IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Exploring Key Success Factors of Indian Pharmaceutical Supply Chain Using Interpretive Structural Modelling

Exploring Key Success Factors of Indian Pharmaceutical Supply Chain Using Interpretive Structural Modelling
View Sample PDF
Author(s): Anurag Mishra (Indian Institute of Technology, Bombay, India), Pankaj Dutta (Indian Institute of Technology, Bombay, India)and Suruj Kakoti (Indian Institute of Technology, Bombay, India)
Copyright: 2020
Pages: 16
Source title: Multi-Criteria Decision Analysis in Management
Source Author(s)/Editor(s): Abhishek Behl (Indian Institute of Technology, Bombay, India)
DOI: 10.4018/978-1-7998-2216-5.ch003

Purchase

View Exploring Key Success Factors of Indian Pharmaceutical Supply Chain Using Interpretive Structural Modelling on the publisher's website for pricing and purchasing information.

Abstract

Indian pharmaceutical industry is witnessing enormous challenges due to varying patent laws, increasing demand, and continuous pressure from the government to provide medicines at a lower price. To overcome these challenges, there is a need for a more robust supply chain (SC) which will help in information sharing and reduce overall cost. The chapter determines the key drivers of Indian pharmaceutical SC, and draws the attention of industry, stakeholders, and top management to emphasise on these drivers to enhance the performance and profitability of SC. An interpretive structural modelling-based approach has been employed to model the pharmaceutical SC key drivers. The 16 key parameters have been identified across all major dimensions such as SC, HR, & organizational, market, technology, and reverse logistics. Further fuzzy MICMAC analysis is done to categorize based on their driving and dependence power. The factors like collaborative relationship among SC partners, quality regulations, third party logistics, and end-to-end responsive SC are found to be more important enablers.

Related Content

Yu Bin, Xiao Zeyu, Dai Yinglong. © 2024. 34 pages.
Liyin Wang, Yuting Cheng, Xueqing Fan, Anna Wang, Hansen Zhao. © 2024. 21 pages.
Tao Zhang, Zaifa Xue, Zesheng Huo. © 2024. 32 pages.
Dharmesh Dhabliya, Vivek Veeraiah, Sukhvinder Singh Dari, Jambi Ratna Raja Kumar, Ritika Dhabliya, Sabyasachi Pramanik, Ankur Gupta. © 2024. 22 pages.
Yi Xu. © 2024. 37 pages.
Chunmao Jiang. © 2024. 22 pages.
Hatice Kübra Özensel, Burak Efe. © 2024. 23 pages.
Body Bottom