Informative Transparency on Entrepreneurship by Spanish Local Governments

Abstract

In recent decades, city councils have become a powerful tool used to “motivate” entrepreneurship. Through a content analysis of the webpages of 50 Spanish city councils corresponding to the period 2015–2019, the evolution of the degree of disclosure of information on entrepreneurship has been analysed. A series of population, economic and political explanatory factors have researched the disclosure of this type of information in two ways. First, a cluster analysis was carried out based on a previously calculated disclosure index. Second, an analysis of variance was performed to verify the existence of an association between the proposed determining factors. The results show that the information disclosed on entrepreneurship by municipalities is related to the size of the population, municipal debt, institutional capacity, the unemployed population and political competition.

1. Introduction

In recent decades, city councils have played an important role in promoting and sharing an entrepreneurial spirit [1,2]. They have not only become a fundamental engine behind the activities that take place in a territory, they have also contributed to promoting the interests of both companies and the general public to understand where business and entrepreneurial dynamics are within a given territory [3].

One aspect of the incentive of the business creation policy is motivation towards entrepreneurship [4]. There is extensive research on the effect of business models on improving entrepreneurial motivation [5,6]. Entrepreneurial motivation [7,8] is understood as the desire to undertake a feasible project that provides social value [9].

Few studies have analysed the role that municipalities play as a catalyst and diffuser of this motivation towards entrepreneurship. Authors from countries such as Portugal, Sweden, Italy, and Russia have presented effective ways to promote entrepreneurship based on municipal policies [10,11,12,13]. These studies have received little attention in Spain, thus providing a new field to be explored and analysed [14,15,16,17,18].

The role that municipalities play to improve the rate of entrepreneurship is mainly reflected in the influence of the media on improving entrepreneurial desirability [5,6,10,19]. Municipalities also contribute to increasing the level of social acceptance of the entrepreneur, which influences the desire to start new business. Part of the role of city councils to motivate citizens to put new business ideas into practice is to publish entrepreneurship topics on their websites. By increasing the “exposure to entrepreneurship” of the municipal institution, it will be easier for the citizen to start new businesses since they will have updated and complete information on the new opportunities that are generated in each territory [10].

Similarly, local administrations are recipients of training proposals aimed at young people to increase the employment rate among the inhabitants of a certain territory [12,14,20,21,22]. A good part of this training offer corresponds to the promotion of entrepreneurial spirit. At the same time, it is clear that self-employment or, in other words, the development of an entrepreneurial activity, can become an important tool to energise towns and territories, while contributing to the business, professional, and personal development of the inhabitants of a population. Entrepreneurship is not an easy task. It requires a process of permanent accompaniment by training entities and the development of skills and resources that will support the entrepreneur in the difficult moments that every entrepreneurship process entails [23,24].

Entrepreneurial initiatives also require the collusion of institutions that help promote the interest and importance of the training necessary to become a successful entrepreneur. In this sense, city councils play an important role in supporting and promoting the creation of companies. In the process of disseminating the entrepreneurial offer, local administrations have made a vital effort to concentrate and disseminate any initiative based on information and communication technologies (ICTs) [25]. The updating of the servers, the increase in space on municipalities’ websites, the commitment to a more attractive design, and the introduction of interactive dynamics with the potential users of the websites have turned local administrations into an adequate transmission vehicle towards the end user. Specifically, in recent years, important steps have been taken to implement e-government [26]; the promotion of e-government is currently visible in municipalities such as Sweden [27] and Australia [28,29,30,31]. Consequently, and considering municipalities as a fundamental factor supporting entrepreneurial work, the following research questions are posed: (1) Do Spanish town councils disclose information about entrepreneurship? and, (2) What are the determinants of this disclosure? In order to answer this question, the objective of this study is twofold. On the one hand, it analyses the information that Spanish city councils provide to entrepreneurs on their institutional web portals by calculating an information disclosure index for the period between 2015 and 2019. On the other hand, throughout the 2019 financial year, a series of factors determining the disclosure of this type of information is studied. This aims to answer the second research question of this study, contributing to the generation of knowledge in this matter in the field of local administrations in Spain. The reason for this is that the dissemination of entrepreneurship by local administration is a topic that has received little academic attention, despite its importance due to its impact on citizens.

