Performance Evaluation Framework under the Influence of Industry 4.0: The Case of the Czech Manufacturing Industry

dc.contributor.authorHedvičáková, Martina
dc.contributor.authorKrál, Martin
dc.contributor.otherEkonomická fakultacs
dc.date.accessioned2021-03-16T10:51:27Z
dc.date.available2021-03-16T10:51:27Z
dc.description.abstractThe current economic situation creates general pressure to increase performance. Any inefficient use of production factors will lead to problems and long-term economic unsustainability in many industries. The effects of the Covid-19 pandemic will also have a negative impact on all sectors of the economy and the faster onset of the fourth industrial revolution. The article, therefore, proposes a new framework for the performance evaluation of the manufacturing industry, which is based on the composite performance indicator. This indicator is obtained by a cross-sectoral comparison of all sub-key performance indicators. Using cluster analysis and analysis of variance, a total of 6 indicators to evaluate performance in the manufacturing industry were selected as statistically significant. The added value of the whole concept is its direct independence on the economic situation, which eliminates short-term economic oscillations that would be reflected in classical methods of performance evaluation otherwise. The results show that some industries are more efficient in the long run due to their effective investments in the capital, which replaces the labour factor and creates room for the realization of relatively higher profits. By contrast, some sectors, despite high investments, do not achieve the desired level of performance – these investments are not efficient or they are complementary to the labour factor, thus denying the principles of Industry 4.0. It thus creates preconditions for increasing dependence on external factors and, at the same time, makes the given sectors in a freely competitive environment economically unsustainable in the long run.en
dc.formattext
dc.identifier.doi10.15240/tul/001/2021-1-008
dc.identifier.eissn2336-5604
dc.identifier.issn1212-3609
dc.identifier.urihttps://dspace.tul.cz/handle/15240/159933
dc.language.isoen
dc.publisherTechnická Univerzita v Libercics
dc.publisherTechnical university of Liberec, Czech Republicen
dc.publisher.abbreviationTUL
dc.relation.isbasedonAli, A. I., & Nakosteen, R. (2005). Ranking industry performance in the US. Socio-Economic Planning Sciences, 39(1), 11–24. https://doi.org/10.1016/j.seps.2003.10.003
dc.relation.isbasedonAl-Tmeemy, S. M. H. M., Abdul-Rahman, H., & Harun, Z. (2011). Future criteria for success of building projects in Malaysia. International Journal of Project Management, 29(3), 337–348. https://doi.org/10.1016/j.ijproman.2010.03.003
dc.relation.isbasedonAmrina, E., & Yusof, S. M. (2011). Key performance indicators for sustainable manufacturing evaluation in automotive companies. In Proceeding of the 2011 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1093–1097). Singapore. https://doi.org/10.1109/IEEM.2011.6118084
dc.relation.isbasedonAsmalovskij, A., Sadílek, T., Hinčica, V., & Mizerová, M. (2019). Performance of Social Enterprises in the Czech Republic. Journal of Social Entrepreneurship, 10(1), 19–29. https://doi.org/10.1080/19420676.2018.1521865
dc.relation.isbasedonAssociation of Small and Medium-sized Enterprises and Self-employed Persons of the Czech Republic. (2019). Analýza průmyslu 2019 – Asociace malých a středních podniků. https://amsp.cz/vyplati-se-malym-a-strednim-podnikum-digitalizovat-vyrobu-2/
dc.relation.isbasedonBoďa, M., & Úradníček, V. (2020). Methodology of Industry Statistics: Averages, Quantiles and Responses to Atypical Value. E&M Economics and Management, 23(3), 120–137. https://doi.org/10.15240/tul/001/2020-3-008
dc.relation.isbasedonBraz, R. G. F., Scavarda, L. F., & Martins, R. A. (2011). Reviewing and improving performance measurement systems: An action research. International Journal of Production Economics, 133(2), 751–760. https://doi.org/10.1016/j.ijpe.2011.06.003
dc.relation.isbasedonChan, A. P. C., & Chan, A. P. L. (2004). Key performance indicators for measuring construction success. Benchmarking: An International Journal, 11(2), 203–221. https://doi.org/10.1108/14635770410532624
dc.relation.isbasedonChan, A. P. C., Scott, D., & Chan, A. P. L. (2004). Factors Affecting the Success of a Construction Project. Journal of Construction Engineering and Management, 130(1), 153–155. https://doi.org/10.1061/(ASCE)0733-9364(2004)130:1(153)
dc.relation.isbasedonCheung, S. O., Suen, H. C. H., & Cheung, K. K. W. (2004). PPMS: A Web-based construction Project Performance Monitoring System. Automation in Construction, 13(3), 361–376. https://doi.org/10.1016/j.autcon.2003.12.001
dc.relation.isbasedonCzech Statistical Office. (2019). 293/2019 Sb Decree on the Program of Statistical Surveys for 2020. Prague: Czech Statistical Office.
