Pub Date : 2021-01-01DOI: 10.1504/ijvcm.2021.116401
P. Bisogni, H. Brdulak, F. Cantoni, Tarvo Niine, Helmut E. Zsifkovits
{"title":"The role of European Logistics Association 2020 Standards in facing modern industry expectations and logistics managers' competencies","authors":"P. Bisogni, H. Brdulak, F. Cantoni, Tarvo Niine, Helmut E. Zsifkovits","doi":"10.1504/ijvcm.2021.116401","DOIUrl":"https://doi.org/10.1504/ijvcm.2021.116401","url":null,"abstract":"","PeriodicalId":43149,"journal":{"name":"International Journal of Value Chain Management","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66823565","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 : 2021-01-01DOI: 10.1504/ijvcm.2021.10041783
Mahdi Yousefi Nejad Attari, A. Ala, Saeed Kolahi Randji, E. N. Jami
{"title":"An integrated multi-objective mathematical programming and simulation model for a multi-layer facility location problem","authors":"Mahdi Yousefi Nejad Attari, A. Ala, Saeed Kolahi Randji, E. N. Jami","doi":"10.1504/ijvcm.2021.10041783","DOIUrl":"https://doi.org/10.1504/ijvcm.2021.10041783","url":null,"abstract":"","PeriodicalId":43149,"journal":{"name":"International Journal of Value Chain Management","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66823879","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}
{"title":"Pricing decision in a multi-period hub location problem under uncertainty: a mathematical model","authors":"Mahdi Zare Bidoki, Masoud Rahiminezhad Galankashi, Mostafa Setak","doi":"10.1504/ijvcm.2021.10043023","DOIUrl":"https://doi.org/10.1504/ijvcm.2021.10043023","url":null,"abstract":"","PeriodicalId":43149,"journal":{"name":"International Journal of Value Chain Management","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66823997","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 : 2021-01-01DOI: 10.1504/ijvcm.2021.10033598
Ansuman Sahoo, Deepak Tandon, D. Jena, P. Mishra, Jamini Ranjan Meher, Rashmiranjan Panigrahi
{"title":"Inventory Management and Performance of Manufacturing Firms","authors":"Ansuman Sahoo, Deepak Tandon, D. Jena, P. Mishra, Jamini Ranjan Meher, Rashmiranjan Panigrahi","doi":"10.1504/ijvcm.2021.10033598","DOIUrl":"https://doi.org/10.1504/ijvcm.2021.10033598","url":null,"abstract":"","PeriodicalId":43149,"journal":{"name":"International Journal of Value Chain Management","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66823854","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 : 2021-01-01DOI: 10.1504/ijvcm.2021.10043020
K. Paranitharan, R. Babu, A. S. Kumar
{"title":"S-SMILE model: a leveraging mechanism to polarise performance in small and medium enterprises - an empirical study","authors":"K. Paranitharan, R. Babu, A. S. Kumar","doi":"10.1504/ijvcm.2021.10043020","DOIUrl":"https://doi.org/10.1504/ijvcm.2021.10043020","url":null,"abstract":"","PeriodicalId":43149,"journal":{"name":"International Journal of Value Chain Management","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66823917","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 : 2020-10-20DOI: 10.1504/IJVCM.2020.111077
Ioannis Koliousis, Umair Tanveer, Shamaila Ishaq
Modern supply chains are critical in terms of efficiency, economic activities and commercial impact, particularly in case of security incidents. Inland terminals, commercial ports and dry ports constitute key gateways for the transportation flows in these modern supply chains and are require enhanced security procedures. This paper develops a framework that facilitates the sharing of information among various supply chain stakeholders, which is expected to improve the security level from a value chain perspective. In this context, we propose the upgrade of the current security strategies utilising existing processes, equipment in order to minimise time and cost currently needed but more importantly improving the level of security in the supply chain. A conceptual rule and role-based data fusion framework is developed enabling the seamless and timely exchange of messages. The proposed data fusion framework has a simple architecture that supports quick integration to either network-based, distributed systems or conventional stand-alone systems and adheres to common data fusion principles. The proposed framework considers different components (e.g., sensors, algorithms and fusing procedures) in an equipment agnostic approach so as to enable easy access and easy usage of security information.
