Innovation under Fiscal Constraints: Evidence from Public Sector in Europe

doi:10.21203/rs.3.rs-1604353/v1

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Innovation under Fiscal Constraints: Evidence from Public Sector in Europe

https://doi.org/10.21203/rs.3.rs-1604353/v1

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The Great Recession of 2008 put public sector in Europe under considerable strain. Countries across the continent slashed their public administration budgets to manage their expenditure. Austerity measures also included spending cuts in other important areas like social protection. Under such circumstances, public organizations were under considerable financial and political pressure to find novel and innovative solutions to their increasingly complex social problems. However, evidence shows that financial resources are crucial for organizations to innovate. In this study, we examine the innovation outcomes of public organizations under conditions of budget constraints. Using data from the Coordinating for Cohesion in the Public Sector of the Future (COCOPs) project, we show that fiscal constraints were associated with significant negative innovation outcomes in European public sector. We also use Merton’s strain theory to design a framework for innovation under fiscal constraints. The results support the framework and show that under conditions of strong civic norms, public organizations are forced to innovate when faced with financial strain.

innovation

fiscal austerity

public sector innovation

social capital

strain theory of innovation

The Great Recession of 2008 resulted in negative growth in most European countries. Governments in these countries, facing rising cost of bank bailouts and falling tax revenue, took the unprecedented step to adopt steep austerity measures in order to balance their budgets (IMF, 2012). While nations that required debt financing and conditional support (like Greece and Ireland) bore the largest brunt from these measures, many other European countries also initiated their own austerity programs (Theodoropoulou & Watt, 2011). These programs mostly entailed large spending cuts (and on few occasions tax reductions as well). These cuts have largely been targeted towards public administration and social protection (ibid). In the public sector, governments enforced various measures that can largely be categorized into quantitative adjustments (which included pay cuts, and hiring freezes), and structural reforms (which entailed downsizing, privatizing, and decentralizing) (Vaughan-Whitehead, 2013). Besides affecting public administration, austerity measures also entailed cutting back on public expenditure in social protection programs in various sectors inter alia health, environment, research and development and education (Karanikolos et al., 2013; Theodoropoulou & Watt, 2011). Cuts in public budget was further coupled with an economic environment which included massive unemployment, and lack of access to finance and credit (Karanikolos et al., 2013), necessitating various structural and management reforms undertaken by the public government.

Although public management and public finance reforms date back to the early New Public Management (NPM) era, the financial pressures on government after the financial crisis has been unprecedented (Pollitt, 2010; Raudla et al., 2015). Under such circumstances, political and bureaucratic elites have argued that for the foreseeable future that budget constraints within the public sector is likely to persist and that public sector within their countries need to be smarter, leaner and more productive to achieve “more with less” (Randma-Liiv & Kickert, 2017b; Wanna et al., 2015). On the other hand, public organizations also need to ensure they are able to tackle increasingly complex social, economic, and environmental problems (Albury, 2011). Such conditions require public organizations to find novel and innovative solutions to their day-to-day problems.

However, it is widely perceived that financial resources are crucial to organizational innovation. Neo-Schumpeterian theory argues that access to resources allow organizations to dedicate funds towards innovation to retain their quasi-monopolistic rents (Schumpeter, 1942). Studies have shown that access to finance permits organizations to hire specialized human resources, provides support for exploration and experimentation, and enables them to insource external knowledge through extensive knowledge search or collaboration (Hewitt-Dundas, 2006). High uncertainty and absence of strategic choices due to resource constraints, however, can lead organizations to greater departmental conflicts, and avoidance of risk employees often resort to focusing on their specialization, and refrain from venturing outside beyond their own competence (Hoegl et al., 2008).

Therefore, given the pressure imposed upon the public organizations to perform, it becomes important to understand how financial constraints are affecting their innovative performance. Existing work on fiscal austerity measures has mostly looked at the effects of budget cuts on government performance and innovation from two perspectives. The first group of studies has focused on governance highlighting the innovative approaches to public finance undertaken by national and local governments in Western economies amidst severe budget constraints (Silva & Buček, 2014). However, scholars have argued that studies on financial governance often ignore the effects they can have on public administrations and have called for more investigation into the management strategies undertaken by public service organizations to overcome these challenges (Overmans & Noordegraaf, 2014). To overcome this gap, the second set of studies has examined the phenomenon from a qualitative perspective looking at the effects of such measures on organizational values, and innovation outcomes of public organizations (Heald & Steel, 2018). However, such, case/country-specific studies have often ignored how despite similar fiscal pressures, different nuances of institutional pressures amongst countries that can produce differences in innovation outcomes within public organizations (Demircioglu & Audretsch, 2017; Randma-Liiv & Kickert, 2017a).