These studies will serve to reflect the deficiencies observed with a view to improve the information disclosed. To do this, after this introduction, we will first examine the previous academic literature on the determinants of the disclosure of information. Subsequently, the research hypotheses will be presented, and, through the statistical treatment of data, the degree of information provided by its webpages will be analysed, as well as exploring its evolution over time. The study also detected factors that have conditioned the disclosure of information on entrepreneurship. Finally, we offer results, discussions, conclusions, implications, and future lines of research.

2. Determinants of the Disclosure of Information on Entrepreneurship and Research Hypotheses

Authors such as [32,33] consider that, to date, web portals have become the main information disclosure resource for governments, with the aim of increasing transparency. The literature review reveals that, in recent years, studies that focus on the dissemination of information on entrepreneurship by the local administration have appeared, although these are not numerous despite their importance due to their impact on citizens. Thus, we found recent studies at the national and international level, such as [34,35], which analyses disclosure of information on entrepreneurship in the province of Cáceres. Furthermore, Ref. [36] focused on the study of the websites of the main municipalities of the Extremadura community, namely on Alentejo municipalities, among others. There are quite a few current studies that address the disclosure or dissemination of information in local governments from different areas, such as [37,38,39,40]. A review of the literature on the dissemination of information in public administration through webpages shows that most of studies focus mainly on social, economic, and political factors [37,38,39,40]. In this sense, in order to achieve the second objective of our study, which deals with the determinants of the dissemination of information on entrepreneurship, an analysis of the previous literature on existing social, economic, and political factors was carried out.

2.1. Social Factors

In most of the research that focuses on the dissemination of information through the web, the size of the municipality is one of the factors that determines these practices. According to agency theory, the size of municipalities is positively related to the information disclosed through their websites [41,42], as larger municipalities manage larger budgets, so they have greater technical and human resources at their disposal [43,44,45,46]. In addition, it is expected that municipalities that reveal more information have greater competitiveness and legitimacy with their citizens. Studies carried out in the public sector consider that population size is not a predictive factor for the dissemination of information through the internet [47,48], nor the dependent population, despite being a variable in which there is no broad consensus [21]. Authors such as [46] argued that the larger the dependent population, the greater the demands of citizens regarding the transparency of information. In contrast, they found a negative relationship between the dependent population and the disclosure of information through the web.

The results of the previous literature allow the following hypotheses to be developed in line with the arguments set out above:

H₁: 

There is a significant relationship between the size of the population and the level of disclosure of information on entrepreneurship.

H₂: 

There is a significant relationship between the dependent population and the level of disclosure of information on entrepreneurship.

2.2. Economic Factors

The literature contains numerous studies in which municipal debt is one of the factors that determines the practices of information disclosure in local governments. Thus, municipal debt can be used as an explanatory factor [49]. However, there is no consensus on the type of influence it exerts on the disclosure of information. Refs. [50,51] argue that municipal debt has a negative effect, that is, the higher the level of indebtedness, the more resources required to meet the payments, so the municipality would have fewer resources available for other services. Similar research found no statistically significant differences [52].

Regarding the institutional capacity variable, which disseminates information through its official and institutional channels [46,53], it is evident that municipalities with higher incomes have more resources to improve their information dissemination systems. Ref. [41] analysed institutional capacity through total per capita spending; Refs. [31,49,54] examined institutional capacity represented by total spending. However, Ref. [52] did not establish significant evidence to indicate any relationship between these variables. A third economic factor is the unemployed population. Ref. [55] used the unemployment rate as an explanatory factor and, in their results, concluded that the higher the level of unemployment, the greater the social needs and the greater pressure on local governments to disclose information. In this sense, Ref. [42] identified a significant and positive relationship between the unemployment rate and the level of disclosure of information on sustainability. Refs. [52,56] all observed that municipalities with a high unemployment rate have lower levels of disclosure.

Therefore, the following hypotheses are proposed:

H₃: 

The level of indebtedness of a municipality is related to the disclosure of information on entrepreneurship.

H₄: 

There is a significant relationship between institutional capacity and the level of information disclosed on entrepreneurship.

H₅: 

The unemployed population is related to the level of disclosure of information on entrepreneurship.

