The article undertakes a quantitative approach to investigate the relationship between ICT expenditures and e-maturity in local governments. We rely on data belonging to a unique database on 7106 Italian local governments. We propose a way of assessing e-maturity on a large scale, and we test the relation between e-maturity and ICT expenditures. Results partially confirm the existence of a statistically significant relationship between the two factors. In particular, we observe different patterns depending on the size of the organisation. For small local governments, e-maturity is related with ICT expenditures, meaning that the how (the decision on money allocation) is more important than the how many (the total amount of money spent). On the contrary, for medium and large municipalities, this relation exists, hence a higher e-maturity level is associated with higher ICT expenditures.
Online service provision, digital transformation, and the need for tailored investments in
Information and Communication Technologies (ICT) in public administration have gained
momentum in recent decades. In particular, since early 2000, scholars start looking at the best way
for defining digital maturity (hereinafter e-maturity), defined as the extent to which a public
organization is using digital technologies and online channels in order to manage and deliver its
public services
Our research aims at answering the following research question: are ICT expenditures positively related to e-maturity in local governments? In the concept of ICT expenditures, we include the entire amount of money spent in ICT in a year. The answer to this research question is investigated thanks to an original database on Italian local governments (or municipalities, the two terms are used as synonyms) that collects data from 7106 municipalities regarding the adoption of digital services. In order to answer to the question, we also introduce a novel quantitative measure of e-maturity based on the level of adoption of digital services.
The first model that traces the path of the research concerning e-maturity was proposed by
Previous research led to different and sometimes opposing results in understanding which
factors influence e-maturity. Those factors can be divided into socio-economic factors (for example
income per capita), environmental factors (for example population), and organizational factors (for
example political motivation)
Given these premises, the main contribution of this paper is the test of the following hypothesis: Hp: ICT expenditures by local governments is positively associated with e-maturity.
We focus on local governments because they are in charge of the delivery of the majority of public services. Thus, they are the optimal sample for assessing e-maturity.
3.1
The database used for this study is an official, public database that is the results of a survey delivered by the Italian Supreme Audit Institution (‘Corte dei Conti’) to all Italian public organizations, and represents an official, complete and reliable data source. Data are self-declared by the organizations. The survey compilation was compulsory and remained active for almost one year until 30th October 2019. The survey is divided into thirteen sections. We consider a subset of two sections, related to digital services supply and ICT expenditures.
The first section addresses the topic of digital services supply. The survey considers a sample of 23 services overall. For our study, we select a sub-sample because not all the services were delivered by all the Italian local governments (for example if a local government does not have a school, it does not provide any school-related service). We select the following 10 services: (i) Registry certificate, (ii) Change of residence, (iii) Electoral card, (iv) Disability placard, (v) Building authorization, (vi) Land registry, (vii) Contraventions, (viii) Garbage fee, (ix) Land occupation fee, and (x) Properties fee. For each service, local governments declared whether they were delivering it through the digital channel and the percentage of requests that were issued online out of the total number of requests received by the organization in one year. Hereinafter the latter percentage value is labelled as “penetration”. In the second section, local governments had to declare their expenditures in ICT in the time frame ranging from 2016 and 2018. Overall, 7.153 local governments have answered to the survey, and, after data cleaning, 7.106 answers, which consists of almost 90% of the total Italian local governments, represent the sample of the analysis. The size of the sample ensures representativeness. 3.2
E-maturity is assessed based on the declared penetration. First, for each service, we calculate the descriptive statistics: mean, standard deviation, first and third quartiles. In doing that, we deleted 47 anomalous responses. Second, for each observation, we substitute penetration with a replacing value, as reported in Table 1. This substitution allows to look at penetration in relative terms, thus taking into consideration the overall distribution of the indicator for each service. Third, for each municipality, we calculate the e-maturity score. The score is the arithmetical sum of the replacing values. For the municipalities that do not provide any digital service, the e-maturity score is equal to 0. 0 0,1
Finally, we segment the sample into five different clusters according to the e-maturity score and we label the clusters accordingly (Table 2).
