Network evolution model for supply chain with manufactures as the core.
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ABSTRACT:
SUBMITTER: Fang H
PROVIDER: S-EPMC5784947 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Previous researches for understanding supply chain relationship have mostly focused on its vertical collaboration between buyers and suppliers. However, there have been some instances of volatile and stable collaborative relationships amongst competitors such as Apple-Samsung product manufacturer-component supplier relationship and airline alliances, respectively, which is recognized as coopetition. Even though there have been several qualitative studies and a number of game theory models on coopetition, it is rare to find any attempts on quantitative characterization of such coopetitive dynamic behavior in supply chain relationship. Hence, in this work, we formulated a MINLP model mathematically representing coopetitive relationships in a cost efficient supply chain network. In particular, the coopetition factor was newly introduced to measure the degree of coopetition among supply chain players and determine the optimal level of coopetition to engage in. The utility and practicality of the model were strongly demonstrated using a case study of a hypothetical smartphone supply chain network under different scenarios, thus proposing their strategically viable optimal interactions. Therefore, this exploratory study can herald a new era of global coopetitive business.
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Project description:World Health Organization (WHO) declared COVID-19 as a pandemic On March 12, 2020. Up to January 13, 2022, 320,944,953 cases of infection and 5,539,160 deaths have been reported worldwide. COVID-19 has negatively impacted the blood supply chain by drastically reducing blood donation. Therefore, developing models to design effective blood supply chains in emergencies is essential. This research offers a novel multi-objective Transportation-Location-Inventory-Routing (TLIR) formulation for an emergency blood supply chain network design problem. We answer questions regarding strategic, operational, and tactical decisions considering disruption in the network and blood shelf-life. Since, in real-world applications, the parameters of the proposed mathematical formulation are uncertain, two flexible uncertain models are proposed to provide risk-averse and robust solutions for the problem. We applied the proposed formulations in a case study. Under various scenarios and realizations, we show that the offered robust model handles uncertainties more efficiently and finds solutions that have significantly lower costs and delivery time. To make a reliable conclusion, we performed extensive worst-case analyses to demonstrate the robustness of the results. In the end, we provide critical managerial insights to enhance the effectiveness of the supply chain.Supplementary informationThe online version contains supplementary material available at 10.1007/s10479-022-04673-9.
| S-EPMC9022900 | biostudies-literature
Project description:In this paper, we study the topological properties of the global supply chain network in terms of its degree distribution, clustering coefficient, degree-degree correlation, bow-tie structure, and community structure to test the efficient supply chain propositions proposed by E. J.S. Hearnshaw et al. The global supply chain data in the year 2017 are constructed by collecting various company data from the web site of Standard & Poor's Capital IQ platform. The in- and out-degree distributions are characterized by a power law of the form of γin = 2.42 and γout = 2.11. The clustering coefficient decays [Formula: see text] with an exponent βk = 0.46. The nodal degree-degree correlations 〈knn(k)〉 indicates the absence of assortativity. The bow-tie structure of giant weakly connected component (GWCC) reveals that the OUT component is the largest and consists 41.1% of all firms. The giant strong connected component (GSCC) is comprised of 16.4% of all firms. We observe that upstream or downstream firms are located a few steps away from the GSCC. Furthermore, we uncover the community structures of the network and characterize them according to their location and industry classification. We observe that the largest community consists of the consumer discretionary sector based mainly in the United States (US). These firms belong to the OUT component in the bow-tie structure of the global supply chain network. Finally, we confirm the validity of Hearnshaw et al.'s efficient supply chain propositions, namely Proposition S1 (short path length), Proposition S2 (power-law degree distribution), Proposition S3 (high clustering coefficient), Proposition S4 ("fit-gets-richer" growth mechanism), Proposition S5 (truncation of power-law degree distribution), and Proposition S7 (community structure with overlapping boundaries) regarding the global supply chain network. While the original propositions S1 just mentioned a short path length, we found the short path from the GSCC to IN and OUT by analyzing the bow-tie structure. Therefore, the short path length in the bow-tie structure is a conceptual addition to the original propositions of Hearnshaw.
