societies to gain a deeper understanding of the institutional and systemic factors that influence the choice and implementation of pro-poor policies, as well as the logic and interrelationships among different actors in the policy implementation network. The final conclusion is that the government should enter more into the life world of the poor, listen to their voices, understand at what level and to what extent their lives are affected by the implementation of pro-poor policies, and how the informal institutions of the vernacular society interact with the formal institutions in the process of policy implementation. This series of questions can help the government examine the theoretical and practical issues of rural poverty alleviation policies from a more comprehensive and historical perspective, which is important for promoting the practice of rural poverty alleviation policies.","PeriodicalId":313803,"journal":{"name":"Journal of Soft Computing and Decision Analytics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135258095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
It is vital for businesses to run Integrated Marketing Communications (IMC) campaigns in order to communicate with their target audience in an efficient manner. During the course of this research, a critical evaluation of the IMC campaign that Wants Want Group developed in conjunction with the 2022 Chinese New Year event will take place. The decision analytics of this research is to assess the goals and effectiveness of the campaign, as well as to provide an explanation of the consumer demographics that are being targeted by the campaign, therefore demonstrating understanding of the strategies used to segment markets. In addition, our research will make use of relevant theories to assist our analysis and will conduct an analysis of the benefits and drawbacks of the media channels used by the Want Want Group. The results show Want Want's IMC campaign for the 2022 Chinese New Year was effective in establishing an emotional connection with its audience and in increasing holiday sales. The campaign was successful in accomplishing its objectives of increasing brand recognition, customer loyalty, and customer base by using a range of promotional strategies.
{"title":"Evaluating the Effectiveness of Want Want Group's Integrated Marketing Communications (IMC) Campaign during Chinese New Year 2022","authors":"Yuan Xuan Xin","doi":"10.31181/jscda11202319","DOIUrl":"https://doi.org/10.31181/jscda11202319","url":null,"abstract":"It is vital for businesses to run Integrated Marketing Communications (IMC) campaigns in order to communicate with their target audience in an efficient manner. During the course of this research, a critical evaluation of the IMC campaign that Wants Want Group developed in conjunction with the 2022 Chinese New Year event will take place. The decision analytics of this research is to assess the goals and effectiveness of the campaign, as well as to provide an explanation of the consumer demographics that are being targeted by the campaign, therefore demonstrating understanding of the strategies used to segment markets. In addition, our research will make use of relevant theories to assist our analysis and will conduct an analysis of the benefits and drawbacks of the media channels used by the Want Want Group. The results show Want Want's IMC campaign for the 2022 Chinese New Year was effective in establishing an emotional connection with its audience and in increasing holiday sales. The campaign was successful in accomplishing its objectives of increasing brand recognition, customer loyalty, and customer base by using a range of promotional strategies.","PeriodicalId":313803,"journal":{"name":"Journal of Soft Computing and Decision Analytics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135258312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Enhancing the smartness of the supply chain under the influence of information technology development at different levels can have a significant effect on its overall performance and a favorable response to the continuous changes in the business environment in the wide network of local and global supply chains. Therefore, in this study, the important and influential aspects of supply chain smartness have been investigated via a comprehensive assessment model. Then, evaluation criteria are prioritized using the new combined multi-criteria decision-making method. For this purpose, the supply chain of Iran Khodro Company has been considered as a case study. The identification and selection of assessment criteria are based on the literature review and experts' opinions via the Delphi method. Then, by using the developed best-worst group fuzzy method, the final prioritization of the criteria has been proposed. Finally, the evaluation of smartness improvement solutions is proposed by using the Vikor method. The main obtained results indicate the importance of cost, technology, security, customer relationship management, and agility criteria.