As the second and more important step, we look at ICT expenditures. We consider the average of the three years of expenditures declared (2016-2018) and we calculate the expenditures per capita by dividing for the population. In this phase, we perform a data check that results in the elimination of 804 answers due to data unavailability.
Finally, for testing the hypothesis, we perform linear regression analyses. First, we divide the sample into 7 categories considering the population. In fact, there is a significant difference between small and big municipalities, thus it was not possible to include all the items in the same regression analysis. Second, for each category, we perform a linear regression analysis between the three-year average ICT expenditures per capita and the identified clusters. The only exception is the cluster that includes municipalities with more than 250k inhabitants.
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The distribution of ICT expenditures per capita varies according to the size. The smallest municipalities (below 2.000 inhabitants) are the most expensive ones, characterized by a U-shape that starts from 19,40€/person for the No Digitals, has the minimum in correspondence with the Moderates cluster (18,05€/person) and finally raises until 20,60€/person for the Champions cluster. Similarly, the biggest municipalities (more than 250k inhabitants) also have remarkably high expenditures in ICT per capita (13,47€/person in the Believers cluster and 18,75€/person in the Champions one). All the other municipalities in the range of population between 2k and 250k inhabitants interact with growing clusters of maturity differently, as specifically disclosed in Figure 1. Municipalities with a higher e-maturity level, have higher ICT expenditures.
From 2000 to 4999 From 5000 to 9999 From 10000 to 19999 From 20000 to 59999 From 60000 to 249999 Sum of observations €9.00 A IPT€8.00 A C R PE€7.00 S E R U ITD€6.00 N E P X E€5.00 T C I €4.00
N O D I G I T A L S
B E G I N N E R S
M O D E R A T E S
B E L I E V E R S
C H A M P I O N S From 2000 to 4999 From 20000 to 59999
From 5000 to 9999 From 60000 to 249999
From 10000 to 19999
The linear regression (Table 4) confirms the results disclosed in Figure 1. The results confirm what emerged from the first analysis and add statistical significance to previous considerations. Each model of Table 4 corresponds to a subset related to the corresponding range of population.
For municipalities belonging to the first model (population lower than 2k inhabitants), the ICT expenditures do not depend on maturity level, since associated coefficients result to be not statistically significant. The same considerations can be applied to the second model (population between 2k and 5k inhabitants), which differs from the previous one only in terms of scale of ICT per capita, which are significantly lower than the first subset. Municipalities tested in the third model (population between 5k and 10k inhabitants) start to behave differently. In particulars, the beginners (thus municipalities with low e-maturity level), have significantly higher ICT expenditures. The fourth model (population between 10k and 20k inhabitants) depicts a slightly different scenario. In particular, it has almost all the coefficients statistically significant (except the one associated with beginners) and remarkably different. Thus, higher e-maturity levels correspond to higher ICT expenditures. The fifth model (population between 20k and 60k inhabitants) and the sixth model (population between 60k and 250k inhabitants) report the same trend, that is statistically significant for all the e-maturity clusters. The seventh model (population higher than 250k inhabitants) is not tested because it includes only twelve municipalities that belong to the highest e-maturity clusters (clusters 3 and 4), hence there are too few observations for regression analysis.
Despite the linearity and simplicity of the research question, results show a complex and fragmented picture. Three insights are here further discussed: (i) local governments’ e-maturity; (ii) local governments’ ICT expenditures and, most notably, (iii) the presence of a relation between the two.
First, results confirm that e-maturity is extremely context-specific [1]. Several environmental factors can influence the e-maturity level of local governments, in particular the dimension of the municipality. Consequently, policymakers should reflect on how to implement a structural change of course, that is even more urgent nowadays that the COVID-19 crisis is impeding (or at least discouraging) people to physically go to the counter.
