THE INTERNET AND ELE TORAL MO ILIZATION IN DUTH … · 2014-08-28 · To answer these two questions we will use a theoretical model in which we both explain the adoption of ... necessary

Paper for EGPA Conference, Speyer (Germany), 10-12 September 2014

THE INTERNET AND ELECTORAL

MOBILIZATION IN DUTCH LOCAL

GOVERNMENT ELECTIONS.

BAS DENTERS & WOUTER JANS1

INSTITUTE FOR INNOVATION AND GOVERNANCE STUDIES,

UNIVERSITY OF TWENTE, THE NETHERLANDS

INTRODUCTION

Information and communication technologies (ICT) provide new opportunities for electoral

mobilization. A well-known use of ICT in the electoral process is e-voting in which electronic

systems are used to aid casting and counting votes. But ICT can be used to boost the turnout in

elections and to inform the public about the elections and what is at stake at the polls. It is now

widely recognized that new ICT applications have the potential as a powerful tool in modern

election campaigns. We have entered into a new age of political communication in which old ways

of mobilizing and communicating with voters are supplemented with or replaced by web-based

means of communication (Blumler & Kavanagh 1999; Hindham 2009; Karlsen 2010; Karlsson 2013).

Many of these new means of campaign communication are party-controlled (Karlsen 2010). But

increasingly we also see the rise of applications that are not party-controlled. Such independent

(uncontrolled) means of communication are not only provided by the press, but we also see that

governments are conducting “get out the vote” campaigns. Just like the EU and national

governments, we see that local governments in various countries are active in this domain and use

web-based means of communication in the voter mobilization campaigns.

1 This is a working paper based on preliminary analyses, therefore this paper should not be quoted without the prior

consent of the first author. This research is conducted by a research team that not only includes the two authors but also prof. dr. Ariana Need and dr. Minna van Gerven-Haanpää. In subsequent versions of this paper these colleagues will also be included as co-authors.

IGS, University of Twente The internet and electoral mobilization in Dutch local government elections

2

In the UK there is even a private company (UK Engage) that provides a wide range of oftentimes

ICTbased services to help municipalities and other public sector organizations in publicizing their

elections and facilitating the act of voting. In this paper we analyze data on the use of ICT in

“getting out the local vote” in Dutch municipalities. For 377 municipalities in which there were local

elections in 2014 we have collected 15 indicators regarding the use of ICT in the electoral

mobilization: ranging from providing web-based practical information on the election, location and

opening hours of polling station, etc.; providing information on campaign events; links to sites of

political parties and information about party platforms and candidates; offering one or more voting

advice applications (VAA) and a municipality’s use of new social media in the campaign.2 In this

paper we ask two questions:

1. How can we explain differences in the use of ICT tools for electoral mobilization between

Dutch municipalities in the 2014 municipal elections?

2. To what does the use of ICT tools for electoral mobilization by Dutch municipalities have an

effect on the level of turnout in the 2014 municipal elections?

In answering the second question we will look at the effect of ICT mobilization in the context of

other municipal factors that also may have an impact on turnout.

THEORETICAL MODEL

To answer these two questions we will use a theoretical model in which we both explain the

adoption of technological innovations in local government and subsequently also explain how this

technological innovation and other factors can have an impact on electoral turnout. The theoretical

model is based on the assumption that in political contexts actors decide on the basis of

preferences with regard to a set of choice options (or opportunities), and in the light of the

resources of the actor.3

ADOPTING TECHNOLOGICAL INNOVATIONS

Technological innovations, like the adoption of new ICT tools for electoral mobilization, may be

conceived as a form of policy innovation. In the political science literature innovations are

traditionally defined as the introduction of a program that is new to the governmental jurisdiction

that is adopting it (Walker 1969: 881; Berry & Berry, 1999: 169). Thus, in a particular context a

program may be “innovative” even though several years before the same program was already

implemented in other jurisdictions.

2 For three of the 380 municipalities that held elections in 2014 we were unable to visit the local website.

3 The latter two factors define what economists call an “opportunity set”: the available opportunities or choice options

that an actor can realize with the resources that he commands.


3

Various researchers of policy innovations have argued that decisions to adopt “new” programs are

influenced by the preferences of actors. Braun and Gilardi (2006) have argued that the willingness

to innovate might be influenced by two types of considerations.

First, from a “policy-seeking” perspective politicians may be inclined to adopt a program because it

helps them in solving an important social or political problem. The more serious the problem in a

particular jurisdiction, the more likely it is that a new policy or measure that promises to reduce the

problem will be adopted. Although there may be some debate about whether or not a high degree

of electoral abstentions is a problem or not, many local politicians consider the current level of

turnout as problematic. And likewise an increase in abstentions is also seen as undesirable. For this

reason we expect that:

The higher the level of abstention in the previous municipal election (hypothesis 1.1)

and the larger the increase in abstentions between the last previous elections

(hypothesis 1.2) in a municipality are, the more ICT-based tools for electoral

mobilization will have been implemented in this municipality

Moreover the likelihood of adoption of a new program is higher if the expected effectiveness of the

solution is higher. In municipalities where internet access is better and where digital literacy is

higher, investments in an internet-based electoral mobilization campaign are more likely to be

rewarding than elsewhere. Unfortunately we do not have direct measures for internet access and

digital literacy. But in the literature on the so-called digital divide there is ample evidence

thatinternet access and digital literacy are closely related to income, education and other indicators

of citizens’ socio-economic status. Moreover, it is also recognized that internet use and digital skills

are relatively widespread amongst the younger generation (Norris 2001; Van Dijk & Hacker 2003;

Mossberger, Tolbert & McNeal 2012). For this reason we hypothesize that:

The higher the percentage of the population with higher education (hypothesis 2.1),

the higher the per capita disposable income (hypothesis 2.2), and the larger the 15-25

age cohort in a municipality (hypothesis 2.3) are, the more ICT-based tools for electoral

mobilization will have been implemented in this municipality.

