A big data approach to assessing the US higher education service

Robin G. Qiu, Zuqing Huang, Iswar C. Patel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

There are a number of ranking systems to provide assessment services on higher education regionally, nationally, or internationally. Note that the subjective evaluation index and indicator inclusions and weights that are usually applied in current ranking systems. As a result, the question of the objectivity and impartiality of the provided rankings arises. One of our studies addressed these concerns by applying a quantitative and model-driven approach to acquiring the evaluation index and factor weights, which was successfully validated in the US News & World Report ranking system [1]. To extend our earlier study, this paper further shows a very interesting result by developing a real-time, scalable, and model-driven higher education ranking system with the support of big data technologies. This extended study reveals promising potential in enhancing varieties of applications across the service industry.

Original languageEnglish (US)
Title of host publication2015 12th International Conference on Service Systems and Service Management, ICSSSM 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479983285
DOIs
StatePublished - Jul 28 2015
Event12th International Conference on Service Systems and Service Management, ICSSSM 2015 - Guangzhou, China
Duration: Jun 22 2015Jun 24 2015

Publication series

Name2015 12th International Conference on Service Systems and Service Management, ICSSSM 2015

Other

Other12th International Conference on Service Systems and Service Management, ICSSSM 2015
CountryChina
CityGuangzhou
Period6/22/156/24/15

All Science Journal Classification (ASJC) codes

  • Business and International Management
  • Strategy and Management
  • Management Science and Operations Research
  • Transportation

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