DETERMINANTS AND CONSEQUENCES OF THE ANTI-MAFIA ENTREPRENEURIAL
BEHAVIOR: AN EMPIRICAL STUDY ON SOUTHERN ITALIAN SMALL-MEDIUM
ENTERPRISES1
Fabio La Rosa, Ph.D., KORE University of Enna
Sergio Paternostro, Ph.D., University of Palermo
Loredana Picciotto, Ph.D., University of Palermo
Abstract: In this study we question what determinants lead firms to adopt anti-mafia behaviors
and whether firms adopting anti-mafia behaviors “pay the piper” for their conduct through reduced
financial performance. A sub-sample of 111 Southern Italian Small and Medium Enterprises whose
entrepreneurs have publicly opposed the mafia extortion was initially selected. By adopting a
matched-pair design, anti-mafia firms were subsequently matched against a sub-sample of neutral
firms. Determinants of anti-mafia behavior were investigated by using a regression logistic model in
order to regress the anti-mafia choice on a set of financial, demographic, governance, and control
variables. Performance and financial structure was compared by adopting both different “between
analysis” of the full sample and a “within analysis” of the sub-sample of the anti-mafia firms in
order to investigate the statistical significance of the differences of means and medians. Results
show that the financial variables are the more significant determinants of the anti-mafia behavior,
while the analysis performed seem to confirm that anti-mafia behavior implies lower performance
in the short term.
1. INTRODUCTION
The organized crime is a relevant ethical, cultural, legal, sociologic and economic issue in many
developed and in developing countries. In Italy, in particular, the importance of this phenomenon
can be explained by some data (Confesercenti, 2012): the total turnover of “mafia” (the most
powerful form of organized crime) is estimated at about 137 billion Euros (24 billion by “mafia
taxes”, i.e. racket and usury); about 160.000 retail traders involved in the pizzo payment, 50.000 of
them only in Sicily (70% of the total); an estimated cost for the retail traders of about 37 billion
Euros. Despite these figures, in the last years there have been some positive signs of a cultural and
social reaction against the mafia. One of this is the successful experience of Addiopizzo, an antibribery association founded in Palermo in 2004 by seven young friends that today counts over 500
affiliated firms. As confirm of its success, Addiopizzo was recently awarded the “Social
1
Although this paper is the result of shared research, Sergio Paternostro authored the sections 1 and 2.2, Fabio La Rosa
authored the section 3 e 4, while Loredana Picciotto authored section 2.1.
1
Entrepreneur of the Year 2013”, by Schwab Foundation, “for its innovative approach and potential
global impact”. This award has the intent to encourage a new generation of entrepreneurs, to
enhance good examples of social entrepreneurship and to promote a business model able to
combine business and social purposes.
In literature, several approaches have been proposed to study the organized crime adopting a
sociological, cultural, political, relational or economic perspective (Arlacchi, 1986; Gambetta,
1993; Santino, 1995; Paoli, 2003; Scalia, 2010). Gambetta (1993), adopting the lens of economic
analysis, suggests the Mafia could better be understood as a profit maximizing corporation in the
marketplace for private protection. Despite this position has been criticized (Scalia, 2010), it
highlights the crucial role of the pizzo2 for the mafia activities. Due to its ethical, cultural and
symbolic relevance, in this study we identify as a firm’s “anti-mafia” behavior the choice of the
firm of not paying the pizzo and making this commitment public and visible.
Previous empirical researches on the topic have been focused on the macro-level of analysis
(i.e., the impact of organized crime on the social and economic system) using quantitative data, or
on the micro-level adopting mainly a qualitative approach (e.g., by using case studies) (Vaccaro,
2012). This paper tries to fill this gap by analyzing the determinants and the consequences of the
choice to refuse the mafia’s logic and culture using a quantitative method. In this sense, this study
poses two main research questions: 1) why do some firms decide not to pay mafia’s extortionists?
what are the determinants of anti-mafia entrepreneurial behavior? 2) what is the impact of this
decision on firm performance?
The two research questions are consistent with the idea that the firm can contribute not only to
the economic growth but also to the social development of the territory. In this sense, following a
consolidated literature, this study considers the firm as a multi-dimensional entity (Carroll 1979;
Coda, 1988; Catturi, 2003; Sorci, 2007). In the multi-dimensional model of the “integral
development of the firm”, Sorci (2007) identifies the four dimensions characterizing every firm: the
economic one, concerning the processes of production and its financial results; the socio-community
one, regarding the people working into the firm; the competitive one, referring to the satisfaction of
the customer’s needs; the socio-environmental one, inherent the social and environmental context.
In this sense, the anti-mafia behavior of the entrepreneur represents, beyond the specific individual
motivations, a social and ethical choice contributing to create a better society. The fight against
mafia’s extortionists is more effective if it is higher the number of entrepreneurs publicly refusing
the mafia’s culture. A strong incentive to pay is the mafia’s violence (Gambetta, 1993), but for the
2
The pizzo means the bribe required by mafia to the firms for ensuring protection.
2
organized crime is more difficult to impose its abuses if it has to face a structured and visible group
of people rather than individual entrepreneurs. The decision to reject the mafia’s threats is therefore
undoubtedly related to the socio-environmental dimension of the firm.
Considering the anti-mafia behavior crucial to the social development of the territory in which
the organized crime is particularly powerful, it is need to better understand its determinants. This
aspect is particularly relevant to identify the policies able to support the choice of the entrepreneur
to react to the violence of the mafia.
Looking also at the relationship between anti-mafia behavior and firm performance does not
necessarily mean to apply an instrumental approach to the topic for which the choice of not paying
and to publicly oppose mafia’s extortionists would be related to its positive economic impact. This
view would be consistent whit the classical Friedman’s idea that the only goal of the firm is to
create shareholder profit and a decision or behavior is positive only if it is consistent whit this
purpose (Friedman, 1970). On the contrary, looking at the relationship between anti-mafia behavior
and performance is aimed at understanding how a socially desirable action can be integrated with
the economic dimension of the firm. According to this view, the good firms are those able to
strongly incorporate the “common good” in their social dimension (Coda, 2012).
Our study tries to build a model of firm development different than the mere quantitative
approach to the firm growth. In this sense, the firm’s development should be oriented towards a
coordinated increase of the various dimensions and it should be assessed also by qualitative
parameters (Catturi, 2009). In contexts in which the presence of the mafia is particularly strong, this
firm development cannot be achieved without a concrete integration between anti-mafia behavior
and economic sustainability.
To the best of our knowledge this paper is the first about the determinants and consequences of
“anti-mafia” entrepreneurial behavior. One of the main reasons to explain this gap in literature is
probably the strong difficulty to measure an “hidden” phenomenon like the payment of pizzo by the
firms (Gambetta, 1993). The paper mainly contributes to the entrepreneurship and corporate
performance literature. First, as for the entrepreneurship literature, prior works about the
determinants of entrepreneurial behavior exist related to corruption towards public officers. These
works are mainly focused on the bribe-takers and not on the bribe-payers and they study macrolevel determinants (Tonoyan et al., 2010). This paper assumes the bribe-payers perspective, it
examines micro-level determinants and it does not study the corruption towards public officers but
the payment of the pizzo to organized crime. Second, the paper contributes to the performance
literature (Hansen and Wernelfelt, 1989; Dyer, 2006) by analyzing an internal determinant (the anti3
mafia behavior) not yet investigated. In addition, the paper contributes also to the corruption and
corporate social performance literature. Concerning the corruption literature, some previous
research (Kaufmann and Wei, 1998; Athanasouli, Goujard and Sklias, 2012) studies mainly the
“dark side” of the behavior, while this paper studies the positive one, i.e. the correlation between
anti-mafia behavior and performance. This paper contributes also to the literature about the
relationship between corporate social performance and financial performance (Margolis and Walsh,
2003; Wood, 2010) studying the economic impact of a specific socially desirable behaviour.
Finally, this paper can also offer some contributions to both the SMEs literature (especially
literature concerning SMEs located in less developed regional areas) and the family business
literature, because respectively of the size and the family nature of the firms investigated in our
sample.
The paper is structured as follows. Next section shows relevant theoretical and empirical
literature on both determinants and economic effects of illegal corporate behavior, so building a set
of different hypotheses. Section 3 presents sample selection and methodology adopted in this work.
Section 4 shows empirical results and some limits of the analyses performed. Finally, last section
offers a brief discussion and conclusions.
2.
BACKGROUND,
CONCEPTUAL
FRAMEWORK
AND
HYPOTHESES
DEVELOPMENT
2.1. Motivations and determinants of “anti-mafia” behavior of the firm
Many scholars have analyzed the impact of mafia on local, social and economic development, as
well as the costs it imposes on society (Arlacchi, 1986; Centorrino and Signorino, 1993; Anderson,
1995; Centorrino, La Spina and Signorino, 1999; Felli and Tria, 2000; Daniele, 2009; Krkoska and
Robeck, 2009; Daniele and Marani, 2011). However, scholars have not paid much attention to the
behavior of firms with respect to the mafia. Some scholars have examined the interaction between
entrepreneurs and mafia extortionists, using laboratory experiments (Bolle et al., 2011) or by using
the approach of game theory (Smith and Varese, 2001; Bueno de Mesquita and Hafer, 2008). Others
have focused on which characteristics make firms more vulnerable to an attack of crime (Krkoska
and Robeck, 2009) and what countermeasures should consequently be taken (Grutzner, 1970). The
reasons that drive firms to react to the pressures of mafia extortion are instead under-investigated.