Second, politicians may also be motivated by electoral motives (office-seeking): for a successful

political career they depend on their electoral success. In a more competitive environment they

face more severe challenges and are therefore more likely to invest in voter mobilization. If in a

locality the political arena is dominated by one large party that commands a solid council majority,

this party is not seriously challenged to mobilize the vote because it can be pretty confident about

the continuation of its dominance. In a setting where the balance of power is more equal parties

cannot be as complacent and have to invest more in efforts to mobilize voters.4

4 The effective number of parties (Laakso & Taagepera 1979) is an often used measure for electoral competition

(Denters 1987: 61-63). It is based on the number of political parties competing in a municipal election or council, taking


4

Therefore we expect that:

The higher the electoral competition in a municipality is, the more ICT-based tools for

electoral mobilization will have been implemented in this municipality (hypothesis 3).

In our model we also assume that the opportunity structure and resources of municipalities affect

their adoption of ICT innovations. Municipalities have many internet-based options available to

municipalities to use the internet in efforts to boost turnout in local elections.5 The degree to which

such opportunities may be used is not only determined by the local needs and preferences but also

by the availability of necessary resources. The use of ICT and especially the more sophisticated tools

requires a degree of expertise and experience that may not be available in each and every

municipality. For this reason we hypothesize that:

The stronger the municipal track record of using the internet in other domains (like in

e-services) is, the more ICT-based tools for electoral mobilization will have been

implemented in this municipality (hypothesis 4).

In addition to these factors we will also include the population size of municipalities. This factor

might affect the likelihood of ICT innovations. First, it is clear that increasing size of municipalities

makes intensive personal contacts between politicians and their electorate more difficult (e.g. Dahl

& Tufte 1973; Denters et. al 2014). In large municipalities – with the rising popularity of the internet

– web-based communication may therefore be seen as an attractive alternative strategy for

political communication, especially during electoral campaigns. At the same time, the size of a

municipality is also likely to have a positive effect on the availability of financial resources that are

necessary to purchase fancy new applications (like VAA’s) and to hire the ICT specialists who can

implement such state-of-the-art tools. Therefore we expect that (directly and indirectly)

The larger the population size of a municipality is, the more ICT-based tools for

electoral mobilization will have been implemented in this municipality (hypothesis 5).

EXPLAINING ELECTORAL TURNOUT

After having identified major factors that may explain the adoption of ICT innovations in electoral

mobilization policies it is now time to develop a theoretical model that will help in explaining the

effects of such ICT innovations on the turnout in municipal elections. We identify three main factors

that may explain the level turnout:

into account their relative size. The higher the score, the more competitive and politically diverse a municipal political arena is.

5 In the Netherlands during the period 1991 and 2009 electronic voting machines were used throughout all polling

stations in order to facilitate the voting process. In 2009 the use of these machines was discontinued because of concerns about the verifiability of election results. Since the Dutch legislation rules out this option to facilitate voting, but as we will see there are numerous other options for municipalities to facilitate voting and boost turnout.


5

Engagement (the preferences, motives and values of the local electorate);

Resources (the time, money and civic skills of voters) and

Mobilization (creating opportunities for participation and stimulating the use of these

opportunities).6

In this paper we will use this basic model to explain inter-municipal variations in electoral

participation of citizens. In our analysis we are of course primarily interested in the effects of one

aspect of the mobilization of voters, namely the use of ICT to stimulate people to participate in

municipal elections. But in order to get an adequate picture of the effects of this specific factor we

will have to view its impact in a broader perspective, including also the potential impact of other

explanatory factors. Therefore we formulate a number of hypotheses.

MOTIVATIONS

First, we focus on motivational factors. In the political science literature we find a distinction

between instrumental and expressive motives for civic participation (Brennan & Lomasky 1993;

Verba c.s. 1995: 102; Schuessler 2000).

Instrumental motives relate to efforts that people make with the aim to influence the outcomes of

the political process according to their personal preferences or to protect personal or group

interests. A key interest of citizens is the protection of their “property and estate”. For most voters

the most valuable property they may own is their home. For home-owners, municipal policies are

important. To begin with, through its policies (for example zoning and planning decisions) the

municipality can have a substantial impact on the value of these homes. Moreover, the main

municipal tax in Dutch municipalities is a highly visible property tax. Therefore in line with Johnston

et al. (2001) we can expect that housing tenure matters. We therefore hypothesize that:

The higher the percentage of housing tenure in the municipal housing stock the higher

the turnout rate in the municipal election will be (hypothesis 6).

In a similar vein we assume that turnout is likely to be affected by the local tax burden. The higher

the tax burden, the more perceptible local government is for its citizens and the more salient local

elections are likely to be. Therefore we hypothesize that:

6 This model is based on the Civic Voluntarism Model US (Verba c.s. 1995: 269-287. The factors in this model are similar

to the three main factors we used to explain decisions on the adoption of innovations in the previous section. For the

engagement (motivations and preferences) and the resources this is immediately obvious. The mobilization factor is

about creating participatory opportunities (institutionalization) and raising the public’s awareness about the availability

of these options (recruitment). In their book Verba c.s. put a lot of emphasis on the recruitment (asking) of citizens

through non-political institutions of adult life (workplace, voluntary associations and the church). But in our view

mobilization should be interpreted more broadly, to include political mobilization by using new ICT to introduce new

participatory opportunities and to raise public awareness of these opportunities.


6

The higher the local tax burden is (hypothesis 7.1) and the larger the pre-election

increases in the local tax burden (hypothesis 7.2) in a municipality are, the higher the

turnout in the municipal election will be.

It is widely accepted that the decision to vote is likely to be determined to a considerable degree by

non-instrumental, expressive motivations (Brennan & Lomasky 1993; Verba c.s. 1995: 102;

Schuessler 2000). Such expressive motivations include the degree to which citizens consider voting

as a civic duty (Campbell et al. 1971; 1980) and various forms of social embeddedness (Miller &

Shanks 1996), e.g. one’s attachments to the local community. Both the sense of civic duty and local

iattachments are likely to be stronger amongst older age groups. Therefore we expect that age –

through such unmeasured intervening variables – is likely to affect turnout (e.g. Strate et al. 1989).

