{"title":"Evaluation of the impact of strategic staff planning in a university using a MILP model","authors":"R. D. L. Torre, A. Lusa, M. Mateo","doi":"10.1504/EJIE.2017.084879","DOIUrl":null,"url":null,"abstract":"A mathematical model for optimising the strategic staff planning in universities is used to analyse the impact of different personnel and academic policies on the strategic staff plan, considering a preferable staff composition. The personnel policies are evaluated allowing or not the dismissals of permanent workers; the ratio of internal promotion for workers and the personnel budget. The academic policies are tested through the impact of different demand trends. Addressing the specificities of the university, the optimisation model considers not only economic criteria, i.e., personnel costs, but also other factors related to the fulfilment of the required service level and the achievement of a preferable workforce composition. Several computational scenarios are used, based on real data from the Universitat Politecnica de Catalunya (Barcelona, Spain). The results show the adjustment to the preferable workforce composition through the available mechanisms (dismissals, hiring and internal promotions). [Received 12 June 2015; Revised 24 November 2015; Revised 24 July 2016; Accepted 7 December 2016]","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":null,"pages":null},"PeriodicalIF":16.4000,"publicationDate":"2017-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2017.084879","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1504/EJIE.2017.084879","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 1
Abstract
A mathematical model for optimising the strategic staff planning in universities is used to analyse the impact of different personnel and academic policies on the strategic staff plan, considering a preferable staff composition. The personnel policies are evaluated allowing or not the dismissals of permanent workers; the ratio of internal promotion for workers and the personnel budget. The academic policies are tested through the impact of different demand trends. Addressing the specificities of the university, the optimisation model considers not only economic criteria, i.e., personnel costs, but also other factors related to the fulfilment of the required service level and the achievement of a preferable workforce composition. Several computational scenarios are used, based on real data from the Universitat Politecnica de Catalunya (Barcelona, Spain). The results show the adjustment to the preferable workforce composition through the available mechanisms (dismissals, hiring and internal promotions). [Received 12 June 2015; Revised 24 November 2015; Revised 24 July 2016; Accepted 7 December 2016]
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.