Blaming the bureaucrat: does perceived blame risk influence inspectors’ enforcement style?

Abstract

Is there a relation between street-level bureaucrats’ enforcement style and their perception of the risk of getting blamed? This article answers this question on the basis of a survey (n = 507) among inspectors of the Netherlands Food and Product Safety Authority. We included perceived media attention on their work as a factor that might influence street-level bureaucrats’ perception of blame risk and their enforcement style. Three dimensions of enforcement style were distinguished from earlier research: legal, facilitative and accommodative. We found that when inspectors perceive more blame risk, they employ a slightly less legal style and, instead, employ a more accommodative style. Thus, they act a little less formally and less coercively (i.e. legal) and take greater account of their peers’ opinions (i.e. accommodative). However, perceived media attention did not have a significant influence on enforcement style.

Points for practitioners

1. When inspectors perceive more blame risk, they tend to pay more attention to the opinion of peers (other inspectors, supervisors, etc.).

2. Blame risk does not lead to the use of a more formal inspection style.

3. Media attention does not play an important role in enhancing the blame risk perception of inspectors.

4. This media and blame risk is less important than often found in the case of politicians. This may be connected to the fact that the work of inspectors as street-level bureaucrats is less visible to the wider public (and the media).

Keywords

blame avoidance blame risk enforcement style inspectors street-level bureaucrat

Introduction

Inspectors are typical street-level bureaucrats with considerable discretion and autonomy, who enforce policies during interactions with inspectees. During these encounters, inspectors risk being blamed for their actions (Gilad et al., 2018; Hood, 2011).

Hood (2011), whose seminal book has become a major reference in the literature on blame, points out that blame risk and its negative consequences can be found at all levels of administration, from politicians to street-level bureaucrats, such as inspectors. However, very little research actually focuses on street-level bureaucrats. Recent literature focuses more on citizens who blame political actors and other actors in policy processes (see, for instance, Marvel and Girth, 2015; Olsen, 2017; Piatak et al., 2017), or on how politicians react to blame (Baekkeskov and Rubin, 2017; Hinterleitner and Sager, 2015; Nielsen and Baekgaard, 2013). Moreover, blame risk itself, as an actor’s perception, is rarely directly measured.

This is remarkable because inspectors and their regulatory organizations are repeatedly under scrutiny, not just by politicians, but also by the media, inspectees and the public. An example of regulators being held responsible and receiving a great deal of blame is the horsemeat scandal in 2013, where horsemeat was found in beef products in European Union countries such as the UK, The Netherlands and France. The scandal led to massive criticism in the media and society, as well as in the political sphere, regarding the regulatory agencies in those countries (Ibrahim and Howarth, 2017; The Guardian, 2016).

Blame risk as a conditioner of inspector style

The risk of blame (‘blame risk’) influences the way in which organizations work and how their members behave (Hood, 2011). The literature on blame risk and blame avoidance – a behavioural strategy of actors who perceive blame risk – emphasizes that actors act differently and apply certain blame avoidance strategies to counter the possible negative effects of blame (Hinterleitner and Sager, 2015; Hood, 2011; Nielsen and Baekgaard, 2013). As Hood (2011) argues in The Blame Game, street-level bureaucrats, such as inspectors, are regularly blamed for what they do. Moreover, the recent trend towards more transparency and the disclosure of performance information about public organizations is argued to increase the risk of blame as the performance of street-level bureaucrats becomes more visible and, in turn, open to scrutiny (De Boer et al., 2018; Ellerman, 2006; Van Erp, 2011). An interesting – but not well-researched – question is thus how the perceived blame risks of street-level bureaucrats (in our case, inspectors) influence their behaviour during inspections, particularly their enforcement style (May and Wood, 2003). Given the blame risk literature (and especially Hood’s work), we expect a significant influence of blame risk on inspectors’ enforcement style.