This study departs from existing literature in its focus on examining variations in creativity and innovation displayed by organizations and their employees amidst fiscal crises. It takes a comparative institutional approach to understand variations in innovation outcomes by examining the moderating role played by national institutions. Combining data from the Coordinating for Cohesion in the Public Sector of the Future (COCOPs) project, the European Values Survey (EVS) and the World Governance Survey (WGS), it investigates how differences in social norms and values across countries can moderate the effect fiscal austerity can have on innovation outcomes in the public organizations.

1.1 Financial constraints and innovation

Declining budgets, along with rising complexity of social problems and increasing potential for collaboration, has been attributed as a major driver of innovation in the public sector (Torfing & Triantafillou, 2016). However, resource-based view of the firm often posits that an organization’s ‘combinative capacity’ or its ability to innovate is not only a function of its tacit and accumulated knowledge-base but also its accumulation of financial resources. Access to financial resources is typically expected to improve an organization’s innovation capacity since it allows organizations to accumulate new knowledge and improve its existing knowledge base (Hewitt-Dundas, 2006). Resourceful organizations can augment their human resource capacity, invest in research and development, or collaborate with external agencies that improve their absorptive capacities and enable them to innovate. Generating tacit knowledge base also takes time (Zhang & Zheng, 2020). Returns to investments in innovation are highly uncertain, sticky and consist of high adjustment costs (Hall, 2002). More specifically, costs incurred in hiring and retaining additional resources tend to be highly recurrent and drive up the equilibrium rate of return for investments in innovation (ibid). As a result, financial constraints disincentivize organizations to take greater risks over longer periods of time and invest in innovation generation.

Additionally, absence of sufficient resources produces other problems that might impede innovation. As Cyert and March (1963) argue, an organization is a coalition of self-interested subunits, yet resource availability and slack act as lubricants that permit relatively frictionless coexistence of such subunits. A situation of scarcity then can lead to conflicts amongst subgroups in organizations threatening organizational harmony (Nohria & Gulati, 1997). More pertinently, such situations of conflict also increase coordination costs within organizations and increase barriers to information flow and processing from within and beyond organizations (ibid). If knowledge flow and absorption is crucial for generating innovation, rise in cost of knowledge search and absorption is bound to discourage innovative activities. Even at individual or team level, lack of resources might lead to lower employee morale, with employees blaming their poor innovative performances on their “circumstances” (Hoegl et al., 2008). In such situations, organizations often resort to their core competence and are disinclined to undertake any unnecessary risks.

H1: Resource constraints lead to lower innovation outcomes in public organizations

However, under certain circumstances, constraints in resources can also incentivize innovation. Early Schumpeterian theory argued that smaller firms with lower resources possess the dynamic creativity to drive innovation forward (Schumpeter, 1934). While this view has been challenged in recent times, evidence shows that there are still sufficient reasons to argue that resource constraints can also drive innovation forward. Various studies have pointed out that under research constraints, production teams and users have produced more innovative results than comparatively resource counterparts (Gibbert & Scranton, 2009; Mehta & Zhu, 2016; Rosso, 2014).

These studies show different factors drive innovation at different organizational levels. For instance, at the individual level, innovations can arise from entrepreneurial bricolage (Baker & Nelson, 2005), or leadership (Marvel & Patel, 2018), or simply, the intrinsic motivation attached with the work (including the nature of the problem itself) (Amabile et al., 2002; Cromwell, 2018). At the team level, factors such as clarity of goals, team climate, team cohesion, domain-specific skills, and team leadership have been attributed to teams generating innovative outcomes under resource constraints (Hoegl et al., 2008; Rosso, 2014; Weiss et al., 2011). At the organizational level, theories have been put forward to argue that environmental factors under which organizations operate, nature and dynamics of the resource constraint and the size of the organizations can determine their innovative capacity (Hewitt-Dundas, 2006; Katila & Shane, 2005).