The imposition of the pizzo is the main crime of mafia, its core business (Gambetta and Reuter,
1995; Skaperdas, 2001), which aims to ensure a regular flow of income and to guarantee a capillary
4
control of the territory (Allum and Sands, 2004; Daniele, 2009). The mafia families exercise a
power of intimidation and they extort periodic payments from legitimate business enterprises. It is
an old phenomenon started in rural areas and it progressively extended to urban areas. Although it
did not change its substance, the forms of extortion are more flexible, so following the evolution of
the economic system (Confesercenti, 2012). Indeed, in some cases, these payments can also be
made in the form of goods or services, or certain conditions are imposed on business management,
such as preferred suppliers and personnel to be hired (Anderson, 1995).
Since pizzo has a very high impact in terms of economic and social costs, firms may differently
react by publicly declare their resistance to the mafia and/or by denouncing the extortionists as it is
demonstrated by many judicial inquiries. In this sense, firms adopting an “anti-mafia” behavior are
those choicing to refuse to pay the pizzo and making public and visible this commitment. If there
are the conditions for a complaint, more virtuous firms may also to report extortionists or any
pressure. This is because an entrepreneur may decide not to pay the pizzo but not to denounce his
extortionists, even when they are identified, thus protecting them with his silence.
Why do some firms decide not to pay mafia’s extortionists? Why do some firms react to the
mafia with a visible commitment and others do not? These are some questions we attempt to answer
in this section. In this perspective, we distinguish two main situations: entrepreneurs who pay the
pizzo and others who do not pay (or who do not pay anymore). The analysis of the reasons that
justify these behaviors can shed light on the factors affecting the response to the mafia.
Entrepreneurs who pay the pizzo
With reference to the first group of entrepreneurs (see situation A of Figure 1), we can indicate
different motivations underlying the behavior of paying the pizzo. The fear of reprisals against
themselves, against the company and, above all, against his/her family is the main reason why an
entrepreneur pays the pizzo (Comitato Addiopizzo, 2008; Costantino and Milia, 2008). This is a
relevant reason because the mafia organization has an inherent ability to instill fear through the use
of violence (Smith and Varese, 2001; Allum and Sands, 2004). The acts of intimidation, committed
by criminals to induce entrepreneurs to pay extortion, may cause little damage to the firm (like the
practice of filling the shop’s bolts and locks with glue) or may be far more serious and turn into
attacks or arson (see Daniele, 2009; La Spina and Lo Forte, 2006; Vaccaro, 2012). The pizzo is,
therefore, the “tax” that entrepreneur must pay to live and work without any inconvenience. Some
scholars emphasize the need for protection as a reason relevant to pay the pizzo (Gambetta, 1993;
Kumar and Skaperdas, 2008; Krkoska and Robeck 2009). Actually, it is connected to the fear of
5
reprisals because few entrepreneurs consider the payment of pizzo a form of insurance against
common crime (Comitato Addiopizzo, 2008), since it is generally paid as a consequence of an
extortive pressure by a mafia family. Indeed, mafia artificially creates its own demand for
protection exercising an authoritarian and threatening power over the territory. The reference to
“protection” is plausibly related to the nature of pizzo. It wants to communicate the power of clan,
but also to reassure. In this way, the collector of the pizzo, asking every week or every month a sum
of money, becomes, in time, a sort of member of the family helpful in solving for any kind of
problem, relying on his relationships in business network, to entrust the resolution of disputes
(Confesercenti, 2012). The mistrusts in the institutions contributes to the decision of entrepreneurs
to pay the pizzo (Comitato Addiopizzo, 2008). They are motivated by mistrust in the rapidity and
effectiveness of institutional action against the extortion racket. In particular, inadequate control of
the police on the territory (or the perception of this), the long duration of judicial proceedings,
penalties still not considered enough rigid or certain, are important factors that limit the reaction of
entrepreneurs (Costantino and Milia, 2008). In addition, there is mistrust in the political class, in its
willingness and ability to deal with the problem of racket. On the other hand, the mistrust is also
related to the ability of the mafia to influence policy by developing strong connections (Blok, 1971;
De Mesquita and Hafer, 2008; Scalia, 2010), and, in general, by infiltrating the institutions and
weakening the integrity of public officials (Van Dijk, 2007). Territorial control and protection of the
economic interests take place, in fact, through the corruption and collusion with representatives of
institutions. The economic sustainability of the pizzo (sum of money, goods or services imposed,
higher cost of some goods, etc.), often makes the entrepreneurs cooperative with mafia families, so
they run the business “rationalizing” that cost. This because mafia has adopted, in the last decade,
an extortive strategy based on the criterion “pay less pay all” in order to make pizzo an acceptable
cost for the firms (Costantino and Milia, 2008). The strategy of “underground” pushes the victim to
omit the complaint of extortion, hoping to contain the cost of economic activity. The payment of
pizzo may also stem from adhesion to the culture or the logic of the mafia. Some scholars have
pointed out that the mafia is also a cultural phenomenon, specific to Southern Italian values, norms
and traditions (Paoli, 1998; 2003), that has developed its own organizational identity with specific
rules and a cultural code (Gambetta, 1993; Santino, 1995; Allum and Sands, 2004; Kumar and
Skaperdas, 2008; Gond, Palazzo and Basu, 2009). According to Gambetta (1993), the most
important rule is omertà, a code of secrecy, which prescribes an absolute silence that insiders must
observe with respect to outsiders. In our case, the entrepreneurs are encouraged to follow this rule
creating a sort of “forced marriage” with the extortionists (Daniele, 2009). In other cases this
6
“marriage” can bear some advantages for the entrepreneurs who may desire to pay the pizzo in order
to achieve economic benefits, such as an exclusive and relevant supply of products at the expense of
other entrepreneurs (buyers, sellers as well as competitors) and consumers (Comitato Addiopizzo,
2008); this occurs especially if they assess low the possibility to be punished (Baucus and Baucus,
1997). Among other things, it was found that firms with a bad business conduct are also more likely
to be targeted by crime (Krkoska and Roberck, 2009). Finally, there are entrepreneurs who pay the
pizzo because they underestimate the mafia, not being aware of its many negative impacts on the
economy and society. Vaccaro (2012) pointed out that a significant part of the Sicilian population
has a limited aptitude to morally analyze the mafia problem; more precisely, the results of his study
have confirmed that the mafia is not seen by a part of Sicilians as an immoral institution and that
they do not understand how their behavior can affect its activities. It can even be considered an
ethical institution opposed to the State, reliable and efficient in the activity of protection, whose
members are respectable individuals (Gambetta, 1993; Skaperdas, 2001; Vaccaro, 2012).
Entrepreneurs often do not realize that their behavior is inappropriate (Fassin, 2005) and this lack of
awareness reinforces, in turn, their resistance to change. Entrepreneurs who pay pizzo are victims of
the mafia but, at the same time, they may become complicit with their behavior in mafia activities.
This happens not only when the entrepreneur does not report the extortionists, but also when he/she
denies their existence. Therefore, entrepreneurs are in collusion with the mafia as they protect the
“protectors” by their silence.
Entrepreneurs who do not pay the pizzo
With reference to the second group of entrepreneurs – those who do not pay the pizzo anymore
or who have never paid it – their behavior can be again explained by different reasons and also their
reaction may be different (report or do not report the crime, join or do not join anti-racket
associations). Threats and/or pressures experienced by entrepreneurs may, in turn, influence their
motivations.
As for the reasons leading to the decision of not paying, it is important to emphasize that in the
last two decades the State has been exercising a stronger and more constant action against the
mafia, as showed by the arrests of the bosses of mafia gangs and the successes achieved by the
Judiciary and law enforcement. It is also important to consider the growth and development of the
anti-mafia movement involving society. In Sicily there is a dense network of associations operating
in different fields, which range from the opposition to the pizzo to the anti-mafia communication
and propaganda in schools and society (Scalia, 2010). The active presence on the territory of anti7
racket associations provide human, legal and bureaucratic support to entrepreneurs helping them to
react to extortion (see Vaccaro, 2012). In addition, a few years ago the professional associations of
Business, Commerce and Handicraft have taken the revolutionary decision to expel the firms who
continue to pay the pizzo. All this has contributed to shape, more than in the past, a socioinstitutional and cultural climate favorable to the reaction of the entrepreneurs.
