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Influence of SME’s size on internet connectivityMilanka Bogavac, Assistant Professor, Ph.D.Dr. Zoran Čekerevac, Full Professor“Union - Nikola Tesla” University, Belgrade, SerbiaINFLUENCE OF SME’s SIZE ON INTERNET CONNECTIVITYAbstract. This paper presents an overview of the part of the research performed to definethe ways and criteria for determining the degree of success of the digitalization of small andmedium-sized enterprises (SMEs). During the research, an Index of the Digitalization of SMEs(IDSME) was defined. After a brief introduction into the IDSME index, because of the importanceof Internet connections, the authors analyzed whether and how the company size is connected to theInternet connectivity dimension. The research covered 226 companies of different sizes andbusiness orientations from Slovakia, Serbia, and Russia. During the research, the main researchquestion was: What is the relationship between the size of SMEs and their links to the Internetexpressed through the "Connection to the Internet" dimension of the IDSME index? The answer tothis question was found by examining the correlation between these two variables, where the"Connection to the Internet" dimension appeared as the dependent variable. The independentvariable was the number of employees in SMEs.Keywords: Digitalization, SME, Internet, IDSME Index, Business Process.1IntroductionDue to the development of the market and automation, the elimination of bordersand competition, or the inability to adapt to the new conditions, many companies arefailing. Small and medium-sized enterprises (SMEs) have appeared as possible waysof survival of their owners and employees. It is good that SMEs can quickly adapt tonew business conditions, but their size is often a problem because of the size of boththe material and human resources available to them. More about SMEs is discussed inmany literature sources, such as, for example, [1], [2], [3], etc. It can be noted thataccording to the data of the Serbian Chamber of Commerce [4] 340,112 SMEs with837,532 employees operated in Serbia in 2016, making 99.8% of the number ofcompanies, and by number employees 65.7%. In Germany, one of the most developedeconomies in the world, 99.5% of companies in 2018 were classified in the SME group[5, p. 2]. A very similar situation is also in other countries.Digitalization is a term that is widely used nowadays. Many criteria have beencreated to point out to the level of digitalization of individual economies and countries,e.g. DESI - Digital Economy and Society Index [6], I-DESI International DigitalEconomy Index [7], EDI - Enabling Digitalization Index [8], GCI - GlobalConnectivity Index [9], and other indices, but the area of SMEs remained neglected.Considering the data presented and the importance of SMEs, it is very importantto consider the factors that influence and can influence the efficiency and quality of thework of these legal entities. Bearing in mind the ubiquity of information technologies,digitalization is imposed as an undeniable influence on the functioning of small andmedium-sized companies.11

Milanka Bogavac, Zoran ČekerevacThis research was carried out as part of the preparation of the doctoraldissertation [10], a broader study of the impact of business process digitalization onincreasing the performance and sustainability of SMEs. It was carried out in threecountries, Slovakia, Serbia, and Russia. In this paper, the accent is placed on thedimension of the Connection to the Internet. Since authors are not aware that theprevious research on digitalization measurements at the level of SMEs exists, theauthors consider this research a pioneering work in that field.2The SME Digitalization IndexThe SME Digitalization Index (IDSME) allows SMEs to carry out selfevaluation and determine to what level they are digitalized and on what they need topay attention to in their development plans. Its dimensions are Connection to theInternet, Digital Skills, Integration of Digital Technologies, and Internet Usage. TheIDSME measures the progress of SMEs in the digitalization process. It was developedon the principles and recommendations given in the handbook on constructingcomposite indicators [11]. Twenty-eight indicators are grouped into 10 sub-dimensionsand four dimensions. Dimensions and sub-dimensions are weighted, but indicators arenot. The aggregation method is presented in Section 2.2.The structure of the IDSME index and weightings are explained in detail in [10]and [12]. Therefore, they will not be fully discussed here, and only the part that relatesto this research will be shown here.2.1 Dimension – Connection to the InternetThis dimension, the connection to the Internet is today the precondition of allconditions. Except in extremely rare applications, e.g. connecting ATMs or fiscal cashregisters, dial-up connections to the Internet cannot be considered a favorable solution.Therefore, fast internet connections can be considered as a very significant dimensionof IDSME indicators. This dimension is divided into four sub-dimensions, eachfocusing on one aspect of connecting to the Internet: Connectivity to broadband Internet. Connection to the Internet via a public telecommunication network. Internet speed as a factor influences processes in SMEs and focuses on theability (and desire) of a business to make better use of the Internet's capabilities. As the"high-speed Internet" limit, the declared value of the Internet access speed of 30 Mbpsis taken because of the comparability of companies from different countries. At thetime of writing this work, the standard offer in Serbia was 20/4 Mbps and the optimal100/10 Mbps. The boundary speed will certainly be a parameter that will change overtime. As an indicator in the model, a subscription to a fast broadband Internet abovethe limit value in the year under review was considered a limit value subscription. Table1 shows the structure of SMEs' Internet connectivity.Table 1. Results of the survey on the connection of SMEs to the Internet.SMEsMediumDial-up40.4%Cable91.5%Broadband InternetMediumMediumdeclareddeclaredspeed [Mb/s] Mobile speed [Mb/s]117.751.1%41.312