This study: inspectors’ blame risk perception and its consequences

According to Lipsky (1980), street-level bureaucrats such as inspectors have considerable discretion in the implementation of rules and regulations. Inspectors enforce rather than implement public policies when encountering inspectees. Their enforcement attitude has been substantially studied using the concept of enforcement style. An inspector’s enforcement attitude is complex and consists of multiple dimensions that can be combined or highlighted separately to assess inspectees’ compliance (De Boer, 2019; Lo et al., 2009; May and Winter, 2011). In this article, we study whether inspectors’ perception of blame risk influences three dimensions of their enforcement style. We thus study one specific, but often discussed, driver of street-level bureaucrats’ behaviour. We also look at an important context of blame risk: the media attention that their work receives. We focus on the media’s role for two reasons: first, in the blame risk and blame avoidance literature, media attention is treated as an important possible trigger of blame risk (Hood, 2011; see also, e.g., Hinterleitner and Sager, 2015); and, second, the literature on media attention emphasizes that it has a certain negativity bias in that negative news attracts more attention than positive news does (Bennett, 2009; Esser and Strömbäck, 2014; Mazzoleni and Schultz, 1999). This suggests that a high level of media attention implies increased attention on regulatory failure (instead of regulatory success) and, accordingly, increased blame risk. Thus, we look at perceived media attention as a variable that possibly increases blame risk. Our research question is: How do inspectors perceive blame risk, and to what extent does this influence the enforcement style that they employ?

This study focuses on inspectors from the Netherlands Food and Consumer Product Safety Authority (NVWA). These inspectors are concerned with food safety and perform on-the-spot inspections of organizations such as restaurants and the fish and meat industries. For the analysis, we conducted a survey among all NVWA inspectors (507 respondents).

This article first presents a theoretical framework in the second section, focusing on the concept of blame risk and how it affects enforcement styles. The theoretical framework also addresses a possible source of blame risk often mentioned in the blame risk literature: media attention on inspectors’ work. Then, the article elaborates on the research design in the third section and the results in the fourth section. We end with conclusions and reflections in the fifth section.

Blame risk, blame avoidance and inspector styles: A theoretical framework

In the blame world, public individuals, such as politicians, public managers and also street-level bureaucrats (Hood, 2011), can and will be held personally accountable for possible mistakes, wrongdoings or crises, which, blame risk authors argue, will affect their behaviour (Ellermann, 2006; Nielsen and Baekgaard, 2013; Weaver, 1986). In this section, we discuss the mechanism of blame risk and how it could affect inspectors’ enforcement style. We first elaborate on the blame risk concept and the possible consequences for actors’ behaviour, as discussed in the literature. We then turn to enforcement styles and elaborate how these could be affected by blame risk. We also discuss a possible important factor influencing inspectors’ blame risk perceptions: the media attention that they perceive on their work.

The mechanism of blame risk and blame avoidance

Hood (2011: 6) argues that what public officials are dealing with is the risk of blame: ‘the act of attributing something considered to be bad or wrong to some person or entity’. Being blamed is often experienced as a negative phenomenon; therefore, people try to reduce the blame risk, and this behavioural reaction is called blame avoidance behaviour (Hinterleitner and Sager, 2015; Hood, 2011; Weaver, 1986). Hood (2011: 7) argues that blame involves two sets of actors – blame makers and blame takers – and blame risk can come from many sources, such as oppositional politicians, the public and, last but not least, the media (Hinterleitner and Sager, 2015).

According to the blame avoidance literature, public officeholders care about blame risk because of their psychological traits and because they think it affects their personal career prospects (Hood, 2011; Nielsen and Baekgaard, 2013). Blame risk arises at every level of public organizations: managers, professionals and street-level bureaucrats. Hood emphasizes that blame avoidance is an inherent characteristic of life in general, and certainly public life. He argues that variations in concern about blame are part of the social setting in which individuals function. Thus, the importance of blame risk is not constant, but varies with aspects such as organizations’ culture and leadership, the external attention on a specific behaviour, and also probably the type and visibility of tasks done (Ellermann, 2006; Hood, 2011). Hinterleitner and Sager (2015) emphasize that blame risk depends on both institutional (mainly related to the political system) and non-institutional factors (like the type of issue and media attention).

The lion’s share of the blame risk and blame avoidance literature is about political officeholders, who are under much stronger scrutiny than others. This makes our research – which focuses on street-level bureaucrats, who are, for instance, less visible and less prone to media attention than elected officials, Hood (2011: 30–31) argues – all the more interesting.

