Pub Date : 2023-04-15DOI: 10.31181/dmame0318062021g
Sayan Gupta, Gautam Bandyopadhyay, S. Biswas, A. Mitra
Investment extortion in the stock market is a crucial aspect considered by the investors. Therefore, investors implemented different strategies. This study was intended at constructing an investment portfolio (IP) of stocks within the NSE 100 listed companies of Non-parametric nature, fulfilling the basic premise of portfolio making that is, reducing risks while yielding an attractive return higher than any other instrument for the investors. Using DP omnibus test, the desired sample of companies following the non-normal distribution was achieved. Using financial beta, we have selected the outcome based on the nature of their ‘return’ and ‘risk'. We introduce TOPSIS (Technique for order of performance by similarity to ideal solution), a multi-criteria decision-making process (MCDM) to study the profitability of stocks, rank wise for each year, and finally, the Bayes portfolio model help to select the overall profitability associate with low risk for the construction of the portfolio.
股票市场中的投资敲诈是投资者关注的一个重要问题。因此，投资者采取了不同的策略。本研究旨在构建NSE 100上市公司非参数性股票的投资组合(IP)，实现投资组合的基本前提，即降低风险，同时为投资者提供高于任何其他工具的有吸引力的回报。采用DP综合检验，得到了符合非正态分布的期望样本。使用金融beta，我们根据它们的“回报”和“风险”的性质选择了结果。我们引入了多准则决策过程(MCDM) TOPSIS (technical for order of performance by similarity to ideal solution)来研究股票的盈利能力，对每年进行明智的排名，最后，贝叶斯投资组合模型帮助选择与低风险相关的整体盈利能力来构建投资组合。
{"title":"An integrated framework for classification and selection of stocks for portfolio construction: Evidence from NSE, India","authors":"Sayan Gupta, Gautam Bandyopadhyay, S. Biswas, A. Mitra","doi":"10.31181/dmame0318062021g","DOIUrl":"https://doi.org/10.31181/dmame0318062021g","url":null,"abstract":"Investment extortion in the stock market is a crucial aspect considered by the investors. Therefore, investors implemented different strategies. This study was intended at constructing an investment portfolio (IP) of stocks within the NSE 100 listed companies of Non-parametric nature, fulfilling the basic premise of portfolio making that is, reducing risks while yielding an attractive return higher than any other instrument for the investors. Using DP omnibus test, the desired sample of companies following the non-normal distribution was achieved. Using financial beta, we have selected the outcome based on the nature of their ‘return’ and ‘risk'. We introduce TOPSIS (Technique for order of performance by similarity to ideal solution), a multi-criteria decision-making process (MCDM) to study the profitability of stocks, rank wise for each year, and finally, the Bayes portfolio model help to select the overall profitability associate with low risk for the construction of the portfolio.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45121434","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}
Pub Date : 2023-04-15DOI: 10.31181/dmame0301072022m
Power outage is one of the significant problems for electricity distribution companies. Power outages cause customer dissatisfaction and reduce distribution companies' profits and revenues. Therefore, the electricity distribution companies are trying to moderate the leading causes of the outage. However, the dynamics of environmental conditions create uncertainties that require prioritizing the solutions of outages causes in different situations. Therefore, this study presents a scenario-based approach to prioritize power outage causes. Four case studies have been conducted in four cities of Kerman province in Iran. First, the prioritization criteria and causes of the outage were identified using literature and interviews with experts in this field. Then, the Global Business Network matrix was used to create four possible scenarios. Then, the Best-Worst method and TOPSIS method were applied to weight the prioritizing criteria and prioritize the causes of the outages in different scenarios. The results showed that working in the power network limit zone, as one of the causes of outage in Sirjan and Jiroft cities, has the most priority. Also, the collision of external objects, birds, and annoying trees should be considered by managers as the leading causes of outages in Bam and Kahnuj cities.
