EconPapers    
Economics at your fingertips  
 

Operation Architecture Planning Method of Information System and Person-Job Fit Application

Ai Wang () and Xuedong Gao ()
Additional contact information
Ai Wang: University of Science and Technology Beijing
Xuedong Gao: University of Science and Technology Beijing

A chapter in LISS 2021, 2022, pp 311-320 from Springer

Abstract: Abstract Constructing the analytical information system that has the capacity to integrate enterprises’ multiple business systems is embracing a fierce demand especially. This paper studies the operation architecture planning problem for building information system. Firstly, the multi-scale data processing subjects-skills matrix model of information system is established to describe the connection between operating job and skills requirement. Then, the multi-scale skills similarity indicator is proposed to measure whether an employee’s skills are fit for the job responsibilities. Finally, a skills-matched operation jobs establishment method for information system (SMOJs) is put forward. The numerical experiments in the context of the state-owned steel trade enterprise in China verify the effectiveness and practical value of our proposed method.

Keywords: Operation architecture planning; Multi-scale data model; Person-job fit; Information system planning; Job discovery technique (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-981-16-8656-6_29

Ordering information: This item can be ordered from
http://www.springer.com/9789811686566

DOI: 10.1007/978-981-16-8656-6_29

Access Statistics for this chapter

More chapters in Lecture Notes in Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-04-01
Handle: RePEc:spr:lnopch:978-981-16-8656-6_29