Scholars argue that blame avoidance is central to understanding the behaviour of public officials (Hood, 2007; Weaver, 1986). Blame avoidance is, then, the behavioural consequence of blame risk and, according to most of the literature, stems from the fact that potential losses (blame) are weighted more heavily than potential gains (credit) (Weaver, 1986). Blame avoidance thus results in defensive (political and bureaucratic) behaviour. Various behavioural strategies for blame avoidance are discussed in the literature. Hinterleitner and Sager (2017) discuss differences between anticipatory and reactive forms of blame avoidance. Hood (2007, 2011) makes a distinction between agency strategies, presentational strategies and policy strategies, but almost all authors argue that blame avoidance influences how street-level bureaucrats perform their jobs (Hood, 2011) – what we call their ‘enforcement style’.

Behavioural consequences: blame avoidance and its effects on enforcement style

Inspectors are not mechanical implementers of policies; they have autonomy in their daily tasks and certain room to implement policies in ways they see fit (Lipsky, 1980). As Lipsky emphasizes, bureaucrats cope with various kinds of pressures, such as scarcity of time and resources, and the inadequacy of information (Hill and Hupe, 2009; Lipsky, 1980). This particularly holds for inspectors, who, as public officials, have to ensure that societal actors comply with public regulations and sanction accordingly.

Enforcement style can be studied at the organizational or the individual level (May and Winter, 1999, 2011). These two levels of enforcement are interrelated because the organization sets the boundaries within which individual bureaucrats execute their enforcement. As the focus here is on the individual level, enforcement style is defined as ‘the character of the day-to-day interactions of inspectors when dealing with representatives of regulated entities’ (May and Wood, 2003: 119). Although enforcement style was traditionally seen as one-dimensional (Kagan, 1994), there is now consensus that it is multidimensional. However, there is some disagreement about whether it is composed of two or more dimensions (e.g. De Boer, 2019; Lo et al., 2009; May and Winter, 1999, 2011). May and Winter’s (1999, 2011) conceptualization has long been the most followed. They define enforcement style as being composed of formalism and coercion: the former concerns sticking to rules rigidly and a degree of flexibility, whereas the latter concerns threatening with sanctions. However, May and Winter themselves note that there may be even more dimensions.

Recently, scholars have followed up on this idea and started to explore whether enforcement style has more than two dimensions (De Boer, 2019; De Boer et al., 2018; Lo et al., 2009). De Boer’s (2019) work is devoted solely to developing a measurement instrument and identifying the number of underlying dimensions. De Boer (2019) draws on Lo et al. (2009), who identify a total of five dimensions of enforcement style in a Chinese context, and she convincingly shows that there are three dimensions in a Western context. The first dimension, labelled ‘legal’, is composed of both formalism and coercion. To illustrate, an inspector could articulate the consequences of non-compliance to inspectees. The second dimension is ‘facilitative’ and ‘encompasses the communicative function … of the law while considering circumstances at hand’ (De Boer, 2019: 9). To illustrate, an inspector can provide an inspectee with a tip on how to improve compliance when he/she feels that the inspectee may benefit from that. Lastly, the ‘accommodative’ dimension is more cognitive in nature and addresses the degree to which opinions of others, such as supervisors, are considered when the inspector conducts the inspection visit. An inspector could, for instance, consider that their team leader is very polite during inspections and, in turn, also be very polite themselves. These three dimensions can be combined in varying constellations and to varying extents, and constitute an inspector’s total enforcement style. This study follows this most recent conceptualization in the enforcement style literature.

From the literature on blame risk and the shaming of street-level bureaucrats, it can be expected that the risk of receiving blame is an important condition (Hood, 2011; Van Erp, 2011). We therefore explore how blame risk possibly influences enforcement style. Various authors argue that a well-known blame avoidance strategy is protocolling (see, for instance, Hood, 2011). In this strategy, actors, especially street-level bureaucrats, stick very strongly to the rules in order to avoid any blame afterwards. This strategy of hiding behind rules is also mentioned in earlier research about bureaucracy and bureaucratic behaviour as a possible strategy to cope with criticism (see, for instance, Kiser, 2010). Thus, given the literature on bureaucracy and blame avoidance, we may expect that more perceived blame risk leads to a more formal enforcement style. This leads to the first hypothesis:

H1a: When inspectors perceive more blame risk, this will correlate with a higher score on the legal dimension of their enforcement style.

