LABOUR PRODUCTIVITY AND TECHNOLOGICAL INTENSITIES OF SMALL AND MEDIUM ENTERPRISES IN MANUFACTURING

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1 LABOUR PRODUCTIVITY AND TECHNOLOGICAL INTENSITIES OF SMALL AND MEDIUM ENTERPRISES IN MANUFACTURING Tomáš Volek Martna Novotná Abstract Technologcal ntensty s a crtcal determnant of enterprses labour productvty growth and compettveness. The mpacts of technologcal ntensty can be expected n economcs performance of enterprses. The goal of ths paper s to examne the role of technologcal ntensty n changes labour productvty and economcs performance of small and medum enterprses n manufacturng (SMEs). The artcle analyss manufacturng ndustry accordng to technologcal ntensty. The analyss focuses on the Czech Republc. The observed data were from the 5-year perod ( ). The source of data for the conducted analyss of the enterprses was a database contanng accountng data of companes wth at least one employee. It was found that labour productvty decreased due to a sgnfcant ncrease n labour costs compared wth enterprses performance growth n all technology-ntensty groups (except lowtechnology ndustry). The reason s a stuaton on the Czech labour market. Key words: labour productvty, technologcal ntensty, enterprses, manufacturng JEL Code: D24, E01, E23 Introducton Level of labour productvty s one of the crtcal factors nfluencng the compettveness of enterprses n the manufacturng. An mportant nfluence that can nfluence labour productvty s the level of technologcal ntensty. It can be assumed that companes wth hgher technologcal ntensty also acheve hgher labour productvty. The am of the paper s to assess the role of technologcal ntensty n changes of labour productvty and economc performance of small and medum enterprses n manufacturng. Manufacturng s not unform sector. Manufacturng conssts of dfferent dvsons wth dfferent development of productvty and economc performance. The sgnfcant factors that affects these dvsons of manufacturng are nnovaton, level of R&D (Raymond & St-Perre, 2010) or busness cycle (Marchett, 2002). Cyclcal mpact of the economy on the dvsons 1884

2 performance s n some sectons more some less. Important s also the cause of ts orgn (Vorlcek & Cermakova, 2017). The performance of enterprse can be measured by usng the fve basc fnancal ndcators: lqudty, solvency, proftablty, effcency and productvty. Productvty s n frm measured the effcency of usng factors of producton. The productvty of frm we can measure by many ndcators of productvty. The most frequently measured ndcator s labour productvty. We have other types of productvty as captal productvty or total factor productvty. The captal productvty shows how productvely captal s used to generate value added. Total factor productvty measure technologcal change and TFP s a very mportant drver of long-run economc growth (Everaert et al., 2015). Labour productvty provdes a measure of the effcency wth whch labour are used n enterprse to produce goods and servces, t can be measured n varous ways. Labour productvty s equal to the rato between a volume of output (value added, sales) (Huynh et al., 2015) and a measure of nput use (the total number of hours worked, labour cost or total employment). Labour productvty s nfluence by many factors as sector (Aoyama et al., 2009), enterprses age (Cucculell et al., 2014), nnovatons (Mura & Rozsa, 2013), sze of frm (Chmelkova &Redlchova, 2013) or technologcal ntensty (Hall et al.,2009). 1 Data and methodology The am of the paper was to assess the dfferences n the labour productvty and economcs performance of small and medum enterprses dvded accordng to technologcal ntensty. The goal was also to fnd a change n ths effcency n 2016 compared to 2012 (change after fve years) n enterprses n manufacturng of the Czech Republc. The analyss was performed n 1068 SMEs, through ther fnancal statements drawn from the Albertna database. The same enterprses were under revew n both of the years. We used the classfcaton by Commsson Recommendaton 2003/361/ESES based on number of employees, turnover and balance sheet total. Attenton was focused on enterprses n the manufacturng ndustry, whch were dvded accordng to economc actvty or technologcal demands. The enterprses were sorted nto four categores. Eurostat uses the aggregaton of the manufacturng ndustry accordng to technologcal ntensty and based on NACE Rev. 2 at 2-dgt level: HT (hgh-technology), MHT (medum-hgh-technology), MLT (medum-low-technology), LT (low-technology). It was evaluated not only the effcency of the labour factor but also the company's performance. Effcency of work was measured through ndcators: Labour productvty (Sales 1885

