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A Framework for Analyzing Operational Performance in Healthcare Industry


Affiliations
1 Research Scholar, Amity Business School, Amity University, Sector- 125, Noida, Uttar Pradesh, India
2 Assistant Professor, Business School, Amity University, Sector- 125, Noida, Uttar Pradesh, India

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The present paper focused on designing a framework to study the impact of Big Data analytics on service supply chain management and in turn improving operational performance. Different parameters for all the three major areas have been identified to study the impact on each other. First, for Big Data Analytics, different techniques for data collection, data reposition and data analysis were identified. For Service Chain Management, there are two types of Service Supply Chains i.e. Service Only Supply Chain and Product Service Supply chain. In the healthcare industry, Service Only Chain is applicable and therefore, it was analyzed. Also, the role of data analytics in performing different steps of service chain management namely, planning, sourcing, and delivery were studied and last, the impact on operational performance was analyzed by identifying three parameters for measuring operational performance namely Turn Around Time (TAT), Order Fill Rate (OFR), and Accuracy.

Keywords

Big Data Analytics, Operational Performance, Service Supply Chain Management

No Classification

Manuscript received July 5, 2017; revised September 3, 2017; accepted September 25, 2017. Date of publication November 6, 2017.

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  • A Framework for Analyzing Operational Performance in Healthcare Industry

Abstract Views: 297  |  PDF Views: 0

Authors

Bhawna Singh
Research Scholar, Amity Business School, Amity University, Sector- 125, Noida, Uttar Pradesh, India
Rushina Singhi
Assistant Professor, Business School, Amity University, Sector- 125, Noida, Uttar Pradesh, India

Abstract


The present paper focused on designing a framework to study the impact of Big Data analytics on service supply chain management and in turn improving operational performance. Different parameters for all the three major areas have been identified to study the impact on each other. First, for Big Data Analytics, different techniques for data collection, data reposition and data analysis were identified. For Service Chain Management, there are two types of Service Supply Chains i.e. Service Only Supply Chain and Product Service Supply chain. In the healthcare industry, Service Only Chain is applicable and therefore, it was analyzed. Also, the role of data analytics in performing different steps of service chain management namely, planning, sourcing, and delivery were studied and last, the impact on operational performance was analyzed by identifying three parameters for measuring operational performance namely Turn Around Time (TAT), Order Fill Rate (OFR), and Accuracy.

Keywords


Big Data Analytics, Operational Performance, Service Supply Chain Management

No Classification

Manuscript received July 5, 2017; revised September 3, 2017; accepted September 25, 2017. Date of publication November 6, 2017.




DOI: https://doi.org/10.17010/ijcs%2F2017%2Fv2%2Fi6%2F120442