There are entrepreneurs who have a strong reaction to the mafia, denouncing extortion or joining
anti-racket associations (or both). Within this category, we can then distinguish those who have
never paid the pizzo and those who paid it in the past. The former (situations B and C of Figure 1)
can be motivated by a variety of reasons, likely the most influential are: trust in institutions (or, at
least, to some of them); confidence in anti-racket associations and their activities; the refusal of
constraints management imposed by the mafia; a strong enough business situation (in terms of
economic and financial balance, and asset structure) able to withstand any adverse effects in the
short term; the civic consciousness, that is a sense of justice (Vaccaro, 2012) and, therefore, the
rejection of the mafia culture. Instrumental reasons, however, cannot be excluded (Friedman, 1970;
Porter and Kramer, 2006) such as interest in a positive image in the market extending from
belonging to important anti-racket associations (such as Addiopizzo). The latter are instead those
entrepreneurs who change their behavior and decided to stop paying the pizzo (situation D). Some
reasons may be common to the previous category (renewed confidence in the institutions and in the
activity of anti-racket associations, refusal of constraints management imposed by the mafia), others
are related to past experience. In this sense, the behavior can be explained by the economic
unsustainability of the pizzo, especially in a time of crisis and in highly competitive sectors; by the
constraints and impediments it poses to business investment (Skaperdas, 2001; Konrad and
Skaperdas, 1998; Kroska and Robbeck, 2009); by a cultural change involving part of the
entrepreneurial class (for example, the younger generations) and that makes this decision more
natural, although difficult; by the changed circumstances in which the company operates (such as
the more stringent policy of category professional associations).
Within the category under consideration, there may be entrepreneurs who have a less resolute
reaction to the mafia, by not denouncing the extortionists (or any extortion threat) nor joining antiracket associations (situations E, F and G). Therefore the reaction is more silent, the pizzo is not
paid but this choice is not made public. The reasons for this behavior may be different, some of
which have already been recalled. The fear of reprisals as well as distrust in institutions and antiracket associations may justify a weaker reaction. Their behavior could even be interpreted as
collusion when there are the conditions for a complaint. In this study, in fact, we consider as
8
virtuous behavior not to pay the pizzo and to report extortionists or any pressure. There may also be
entrepreneurs who prefer not to expose themselves because they do not find it economically
convenient (fearing, for example, the reaction of customers), they do not have sense of justice or
civic consciousness, or because they are individualists. In the latter case, especially when they have
never suffered threats or pressures, they do not understand the importance of contributing to the
contrast of the mafia by his own action, preferring to keep the distance from the circuit of antiracket associations. They are therefore hybrid situations, ambiguous, difficult to detect and
differentiate into reality, configuring a sort of grey area (as shown in Figure 1).
Gathering data on entrepreneurial behaviors related to extortion is extremely difficult (Gambetta,
1993), since privacy and confidential rules do not allow the access to relevant information. As a
consequence, here we examine only the entrepreneurs who have joined anti-racket associations
whose names are publicly available. However, it is not possible to further distinguish among them
without a specific questionnaire capable of explaining motivations, past events and contingencies.
For all other entrepreneurs, although with different connotations, their behavior can be judged
hybrid, ambiguous or even complicit.
9
Does the entrepreneur pay the pizzo?
Situation A. Entrepreneurs in collusion
with the Mafia motivated by:
Yes
No
-
Fear of reprisals
Need for protection
Mistrusts in the institutions
Economic sustainability of the pizzo
Adhesion to the culture or the logic of
the Mafia
- Lack of awareness
The entrepreneur has
denounced and/or joined
anti-racket associations?
Yes
No
Entrepreneur with a strong
reaction to the Mafia
Entrepreneur with a weak
reaction to the Mafia
(ANTI-MAFIA FIRMS)
(NEUTRAL FIRMS)
Situation D. Entrepreneurs
motivated by:
- Renewed confidence in
the institutions
- Renewed confidence in
the activity of anti-racket
associations
- Cultural change
- Economic unsustainability
of the pizzo
- Changed circumstances
Yes
Yes
The pizzo was paid in the past?
No
- Fear of exposing himself
further
- Mistrusts in the institutions
- Lack of civic consciousness
No
Previous threats
or pressures
Previous threats
or pressures
Any threats or
pressures
Any threats or
pressures
Situation B. Entrepreneurs motivated
by:
- Trust in institutions
- Confidence in anti-racket
associations
- Rejection of the Mafia culture
- Refusal of constraints management
- Solid business situation
Situation C. Entrepreneurs
motivated by:
- Civic consciousness
- Interest in a positive
image in the market
Situation G. Entrepreneurs
motivated by:
Situation F. Entrepreneurs
motivated by:
- Fear of reprisals
- Mistrusts in the institutions
- Lack of civic consciousness
Situation E. Entrepreneurs
motivated by:
- Limited economic convenience
to be exposed
- Lack of civic consciousness
- Underestimation of the
phenomenon
- Entrepreneurial individualism
Figure 1. Taxonomy of anti-mafia or neutral entrepreneurial behaviors and underlying motivations
2.1.1. Determinants of anti-mafia behavior
The reasons discussed above are useful to understand what are the possible determinants of antimafia behavior. Indeed, it has been stressed that motivation is crucial in predicting and explaining
entrepreneurial behavior (Casrud and Brannback, 2011). In summary, we can distinguish three
possible categories of factors likely to affect the behavior of those entrepreneurs who react
resolutely to the extortion racket: the personal characteristics of the entrepreneur or of the firm, the
10
firm’s operating conditions and the environmental conditions. In this stage of our research we focus
the attention mainly on the second category, the operating conditions, trying to examine their
influence on the adoption of the anti-mafia behavior. This choice depends on the methodological
instruments used in this study that are based on data gathered by database and analysis of the web
sites of the companies. In the next stages of the research, we will use other instruments (such as
questionnaire, interviews, etc.) able to measure variables related to the personal characteristics of
the entrepreneur, including values, personality traits and entrepreneurial orientation (Miller, 1983)
likely to have a significant impact on entrepreneurial behavior (Henderson 1982; Lumpkin and
Dess, 1996; Okhomina, 2010).
The analysis carried out shows also the importance of the environmental conditions in
influencing an entrepreneurial reaction to the extortion racket. The characteristics of the sector in
which the firm operates (such as its life-cycle stage and competitiveness) and the economic trend,
which can make the payment of the pizzo unsustainable or preclude the possibility of carrying out
the activity elsewhere (Comitato Addiopizzo, 2008), as well as the institutional context and the
socio-cultural climate (Tonoyan et al., 2010; Weiter and Smallbone, 2011) are all factors that
significantly affect entrepreneurial behavior. Some of these aspects will be included as control
variables in this study (e.g., firm’s sector), others are undoubtedly worthy of further investigation in
future research (we refer to some variables such as the local culture, the strength of organized crime
and the level of institutional corruption, the quality of political institutions, the efficiency and the
effectiveness of judicial system, the existence of anti-racket organizations, the quality of the
policies pursued by the professional associations, and so on).
As mentioned above, in this paper we focus our analysis on the potential influence of the
operating conditions on the anti-mafia behavior and also on some characteristic of entrepreneur.
Since the decision not to pay the pizzo appears as a particularly risky behavior, it seems
appropriate to consider a theoretical approach pivoted on the risk preferences of the decisionmakers. Specifically, we refer to the behavioral agency model that incorporates the agency theory
into a model of risk based on the behavioral theory of the firm (Wiseman and Gomez-Mejia, 1998;
Deephouse and Wiseman, 2000). According to this theoretical model, the risk preferences of
decision makers and, therefore, their risk-taking behavior change with the framing of problems.
The problems are framed by comparing the expected results of available options with a point of
reference, such as current wealth or aspiration for wealth. There is a positive framing of the
problems when the available options generate acceptable expected values and, by contrast, there is a
negative framing of the problems when the available options generate unacceptable expected
11
values. Thus, problems can be framed as a choice among potential gains or a choice among
potential losses (Wiseman and Gomez-Mejia, 1998). Framing problems as gains or losses may
influence the risk preferences of decision-makers. The behavioral model predicts, in particular, that
decision-makers exhibit preference of risk aversion when selecting among perspectives framed
positively and exhibit preferences of risk propensity when selecting among identical perspectives
but negatively framed. This can be explained as follows: under the conditions of gain (positively
framed problems), decision makers perceive more risk for the wealth since they have something to
lose, namely the expected gains of wealth. On the contrary, when they face a loss condition
(problems framed negatively) the decision makers perceive a lower risk for wealth, since wealth is
actually already lost. So, in the first case they are more conservative, while in the second case more
inclined to risk. Underlying this difference is the tendency of individuals to avoid the losses, the socalled “loss aversion” (Kahneman and Tversky, 1979), such that even higher risks would be
accepted. In other words, decision-makers are willing to take riskier actions to prevent or reduce
losses in order to preserve their utility.
Studies on the behavioral theory of firm (Cyert and March, 1992) suggest that the results of
previous strategic choices (current and past performance) may influence risk taking through its
effects on the reference point used in framing problems (Bromiley, 1991). In this model managers
decide on their risk preferences after comparing their firm’s performance to certain reference points,
such as their firm’s past performance (Deephouse and Wiseman, 2000). In the behavioral view the
firm is seen as a system of rules and routines that change over time in response to experience, and
the experience is interpreted in terms of the relation between performance and aspirations (Cyert
and March, 1963). Aspirations act as adaptive firm goals that are modeled as a function of past
performance. The difference between performance aspirations and expected performance influences
the entrepreneurial behavior (Lant, 1992). In particular, when expectations for future performance
exceed aspirations there is little incentive to search for new routines; instead, when expected
performance is below aspirations firm searches for new routines (Cyert and March, 1963). In the
latter case it takes on a new course of action, exploring alternatives that are different from
traditional solutions (Nelson and Winter, 1982) likely to increase the uncertainty of the firm’s
income stream (Deephouse and Wiseman, 2000). Hence, according this theory the firm’s risk
propensity depends on the gap between aspired performance and expected performance.