While the importance of aforementioned factors cannot be overstated, this study departs from the earlier literature by arguing that broader social norms under which organizations operate also play a crucial role in moderating the role between financial resource constraints and innovation. The focus on broader social factors permits us to explore two novel but important dimensions in innovation literature. First, it allows for a more nuanced understanding of innovation in public organizations whose performance is not particularly motivated by the contingent market based factors like competition or market size, but more so by their objective to generate public value (Cowley & Smith, 2014; Moore, 1995). Second, it allows making comparison of organizations across societies and reflect whether broader social norms play a role in differential innovation outcomes across countries.

1.2 Social norms, resource constraints and innovation

We use Merton’s strain theory of deviance to argue that social norms play an important role in incentivizing innovation in organizations (Merton, 1968). Merton argues that strains arise when there is a misalignment between the normative social goals and the legitimate or institutional mechanisms to achieve them. Given sufficient strain, individuals deviate from their expected behavior (Merton, 1968). While the original strain theory and the subsequent general strain theory were designed to understand deviant and criminal behavior amongst individuals in the society, over the years, the framework has also been used to explain deviances (like corruption and more pertinently innovation) within organizations (Tenzer & Yang, 2020; Wang et al., 2020).

As mentioned earlier, strain theory argues that misalignment between normative social goals and legitimate institutional mechanisms to achieve those goals lead to deviances. In case of organizations, this misalignment can result in what organizational theorists call, destructive, and constructive deviances (Warren, 2003). In an organization, destructive deviance can lead to undesirable activities like fraud, embezzlement or violence which can impose significant costs to the organization and the society (Galperin & Burke, 2006). However, potentially harmful behavior, the strain theory argues, is just one type of outcome of the strain arising out of misalignment. Depending on the nature of the misalignment, the strain theory posits that deviances can be of different types (ritualism, retreatism, and rebellion). Only when organizations or their employees reject broader social norms and mechanisms, and the institutional mechanisms to achieve those norms, are they expected to conduct themselves unethically. Meanwhile, innovations can arise when the deviant organizations accept the broader social goals but reject the mechanisms provided to achieve them (refer to (Pals, 2015) for an overview). While traditionally such deviant actions have been perceived in behavioral terms (such as whistleblowing or exercising voice), there is no reason to delimit constructive deviance to exclude innovation (Demir & Knights, 2021; Vadera et al., 2013). After all innovations, as Merton would argue, would require non-conformity against established products or processes to achieve organizational goals (Heckert & Heckert, 2002).

1.3 Civic norms, resource constraints and public sector innovation

Given that budget cuts impose a financial strain on public organizations, innovations can arise when conditions are right (Demircioglu & Audretsch, 2017; Sahni et al., 2013). For instance, Glor (2001) found that council government in New Brunswick had to resort to innovative solutions under conditions of austerity provided conditions for performance imposed by the central authorities. While imposition of direct authority can be a way forward, we argue that under condition of financial scarcity, existence of strong civic norms provide the necessary strain for the public organizations to innovate.

There are two mechanisms through which civic norms might influence the effect of financial constraints on innovation. First, at broader social level, persistence of strong civic norms creates accountable political institutions that put pressure on public organizations to perform even during times of financial stress. In other words, it makes “citizens sophisticated consumers of politics” (Boix & Posner, 1998). This is because societies with stronger civic norms are more likely to 1) be vigilant and to monitor government performance (Coffé & Geys, 2005); 2) engage in policy activism and collective bargaining to demand policy changes (Coffé & Geys, 2005; Tavits, 2006); and 3) punish non-performing politicians (Nannicini et al., 2013). Under circumstances where resources to insource knowledge on popular will is scarce, vocalization and representation of people’s demand reduces the cost of gathering information for public organizations. At the same time, the political and bureaucratic demand to perform is also likely to be higher and therefore, constraints on institutional mechanisms likely to put larger strain on public organizations.

Second, at the organizational level, presence of strong civic norms is likely to lead to improved bureaucratic capacity and increased possibility to innovate. Studies show that political elites and bureaucrats in societies with strong civic norms are more likely to create an atmosphere of greater trust and compromise between and among themselves (Boix & Posner, 1998). This reduces cost of networking and coordination under strenuous conditions making innovations more viable and easier to implement (Hsin-Mei, 2006). Strong civic norms are also likely to generate greater civic sense and esprit de corps amongst public officials under such stressful conditions (Boix & Posner, 1998) while greater trust and cooperation between the public employees is likely to empower individuals within their social networks and enable them to undertake more risks (Ferris et al., 2017; Leana & van Buren, III, 1999). Therefore, greater empowerment, lower cost of networking and higher civic sense is likely to motivate public employees to innovate when financial constraints lead to strain in public organizations.