Here the 65-80 age cohort is of particular interest because this is the group that was raised in a

period that in the Netherlands voting was still compulsory. Therefore we hypothesize that:

The larger 65-80 age cohort in a municipality is, the higher the turnout in the municipal

election will be (hypothesis 8).7

RESOURCES

Electoral turnout is also positively affected by the resources available to citizens. Verba c.s have

pointed out that for participation three resources may be important: civic skills/education, income,

and time. These resources are typically strongly related to socio-economic background variable

(Verba c.s. 1995: 281-283), and in our analysis we will therefore use such characteristics to explain

turnout. First we hypothesize that:

The higher the proportion of the municipal population (between 15-65 years of age)

with higher education is, the higher turnout in the municipal election will be

(hypothesis 9).8

In addition to the degree of formal education Verba c.s. have also pointed at the importance of

language skills. In their research they use a survey-based indicators for the richness of a

respondent’s vocabulary and the domestic use of the official national language. As a proxy for such

language skills we will use the size of the immigrant population. We hypothesize that

The larger the relative size of the immigrant population in a municipality is, the lower

the turnout in the municipal election will be (hypothesis 10).

In previous studies, income was frequently found to be an important determinant of various forms

of citizens’ political participation.9 Therefore, we also hypothesize that:

7 We exclude the age group of 80+ because due to health and mobility related reasons these elderly people are likely to

find it increasingly more difficult to participate actively in social and political life.

8 The minimum voting age in the Netherlands is 18 years. But for reasons of data availability we will use this indicator as

a proxy measure (data on education level are only available for residents in this age bracket).


7

The higher the per capita disposable income in a municipality is, the higher the higher

turnout in the municipal election will be (hypothesis 11).

The third major resource in the model relates to the time that people will have available. Direct

measures for the time factor are also not available. But it seems plausible that working people

(especially if they are working full time) and people who have to travel a long way to their job will

have less free time available and may be less flexible in finding the opportunity to vote on election-

day than others. Therefore we expect that:

The larger the proportion of the population with paid employment (hypothesis 12.1),

the higher the percentage of the employed population with full-time employment

(hypothesis 12.2) and the larger the working population’s travel distance between the

municipality of work and the municipality of residence (hypothesis 12.3) are, the lower

the turnout in the municipal elections will be.

MOBILIZATION

Mobilization is both about the available opportunities for participation and the efforts made to

make people aware of these opportunities and to persuade them to use these. In our research we

include both aspects of mobilization.

A major factor that is likely to affect both the opportunity structure for electoral participation and

the efforts that local parties and politicians are likely to make to mobilize voters in elections is the

degree of electoral competition in a locality. For the voter the elections are more interesting, they

have a genuine choice and their vote may actually have some impact. And for parties, a more

competitive political arena (where the effective number of political parties is higher) will imply the

need to make more efforts at mobilizing the electorate. Therefore we hypothesize that:

The higher the effective number of parties in a municipality is, the larger the turnout in

the municipal election will be (hypothesis 13).

A second factor that is likely to affect the participatory opportunity structure in a locality is the

population size of the municipality. With regard to the effects of size there are essentially two

theoretical arguments (Dahl & Tufte 1973, Verba et al. 1995; Denters et al 2014). On the one hand

the mobilization model hypothesizes that size may have a positive effect on turnout, because larger

municipalities will provide a more differentiated organizational ecology (Baglioni et al. 2007).

Moreover a well-functioning local press developed media landscape, that may be typical for larger

municipalities, is also likely to mobilize voters (see Baekgaard et al. 2014). In part this size effect

may be indirect – operating through the higher degree of political competition that is likely to go

9 At the individual level high income many studies were have confirmed such a relation (references to be added). At the

aggregate level (Powell / Blais 2006).


8

hand in hand with increasing size. But in part there might also be a residual direct effect through

unmeasured variables like the diversity of its organizations. On the other hand the decline of

community model implies a negative size effect. This model argues that in small municipalities local

politics is relatively simple. Citizens personally know their representatives and strong community

ties stimulate widespread participation. With increasing size such community characteristics will

decline and this is expected to have a negative impact on electoral turnout. Although theoretically

there are two contradictory expectations, the empirical evidence is clearly in support of a negative

size effect (both on the basis of macro-level analyses: Geys 2006: 642-643; and on the basis of

individual level data: Denters et al 2014, chapter 10). Therefore we hypothesize that:

The larger the population size of a municipality, the lower the turnout in the municipal

election will be (hypothesis 14).

The literature on determinants of electoral turnout also emphasizes the importance of electoral

laws and measures to facilitate voting (Blais 2006; Franklin 2002). In the Dutch context the national

parliament in the local government act and the electoral laws has provided municipalities with a

uniform framework for organizing municipal elections. In this uniform legal framework, however,

municipalities are free to take additional measures to stimulate turnout. In this article we

concentrate on a number of such measures where municipalities can use ICT-based measures to

boost turnout. From its early days onwards the rise of the Internet has given rise to great

expectations (as a major force in democratizing our political systems), gloomy perspectives (either

Orwellian fears about Big Brother or worries about a digital divide) or skepticism (based on the idea

that the new technologies are not likely to have a major impact).10 In this paper we will test

whether internet mobilization by municipalities has a positive impact on local turnout. An earlier

study in Norway by Saglie and Vabo (2009) based on individual level data, shows that there may

indeed be a positive effect on local political participation of municipal efforts to facilitate

participation through the internet. Therefore we hypothesize that:

The more a municipality has implemented ICT-based tools for electoral mobilization,

the higher the turnout in the municipal election will be (hypothesis 15).

METHODS AND DATA

Before we can test these hypotheses we will outline the design of our research. This paper will be

based on an analysis of aggregate data about 377 Dutch municipalities that held municipal elections

on March 19 2014. In the remaining Dutch municipalities there were no municipal elections

because these municipalities were or will be involved in amalgamation reforms and elections

already took place or will be organized at a later date. In order to answer our research questions we

used OLS multiple regression analyses.

10 For an early overview see Van den Donk & Tops (1994) and more recently Hindman (2009)


9

The data for this research are in part collected by means of a content analysis of 377 municipal

websites and for another part by collecting official statistics collected for these 377 municipalities.

For the analysis of municipal websites we visited the sites of all these municipalities in the period

from 7 – 10 March 2014.

TABLE 1: ITEMS OF INTERNET MOBILIZATION INDEX (IMI-INDEX)*

Homepage Does the homepage contain an announcement of the municipal elections taking place on 19 March 2014?

