Pub Date : 1900-01-01DOI: 10.4018/978-1-5225-7299-2.CH004
A. R. Sadurdeen, J. Sutha
Organizations adopt many strategies to gain competitive advantage. An important strategy is adopting green practices. Cost-benefit and customer value enhancement are two other strategies. By combining all of these elements, organizations can acquire a superior competitive advantage. There are contradictory findings on applying the cost-benefit element to green supply chain management (GSCM) and no clear theory on how to combine these elements to gain a competitive advantage. The primary objective of this study is to identify the impact of GSCM on competitive advantage of business organizations in Sri Lanka. Sample technique used was convenience sampling method. Data was collected from 30 organizations that were following green practices in Sri Lanka. The data were analyzed using descriptive analysis, correlation coefficient, and simple regression model. The results show that there is a strong positive relationship between GSCM and competitive advantage, and rather than applying just one element to gain a competitive advantage, it was considered more effective to apply both cost-benefit and customer value enhancement simultaneously.
{"title":"Impact of Green Supply Chain Management on Competitive Advantage of Business Organizations in Sri Lanka","authors":"A. R. Sadurdeen, J. Sutha","doi":"10.4018/978-1-5225-7299-2.CH004","DOIUrl":"https://doi.org/10.4018/978-1-5225-7299-2.CH004","url":null,"abstract":"Organizations adopt many strategies to gain competitive advantage. An important strategy is adopting green practices. Cost-benefit and customer value enhancement are two other strategies. By combining all of these elements, organizations can acquire a superior competitive advantage. There are contradictory findings on applying the cost-benefit element to green supply chain management (GSCM) and no clear theory on how to combine these elements to gain a competitive advantage. The primary objective of this study is to identify the impact of GSCM on competitive advantage of business organizations in Sri Lanka. Sample technique used was convenience sampling method. Data was collected from 30 organizations that were following green practices in Sri Lanka. The data were analyzed using descriptive analysis, correlation coefficient, and simple regression model. The results show that there is a strong positive relationship between GSCM and competitive advantage, and rather than applying just one element to gain a competitive advantage, it was considered more effective to apply both cost-benefit and customer value enhancement simultaneously.","PeriodicalId":185056,"journal":{"name":"Hierarchical Planning and Information Sharing Techniques in Supply Chain Management","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129419695","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 : 1900-01-01DOI: 10.4018/978-1-5225-7299-2.CH005
S. Srinivasan
Supply chain management (SCM) is essentially a set of approaches utilized to efficiently integrate suppliers, manufacturers, warehouses, and stores, so that merchandise is produced and distributed at the right quantities, to the right locations, and at the right time in order to minimize system-wide costs or maximize profits while satisfying service level requirements. To solve complex problems in SCM and to obtain optimization, various meta-heuristics algorithms can be used. Thus, this chapter discusses the background of meta-heuristics algorithms. The related work and future research direction for using meta-heuristics approaches for supply chain management are addressed in this chapter.
{"title":"Meta-Heuristic Approaches for Supply Chain Management","authors":"S. Srinivasan","doi":"10.4018/978-1-5225-7299-2.CH005","DOIUrl":"https://doi.org/10.4018/978-1-5225-7299-2.CH005","url":null,"abstract":"Supply chain management (SCM) is essentially a set of approaches utilized to efficiently integrate suppliers, manufacturers, warehouses, and stores, so that merchandise is produced and distributed at the right quantities, to the right locations, and at the right time in order to minimize system-wide costs or maximize profits while satisfying service level requirements. To solve complex problems in SCM and to obtain optimization, various meta-heuristics algorithms can be used. Thus, this chapter discusses the background of meta-heuristics algorithms. The related work and future research direction for using meta-heuristics approaches for supply chain management are addressed in this chapter.","PeriodicalId":185056,"journal":{"name":"Hierarchical Planning and Information Sharing Techniques in Supply Chain Management","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127903244","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 : 1900-01-01DOI: 10.4018/978-1-5225-7299-2.CH007
Arzu Eren Şenaras
System dynamics is an interdisciplinary problem-solving methodology that utilizes several significant thinking skills such as dynamic thinking and cause-and-effect thinking. System dynamics is a disciplined collaborative approach that could accelerate learning by combining a multifaceted perspective that provides insight into complex and interactive issues. System dynamics is designed to model, analyze, and improve socio-economic and administrative systems using a feedback perspective. Dynamic structured administrative problems are modeled by mathematical equations and using computer software. Dynamic constructions of model variables are obtained using computer simulations. In this chapter, a system dynamics model will be developed for supply chain management. The case study will be developed using VENSIM package program.
