{"title":"Supply Chain Finance Revisited: A Critical Review with Future Prospects","authors":"G. Vousinas","doi":"10.2139/ssrn.3286977","DOIUrl":"https://doi.org/10.2139/ssrn.3286977","url":null,"abstract":"Supply Chain Finance (SCF) is a relatively recent thinking in Supply Chain Management (SCM) literature. Major Interest in SCF has steadily increased since the past decades and especially during the global financial crisis of 2008. However, SCF places the focus of research on the interconnection among SCM, corporate value and financial performance, away from the myopic perspective of managing solely the cost when studying financial aspects of SCM. Despite the crisis-related research interest and the growing importance of SCF, academic contributions on the subject remain vague, while scarce research efforts have been identified toward the systematic documentation of its core concepts and the development of a “general theory” of SCF. This paper aims to redefine the term SCF by shedding light on theoretical ambiguities, provide an up-to-date systematic literature review of the SCF concept and identify research gaps. The goal is to also highlight emerging areas like the “Supply Chain Financial Bullwhip Effect” and Blockchain Technology.","PeriodicalId":330843,"journal":{"name":"PROD: Analytical (Supply) (Topic)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116676547","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":"The Use and Value of Social Information in Selective Selling of Exclusive Products","authors":"Ruslan Momot, E. Belavina, Karan Girotra","doi":"10.2139/ssrn.2755638","DOIUrl":"https://doi.org/10.2139/ssrn.2755638","url":null,"abstract":"We consider the use and value of social-network information in selectively selling goods and services whose value derives from exclusive ownership among network connections or friends. Our model accommodates customers who are heterogeneous in their number of friends (degree) and their proclivity for social comparisons (conspicuity). Firms with information on either (or both) of these characteristics can use it to make the product selectively available and to personalize prices. We find that firms’ preferred customers are low degree and high conspicuity, with the conspicuity threshold nondecreasing in degree. Interestingly, although both degree and conspicuity levels are relevant to curating the desired customer base, we find that firms do not need conspicuity information to do so; its absence can be substituted by incentivizing customers to self-select. There is no such recourse for the absence of degree information. As a result, degree information is typically more valuable than conspicuity information. Our analysis suggests that there are two canonical categories of social information—less valuable “consonant” information on characteristics where firm and customer preferences are aligned and more valuable “competing” information where preferences are misaligned. Customers can be incentivized to act in a way that their actions are a perfect substitute for consonant information, making it less valuable. This paper was accepted by Gad Allon, operations management.","PeriodicalId":330843,"journal":{"name":"PROD: Analytical (Supply) (Topic)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124611007","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":"Adding the Online-to-Store Channel to Supply Chain: Impact of Spillover Effect","authors":"Lin Chen, Guofang Nan, Minqiang Li, Yong Tan","doi":"10.2139/ssrn.3202600","DOIUrl":"https://doi.org/10.2139/ssrn.3202600","url":null,"abstract":"This paper investigates the impacts of an additional online-to-store channel and spillover effect on the optimal retail channel choice of a supply chain. In the presence of spillover effect, we discuss how the chosen retail channel affects the manufacturer’s profit, online retailer’s profit, and consumer surplus. Interestingly, our results reveal that there is an asymmetric effect of the online-to-store channel on the manufacturer and the retailer under spillover effect. Specifically, the retailer is better off adding the online-to-store channel if the spillover intensity is in the intermediate range, while the manufacturer is better off adding the channel if the spillover intensity is relatively high or low. Consequently, a win-win outcome for the retailer and the manufacturer will occur when adding the online-to-store channel under medium spillover intensity. We also show that the impact of online-to-store channel's introduction on consumer surplus depends on the spillover intensity. In particular, when the spillover intensity is at a moderate level, the consumer will gain more utility from buying through the online-to-store channel. Otherwise, the consumer will suffer a loss due to the online disutility cost. Overall, there is a win-win-win outcome for all channel members when the spillover intensity is not markedly positive or negative. Our findings offer valuable insights for managers and scholars by providing a better understanding of the joint functionality of online-to-store channel and spillover effect in retail channel management.","PeriodicalId":330843,"journal":{"name":"PROD: Analytical (Supply) (Topic)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121291598","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":"Influencing factors in Supply Chain Network - A comparative analysis of Fast-fashion and Automotive Industry","authors":"Danjie Shen","doi":"10.2139/ssrn.3905299","DOIUrl":"https://doi.org/10.2139/ssrn.3905299","url":null,"abstract":"A supply chain is the process that delivers a product or service from supplier to customer, which involves the movement of information and material flow from upstream to downstream. And supply chain management has been defined as “design, planning, execution, control and monitoring of supply chain activities with the objective of creating net value, building a competitive infrastructure, leveraging worldwide logistics, synchronizing supply with demand and measuring performance globally.”1 But supply chain network shows a bigger picture which involves interactions among organizations. The complexity is also increased as well in supply chain networks. In order to better manage supply chain, complexity drivers need to be defined and the impacts need to be analyzed.2 According to Serdarasan (2013)“ Studies on supply chain complexity mainly use the static and dynamic complexity distinction. While static complexity describes the structure of the supply chain, the number and the variety of its components and strengths of interactions between these; the dynamic complexity represents the uncertainty in the supply chain and involves the aspects of time and randomness.”3 In this paper I will mainly focus on defining the factors that lead to the complexity and analyzing their impact on the network structure. In order to better discovering the factors, I will compare and analyze actual company cases in two industries in which structures and characteristics differ the most in diverse aspects—Automotive and Fast-fashion industries.","PeriodicalId":330843,"journal":{"name":"PROD: Analytical (Supply) (Topic)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125785574","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":"Supplier Diversification Under Buyer Risk","authors":"J. Chod, Nikolaos Trichakis, Gerry Tsoukalas","doi":"10.2139/ssrn.3328249","DOIUrl":"https://doi.org/10.2139/ssrn.3328249","url":null,"abstract":"When should a firm diversify its supply base? Most extant theories attribute supplier diversification to supplier risk. Herein, we develop a new theory that attributes supplier diversification to b...","PeriodicalId":330843,"journal":{"name":"PROD: Analytical (Supply) (Topic)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132231391","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":"Collaborate or Compete: Examining Manufacturers' Replacement Strategies for a Substance of Concern","authors":"Tim Kraft, Gal Raz","doi":"10.2139/ssrn.2345884","DOIUrl":"https://doi.org/10.2139/ssrn.2345884","url":null,"abstract":"The recent proliferation of media reports on substances of concern has increased consumer fears, sparked scientific debate, and highlighted the need for stronger chemical regulations. When a substance of concern is identified (e.g., bisphenol-A (BPA) in reusable water bottles), manufacturers face difficult trade-offs in deciding whether to proactively replace the substance in their products or to defer replacement and wait to see if regulation occurs. In this paper, we model a vertically differentiated market consisting of a high-end manufacturer and a low-end manufacturer, both of whom sell a product that contains a substance of concern. We examine when opportunities exist for the manufacturers to avoid competing to replace the substance, and instead, share the cost to remove it from their products. Our analysis investigates how market dynamics (competition and consumer preferences) and external factors (replacement costs and regulatory uncertainty) influence manufacturers' collaboration, replacement, and pricing decisions. We find that when the manufacturers compete to replace a substance of concern, the high-end manufacturer can use the identification of the substance to maintain, and in some cases, increase his control of the market. Collaboration is possible when either the high-end manufacturer can use collaboration to further control the market or the low-end manufacturer can use it to better position himself in the market. There are, however, potential trade-offs in consumer benefit to the manufacturers working together. For example, although collaboration reduces consumers' exposure to the substance of concern, it can decrease consumer surplus when the replacement substance is particularly costly.","PeriodicalId":330843,"journal":{"name":"PROD: Analytical (Supply) (Topic)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114151810","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":"Modeling Multichannel Supply Chain Management with Marketing Mixes: A Survey","authors":"G. Cai, Yue Dai, Wenzhu Zhang","doi":"10.4337/9780857938602.00016","DOIUrl":"https://doi.org/10.4337/9780857938602.00016","url":null,"abstract":"This book chapter reviews the literature on multichannel supply chain