Practical info Does the website provide practical information about the voting procedures, opening hours of polling stations, absentee ballots et cetera?

Party links Does the municipal website provide a page with links to the websites of local parties that are competing in the 2014 election?

Campaign events Does the website provide information on events that are part of the election campaign (electoral debates, information markets etc. media events)? ,

Programs Is it possible to download the party programs of the parties that are competing in the election from the municipal website?

Campaign content Is it possible to download (or consult) written information about the municipal elections about the importance and organization of these elections and/ or an overview of party positions (e.g. by a local newspaper) on the municipal website?

VAA Does the municipality provide its citizens with the opportunity to use of one or more of the available Voting Advice Applications (VAA)?

Video / Audio Does the municipality use video or audio fragments to inform about the imminent elections on its website?

Social media Does the municipal website explicitly refer to social media (e.g. Facebook or Twitter) that provide information on the elections? Or is it possible to ask questions on the elections through Skype?

* All these nine items are dichotomous

On the basis of a data collection protocol we collected data about the provision of information

about the upcoming election on the municipal website. These data were subsequently used for

constructing an index for measuring the broadness of the information and the facilities that were

offered to the local citizens to inform themselves about the elections, the candidates and the local

parties. Table 1 provides an overview of the items that were included in this IMI index.

In this paper the IMI index is the central variable. But for answering our research questions we had

to collect additional information about the other variables in our two stage explanatory model.

Most of these data were collected through the STATLINE website of Statistics Netherland (CBS) on

the first of July 2014. Data on the 2014 election results were retrieved form the website of the

Dutch Election Council (Kiesraad). The effective number of parties was computed using data on the

2010 elections, retrieved from the website nlverkiezingen.com; visited on 26-6-2013). The data on


10

municipal tax burdens were retrieved from the Groningen University COELO website. In appendix A

we have specified the exact measures used for these variables and the source of these data.

EMPIRICAL FINDINGS

Before we turn to the research questions we will first provide some descriptive information about

the IMI index and its different indicators. Subsequently, we will try to explain why some

municipalities are more active in ICT-based getting out the vote campaigns than others (research

question 1). And finally we will also look into the effects of such campaigns on the 2014 electoral

turnout in Dutch municipalities (research question 2).

INTERNET VOTER MOBILIZATION BY MUNICIPALITIES

Our analyses show that virtually all the municipalities where elections were held in 2014 in one way

or another paid attention to this event on their website.11 In Figure 1 we provide some basic

information about the frequencies of the different tools and types of information that

municipalities provide through their websites.

On the basis of Figure 1 we can conclude that almost all municipalities pay some attention to the

elections on their website. Minimally they provide information on the date of the elections and

other types of basic information, for example about opening hours and locations of polling stations

et cetera. About 90 percent of the municipalities give the event of the election a prominent place

on the website (on the municipality’s home page). Quite a lot of the municipalities also provide

links to the websites of the local parties (59%) and inform the public about campaign events (43%).

All the other types of content are provided by less than a third of the municipalities. The number of

municipalities that provide more advanced applications, like VAA, Video and Audio, and new social

media like Twitter, Facebook or Skype is limited. Even so, in the light of the substantial costs

involved, it is remarkable that about every fourth municipalities has subscribed to one of the

available VAA’s.12

On the basis of a principal components analysis (PCA) of the nine items we can distinguish between

three types of information:

Basic information: practical information (available on the municipality’s homepage) and the

provision of links to local party websites.

11 For three municipalities we were unable to access the municipal website in the period of data collection.

12 This figure has to be treated with some caution. We are in the process of validating this finding, by checking with the

VAA providers. So far this validation effort suggests that our findings for the VAA indicator are reasonably accurate, but there are differences in between the reports of the providers and the municipal websites. Probably we somewhat underestimate the use of VAA by municipalities. In part this may be the result of municipalities not putting a link to a municipal VAA on their website. In other cases the VAA may be commissioned not by the municipality but by another local organization (e.g. a newspaper or broadcasting company). In a subsequent version of this paper we will be able to provide a more detailed account of the results of this validation exercise.


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Campaign related information: informing about events and substantive themes in the

campaign, and making party programs available through the municipal website

Advanced applications: VAA’s, Audio/Video and new social media

FIGURE 1: FREQUENCY OF DIFFERENT (IN %) TYPES OF CONTENT PROVIDED ON MUNICIPAL WEBSITES

(N=377); for explanation of labels see Table 1.

In this paper we will only use the IMI index which is based on a simple count (the IMI index) of the

nine dichotomous items. This scale ranges between 0 and 9. Figure 2 shows that most

municipalities provide only limited information on their website. The mean scale score for

municipalities is 4,03 (with a standard deviation of 1,69).

FIGURE 2: NUMBER OF CONTENTS OFFERED ON MUNICIPAL WEBSITES, IN % OF ALL MUNICIPALITIES

(N=377; mean: 4,03; standard deviation 1,69 )

96% 89%

59%

43%

28% 26% 26% 21% 15%

0%10%20%30%40%50%60%70%80%90%

100%

1,1

14,1

24,1 22,5

18

10,6

6,1

2,7 0,8 0

0

5

10

15

20

25

30

0 1 2 3 4 5 6 7 8 9


12

It is also clear from the figure that most municipalities offer only rather limited content. Actually

more than 60 percent of the municipalities provide less than the average (about 4 types of

content), and only 20 percent offers more than this average.

ADOPTING TECHNOLOGICAL INNOVATIONS: PRELIMINARY FINDINGS

In the introduction of this paper we have formulated two questions with regard to the use of ICT in

the process of electoral mobilization in Dutch municipalities. The first question concerns the

adoption of ICT innovations in electoral mobilization. We have developed a theoretical model that

is aimed at answering this question. In this section we will present the results of OLS regression

analyses to test the empirical validity of this model. In Table 2 we present the preliminary results of

this analysis.13 In our analysis we have entered our explanatory variables stepwise. Following the

logic of our theoretical model we will set out to identify the possible effects of the motivational

variables and the resources. Before we enter these two blocks of variables in the analysis however,

we will first introduce the municipal size, because the size factor – as we explained in the

theoretical section – is related to motivational factors but also is likely to affect the availability of

resources. In the final step of the analysis we enter all explanatory factors and can establish the

direct effects of all these variables.