However, applying a more legalistic style may not be inspectors’ only reaction to blame (risk). They may also use what Hood (2011) has called a more presentational strategy, in particular, using argumentation strategies to decrease the possibility of blame or to frame behaviour in such a way that they cannot, or cannot easily, be blamed. In the facilitative style, inspectors explain more to inspectees about both the rules that are applicable and their own decisions. Therefore, using a more facilitative enforcement style is an anticipatory blame avoidance strategy to reduce the possible risks of blame (Hinterleitner and Sager, 2017). This is in line with research which shows that citizens attribute less blame when they receive more information about the context (Piatak et al., 2017). Thus, our second hypothesis is:

H1b: When inspectors perceive more blame risk, this will correlate with a higher score on the facilitative dimension of their enforcement style.

The blame risk literature mentions another important blame avoidance strategy deployed by street-level bureaucrats to diminish blame risks, called ‘herding’. The aim of this strategy is to shield them from possible challengeable decisions by sharing responsibility with others (Hood, 2011). This can be done, for instance, by taking decisions not separately, but in a group, as well as by including supervisors in decisions in order to shield oneself from possible blame later on. Several authors (Hinterleitner and Sager, 2017; Hood, 2011; Weaver, 1986) argue that this is a well-known strategy in a bureaucracy. This observation matches others on street-level bureaucracy, for instance, Maynard-Moody and Musheno (2003) and Kiser (2010) emphasize that street-level bureaucrats, and especially their behaviour, are influenced by their peers and the micro-network in which they are located. Reasoning from the blame avoidance strategy of herding likely means that inspectors will pay more attention to the opinion of their peers (e.g. other inspectors, as well as their superiors) if they perceive more blame risks. Accordingly, translating this into a hypothesis, we expect the following:

H1c: When inspectors perceive more blame risk, this will correlate with a higher score on the accommodative dimension of their enforcement style.

Media attention as a factor for blame risk

In the literature on blame risk, media attention is mentioned as a very important factor that influences blame risk and especially increases the negativity bias that is an important element of blame risk (see Hinterleitner and Sager, 2015: 146; Hood, 2011: 11). However, there is also a wide literature in the field of media studies (Bennett, 2009) and agenda-forming studies (Baumgartner and Jones, 2009) that emphasizes the negativity bias in the media and the tendency to blame and search for ‘scapegoats’. The argument goes that, in general, more media attention leads to more negative than positive attention (Baumgartner and Jones, 2009; Bennett, 2009). This focus on negativity can be explained by some of the institutional rules of the media, which focus strongly on getting as many readers (newspapers), viewers (TV or podcasts and videos) or followers (blogs) as possible. It is argued in the literature on mediatization that negativity attracts more readers than positive reports do (Bennett, 2009; Mazzoleni and Schultz, 1999). The media tends to be more negative and often uses frames that embrace issues such as blame (Bennett, 2009; Hjarvard, 2008). Thus, the media amplifies negative bias and signals (Kasperson, 1992; Korthagen and Klijn, 2014), potentially leading to more blame risk (Bennett, 2009; Hinterleitner and Sager, 2015; Hood, 2011).

The existing literature shows that intense media attention influences the behaviour of politicians and public managers (e.g. Corner and Pels, 2003) and has a negative effect on governance performance (Korthagen and Klijn, 2014). Thus, we also expect that media attention will increase the likelihood of inspectors perceiving more blame:

H2: When inspectors perceive more media attention on their work, they will perceive more blame risk.

Figure 1 presents the conceptual model of this research.

Figure 1.

Conceptual model of the research.

Research design and measures

The conceptual model developed in the previous section was tested in a survey among NVWA inspectors. The NVWA is tasked with regulating the safety of food, consumer products, animal welfare and nature. Its authority ranges across numerous sectors and many companies, for instance, the catering industry (about 80,000 companies) and slaughterhouses (about 200). It is one of the largest regulatory agencies in The Netherlands (with 1,201 inspectors). Its size, which allows for a large-n survey, and its prominent role as an inspection agency make the NVWA an important actor that is relevant and suitable for studying blame risk among street-level bureaucrats by way of a survey.

Data sample

The data for this research were collected through an online survey among inspectors in the autumn of 2016. All inspectors work in three NVWA domains: consumer and safety; agriculture and nature; and veterinary and import. Those domains were selected because only inspectors in these domains conduct inspection visits.