2.3. Political Factors

Many studies confirm that political factors can influence the disclosure of this type of information in local governments, including variables such as the degree of political competition, defined as the number of political parties participating in the elections. In this sense, authors such as [31] consider that in those municipalities in which there is more political competition, the opposing political parties will exert greater pressure on the governing political party. As a result, the latter will tend to disclose more information [42].

Authors such as [45,46,48] discovered a statistically significant relationship between political competition and the disclosure of information, specifically on sustainability. Among the political factors, other authors point out that citizen participation in municipal elections is an indicator of information disclosure; indeed, greater voter participation leads to greater interest from citizens in government activities [56]. In other words, municipalities with higher participation rates will present higher levels of disclosure by municipalities [21].

Another of the political variables used is political rivalry; the fact that the party that governs at the time of study is more transparent can become decisive [42,57]. Finally, the gender of the mayor can be considered as an explanatory variable. Today, women have gained significance in Spanish culture and society. In this context, authors such as [42] found a significant effect between the mayor’s gender and the municipality’s level of transparency.

Based on these arguments, the following hypotheses are proposed:

H₆: 

There is a significant relationship between political competition and the degree of disclosure of information on entrepreneurship.

H₇: 

There is a significant relationship between the level of electoral participation and the level of information disclosed on entrepreneurship.

H₈: 

There is a significant relationship between political rivalry and the degree of information disclosed on entrepreneurship.

H₉: 

There is a significant relationship between the gender of the mayor of the municipality and the level of information disclosed on entrepreneurship.

3. Empirical Study

Selection of the Sample, Objectives and Methodology

In the study carried out by [33], an analysis was conducted using the information disclosed in the field of entrepreneurship for a sample of the 50 Spanish provincial capitals’ local governments, according to article 141 of the Spanish Constitution, corresponding to the period between February and May 2015. In order to accurately compare disclosure practices over time, the present study uses the same sample of Spanish municipalities from the period between February and May 2019. According to official data from the National Statistics Institute, the selected sample covers 14,898,433 resident inhabitants and is capable of yielding significant results in terms of the level of information offered to entrepreneurs.

In order to achieve the proposed objectives, we first intend to carry out a temporary study collecting data from the webpages of Spanish local governments at two points in time (2015 and 2019) to verify if the entities are involved in an evolution process aimed at satisfying the information needs expressed by users. In addition, we analysed whether this evolution occurred in all initial analysis axes. For this, the content analysis technique was used, which facilitates the systematisation of qualitative information. The instruments used to collect information were the indicators explained by [35], which have been used in previous studies [35], comprising a total of 49 indicators divided into five axes of analysis (

Table 1. Proposed analysis axes.

Analysis Axes	Definition	Indicator Number
Analysis axis 1	General information	10
Analysis axis 2	Information on resources and support to the entrepreneur	12
Analysis axis 3	Information on active entrepreneurship	10
Analysis axis 4	Information on digital entrepreneurship	6
Analysis axis 5	Information on disclosure and communication with the entrepreneur	11
Total		49

Source: [35].

).

The information collected allowed an index to be prepared in order to analyse the degree of disclosure of entrepreneurship that Spanish municipalities offer through their websites. For the elaboration of the index, a dichotomous scale was assigned to each indicator, that is, a value of 1 if the item was found in the analysed institutional portal and 0 in the case that it was not present [31,58].

Once the webpages of the different municipalities in the sample have been analysed, a series of disclosure indices were drawn up, with the aim of obtaining the type and degree of information on entrepreneurship that they offer. Thus, a measurement of the disclosure of information was carried out at two levels. First, disclosure was measured by municipality in each of the dimensions from an index of items (IDGE) and, second, a new index was calculated to obtain information for each selected municipality in the present study (IDG).

The disclosure obtained by each indicator (IDI) was calculated, building another indicator for each of the previously exposed dimensions (IDE), culminating the task by measuring the total disclosure of the sample (IDT). The indices can be seen as follows in

Table 2. Disclosure rates.