If we consider the results it is clear that municipal size is a significant factor in the explanation of

the ICT mobilization efforts. In model 1 – where it is the only explanatory factor – size has a

relatively strong bivariate effect (0.42) and this effects is only somewhat weakened (0.32) when we

control for the effects of other model variables. This suggests that the bivariate size effects, for the

most part, is not the result of indirect effects of size through the variables entered in steps 2 and 3

as intervening variables. Rather, as we anticipated in our theoretical model (hypothesis 5), there

may be two mechanisms producing this effects. First, size may have an effect because the nature of

political communication changes when municipal size increases. In smaller municipalities political

communication and mobilization are likely to be based on personal contacts between politicians

and their electorate (e.g. Dahl & Tufte 1973; Denters et. al 2014). In large municipalities these

personal contacts may be more difficult to maintain and web-based communication may be seen as

an attractive alternative strategy for political communication. Second, the size of a municipality is

also likely to have a positive effect on the availability of financial resources that are necessary to

adopt these ICT innovations. For reasons that will become clear later in the analysis, we suspect

that especially the first mechanism is responsible for the size effect.14 But future research will have

to demonstrate to what extent either of these mechanisms can account for the effect of size that

we found in our analysis.

13 These results should explicitly be treated as preliminary. For one thing: we still have to conduct a test of the

regression assumptions. Moreover we may also want to consider alternative model specifications.

14 These reasons have to do with the results of our test of hypothesis 4.


13

In the second step of analysis we have looked at the effect of the motivational factors. If we look at

these factors and compare the results of the second and fourth step in the analysis it is clear that

the explanatory power of these factors is rather limited.

TABLE 2: EXPLANATORY FACTORS IMI-FACTOR (RESULTS OLS REGRESSIONS)

OLS Q1 Model

1

OLS Q1 Model 2 OLS Q1 Model 3 OLS Q1 Model 4

beta/se/p beta/se/p beta/se/p beta/se/p

Municipal size 0.417*** 0.321***

(0.000) (0.000)

Turnout -0.090 0.027

(0.103) (0.644)

Decline in turnout 0.058 0.016

(0.281) (0.764)

Education 0.161** 0.020

(0.046) (0.811)

Disposable income 0.063 0.163**

(0.443) (0.047)

Age 15-25 0.089 0.045

(0.151) (0.461)

Effective parties 0.235*** 0.138**

(0.000) (0.019)

ICT Track record 0.291*** 0.054

(0.000) (0.360)

N 377 320 371 318

r2 0.173 0.152 0.085 0.217

r2_a 0.171 0.136 0.082 0.197

df_r 375 313 369 309

* p<0.10, ** p<0.05, *** p<0.001

The theoretical expectations (hypotheses 1.1. and 1.2) based on the assumption that the adoption

of ICT mobilization would be more likely when a municipality would be confronted by a low level of

turnout or a large decline in turnout in the previous municipal elections are disconfirmed. A second

expectation was that in municipalities with a higher degree of digital literacy and internet access

the introduction of internet-based electoral mobilization is more likely. In the absence of direct

measures we used a number of proxy variables for digital literacy and internet access. Only one of

these factors (per capita income; hypothesis 2.2) did have the expected effect. This is a relatively

weak effect (0.16), that only appears after controls for all other variables in the model.15 We also

looked at electoral motives that might inspire municipalities to invest in ICT electoral mobilization.

If the electoral competition in a municipality is keen, we expect ICT mobilization to be more

intensive (hypothesis 3). Our results in Table 2 provide confirmation for this expectation. Even after

15 Education did have an effect in step 2 but once we introduce controls for the other factors in the analysis this effect

disappears. This suggests that the initial effect is spurious, and produced by the effects of municipal size on the IMI index and on education (the correlation between size and education is 0.26).


14

controls for other factors in the model (including the size factor) a positive direct effect of the

effective number of parties remains.16

The adoption of ICT innovations in electoral mobilization was also expected to be affected by the

command over resources. In this respect we hypothesized that the more experienced the

municipality is in ICT applications in other domains the more likely it would be to also implement

ICT innovations in the domain of electoral mobilization (hypothesis 4). The results for model 3

suggest that this hypothesis might be corroborated, but if we control for other factors the bivariate

association disappears. The relation between this factor and the IMI index is spurious and to a

considerable extent the result of the dependence of both variables on one or more explanatory

variables (amongst others the size variable which is not only associated with the IMI index but also

with ICT track record; correlation: 0.50). Apparently the command over resources that allow

municipalities is not an independent explanatory factor for the adoption of ICT innovations. This is

not only relevant for our evaluation of hypothesis 4, but also may have implications for our

interpretation of the results for the size factor. Previously we argued that the direct size effect that

we found previously may be the result of the resourcefulness of large municipalities. Our results

here cast doubt on this interpretation. For this reason another interpretation of the previously

reported size effect (different needs because of declining importance of personal communication

and increasing needs for alternative communication strategies) appears to be more plausible.

EXPLAINING 2014 ELECTION TURNOUT: PRELIMINARY FINDINGS

Now that we have provided a preliminary answer to our first research question we turn to the

second question we formulated in the introduction. This question pertains to the effects of ICT

mobilization efforts on electoral turnout. One of the aims of introducing these ICT innovations is to

increase the turnout in municipal elections. To what extent does internet mobilization contribute to

this aim. In answering this question we will analyze the impact of this factor in the context of other

relevant factors that can explain the turnout in municipal elections. In analyzing our data we follow

the same stepwise approach as we used in answering our first research question. The results of our

analysis are presented in Table 3.

16 In part the effect of size in model 1 is an indirect effect that runs through the competition factor (that is associated

with size; correlation with size is 0.50).