Out of 1,201 inspectors, 679 completed the questionnaire, resulting in a response rate of 56.5%. From this group, we excluded 172 respondents who completed only 50% or less of the survey. This resulted in a final sample of 507 respondents.

Analysis of the demographics and division of respondents over the organizational units shows that the sample is representative of the entire population of inspectors in this organization. The most important indicators are as follows:

male/female = 72%/28%;

average age = 48 years (SD = 12.9); and

average work experience = 16 years.

We took several measures to ensure the validity of our data: first, we guaranteed the respondents’ anonymity and confidentiality in order to prevent biased answers; and, second, we validated the scales that we developed for this survey with 11 expert interviews before the survey, including six inspectors and five senior staff members.

Data analysis

We analysed the data through multivariate regression analysis because this is a proven and robust way to analyse relationships between multiple variables (Field, 2018; Hayes, 2018). We applied Hayes’s process tool in SPSS as it is a validated and well-recommended model for testing mediation effects (see, e.g., Field, 2018).

Variables in the analysis

The key variables to be explained are enforcement style, blame risk and media attention.

Enforcement style

Following De Boer (2019), we measure enforcement style in three dimensions: (1) legal, (2) facilitative and (3) accommodative. Each dimension was measured with four or five items on a 10-point scale (1 = never; 10 = always). Thus, a high score on a dimension for an inspector means that their style is strongly characterized by that dimension. The items are presented in Table 1.

Table 1.

Measurement items for the three dimensions of enforcement style.

Style	Items
LegalDuring inspections, I focus on:	implementing the intervention policy by following the letter of the law enforcing in an unambiguous way making strict agreements with [inspectees] executing the inspection as completely as possible upholding high standards for compliance with rules and regulations for [inspectees]
FacilitativeDuring inspections, I consider:	transferring my professional knowledge to [inspectees] giving indications to [inspectees] on how to improve compliance being as helpful as possible to clients considering the circumstances of [inspectees]
AccommodativeDuring inspections, I consider:	the opinions of inspectors from my team about enforcing the opinions of inspectors from other teams about enforcing the opinion of my team leader about enforcing the opinions of directors/head inspectors about enforcing

Blame risk

Inspectors’ perceived risk of being blamed was measured by three items on a scale from 1 (totally disagree) to 10 (totally agree). These items were:

I run the risk that problems regarding an inspection by the NVWA will be blamed on me personally by my manager.

I run the risk that problems regarding an inspection by the NVWA will be blamed on me personally by colleagues on my team.

I run the risk that problems regarding an inspection by the NVWA will be blamed on me personally by inspectees.

In the survey, we thus measured inspectors’ perception of the risk of being blamed. This is exactly what we wished to measure because it is the inspectors’ perceived risk of being blamed that initiates their action and influences their enforcement style rather than any objective indicators of blame (such as the number of mistakes measured in inspections) – of course, inspectors can also be blamed even when they do not make mistakes, but simply apply the rules.

Media attention

Media attention was measured by two items: the amount of perceived media attention by classical media (TV, newspapers and radio) and by social media (Twitter, blogs, Facebook and forums). The question was: ‘Have classical media/social media focused attention on subjects related to my division?’

Since it is not objective media attention that triggers how inspectors view the risk of being blamed, but media attention perceived by inspectors, we measured perceived attention (measured on a 10-point scale for both items). To create a variable ‘total media attention’, the two scales (classical media and social media) were combined into one scale. A low score meant that the inspector did not perceive much attention on issues in their area.

Measurement issues

Data analysis was conducted through regression analyses with mediation, using Model 4 in the process model tool developed by Hayes (2018) in SPSS (Field, 2018). As preliminary analysis showed that the data departed slightly from normality, we performed (bias-corrected) bootstrapping using 1,000 samples (Field, 2018). The means, standard deviations and correlational data were estimated via bootstrapping, as well as the standard errors, p-values and direct and indirect effects in the regression analysis.

All variables used in this research have a good Cronbach’s alpha (see Table 2). We used two control variables – years of experience and gender – because these have been mentioned in earlier literature as important (see, for instance, Kaufman, 2017).

Table 2.

Cronbach’s alpha of the variables.