{"title":"A Comprehensive Evaluation Model for Smart Supply Chain Based on The Hybrid Multi-Criteria Decision-Making Method","authors":"Arezo Vahidinia, Aliakbar Hasani","doi":"10.31181/jscda11202313","DOIUrl":"https://doi.org/10.31181/jscda11202313","url":null,"abstract":"Enhancing the smartness of the supply chain under the influence of information technology development at different levels can have a significant effect on its overall performance and a favorable response to the continuous changes in the business environment in the wide network of local and global supply chains. Therefore, in this study, the important and influential aspects of supply chain smartness have been investigated via a comprehensive assessment model. Then, evaluation criteria are prioritized using the new combined multi-criteria decision-making method. For this purpose, the supply chain of Iran Khodro Company has been considered as a case study. The identification and selection of assessment criteria are based on the literature review and experts' opinions via the Delphi method. Then, by using the developed best-worst group fuzzy method, the final prioritization of the criteria has been proposed. Finally, the evaluation of smartness improvement solutions is proposed by using the Vikor method. The main obtained results indicate the importance of cost, technology, security, customer relationship management, and agility criteria.","PeriodicalId":313803,"journal":{"name":"Journal of Soft Computing and Decision Analytics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135353673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As a new environmentally friendly mode of transportation, sharing bike provide the benefits of reduced carbon emissions and inexpensive costs, and have grown significantly in China in recent years. Based on the theoretical analysis and experience summary of the current situation of shared bicycle management in Shanghai, this paper investigates the management personnel of shared bicycles, analyses their management mode and its influencing factors, investigates the problems existing in the shared bicycle management mode, and proposes the collaborative optimization perspective. From the standpoint of the sharing economy, it gives references for the invention and development of shared bicycle management mode and aids in the sustainable growth of shared bicycles.
{"title":"The Management Model of Bike Sharing System","authors":"Yuan Xuan Xin","doi":"10.31181/jscda1120239","DOIUrl":"https://doi.org/10.31181/jscda1120239","url":null,"abstract":"As a new environmentally friendly mode of transportation, sharing bike provide the benefits of reduced carbon emissions and inexpensive costs, and have grown significantly in China in recent years. Based on the theoretical analysis and experience summary of the current situation of shared bicycle management in Shanghai, this paper investigates the management personnel of shared bicycles, analyses their management mode and its influencing factors, investigates the problems existing in the shared bicycle management mode, and proposes the collaborative optimization perspective. From the standpoint of the sharing economy, it gives references for the invention and development of shared bicycle management mode and aids in the sustainable growth of shared bicycles.","PeriodicalId":313803,"journal":{"name":"Journal of Soft Computing and Decision Analytics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135394697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Encountering numerous vehicles on the roads can pose several risks, including a higher probability of accidents. To address these issues, a thorough examination of cars can significantly reduce these dangers. Technical inspection centers play a crucial role in this process and should be easily accessible. To provide the most customer service coverage at the lowest cost of transportation for technical inspection centers, facility location optimization is proposed in this paper. Specifically, we investigate the location of technical inspection centers (TICs) as a maximum coverage problem while minimizing the cost of TIC locations' construction and customers' transportation. To deal with this problem, we propose a robust programming considering our numeric data's uncertainty. Our research contributes to facility location optimization by providing a novel insight into solving the problem using a hybrid mathematical model. It presents a two-objective linear optimization model with binary variables to address this optimization problem. We used the Augmented Epsilon Constraint (AEC) method via the CPLEX solver and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) method for large-scale problems to solve the model. A case study was conducted to test the numerical analysis methodology and several practical problems of varying scales. The final results demonstrate the effectiveness of the proposed approach in meeting the optimality and feasibility robustness criteria. Identifying optimal TIC locations regarding the paper's main objective proves the advantage of using the mentioned innovative methodology.
{"title":"Facility Location Optimization For Technical Inspection Centers Using Multi-Objective Mathematical Modeling Considering Uncertainty","authors":"Raheleh Arabahmadi, Mehrdad Mohammadi, Mahrou Samizadeh, Masoud Rabbani, Kazhal Gharibi","doi":"10.31181/jscda11202314","DOIUrl":"https://doi.org/10.31181/jscda11202314","url":null,"abstract":"Encountering numerous vehicles on the roads can pose several risks, including a higher probability of accidents. To address these issues, a thorough examination of cars can significantly reduce these dangers. Technical inspection centers play a crucial role in this process and should be easily accessible. To provide the most customer service coverage at the lowest cost of transportation for technical inspection centers, facility location optimization is proposed in this paper. Specifically, we investigate the location of technical inspection centers (TICs) as a maximum coverage problem while minimizing the cost of TIC locations' construction and customers' transportation. To deal with this problem, we propose a robust programming considering our numeric data's uncertainty. Our research contributes to facility location optimization by providing a novel insight into solving the problem using a hybrid mathematical model. It presents a two-objective linear optimization model with binary variables to address this optimization problem. We used the Augmented Epsilon Constraint (AEC) method via the CPLEX solver and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) method for large-scale problems to solve the model. A case study was conducted to test the numerical analysis methodology and several practical problems of varying scales. The final results demonstrate the effectiveness of the proposed approach in meeting the optimality and feasibility robustness criteria. Identifying optimal TIC locations regarding the paper's main objective proves the advantage of using the mentioned innovative methodology.","PeriodicalId":313803,"journal":{"name":"Journal of Soft Computing and Decision Analytics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135935949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
There are few literature evaluations that analyse the growing environment of indoor mould, despite its health risks and building management burden. This paper examines the most significant factors influencing indoor mould growth and risk levels through a literature review. It was discovered that relative humidity, temperature, time, and nutrients in the substrate were the most significant factors affecting the growth of moulds and that the development of the majority of mould species depended heavily on the relative humidity and temperature values. The optimal ranges for mould growth in terms of temperature and relative humidity are 30°C to 35°C and 95% to 99%, respectively. In order to prevent the growth of indoor mould, this review suggests that the indoor environment of future buildings should pay particular attention to the control of the thermal and humid environment, as well as the accumulation of nutrients and time within the interior of walls.