Based on these arguments, we assume that past performance affects the entrepreneurial antimafia behavior because it is used by decision-makers as a reference point to frame the problems in
terms of potential gains or losses. However, it is not possible to predict the expected sign of the
12
relationship between past performance and anti-mafia behavior, since the risk preferences of the
decision-makers – and, consequently, the type of behavior adopted – stem from their personal
aspirations. These are modeled as a function of past performance, which can be judged more or less
satisfactory by the entrepreneur.
The anti-mafia behavior could more likely occur when the decision-makers anticipate that
performance aspirations will not be achieved, conceivably also due to the negative effects of
extortion. In this case they frame the situation as a potential loss (“problems framed negatively”)
and engage in search behavior (and risk taking) in an attempt to avoid failure (March and Shapira,
1992). We affirm that because the decision not to pay the pizzo (or do not pay it anymore) can be
considered as a “risky” behavior likely to increase uncertainty and variability of future income. On
the one hand, it can cause economic damages, generate supply difficulties (created ad hoc by mafia
organizations), or frighten customers and to contract sales. On the other hand, this choice has the
effect of reducing the overall costs and can generate, in contrast, a positive return of the image with
beneficial effects on revenues. Therefore, this decision represents a new course of action (compared
to the past or compared to the traditional solution and most widely adopted by other firms), which
may increase the uncertainty of future income for its possible consequences.
However, the decision not to pay the pizzo could also occur in the case where the past
performance is positively assessed by the entrepreneur, and such that the expected performance is
higher to the aspirations (“problem framed positively”). On this occasion, the entrepreneur may also
exhibit a preference for riskier actions because he is aware that to pay the pizzo worsens the
economic and financial situation in the future. This can be explained by the concept of “loss
aversion” previously mentioned, namely the tendency for the individual to assume a more risky
decision in order to avoid losses anticipated and preserve its utility (in our case, a performance
deemed satisfactory). In this sense, Mishina et al. (2010) provide evidence that performance that
exceeds aspirations and external expectations increases the likelihood of corporate illegality.
In addition to the arguments of the behavioral agency model, another explanation of the
correlation between past performance and anti-mafia behavior stems from the motivations
mentioned above explaining the entrepreneurial choices to refuse to pay the pizzo. Specifically, the
financial unsustainability of the pizzo can lead the entrepreneur who has had a poor performance to
adopt an anti-mafia behavior.
These different arguments do not allow us to predict the sign of the relationship between past
performance and anti-mafia behavior but lead us to formulate the following hypothesis:
H1: The past performance influences the adoption of an anti-mafia behavior.
13
Another important dimension of business activity that may cause the adoption of an anti-mafia
behavior by firms is the leverage. The consideration of this possible determinant is quite intuitive,
since the financial structure affects investment decisions and, in this case, the decision to use the
resources for the “protection service”.
In the literature, the relationship between leverage and other significant variables have been
investigated. Some studies have focused on the relationship between debt-equity ratio and risk
(Jensen and Meckling, 1976; Wiseman and Bromiley, 1996), others on the relationship between
leverage and return (Deephouse and Wiseman, 2000), and still others on the relationship among
leverage, efficiency and firm performance (Margaritis and Psillaki, 2010). At our best knowledge,
there are not studies that explicitly take into account the impact of leverage on the kind of
entrepreneurial behavior considered here. If anything, it was examined the effect of crime on
investment decisions (Krkoska and Robeck, 2009) or the inefficiency in the use of business
resources caused by illegal activities (Argandona, 2001). Nonetheless we can predict the influence
of leverage on the anti-mafia entrepreneurial choice reflecting on some of the effects generated by
the leverage highlighted by scholars, as well as on the different risk tolerance of the decisionmakers on the basis of agency theory often used in such studies.
The main benefits arising from the use of debt capital to finance risky projects are linked to the
existence of a fixed cost while profit potential associated with the increase in risk is not (Jensen and
Meckling, 1976). The leverage, however, puts the firm’s future at greater risk. Contrasting effects
have been identified by the use of leverage. On the one hand, it can increase the risk of bankruptcy,
negatively affected cash flows through higher interest expenses (Ross, 1977). On the other hand, it
can have a positive effect on corporate performance, pushing managers to reduce waste in the
investment of resources through the threat of liquidation (Grossman and Hart, 1982) or through
pressure to generate cash flows to service debt (Jensen, 1986) and to reduce organizational
inefficiencies (Margaritis and Psillaki, 2010). In this regard, it should be noted that according to the
agency theory, based on the idea that the interests of the firm’s managers and its shareholders are
not perfectly aligned (Jensen and Meckling, 1976), managers cannot diversify their firm-specific
human capital investment (the employment risk) showing a lower risk propensity. Fearing the
employment risk, they prefer therefore less profitable investments. In this sense, for managers
concerned about a possible bankruptcy, leverage should encourage greater efforts aimed at higher
returns.
14
A high level of debt could make the payment of the pizzo unsustainable for the firm. Moreover,
that burden adversely affects the cash flows accenting consequently the risk of bankruptcy that can
result from a high rate of debt; such effect can also occur in cases where protection money is paid in
other ways (for example, supplies more expensive) likely to generate inefficiencies and a poorer
performance. In particular, we expect that it will manifest a greater resistance to pressures from
mafia if the firm already supports high interest expenses. Even the difficulties of access to credit
consequent to a high leverage may make to pay the pizzo difficult, especially in situations of low
liquidity. In other words, we believe that the increased risk of default associated with a high
leverage could lead to greater resistance to the payment of the pizzo (and therefore an anti-mafia
behavior), even considering what previously said about the tendency of individuals to take risky
actions in case of anticipated losses. Our hypothesis is therefore as follows:
H2: The leverage has a positive correlation with the adoption of an anti-mafia behavior.
Academic research suggests that ownership has a significant influence on business decisions
(Calabrò et al., 2013; George et al., 2005; Zahra, 1996). The corporate ownership is mainly
concentrated in European countries (Faccio and Lang, 2002), especially in the regions of Southern
Italy where there is a prevalence of SMEs. In this case there is a small number of large shareholders
(La Porta et al., 1999) who hold more control thanks to the greater shares held, compared to the
case of a not concentrated ownership. In such a situation does not arise, therefore, a problem of
separation of ownership and control (Berle and Means, 1932) since shareholders can monitor
managers more effectively to the benefit of minority shareholders (Shleifer and Vishny, 1986).
Rather, there is a risk that large shareholders can pursue private goals that differ from the profit
maximization, reduce valuable managerial incentives or also the external reporting (Burkart et al.,
1997; Maury and Pajuste, 2005; García-Meca and Sánchez-Ballesta, 2011).
According to these considerations, we can affirm that the anti-mafia behavior could be
influenced by the concentration of ownership. That is why such a hazardous and controversial
decision could be taken right from a small number of shareholders with more control of the firm
and that it has a stronger interest in its survival and prosperity. After all, it was found that the
ownership structure and characteristics of the board may have a role in the propensity to commit
frauds (Chen et al., 2006).
Agency theory suggests that managers tend to act in their own interests if they are able to do so
(Donnelly and Kennelly, 2005). Consequently, they could suffer the pressures of the mafia and
decide to pay protection money to avoid dangers and damages associated with a reaction. After all,
15
their interest is to protect their employment (employment risk). In the case of a concentrated
ownership, a small number of shareholders can more effectively monitor the managers and if its
orientation is to behave in an anti-mafia manner it also has the power to enforce its decision. Our
hypothesis is therefore as follows:
H3: The anti-mafia behavior is more likely to occur when the ownership is concentrated.
It is very common, especially in Europe, that families hold a significant equity stake, so firms are
family-controlled (Faccio and Lang, 2002; Anderson et al., 2003; Siregar and Utama, 2008; Calabrò
et al., 2013). Such firms can pursue different objectives and management styles from non-family
firms (Corbetta and Montemerlo, 1999), sometimes achieving a better performance. It was, in fact,
pointed out that family control lowers agency costs (Andres, 2008; Maury, 2006; Siregar and
Utama, 2008), reduces the cost of debt financing (Anderson et al., 2003) and can significantly
increase corporate efficiency (Maury, 2006). That is why families can exercise additional control
and place one of their members in the CEO position (Anderson et al., 2003), thus influencing the
business decisions. Furthermore, the family’s presence in ownership and management of small or
medium firms results in lower goal divergence between owners and managers. It should be
emphasized that the family involvement is the typical characteristic of family-owned firms. It can
assume different forms, for example, family members may serve as members of the firm’s top
management team or the board of directors (Calabrò et al., 2013). Family members have a deep
relationship with the firm and may even feel responsible towards the other shareholders (Andres,
2008), being their family reputation also involved (Anderson et al., 2003).