{"title":"Prioritizing power outages causes in different scenarios of the global business network matrix","authors":"","doi":"10.31181/dmame0301072022m","DOIUrl":"https://doi.org/10.31181/dmame0301072022m","url":null,"abstract":"Power outage is one of the significant problems for electricity distribution companies. Power outages cause customer dissatisfaction and reduce distribution companies' profits and revenues. Therefore, the electricity distribution companies are trying to moderate the leading causes of the outage. However, the dynamics of environmental conditions create uncertainties that require prioritizing the solutions of outages causes in different situations. Therefore, this study presents a scenario-based approach to prioritize power outage causes. Four case studies have been conducted in four cities of Kerman province in Iran. First, the prioritization criteria and causes of the outage were identified using literature and interviews with experts in this field. Then, the Global Business Network matrix was used to create four possible scenarios. Then, the Best-Worst method and TOPSIS method were applied to weight the prioritizing criteria and prioritize the causes of the outages in different scenarios. The results showed that working in the power network limit zone, as one of the causes of outage in Sirjan and Jiroft cities, has the most priority. Also, the collision of external objects, birds, and annoying trees should be considered by managers as the leading causes of outages in Bam and Kahnuj cities.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45284991","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}
Pub Date : 2023-04-15DOI: 10.31181/dmame0313052021b
Bipradas Bairagi
In the rapidly changing global circumstances, managements of industrial organizations are making decisions for their survival in business atmosphere in future. Decision makers in industries are steering their respective organizations towards for appropriate decision making satisfying the condition of ‘Go green’. Appropriate decision making in fuzzy environment is always a hard task. The current investigation explores a new multi criteria decision making approach for green selection of material handling equipment under fuzzy environment. The proposed technique has the capability of capturing effects of economical, environmental and social factors of benefit, non-benefit and target based criteria under uncertainty and vague information. The proposed method is illustrated with a suitable example on material handling equipment selection under fuzzy environment. The result clearly shows that the proposed technique is useful and effective in the decision making process regarding green material handling selection under fuzzy environment.
{"title":"A new framework for green selection of material handling equipment under fuzzy environment","authors":"Bipradas Bairagi","doi":"10.31181/dmame0313052021b","DOIUrl":"https://doi.org/10.31181/dmame0313052021b","url":null,"abstract":"In the rapidly changing global circumstances, managements of industrial organizations are making decisions for their survival in business atmosphere in future. Decision makers in industries are steering their respective organizations towards for appropriate decision making satisfying the condition of ‘Go green’. Appropriate decision making in fuzzy environment is always a hard task. The current investigation explores a new multi criteria decision making approach for green selection of material handling equipment under fuzzy environment. The proposed technique has the capability of capturing effects of economical, environmental and social factors of benefit, non-benefit and target based criteria under uncertainty and vague information. The proposed method is illustrated with a suitable example on material handling equipment selection under fuzzy environment. The result clearly shows that the proposed technique is useful and effective in the decision making process regarding green material handling selection under fuzzy environment.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46549561","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}
Pub Date : 2023-04-15DOI: 10.31181/dmame060127022023t
M. Tutak, Jarosław Brodny
The article presents the results of a study aimed at assessing the level of innovation potential of European Union member states. The research was based on 8 diagnostic variables characterizing the two most important dimensions of innovation, namely human resources and R&D expenditures. As a result of the research, the levels of innovation potential of European Union countries between 2010-2020 were specified. The GRA approach and multidimensional scaling were used for the study. Based on the results, the European Union countries were divided into 4 classes. The findings showed large differences in this potential across countries, which was graphically illustrated by using the multidimensional scaling method. In addition, using two non-parametric tests, (Spearman Rank Correlation Coefficient and Kendall Correlation Coefficient), relationships between the innovation potential of member states and selected economic and innovation parameters of their economies were determined. The results of the study indicate that in the old EU-14 countries, this level was at a significantly higher level than in the new EU-13 countries. The EU-27 innovation potential leaders were found to be Finland, Sweden, Luxembourg, Denmark, and Germany. The worst performers, on the other hand, are Malta and Romania. Also, geographically, there were noticeable differences between the countries studied. The results presented should be used to develop strategies and implement policies for sustainable innovative development in the European Union. To the best of the authors' knowledge, this study is a new contribution to assessing the level of innovation potential of European Union member countries and determining the relationship of this potential with selected parameters of the economy of these countries.