{"title":"An Assessment of the Influencing Factors Promoting the Development of Mould in Buildings, A Literature Review","authors":"Junpeng Lyu, Michael Pitt, Tim Broyd","doi":"10.31181/jscda11202320","DOIUrl":"https://doi.org/10.31181/jscda11202320","url":null,"abstract":"There are few literature evaluations that analyse the growing environment of indoor mould, despite its health risks and building management burden. This paper examines the most significant factors influencing indoor mould growth and risk levels through a literature review. It was discovered that relative humidity, temperature, time, and nutrients in the substrate were the most significant factors affecting the growth of moulds and that the development of the majority of mould species depended heavily on the relative humidity and temperature values. The optimal ranges for mould growth in terms of temperature and relative humidity are 30°C to 35°C and 95% to 99%, respectively. In order to prevent the growth of indoor mould, this review suggests that the indoor environment of future buildings should pay particular attention to the control of the thermal and humid environment, as well as the accumulation of nutrients and time within the interior of walls.","PeriodicalId":313803,"journal":{"name":"Journal of Soft Computing and Decision Analytics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135982361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the airline industry, after fuel costs, the crew costs con- stitute airlines’ second-highest cost items. For this reason, an airline needs to manage the valuable crew resource effi- ciently. Deviations from plans are fact in airline business and fixing deviations from crew schedules that occurred during operations by minimizing the crew-related delays and associated costs is one of the most important opera- tional burdens of airlines. In this context, the analysis of crew disruption data is vital in order to find disruption characteristics. Clustering analysis is one of the key meth- ods for analyzing the disruption characteristics. In this context, although there have been satisfactory studies in the literature and applications in the industry for small and medium-sized airlines, there is no good solution or industry practice for airlines with extensive networks and fleets. This study aims to analyze and categorize large- scale crew disruption data of a European airline. The relationship between categories of crew disruption and variables such as flight and crew types etc., are determined, and the disruption characteristics are revealed. For this purpose, clusters hidden in the large data set are extracted by spectral clustering. Due to the large size of the input data, a new approximation approach for spectral clustering is introduced. With the help of this new approximation approach, spectral clustering techniques are applied within a limited computational power and time frame as most real world scenario require. Even if the data set is gathered from one airline, the characteristics that are derived from the data is representing most of the cases an airline may face today. and will serve as a basis for further estimation and analysis of crew disruption.