Therefore, in situations where organizations find themselves in financial stress, differences in the strength of social and civic norms can lead to differences in innovation outcomes.

H2: Strength of civic norms positively moderates the relationship between resource constraints and public sector innovation

2.1 Data

The study uses a comparative analysis to compare innovation outcomes across 21 countries in Europe. Europe makes an interesting case because several countries in Europe were highly affected due to the crisis although the financial crisis originated in the United States (IMF, 2012). Europe was also the epicenter of the fiscal crisis and the consequent austerity measures. More relevant for the purpose of this study, due to the variations in the extent and the nature of the crisis, fiscal measures implemented by the member countries in Europe were also variant, providing a well-suited context to perform a comparative study in the region (Kickert et al., 2015; Randma-Liiv & Kickert, 2017a). The study uses data from the COCOPS Executive Survey, under the COCOPS project, which was designed and implemented by the European Commission between 2012 and 2015 to understand the impact of the NPM reforms on public administrations covering 21 European nations (Hammerschmid et al., 2013; Suzuki & Hur, 2020). The survey includes responses from 9,333 public administration executives from 21 European countries (a response rate of 25%). The survey consists of a wide range of indicators that measure organizational management, performance, and behavior; for the purpose of this study, it additionally includes a separate section on the extent of impact the fiscal crisis had on the respondents’ organizations and the measures undertaken by those organizations in response.

To measure the role of civic values on innovation, we used the European Values Survey and the World Governance Indicators (WGIs). The penultimate wave of the European Values Survey was administered in 47 different countries between 2008 and 2010 which conveniently matches the years of great recession and the era of fiscal crisis. In the study, adult population (18 years and older) was surveyed across a wide range of social indicators including, among other things, various aspects of the civic lives and norms of the people in the countries from which we construct a variable that measures civic norms. (Gedeshi et al., 2011). Finally, we used the 2010 corruption perception index under the WGI constructed by the World Bank to measure the extent of breakdown of civic norms at various European nations.

2.2 Variables

2.2.1 Dependent variable

Our primary dependent variable (innovation outcome) is a response to the question “Thinking about your policy area over the last five years how would you rate the way public administration has performed on innovation outcomes” in the COCOPs Survey. The question in the survey is contextualized in the overall response of the public sector in European Union to the public sector report due the fiscal crisis of Great Recession. This question was first analyzed as a continuous and subsequently as an ordinal variable with response ranging from (1) deteriorated significantly to (7) improved significantly.

2.2.2 Independent variable

Our independent variable is resource constraint. To measure the severity of constraint placed upon the organization, the survey asks the respondents the response of the organization in response to the fiscal crisis in terms of budget cuts in 9 categories. We created a composite scale variable budget_cuts based on the 9 variables (Cronbach’s alpha 0.76) to measure the degree of resource constraints faced by the organizations.

The moderator variable (civic_norms) was created using the responses from the European Values Survey 2008. Following Dakhli and De Clercq (2004), we conceptualized civic_norms in terms of four dimensions: associational activity (association), trust in existing governmental institutions (trust), tolerance towards non-conformism (tolerance) and ethical responses to negative civic behavior (ethics). Specifically, associational activity of respondents was measured using a scale of their membership in 15 different social, political and religious bodies (more details in Appendix 2) (Cronbach’s alpha 0.7). Trust in social institutions was measured with a similar scale that measured the level of confidence that respondents had for 18 social institutions (Cronbach’s alpha 0.88). Tolerance towards non-conformism, included by us since innovation itself is in essence deviancy from normal response to a social situation (Coser, 1962; Merton, 1968), was measured using 15 components where respondents were asked if respondents would welcome certain groups of people as their neighbors (Cronbach’s alpha 0.80). Finally, ethical acceptance of negative social behavior was measured as a scale of 7 unethical behaviors such as avoiding taxes, joyriding, and lying (Cronbach’s alpha 0.79). We conducted a principal component analysis using the first component to create an overall index of social capital of the 21 different European countries. As a robustness test, we proxied the level of deterioration of civic norms using the level of corruption in the country. We used estimates of Control of Corruption Values from the World Bank’s World Governance Indicators to measure the moderating effect of level of corruption on the innovation outcomes.