{"title":"Progress towards the innovation potential of the European union member states using grey relational analysis and multidimensional scaling methods","authors":"M. Tutak, Jarosław Brodny","doi":"10.31181/dmame060127022023t","DOIUrl":"https://doi.org/10.31181/dmame060127022023t","url":null,"abstract":"The article presents the results of a study aimed at assessing the level of innovation potential of European Union member states. The research was based on 8 diagnostic variables characterizing the two most important dimensions of innovation, namely human resources and R&D expenditures. As a result of the research, the levels of innovation potential of European Union countries between 2010-2020 were specified. The GRA approach and multidimensional scaling were used for the study. Based on the results, the European Union countries were divided into 4 classes. The findings showed large differences in this potential across countries, which was graphically illustrated by using the multidimensional scaling method. In addition, using two non-parametric tests, (Spearman Rank Correlation Coefficient and Kendall Correlation Coefficient), relationships between the innovation potential of member states and selected economic and innovation parameters of their economies were determined. The results of the study indicate that in the old EU-14 countries, this level was at a significantly higher level than in the new EU-13 countries. The EU-27 innovation potential leaders were found to be Finland, Sweden, Luxembourg, Denmark, and Germany. The worst performers, on the other hand, are Malta and Romania. Also, geographically, there were noticeable differences between the countries studied. The results presented should be used to develop strategies and implement policies for sustainable innovative development in the European Union. To the best of the authors' knowledge, this study is a new contribution to assessing the level of innovation potential of European Union member countries and determining the relationship of this potential with selected parameters of the economy of these countries.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47433013","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}
Pub Date : 2023-04-15DOI: 10.31181/dmame060113032023j
Henrietta Janik, Zsuzsanna Naár-Tóth, S. Vinogradov
International student mobility is increasing and transforming the image of higher education institutions. This study examines the factors that motivate international students in choosing a destination country. The aspects of the institution selection were examined using a non-parametric test, factor analysis and principal component analysis based on a sample of 270 people. Relying on the results of the research conducted in Hungary, the paper examines the factors influencing the selection of the destination country and further research examining the elements effecting the selection of the final host institution. Based on these results, the study disputes that economic and social impulses within the country of origin serve to “push” students abroad. However, the decision of which destination country to choose depends on several “pull” factors. The study features the usefulness of the quality of human environment, geographic proximity, tuition and living costs, scholarship opportunities, job opportunities after graduation, and the reputation of the destination country or institution, as well as the impact of linguistic proximity on student flow. The present empirical research reveals the close relationships between some pull factors, such as favourable geographical location, institutional support, the quality of the human environment, the expected balanced work environment after graduation, and the country of origin of international students. The results of the factor analysis confirm the underlying structure of the learning variables used in this research and provide empirical support for its application in future studies of international students' higher education study experiences.