dc.relation.isbasedonEurofond. (2020). Industrial relations index. Eurofond. https://www.eurofound.europa.eu/data/Industrial-relations-index?period=2013-2017&breakdown=index&mode=all&country=all
dc.relation.isbasedonFalle, S., Rauter, R., Engert, S., & Baumgartner, R. (2016). Sustainability Management with the Sustainability Balanced Scorecard in SMEs: Findings from an Austrian Case Study. Sustainability, 8(6), 545. https://doi.org/10.3390/su8060545
dc.relation.isbasedonFerreira, L. M. D. F., Silva, C., & Azevedo, S. G. (2016). An environmental balanced scorecard for supply chain performance measurement (Env_BSC_4_SCPM). Benchmarking: An International Journal, 23(6), 1398–1422. https://doi.org/10.1108/BIJ-08-2013-0087
dc.relation.isbasedonFlynn, J., Dance, S., & Schaefer, D. (2017). Industry 4.0 and Its Potential Impact on Employment Demographics in the UK. In J. Gao, M. E. Souri, & S. Keates (Eds.), Advances in Manufacturing Technology XXXI: Proceedings of the 15th International Conference on Manufacturing Research, incorporating the 32nd National Conference on Manufacturing Research, September 5–7, 2017, University of Greenwich, UK. Amsterdam: IOS Press.
dc.relation.isbasedonFranceschini, F., Galetto, M., & Maisano, D. (2007). Management by Measurement Designing Key Indicators and Performance Measurement Systems. http://www.vlebooks.com/vleweb/product/openreader?id=none&isbn=9783540732129
dc.relation.isbasedonGloberson, S. (1985). Issues in developing a performance criteria system for an organization. International Journal of Production Research, 23(4), 639–646. https://doi.org/10.1080/00207548508904734
dc.relation.isbasedonGraham, I., Goodall, P., Peng, Y., Palmer, C., West, A., Conway, P., Mascolo, J. E., & Dettmer, F. U. (2015). Performance measurement and KPIs for remanufacturing. Journal of Remanufacturing, 5(1), 10. https://doi.org/10.1186/s13243-015-0019-2
dc.relation.isbasedonGuerola-Navarro, V., Oltra-Badenes, R., Gil-Gomez, H., & Gil-Gomez, J. A. (2020). Research model for measuring the impact of customer relationship management (CRM) on performance indicators. Economic Research – Ekonomska Istraživanja, 1–23. https://doi.org/10.1080/1331677X.2020.1836992
dc.relation.isbasedonHálek, V., Borkovcová, A., & Hašek, F. (2020). Non-financial Indicators in the Valuation Process – Actual Trends. E&M Economics and Management, 23(1), 60–74. https://doi.org/10.15240/tul/001/2020-1-005
dc.relation.isbasedonHedvičáková, M., & Král, M. (2019). Benefits of KPIs for Industry Sector Evaluation: The Case Study from the Czech Republic. E&M Economics and Management, 22(2), 97–113. https://doi.org/10.15240/tul/001/2019-2-007
dc.relation.isbasedonHope, J., & Fraser, R. (2003). Beyond budgeting: How managers can break free from the annual performance trap. Brighton, MA: Harvard Business School Press.