3 - S/labour costs - PC), Labour ntensty (labour costs - PC/ total costs - TC), Captal-Labour rato (fxed assets/labour costs). Busness performance was evaluated usng ROA,.e. the rato of EBIT and Assets a Return on Equty (ROE) rato EAT and Equty. The partal objectve was to analyse the contrbutons of ndustry dvded by technologcal ntensty to a change n labour productvty or a change n asset proftablty n 2016 compared to Ths analyss was based on a data of 1068 small and medum-szed enterprses to dvde the overall change n labour productvty (or asset return) nto parts that could be attrbuted to ndvdual groups of enterprses. The analyss should dentfy the groups of frms that have major contrbuton to the change n the labour productvty and ROA n SME. The bass for determnng the sze of the beneft or loss s to come out of the varable composton ndex as a comparson of two arthmetc averages (Jílek & Vojta, 2000),.e. γ γ Where γ 1,, γ 0 = Labour productvty n perod 1 (2016) and n the year 0 (2012) for the category of enterprses by technologcal ntensty, or ROA, L 1, L 0 γ L = Labour costs for the perod 1 (2016) and n the year 0 (2012) for the category of enterprses by technologcal ntensty, or assets. To calculate the beneft of each category of enterprse to change labour productvty for the whole set of enterprses or to change the ROA, only the group of enterprses whose mpact s calculated should be placed n the frst perod for the other groups of enterprses to enter data from the base perod. The computatonal relatonshp was used to analyse both labour productvty and ROE. L Based on the pyramdal breakdown of ROE change and the logarthmc method of decomposng ndcator values, the effect of changes n the labour productvty for ndvdual categores of enterprses on changes n return on equty can be observed. The breakdown s based on a causal determnstc model: : γ L L (1) ROE ROA * leverage (1 costrato) * turnover* leverage labourcosts othercosts (1 ( ) * turnover* leverage costs costs othercosts (1 ( averagewages* labour productvty) * turnover* leverage costs (2) The nfluence of labour productvty then can be fnd by usng the logarthmc method. 1886

4 ROE log I log I ROA (1 n) rato labour costs * labour productvty log I log I * n ROE ROA 0 0 rato labour costs n 1 1 * log I * log I rato LP labour costs (3) 2 Results 2.1 Labour productvty and frms performance n manufacturng The analysed enterprses group conssts from Czech small and medum-szed enterprses n manufacturng whch were dvded accordng to technologcal ntensty (see methodology). The montored enterprses are n groups Medum hgh technology (45%), low technology (30%), medum low technology (22%). The lowest representaton has SMEs n the hgh technology sector, whch s n lne wth the representaton of these sectors and across the natonal economy. The Czech manufacturng ndustry s characterzed by the hgh share of Medum hgh technology sector, medum low technology and low share of hgh technology sector n comparson to the EU average. All ndcators were surveyed n 2012 and 5 years later,.e. 2016, and then a comparson was made. The followng table 1 descrbes development of labour productvty ndvdual groups. We can see a declne n labour productvty due to dsproportonate labour costs n all groups except low technology sector. Captal-labour rato and the labour ntensty s ncreased n most sectors. In terms of busness performance measured by proftablty, outputs of sngle sectors are dfferent. 1887