{"title":"Examining the aspects of institution choice in connection with the internationalization of higher education","authors":"Henrietta Janik, Zsuzsanna Naár-Tóth, S. Vinogradov","doi":"10.31181/dmame060113032023j","DOIUrl":"https://doi.org/10.31181/dmame060113032023j","url":null,"abstract":"International student mobility is increasing and transforming the image of higher education institutions. This study examines the factors that motivate international students in choosing a destination country. The aspects of the institution selection were examined using a non-parametric test, factor analysis and principal component analysis based on a sample of 270 people. Relying on the results of the research conducted in Hungary, the paper examines the factors influencing the selection of the destination country and further research examining the elements effecting the selection of the final host institution. Based on these results, the study disputes that economic and social impulses within the country of origin serve to “push” students abroad. However, the decision of which destination country to choose depends on several “pull” factors. The study features the usefulness of the quality of human environment, geographic proximity, tuition and living costs, scholarship opportunities, job opportunities after graduation, and the reputation of the destination country or institution, as well as the impact of linguistic proximity on student flow. The present empirical research reveals the close relationships between some pull factors, such as favourable geographical location, institutional support, the quality of the human environment, the expected balanced work environment after graduation, and the country of origin of international students. The results of the factor analysis confirm the underlying structure of the learning variables used in this research and provide empirical support for its application in future studies of international students' higher education study experiences.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45593777","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}
K. Pandey, A. Mishra, Pratibha Rani, Jabir Ali, R. Chakrabortty
Feature selection is the most significant pre-processing activity, which intends to reduce the data dimensionality for enhancing the machine learning process. The evaluation of feature selection must consider classification, performance, efficiency, stability, and many factors. Nowadays, uncertainty is commonly occurred in the feature selection process due to time limitations, imprecise information, and the subjectivity of human minds. Moreover, the theory of intuitionistic fuzzy set has been proven as an extremely valuable tool to tackle the uncertainty and ambiguity that arises in many practical situations. Thus, this study introduces a novel feature selection framework using intuitionistic fuzzy entropy. In this regard, new entropy for IFS is proposed first and then compared with some of the previously developed entropy measures. As entropy is a measure of uncertainty present in data (features), features with higher entropy values are filtered out, and the remaining features having lower entropy values have been used to classify the data. To verify the effectiveness of the proposed entropy-based feature selection, some experiments are done with ten standard benchmark datasets by employing a support vector machine, K-nearest neighbor, and Naïve Bias classifiers. The outcomes of the study validate that the proposed entropy-based filter feature selection is more feasible and impressive than existing filter-based feature selection methods.
{"title":"Selecting features by utilizing intuitionistic fuzzy Entropy method","authors":"K. Pandey, A. Mishra, Pratibha Rani, Jabir Ali, R. Chakrabortty","doi":"10.31181/dmame07012023p","DOIUrl":"https://doi.org/10.31181/dmame07012023p","url":null,"abstract":"Feature selection is the most significant pre-processing activity, which intends to reduce the data dimensionality for enhancing the machine learning process. The evaluation of feature selection must consider classification, performance, efficiency, stability, and many factors. Nowadays, uncertainty is commonly occurred in the feature selection process due to time limitations, imprecise information, and the subjectivity of human minds. Moreover, the theory of intuitionistic fuzzy set has been proven as an extremely valuable tool to tackle the uncertainty and ambiguity that arises in many practical situations. Thus, this study introduces a novel feature selection framework using intuitionistic fuzzy entropy. In this regard, new entropy for IFS is proposed first and then compared with some of the previously developed entropy measures. As entropy is a measure of uncertainty present in data (features), features with higher entropy values are filtered out, and the remaining features having lower entropy values have been used to classify the data. To verify the effectiveness of the proposed entropy-based feature selection, some experiments are done with ten standard benchmark datasets by employing a support vector machine, K-nearest neighbor, and Naïve Bias classifiers. The outcomes of the study validate that the proposed entropy-based filter feature selection is more feasible and impressive than existing filter-based feature selection methods.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47382060","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}
Pub Date : 2023-04-15DOI: 10.31181/dmame0318102022t
D. Tripathi, Santosh K. Nigam, Pratibha Rani, Abdul Raoof Shah
The present study introduces a decision-making approach with the combined compromise solution (CoCoSo) under intuitionistic fuzzy sets (IFSs) named as the IF-CoCoSo method based on proposed divergence measures and score function. The aim of the presented approach is to obtain an effective solution for multi-criteria decision-making problems on IFSs context. In this line, a new procedure is presented to derive the criteria weights using generalized score function and parametric divergence measures of IFSs. To compute the criteria weight, a generalized score function and parametric divergence measures are developed on IFSs and discussed some interesting properties. Further, the presented approach is applied to rank and evaluate the therapies for medical decision making problems, which demonstrates its applicability and feasibility. Finally, comparative and sensitivity analyses are discussed for validating the developed method.