15

TABLE 3: EXPLANATORY FACTORS MUNICPAL ELECTION TURNOUT 2014 (RESULTS OLS REGRESSIONS)

OLS Q2 Model

1

OLS Q2 Model

2

OLS Q2 Model

3

OLS Q2 Model

4a

OLS Q2 Model

5a

beta/se/p beta/se/p beta/se/p beta/se/p beta/se/p

Municipal size -0.497*** -0.138*

(0.000) (0.061)

Housing tenure 0.403*** -0.006

(0.000) (0.938)

Local tax burden 0.144** 0.047

(0.003) (0.333)

Increase local tax

burden

-0.001

(0.977)

-0.031

(0.485)

65-80 age cohort

0.002

-0.076

(0.960) (0.216)

Education 0.406*** 0.399***

(0.000) (0.000)

Immigrants -0.707*** -0.619***

(0.000) (0.000)

Disposable income 0.053 0.037

(0.398) (0.652)

Paid employment -0.146** -0.142**

(0.024) (0.034)

Full employment 0.098 0.065

(0.111) (0.300)

Distance -0.025 -0.018

(0.642) (0.740)

Effective parties -0.314*** -0.028

(0.000) (0.594)

IMI -0.037 -0.018

(0.469) (0.712)

N 377 376 327 377 326

r2 0.247 0.195 0.383 0.108 0.399

r2_a 0.245 0.186 0.372 0.103 0.374

df_r 375 371 320 374 312

* p<0.10, ** p<0.05, *** p<0.001

Again the first factor we take into consideration is municipal size. In the bivariate model size has a

relatively strong negative effect. This negative size effect is in line with previous studies (both based

on aggregate and individual level data; see e.g. Geys 2006: 642-643; and Denters et al 2014,

chapter 10) results about the negative effects of size on turnout and several other forms of non-

electoral participation. This effect is in part a relatively weak direct effect (-0.14) and for another

part the result of a variety of indirect effects through other factors in the model.17

The introduction of the other factors in the analysis is not only interesting to evaluate the empirical

validity of the hypothesis, but also to analyze which factors may play a role in establishing this

indirect effects of size. A first cluster of explanatory factors relate to citizens’ motivations. Initially

17 Moreover, part of this bivariate association may also be non-causal, as a result of effects of factors that have effects

on turnout and that are associated (but not causally related) to size.


16

(in model 2) two factors appear to have an effect on turnout: housing tenure and the local tax

burden. But after controls for other model variables this effect disappears (see result for model

5).18

The next cluster of variables pertain to participatory resources. Amongst these factors, three

variables have a direct effect on turnout. Two of them are skills-related: education and the size of

the migrant population have effects on turnout (both in model 3 and after control for other

relevant factors). Turnout is higher in municipalities with a highly educated population and in

municipalities where there are relatively few migrants. 19 Moreover, as was expected paid

employment (as a proxy measure for having less free time and problems of flexibility in using

available time) also has a negative effect on turnout.

Finally, our results also shed light on the effects of mobilization factors. First of all we find that

although there initially appeared to be an effect of political competition on turnout, this effect

turns out to be spurious when we control for other model variable.20 Second, and most

importantly from the perspective of our paper. Internet mobilization is not even weakly related to

the turnout in municipal elections, neither in the simple model 4 nor in the more sophisticated

model 5. In the subsequent section we will summarize our findings regarding the two research

questions and reflect upon some of the implications of our results.

DISCUSSION

In this paper we have asked two research questions with regard to internet mobilization efforts in

Dutch municipal elections. The first question asks which factor can explain the adoption of such ICT

innovations. Our analyses demonstrate that municipal size is the single most important factor that

affects the likelihood of implementing ICT tools for electoral mobilization. We have argued have

argued that there were two potential mechanisms that could be responsible for such an effect:

differences in patterns of political communication and variations in the availability of resources

between large and small municipalities. On the basis of our analyses we have argued that the latter

explanation does not seem to hold, because the size-related ICT track record variable, did not have

an effect on ICT electoral mobilization efforts. Therefore, it seems plausible that the first

mechanism may be responsible for the observed direct size effect. This mechanism is based on the

presumption that there are major differences in patterns of political communication between large

and small municipalities (Denters et al. 2014). In larger municipalities, there are fewer direct

18 In the case of housing tenure it is likely that this correlation is in part spurious because both turnout and housing

tenure are strongly related to municipal size (the correlation of housing tenure and size is -0.63).

19 These two factors, and especially the migrant factor (with its 0.68 correlation with size) are also important factors in

accounting for the large bivariate effect (model 1) of size. In the theoretical literature the association between size and the composition of the municipal population is normally considered as non-causal (see Denters et al. 2014)>

20 Again to a considerable degree the size factor might be held responsible for his; it has a correlation with the effective

number of parties of 0.50. We


17

contacts between local parties and politicians and voters than in smaller municipalities, and in the

se larger places ICT tools may be an attractive alternative for more traditional forms of personal

face-to-face communication and mobilization with the electorate. Subsequent research should be

conducted to further substantiate this interpretation. In addition to this direct size effect we also

found an effect of electoral competition. The higher the degree of electoral competition, the more

efforts at ICT mobilization are made. We should also realize that size is relatively strongly related to

the degree of electoral competition. Therefore, in addition to the reported direct effect of size,

there is also an indirect effect of size through electoral competition as an intervening variable.

Finally we found a small effect of disposable income (which we used as a proxy measure for

resources like digital literacy and internet access).

Our second research question pertains to the effects of the use of ICT tools in electoral

mobilization. Our main conclusion here was that in the context of other explanatory factors

internet mobilization efforts by municipalities do not have an effect on municipal turnout. This

conclusion requires two qualifications. From a theoretical perspective we need to emphasize that

the present model is only a first step in the analysis. In our current analysis we have assumed that

motivations, resources and mobilization are clusters of factors that affect turnout independently. In

estimating our regression models we therefore have introduced these factors in a linear additive

model, without interaction effects. In subsequent versions of this paper we will also test more

complex models in which we assume that internet mobilization acts as a facilitating factor. One

might for example expect that internet mobilization will only be effective under specific

circumstances (e.g. VAA are only likely to be used when there is at least some motivation to vote

and when there is a particular level of digital literacy). Moreover, in subsequent versions of this

paper we also intend to conduct a more detailed analysis in which we look at the effects of three

types of ICT application in the context of electoral mobilization:

Basic information: practical information (available on the municipality’s homepage) and the

provision of links to local party websites.