dc.relation.isbasedonHristov, I., & Chirico, A. (2019). The Role of Sustainability Key Performance Indicators (KPIs) in Implementing Sustainable Strategies. Sustainability, 11(20), 5742. https://doi.org/10.3390/su11205742
dc.relation.isbasedonHristov, I., Chirico, A., & Appolloni, A. (2019). Sustainability Value Creation, Survival, and Growth of the Company: A Critical Perspective in the Sustainability Balanced Scorecard (SBSC). Sustainability, 11(7), 2119. https://doi.org/10.3390/su11072119
dc.relation.isbasedonHsu, C.-H., Chang, A.-Y., & Luo, W. (2017). Identifying key performance factors for sustainability development of SMEs – integrating QFD and fuzzy MADM methods. Journal of Cleaner Production, 161, 629–645. https://doi.org/10.1016/j.jclepro.2017.05.063
dc.relation.isbasedonHuff, R. F. (2011). Measuring Performance in US Municipalities: Do Personnel Policies Predict System Level Outcomes? Journal of Comparative Policy Analysis: Research and Practice, 13(1), 11–33. https://doi.org/10.1080/13876988.2011.538535
dc.relation.isbasedonJahangirian, M., Taylor, S. J. E., Young, T., & Robinson, S. (2017). Key performance indicators for successful simulation projects. Journal of the Operational Research Society, 68(7), 747–765. https://doi.org/10.1057/jors.2016.1
dc.relation.isbasedonKang, N., Zhao, C., Li, J., & Horst, J. A. (2016). A Hierarchical structure of key performance indicators for operation management and continuous improvement in production systems. International Journal of Production Research, 54(21), 6333–6350. https://doi.org/10.1080/00207543.2015.1136082
dc.relation.isbasedonKaplan, R. S., & Norton, D. P. (1992). The Balanced Scorecard – Measures that Drive Performance. Harvard Business Review, 1992(70), 71–79.
dc.relation.isbasedonKarl, A. A., Micheluzzi, J., Leite, L. R., & Pereira, C. R. (2018). Supply chain resilience and key performance indicators: A systematic literature review. Production, 28, e20180020. https://doi.org/10.1590/0103-6513.20180020
dc.relation.isbasedonKumaraswamy, M., Mahesh, G., Mahalingam, A., Loganathan, S., & Kalidindi, S. N. (2017). Developing a clients’ charter and construction project KPIs to direct and drive industry improvements. Built Environment Project and Asset Management, 7(3), 253–270. https://doi.org/10.1108/BEPAM-02-2017-0013
dc.relation.isbasedonLam, E. W. M., Chan, A. P. C., & Chan, D. W. M. (2007). Benchmarking the performance of design‐build projects: Development of project success index. Benchmarking: An International Journal, 14(5), 624–638. https://doi.org/10.1108/14635770710819290
dc.relation.isbasedonLindberg, C.-F., Tan, S., Yan, J., & Starfelt, F. (2015). Key Performance Indicators Improve Industrial Performance. Energy Procedia, 75, 1785–1790. https://doi.org/10.1016/j.egypro.2015.07.474
dc.relation.isbasedonLuu, V. T., Kim, S.-Y., & Huynh, T.-A. (2008). Improving project management performance of large contractors using benchmarking approach. International Journal of Project Management, 26(7), 758–769. https://doi.org/10.1016/j.ijproman.2007.10.002
dc.relation.isbasedonMaresova, P., Soukal, I., Svobodova, L., Hedvicakova, M., Javanmardi, E., Selamat, A., & Krejcar, O. (2018). Consequences of Industry 4.0 in Business and Economics. Economies, 6(3), 46. https://doi.org/10.3390/economies6030046
dc.relation.isbasedonNeely, A., Gregory, M., & Platts, K. (1995). Performance measurement system design: A literature review and research agenda. International Journal of Operations & Production Management, 15(4), 80–116. https://doi.org/10.1108/01443579510083622
dc.relation.isbasedonParmenter, D. (2015). Key performance indicators: Developing, implementing, and using winning KPIs (3rd ed.). Hoboken, NJ: Wiley.
dc.relation.isbasedonPavelková, D., Homolka, L., Knápková, A., Kolman, K., & Pham, H. (2018). EVA and Key Performance Indicators: The Case of Automotive Sector in Pre-Crisis, Crisis and Post-Crisis Periods. Economics & Sociology, 11(3), 78–95. https://doi.org/10.14254/2071-789X.2018/11-3/5
dc.relation.isbasedonPeral, J., Maté, A., & Marco, M. (2017). Application of Data Mining techniques to identify relevant Key Performance Indicators. Computer Standards & Interfaces, 50, 55–64. https://doi.org/10.1016/j.csi.2016.09.009
dc.relation.isbasedonPeruzzini, M., Grandi, F., & Pellicciari, M. (2017). Benchmarking of Tools for User Experience Analysis in Industry 4.0. Procedia Manufacturing, 11, 806–813. https://doi.org/10.1016/j.promfg.2017.07.182
dc.relation.isbasedonPriceWaterhouseCoopers. (2007). Guide to key performance indicators – Communicating the measures that matter. 2007. https://www.academia.edu/10347249/Guide_to_key_performance_indicators_Communicating_the_measures_that_matter_connectedthinking_pwc
dc.relation.isbasedonRajnoha, R., Lesníková, P., & Krajčík, V. (2017). Influence of business performance measurement systems and corporate sustainability concept to overal business performance: “Save the planet and keep your performance”. E&M Economics and Management, 20(1), 111–128. https://doi.org/10.15240/tul/001/2017-1-008
dc.relation.isbasedonRaynsford, N. (2000). KPI Report for The Minister for Construction by the KPI Working Group. KPI Working Group. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/16323/file16441.pdf
dc.relation.isbasedonRobbins, G., Turley, G., & McNena, S. (2016). Benchmarking the financial performance of local councils in Ireland. Administration, 64(1), 1–27. https://doi.org/10.1515/admin-2016-0009
dc.relation.isbasedonSorovou, C., Politou, D., Kalligeris, A., & Topouzidou, S. (2001). D3-KPI Manual Part I – General Methodology. IST-2000-28760.