Family traits, such as trust, altruism, and paternalism can encourage an atmosphere of love and
commitment towards the business (Randøy and Goel, 2003) and push the owners to adopt an antimafia behavior, since the extortion pollutes the proper conduct of the business. This behavior can be
caused by an intolerance of the owners against the pizzo for a sense of justice and fairness. But an
anti-mafia behavior can also arise when the payment becomes unsustainable and increases the risk
of a failure. That is why one of the key interests of the owning family is to ensure the longevity of
the firm, by preserving the resources (Tagiuri and Davis, 1992; Anderson, 2003; Randøy and Goel,
2003), so as to pass it on to their descendants. In other words, the love for the firm can lead to a
strong reaction to pressures from mafia, deciding to undertake a behavior so risky to preserve its
survival.
On the other hand, it should also be pointed out that the families (having a representation in key
management positions and/or the board) are more prone to acquire private benefits if they are not
16
monitored by another strong shareholder (Maury and Pajuste, 2005). The tendency to pursue their
own interests may consequently induce the owners to passively submit to the payment of pizzo for
the “quiet living” so as not to expose to risk the firm and then pass it on to their descendants. In this
case it occurs in the corporate context the idea of “amoral familism” of Banfield’s (1958), such that
the family behaviors are based on self interest at the expense of the broader society. The concept of
amoral familism would suggest that owning-families would not likely behave in an anti-mafia
manner, but would likely emphasize self-interest.
As a result, we propose two alternatives hypothesis:
H4a: The presence of the family in the ownership structure could foster the anti-mafia behavior.
H4b: The presence of the family in the ownership structure could be inversely related to the
adoption of the anti-mafia behavior.
Among the personal/firm characteristics able to influence the firm behavior, the personal
characteristics of the key decision-maker are relevant. In particular, the literature studied the impact
of CEO characteristics on investment decisions and strategies (Bertrand and Schoar, 2003;
Malmendier, Tate and Yan, 2011). The results of this kind of researches can be extended also to the
firms, such as SMEs, in which the decision-maker is the major owner of the firm. Two
characteristics of the key decision maker has been much investigated: age and gender.
As for the age, there are two different and contradictory literatures about the impact of CEO age
on behaviors and decisions. The former is the market learning model according to which the
younger CEOs, since they do not have a strong reputation as top executive and they are more
scrutinized by the market, are more risk-averse because a bad decision can strongly reduce their
future career opportunities (Zwiebel, 1995; Holmstrom, 1999). In this line of thought, seeing the
anti-mafia behavior as a risky behavior, the older CEO should adopt it more likely than the younger
ones. The latter, on the other hand, is the managerial signaling model according to which the
younger CEO acts in more aggressive and risky manner due to the need to signals to the market
their superior ability (Prendergast and Stole, 1996). The older CEO have less attitude to change
since this could be a signal of a previous incorrect decision. Following this second view, the
younger CEO should be more likely adopt an anti-mafia behavior. There is also a social and cultural
motivations that can lead to prefer the second view. In particular in the Sicilian context, the Falcone
and Borsellino assassinations in the 1992 caused a strong reaction against the Mafia that found an
evidence in a strong activity of education within the schools (i.e., the “Nave della legalità” (boat of
legality) that each anniversary of the Falcone and Borsellino death brings students from every part
17
of Italy to Palermo to remember the sacrifice of the two judges). The generations grown up after the
1992 developed a stronger sensitivity towards this issue as it is evident, for example, in the story of
Addiopizzo realized by some young people (Vaccaro, 2012).
In light of this, our hypothesis is:
H5: The age of the CEO or major owner has a negative correlation with the adoption of an
anti-mafia behavior.
Considering the gender of the key decision-maker, in literature there are many studies about the
influence of gender diversity on corporate decisions and outcomes (Adams and Ferreira, 2009;
Weber and Zulehner, 2010; Ahern and Dittmar, 2012). These studies, however, are mainly focused
on board diversity rather than the decision-makers (CEO or major owner).
Although some researches highlight the lower risk-propensity of female compared to the male
(Byrnes et al., 1999; Eckel and Grossman, 2002), other several thoughts can lead to predict a
positive correlation between the presence of a female CEO or major owner and the probability to
adopt an anti-mafia behavior. Some studies founded that female provide within organization
different perspectives than the male (Robinson and Dechant, 1997; Hillman et al., 2002; Daily and
Dalton, 2003); the presence of females in a board foster the realization of social initiatives such as
charitable giving (Williams, 2003) or environmental commitment (Post et al., 2011); the leadership
style of female directors promotes more communication and dialogue at the management level
allowing a better assessment of the different stakeholder needs and the social problems (Helgesen,
1990; Rosener, 1995; Rudman and Glick, 2001; Eagly et al., 2003). In addition, there is a wide nonacademic literature on the relevant role of women in the fight against the organized crime (Dalla
Chiesa, 2006; Abbate, 2013).
Our hypothesis is:
H6: The presence of a female CEO or major owner has a positive correlation with the
adoption of an anti-mafia behavior.
Among the firm characteristics, another variable to be considered in the study of the
determinants of anti-mafia behavior is the board of directors, one of the most important internal
mechanisms of corporate governance. The board of directors is charged with advising and
monitoring management and has the responsibility to hire, fire and compensate the top management
(Jensen, 1993). The directors also fulfill resource, service and strategy roles, and they are ultimately
responsible for effective organizational functioning (Johnson et al., 1996; Daily et al., 2003; Dunn
18
and Sainty, 2009). A factor we focus our attention on and which influences the board’s ability to
function effectively is its size (Coles et al., 2008). Board size represents the number of directors on
the board.
Scholars employed different theoretical perspectives to interpret the role of the board and to
understand the features that may increase its effectiveness. Daily et al. (2003) point out, in fact, the
importance of a multi-theoretical approach in the studies of corporate governance for recognizing
many mechanisms that might reasonably enhance organizational functioning. In this paper we
assume two theoretical perspectives, the agency theory and resource-dependence theory, since we
believe that they provide the theoretical foundations on how the board size can influence the antimafia behavior.
Agency theory is the dominant perspective in the literature because it is the most appropriate for
conceptualizing the control/monitoring role of directors. The board has a fiduciary obligation to
shareholders and it represents a mechanism to protect their interests from managerial self-interest
(Gillan, 2006). The studies suggest that as board size increases some problems occur limiting its
effectiveness. Specifically, the emphasis is on two main aspects: the increased problems of
communication and coordination, and decreased ability of the board to control management (Lipton
and Lorsch, 1992; Jensen, 1993). These authors argue, in fact, that larger boards could be less
effective than smaller boards because of coordination problems and director free-riding. Similarly,
other studies show a negative relationship between board size and corporate performance
(Yermack, 1996; Eisenberg et al., 1998; Bennedsen et al., 2008). When a board becomes larger it is
more difficult for the firm to arrange board meetings and for the board to reach a consensus on a
choice. The decisions tend to be less extreme because they are the result of negotiation and
compromise among different individual positions (Cheng, 2008). As a result, larger boards are less
efficient and slower in decision-making. Instead, smaller boards are more cohesive, more
productive, and can monitor the firm more effectively (Coles et al., 2008). Since the decisions taken
by larger boards tend to be less extreme is more likely that the risky projects will be rejected having
to be accepted by several group members. Consequently, we can expect that in the presence of a
larger board it will be less likely the adoption of an anti-mafia behavior. The decision not to pay the
pizzo is, in fact, a delicate and complex decision, involving a number of business risks and uncertain
consequences. Reaching a consensus on it requires an agreement among individuals with different
opinions and this is more difficult in larger boards.
On the other hand, we could formulate the hypothesis contrary considering the effect of board
size from the theoretical perspective of resource dependence theory (Pfeffer and Salancik, 1978),
19
more appropriate with regard to directors’ resource, service and strategy roles (Daily et al., 2003).
This theory offers a theoretical foundation for the board’s function of providing critical resources to
the firm. Proponents of this theory consider board members as boundary elements of the
organization and its environment, useful for understanding and respond appropriately (Dalton et al.,
1999). In this sense, the outside directors provide access to resources needed by the firm, enhancing
organizational functioning and ensuring higher levels of firm performance. Furthermore, a larger
and more independent board appears to reduce the risk of bankruptcy and decrease the likelihood
that a firm will fail (Darrat, 2010; Platt and Platt, 2012). According to scholars, board size may be a
measure of the organization’s ability to form environmental links to secure critical resources. A
board offers the collective experience and the expertise of board members: insiders with knowledge
firm-specific, business experts with knowledge of corporate strategy, support specialists with
knowledge of legal, banking and insurance affairs, community influentials with knowledge and
relationships with external stakeholders (Hillman et al., 2000). Bear, Rahman and Post (2010) also
argue that the diversity of board resources, which increases with its size, affects the critical function
of monitoring management. Board resources (skills, knowledge, expertise and professional
backgrounds) are crucial for an effective monitoring. Furthermore, the board offers advices,
counsels and links to other organizations helping the firm to manage business challenges. Also
Coles et al. (2008) found that complex firms, which have greater advising requirements than simple
firms, have larger boards with more outside directors. The greater is the diversity of board resources
better is the interaction of the firm with the environment because it increases the potential for
understanding and problem solving.