5 Tab. 1: Labour productvty group of technologcal ntensty Indcator Technologcal Index (2016/2012) ntensty Labour HT 4,060 3,317 0,817 productvty n MHT 3,893 3,549 0,912 CZK MLT 3,632 3,494 0,962 LT 3,559 3,605 1,013 Total 3,692 3,533 0,957 C-L Rato n CZK HT 0,820 0,985 1,201 MHT 1,417 1,389 0,980 MLT 1,312 1,432 1,091 LT 1,486 1,526 1,027 Total 1,259 1,333 1,059 Labour ntensty HT 0,217 0,286 1,321 MHT 0,206 0,254 1,229 MLT 0,248 0,269 1,084 LT 0,235 0,245 1,041 Total 0,227 0,263 1,162 ROA n % HT 11,500 11,330 0,985 MHT 1,908 5,196 2,724 MLT 7,845 9,166 1,168 LT 6,495 4,902 0,755 Total 5,842 6,975 1,194 ROE n % HT 14,585 14,100 0,967 MHT 0,499 8,730 17,487 MLT 10,479 12,392 1,183 LT 9,199 6,137 0,667 Total 7,776 9,885 1,271 Source: Own calculatons based on frm database ALBERTINA Fgure 1 llustrates the contrbutons of ndvdual groups to the overall change n labour productvty or overall change n return on assets n 2016 compared to The greatest contrbuton to the change n labour productvty had medum-hgh-technology and low-tech ndustres. Low-tech and medum-hgh-tech ndustres contrbuted the most to the growth of small and medum-szed enterprses. 1888

6 Fg. 1: Contrbutons of enterprses accordng to technologcal ntensty to change of labour productvty and proftablty (ndex 2016/2012) Change n labour productvty n % (Total growth -4.31%) Change n Return on Assets n % (Total growth 19.4%) 0, ,5-1 -1,5-2 -2,5-3 -3,5-4 0,07-0,38 1-2,81-1, ,48 15,08 0,49-9,66-4, HT MHT MLT LT HT MHT MLT LT Source: Own calculatons based on frm database ALBERTINA The relatonshp between the change n proftablty and the change n labour productvty s descrbed n Table 2 below. The logarthmc method has been found to contrbute negatvely to the growth of frm proftablty n group HT, MHT and MLT. Tab. 2: Proftablty and labour productvty group of technologcal ntensty Technologcal Change of ndcator ROE Influence of labour productvty ntensty Absolute Index Absolute Relatvní (ndex) n CZK n CZK HT -0,005 0,967-0,075 0,594 MHT 0,082 17,487-0,015 0,594 MLT 0,019 1,183-0,022 0,822 LT -0,031 0,667 0,005 1,064 Source: Own calculatons based on frm database ALBERTINA On the other hand, n the low-technology ndustry, the postve effect of labour productvty on the proftablty of enterprses (ROE) was found. 2.2 Labour productvty and labour cost If labour productvty s based on labour costs, t s necessary to montor labour ntensty and captal-labour rato. Fgure 2 shows the average growth rate n the montored perod for 1889

7 ndvdual categores of enterprses for ndcators related to the effcency of the labour. The bg declne of labour productvty and large ncrease n labour cost wth growth of captal-labour rato was found n hgh-tech ndustry. On the other hand, n the low-tech ndustry was found low growth of captal-labour rato and labour cost wth had a postve effect on labour productvty growth. Fg. 2: Average annual growth rate of selected ndcators by technologcal ntenstes n LT MLT MHT HT 0,88 0,9 0,92 0,94 0,96 0,98 1 1,02 1,04 1,06 1,08 1,1 Labour ntenzty Labour productvty C-L Rato Source: Own calculatons based on frm database ALBERTINA The last analyss s focused on the ndvdual ndcators from whch labour productvty s based. Fgure 3 analyses the average annual growth rate of frms performance and labour costs. In order to ncrease labour productvty, whch at the same tme postvely affects the performance of the company or ts proftablty, growth of corporate performance should be hgher than the growth of labour costs. Fg. 3: Average annual growth rate of outputs and labour costs by technologcal ntenstes n

