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Data-Driven 'Market Basket'-Pricing and Personalized Health Information Services Using Salesforce's Model-Driven Systems Service Design

  • Sunway University
  • Salesforce.com, Inc.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Citations (Scopus)

Abstract

Risk management and customer loyalty are increasingly critical. Being able to reduce risks through data-driven packaging and pricing and sustaining customer loyalty are therefore important. This study presents a case study on data-driven packaging (simulating market-basket analysis) and pricing to enable patients, and caregivers to obtain personalized health information services and for hospitals, knowledge sharing on marketing opportunities (who and what to target), which services should be paired with which, corresponding pricing and to predict based on past trends, resource allocation. Our personalized health information system, E-healthzone, builds on Salesforce's model-driven systems service design. It is currently a management information system but we hope to include intelligence eventually. Technology acceptance by sample users indicate positive acceptance. E-healthzone is perceived as useful especially if hospital fees are expensive, and quality and reasonably-priced services are preferred. Most users intend to use the system when it is released. Expert evaluations view the pricing and booking system and gaining insights through the analytics and dashboards as E-healthzone's greatest strengths.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2019
PublisherIEEE Computer Society
Pages576-580
Number of pages5
ISBN (Electronic)9781728138046
DOIs
Publication statusPublished - Dec 2019
Externally publishedYes
Event2019 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2019 - Macao, Macao
Duration: 15 Dec 2019 → 18 Dec 2019

Publication series

NameIEEE International Conference on Industrial Engineering and Engineering Management
ISSN (Print)2157-3611
ISSN (Electronic)2157-362X

Conference

Conference2019 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2019
Country/TerritoryMacao
CityMacao
Period15/12/19 → 18/12/19

Keywords

  • data-driven
  • model-driven systems service design
  • personalized health information services

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