Measure	Cronbach
Media attention (perceived) (2 items)	.82
Blame risk (perceived) (3 items)	.78
Legal style (5 items)	.80
Facilitative style (4 items)	.85
Accommodative style (4 items)	.83

Results and hypotheses testing

In this section, we present the results of the empirical analysis. We first look at the simple correlations between the variables. After that, we present the results of the regression analysis.

Descriptive statistics

Table 3 shows the descriptive statistics. We can see that inspectors have a high average score on the legal enforcement style (8.1/10), and this enforcement style also shows relatively little variance among the respondents (SD = 1.02). This shows that, in general, inspections are strongly characterized by a legal style, especially if we compare this with the average scores on the facilitative dimension (7.4) and the accommodative dimension (6.0), which are (much) lower. Furthermore, the average level of perceived blame risk is relatively low (4.6/10), though there is quite some variance here (SD = 2.13). However, it is obvious that blame risk is not considered very high by inspectors; this is interesting given all the publicity about scandals, as mentioned in the introduction, and news items about inspectors being intimidated during their work.

Table 3.

Correlations between the main variables.

	Variable (scales 1–10)		SD	1	2	3	4	5	6	7
1	Perceived blame risk	4.6	2.13	1
2	Legal enforcement style	8.1	1.02	−.109*	1
3	Facilitative enforcement style	7.4	1.40	.099*	.310**	1
4	Accommodative enforcement style	6.0	1.74	.142**	.145**	.333***	1
5	Perceived media attention	6.9	1.87	−.025	.097	−.007	.111*	1
6	Work experience (number of years)	16.3	11.2	−.100*	−.045	.107*	−.015	−.087	1
7	Gender (m/f)	72%/28%		.017	−.043	−.058	.107*	.103*	−.386**	1

Notes: n = 507. **p < .001; *p < .05.

There is a significant correlation between blame risk and the legal and the accommodative dimensions of enforcement style. The first relation is negative (when inspectors perceive more blame risks, they employ a less legal style), whereas the second relation is positive (a higher perception of blame risk correlates with a more accommodative style). There is a significant negative relation of the gender control variable with accommodative style and with experience. Thus, female inspectors are more likely to pay attention to the opinions of peers (other inspectors and superiors) and inspectees. The relation with experience probably has to do with the fact that the NVWA is an organization dominated by older male employees (female employees are better represented in younger age groups).

There are hardly any significant correlations between perceived media attention and enforcement style. There is only a positive relation between perceived media attention and the accommodative style: when there is more perceived media attention, inspectors tend to choose a more accommodative style.

Multivariate analysis of the data

As mentioned, we performed a regression analysis with mediation in SPSS analysis. We analysed three models to study the direct and the indirect effects on each of the dimensions of enforcement style. The results are presented in Table 4 and Figures 2, 3 and 4.

Table 4.

Result of three regression analyses of enforcement styles on perceived media attention mediated by perceived blame risk.

	Model 1 Dependent variable: legal enforcement style					Model 2 Dependent variable: facilitative enforcement style					Model 3 Dependent variable: accommodative enforcement style
	Coef.	SE	t	Sig.	95% conf. interval	Coef.	SE	t	Sig.	95% Conf. Interval	Coef.	SE	t	Sig.	95% conf. interval
Direct effects
Perceived blame risk	−.056	.026	−2.16	.031*	−.107 −.005	.066	.035	1.89	.059	−.003 .134	.117	.043	2.74	.006**	.033 .202
Perceived media attention	.031	.030	1.03	.303	−.028 .091	−.010	.039	−.262	.793	−.088 .067	.098	.051	1.905	.058	−.003 .198
Work experience	−.009	.005	−1.76	.079	−.018 .001	.014	.006	2.269	.024*	.002 .027	−.005	.008	−.568	.570	−.020 .011
Gender	−.249	.26	−1.98	.048*	−.496 −.002	−.051	.166	−.309	.757	−.378 .275	−.398	.206	−1.94	.054	−.803 .006
Constant	8.32	.248	33.58	.000	7.831 8.805	6.97	.354	19.68	.000	6.27 7.67	5.004	.450	11.12	.000	4.12 5.89
Indirect effects (completely standardized) Perceived media attention via perceived blame risk
Media attention	.001	.006			−.010 .017	−.001	.006			−.016 .008	.000	.008			−.015 .019
	Note model 1: n = 422; R² = 0.027; F = 2.56 (df1 = 4.0; df2 = 417); p = .039*					Note model 2: n = 417; R² = 0.023; F = 2.49 (df1 = 4.0; df2 = 410); p = .043*					Note model 3: n = 424; R² = 0.041; F = 3.90 (df1 = 4.0; df2 = 419); p = .004**

Note: ** p < .001; * p < .05.