Index	Concept	Formula
Disclosure index by local government and axis of analysis (IDGE)	Measures the percentage of total disclosure of each local government in each of the analysis axes	${IDGE}_j=\left(\frac{{\sum }_{i=1}^M\left(Aij\right)}{M}\times p\right)\ast 100$
Disclosure index by local government (GDI)	Measures the total disclosure of each local government	${IDG}_j={\displaystyle \sum _{i=1}^E}\left({IDGE}_j\right)$
Disclosure index by item (IDI)	Measures the percentage of local governments that report each item	${IDI}_i=\frac{{\sum }_{i=1}^N\left(Aij\right)}{N}\times 100$
Disclosure index by analysis axis (IDE)	Measures the total disclosure of each axis of analysis	${IDE}_i=\left(\frac{{\sum }_{i=1}^M\left({IDI}_i\right)}{M}\times p\right)\ast 100$
Total disclosure index (IDT)	Measures the total disclosure of the sample	$IDT={\displaystyle \sum _{i=1}^E}\left({IDE}_i\right)$

Where M = number of items that make up each axis of analysis; E = number of analysis axes; Aij = takes a value of 1 if the characteristic that defines the indicator (i) is present in the local government (j), and 0 otherwise; N = number of local governments. As there is no empirical evidence on the importance of the different partial indices that make up the total index, the same specific weight is assigned to each of the dimensions (p = 20%).

.

In order to achieve the second objective of this study, and once the literature review had been carried out, the explanatory variables defined in previous sections were considered, as shown in

Table 3. Definition of explanatory variables.

Dimension	Variables/Hypothesis	Measures	Sources
Social Factors	Population size H1	Number of inhabitants of the municipal term. Data referring to the last revised registry of 2019	Instituto Nacional de Estadística http://www.ine.es/ (accessed on 17 April 2021)
	Dependent population H2	Dependency rate. Data referring to the last revised registry of 2019	Instituto Nacional de Estadística http://www.ine.es/ (accessed on 11 November 2023)
Economic Factors	Municipal debt H3	Public debt of the municipality (2019)	Ministerio de Hacienda y Administraciones Públicas http://www.minhap.gob.es/ (accessed on 11 November 2023)
	Institutional capacity H4	Total expenditure per capita (2019)	Ministerio de Hacienda y Administraciones Públicas http://www.minhap.gob.es/ (accessed on 11 November 2023)
	Unemployed population H5	Number of unemployed citizens (2019)	Servicio Público de Empleo Estatal http://www.sepe.es/ (accessed on 11 November 2023)
Political Factors	Political competition H6	Number of political parties participating in the elections. Data referring to the last municipal elections held in 2015	Dirección General de Política Interior del Gobierno de España http://www.infoelectoral.interior.es/ (accessed on 8 September 2022)
	Electoral participation H7	Abstention rate in the last elections. Data referring to the last municipal elections held in 2015	Dirección General de Política Interior del Gobierno de España http://www.infoelectoral.interior.es/ (accessed on 11 November 2023)
	Political rivalry H8	Political party in the last elections. Data referring to the last municipal elections held in 2015	Dirección General de Política Interior del Gobierno de España http://www.infoelectoral.interior.es/ (accessed on 8 Septiember 2022)
	Mayor’s gender H9	Mayor’s gender in the last elections. Data referring to the last municipal elections held in 2015	Dirección General de Política Interior del Gobierno de España http://www.infoelectoral.interior.es/ (accessed on 11 November 2023)

Own resource.

[35,59].

We proceed to carry out an explanatory analysis in order to identify the factors that significantly influence the disclosure of information on entrepreneurship in the town councils of Spanish capitals.

To contrast with the hypotheses that are initially raised, various statistical methodologies were used. A cluster analysis was carried out, similar to [46,60], which highlighted the five disclosure indices for each axis of analysis as variables.

The most suitable method used to estimate the optimal number of clusters to be used is, within the hierarchical methods, the agglomerative full linkage method (Complete Link or Farthest Neighbour). This method consists of knowing the distances or similarities between two individuals, observing which are the closest individuals in terms of this distance or similarity (which two individuals have less distance or greater similarity). These two individuals will form a group that were not separated again during the process.

Finally, to determine the possible association or independence between the initially proposed factors and the disclosure indices, the inferential statistical procedure was used to compare the means of the distributions of the quantitative variables in the different groups established by the categorical variable resulting from the cluster analysis.

The comparison of means was carried out through an analysis of variance (ANOVA). The estimation was made using SPSS 25 software.

4. Analysis and Discussion of the Results

4.1. Evolution of the Information Disclosure Index

Table 4. Evolution of the partial disclosure index.