2.2.3 Control variables

We used control variables at organization and national level. At organizational level, type of public organization (ministry or agency, national or regional), size of the organization, and its policy area were used as control variables. At national level, we control for the level of human development (HDI level) of the country to account for its human capital, its level of economic development (GDP per capita in purchasing power terms), and the level of government debt to GDP all in pre-crisis terms measured in 2007. Given the data was available on request, respondents’ identifiers such as age, gender, and experience (i.e., individual level controls) were not available for adjustment.

[Insert Table 1 about here]

Table 1

Descriptive statistics of variables
Variable	Obs	Mean	Std. Dev	Min	Max
Organization level
Innovation (innovation)	6,452	4.565	1.351	1	7
Budget cuts (budget_cuts)	5,914	3.797	1.244	1	7
Organization type (org_type)	7,201	1.649	0.573	1	3
Ministry at central level	2,889	1	0	1	1
Agency at central level	3,951	2	0	2	2
Ministry at regional level	361	3	0	3	3
Organization size (size)	7,185	3.489	1.513	1	6
< 50	918	1	0	1	1
50–99	673	2	0	2	2
100–499	2,551	3	0	3	3
500–999	993	4	0	4	4
1000–5000	1,124	5	0	5	5
Over 5000	926	6	0	6	6
6,859	6.716	3.75	1	13
National level
Civic norms (civic_norms)	21	-0.021	0.487	-0.713	1.072
GDP Per capita (PPS) (gdpc)	21	100.645	35.66	39	176
Corruption index (corrupt)	21	-0.304	0.921	-1.45	1.35
Debt to GDP ratio (debt)	19	52.703	22.36	7.20	110.20
HDI (hdi)	21	0.868	0.054	0.758	0.936

Descriptive statistics of all given variables are provided in Table 1. Following Suzuki and Hur (2020), we conducted a VIF test to measure the level of correlation between variables to test for the problem of multicollinearity (Appendix 1). We found that a country’s HDI level and GDP per capita are highly correlated and given marginally higher explanatory power of HDI, use HDI as a measure of level of development. All other variables have VIF scores of less than 5.

2.3 Method

Due to the hierarchical nature of our data (public organizations are nested within countries that they reside), we conducted a multilevel analysis to test for the association between national level factors and organization-level outcomes (Hox, 1998; Lapuente & Suzuki, 2020; Suzuki & Hur, 2020). We employed a random-intercept model and a random-intercept and random-slope model to validate the robustness of our findings (Snijders, 2005). Given the multitude of the levels of our dependent variable, we initially used our dependent variable as a continuous variable and support the findings by testing it as an ordinal variable. We tested the robustness of the findings using four regression regressions. The first model only included the dependent variable (as a continuous variable), the independent variable and the interaction term. The second and the third model controlled for organization level and national level variables respectively. The fourth model includes dependent variable as an ordinal variable and is estimated using a random-intercept and random-slope model.

Table 2 displays the results of first set of regressions. Four models are reported. Model 1 displays relationship between our main independent variable and the dependent variable assuming innovation is a continuous variable. Model 2 and 3 include organization level and national level control variables. In model 4 we relax the assumption of linearity and conduct a multilevel ordered logit regression. The findings strongly support H1. Across all four models, we noticed a strong negative relationship between budget cuts and innovation outcomes in public organizations (p < 0.00), suggesting that under general circumstances, public organizations require strong financial support to generate innovative outcomes. The statistical significance of the variance of level 2 coefficient and the intraclass correlation coefficient, provided support for our use of the multilevel model. Regarding the control variables, the results showed that regional bodies were less innovative than central bodies, while organization size seemed to have no association with innovation outcomes. Meanwhile, relationship between sectoral classification of organizations and innovation outcomes displayed interesting patterns. Crucial sectors including health, education and environmental protection were less innovative than general government services. National-level control variables, however, were found to have no effect on innovation outcomes.