{"title":"New intuitionistic fuzzy parametric divergence measures and score function-based CoCoSo method for decision-making problems","authors":"D. Tripathi, Santosh K. Nigam, Pratibha Rani, Abdul Raoof Shah","doi":"10.31181/dmame0318102022t","DOIUrl":"https://doi.org/10.31181/dmame0318102022t","url":null,"abstract":"The present study introduces a decision-making approach with the combined compromise solution (CoCoSo) under intuitionistic fuzzy sets (IFSs) named as the IF-CoCoSo method based on proposed divergence measures and score function. The aim of the presented approach is to obtain an effective solution for multi-criteria decision-making problems on IFSs context. In this line, a new procedure is presented to derive the criteria weights using generalized score function and parametric divergence measures of IFSs. To compute the criteria weight, a generalized score function and parametric divergence measures are developed on IFSs and discussed some interesting properties. Further, the presented approach is applied to rank and evaluate the therapies for medical decision making problems, which demonstrates its applicability and feasibility. Finally, comparative and sensitivity analyses are discussed for validating the developed method.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":"61 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41246654","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}
Pub Date : 2023-04-15DOI: 10.31181/dmame0323062022s
In this paper, we formulate and solve an Imprecise Covering Ring Star Problem (ICRSP), which is a generalization of the Ring Star Problem (RSP). Here the objective of this problem is to find a subset of nodes in a network to minimize the sum of routing costs of interconnecting cycle and assignment costs of the nodes which are out of cycle, to their nearest concentrators such that no assigned node exceeds a predetermined distance (say, covering distance) from the concentrators. The covering distance, as well as the routing and assignments costs, are considered as fuzzy in the proposed ICRSP. A Modified Genetic Algorithm (MGA) is developed and used to solve this model for different confidence levels depending on the corresponding imprecise parameters, reducing it to deterministic form with fuzzy possibility and necessity approaches. Some comparisons with existing benchmark problems are made to justify the performance of the algorithm. As individual cases, some practical ICRSPs are also solved and presented numerically.
{"title":"Imprecise covering ring star problem","authors":"","doi":"10.31181/dmame0323062022s","DOIUrl":"https://doi.org/10.31181/dmame0323062022s","url":null,"abstract":"In this paper, we formulate and solve an Imprecise Covering Ring Star Problem (ICRSP), which is a generalization of the Ring Star Problem (RSP). Here the objective of this problem is to find a subset of nodes in a network to minimize the sum of routing costs of interconnecting cycle and assignment costs of the nodes which are out of cycle, to their nearest concentrators such that no assigned node exceeds a predetermined distance (say, covering distance) from the concentrators. The covering distance, as well as the routing and assignments costs, are considered as fuzzy in the proposed ICRSP. A Modified Genetic Algorithm (MGA) is developed and used to solve this model for different confidence levels depending on the corresponding imprecise parameters, reducing it to deterministic form with fuzzy possibility and necessity approaches. Some comparisons with existing benchmark problems are made to justify the performance of the algorithm. As individual cases, some practical ICRSPs are also solved and presented numerically.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44103588","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}
Pub Date : 2023-04-15DOI: 10.31181/dmame0319102022d
A. Dash, B. Giri, A. Sarkar
When dealing with uncertainties in the supply chain and ensuring customer satisfaction, efficient management of lead time plays a significant role. Likewise, besides managing inventory and pricing strategies adeptly in multi-retailer supply chains, it has become inevitable for firms to embrace green and sustainable business practices. In this context, this paper considers a two-level supply chain consisting of a single manufacturer and multiple retailers in which the manufacturer produces a single product and delivers it to the retailers in equal-sized batches. Each retailer faces a price and green-sensitive market demand. The lead time is assumed to be a random variable that follows a normal distribution. Shortages for retailer inventory are allowed to occur and are completely backlogged. The centralized model and a decentralized model based on the leader-follower Stackelberg gaming approach are developed. A price discount mechanism between the manufacturer and retailers is proposed. For the acceptance of this contract, the upper and lower limits of the price discount rate are established. Numerical outcomes exhibit that the price discount mechanism effectively coordinates the supply chain and enhances both environmental and economical performances. A sensitivity analysis with respect to some key parameters is performed, and certain managerial insights are emphasized.
