International journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN:2313-626X

Frequency: 12

line decor
  
line decor

 Volume 6, Issue 2 (February 2019), Pages: 6-11

----------------------------------------------

 Original Research Paper

 Title: How can the company choose the best web designer? Decision-making application within a company

 Author(s): Blanka Bazsova *

 Affiliation(s):

 Faculty of Economics, VSB – Technical University of Ostrava, Ostrava, Czech Republic

  Full Text - PDF          XML

 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0001-7056-896X

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2019.02.002

 Abstract:

The demand for web designers is currently increasing, and HR managers are looking for the most suitable candidates for this position. Consequently, HR departments need to thoroughly assess such job seekers in the admission process. The purpose of this paper is to help HR managers to identify criteria for best web designers and evaluate their relevance for the admission process. The admission process is based on a questionnaire, interview and tests. Generally, the role of HR manager is to summarize information from the Curriculum Vitae. The aim of this paper is to choose the criteria for the web designer position in the admission process and evaluate them according to the utility and risk. As a result, the best applicant for the position is chosen on the basis of a decision-making process which follows several assessment criteria. This process ensures an objective assessment of the main criteria among a number of choices. HR managers do not use these objective and quantitative methods, which evaluate the choices according to a set of criteria. Such an evaluation will shorten the time required to judge the appropriate candidate. Then the subsequent interview may be focused only on assessing the candidate´s social and managerial competencies. The most appropriate applicant is chosen according to the evaluation of seven main criteria defined in this article. 

 © 2019 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Criteria, Decision-making, Problem solving, Web designer

 Article History: Received 27 August 2018, Received in revised form 9 December 2018, Accepted 12 December 2018

 Acknowledgement:

This paper was supported within Operational Programme Education for Competitiveness – Project No. CZ. 1.07/2.3.00/20.0296 and SP2017/141.

 Compliance with ethical standards

 Conflict of interest:  The authors declare that they have no conflict of interest.

 Citation:

 Bazsova B (2019). How can the company choose the best web designer? Decision-making application within a company. International Journal of Advanced and Applied Sciences, 6(2): 6-11

 Permanent Link to this page

 Figures

 Fig. 1

 Tables

 Table 1 Table 2 Table 3 Table 4 Table 5 Table 6 Table 7 Table 8 Table 9 Table 10

----------------------------------------------

 References (26) 

Anderson DR, Sweeney DJ, and Williams TA (1988). Instructor's manual with solutions to accompany an introduction to management science: Quantitative approaches to decision making. West Publishing Company, Eagan, Minnesota, USA.   [Google Scholar]

Armstrong M (2006). A handbook of human resource management practice. Kogan Page Limited, London, UK.   [Google Scholar]

Castro-Nuño M and Arévalo-Quijada MT (2018). Assessing urban road safety through multidimensional indexes: Application of multicriteria decision making analysis to rank the Spanish provinces. Transport Policy, 68: 118-129. https://doi.org/10.1016/j.tranpol.2018.04.017   [Google Scholar]

Horita FE, de Albuquerque JP, and Marchezini V (2018). Understanding the decision-making process in disaster risk monitoring and early-warning: A case study within a control room in Brazil. International Journal of Disaster Risk Reduction, 28: 22-31. https://doi.org/10.1016/j.ijdrr.2018.01.034   [Google Scholar]

Charlesworth D (2017). Decision analysis for managers: A guide for making better personal and business decisions. Business Expert Press, New York, USA.   [Google Scholar]

Khan MI (2018). Evaluating the strategies of compressed natural gas industry using an integrated SWOT and MCDM approach. Journal of Cleaner Production, 172: 1035-1052. https://doi.org/10.1016/j.jclepro.2017.10.231   [Google Scholar]

Krulis J (2011). How to win over the risks. Active risk management – A tool for managing successful businesses. Linde, Prague, Czech Republic.   [Google Scholar]

Ministr J (2013). The influence of human resources on the IT service management. In the 35th International Conference on Information Technology Interfaces (ITI), IEEE, Cavtat, Croatia: 323-328.   [Google Scholar]

Pineda PJG, Liou JJ, Hsu CC, and Chuang YC (2018). An integrated MCDM model for improving airline operational and financial performance. Journal of Air Transport Management, 68: 103-117. https://doi.org/10.1016/j.jairtraman.2017.06.003   [Google Scholar]

Purcarea A, Popescu M, and Gheorghe S (2017). Online platforms- method of promoting an IT company through social media. In the 25th Interdisciplinary Information Management Talks Confrence in Digitalization in Management, Society and Economy, Trauner Verlag Universität, Poděbrady, Czech Republic: 201-208.   [Google Scholar] PMid:29362593 PMCid:PMC5771248

Řeháček P (2015). Organization forms for project management. In the 25th International Business Information Management Association Conference, IBIMA, Amsterdam, Netherlands: 2092-2101.   [Google Scholar]

Řeháček P (2018). Risk management standards for P5M. Journal of Engineering Science and Technology, 13(1): 11-34.   [Google Scholar]

Saaty T and Vargas L (2001). Models, methods, concepts and applications of the analytic hierarchy process. Kluwer Academic Publishers, Boston, Massachusetts, USA. https://doi.org/10.1007/978-1-4615-1665-1   [Google Scholar]

Zaman UK, Rivette M, Siadat A, and Mousavi SM (2018). Integrated product-process design: Material and manufacturing process selection for additive manufacturing using multi-criteria decision making. Robotics and Computer-Integrated Manufacturing, 51: 169-180. https://doi.org/10.1016/j.rcim.2017.12.005   [Google Scholar]