Influence of SME’s size on internet %49.4%108.757.8%36.0Total - have53.5%75.2%115.056.2%36.5Source: Authors’ research Possibility to work from a remote location (or the possibility to work on aremote computer) is an option that has been seriously talked about for some twentyyears, and which gets its importance in time especially in crises such as with COVID19. This sub-dimension focuses on the willingness of SMEs to organize and usedistance working. As a criterion, the percentage of employees is taken here about thetotal number of employees. It is obvious that if corrections are not introduced, theremay be unjustified favorability for micro-companies to others. Therefore, the modelset the limit to 10% of the total number of employees. With ten or more percent ofthose who worked remotely the surveyed SMEs achieved the maximum number ofpoints according to this criterion. Survey results related to the possibility to work froma remote location for this set of SMEs are shown in Table 2.Table 2. Survey results related to the possibility to work from a remote 0%56.6%52.2%Criterion A6.9%13.4%54.3%10.4%Criterion B3.3%6.5%27.7%5.0%Criterion A – % of those who worked remotely related to the number ofemployees in SMEs that enable distance workCriterion B – % of those who worked remotely related to the number ofemployees in SMEsSource: Authors’ research2.2 AggregationThe aggregation of indicators in the Internet connectivity dimension wasconducted on the way that the indicators were aggregated into the sub-dimensions, andthen the weighted values of the sub-dimensions were aggregated into dimensionInternet connectivity.The aggregation of indicators into dimension was done as follows:1.Before aggregation, the normalization of the indicators was done to unifythe units. It was performed using the min-max method by the linear projection of eachindicator on a scale in the range 0 to 1. The zero corresponds to the minimum valueand the one to the maximum value (see Table 4).2.In the second stage, the indicators are aggregated into sub-dimensions bysimply summing their values.3.In the third stage, the sub-dimensions were weighted using the w valuesshown in Table 4 and by summing aggregated into the Internet connectivity dimension.13

Milanka Bogavac, Zoran ČekerevacTable 3. Structure of inclusion the indicators into the dimensions Connection to theInternetDimension1.Connectionto ection to a Possession of1a. Connectivity tofixedanactivebroadband InternetbroadbandconnectionInternet1a2.Connection to a Possession of(w 25%)mobileanactivebroadbandconnectionInternet1b. Connection to1b1.the Internet via aPossession ofConnection topublicanactivethe Internet viatelecommunicationconnectionphone linenetwork (w 15%)min max0101011c1.1c. Internet speedSubscription to(w 30%)fast BB accessDeclaredaccess speed 30Mbps011d. Possibility toworkfromaremotelocation(w 30%)% ofemployeeswho used thisopportunity inthe last threemonths0101d1. Users ofthe workingfrom remotelocation optionSource: [12]In the case of aggregation of the Internet connectivity dimension (ICD) for thei SME, the following formula was applied [12]:thICD(SMEi) Connection to broadband Internet(SMEi) * 0.25 Connection via a public telecommunication network(SMEi) * 0.15 Internet speed(SMEi) * 0.3 Share of distance working(SMEi) * 0.33Methodology of ResearchThis research is exploratory with elements of explanatory and descriptive. Theresearch used an empirical method as an analytical method that enables reliableconclusions on the interdependence of certain observed elements and trends inindividual phenomena. The statistical analysis covered the relevant data that enabledthe detection of the legality of mass events covered by this analysis.14