Figure 2.

Results of the mediated regression analysis of legal enforcement style.

Figure 3.

Results of the mediated regression analysis of facilitative enforcement style.

Figure 4.

Results of the mediated regression analysis of accommodative enforcement style.

The three figures show that there is no direct effect of perceived media attention on enforcement style. Nor is there a mediation effect, that is, there is no indirect effect of perceived media attention via perceived blame risk on enforcement style. However, there are direct effects of perceived blame risk on the legal and accommodative enforcement styles.

Table 4 shows that all three models are significant even though their explanatory power is limited given the relatively low R² (0.027 for Model 1; 0.023 for Model 2; and 0.041 for Model 3). Table 4 also shows significant effects of perceived blame risk on legal style (negative) and accommodative style (though the coefficient of the legal style is small), and an almost significant effect on facilitative style.

This result confirms H1c: when inspectors perceive a higher blame risk, they will adopt a more accommodative style. As explained in the theoretical section, this is logical: if inspectors perceive more blame risk, they are likely to pay more attention to the opinions of their superiors and colleagues. However, it disconfirms H1a because we expected a positive effect of perceived blame risk on legal style, whereas we see a negative effect. Thus, inspectors tend to use a less legal style when they perceive risk; this is both interesting and unexpected. We reflect more on this in the conclusion.

However, media attention has no significant impact either on enforcement style or on perceived blame risk. Contrary to our expectations, (perceived) media attention on inspectors’ work does not influence the perception of blame risk. The weak relationship between media attention and blame risk also explains why there is no mediation effect. As the confidence intervals show, no indirect effect of media attention on enforcement style can be established within the confidence interval of 95%. We suggest possible explanations for this finding in the conclusion.

Conclusions and reflections

This article analysed the relation between the blame risks that inspectors perceive and their enforcement style. Additionally, the effect of perceived media attention on enforcement style was studied as a factor that may influence inspectors’ perception of blame risk. In line with the literature, we expected that when inspectors perceived more blame risk, this would result not only in inspectors using a more legal style, but also in an intensified use of a facilitative style and an accommodative style (Hood, 2011). Moreover, we expected that more media attention would increase perceived blame risk given that media attention is often mentioned in the blame risk literature as an important factor (Hinterleitner and Sager, 2015; Hood, 2011).

Empirical findings and possible explanations

The first major and surprising finding is that blame risk leads not to a more legal style, but to a less legal style, and although we did find the expected positive correlations between blame risk and accommodative style, we did not find a significant relation between blame risk and facilitative style. Despite the significant relations (blame risk and both legal and accommodative style), the explained variance is not very high, indicating that enforcement style is only limitedly explained by blame risk. Blame risk does not prove to be the strong predictor of enforcement style that we could have expected on the basis of the blame risk literature. Existing research indicates that other factors (such as the disclosure of performance information that we studied earlier (see De Boer et al, 2018)) explain more of the variance in street-level bureaucrats’ behaviour than blame risk. We therefore suggest a refinement and nuancing of blame risk theory, and argue that it should not be too easily generalized from political officeholders to street-level bureaucrats.

Perceived media attention does not have any significant impact on either blame risk or enforcement style; this is also contrary to our expectation and that of the blame risk literature. The last finding is interesting because some of the literature – though this is more aimed at elected officeholders’ blame risks (Hinterleitner and Sager, 2015; Nielsen and Baekgaard, 2013) – suggests that blame risk is enhanced by media attention on the issue, on the public organization or on the official (Hood, 2011). If we look at our findings, this is obviously less so for street-level bureaucrats, which may necessitate an adaptation of our theory about blame risk and the media. A possible explanation is that there is considerable interaction between inspectors and inspectees but that actual media attention on inspection activities is only limited. Thus, media attention may be less important, both in frequency of occurrence and in consequences, for inspectors than for elected officeholders. The latter receive more intense media attention. News value is a crucial factor for the media in selecting what to report (Bennett, 2009; Hjarvard, 2008), and the news value of the enforcement behaviour of single inspectors is probably lower than the news value of the behaviour of elected officeholders (politicians). This also means that we should look for other possible causes to explain the level of blame risk in future research on street-level bureaucrats, for instance, causes related to the nature and salience of the tasks of street-level bureaucrats, or the direct relation between their work and the political arena.