| S-EPMC7529254 | biostudies-literature
Project description:One major issue in pharmaceutical supply chain management is the supply shortage, and determining the root causes of medicine shortages necessitates an in-depth investigation. The concept of risk management is proposed in this study to identify significant risk factors in the pharmaceutical supply chain. Fuzzy failure mode and effect analysis and data envelopment analysis were used to evaluate the risks of the pharmaceutical supply chain. Based on a case study on the Malaysian pharmaceutical supply chain, it reveals that the pharmacy node is the riskiest link. The unavailability of medicine due to unexpected demand, as well as the scarcity of specialty or substitute drugs, pose the most significant risk factors. These risks could be mitigated by digital technology. We propose an appropriate digital technology platform consisting of big data analytics and blockchain technologies to undertake these challenges of supply shortage. By addressing risk factors through the implementation of a digitalized supply chain, organizations can fortify their supply networks, fostering resilience and efficiency, and thereby playing a pivotal role in advancing the Pharma 4.0 era.
| S-EPMC10721629 | biostudies-literature
Project description:The COVID-19 crisis has notably impacted global supply chains as it has disrupted manufacturing operations. To recover from the aforementioned disruptions, supply chain digitalization [SCD] is increasingly being acknowledged to help the recovery process. Based on this, scholars have called for additional research on how SCD can enhance supply chain visibility [SCV] and boost supply chain performance [SCP] in turbulent environments. Based on 399 valid responses collected through cross-sectional method from Turkish manufacturing firms and using a non-probabilistic sampling method [i.e., purposive sampling], this research explores the effect of SCD on SCP. The mediating role of SCV and the moderating role of supply chain survivability [SCS] on the SCD-SCP relationship were also explored. The findings showed that SCD has a positive effect on SCP. SCD has a positive effect on SCV. SCV has a positive effect on SCP. The link between SCD and SCP is mediated by SCP. The results also revealed that SCS moderated the SCD-SCV link such that SCD has a stronger, positive relationship with SCV when SCS is high than when it's low. SCS moderates the SCD-SCP link, such that at low levels of SCS, the positive effect of SCD on SCP is weakened. The indirect positive effect of SCD on SCP via SCV is strongest when supply chain survivability is high. The findings suggest that SCD can improve cost-effectiveness, promote communication and information efficiency, and enhance supply chain resilience to improve performance after disruptions. This study provides insightful new implications for both supply chain literature and practitioners.
| S-EPMC10881317 | biostudies-literature
Project description:BackgroundCriPec technology enables the generation of drug-entrapped biodegradable core-crosslinked polymeric micelles (CCPM) with high drug loading capacity, tailorable size, and drug release kinetics. Docetaxel (DTX)-entrapped CCPM, also referred to as CPC634, have demonstrated favorable pharmacokinetics, tolerability, and enhanced tumor uptake in patients. Clinical efficacy evaluation is ongoing. CPC634 is currently stored (shelf life > 5 years) and shipped as a frozen aqueous dispersion at temperatures below -60°C, in order to prevent premature release of DTX and hydrolysis of the core-crosslinks. Consequently, like other aqueous nanomedicine formulations, CPC634 relies on cold chain supply, which is unfavorable for commercialization. Lyophilization can help to bypass this issue.Methods and resultsFreeze-drying methodology for CCPM was developed by employing CPC634 as a model formulation, and sucrose and trehalose as cryoprotectants. We studied the residual moisture content and reconstitution behavior of the CPC634 freeze-dried cake, as well as the size, polydispersity index, morphology, drug retention, and release kinetics of reconstituted CPC634. Subsequently, the freeze-drying methodology was validated in an industrial setting, yielding a CPC634 freeze-dried cake with a moisture content of less than 0.1 wt%. It was found that trehalose-cryoprotected CPC634 could be rapidly reconstituted in less than 5 min at room temperature. Critical quality attributes such as size, morphology, drug retention, and release kinetics of trehalose-cryoprotected freeze-dried CPC634 upon reconstitution were identical to those of non-freeze-dried CPC634.ConclusionOur findings provide proof-of-concept for the lyophilization of drug-containing CCPM and our methodology is readily translatable to large-scale manufacturing for future commercialization.