Analysis Axes	${\mathit{I}\mathit{D}\mathit{E}}_{\mathit{j}}$
	2015	2019
General information	11.44%	12.14%
Information on resources and entrepreneur support	5.33%	10.30%
Information on active entrepreneurship	5.44%	10.36%
Information on digital entrepreneurship	10.60%	15.27%
Information on disclosure and communication with the entrepreneur	11.67%	14.53%

Own resources.

shows the results of the partial index of the disclosure of information on entrepreneurship, as well as its evolution in the year considered.

Likewise,

Table 5. Evolution of the total disclosure index.

Municipality	${\mathit{I}\mathit{D}\mathit{T}}_{\mathit{j}}$		Municipality	${\mathit{I}\mathit{D}\mathit{T}}_{\mathit{j}}$
	2015	2019		2015	2019
A Coruña	31.09%	55.23%	Madrid	70.36%	90.18%
Albacete	27.42%	48.56%	Málaga	70.36%	90.18%
Alicante	66.70%	82.68%	Murcia	67.03%	81.85%
Almería	29.42%	53.39%	Ourense	31.09%	52.39%
Ávila	27.42%	52.39%	Oviedo	27.42%	50.56%
Badajoz	37.09%	58.39%	Palencia	33.09%	55.39%
Barcelona	70.36%	90.18%	Palma de Mallorca	60.06%	74.55%
Bilbao	70.36%	86.44%	Palmas de Gran Canaria	45.24%	63.47%
Burgos	33.42%	54.56%	Pamplona	34.88%	56.03%
Cáceres	35.09%	56.39%	Pontevedra	29.42%	53.39%
Cádiz	65.03%	79.85%	Salamanca	67.03%	80.02%
Castellón	33.09%	58.23%	San Sebastián	56.24%	73.55%
Ciudad Real	37.09%	58.39%	Santa Cruz de Tenerife	50.58%	68.80%
Córdoba	27.42%	51.39%	Santander	61.70%	77.27%
Cuenca	25.42%	47.56%	Segovia	31.42%	55.39%
Girona	68.70%	81.94%	Sevilla	70.36%	90.18%
Granada	33.42%	56.39%	Soria	29.42%	51.56%
Guadalajara	29.42%	51.56%	Tarragona	61.70%	75.44%
Huelva	29.09%	51.39%	Teruel	27.42%	50.56%
Huesca	31.42%	52.56%	Toledo	39.09%	60.39%
Jaén	29.42%	52.39%	Valencia	68.55%	89.27%
León	29.42%	52.39%	Valladolid	68.70%	82.85%
Lleida	31.42%	53.56%	Vitoria	65.36%	78.27%
Logroño	27.42%	49.56%	Zamora	37.09%	58.39%
Lugo	27.42%	50.56%	Zaragoza	67.03%	83.77%

Own resources.

reflects the results of the total disclosure index achieved by each municipality.

As Table 4 and Table 5 illustrate, the notable increase in the information provided by the municipalities through their websites positively stands out. In 2015, the disclosure of information on entrepreneurship was scarce in most municipalities, whereas in 2019, there was an increase in the amount of information disclosed. An important fact to highlight, regarding a possible reason behind this noticeable increase, is the municipal elections that were held in 2015, which involved changes in the government, which we contrast below, in order to see if this increase may be due to political factors.

4.2. Explanatory Factors

Once the evolution of the information disclosure index had been analysed, we proceeded to investigate the explanatory factors that determine it. To achieve this, we chose to use the values of the index for the most recent study year (2019) as the dependent variable, as it contains the most up-to-date and complete information. First, a cluster analysis was performed. Figure 1 allows us to visualise the behaviour of the clusters in relation to the average of the index of the five analysis axes, whilst

Table 6. Municipalities corresponding to the different clusters.

CLUSTER 1 BAJO N = 18	CLUSTER 2 ALTO N = 19	CLUSTER 3 MEDIO N = 13
A Coruña	Alicante	Badajoz
Albacete	Barcelona	Burgos
Almería	Bilbao	Cáceres
Ávila	Cádiz	Castellón de la Plana
Córdoba	Girona	Ciudad Real
Cuenca	Madrid	Granada
Guadalajara	Málaga	Huesca
Huelva	Murcia	Lleida
Jaén	Palma de Mallorca	Palencia
León	Salamanca	Palmas de Gran Canaria
Logroño	San Sebastián	Santa Cruz de Tenerife
Lugo	Santander	Segovia
Ourense	Sevilla	Zamora
Oviedo	Tarragona
Pamplona	Toledo
Pontevedra	Valencia
Soria	Valladolid
Teruel	Vitoria
	Zaragoza

Own resources.

presents the municipalities of the Spanish capitals included in the three clusters identified based on the level of disclosure for each. As can be seen, the municipalities included in Cluster 2 stand out favourably and achieve the highest disclosure rates. Thus, there are 19 municipalities that present high levels of disclosure in the five established analysis axes.

