Plan de Inversiones y Financiamiento:

In this study, the aim was to contribute to the field of public administration research by answering the following research question: “To what extent does organisational complexity affect the use of participatory innovation in the drafting of a municipal budget”? Due to the different results for both hypotheses, there is not a straight answer to this research question in general. However, this study provided further evidence that organisational complexity expressed through functional departments is related to the occurrence of participatory innovation, while organisational size is not related to participatory innovation. If the value of functional differentiation increases by 1, the likelihood of participatory innovation increases by the factor 1.098.

The empirical outcomes of this study about functional differentiation are in line with theoretical assumptions and empirical studies from other scholars. In hypothesis 1, it was assumed that higher functional differentiation has a positive effect on the occurrence of participatory budgeting. The empirical findings in this study support this hypothesis, as it was found that functional differentiation has a statistically significant and positive relationship with the occurrence of participatory budgeting. This is supported by the theory, as previous studies argued that when an organisation is functionally differentiated, they are more likely to innovate (Aiken et al., 1980; Damanpour, 1991, 1996). As a consequence of the research design, this study cannot explain empirically how this relationship works. Other scholars used interviews or surveys to examine mechanisms in this relationship and argued that functional differentiation establishes expert knowledge and cross-fertilisation of these experts, which both promote innovation (Aiken & Hage, 1971; Baldridge & Burnham, 1975). However, previous studies focused on the relationship of functional differentiation and process innovation or service and product innovation (Aiken et al., 1980; Damanpour, 1996). These studies have ignored the third type of innovation, which is ancillary innovation and is examined through the subtype participatory innovation in this study. Hence, the research is now more holistic, as with the results of this study it can be stated that functional differentiation is positively related to all three types of innovation. In addition, these findings have been proved in a different context, which has not yet been studied to test this relationship.

32 Additionally, it has been hypothesized that organisational size has a positive effect on the occurrence of participatory budgeting. This hypothesis is rejected, as the results of this study did not provide a statistically significant relationship between the two variables. Scholars have discussed if the influence of organisational size is positive or negative on innovation (Camisón-Zornoza et al., 2004; Damanpour, 1992). This research followed arguments that the relationship of organisational size and innovation is positive. The correlation between the variables was positive and thereby points in the direction of a positive relationship. Nevertheless, a conclusion cannot be drawn from this, as the findings were not statistically significant. Whereas the findings do not fit in those two broad categories of either positive or negative relation, it is in line with a study from Aiken et al. (1980), who investigates Belgian municipalities in a quantitative study and also did not find a statistically significant relationship between organisational size and innovation.

A possible reason for the statistically non-significant result might be that organisational size is not directly related to participatory innovation. It could be that the relationship of organisation size and innovation is mediated by functional differentiation. Baron and Kenny (1986) explain that a potential mediation can be detected if the independent variable has an effect on the mediator, the mediator has an impact on the dependent variable and if both are included in a model, only the mediator has an influence on the dependent variable, while a previous statistically significant relationship between the independent and dependent variable changed to statistically non-significant. In this study, organisational size and functional differentiation have a statistically significant relationship. In addition, functional differentiation is statistically significant related to participatory budgeting. In a multivariate model, only functional differentiation has a statistically significant relationship, whereas organisational size is no longer statistically significant related to participatory budgeting. Baron and Kenny (1986) assumed a causal path between the independent variable, the mediator and the dependent variable, whereas this study can only provide correlations. As a result, other variables could influence the tested relationships. In addition, Baron and Kenny (1986) state that multicollinearity between the independent variable and the mediator should be detected, as the independent variable correlates highly with the mediator. In this study, the VIF for both variables were higher than the others, but not on a level that one can be sure about multicollinearity. Hence, there is some evidence that the relationship of organisational size and participatory innovation is mediated by functional differentiation, but two assumptions of the test were not fully met.

With a view on both variables, it can be concluded that organisational complexity matters in the relationship with innovation. From these findings, it could be argued that structural complexity (i.e. functional differentiation) might be positively related to innovation, while the size-innovation- relationship might not be relevant for innovations in municipalities. Apart from the potential