{"title":"Coordination of a single-manufacturer multi-retailer supply chain with price and green sensitive demand under stochastic lead time","authors":"A. Dash, B. Giri, A. Sarkar","doi":"10.31181/dmame0319102022d","DOIUrl":"https://doi.org/10.31181/dmame0319102022d","url":null,"abstract":"When dealing with uncertainties in the supply chain and ensuring customer satisfaction, efficient management of lead time plays a significant role. Likewise, besides managing inventory and pricing strategies adeptly in multi-retailer supply chains, it has become inevitable for firms to embrace green and sustainable business practices. In this context, this paper considers a two-level supply chain consisting of a single manufacturer and multiple retailers in which the manufacturer produces a single product and delivers it to the retailers in equal-sized batches. Each retailer faces a price and green-sensitive market demand. The lead time is assumed to be a random variable that follows a normal distribution. Shortages for retailer inventory are allowed to occur and are completely backlogged. The centralized model and a decentralized model based on the leader-follower Stackelberg gaming approach are developed. A price discount mechanism between the manufacturer and retailers is proposed. For the acceptance of this contract, the upper and lower limits of the price discount rate are established. Numerical outcomes exhibit that the price discount mechanism effectively coordinates the supply chain and enhances both environmental and economical performances. A sensitivity analysis with respect to some key parameters is performed, and certain managerial insights are emphasized.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44491309","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}
Pub Date : 2023-04-15DOI: 10.31181/dmame060120032023m
Albert Molnár, Laszlo Vasa, Ágnes Csiszárik-Kocsir
This paper applies the hidden Markov switching dynamic regression (MSDR) model to estimate transition probabilities of the Hungarian GDP between recessionary and expansionary periods. The transition probabilities are then compared to the OECD Hungarian binary business cycle indicator to assess the predictive power of the model. The paper proposes a linear model with a mean and a homoscedastic component. The level of symmetricity between the GDP and business cycles is explained by the panel data variables (Unemployment rate, IPI index, Inflation, BUX year-on-year change, and 10-3 Year sovereign bond yield spreads). It is assumed in this paper that by extending the model to encompass an exogenous variable listed in the panel data, essentially making the model bivariate, the maximum likelihood function would capture the business cycle more accurately. The results show that by plugging the unemployment rate as the exogenous variable in the regression, our model’s accuracy is 70%.
{"title":"Detecting business cycles for Hungarian leading and coincident indicators with a Markov switching dynamic model to improve sustainability in economic growth","authors":"Albert Molnár, Laszlo Vasa, Ágnes Csiszárik-Kocsir","doi":"10.31181/dmame060120032023m","DOIUrl":"https://doi.org/10.31181/dmame060120032023m","url":null,"abstract":"This paper applies the hidden Markov switching dynamic regression (MSDR) model to estimate transition probabilities of the Hungarian GDP between recessionary and expansionary periods. The transition probabilities are then compared to the OECD Hungarian binary business cycle indicator to assess the predictive power of the model. The paper proposes a linear model with a mean and a homoscedastic component. The level of symmetricity between the GDP and business cycles is explained by the panel data variables (Unemployment rate, IPI index, Inflation, BUX year-on-year change, and 10-3 Year sovereign bond yield spreads). It is assumed in this paper that by extending the model to encompass an exogenous variable listed in the panel data, essentially making the model bivariate, the maximum likelihood function would capture the business cycle more accurately. The results show that by plugging the unemployment rate as the exogenous variable in the regression, our model’s accuracy is 70%.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45760203","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：