Data-Driven Inventory Management in the Healthcare Supply Chain

2020 ◽  
pp. 1390-1403
Author(s):  
Shuojiang Xu ◽  
Kim Hua Tan
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Inventory Management ◽  
Data Driven ◽  
Forecasting Model ◽  
Market Demand ◽  
Improved Model ◽  
Future Work ◽  
Statistic Approach

From 21st century, enterprises combine supply chain management with big data to improve their products and services level. In China healthcare industry, supply chain decisions are made based on experience, due to the environment complexities, such as changing policies and license delay. A flexible and dynamic big data driven analysis approach for supply chain decisions is urgently required. This report demonstrates a case study on CRT forecasting model of inventory data to predict the market demand based on pervious transaction data. First a basic statistic approach has been applied to represent the superficial patterns and suggest some decisions. After that a CRT model has been built based on the several independent variables. And there is also a comparison between CRT and CHAID models to choose a better one to further build an improved model. Finally some limitations and future work have been proposed.

Data-Driven Inventory Management in the Healthcare Supply Chain

2017 ◽  
pp. 75-91
Author(s):  
Shuojiang Xu ◽  
Kim Hua Tan
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Inventory Management ◽  
Data Driven ◽  
Forecasting Model ◽  
Market Demand ◽  
Improved Model ◽  
Future Work ◽  
Statistic Approach

From 21st century, enterprises combine supply chain management with big data to improve their products and services level. In China healthcare industry, supply chain decisions are made based on experience, due to the environment complexities, such as changing policies and license delay. A flexible and dynamic big data driven analysis approach for supply chain decisions is urgently required. This report demonstrates a case study on CRT forecasting model of inventory data to predict the market demand based on pervious transaction data. First a basic statistic approach has been applied to represent the superficial patterns and suggest some decisions. After that a CRT model has been built based on the several independent variables. And there is also a comparison between CRT and CHAID models to choose a better one to further build an improved model. Finally some limitations and future work have been proposed.

A systematic literature review of healthcare supply chain and implications of future research

2019 ◽  
Vol 13 (4) ◽  
pp. 405-435 ◽  
Author(s):  
Anuj Dixit ◽  
Srikanta Routroy ◽  
Sunil Kumar Dubey
Keyword(s):  
Supply Chain ◽  
Literature Review ◽  
Inventory Management ◽  
Cold Chain ◽  
Future Research ◽  
Research Papers ◽  
Content Type ◽  
Drug Manufacturing ◽  
Customer Training

Purpose This paper aims to review the healthcare supply chain (HSC) literature along various areas and to find out the gap in it. Design/methodology/approach In total, 143 research papers were reviewed during 1996-2017. A critical review was carried out in various dimensions such as research methodologies/data collection method (empirical, case study and literature review) and inquiry mode of research methodology (qualitative, quantitative and mixed), country-specific, targeted area, research aim and year of publication. Findings Supply chain (SC) operations, performance measurement, inventory management, lean and agile operation, and use of information technology were well studied and analyzed, however, employee and customer training, tracking and visibility of medicines, cold chain management, human resource practices, risk management and waste management are felt to be important areas but not much attention were made in this direction. Research limitations/implications Mainly drug and vaccine SC were considered in current study of HSC while SC along healthcare equipment and machine, hospitality and drug manufacturing related papers were excluded in this study. Practical implications This literature review has recognized and analyzed various issues relevant to HSC and shows the direction for future research to develop an efficient and effective HSC. Originality/value The insight of various aspects of HSC was explored in general for better and deeper understanding of it for designing of an efficient and competent HSC. The outcomes of the study may form a basis to decide direction of future research.

Big data-driven supply chain and performance: a resource-based view

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shampy Kamboj ◽  
Shruti Rana
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Small And Medium Enterprises ◽  
Data Driven ◽  
Equation Modeling ◽  
Firm Age ◽  
Content Type ◽  
Sustainable Performance ◽  
Medium Enterprises

PurposeThe main objective of this paper is to study the role of supply chain performance (SCP) as a mediator between big data-driven supply chain (BDDSC) and firm sustainable performance. In addition, the role of firm age as a moderator between BDDSC and SCP as well as between SCP and firm sustainable performance has also been explored.Design/methodology/approachThe 200 managers of medium or senior level positions in micro, small and medium enterprises (MSMEs) located at Delhi-NCR have been contacted. Further, collected data have been confirmed with confirmatory factor analysis (CFA). In this paper, structure equation modeling (SEM) has been employed to empirically check the proposed hypotheses and their relationships.FindingsThe findings confirmed that SCP mediates the link between BDDSC and firm sustainable performance. Additionally, firm age moderates the association between BDDSC and SCP as well as between SCP and firm sustainable performance.Research limitations/implicationsThe role of SCP and firm age between BDDSC and sustainable performance have been examined in the context of MSMEs in Delhi-NCR and thereby limit the generalization of results to other industries and country contexts.Originality/valueThe present study adds to the existing literature via recognizing the blackbox using SCP and firm age to comprehend BDDSC and firm sustainable performance relationship.