Table 2

Mixed models depicting relationship between budget cuts and innovation outcomes
Innovation outcome	Model 1	Model 2	Model 3	Model 4
Budget cuts	-0.097***	-0.095***	-0.099***	-0.123***
	[0.017]	[0.018]	[0.019]	[0.029]
Organization type (1 = Ministry at Central Level)
Agency at central level		0.016	0.014	0.062
		[0.043]	[0.045]	[0.064]
Ministry at regional level		-0.234**	-0.224**	-0.278*
		[0.112]	[0.109]	[0.161]
Organization size (1 = < 50 employees)
50–99 employees		-0.109	-0.051	-0.083
		[0.081]	[0.089]	[0.128]
100–499 employees		-0.103	-0.067	-0.084
		[0.065]	[0.073]	[0.105]
500–999 employees		-0.07	0.009	0.012
		[0.075]	[0.081]	[0.115]
1000–5000 employees		0.05	0.083	0.148
		[0.074]	[0.082]	[0.117]
Over 5000 employees		0.049	0.101	0.21*
		[0.079]	[0.085]	[0.122]
Policy area (1 = General government)
Foreign affairs		-0.025	0.01	-0.018
		[0.108]	[0.109]	[0.152]
Finance		0.104	0.16*	0.249*
		[0.081]	[0.091]	[0.13]
Economic affairs		-0.068	-0.043	-0.055
		[0.080]	[0.086]	[0.121]
Infrastructure and transportation		-0.309***	-0.275***	-0.340***
		[0.086]	[0.091]	[0.129]
Defense		-0.298**	-0.293**	-0.320*
		[0.130]	[0.129]	[0.187]
Justice, public order & safety		-0.174**	-0.173**	-0.243**
		[0.079]	[0.081]	[0.114]
Employment services		-0.258***	-0.224**	-0.285**
		[0.093]	[0.095]	[0.134]
Health		-0.313***	-0.260***	-0.415***
		[0.091]	[0.094]	[0.133]
Other social protection and welfare		-0.127	-0.1	-0.114
		[0.084]	[0.086]	[0.123]
Education		-0.170**	-0.183**	-0.275**
		[0.086]	[0.088]	[0.123]
Environmental protection		-0.163*	-0.188**	-0.254**
		[0.086]	[0.09]	[0.127]
Recreation, culture, religion		-0.350***	-0.396***	-0.577***
		[0.098]	[0.102]	[0.144]
HDI			-0.89	-2.555
			[1.59]	[2.894]
Debt			-0.001	-0.001
			[0.002]	0.003
Constant	4.976***	5.152	5.954
	[0.086]	[0.121]	1.427
Variance [residual]	1.761***	1.699***	1.6***	0.112***
	[0.033]	[0.033]	[0.033]	[0.050]
Observations	5745	5324	4714	4714
Groups	21	21	19	19
Residual Interclass Correlation	0.034***	0.039***	0.035***	0.033***
	[0.012]	[0.013]	[0.013]	[0.014]
* p < 0.05, p < 0.01, * p < 0.001, standard errors in parenthesis

[Insert Table 2 about here]

To examine the potential moderating effect of civic norms, we introduced an interaction term civic_norms*budget_cuts. The results from the regressions are presented in Table 3. The sign of the interaction term was positive and coefficient was significant suggesting civil norms positively moderates the relationship between fiscal constraints and innovation outcomes (p < 0.00). To test the validity of our moderator variable, we also tested corruption as a potential proxy for deterioration of civic norms in the same model. As expected, the findings are consistent with our theoretical framework and the overall results provide strong support to H2.