Second, Cluster 1 contains the municipalities that disclose the least information in each of the dimensions. As can be seen, there are 18 municipalities classified in this group.

There is also a group of 13 municipalities that do not present a high level of disclosure but do not have low levels either, which allows them to be characterised as municipalities with medium disclosure. In all groups, information on digital entrepreneurship and information on dissemination and communication with the entrepreneur are the dimensions with the highest scores. On the contrary, in the three clusters, the information on resources and support for the entrepreneur denote the dimensions with the lowest scores.

A mean difference analysis was performed, which compares the means of the distributions of the quantitative variables in the different groups established by the categorical variable from the cluster analysis. Since there were three groups, ANOVA was carried out. Previously, we proceeded to verify that the quantitative variables met the assumptions of normality and homoscedasticity. For this, the Kolmogorov–Smirnov contrasts and the Levene test are carried out, respectively. Because the size of the population, municipal debt, institutional capacity, unemployed population and electoral participation did not fulfil the assumptions of normality, a transformation of the variables was carried out using the Neperian logarithm. The results obtained are reflected in

Table 7. Variable tests of normality and homogeneity.

	Kolmogorov–Smirnov			Homogeneity
	Statistic	gl	Sig.	Levene	df1	df2
Population size	0.088	50	0.200	2	47	0.251
Dependent population	0.069	50	0.200	2	47	0.556
Municipal debt	0.114	50	0.136	2	46	0.616
Institutional capacity	0.101	50	0.200	2	47	0.304
Unemployed population	0.067	50	0.200	2	47	0.731
Political competition	0.115	50	0.094	2	47	0.302
Electoral participation	0.092	50	0.200	2	47	0.946

Own resources.

. We verified that all the study variables met the assumptions of normality and homogeneity (p> 0.05), so we used the ANOVA F test to perform the proposed contrasts.

Table 8. Analysis of variance.

		Population Size	Dependent Population	Municipal Debt	Institutional Capacity	Unemployed Population	Political Competition	Electoral Participation
CLUSTE	Mean	11.6521	55.4300	10.2002	18.5644	8.9440	10.11	37.520
	S.D.	0.62994	4.19428	2.06304	0.58382	0.79843	2.847	5.1639
CLUSTER 2	Mean	12.8102	55.5200	11.8498	19.8983	10.0560	14.33	37.431
	S.D.	0.93006	5.03125	1.47336	0.97784	0.92476	4.201	5.1224
CLUSTER 3	Mean	11.6725	53.7207	10.0564	18.5927	9.0395	11.14	36.751
	S.D.	0.60775	4.64091	1.37521	0.68194	0.81816	3.035	5.1879
Total	Mean	12.0747	54.9838	10.7680	19.0525	9.3711	11.92	37.273
	S.D.	0.91995	4.60807	1.85631	0.99200	0.98295	3.859	5.0601
ANOVA	F.	13.621	0.724	5.831	16.833	9.149	7.258	0.101
	Sig.	0.000 ***	0.490	0.006 ***	0.000 ***	0.000 ***	0.002 ***	0.904

Own resources. Notes: (***) = significant at the 1% level

summarises the results of the cluster analysis for each of the variables considered in this study, with the exception of the “political rivalry” and “mayor’s gender” variables, for which we used a non-parametric contrast. Firstly, regarding the “population size” variable, we observed that the municipalities with the largest populations are those with the highest levels of disclosure (Cluster 2), while the municipalities that disclose the least are those with the smallest population size (Cluster 2). The F value is 13.621 with an associated probability of 0.000. We can therefore say that there are significant differences between the means in the different clusters, which leads us to accept/reject H₁.