| S-EPMC7611944 | biostudies-literature
Project description:This article presents the multilayered complex network formulation for three different supply chain network archetypes on an urban road grid and describes how 500 instances were randomly generated for each archetype. Both the supply chain network layer and the urban road network layer are directed unweighted networks. The shortest path set is calculated for each of the 1 500 experimental instances. The datasets are used to empirically explore the impact that the supply chain's dependence on the transport network has on its vulnerability in Viljoen and Joubert (2017) [1]. The datasets are publicly available on Mendeley (Joubert and Viljoen, 2017) [2].
| S-EPMC5767570 | biostudies-literature
Project description:To better prevent the potential risks in Internet-based Supply Chain Financing (SCF) products, this paper optimizes and evaluates the Internet-based SCF-oriented Credit Risk Evaluation (CRE) method. Firstly, this paper summarizes 12 risk factors of SCF business, establishes a Risk Assessment Index System (RAIS) with good consistency and stability; then, the principles of Backpropagation (BP) Neural Network (NN) is expounded together with Support Vector Machines (SVM) and Genetic Algorithm (GA) model. Consequently, a CRE model is implemented by the NN tools in MATLAB based on the collection of multiple groups of SCF-oriented risk assessment samples. Subsequently, the assessment samples are trained and tested. Finally, the SCF-oriented CRE model is proposed and verified. The results show that the BP-GA model has presented high prediction consistency with the actual classification. According to the comparison of classification results of SVM, BP model, and BP-GA model, the classification accuracy of test samples of the proposed Internet-based SCF-oriented CRE system using BP-GA model reaches 97.19%; the Type I and Type II error rate of the CRE system based on BP-GA model is 7.2% and 14.21%, respectively. Therefore, a suitable SCF-oriented CRE method is put forward for China's commercial banks along with scientific and feasible suggestions to manage SCF-oriented credit risks more reasonably and effectively.
| S-EPMC8782329 | biostudies-literature
Project description:Over the past few years, academics and practitioners have started paying more attention to analyze and understand value creation and business models from a business ecosystem perspective. Such business ecosystems have been constructed based on the connected networks of people, firms, industries, and countries. Developing strategies to help sustain the firms’ competitive advantage in business ecosystems is a key challenge for businesses and policymakers worldwide. Recent disruptions to global supply chains due to the COVID-19 pandemic have exposed the high risk and challenges of managing sustainable global and intertwined supply chain networks. Using the data mined from financial records, the present study constructs the global supply chain network of the auto manufacturing sector. The data from 32,396 notable first-tier forward and backward supply chain connections were mined to build the global supply chain network in this sector. The global supply chain network structure was analyzed using centrality measures and clustering analysis. We utilized path analysis to explore the effect of various supply chain centrality measures on firms' financial performance, investment risk, and market value volatility. The findings provide new insight into our understanding of the relationship between the firm's location characteristics in the global supply chain ecosystem and various aspects of the asset's performance. Furthermore, discussions are presented about strategies that support sustainable collaborative value creation and sustainable competitiveness of businesses across the global manufacturing ecosystems. The research method used in this study has the potential to be applied to several industries. Supplementary Information The online version contains supplementary material available at 10.1007/s42943-021-00026-8.
| S-EPMC8220882 | biostudies-literature
Project description:http://www.sanger.ac.uk/resources/downloads/bacteria/streptococcus-suis.htmlThese data are part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/
2014-04-28 | E-ERAD-241 | biostudies-arrayexpress