Table 3

Mixed models depicting the moderating role of civic norms on budget cuts and innovation outcomes
Innovation outcomes	Model 5	Model 6
Budget cuts	-0.111***	-0.146***
	[0.019]	[0.024]
Civic norms	-0.549**
	[0.221]
Corruption		0.449***
		[0.169]
Budget cuts * civic norms	0.160***
	[0.041]
Budget cuts * corruption		-0.089***
		[0.026]
Organization type (1 = Ministry at Central Level)
Agency at central level	0.009	0.011
	[0.045]	[0.045]
Ministry at regional level	-0.2*	-0.216*
	[0.110]	[0.111]
Organization size (1 = < 50 employees)
50–99 employees	-0.059	-0.05
	[0.089]	[0.089]
100–499 employees	-0.067	-0.063
	[0.073]	[0.073]
500–999 employees	0.006	0.011
	[0.081]	[0.081]
1000–5000 employees	0.074	0.082
	[0.082]	[0.081]
Over 5000 employees	0.094	0.098
	[0.085]	[0.085]
Policy area (1 = General government)
Foreign affairs	-0.035	0.006
	[0.109]	[0.109]
Finance	0.159*	0.150*
	[0.091]	[0.091]
Economic affairs	-0.041	-0.041
	[0.086]	[0.086]
Infrastructure and transportation	-0.28***	-0.274***
	[0.091]	[0.091]
Defense	-0.295**	-0.305*
	[0.129]	[0.129]
Justice, public order & safety	-0.176**	-0.173**
	[0.081]	[0.081]
Employment services	-0.242**	-0.235**
	[0.095]	[0.095]
Health	-0.272***	-0.271***
	[0.094]	[0.094]
Other social protection and welfare	-0.103	-0.104
	[0.086]	[0.086]
Education	-0.186**	-0.187**
	[0.088]	[0.089]
Environmental protection	-0.198**	-0.196**
	[0.09]	[0.09]
Recreation, culture, religion	-0.407***	-0.404***
	[0.102]	[0.102]
HDI	-1.57	0.632
	[1.96]	[2.738]
Debt	-0.001	-0.001
	[0.002]	0.002
Constant	6.60***	4.899
	[1.734]	[2.348]
Variance [residual]	1.59***	0.112***
	[0.033]	[0.050]
Observations	4714	4714
Groups	19	19
Conditional Interclass Correlation	0.029**	0.027**
	[0.013]	[0.014]
* p < 0.05, p < 0.01, * p < 0.001, standard errors in parenthesis

[Insert Table 3 about here]

Given that results from Model 1 and Model 5 show that assuming a linear relationship between our variables of interest does not lead to significant loss of information (if any there is an underestimation of the effect), for the ease of visualization we persisted with the linear model. Figure 1 provides a visual representation of the marginal relationship between our primary variables of interest. In the x-axis is the budget_cuts variable, and the movement along the x-axis represents increase in extent of cutback measures applied by the organizations. The y-axis presents linear predictions on the change in innovation outcomes where movement upwards the y-axis represents greater innovation outcomes. The five-different curves represent 5 different levels of civic norms separated by its standard deviation. Overall, the results showed that the effect of budget cuts on innovation was highly contingent on the level of national civic norms. At lower levels of civic norms, there was a strong negative relationship between budget cuts and innovation and larger budget cuts consistently led to deteriorating innovation outcomes. However, rise in civic norms moderated this relationship and at highest levels of civic norms, as predicted by the framework, one can notice a positive relationship between budget cuts and innovation outcomes.

As an additional note, even after including the moderating effect, we still found persistent negative relationship between power distance and innovation outcomes, i.e., regional bodies, were found to be less innovative than central ones. Similar relationship was noticed in terms of policy sectors as well with sectors such as employment services, health services, education and environmental protection continuing to show worse performances than general public administration.

The purpose of this paper was to examine the relationship between fiscal constraints, innovation and institutional environment under which such constraints are operational. We argued that fiscal constraints limit the potential for public organizations to innovation. Furthermore, we also developed a theoretical framework based on Merton’s strain theory of deviance to conceptually demonstrate that such fiscal constraints might incentivize public managers to pursue more innovative solutions to the social problems under conditions of strong social norms

The first important finding of the study is that, indeed in European countries, severe fiscal constraints limited their ability to innovate. Even after controlling for country-level effects, public managers reported that innovation outcomes were more difficult under situations of fiscal stress. The findings are not surprising. Raudla et al. (2013, p. 38) have provided a detailed overview on various empirical reasons on why change management and innovation is difficult under conditions of fiscal austerity. To elaborate, under conditions of human resource cutbacks, tacit and institutional knowledge embedded within individuals lead to non-linear reduction in organization’s learning capacity which significantly impedes innovation (Fisher & White, 2000). For instance, Rusaw (2004) reports how ‘hollowing out’ of the government has led to significant delays in public service delivery, inability to adjust to growing social problems, and its ability to monitor and enforce rules and regulations. At the same time, general and personnel cutbacks significant reduce the degree of cooperation and inter-personal trust within public organizations that lead to lack of transfer of knowledge and information critical for innovation (Raudla et al., 2013). In their survey of public sector executives in the US, Ingraham and Barrilleaux (1983) find that cutbacks lead to loss of organizational trust due to greater competition for resources and diminished career opportunities and argue for greater financial incentives to encourage cooperation. At the same time, conditions of prolonged stress diminish the propensity for managers to take risks or deviate from existing rules (Levine, 1979). Winchell (1982) reported that during times of fiscal stress, even inadvertent deviance from prevalent practices amongst local governments, created such bureaucratic pushback that employees strongly resisted changes from norms.