Big Data Analytics in the Agribusiness Supply Chain Management

2021 ◽  
Vol 9 (3) ◽  
pp. 32-42
Author(s):  
Marisol Valencia-Cárdenas ◽  
Jorge Anibal Restrepo-Morales ◽  
Francisco Javier Día-Serna
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Structural Equation Model ◽  
Inventory Management ◽  
Latent Variables ◽  
Structural Equation ◽  
Big Data Analytics ◽  
Equation Model ◽  
Chain Management

Importance and impact of the systems related to Agribusiness and Agri-food, are increasing around the world and demand a paramount attention. Collaboration in the inventory management is an integral part of the supply chain management, related to proactive integration among the chain actors facilitating production and supply, in especial in the agroindustrial sector of the Departamento de Antioquia, Colombia. This research establishes the main relationships between latent variables as collaboration, technology, models, optimization and inventory management, based on a literature review and applying a Structural Equation Model to a survey data of a sample of agribusiness companies. The results show that Available Technologies associated with Big Data, generates improvement of Collaboration Strategies, improving also Forecasting and Optimization; besides, Inventory Planning and Collaboration are related to Available Technologies associated with Big Data. A Poisson regression model and a Structural Equation Model estimations detect that the increasing strategies of technologies and Big Data are favorable to apply collaboration in the supply chain management, increasing possibilities to the enterprise competitiveness.

scholarly journals Big Data Driven Agricultural Products Supply Chain Management: A Trustworthy Scheduling Optimization Approach

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 49990-50002 ◽  
Author(s):  
Qian Tao ◽  
Chunqin Gu ◽  
Zhenyu Wang ◽  
Joseph Rocchio ◽  
Weiwen Hu ◽  
...  
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Agricultural Products ◽  
Data Driven ◽  
Optimization Approach ◽  
Scheduling Optimization ◽  
Chain Management

Decision Support Tools for Managing Unpredictability in the Supply Chain

2000 ◽  
Author(s):  
Carol Vesier
Keyword(s):  
Supply Chain ◽  
Decision Support ◽  
Inventory Management ◽  
Production Scheduling ◽  
Capital Investment ◽  
Investment Strategy ◽  
Decision Support Tools ◽  
Business Outcomes ◽  
Support Tools

Abstract Effectively managing unpredictability requires decision support tools that can predict the financial and business outcomes of various supply chain strategies. This paper will discuss the role of these decision support tools and their characteristics as well as review a case study. In the case study, decision support tools facilitated development of strategies that increased after tax profit by $140 Million. These strategies included: • Reliability improvement strategy: Identifying the reliability improvements that offered the biggest profitability impact. • Supply chain strategy: Defining inventory management and production scheduling rules that ensured order shipment within two days. • Capital investment strategy: Defining when new capacity should come on line as well as the minimum capital investment.

Understanding the role of big data analytics for coordination of electronic retail service supply chain

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fatao Wang ◽  
Di Wu ◽  
Hongxin Yu ◽  
Huaxia Shen ◽  
Yuanjun Zhao
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Data Analysis ◽  
Big Data Analytics ◽  
Big Data Analysis ◽  
Coordination Mechanism ◽  
Market Demand ◽  
Content Type ◽  
Service Supply Chain ◽  
Retail Service

PurposeBased on the typical service supply chain (SSC) structure, the authors construct the model of e-tailing SSC to explore the coordination relationship in the supply chain, and big data analysis provides realistic possibilities for the creation of coordination mechanisms.Design/methodology/approachAt the present stage, the e-commerce companies have not yet established a mature SSC system and have not achieved good synergy with other members of the supply chain, the shortage of goods and the greater pressure of express logistics companies coexist. In the case of uncertain online shopping market demand, the authors employ newsboy model, applied in the operations research, to analyze the synergistic mechanism of SSC model.FindingsBy analyzing the e-tailing SSC coordination mechanism and adjusting relevant parameters, the authors find that the synergy mechanism can be implemented and optimized. Through numerical example analysis, the authors confirmed the feasibility of the above analysis.Originality/valueBig data analysis provides a kind of reality for the establishment of online SSC coordination mechanism. The establishment of an online supply chain coordination mechanism can effectively promote the efficient allocation of supplies and better meet consumers' needs.

Inventory Management, a Decision Support Framework to Improve Operational Performance

2012 ◽  
pp. 581-600
Author(s):  
Jan van den Berg ◽  
Guido van Heck ◽  
Mohsen Davarynejad ◽  
Ron van Duin
Keyword(s):  
Supply Chain ◽  
Decision Support ◽  
Inventory Management ◽  
Enterprise Resource Planning ◽  
Resource Planning ◽  
Performance Improvements ◽  
Decision Support Framework ◽  
Comparable Performance ◽  
Potential Benefits

Enterprise Resource Planning systems have been introduced to support the efficient and effective execution of business processes. In practice, this may not fully succeed. This also holds in particular for inventory management (IM), which forms a part of supply chain management. Within this research, by analyzing the IM business process theoretically, eleven potential benefits are indicated. Next, by using a Business Intelligence approach, key performance indicators (KPIs) are selected to measure the performance of IM sub-processes. Integration of these approaches yields an IM performance decision support framework that can be used to obtain a generic, coherent picture of the fundamental IM processes in an organization. In addition, by tracking and analyzing KPI measurements, adequate decisions can be prepared towards the improvement of the operational IM performance. The proposed framework is validated using experts’ opinions and a comparative case study. The experts’ comments yielded a list of top-10 KPIs, based on the measurements of which a set of quick wins can be determined. The case study results show that some of the identified potential benefits are also observed in practice. Future research may reveal that comparable performance improvements are possible in other IM environments (and even in other supply chain domains) based on similar decision support frameworks.

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