33 mediation, another reason for the different outcomes of the explanatory variables could be related to the different forms of assumed benefits they have on innovation. The organisational size is based on the number of employees in a municipality. Scholars argue that the more employees an organisation has, the more human resources are available for innovation (Nord & Tucker, 1987). In contrast, functional differentiation can lead to diversity, expert knowledge and cross-fertilisation (Aiken & Hage, 1971; Damanpour, 1996). Results from this study support the argument that for participatory budgeting among municipalities it is not the number of people in an organisation that matters (i.e. quantity), but the functional expert knowledge they can bring into the organisation (i.e. quality). Unexpectedly, none of the control variables are statistically significant related to the occurrence of innovation. We argued that slack resources are positively related to the occurrence innovation, as finically strong municipalities might have more leeway to finance additional innovation (Aiken & Hage, 1971; Damanpour, 1991). We measured slack resources negatively, by assuming that less municipal debt expresses more slack resources. However, the findings were not statistically significant and hence, do not support our assumption. One reason might be that the amount of financial resources (i.e. quantity) might not be relevant for this type of innovation in the researched context. This might be in line with the findings about the explanatory variables, where it was already argued that the quality of resources might be more important for the relationship with participatory innovation than the quantity of resources. Political support was also assumed to be positively related to the occurrence of participatory budgeting (Brun-Martos & Lapsley, 2017; Röcke, 2014), but the results were not statistically significant. However, the statistical significance of political support is with a p-value of 0.161 considerably lower than the other control variables. Our objective measurement of political support by parties in the municipal council might be too broad for this type of innovation, whereas investigating individual political support (e.g., party of the major) could lead to different results. Furthermore, environmental variables like political activity and wealth of citizenry have been included due to the potential effects stated by mainly participatory budgeting studies (Ebdon & Franklin, 2006; Michels, 2011; Rossmann & Shanahan, 2011). A statistically significant correlation of these variables with the occurrence of participatory budgeting has not been detected. One attempt of explanation is that for this type of innovation in this sample, internal factors and especially organisational structure variables are more relevant than external factors. This has already been argued in the classical study on innovation of Burns and Stalker (1961) that highlighted the importance of organisational structure for organisational innovation.

5.2 Theoretical implications

This thesis provides some interesting results for the existing theory. It highlights the importance of functional differentiation in research about organisational structure and innovation. In the past,

34 management research examined this relationship extensively and discovered that functional differentiation is positively related to innovation (e.g. Aiken & Hage, 1971; Baldridge & Burnham, 1975; Damanpour, 1991, 1996). However, following the recent meta-analysis of Jakobsen and Thrane (2016), public administration research overlooks this explanatory variable, as they focus predominantly on the relationship of centralisation, formalisation and specialisation with innovation in public organisations. Usually these parameters are investigated through perceptions (Pennings, 1973), while this study focused on more objective information. We will discuss the benefits of the objective measurements in the next subchapter, however, for the existing theory in the field of public administration we argue that models of organisational structure should not only exist of perceived organisational structures, but should also include objective paraments like functional differentiation to have a more balanced view on organisational structure.

The outcomes of this study have also implications on academic research regarding the size-innovation- relationship. Scholars argue mainly that the relationship of size and innovation is either positive or negative (Camisón-Zornoza et al., 2004; Damanpour, 1992). In their meta-analysis, Camisón-Zornoza et al. (2004) also detected examples of non-significant relationships of size and innovation, but they did not discuss this option. In addition, Aiken et al. (1980) investigated innovations in Belgian municipalities and did also discover statistically non-significant results of the size-innovation relationship. It might be that organisational size does not have a direct relationship with innovation in municipalities. In this study we already argued that a relationship of size and innovation could be mediated by functional differentiation, as we found some evidence for this indirect relationship. In his study of the size-innovation relationship, Damanpour (1992) assumed that mediators might influence this relationship and future research should focus on that. It seems that has not happened. Thus, it might be appropriate that the size-innovation theory does not only cover positive or negative directions, but also investigates potential mediators of this relationship. Outcomes of this study point in the direction of a mediation through functional differentiation, but more empirical evidence is needed.

This study also has some relevance for research that deals exclusively with participatory innovation. Ebdon and Franklin’s (2006) impact model on participatory budgeting consists of several environmental variables that either support or harm the process of participatory budgeting. They also mentioned that their conclusion derived mainly from case studies or surveys that investigated other topics (Ebdon & Franklin, 2006). Findings from this quantitative study do not support their assumptions, as environmental variables have no statically significant relationship with the occurrence of participatory budgeting. This study highlights the relevance of internal factors. A reason for this could be that participatory budgeting studies focus more on achieved outputs and values (e.g. Baiocchi

35 & Ganuza, 2014; Hong, 2015; Rossmann & Shanahan, 2011). Our study did not evaluate on specific outcomes of the participatory budgeting, as we have seen the occurrence of this innovation as the outcome itself. Since participatory budgeting is about the input from external actors, it is logical that scholars focus on external factors. Nonetheless, participatory innovation consists of the interplay between the municipality and those external actors. The classical study from Burns and Stalker (1961) supports our argument of the importance of internal factors, as they have already argued that the innovative capabilities of organisations can be determined by its organisational structure. Further support is provided by a more recent meta-analysis on antecedents of innovation in local governments by Walker (2014), who concluded that internal factors are more relevant explanatory variables than external factors. Therefore, future studies of participatory innovation should include internal factors like organisational structure variables to have a more comprehensive view of the interplay of public actors and citizens.

5.3 Methodological implications

This study has relevance for the selection of methods of further public administration research. De Vries et al. (2016) already stated that innovation research in the field of public administration is dominated by qualitative approaches and they argued more quantitative studies were needed. Theory in this field is poorly developed, as case studies focus on the exploration of new theories and do not test existing theories (De Vries et al., 2016). Our study supports the claim for more quantitative studies on innovation in the field of public administration. Assumptions that this study builds on theory from quantitative studies in the field of management (e.g. Damanpour, 1996) were more appropriate to forecast variance in the occurrence of innovation, while assumptions derived from the impact model of participatory budgeting from Ebdon and Franklin (2006), which is based on case studies, were not related to innovation in this study. If findings from case studies cannot be replicated in large-N studies, the results should not be used for general models. To contribute to the field of innovation, public administration scholars should focus more on large-N studies to test and develop theory further instead of creating new ones through case studies. As a result, the interplay of quantitative and qualitative approaches would lead to a more comprehensive research body.