8 1,06 1,05 1,05 1,04 1,04 1,03 1,02 1,01 1,00 1,01 1,03 1,03 1,02 1,02 1 0,99 0,98 HT MHT MLT LT Performances (ndex) Personal costs (ndex) Source: Own calculatons based on frm database ALBERTINA The growth rate of labour costs excesses the growth rate of enterprses performance for all groups of enterprses dvded by technologcal ntensty except low-technology group. Ths stuaton can ental a rsk for enterprses to reduce ther compettveness. Concluson The paper deals wth the role of technologcal ntensty n changes labour productvty and frms performance of small and medum enterprses n manufacturng. Compared to the orgnal assumpton, t was found that low-technology ndustry has the postve effect on the growth of labour productvty. On the contrary, labour productvty n the hgh-tech ndustry declned, compared to the orgnal expectaton, whch was manly due to the hgh growth of labour cost compared to the enterprses performance growth. It was found that, apart from the low-tech ndustry n all sectors, labour productvty decreased due to a sgnfcant ncrease n labour costs over the perod under revew as compared to the growth n the producton performance of enterprses. Ths stuaton s caused by stuaton n the labour market where labour productvty s very nfluenced by the flexblty n the labour market (Pavelka & Loester, 2013). Next dsproportonate wages growth can mean a sgnfcant rsk of losng compettveness for enterprses n the future. 1891

9 Acknowledgment Ths paper was supported by the Grant Agency of the Unversty of South Bohema GAJU - GAJU 053/2016/S. References Aoyama, H., Fujwara, Y., Ikeda, Y., Iyetom, H., & Souma, W. (2009). Superstatstcs of Labour Productvty n Manufacturng and Nonmanufacturng Sectors. Economcs-the Open Access Open-Assessment E-Journal, 3. Chmelkova, G., & Redlchova, R. (2013). Start-ups and ther Role n the Economy. In Regon n the development of socety 2013 (s ). Zemedelska 1, Brno, , Czech Republc: Mendel Unv Brno, p Cucculell, M., Mannarno, L., Pupo, V., & Rcotta, F. (2014). Owner-Management, Frm Age, and Productvty n Italan Famly Frms. Journal of Small Busness Management, 52(2), do: /jsbm Everaert, G., Heylen, F., & Schoonackers, R. (2015). Fscal polcy and TFP n the OECD: measurng drect and ndrect effects. Emprcal Economcs, 49(2), do: /s Huynh, K. P., Jacho-Chávez, D. T., Petruna, R. J., & Voa, M. C. (2015). A nonparametrc analyss of frm sze, leverage and labour productvty dstrbuton dynamcs. Emprcal Economcs, 48(1), do: /s Jílek, J., & Vojta, M. (2000). Vypovídací vlastnost změn jednotkových pracovních nákladů a souvsejících ukazatelů. Statstka, 20(4), Mura, L., & Rozsa, Z. (2013). The mpact of networkng on the nnovaton performance of SMEs. In Loster, T and Pavelka, T (Ed.), 7th Internatonal days of statstcs and economcs (s ). Fugnerova 691, Slany, 27401, Czech Republc: Melandrum. Marchett, D. (2002). Markups and the busness cycle: Evdence from Italan manufacturng branches. Open Economes Revew, 13(1), Hall, B. H., Lott, F., & Maresse, J. (2009). Innovaton and productvty n SMEs: emprcal evdence for Italy. Small Busness Economcs, 33(1),

10 Pavelka, T., & Loester, T. (2013). Flexblty of the czech labour market from a perspectve of the employment protecton ndex. 7th Internatonal Days of Statstcs and Economcs, p Raymond, L., & St-Perre, J. (2010). R&D as a determnant of nnovaton n manufacturng SMEs: An attempt at emprcal clarfcaton. Technovaton, 30(1), do: Vorlcek, J., & Cermakova, K. (2017). Strategc behavor as the cause of busness cycles. Internatonal Journal of Economc Scences, 6(1), do: /es Contact Tomáš Volek Faculty of Economcs, Unversty of South Bohema Studentská 13, České Budějovce, Czech Republc volek@ef.jcu.cz Martna Novotná Faculty of Economcs, Unversty of South Bohema Studentská 13, České Budějovce, Czech Republc novnotna@ef.jcu.cz 1893