Second, our theoretical framework and the subsequent findings show that civic norms play an important role in determining innovation outcomes due to changes in fiscal constraints. The framework conceptually predicts that when fiscal strain is imposed under conditions of strong social norms, public organizations have greater incentives and capacity to innovate. The empirical findings from the study strongly support this claim. More importantly, the findings corroborate with literature from political science where studies have shown that government and politicians’ performances are positively correlated with social capital. For instance, Nannicini et al. (2013) found that voters in regions with stronger social capital in Italy frequently punished politicians for their misdemeanors, which led to better public institutions. Knack (2002) also found similar results amongst various states in the US where better social capital was associated with greater government efficiency and general performance.

The study investigated the role played by financial constraints in determining innovation outcomes in public organizations amidst European countries. The study combined the data from the COCOPS and the EVS datasets to create a novel dataset to examine the role of fiscal constraints and civic norms on innovation outcomes. Overall, the findings of the study show that financial constraints negatively affected innovation outcomes of public organizations in European countries. In addition, the study also shows that organizations in countries with stronger civic norms are more likely to have better innovation outcomes while facing such constraints. The findings illustrate that exerting undue pressure on public bodies to enhance their innovation outcomes while simultaneously reducing their budget might not be a fruitful exercise.

This study makes several contributions to the public service innovation literature. At a conceptual level, it constructs a framework for understanding the role broader social institutions can play in determining innovation outcomes in public organizations. At an empirical level, it provides evidence on the potentially negative impact fiscal constraints might have on innovation outcomes. The study also provides much needed evidence on the importance of conducting cross-country comparative study by highlighting the important role social institutions play in determining innovation outcomes in the public sector.

While saying so, there are important limitations to our study. First, the analysis was done based on self-reported perceptions of senior executive level which might result in an upward bias in the level and degree of innovation and change that occurs at employee level (Dobni et al., 2015; Jones et al., 2008). Second, due to data limitations, the study only controlled for limited number of organization and national level variables and does not account for the role employee or within-organization level variables can play in determining innovation outcomes. Third, due to the nature of the survey, the concept of innovation in the survey and consequently study is underdeveloped. This does not permit us to explore various nuances of the nature or the effects of undertaken innovation.

COCOPs

Coordinating for Cohesion in the Public Sector of the Future

EVS

European Values Survey

GDP

Gross Domestic Product

Hypothesis 1

Hypothesis 2

HDI

Human Development Index

IMF

International Monetary Fund

NPM

New Public Management

WGS

World Governance Survey

VIF

Variance Inflation Factor

Availability of data and materials: Various sources of data were used for this study. The data from the Coordinating for Cohesion in the Public Sector of the Future (COCOPs) project and the European Values Study is available from the Leibniz Institute for the Social Sciences upon request.[1][2]Similarly, World Governance Indicators and Human Development Indexes are publicly available at the websites of the issuing institutions.

Competing interests: The author does not have any conflict of interest to disclose.

Funding: This work was supported by the National University of Singapore Research Scholarship.

Author’s Contribution: SK worked on conceptual framing of the manuscript. SK also worked on data analysis, writing and editing of the manuscript. The manuscript is solely authored by SK.

Acknowledgement: I am grateful to the guidance and support provided by Dr. You-Na Lee. I am also thankful to Jingyuan Xiao for her valuable suggestions.

[1]https://search.gesis.org/research_data/ZA6599

[2]https://search.gesis.org/research_data/ZA4800?doi=10.4232/1.12458

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Innovation under Fiscal Constraints: Evidence from Public Sector in Europe

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Abstract

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1. Introduction

1.1 Financial constraints and innovation

1.2 Social norms, resource constraints and innovation

1.3 Civic norms, resource constraints and public sector innovation

2. Methods

2.1 Data

2.2 Variables

2.2.1 Dependent variable

2.2.2 Independent variable

2.2.3 Control variables

2.3 Method

3. Results

4. Discussion

5. Conclusion

Abbreviations

Declarations

References

Supplementary Files

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