{"title":"Spectral Clustering Approximation For Large Scale Crew Disruption Data Of An Airline Company For Intelligent Crew Recovery","authors":"Ahmet Herekoglu, Özgür Kabak","doi":"10.31181/jscda11202315","DOIUrl":"https://doi.org/10.31181/jscda11202315","url":null,"abstract":"In the airline industry, after fuel costs, the crew costs con- stitute airlines’ second-highest cost items. For this reason, an airline needs to manage the valuable crew resource effi- ciently. Deviations from plans are fact in airline business and fixing deviations from crew schedules that occurred during operations by minimizing the crew-related delays and associated costs is one of the most important opera- tional burdens of airlines. In this context, the analysis of crew disruption data is vital in order to find disruption characteristics. Clustering analysis is one of the key meth- ods for analyzing the disruption characteristics. In this context, although there have been satisfactory studies in the literature and applications in the industry for small and medium-sized airlines, there is no good solution or industry practice for airlines with extensive networks and fleets. This study aims to analyze and categorize large- scale crew disruption data of a European airline. The relationship between categories of crew disruption and variables such as flight and crew types etc., are determined, and the disruption characteristics are revealed. For this purpose, clusters hidden in the large data set are extracted by spectral clustering. Due to the large size of the input data, a new approximation approach for spectral clustering is introduced. With the help of this new approximation approach, spectral clustering techniques are applied within a limited computational power and time frame as most real world scenario require. Even if the data set is gathered from one airline, the characteristics that are derived from the data is representing most of the cases an airline may face today. and will serve as a basis for further estimation and analysis of crew disruption.","PeriodicalId":313803,"journal":{"name":"Journal of Soft Computing and Decision Analytics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123095644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sarbast Moslem, Hiba Solieman, Laila Oubahman, S. Duleba, T. Senapati, F. Pilla
This paper delves into the realm of public transport system enhancement, a critical consideration for decision makers due to its profound impact on citizens' lives and government in-vestments. The primary objective is to assess the quality of public bus transport supply and identify the most effective improvements to heighten passenger satisfaction and attract new users. To accomplish this goal, two prominent multi-criteria decision-making approaches, namely the Analytical Network Process (ANP) and the Analytical Hierarchy Process (AHP), were employed, leveraging a dynamic questionnaire survey. The ANP method, recognized for its robustness, takes into account the interrelationships and feedback among various criteria levels, offering a systematic evaluation framework. In contrast, the AHP method overlooks these factors. The adoption of both methods was crucial in obtaining a comprehensive under-standing of experts' perceptions regarding public transport service quality. To illustrate the practical implementation of these approaches, an empirical study was conducted using a re-al-life case. This study serves as a testament to the efficacy of these decision-making methods and underscores their value in the decision-making process. Ultimately, this paper under-scores the significance of prioritizing public transport system improvements as a means to en-rich citizens' lives and bolster government investments.
{"title":"Assessing Public Transport Supply Quality: A Comparative Analysis of Analytical Network Process and Analytical Hierarchy Process","authors":"Sarbast Moslem, Hiba Solieman, Laila Oubahman, S. Duleba, T. Senapati, F. Pilla","doi":"10.31181/jscda11202311","DOIUrl":"https://doi.org/10.31181/jscda11202311","url":null,"abstract":"This paper delves into the realm of public transport system enhancement, a critical consideration for decision makers due to its profound impact on citizens' lives and government in-vestments. The primary objective is to assess the quality of public bus transport supply and identify the most effective improvements to heighten passenger satisfaction and attract new users. To accomplish this goal, two prominent multi-criteria decision-making approaches, namely the Analytical Network Process (ANP) and the Analytical Hierarchy Process (AHP), were employed, leveraging a dynamic questionnaire survey. The ANP method, recognized for its robustness, takes into account the interrelationships and feedback among various criteria levels, offering a systematic evaluation framework. In contrast, the AHP method overlooks these factors. The adoption of both methods was crucial in obtaining a comprehensive under-standing of experts' perceptions regarding public transport service quality. To illustrate the practical implementation of these approaches, an empirical study was conducted using a re-al-life case. This study serves as a testament to the efficacy of these decision-making methods and underscores their value in the decision-making process. Ultimately, this paper under-scores the significance of prioritizing public transport system improvements as a means to en-rich citizens' lives and bolster government investments.","PeriodicalId":313803,"journal":{"name":"Journal of Soft Computing and Decision Analytics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115438293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mahmoud Zahedian Nezhad, Javad Nazarian-Jashnabadi, J. Rezazadeh, Mohammad Mehraeen, Ruhollah Bagheri
The rapid growth of the information age and digital technologies has ushered in innovative concepts such as Industry 4.0, smart health, digital services, and smart cities. The Internet of Things (IoT) technology has emerged as a crucial driver across domains, engaging businesses, platforms, and industries. The IoT encompasses a holistic ecosystem and a value chain that necessitate evaluating influential dimensions for successful implementation. This research applies Fuzzy DEMATEL and Fuzzy AHP methods to rank and examine dimensions affecting IoT implementation readiness. Findings underscore the significance of organizational factors, hard infrastructures, and soft infrastructures as critical dimensions. Attention to strengthening organizational aspects and developing reliable infrastructures facilitates successful IoT integration. Additionally, while relatively less significant, environmental factors, security and privacy, data analytics, and customer and training dimensions contribute to industry readiness. The combined results provide insights for decision-makers and stakeholders involved in IoT implementation, guiding the development of appropriate strategies, resource allocation, and enhancing operational efficiency. By comprehending the interrelationships and prioritizing influential factors, industries can effectively prepare for successful IoT implementation.