Of course, the other outcome of our research – that more blame risk leads to a less formal style of enforcement – is more difficult to explain. Possible explanations might be related to the circumstances and context in which the NVWA as a regulatory agency has to operate. As shown in the survey results, the average score for the legal dimension of inspection style is very high (8.1 on a 10-point scale, with limited variance in the variable). This means that inspectors perceive their style as already highly legal, and may therefore perceive limited possibilities for making their style even more legal than it already is. Thus, this may encourage them to try a slightly less legal style to reduce potential blame risk emanating from the inspectees. Another explanation might be found in the fact that in the case of street-level bureaucrats, the relation is actually quite different than what the literature suggests. Due to their relatively intensive relation with inspectees, compared to most other bureaucrats, inspectors may be inclined to try a more understanding approach with less emphasis on rules in order to induce a more compassionate and understanding reaction from inspectees and the wider environment, thereby reducing the risk of blame. Thus, choosing a less legal style is actually seen as a blame avoidance strategy by inspectors. The fact that we find a positive relation with the facilitative dimension of enforcement style also hints at this way of thinking as a possible explanation for this. Given that we find a significant but not very strong relation between perceived blame risk and legal enforcement style, more research on this relation is needed to be sure of the relation and its possible explanations.

Limitations of the research

Naturally, this research has limitations. Notwithstanding the advantage of a relatively large sample size of street-level bureaucrats (n = 507), which enhances the generalizability of the findings, we have only inspectors’ perceptions as data. Given the strict rules and privacy policies in Dutch inspection organizations, it was not possible to connect the survey to more objective data about inspectors (such as the number of fines or warnings issued by inspectors to inspectees). As blame risk is essentially a perception, and it is the perception of risk that drives inspectors’ behaviour, this is less of a problem in this case.

Other limitations are that we only studied one possible explanation of blame risk: media attention on the inspectors’ work. For this study, we were mainly interested in the effect of blame risk on enforcement style, but studying more antecedents of blame risk is important to increase the understanding of blame risk among public officials.

Of course, the risk of common source bias exists, which is a theme that has received a great deal of attention lately (George and Pandey, 2017; Podsakoff et al., 2012). However, we did several things to minimize common source bias, as mentioned in the literature (Podsakoff et al., 2012): first of all, the survey was initially tested among inspectors; second, we presented the dependent and the independent variable on different pages of the questionnaire; and, finally, we secured cooperation for the research and motivated the respondents by informing them through various channels of how important their participation was. This resulted in a high response rate despite the warning from some of our contact persons that NVWA inspectors are surveyed very frequently.

Despite these limitations, we believe that this study is valuable. To date, the theoretical statements about blame risk and its resulting behaviour have hardly been tested among street-level bureaucrats. Most of the literature and research is based on case-study research, and there is a lack of systematic large-scale quantitative research that provides generalized insights. Our results provide evidence that blame risk is also relevant for street-level bureaucrats but it seems less so than suggested in the literature, which focuses much more on (political) officeholders. As some of our findings indicate, especially those regarding the negative relation between blame risk and the formal dimensions of enforcement style, this is an area in urgent need of further clarification in future research.

Footnotes

Declaration of conflicting interests

The authors declare no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by The Netherlands Food and Consumer Product Safety Authority (NVWA).

Erik Hans Klijn is Professor at the Department of Public Administration and Sociology, Erasmus University, The Netherlands.

Jasper Eshuis is Associated Professor at the Department of Public Administration, Erasmus University, The Netherlands.

Alette Opperhuizen is Research Assistant at the Department of Public Administration, Erasmus University, The Netherlands.

Noortje de Boer is Assistant Professor at Utrecht School of Governance, Utrecht University, The Netherlands.

ORCID iD

Erik Hans Klijn

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