management that uses marketing mixes. A multichannel supply chain includes at least two channels, at least one of which is a supply chain. This survey categorizes existing contributions according to three dimensions: channel architecture, marketing mixes, and supply chain mixes. This chapter also suggests some research directions.","PeriodicalId":330843,"journal":{"name":"PROD: Analytical (Supply) (Topic)","volume":"AES-21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126555732","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":"A General Multitiered Supply Chain Network Model of Quality Competition with Suppliers","authors":"Dong Li, A. Nagurney","doi":"10.2139/ssrn.2646906","DOIUrl":"https://doi.org/10.2139/ssrn.2646906","url":null,"abstract":"In this paper, we develop a general multitiered supply chain network equilibrium model consisting of competing suppliers and competing firms who purchase components for the assembly of their final branded products and, if capacity permits, and it enhances profits, produce their own components. The competitive behavior of each tier of decision-makers is described along with their strategic variables, which include quality of the components and, in the case of the firms, the quality of the assembly process itself. The governing equilibrium conditions of the supply chain network are formulated as a variational inequality and qualitative properties are presented. The algorithm, accompanied with convergence results, is then applied to numerical supply chain network examples, along with sensitivity analysis in which the impacts of capacity disruptions and complete supplier elimination are investigated.","PeriodicalId":330843,"journal":{"name":"PROD: Analytical (Supply) (Topic)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115913557","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":"Syngenta Uses a Cover Optimizer to Determine Production Volumes for Its European Seed Supply Chain","authors":"Peter Comhaire, Felix Papier","doi":"10.2139/ssrn.2533852","DOIUrl":"https://doi.org/10.2139/ssrn.2533852","url":null,"abstract":"The European seed business of Syngenta relies on its supply chain to supply seed products to the different European markets, which led to more than 1.2 billion USD revenues in 2013. The seed supply chain is, however, exposed to a high level of uncertainty – from the demand side as well as from the supply side. Determining optimal production volumes in a highly volatile environment and more than one year before the sales period is not only a complex business decision but also one which strongly affects the company’s profitability through lost sales and unsold supply. In order to better handle the production volume planning, Syngenta has developed a planning tool which determines optimal production volumes by taking the different levels of uncertainty into account. We report on this tool, the impact it has achieved, its integration into the planning process at Syngenta, and its technical design. In 2013, its first year of application, the production optimization tool has already avoided approximately 1.5 million USD in supply discards and has led Syngenta to revise the way how it handles uncertainty in its supply chain planning.","PeriodicalId":330843,"journal":{"name":"PROD: Analytical (Supply) (Topic)","volume":"128 1 Suppl 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131368869","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":"Spatial Price Equilibrium with Information Asymmetry in Quality and Minimum Quality Standards","authors":"A. Nagurney, Dong Li, L. Nagurney","doi":"10.2139/ssrn.2330891","DOIUrl":"https://doi.org/10.2139/ssrn.2330891","url":null,"abstract":"A spatial price equilibrium model with information asymmetry in quality is developed in both static and dynamic versions. Producers at the supply markets are aware of the quality of their products, whereas consumers, located at the demand markets, are aware only of the average quality of the products that are shipped to their demand markets. Minimum quality standards are also captured in order to assess the impacts of such policy interventions. We establish qualitative results, in the form of existence, uniqueness, and stability analysis. An algorithm is proposed, along with a convergence proof. It is then utilized to compute solutions to a spectrum of spatial price equilibrium numerical examples in order to explore the impacts of information asymmetry under different scenarios. The numerical examples, which are of quite general functional forms, reveal that, as the number of supply markets increases, the “anonymizing” effect leads to a decrease in the average quality. On the other hand, as the number of demand markets increases, the pressure to improve quality increases, and the average quality increases. Finally, we demonstrate that, after the imposition of minimum quality standards, the average quality at the demand markets increases and the prices also increase.","PeriodicalId":330843,"journal":{"name":"PROD: Analytical (Supply) (Topic)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116976464","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}