Considering the role of the board in this perspective we can therefore affirm that the adoption of
an anti-mafia behavior could be positively correlated to the board size. After all, our study refers to
small and medium-sized firms for which certain theoretical principles of agency theory may not be
fully applicable, given that in such firms a little separation of ownership and control presumably
exists (Eisenberg et al., 1998). A larger board can offer valuable advice on the decision not to pay
the pizzo, highlighting the negative effects that it causes or could cause to the firm. As pointed out,
it potentially brings more experience and knowledge and offer better advice to CEO (Dalton et al.,
1999). In addition, a larger border offers a variety of resources capable to improve the functioning
of an organization, important aspect in case it is decided to stop paying the pizzo and you need to
restore the compromised conditions of efficiency, solvency and profitability. And yet, it was
stressed that the board resource diversity may also enhance network ties as members of a larger
board may offer connections with suppliers, customers, professional associations, academic experts,
20
legal and banking networks, government agencies, community groups and non-profit organizations
(Hillman et al., 2000; Bear et al., 2010). Such links may foster collaboration and cooperation with
key stakeholders and be useful when the firm has to decide whether reacting to extortion, as well as
when it needs support and assistance from other external actors to deal with the risks, damages and
problems resulting from the decision.
In summary, the theoretical perspectives presented offer us two possible alternative explanations
of the relationship between board size and anti-mafia behavior that we hypothesize as follows:
H7a: The board size is negatively related to the anti-mafia behavior.
H7b: The board size is positively related to the anti-mafia behavior.
2.2 Anti-mafia behavior and firm performance
Several studies have explored the determinants of firm performance. The literature distinguishes
two main groups of performance determinants (Hansen and Wernelfelt, 1989): the economic
(external) and organizational (internal) factors.
The first group can be splitted in two sub-categories of determinants (Short et al., 2007): the
influence of the economic sector (industry variables) and the influence of the strategic approach.
The economists have long argued that some structural industry elements can affect the performance
(Bain, 1956; Schmalensee, 1985) but also in the strategy field many researchers considered the
crucial role of the industry to explain the heterogeneity of the performance between the firms
(Rumelt, 1991; McGahan and Porter, 1997; McNamara, Aime and Valeer, 2005). Also the strategic
approach has been investigated and considered as a possible driver of performance, in particular the
effects of the belonging to a strategic group have been studied (Fiegenbaum and Thomas, 1990;
Short et al., 2003).
The internal determinants of firm performance mainly include the governance structure and
firm/entrepreneur/management characteristics and behaviors (Dyer, 2006).
The possibility to identify governance variables and to measure them produced a large and
heterogeneous literature on the topic. Gompers, Ishii and Metrick (2003), using a whole governance
measure, found a positive correlation between strong shareholders rights and performance, but
Core, Guay and Rusticus (2006), using the same measure applied to a different period, did not
confirm this result. In this field, the main variables investigated are related to the board: size
(Yermak, 1996; Eisemberg et al. 1998; Bennedsen et al., 2008), board independence (Hermalin and
Weisbach, 2003), duality in the chair/ceo role (Brickley, Coley and Jarrel, 1997). Similarly, as for
the firm/entrepreneur/management characteristics and behavior the variables studied are wide: firm
21
size (Leibestein, 1976; Sheperd, 1986; Evans, 1987); firm age (Evans, 1987; Correa et al., 2003);
level of disclosure (Healy and Palepu, 2001); characteristics of the network in which the firm
operates (Li, Veliyat and Tan, 2013); entrepreneur and management values (Ling, Zhao and Baron,
2007; Berson et al., 2008); gender of the entrepreneur (Klapper and Parker, 2011); entrepreneurial
orientation (Wiklund and Sheperd, 2005; Stam and Elfring, 2008).
Our paper is focused on “anti-mafia” behavior that is a particular and complex kind of firm
behavior. This topic has not been previously investigated in literature. There are many researches on
the economic effects of organized crime but they are mainly focused on the macro- or system-level,
analyzing the impact of organized crime on some macro-economic variables. Van Dijk (2007)
analyzes the effect of organized crime (measuring by a composite organized crime index developed
by many international databases), rule of law and corruption on GDP: the paper finds the negative
impact of a political strategy aimed to tolerate the organized crime activities. Kumar and Skaperdas
(2009) in their theoretical work summarize the economic effects of organized crime activities:
productive and investment distortions, contractual problem that develop outside the realm of
modern governance; incentives for the development of human skills that are biased towards
appropriation instead of towards production. De Mello and Zimmerman (2008) show the link
between crime and decisions regarding savings in Brazil. From the Italian case, Centorrino and
Signorino (1997) analyze the effect of mafia on the fiscal system assuming a reduction in individual
income and a reduction in fiscal revenue due to the so-called “mafia tax”. They calculate a loss of
revenue due to income not produced in the economy of about 0.7% of GDP. Peri (2004) shows the
influence of the crime (but measuring only as homicide rate) on the regional development of 95
Italian provinces. Also Detotto and Pulina (2009) demonstrate the negative impact of the crime on
per capita output and employment growth. Daniele and Marani (2011) find a negative correlation
between some crime related to the traditional mafia activities and the foreign direct investments in
the Italian provinces, demonstrating the deterrent effect of the mafia. Other studies (Gaviria, 2002)
analyze the impact of corruption and crime on firm performance in a specific environment. He uses
survey data to analyze the impact of crime on firms in Latina America. The study finds the crime
has a negative effect on firm performance, in particular on sales growth.
At the firm level there are not empirical studies on the economic consequences of an anti-mafia
behavior or of the choice to pay or not to pay the pizzo. There are, on the other hand, some studies
that mainly analyze the “dark side” of the firm behavior: the correlation between negative behavior
and firm performance.
22
Davidson and Worrell (1988), study the stock market reaction to Wall Street Journal's
announcements of corporate crime. The findings suggest the market penalizes the stock prices of
firms that are caught in socially irresponsible activities. Baucus and Baucus (1997) study the link
between illegal corporate behavior and long-term financial consequences, extending prior
researches (Baucus and Near, 1991). Illegal corporate behavior in the Baucus and Baucus’s research
is related to unlawful activities of members or agents of a firm engaged in primarily for the firm’s
benefit, so a more general phenomenon compared to our topic. The illegal behavior is measured by
the convicted for illegal acts. The findings support the hypothesis about a negative correlation
between illegal behavior and long-term financial performance. Mishina, Alvarez and Young (2011),
study the mixed effects of illegal behavior and socially responsible behavior on performance. The
definition of illegal behavior is similar to Baucus and Baucus (1997) and it is measured identifying
instances of corporate illegality by searching newspaper and business publication databases and
cross-checking against the Corporate Crime Reporter. They find that the illegal and socially
responsible behaviors have a different impact to firm performance depending on the kind of
stakeholder (primary o secondary) affected.
A similar phenomenon than extortion against firms, is corruption (Vaccaro, 2012). Corruption
can be defined as the abuse of public power for private gain (Cuervo and Cazzura, 2006) and it
concerns two parties, a “demander” and a “supplier” that exchange services for money (Kwok and
Tadesse, 2006). The differences with the mafia extortion are several: the “demander” is the mafia
and not a public officer; the “supplier” does not offer spontaneously to pay for the service; the
service is a pretext for the extortion; the money paid is not proportionate to the service. In spite of
these differences, the similarity between mafia-extortion and corruption can make useful to briefly
review the literature about relationships between corruption and firm performance. Also for this
kind of illegal behavior the literature is mainly focused on the macro-level analysis. These studies
demonstrated the link between corruption and low economic growth (Ades and Di Tella, 1999; La
Porta et al., 1999). Among the few works aimed to analyze the link between corruption and firm
performance, Kaufmann and Wei (1998) find a positive correlation: this result can be explained
because pay a bribe can give the possibility to overcame huge bureaucratic procedures obtaining a
benefit, in particular in the short-term. The paper of Athanasouli, Goujard and Sklias (2012),
focused on administrative corruption in Greek and using aggregate data, shows a negative
correlation between corruption and sales: the authors explanation is that a corrupt environment
leads to an increase of the cost higher than the possible benefit in the short term. Another result of
this research is that the performance of small and medium enterprises is less correlated with
23
corruption than large firms. In line with this explanation, De Jong, Tu and Van Ees (2010),
analyzing a sample of firms in Vietnam, find an inverted u-shape non-monotonic relationship
between bribery and performance: paying a bribe gives a benefit in the short term but a
disadvantages in the long-term.
In the attempt to analyze the positive side of the firm behavior, a way to see the “anti-mafia”
behavior can be as part of the social performance of the firm. Social performance is a construct
much investigated but without an universally accepted definition. In a general view, it “concerns the
harm and benefits that result from a business organization’s interactions with its larger environment,
including the social, cultural, legal, political, economic and natural dimensions” (Wood, 2010: 51).
In a social context in which the mafia is one of the most serious social problems to be addressed, we
can consider the anti-mafia behavior of the firm as a significant part of the firm contribution to the
social development. In this sense, the previous researches about social performance/financial
performance relationships found heterogeneous results (positive, negative and not significant
correlation), but the majority of the results support a positive correlation between social and
financial performance (Margolis and Walsh, 2003).