{"title":"A Case Study for Supply Chain Management Using System Dynamics","authors":"Arzu Eren Şenaras","doi":"10.4018/978-1-5225-7299-2.CH007","DOIUrl":"https://doi.org/10.4018/978-1-5225-7299-2.CH007","url":null,"abstract":"System dynamics is an interdisciplinary problem-solving methodology that utilizes several significant thinking skills such as dynamic thinking and cause-and-effect thinking. System dynamics is a disciplined collaborative approach that could accelerate learning by combining a multifaceted perspective that provides insight into complex and interactive issues. System dynamics is designed to model, analyze, and improve socio-economic and administrative systems using a feedback perspective. Dynamic structured administrative problems are modeled by mathematical equations and using computer software. Dynamic constructions of model variables are obtained using computer simulations. In this chapter, a system dynamics model will be developed for supply chain management. The case study will be developed using VENSIM package program.","PeriodicalId":185056,"journal":{"name":"Hierarchical Planning and Information Sharing Techniques in Supply Chain Management","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124030588","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 : 1900-01-01DOI: 10.4018/978-1-5225-7299-2.CH003
Hassan Yar Bareach, W. Malik, Rania Sohail, A. Javaid, M. N. Jalil
This chapter focuses on the hierarchical planning and execution for supply chain management in public healthcare services. The authors first introduce tiered organizational and services delivery structure of public healthcare services followed by various supply chain issues that public healthcare services encounters. They then review hierarchical planning and execution discussions for the strategic, tactical, and operational decisions in supply chain literature. They continue the discussion with public healthcare services cases on medicine and equipment maintenance supply chains. They compare hierarchical planning execution discussions in supply chain management literature vis-a-vis healthcare services cases. Their main argument is that much can be gained by the public healthcare services by striving for reduced information asymmetry and employing appropriate functional aggregation at various levels of the hierarchically organized public healthcare supply chains.
{"title":"Hierarchical Planning Models for Public Healthcare Supply Chains","authors":"Hassan Yar Bareach, W. Malik, Rania Sohail, A. Javaid, M. N. Jalil","doi":"10.4018/978-1-5225-7299-2.CH003","DOIUrl":"https://doi.org/10.4018/978-1-5225-7299-2.CH003","url":null,"abstract":"This chapter focuses on the hierarchical planning and execution for supply chain management in public healthcare services. The authors first introduce tiered organizational and services delivery structure of public healthcare services followed by various supply chain issues that public healthcare services encounters. They then review hierarchical planning and execution discussions for the strategic, tactical, and operational decisions in supply chain literature. They continue the discussion with public healthcare services cases on medicine and equipment maintenance supply chains. They compare hierarchical planning execution discussions in supply chain management literature vis-a-vis healthcare services cases. Their main argument is that much can be gained by the public healthcare services by striving for reduced information asymmetry and employing appropriate functional aggregation at various levels of the hierarchically organized public healthcare supply chains.","PeriodicalId":185056,"journal":{"name":"Hierarchical Planning and Information Sharing Techniques in Supply Chain Management","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132058630","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 : 1900-01-01DOI: 10.4018/978-1-5225-7299-2.CH001
Youssef Tliche, A. Taghipour, Beatrice Canel-Depitre
The main objective of studying decentralized supply chains is to demonstrate that a better interfirm collaboration can lead to a better overall performance of the system. Many researchers studied a phenomenon called downstream demand inference (DDI), which presents an effective demand management strategy to deal with forecast problems. DDI allows the upstream actor to infer the demand received by the downstream one without information sharing. Recent study showed that DDI is possible with simple moving average (SMA) forecast method and was verified especially for an autoregressive AR(1) demand process. This chapter extends the strategy's results by developing mean squared error and average inventory level expressions for causal invertible ARMA(p,q) demand under DDI strategy, no information sharing (NIS), and forecast information sharing (FIS) strategies. The authors analyze the sensibility of the performance metrics in respect with lead-time, SMA, and ARMA(p,q) parameters, and compare DDI results with the NIS and FIS strategies' results.