{"title":"A conceptual information sharing framework to improve supply chain security collaboration","authors":"Ioannis Koliousis, Umair Tanveer, Shamaila Ishaq","doi":"10.1504/IJVCM.2020.111077","DOIUrl":"https://doi.org/10.1504/IJVCM.2020.111077","url":null,"abstract":"Modern supply chains are critical in terms of efficiency, economic activities and commercial impact, particularly in case of security incidents. Inland terminals, commercial ports and dry ports constitute key gateways for the transportation flows in these modern supply chains and are require enhanced security procedures. This paper develops a framework that facilitates the sharing of information among various supply chain stakeholders, which is expected to improve the security level from a value chain perspective. In this context, we propose the upgrade of the current security strategies utilising existing processes, equipment in order to minimise time and cost currently needed but more importantly improving the level of security in the supply chain. A conceptual rule and role-based data fusion framework is developed enabling the seamless and timely exchange of messages. The proposed data fusion framework has a simple architecture that supports quick integration to either network-based, distributed systems or conventional stand-alone systems and adheres to common data fusion principles. The proposed framework considers different components (e.g., sensors, algorithms and fusing procedures) in an equipment agnostic approach so as to enable easy access and easy usage of security information.","PeriodicalId":43149,"journal":{"name":"International Journal of Value Chain Management","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43716998","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 : 2020-08-18DOI: 10.1504/ijvcm.2020.10031400
Bhushan S. Purohit, V. Manjrekar, Vivek K. Singh, B. K. Lad
The increasing level of automation in manufacturing calls for a decision support system which simultaneously optimises multiple decisions of a value chain. Current work leverages integrated planning approach for the same and integrates four key functions viz. production, maintenance, quality, and material supply at the parametric level. Such a comprehensive integration of various disjoint functions is not reported in past and thus forms the novelty of current work. Further, a composite performance index called 'overall operations rating (OOR)' is explicated to simultaneously accommodate multiple performance indicators of any manufacturing shop floor. For a specific environment, proposed approach demonstrates a reduction of around 15% in operating cost and improvement of around 12% in OOR as compared to conventional operations planning approaches. Further, the application of the demonstrated approach is extended to a broad range of manufacturing environment which generalises the results.
{"title":"Integrated decision support system for manufacturing value chain","authors":"Bhushan S. Purohit, V. Manjrekar, Vivek K. Singh, B. K. Lad","doi":"10.1504/ijvcm.2020.10031400","DOIUrl":"https://doi.org/10.1504/ijvcm.2020.10031400","url":null,"abstract":"The increasing level of automation in manufacturing calls for a decision support system which simultaneously optimises multiple decisions of a value chain. Current work leverages integrated planning approach for the same and integrates four key functions viz. production, maintenance, quality, and material supply at the parametric level. Such a comprehensive integration of various disjoint functions is not reported in past and thus forms the novelty of current work. Further, a composite performance index called 'overall operations rating (OOR)' is explicated to simultaneously accommodate multiple performance indicators of any manufacturing shop floor. For a specific environment, proposed approach demonstrates a reduction of around 15% in operating cost and improvement of around 12% in OOR as compared to conventional operations planning approaches. Further, the application of the demonstrated approach is extended to a broad range of manufacturing environment which generalises the results.","PeriodicalId":43149,"journal":{"name":"International Journal of Value Chain Management","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42691055","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 : 2020-08-18DOI: 10.1504/ijvcm.2020.10031405
J. Won, M. Park
This study clustered the use of information systems (ISs) of firms based on the value chain and analysed the characteristics of each cluster. The empirical analysis utilised major ISs and sample of 2,012 SMEs in the manufacturing industry. Five types of ISs use were classified as a result of clustering based on nine activities suggested in Porter's theory of competitive advantage. For these cluster types, ANOVA showed differences for all the company factors derived from the TOE framework. In particular, it revealed distinct differences in technical factors and in organisational factors. However, environmental factors did not indicate as much of difference. This study was meaningful as it analysed the main characteristics of the company in the value chain rather than just individual IS activities. It also suggests significant implications for alternative policies, such as the operation of industrial complexes and the activities they focus on under the constraints of SMEs.