Campaign related information: informing about events and substantive themes in the

campaign, and making party programs available through the municipal website

Advanced applications: VAA’s, Audio/Video and new social media.

The second qualification is more normative in nature. Even if, in these more sophisticated analyses

ICT mobilization should prove to have no major effects on election turnout, we should realize that

such provisions may be considered as valuable / useful for other reasons, for example because they

increase the openness and transparency of the electoral process, and provide a stimulus for the

public debate.


18

APPENDIX 1: MEASURES OF MAIN VARIABLES IN THE ANALYSIS

Hypothesis Variable label Operationalization

13 Internet mobilization index

See main text

XX Turnout 2014 Turnout percentage in 2014

1.1 Abstentions2010 100- turnout percentage in 2010

1.2 Abstention increase

Difference Abstentions2010 - 2006

2.1 / 9 Education Percentage of population between 15-65 with higher education

2.2 / 11 Income Per capita disposable income for municipal population

2.3 Young Percentage of population in 15 – 25 age group

3 / 13 Competition Effective number of parties 2010

4 ICT track record E-Government Ranking (in Dutch: Overheid.nl Monitor) (ICTU 2011). For each year since 1999, this monitor is based on a relative score and compares the websites of all municipalities in the Netherlands according to their ability to provide various e-government services and e-government content to citizens. The measurements used to calculate the scores change every year due to new priorities and new forms of e-government. Measurements took place in the final three months of each year. We have used the 2011 data for our purposes.

5 / 14 Municipal size Population size municipality (logged)

6 Housing tenure Percentage owner-occupied houses in the total housing stock

7.1 Tax burden 2014 Per capita annual sum paid by a household for local property tax and local levies (computed as mean of average burden for a one person household and a multi-person household). Based on COELO figures

7.2 Tax increase Tax burden 2014 – Tax burden 2013

8 Old Percentage of population in 65 – 80 age group

10 Immigrant population

Percentage of population of immigrant origin

12.1 Employed Percentage of population with paid employment

12.2 Fulltime employment

Percentage of employed population with full-time employment

12.3 Work distance Mean distance between municipality of employment and residence


19

APPENDIX 2: STATISTICS FOR VARIABLES IN THE ANALYSES

DESCRIPTIVE STATISTCS FOR RESEARCH QUESTION 1 (SEE TABLE 2)

Mean sd min max

IMI 4.17 1.68 0.00 8.00

Municipal size (log) 10.40 0.71 9.23 13.61

Turnout 56.40 6.06 42.61 75.55

Decline in turnout -5.30 5.52 -33.60 17.19

Education 25.25 7.75 11.64 52.53

Disposable income 15.05 1.35 12.50 22.40

Age 15-25 11.51 1.64 9.00 24.20

Effective parties 5.55 1.34 2.35 9.22

ICT Track record 89.70 28.66 30.47 177.00

N 318

BIVARIATE CORRELATIONS FOR RESEARCH QUESTION 1 (SEE TABLE 2)

IMI V36 V20c V48 V43f V39a V49 V34 V47c

IMI 1

Municipal

size

0.410***

(0.000)

1

Turnout -0.126*

(0.025) -.426

***

(0.000) 1

Decline in

turnout

0.125*

(0.026)

0.174**

(0.002)

0.0894

(0.111)

1

Education 0.256***

0.260***

0.116* 0.189

*** 1

(0.000) (0.000) (0.039) (0.001)

Disposable

income

0.122*

(0.030)

-0.110*

(0.050)

0.162**

(0.004)

0.118*

(0.035)

0.650***

(0.000)

1

Age 15-25 0.151**

0.353***

-0.0321 0.112* 0.174

** -.275

*** 1

(0.007) (0.000) (0.568) (0.045) (0.002) (0.000)

Effective

parties

0.304***

(0.000)

0.495***

(0.000)

-.275***

(0.000)

0.112*

(0.047)

0.156**

(0.005)

-0.0640

(0.255)

0.172**

(0.002)

1

ICT Track

record

0.248***

(0.000)

0.505***

(0.000)

-0.132*

(0.019)

0.135*

(0.016)

0.211***

(0.000)

-0.0675

(0.230)

0.171**

(0.002)

0.237***

(0.000)

1

N 318 p-values in parentheses * p < 0.05,

** p < 0.01,

*** p < 0.001


20

DESCRIPTIVE STATISTCS FOR RESEARCH QUESTION 2 (SEE TABLE 3)

mean sd min max

Turnout 2014 56.43 6.02 42.61 75.55

Municipal size (log) 10.40 0.70 9.23 13.61

Housing tenure 63.31 8.20 25.40 80.20

Local tax burden 678.29 85.78 460.12 1074.21

Increase local tax burden 1.30 3.13 -9.69 19.70

65-80 age cohort 14.36 2.14 7.10 21.30

Education 25.18 7.71 11.64 52.53

Immigrants 14.30 8.00 3.30 50.70

Disposable income 15.04 1.35 12.50 22.40

Paid employment 67.65 3.43 57.70 78.72

Full employment 39.54 2.92 30.33 46.08

Distance 14.21 3.42 6.40 27.30

Effective parties 5.56 1.33 2.35 9.22

IMI 4.17 1.69 0.00 8.00

N 326


21

BIVARIATE CORRELATIONS FOR RESEARCH QUESTION 2 (SEE TABLE 3)