{"title":"Anticipation of Demand in Supply Chains","authors":"Youssef Tliche, A. Taghipour, Beatrice Canel-Depitre","doi":"10.4018/978-1-5225-7299-2.CH001","DOIUrl":"https://doi.org/10.4018/978-1-5225-7299-2.CH001","url":null,"abstract":"The main objective of studying decentralized supply chains is to demonstrate that a better interfirm collaboration can lead to a better overall performance of the system. Many researchers studied a phenomenon called downstream demand inference (DDI), which presents an effective demand management strategy to deal with forecast problems. DDI allows the upstream actor to infer the demand received by the downstream one without information sharing. Recent study showed that DDI is possible with simple moving average (SMA) forecast method and was verified especially for an autoregressive AR(1) demand process. This chapter extends the strategy's results by developing mean squared error and average inventory level expressions for causal invertible ARMA(p,q) demand under DDI strategy, no information sharing (NIS), and forecast information sharing (FIS) strategies. The authors analyze the sensibility of the performance metrics in respect with lead-time, SMA, and ARMA(p,q) parameters, and compare DDI results with the NIS and FIS strategies' results.","PeriodicalId":185056,"journal":{"name":"Hierarchical Planning and Information Sharing Techniques in Supply Chain Management","volume":"409 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129474384","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 : 1900-01-01DOI: 10.4018/978-1-5225-7299-2.CH002
Hamdi Radhoui, A. Taghipour, Beatrice Canel-Depitre
The literature of vehicle scheduling problems is rich with different approaches, which try to schedule the distribution of products to a network of clients. In this case, the vehicle routing problem with deliveries and pickups of goods is an extension of vehicle routing problem in which goods are transported from a depot (or multiple depots) to customers, as well from customers to the depots. There is tremendous work in the literature of this problem. Freight transport management deals with all distribution problems along the supply chain. This chapter presents a comprehensive review and survey of this literature. The literature is classified into four fundamental classes according to the way of the customers' visit and methods used for solving. Then different variants are generated according to the elements of the proposed framework. During this chapter, based on a proposed framework, the authors analyze the literature of the vehicle routing problem with deliveries and pickups, and as a result, the researchers propose a new classification where they give a short modeling of it.
{"title":"The Distribution and Pickup of Goods","authors":"Hamdi Radhoui, A. Taghipour, Beatrice Canel-Depitre","doi":"10.4018/978-1-5225-7299-2.CH002","DOIUrl":"https://doi.org/10.4018/978-1-5225-7299-2.CH002","url":null,"abstract":"The literature of vehicle scheduling problems is rich with different approaches, which try to schedule the distribution of products to a network of clients. In this case, the vehicle routing problem with deliveries and pickups of goods is an extension of vehicle routing problem in which goods are transported from a depot (or multiple depots) to customers, as well from customers to the depots. There is tremendous work in the literature of this problem. Freight transport management deals with all distribution problems along the supply chain. This chapter presents a comprehensive review and survey of this literature. The literature is classified into four fundamental classes according to the way of the customers' visit and methods used for solving. Then different variants are generated according to the elements of the proposed framework. During this chapter, based on a proposed framework, the authors analyze the literature of the vehicle routing problem with deliveries and pickups, and as a result, the researchers propose a new classification where they give a short modeling of it.","PeriodicalId":185056,"journal":{"name":"Hierarchical Planning and Information Sharing Techniques in Supply Chain Management","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131250295","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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