The lack of previous empirical researches on our topic makes difficult to hypothesize the sign of
the possible correlation between “anti-mafia” behavior and firm performance. Indeed, using some
aspects of the literature about similar issues and adapting it to the choice to not pay the pizzo and
publicly refuse the mafia’s logic, we can try to explain the possible link, in spite of the sign of the
correlation, between “anti-mafia” behavior and performance.
We can identify three categories of explanation about the influence of anti-mafia behavior on
performance due to economic, relational and social/reputational factors. Some factors are mainly
related to the refuse to pay the pizzo, while others are linked to the choice to make visible this
decision.
From the economic point of view, the payment of the pizzo entails some directs effects. The
main economic cost of paying is linked to a distortion in the allocation of resources. The firms that
pay the pizzo cannot invest this amount of money in other more productive and innovative
operations (Konrad and Skaperdas, 1998) risking to lose opportunity to an economic growth. The
payment of the pizzo can also lead towards a sort of lack of motivation of the entrepreneur that
limits new entrepreneurial initiatives (Sciarrone, 2009). The payment can often be accompanied by
the request to hire people linked to the organized crime and without the skills required for the
specific business (or people that only “officially” work in the firm but that does not carry out any
job) or to buy from suppliers at prices and/or quality lower than the market causing a not rational
24
use of resources and a loss of efficiency (Sciarrone, 2009; Confesercenti, 2012). Another economic
effect of the payment could be a loss of competitiveness due to the possible increase in the product
price caused by the shift to consumers of the cost of the pizzo. In other words, the entrepreneur can
decide a mark-up of price to recover the amount paid to the extortionists (Confesercenti, 2012).
Finally, the payment can lead to a vicious circle in which pizzo breed pizzo. If a firm pays once, it is
forced to pay every time and the extortionist can feel himself legitimate to require progressively
higher amount of money. In this sense, the choice to refuse to pay the pizzo can lead the firms
towards an improvement of its performance and a growth of the sales. Consequently, the
performance of a firm that refuse to pay the pizzo should be better than a firm paying. As for the
financial structure, the request of pizzo can lead the firm, both in the short and long term, to have an
“improper” need to liquidity due to external reasons in respect to the normal business activity. The
consequence of this improper need could be an increase of the debt. In this sense, we can predict
that the firms that refuse to pay the pizzo a lower leverage then the firms paying.
Other economic aspects, however, may lead to an opposite direction. The organized crime, by
the pizzo request, offers protection for money, but the same level of protection can be obtained with
legal expenditures. The legal expenditures for protection could be lower than the pizzo, in this case
the firm’s choice to not pay is convenient but on the contrary (i.e., when the pizzo is lower than the
legal expenditures) it could cause a decrease of the performance. The amount of legal protection can
be high due to the presence of the mafia that makes uncertain the property rights and increases the
transaction costs. In addition, the lost of protection due to the end of the payment makes the firms
subject of possible revenge of the mafia, or of petty crime activities able to create economic
damage. The mafia reprisal entails operative problems such as the time to devote to many activities
necessary after the criminal event (Confcommercio, 2008). In particular, whereas the mafia has a
strong control over the territory, the refuse to pay or the choice to join an anti-racket association can
lead to the end of the relationships with suppliers or customers over the direct control of the
organized crime. The lack of protection by mafia can cause negative externalities such as strong
difficulties in trading with protected firms, people in collusion with organized crime or scared
people (Vannucci, 2001). Summarizing, these economic factors could lead to a different
performance (better or worse) between firms that pay the pizzo and those that do not pay. In
addition, also the performance of the firms adopting an anti-mafia behavior should change after this
decision.
Another perspective to explain the correlation we hypothesize is related to the relationships
network and the building of a sort of social capital. Although there are not shared definitions of
25
social capital (Adler and Kwon, 2002), this concept is linked to a set of values and norms shared
among the members of a group that permit cooperation among them (Fukuyama, 1995). The social
capital is not only linked to positive effects as outlined by Portes (1998) that highlights some
possible negative consequences of a strong social capital: exclusion of outsiders, excessive claims
on group members, restrictions on individual freedoms, and downward-leveling norms. From this
perspective, the correlation between anti-mafia behavior and performance is not related to direct
economic effects of the refuse to pay the pizzo but to the effects of the participation, implicit or not,
in a complex system of relationships. The study of the mafia and organized crime as social network
is deeply rooted in the sociological literature (McIlwain, 1999; Matsueda, 2006) and Sciarrone
(2009) identifies the power of the mafia in its capacity to build social capital by the creation of
strong ties inside the network and weak ties in the relationships with the outside. The request and
the payment of the pizzo could be the first step to try to involve the firm in a more complex
relationship aimed to enhance the illegal network built for the organized crime benefit: in this sense
the pizzo is a sort of “tax fee” to entry in the mafia’s system of relationships and the link between
the mafia (hidden) and the society (visible) (Falcone, 1994; Bellavia and De Lucia, 2009). The
engagement, more or less strong, in an illegal network could allow some advantages to the firm
(Reuter, 1983; Catanzaro, 1988; Gambetta, 1993; Sciarrone, 2009; Kumar and Skaperdas, 2009; De
Jong, Tu and Van Ees, 2010) such as: obtaining favours, also by corrupt public officers; resolving
controversial without using the legal system; altering the market competition having more
opportunities than their competitors. This could have a positive impact on performance, in
particular in the short term. In light of these possible benefits, it is also happened that was the
entrepreneur to contact the mafia to pay the pizzo and entry in the illegal network (Confesercenti,
2012). On the other hand, the participation in this illegal network can lead to negative consequences
for the firm. The illegal network, however, is inherently unstable, turbulent and self-referential. This
makes the firm particularly sensitive to external shocks such as, for example, the network
destruction by the State or its dissolution due to internal conflicts (Reuter, 1983; Uzzi, 1997; De
Jong, Tu and Van Ees, 2010). A performance based on external and unstable factors are, as outlined
in literature, inherently weak (Coda, 1988). Through the payment, the mafia controls the
entrepreneurs and their decision making difficult oriented the actions towards the firm’s good.
Through the pizzo (also by the practice to impose the hiring of people) the mafia knows more in
depth the firm activity and it can better monitor the entrepreneur requiring an explicit authorization
for the main investments or projects (Bellavia and De Lucia, 2009). In other cases, the payment is
the first step to expropriate the firm and excluded it from the entrepreneur control (Falcone, 1994;
26
Bellavia and De Lucia, 2009). In addition, the direct or indirect involvement in an illegal network
puts the firm in a “grey area”, on the border between the legal and the illegal, or it can even drive
the firm to commit unlawful acts with a high probability to be punished by law (Reuter,1983).
These last remarks would lead to consider largely negative from a performance point of view the
participation in an illegal or criminal network of relationships. The social network explanation can
also support a positive correlation between anti-mafia behavior and performance following another
direction. Joining an anti-racket association entail the participation in a “positive” social network
that makes less difficult to face the mafia’s threats using strategies of cooperation. The visibility of
the refuse to pay can work as a form of protection: a collaborator of justice has recently stated that
the extortionists were not in stores exposing the label of Addiopizzo (Palazzolo, 2012).
The third approach regards the social and reputational effects and this concerns not only the
refuse to pay but also the stronger refuse of the mafia’s culture and logic by a public stance. This
approach allow us not only to consider the effects on performance to pay or not to pay but also to
compare firm demonstrating an anti-mafia behavior with those having an ambiguous or neutral
behavior. In this case, the impact on performance is founded on a sort of “reward” assigned by the
society/stakeholder or the market to the “good firms”. A first perspective to explain this possible
reward is the legitimacy one. Legitimacy is the perception that the organizational actions are
desirable, proper or appropriate within a social system of norms, values, beliefs and definitions
(Suchman, 1995). Demonstrating to the whole society an anti-mafia behavior can be considered as
part of an strategic approach to organizational legitimacy by a set of symbols, procedures and rituals
(Downling and Pfeffer, 1975). The firm in this way can obtain or maintain legitimacy in an adverse
environment for the strong presence of the organized crime, contributing to the shift of social norms
and values. A similar path was realized as anti-bribery organization by Addiopizzo through its
strategy of information disclosure (Vaccaro, 2012). In this sense, a credible “status” of anti-mafia
behavior entails a social legitimacy that rewards the better firms to the detriment of the neutral or
ambiguous ones. The firms with ambiguous or explicitly negative behavior can be subject of
reputational penalties by investors for its not desirable activities (Davidson and Warrell, 1988;
Karpoff and Lott, 1993; Karpoff, Lee and Martin, 2009). This is in line whit the idea that the forces
of the market are able to correct errant firm behaviors. As for the anti-mafia behavior the legitimacy
process works if the social values are consistent with the choice to refuse to pay the pizzo. The
social reputational effect can depend on the moral perception about the firm behavior: different
illegal activities are punished in a different way (Karpoff et al., 2010). This different penalization
can depend on the social assessment about the different behaviors. In addition, the anti-mafia
27
behavior contributing to make more moral and legal the socio-economic context allows an virtuous
circle in which an ethical behavior is stronger rewarded in a more moral environment avoiding that
mafia can shape the society and the market according its norms and disvalues (Sciarrone, 2009).