Second, per capita ICT expenditures assume a U-shaped trend: extremely small and large
municipalities have the highest expenditures. We can hypothesize that structural ICT expenditures
inefficiencies are embedded in those municipalities that are too small (less than 2k inhabitants) to
reach enough economies of scale. Thus, policymakers should reflect on how to support those
municipalities in diminishing their expenditures pro capita. For example, inter-municipal
collaboration
Finally, and most notably, the paper offers novel quantitative insights on the relation between ematurity and ICT expenditures. We observe that the relation between e-maturity and ICT expenditures varies depending on the size of the municipality. For small municipalities, higher ICT expenditures do not automatically correspond to higher e-maturity. Thus, policymakers should be aware that the sole release of funds to those municipalities is not the proper solution for supporting their digitization process. Rather e-maturity is more related to how administrators decide to spend the money at their disposal. Moreover, small municipalities might need support in their digitization process, for example by upper-tier organizations (such as regional governments). On the opposite, a positive correlation between ICT expenditures and e-maturity is detected for medium and large municipalities. For those municipalities, investing more in ICT is tightly linked to a higher ematurity level. This confirms and corroborates previous qualitative insights [4]. Moreover, it set the boundaries of the validity of the relation clarifying that a positive relation between e-maturity and ICT expenditures is to be expected only for medium and large municipalities. Policymakers should consider that those municipalities have the capacity to properly use and invest money to grow in terms of e-maturity.
Further research shall keep on investigating in the same direction and overcome the existing limitations. First, even though data were collected by a regulatory authority, they are self-declared by the local governments, thus this circumstance opens to possible mistakes and misinterpretations. Second, we limit to a subset of services and a linear way of assessing e-maturity. Further studies should look also at other types of services and develop more quantitative and detailed models for assessing e-maturity. Third, more efforts are required to obtain more granular and detailed data on ICT expenditures, for example dividing between CAPEX and OPEX. Finally, we limit e-maturity determinants to population and ICT expenditures. We do not include any other factors and, in particular, any other organizational factors. We are aware that, within an organization, ICT expenditures are only one of the aspects that can influence e-maturity. Thus, further studies should identify a proper way for a better understanding of which organizational factors that may determine e-maturity. Aral, S., & Weill, P. (2007) IT assets, organizational capabilities, and firm performance: How resource allocations and organizational differences explain performance variation, Organization Science, 18, (5), 763–780.
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Budding, T, & Faber, B. & Gradus, R. (2018) Assessing electronic service delivery in municipalities: determinants and financial consequences of e-government implementation. Local Government Studies, 44(5), 697–718.
Luca Tangi is a project officer at the Joint Research Centre (JRC) of the European Commission. He earned a PhD in Management, Economics and Industrial Engineering at the Politecnico di Milano. His doctoral work focused on understanding how ICTs are affecting public service delivery and transforming the way public organisations are structured and organised. Since June 2021 he collaborates with the JRC carrying out research on the introduction of new, cutting-edge technologies and in particular Artificial Intelligence in public settings.
Marco Gaeta is a researcher in the e-government field at the Department of Management, Economics and Industrial Engineering of the Politecnico di Milano. Here, after his Master's degree in Management Engineering, he started working as a researcher, following the focus and the research interests of his master thesis concerning the digitalization of Italian local governments and innovation in the public sector.
Michele Benedetti is a research fellow and lecturer at the School of Management of the Politecnico di Milano. Since 2001 he has carried out research on digital innovation in the public sector. He also gained almost twenty years of experience in managing complex projects of public sector digital transformation. Since 2009 he has been director of the eGovernment Observatory of the School of Management of the Politecnico di Milano and since 2017 also of the Digital Agenda Observatory.
Giuliano Noci is full professor of Marketing at Politecnico di Milano. At present, he is also: Vice-Rector for China at Politecnico di Milano, member of the Board CEO of Polimilano Educational Consulting Ltd – a company deploying post graduate education and technology transfer projects in China –, member of the Board of Directors of MIP Graduate School of Business and of the Board of Trustee of TongJi University. His main research fields cover the following subjects: marketing, eBusiness, and eGovernment.