{"title":"Assessing Dimensions Influencing IoT Implementation Readiness in Industries: A Fuzzy DEMATEL and Fuzzy AHP Analysis","authors":"Mahmoud Zahedian Nezhad, Javad Nazarian-Jashnabadi, J. Rezazadeh, Mohammad Mehraeen, Ruhollah Bagheri","doi":"10.31181/jscda11202312","DOIUrl":"https://doi.org/10.31181/jscda11202312","url":null,"abstract":"The rapid growth of the information age and digital technologies has ushered in innovative concepts such as Industry 4.0, smart health, digital services, and smart cities. The Internet of Things (IoT) technology has emerged as a crucial driver across domains, engaging businesses, platforms, and industries. The IoT encompasses a holistic ecosystem and a value chain that necessitate evaluating influential dimensions for successful implementation. This research applies Fuzzy DEMATEL and Fuzzy AHP methods to rank and examine dimensions affecting IoT implementation readiness. Findings underscore the significance of organizational factors, hard infrastructures, and soft infrastructures as critical dimensions. Attention to strengthening organizational aspects and developing reliable infrastructures facilitates successful IoT integration. Additionally, while relatively less significant, environmental factors, security and privacy, data analytics, and customer and training dimensions contribute to industry readiness. The combined results provide insights for decision-makers and stakeholders involved in IoT implementation, guiding the development of appropriate strategies, resource allocation, and enhancing operational efficiency. By comprehending the interrelationships and prioritizing influential factors, industries can effectively prepare for successful IoT implementation.","PeriodicalId":313803,"journal":{"name":"Journal of Soft Computing and Decision Analytics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131186113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Operating rooms (ORs) are one of the essential hospital resources and optimal management can result in efficient OR usage. The admission time reduction before surgery in the ORs can lead to on-time surgery and efficient use of ORs. This study addresses this issue by identifying the main failure modes that cause delays in ORs. The conventional methodology known as Failure Mode and Effects Analysis (FMEA) represents one of the prevailing techniques utilized for the purpose of ascertaining failure modes within a given process. This involves the assignment of numerical scores to each failure mode, with the intention of utilizing the resultant Risk Priority Number (RPN) to facilitate the identification of said failure modes. However, RPN scoring has been criticized for some deficiencies. This study proposes a three-phase approach to address some of the shortcomings of the FMEA method. The initial stage involves utilizing the FMEA approach to recognize failure modes and assess the crucial elements of RPN. Following this, the second stage employs the Z-BWM technique and expert insights to determine the weights of the five essential factors. Lastly, in the third phase, risks are prioritized using the proposed Z-ARAS method based on the outputs of the previous phases. This approach considers the uncertainty in the determining factors and assigns different weights to them, while also taking into account the reliability of the risks through the Z-Number theory. Finally, comparing the proposed approach with other traditional approaches, reinforces the usefulness of the proposed method in evaluating failure modes in OR management.
{"title":"A New Extended Approach to Reduce Admission Time in Hospital Operating Rooms Based on the FMEA Method in an Uncertain Environment","authors":"Nazli Ghanbari Ghoushchi, Koohyar Ahmadzadeh, Saeid Jafarzadeh Ghoushchi","doi":"10.31181/jscda11202310","DOIUrl":"https://doi.org/10.31181/jscda11202310","url":null,"abstract":"Operating rooms (ORs) are one of the essential hospital resources and optimal management can result in efficient OR usage. The admission time reduction before surgery in the ORs can lead to on-time surgery and efficient use of ORs. This study addresses this issue by identifying the main failure modes that cause delays in ORs. The conventional methodology known as Failure Mode and Effects Analysis (FMEA) represents one of the prevailing techniques utilized for the purpose of ascertaining failure modes within a given process. This involves the assignment of numerical scores to each failure mode, with the intention of utilizing the resultant Risk Priority Number (RPN) to facilitate the identification of said failure modes. However, RPN scoring has been criticized for some deficiencies. This study proposes a three-phase approach to address some of the shortcomings of the FMEA method. The initial stage involves utilizing the FMEA approach to recognize failure modes and assess the crucial elements of RPN. Following this, the second stage employs the Z-BWM technique and expert insights to determine the weights of the five essential factors. Lastly, in the third phase, risks are prioritized using the proposed Z-ARAS method based on the outputs of the previous phases. This approach considers the uncertainty in the determining factors and assigns different weights to them, while also taking into account the reliability of the risks through the Z-Number theory. Finally, comparing the proposed approach with other traditional approaches, reinforces the usefulness of the proposed method in evaluating failure modes in OR management.","PeriodicalId":313803,"journal":{"name":"Journal of Soft Computing and Decision Analytics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115174742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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