{"title":"Information system use and SME characteristics in value chain activities: evidence from the manufacturing industry in Korea","authors":"J. Won, M. Park","doi":"10.1504/ijvcm.2020.10031405","DOIUrl":"https://doi.org/10.1504/ijvcm.2020.10031405","url":null,"abstract":"This study clustered the use of information systems (ISs) of firms based on the value chain and analysed the characteristics of each cluster. The empirical analysis utilised major ISs and sample of 2,012 SMEs in the manufacturing industry. Five types of ISs use were classified as a result of clustering based on nine activities suggested in Porter's theory of competitive advantage. For these cluster types, ANOVA showed differences for all the company factors derived from the TOE framework. In particular, it revealed distinct differences in technical factors and in organisational factors. However, environmental factors did not indicate as much of difference. This study was meaningful as it analysed the main characteristics of the company in the value chain rather than just individual IS activities. It also suggests significant implications for alternative policies, such as the operation of industrial complexes and the activities they focus on under the constraints of SMEs.","PeriodicalId":43149,"journal":{"name":"International Journal of Value Chain Management","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42899680","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 : 2020-08-18DOI: 10.1504/ijvcm.2020.10031404
N. Sawant, V. V. Panicker, Anoop Kezhe Perumpadappu
This work deals with the movement of food grains in India undertaken by a food grain procurement and storage organisation. The movement is primarily achieved through the railway network, followed by the road network. The scope of the work is confined to the movement of food grains in Kerala region through railway network. This work applies machine learning algorithms to predict the occurrence of rail-wagon detention in the warehouses. Classification models are developed to predict the occurrence of detention at warehouses, and regression models are developed to predict the detention hours, based on the historical data. Popular algorithms used in this work are logistic regression, k-Nearest Neighbour, Naive Bayes, decision tree, random forest, support vector machine and multiple linear regressions. Various performance parameters are used to evaluate the different models, and the best model is chosen for further prediction.
{"title":"Predictive models for rail-wagon detention in food grain logistics: a technological intervention","authors":"N. Sawant, V. V. Panicker, Anoop Kezhe Perumpadappu","doi":"10.1504/ijvcm.2020.10031404","DOIUrl":"https://doi.org/10.1504/ijvcm.2020.10031404","url":null,"abstract":"This work deals with the movement of food grains in India undertaken by a food grain procurement and storage organisation. The movement is primarily achieved through the railway network, followed by the road network. The scope of the work is confined to the movement of food grains in Kerala region through railway network. This work applies machine learning algorithms to predict the occurrence of rail-wagon detention in the warehouses. Classification models are developed to predict the occurrence of detention at warehouses, and regression models are developed to predict the detention hours, based on the historical data. Popular algorithms used in this work are logistic regression, k-Nearest Neighbour, Naive Bayes, decision tree, random forest, support vector machine and multiple linear regressions. Various performance parameters are used to evaluate the different models, and the best model is chosen for further prediction.","PeriodicalId":43149,"journal":{"name":"International Journal of Value Chain Management","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47828947","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 : 2020-04-08DOI: 10.1504/ijvcm.2020.10028363
P. Hashemzahi, A. Azadnia, Masoud Rahiminezhad Galankashi, S. A. Helmi, F. M. Rafiei
Supplier selection and order allocation is a complex managerial decision in today's competitive markets. As an important section of this area, green supplier section has been properly focused in previous literature. However, joint supplier selection and order allocation under stochastic demand is less investigated. Firstly, a fuzzy analytic hierarchy process (FAHP) is applied to weight and select suppliers in terms of economic and environmental criteria. Secondly, a multi-objective nonlinear programming (MONLP) is developed and solved by genetic algorithm (GA) for the aim of order allocation. Findings of this study assist managers to systemically deal with the real-world problem of green supplier selection with different priorities and order quantities.
{"title":"Green supplier selection and order allocation: a nonlinear stochastic model","authors":"P. Hashemzahi, A. Azadnia, Masoud Rahiminezhad Galankashi, S. A. Helmi, F. M. Rafiei","doi":"10.1504/ijvcm.2020.10028363","DOIUrl":"https://doi.org/10.1504/ijvcm.2020.10028363","url":null,"abstract":"Supplier selection and order allocation is a complex managerial decision in today's competitive markets. As an important section of this area, green supplier section has been properly focused in previous literature. However, joint supplier selection and order allocation under stochastic demand is less investigated. Firstly, a fuzzy analytic hierarchy process (FAHP) is applied to weight and select suppliers in terms of economic and environmental criteria. Secondly, a multi-objective nonlinear programming (MONLP) is developed and solved by genetic algorithm (GA) for the aim of order allocation. Findings of this study assist managers to systemically deal with the real-world problem of green supplier selection with different priorities and order quantities.","PeriodicalId":43149,"journal":{"name":"International Journal of Value Chain Management","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43528210","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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