Another methodological implication is that objective measurements of organisational structure and innovation can give a different perspective. Studies about organisational structure frequently measure organisational structure through interviews or surveys (e.g. Aiken et al., 1980; Aiken & Hage, 1971; Greenhalgh, Robert, Macfarlane, Bate, & Kyriakidou, 2004; Jaworski & Kohli, 1993). This is referred to as a questionnaire approach (Pennings, 1973). This study followed an alternative approach, where organisational variables were measured by analysing official documents (Pennings, 1973). Furthermore, the measurement of innovation is frequently based on perceptions (e.g. Aiken et al.,

36 1980; Moon & Bretschneiber, 2002; Walker, 2008). This study used official and objective data sources from government agencies to measure innovation. We found a positive relationship by using official documents and data sources, which had a strong reliability and validity, as the data sources were mainly unambiguous and available for everyone. Typical problems of subjective measurements, such as a low response rate or subjective perceptions (Neuman, 2014), could be avoided by using objective measurements. Hence, due to the predominance of the questionnaire approach in the academic field and its potential pitfalls, future public administration research should make use of the advantages of objective measurements of organisational structure and innovation.

This study has methodological implications on public administrations researchers, who investigate organisational structures and innovation. In our sample, the size of the population of a municipality was highly correlated with other explanatory factors. Researchers have to be aware of the fact that including the number of the inhabitants in studies of municipalities might lead to multicollinearity. In public organisations, the number of employees and even the organisational structure might be dependent on the size of the population. This can be detected by decisions of regulatory agencies that compare different public organisations and build their arguments on the size of the population (GPANRW, 2014a). Problematic is that many studies about organisational structure follow findings from management scholars that do not have this population dependency (e.g. Burns & Stalker, 1961; Damanpour, 1991; Hage & Aiken, 1970; Mintzberg, 1979). Private organisations are usually not bounded to a specific population or area. As a result, they do not include population as a variable in comparative studies between private and public and this collinearity might not be an issue for them (e.g. Damanpour, 1992). As such, we can state two implications. Firstly, comparative studies of private and public organisations miss one relevant control variable, as size of the population might be related to other explanatory variables in the public context. Secondly, by investigating organisational structure and especially the size of municipalities, there is the risk of collinearity with the size of population that researchers should be aware of.

5.4 Limitations

Apart from the effects that the results of this study might have on existing research, it does have certain limitations. Foremost, the research design of this study only allows for certainty of general relationships. As mentioned earlier, quantitative studies can test general relationships between variables (Toshkov, 2016). As a result, it can only be stated that functional differentiation is positively related to the occurrence of participatory budgeting. However, this study cannot contribute to the discussion on how this relationship functions. There are no insights in mechanisms and no proof of causality. We assumed in the theoretical part that through functional differentiation experts in departments are established and if they interact with other experts from different departments, they

37 cross-fertilize each other. However, these assumptions cannot be tested with this research design. Our arguments of these causal mechanisms derive from other studies that did not exclusively focus on organisational complexity and participatory innovation (e.g. Aiken et al., 1980; Damanpour, 1996; Hage & Aiken, 1970). A possibility might be that the relationship of functional differentiation and participatory innovation consist of specific steps in between, which only occur in this sample by examining the specific parameters. Thus, there is strong evidence for a relationship of functional differentiation and participatory budgeting, but this study cannot explain whether functional differentiation has a causal effect on the occurrence of participatory innovation and if there are additional causal steps in between.

Another limitation of this study is that all variables are measured on an organisational or environmental level. We assumed that functional differentiation improves knowledge and collaboration among experts that result in innovativeness. Even though we are interested in an organisational innovation as the outcome, the process of knowledge creation and its transfer might occur on both the organisational and individual level. In addition, political support could consist of the endorsement of individual and influential politicians and not of the compilation of a municipal council. The same is true for political activity and wealth of the citizenry. It could be that only some wealthy and politically active citizens are needed, while we used average numbers from the whole municipality. By leaving out one level of observation, this research excludes one viewpoint on the assumed process, which might be crucial for the occurrence of innovation.

A final limitation is related to the explanatory potential of the final model in this study. While findings about the relationship of functional differentiation were statistically significant on the 0.01 level, all the other independent variables were not statistically significant. Following the Nagelkerke R Square, 21,3 % of the variation of participatory innovation could be explained by the final model. Functional differentiation alone explained already 20,4 % of the variation. This research used the most common control variables from the current theory. However, these might not suffice, since the research in public sector innovation is still in development (De Vries et al., 2016; Torfing & Triantafillou, 2016). This means that the findings from this study could be influenced by confounders that are not discovered yet.

5.5 Future research

To understand the relationship of functional differentiation and participatory innovation, additional qualitative research might be suitable to enlarge the existing research in the field of organisational