We conclude that there is a significant and positive relationship between population size and the level of disclosure of information on entrepreneurship. Second, if we analyse the results of the “dependent population” variable, we observe that there are no significant differences between the three considered clusters (F = 0.724 and p = 0.490). In this case, the variable does not significantly explain the disclosure rates. Therefore, H₂ must be rejected.

If we analyse the “municipal debt” variable, there are significant differences between the three clusters considered (F = 5.831 and p = 0.006), so this variable significantly explains the values of the disclosure indices and we should accept H₃.

The results with respect to the “municipal debt” variable indicate that the Spanish municipalities that disclose the most information present higher levels of education compared to the municipalities with less disclosure, which are those with the lowest educational level.

Observing the statistic (F = 16,833) and its probability (p = 0.000), we conclude that there are significant differences between the means of the different clusters, so we accept H₄. In relation to the “unemployed population” variable, we verify that there are significant differences (F = 9.149 and p = 0.000). Consequently, both variables are related, so we accept H₅. We thus confirm the conclusions of [52,56,61] regarding these authors discovering a relationship between both variables. Regarding the “political competition” variable, the results reveal that there are significant differences between the three clusters identified (F = 7.258 and p = 0.002), so this variable significantly explains the disclosure indices and hypothesis H₆ is accepted. Finally, for the “voter turnout” variable, we verify that there are no significant differences between the three clusters (F = 0.101 and p = 0.904); therefore, H₇ must be rejected.

We analysed the two qualitative variables: “political rivalry” and the “mayor’s gender”. Thus, according to the classification of municipalities by political sign (

Table 9. Distribution of municipalities in relation to political rivalry.

	CLUSTER 1		CLUSTER 2		CLUSTER 3
Party	F	f	F	f	F	f	Total
Conservative	13	44.8%	5	23.8%	18	36.0%	29
Liberal	5	23.8%	8	38.1%	18	36.0%	21
Total	18	36.0%	8	38.1%	14	28.0%	50

Own resources.

), the formation of clusters reveals that the majority of conservative municipalities are located in Cluster 1, while liberal municipalities are concentrated in Cluster 2.

Regarding the mayor’s gender (

Table 10. Distribution of municipalities in relation to the mayor’s gender.

	CLUSTER 1		CLUSTER 2		CLUSTER 3
Gender	F	f	F	f	F	f	Total
Men	14	36.8%	14	36.8%	10	26.3%	38
Women	4	33.3%	4	33.3%	4	33.3%	12
Total	18	36.0%	18	36.0%	14	28.0%	50

Own resources.

), most of the municipalities are presented in a balanced way among the three clusters. Therefore, no evidence has been found to indicate that the level of disclosure of information on entrepreneurship is related to political rivalry or the gender of the mayor.

In view of these findings,

Table 11. Results of the analysis of the research hypotheses.

Hypotheses	Statistic Verification
H1: There is a significant relationship between the size of the population and the level of disclosure of information on entrepreneurship.	Verified
H2: There is a significant relationship between the dependent population and the level of disclosure of information on entrepreneurship.	Not Verified
H3: The level of indebtedness of a municipality is related to the disclosure of information on entrepreneurship.	Verified
H4: There is a significant relationship between institutional capacity and the level of information disclosed on entrepreneurship	Verified
H5: The unemployed population is related to the level of disclosure of information on entrepreneurship.	Verified
H6: There is a significant relationship between political competition and the degree of disclosure of information on entrepreneurship	Verified
H7: There is a significant relationship between the level of electoral participation and the level of information disclosed on entrepreneurship.	Not Verified
H8: There is a significant relationship between political rivalry and the degree of information disclosed on entrepreneurship.	Not Verified
H9: There is a significant relationship between the gender of the mayor of the municipality and the level of information disclosed on entrepreneurship.	Not Verified

Own resources.

presents a synthesis of the results of the analysis of the raised research hypotheses.

5. Discussion and Implications

The present study attempts to fill the gap in research on the information that municipalities disseminate about entrepreneurship through their websites, a topic little studied to date.

The study focuses on the evolution of the degree of dissemination of information on entrepreneurship in 50 Spanish municipalities corresponding to the period 2015–2019, in order to analyse the level of information they disseminate through their web pages, as well as its possible explanatory factors. The content analysis technique was used, based on a dichotomous scale to collect information from the web pages of the municipalities of the sample under study based on the five established axes of analysis. Results were obtained that show an increase in the amount of information disclosed from 2015 to 2019: 0.7% for the general information axis, 4.86% for the information axis on resources and support for the entrepreneur, 4.92% for the information axis on active entrepreneurship, 4.67% for the information axis on digital entrepreneurship, and 2.86% for the information axis on dissemination and communication with the entrepreneur.