dc.relation.isbasedonThe Ministry of Industry and Trade of the Czech Republic. (2018a). Panorama of the Manufacturing Industry of the Czech Republic 2018. https://www.mpo.cz/assets/en/industry/manufacturing-industry/panorama-of-the-manufacturing-industry/2019/10/panorama_aj_web.pdf
dc.relation.isbasedonThe Ministry of Industry and Trade of the Czech Republic. (2018b). Panorama zpracovatelského průmyslu ČR 2018 [Panorama of the Manufacturing Industry of the Czech Republic 2018] (1st ed., Vol. 22). Prague: The Ministry of Industry and Trade of the Czech Republic.
dc.relation.isbasedonTurley, G., Robbins, G., & McNena, S. (2015). A Framework to Measure the Financial Performance of Local Governments. Local Government Studies, 41(3), 401–420. https://doi.org/10.1080/03003930.2014.991865
dc.relation.isbasedonVimrová, H. (2015). Financial Analysis Tools, from Traditional Indicators through Contemporary Instruments to Complex Performance Measurement and Management Systems in the Czech Business Practice. Procedia Economics and Finance, 25, 166–175. https://doi.org/10.1016/S2212-5671(15)00725-X
dc.relation.isbasedonWoerd, F. V. D., & Brink, T. v. d. (2004). Feasibility of a Responsive Business Scorecard: A pilot study. Journal of Business Ethics, 55(2), 173–186. https://doi.org/10.1007/s10551-004-1900-3
dc.relation.isbasedonZafra-Gómez, J. L., López-Hernández, A. M., & Hernández-Bastida, A. (2009). Evaluating financial performance in local government: Maximizing the benchmarking value. International Review of Administrative Sciences, 75(1), 151–167. https://doi.org/10.1177/0020852308099510
dc.relation.isbasedonZhu, L., Johnsson, C., Mejvik, J., Varisco, M., & Schiraldi, M. (2017). Key performance indicators for manufacturing operations management in the process industry. In 2017 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 969–973), Singapore. https://doi.org/10.1109/IEEM.2017.8290036
dc.relation.isbasedonZhu, L., Johnsson, C., Varisco, M., & Schiraldi, M. M. (2018). Key performance indicators for manufacturing operations management – gap analysis between process industrial needs and ISO 22400 standard. Procedia Manufacturing, 25, 82–88. https://doi.org/10.1016/j.promfg.2018.06.060
dc.relation.isbasedonZizlavsky, O. (2016). Innovation performance measurement: Research into Czech business practice. Economic Research – Ekonomska Istraživanja, 29(1), 816–838. https://doi.org/10.1080/1331677X.2016.1235983
dc.relation.ispartofEkonomie a Managementcs
dc.relation.ispartofEconomics and Managementen
dc.relation.isrefereedtrue
dc.rightsCC BY-NC
dc.subjectperformanceen
dc.subjectefficiencyen
dc.subjectindustryen
dc.subjectadded valueen
dc.subjectinvestmenten
dc.subjectKey Performance Indicatorsen
dc.subject.classificationL60
dc.subject.classificationO31
dc.titlePerformance Evaluation Framework under the Influence of Industry 4.0: The Case of the Czech Manufacturing Industryen
dc.typeArticleen
local.accessopen
local.citation.epage134
local.citation.spage118
local.facultyFaculty of Economics
local.filenameEM_1_2021_8
local.fulltextyes
local.relation.abbreviationE+Mcs
local.relation.abbreviationE&Men
local.relation.issue1
local.relation.volume24
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