V20c V36 V41b V50a V50b V46h V43f V37a V39a V42c V42d V44 V34 IMI

Turnout 2014 1 Municipal size -.425*** 1 (.000) Housing tenure .392*** -631*** 1 (.000) (.000) Local tax burden .163** -.165** .0585 1 (.003) (.003) (.292) Increase local tax burden .0131 -.0733 .0381 .163** 1 (.813) (.187) (.493) (.003) 65-80 age cohort .156** -471*** .334*** .153** .0340 1 (.005) (.000) (.000) (.006) (.540) Education .115* .257*** -.246*** .204*** -.00198 -.144** 1 (.038) (.000) (.000) (.000) (.972) (.009) Immigrants -.494*** .680*** -.723*** -.0227 -.0491 -.314*** .424*** 1 (.000) (.000) (.000) (.684) (.377) (.000) (.000) Disposable income .160** -.103 .0622 .356*** .0658 .247*** .654*** .193*** 1 (.004) (.063) (.263) (.000) (.236) (.000) (.000) (.000) Paid employment .147** -206*** .322*** .0259 .0306 -.164** .135* -.215*** .298*** 1 (.008) (.000) (.000) (.641) (.582) (.003) (.015) (.000) (.000) Full emplyment .0350 -.154** .212*** .0215 .00137 -.182*** -.121* -.0877 .122* .627*** 1 (.528) (.005) (.000) (.698) (.980) (.001) (.028) (.114) (.028) (.000) Distance .129* -.188*** .180** -.0446 -.0415 .227*** -.219*** -.358*** -.340*** -.271*** -.317*** 1 (.020) (.001) (.001) (.423) (.456) (.000) (.000) (.000) (.000) (.000) (.000) Effective parties -.269*** .502*** -.460*** -.101 .0201 -.221*** .165** .418*** -.0478 -.183*** -.171** -.0183 1 (.000) (.000) (.000) (.067) (.717) (.000) (.003) (.000) (.389) (.001) (.002) (.742) IMI -.128* .388*** -.261*** -.0139 -.0917 -.171** .239*** .255*** .101 -.0266 -.134* -.0110 .314*** 1 (.021) (.000) (.000) (.803) (.098) (.002) (.000) (.000) (.070) (.633) (.016) (.843) (.000) N 326


22

REFERENCES

Baekgaard, M., Jensen, C., Mortensen, P. B., & Serritzlew, S. (2014). Local News Media and Voter

Turnout. Local Government Studies. 40 (4): 518-532 . Baglioni, S., Denters, B., Morales, L., & Vetter, A. (2007). City size and the nature of associational

ecologies. In W. Maloney & S. Rossteutscher (Eds.), Social capital and associations in European democracies. A comparative analysis (pp. 224-243). London and New York: Routledge.

Berry, F. S., & Berry, W. D. (1999 ). Innovation and diffusion models in policy research. In P. A. Sabatier (Ed.), Theories of the policy process (pp. 169-200). Boulder: Westview Press.

Blais, André. (2006). What affects voter turnout? Annu. Rev. Polit. Sci., 9, 111-125. Blumler, J. G., & Kavanagh, D. (1999). The third age of political communication: Influences and

features. Political Communication, 16(3), 209-230. doi: 10.1080/105846099198596 Braun, D., & Gilardi, F. (2006). Taking ‘Galton's Problem’Seriously. Journal of Theoretical Politics,

18(3), 298-322. Brennan, G., & Lomasky, L. (1993 ). Democracy and decision: the pure theory of electoral preferen-

ce. Cambridge etc.: Cambridge University Press. Campbell, A, Gurin, G., & Miller, W.E. (1971). The voter decides. Westport: Greenwood Press. Campbell, Angus, Converse, Philip E., Miller, Warren E., & Stokes, Donald E. (1980). The American

voter. Chicago etc.: University of Chicago Press. Dahl, R. A., & Tufte, E. R. (1973 ). Size and democracy. Stanford: Stanford University Press. Denters, B., Mike, G., Ladner, A., Mouritzen, P. E., & Rose, L. E. (2014). Size and local democracy.

Cheltenham: Edward Elgar Donk, W. v. d., & Tops, P. W. (1994 ). Informatisering en democratie: Orwell of Athene? In A.

Zuurmond, e.a. (Ed.), Informatisering in het openbaar bestuur: technologie en sturing bestuurskundig beschouwd (pp. 249-267). 's-Gravenhage T: VUGA.

Franklin, Mark N. (2002). The dynamics of electoral participation. In L. LeDuc, R. G. Niemi & P. Norris (Eds.), Comparing democracies 2: New challenges in the study of elections and voting , pp. 148-168.

Geys, B. (2006). Explaining voter turnout: A review of aggregate-level research. Electoral Studies, 25(4), 637-Karlsson, M. (2013). Covering distance. Esays on representation and political communication (Vol. 33). Örebro: Örebro Univerity.

Johnston, RJ, Pattie, Charles J, Dorling, Danny FL, MacAllister, Iain, Tunstall, Helena, & Rossiter, DJ. (2001). Housing tenure, local context, scale and voting in England and Wales, 1997. Electoral studies, 20(2), 195-216.

Karlsen, Rune. (2010). Online and undecided: Voters and the Internet in the contemporary Norwegian election campaign. Scandinavian Political Studies, 33(1), 28-50.

Karlsson, M. (2013). Covering distance. Esays on representation and political communication (Vol. 33). Örebro: Örebro Univerity.

Laakso, M., & Taagepera, R. (1979 ). The 'effective' number of parties: a measure with applications to Western-Europe. Comparative Political Studies, 12 3-27.

Miller, W.E., & Shanks, J.M. (1996 ). The new American voter. Cambridge etc.: Harvard University Press.


23

Mossberger, K., Tolbert, C. J., & McNeal, R. S. (2012). Digital citizenship: Oxford University Press. Powell, G. B. (1980 ). Voting turnout in thirty democracies. In R. Rose (Ed.), Electoral participation

(pp. 5-34). Beverly Hills: Sage. Saglie, J., & Vabo, S. I. (2009). Size and e-Democracy: Online Participation in Norwegian Local

Politics. Scandinavian Political Studies, 32(4), 382-401. Schuessler, A. A. (2000). Expressive voting. Rationality and Society, 12(1), 87-119 Strate, J. M., Parrish, C. J., Elder, C. D., & Ford, C. (1989). Life Span Civic Development and Voting

Participation. The American Political Science Review, 83(2), 443-464. doi: 10.2307/1962399. Van Dijk, Jan and Ken Hacker (2003). The ‘Digital Divide’ as a Complex and Dynamic Phenomenon.

The Information Society. Vol. 19, Nr. 4, 315-326. Verba, S., & Nie, N.H. (1987 [1972]). Participation in America: political democracy and social

equality. Chicago etc.: The University of Chicago Press. Verba, S., Nie, N.H., & Kim, J.O. (1978 ). Participation and political equality: a seven nation

comparison. Cambridge: Cambridge University Press. Walker, J. L. (1969 ). Diffusion of innovations among American states. American Political Science

Review, 63, 880-899 .

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