In order to investigate the explanatory factors that determine this increase in disclosure in 2019, the values of the 2019 index were used as dependent variables and social factors (population size and dependent population); economic factors (municipal debt, institutional capacity and unemployed population)and political factors (political competition and electoral participation)were used as independent variables. To do this, a cluster analysis and an analysis of variance were carried out, with the intention of being able to verify the existence of an association between the proposed conditions. The findings allow us to accept all the hypotheses raised in the research, except H₂, H₇, H₈ and H₉.

It can be said, therefore, that the dissemination of information about entrepreneurship can be a powerful tool for local economic development and the promotion of a solid business ecosystem. However, its success depends on the effective implementation of policies that promote inclusion, equity and long-term sustainability.

6. Conclusions, Implications, Limitations and Future Lines of Research

The present study attempts to fill the gap that exists in the research concerning the information that municipalities disseminate on entrepreneurship through their websites, a subject rarely studied to date. In accordance with the objectives set out in this study, the first conclusion considered is that, increasingly and in general, city councils are aware of and concerned about the aspects of entrepreneurship in municipalities.

However, in response to the first research question posed at the beginning of this study, it can be said, referring to the results obtained, that the dissemination of information about entrepreneurship has experienced a notable increase in the amount of information disclosed about the entrepreneurship during the period between 2015 and 2019 through government websites. A possible reason for this notable increase could be the municipal elections that were held in 2015, which caused changes in the government.

Regarding the second research question, it is evident that the factors that explain the entrepreneurship disclosure rate are the size of the population, municipal debt, institutional capacity, the unemployed population and political competition. However, it has not been possible to verify any type of association with the dependent population and electoral participation.

This study focuses on the evolution of the degree of disclosure of information on entrepreneurship of the 50 Spanish municipalities corresponding to the period 2015–2019, with the purpose of analysing the level of information that they disseminate through their websites, as well as its possible explanatory factors.

Regarding the analysis of the qualitative characteristics in the different clusters, no empirical evidence has been found to verify that the level of disclosure of information on entrepreneurship can be favoured by political rivalry and the mayor’s gender. With these results, the municipalities can now focus their practices and policies on the dissemination of information on entrepreneurship in regard to the factors that have or do not have an effect on the level of disclosure.

In terms of implications, it can be considered that, with regard to the academic field, the study contributes an explanation of what is happening in relation to the disclosure of information on entrepreneurship in the public sector.

As far as local administration is concerned, this study aims to expand the previous literature, as well as to encourage those responsible for public entities to improve the dissemination of information on entrepreneurship through the internet. So far, the few studies that examine the disclosure of information on entrepreneurship by municipalities have examined the effects of different factors (social, economic and political) without actually studying the contribution of these factors online to transparency on environmental, social and economic sustainability. Consequently, and in terms of future research, it would be convenient to approach the study by analysing whether the disclosure of information from the studied sample also contributes to transparency in terms of sustainability.

Spanish municipalities are aware and concerned about the aspects related to entrepreneurship in the municipalities. The dissemination of information about entrepreneurship experienced a notable increase during the period between 2015 and 2019. With the results of this study, it is concluded that municipalities can now focus their practices and policies on the dissemination of information about entrepreneurship with respect to the factors that do or do not have an effect on the level of disclosure.

On the other hand, it should be noted that this work has several limitations that also imply more future lines of research for its authors. Firstly, the inevitable subjective judgment of the researchers inherent in obtaining the information collected from the city council websites, as well as the dichotomous scale of the disclosure index, may not capture the quality or depth of the information disclosed by the municipalities. Furthermore, the sample under study is small, limited only to 50 municipalities of Spanish provinces, leaving out the rest of the Spanish municipalities, so this sample may not be representative of the entire country. On the other hand, we are aware of the limitation of the chosen time period. However, despite the aforementioned limitations, the results are interesting enough to justify and expand research by carrying out longitudinal studies and comparative analyses with other countries or regions, as well as considering their evolution over time.