Another similar explanation is related to the stakeholder approach. Assuming that stakeholders
pursue not only self-interest goals, its relationship with firm depends also on the perception about
the firm’s behavior towards the other stakeholders and the whole society (Larson, 1992; WadeBenzoni, 2002). On one hand, an explicit anti-mafia behavior is positively perceived by
stakeholders leading to an improvement on the relationships with the firm and on firm performance
since the link between good firm-stakeholder relationships and performance (Frooman, 1999). On
the other hand, the strong presence of organized crime, its threatening in the use of violence, a
limited moral imagination related to the mafia activities (Vaccaro, 2012) could lead to negative
social and reputational effects on the performance of an anti-mafia firm. For example, the customers
could be scared to buy goods by an anti-mafia firm or they could consider not important the firm’s
behavior for their purchasing decisions. In the stakeholder perspective, it is also important take in
account the category of stakeholders (primary o secondary) involved in a negative o positive firm
behavior and their power to react for the benefit or the detriment of the firm (Mishina et al., 2011).
The analysis of the social/reputational factors of the anti-mafia behavior shows the possible effects
not only in terms of performance but also in terms of sales growth.
These three groups of explanations are not alternative but they could be mixed causing an
unpredictable finding.
On the basis of these assumptions, other hypotheses to be tested are:
H8a : Firms adopting anti-mafia behavior enjoy different performance than do other firms.
H8b : After the adoption of anti-mafia behavior a firm has a different performance than the past
one.
H9a: Firms adopting anti-mafia behavior has a lower leverage than do other firms.
H9b : After the adoption of anti-mafia behavior a firm has a lower leverage than the past one.
Figure 2 shows the conceptual framework adopted and the hypotheses to be tested, as well as
other a set of environmental conditions here used as control variables:
28
Environmental
conditions
(Legal form)
(Year)
(Size)
(Industry)
(Region)
H8 a-b
(Future
performance)
H1 (Past
performance)
Operating
conditions
H2
(Leverage)
Anti-mafia
entrepreneurial
behavior
FIRM
DETERMINANTS
H3
(Ownership)
H4 a-b
(Familiness)
H6
(Gender)
H5
(CEO Age)
(Firm
Age)
FIRM
EFFECTS
H9 a-b
(Financial
structure)
H7 a-b
(Board size)
Personal/Firm
characteristics
Figure 2. Conceptual framework and hypotheses development
3. METHODOLOGY
3.1. Sample construction
3.1.1. Anti-mafia firms sub-sample: selection process
Sample analyzed was formed of both anti-mafia firms and “neutral” firms. As to the sub-sample
of anti-mafia firms, we collected data from two main sources, including the Addiopizzo list and the
AIDA (Bureau van Dijk) database. We firstly extracted firms from Addiopizzo lists. These lists
contain firms from any part of Sicily, although most of them are from Palermo and Catania, the two
most developed cities in Sicily. Firms from Addiopizzo Naples were also added. The firms
belongings to these lists have all signed a document to join the association in which they expressly
state to not pay the pizzo. Addiopizzo periodically checks the ethical requirements of the firms in the
list. For these reasons the firms belongings to these lists are consistent with our definition of “antimafia behavior”. The lists are public and they can be consulted online. Stemming from this lists we
selected only companies (limited companies or cooperatives), because individual firms are not
observed in the AIDA database. In addition, we had to exclude companies showed in the
Addiopizzo list but not represented in AIDA. So, we were able to build sample of anti-mafia
companies by cross-referring data from these two main sources. We finally excluded companies
29
with too many missing values in AIDA. Table 1 shows the selection criteria adopted for the subsample of anti-mafia companies.
Table 1 – Selection criteria and size of the initial and final sub-samples of anti-mafia firms
Initial size sub-sample: all Southern Italian firms included in the Addiopizzo lists of
Palermo (779), Catania (102), and Naples (355) as of December 2012
Filters
Criteria for dropping
1.236
100%
# firms
dropped
% firms
dropped
1.018
82,3%
101
8,2%
2.
– Firms that are not companies (i.e., individual entrepreneurs) or only divisions
of a principal firm
– Companies not found in AIDA database
3.
– Bankrupted or inactive companies
4
0,3%
4.
– Companies with missing values in AIDA
2
0,2%
111
8,9%
1.
Final size sub-sample
Data extracted from AIDA included performance (Sales, ROA, ROE, ROS, employee
performance), governance and demographics (ownership, number of directors, age and gender of
top management) and control variables (size, industry, location), while company’s entry year into
the Addiopizzo list was obtained by directly contacting a member of the Addiopizzo Committee of
each city.
3.1.2. Neutral firms sub-sample: statistical matching
Especially in order to verify that the true determinant of performance is the anti-mafia or neutral
firms’ behavior, we adopted a matched-pair design (Bowen, Noreen et al., 1981) that provides the
most effective means of controlling demographic data such as location type, industry, and size. The
idea behind this approach, e.g. applied by Allouche et al. (2008) and Jorissen et al. (2005) in the
field of family business studies, is to compare systematically anti-mafia firms with other firms that
are as similar as possible, except they are not assumed to behave in an anti-mafia manner.
Therefore, these are neutral businesses with the same profiles, that is in the same geographical
context or location, in the same industry, and of nearly the same size. This approach allowed us to
neutralize the most important potential factors of performance variance outside of anti-mafia
behavior, that may bias performance differences related to the anti-mafia or neutral firm’s behavior.
In order to build the comparison sub-sample of firms not adopting an anti-mafia behavior we
first set up pairs of business (one anti-mafia business, one neutral business) in the same industry and
of approximately the same size (in terms of total assets and/or number of employees). This
approach helps mitigate two key reasons for performance variance and thereby sheds more light on
the influence of anti-mafia behavior on performance, while the adoption of the same geographical
30
location should avoid cultural and behavior differences among firms of the whole sample. To
identify the firms’ industries, we use the four-digit statistical classification of economic activities in
the European Community (NACE, Rev. 2), an European standard industry classification system
similar in function to Standard Industry Classification (SIC) and North American Industry
Classification System (NAICS) for classifying business activities. For each of the original 111 antimafia companies, we chose a neutral firm with the same NACE code (91% of the matched pairs
have equal NACE codes at the full four-digit level, 9% at the three-digit level). We then chose a
neutral firm with the same location (70% of the matched pairs were located in the same city, 30% in
another city of the same region). Within the same industry and location, the most closely related
family firm in terms of firm size is chosen.
Our measures of the size of the business reflect total assets and/or number of employees. Two
companies in the same industry are regarded as similar in size if their total assets and/or number of
employees are within 20% of each other. Sometimes (for 17% of cases in our sample), we had to
relax this percentage and we referred to a 30%. Besides, we had also to select those comparable
firms showing in AIDA approximately the same number of years (AIDA does not cover the tenyear period of observation for all firms) and complete in financial, demographic and governance
variables. Finally, many potentially comparable firms showed in AIDA were in default, so we could
not consider them.
Notwithstanding these stringent matching criteria, we found well-matching neutral firms for
almost all of the original 111 anti-mafia companies (94,6%). Assuming a sufficient number of such
pairs of anti-mafia and neutral firms, we can compare their determinants and their performance and
other indicators, having controlled for location, size and industry.
Firms of our sample belonged to the following sectors (letters indicate main sections of the
NACE Rev. 2): C) Manufacturing; F) Construction; G) Wholesale and retail trade; repair of motor
vehicles and motorcycles; H) Transportation and storage; I) Accommodation and food service
activities; J) Information and communication; N) Administrative and support service activities; R)
Arts, entertainment and recreation. We created a residual section “Others” for those firms that were
the unique within a given sector and this was the case of five sections of the NACE Rev. 2.
Table 2 – Sample distribution (anti-mafia firms and neutral firms) by city and sector
Southern
Italian
Cities
SECTORS (NACE REV. 2 INDUSTRY CLASSIFICATION)
Accommod
Arts,
Wholesale Transport
Information Administrative
Manufactu
ation and
entertainment
Construction and retail ation and
and
and support
ring
food
and
trade
storage
communication
service
service
recreation
31
Others
TOT
Firms
%
Palermo
Catania
Naples
TOT
28
16
60
8
6
2
4
4
0
0
5
28
19
0
6
35(15,8%) 48(21,6%) 83(37,4%) 8(3,6%) 12(5,4%)
4
0
2
6(2,7%)
6
2
2
10(4,5%)
8
0
2
10(4,5%)
4
140
0
12
6
70
10(4,5%) 222
63,1%
5,4%
31,5%
100%
Table 3 – Descriptive univariate statistics (all values are at the end of the financial year 2011)
Variables
Anti-mafia
Adhesion Year
Size (Sales €000)
Roa (%)
Ros (%)
Roe (%)
Added value
Employee performance
Leverage
Net financial position
%Debt/sales
Firm Age
CEO Age
CEO Gender
Family
#Shareholders
%MajorShareholder
#Directors
N
222
111
222
222
219
213
221
213
222
222
222
222
221
222
219
205
205
222
Mean
0,5
2010
€ 2.904
3,53%
3,21%
-2,12%
552.678
10,30
2,09
692.638
25,26%
14,91
50,17
0,85
0,47
2,73
62,06%
1,97
Median
0,5
2011
€ 1.545
3,16%
2,72%
5,82%
339.561
6,32
0,66
130.871
11,24%
12
48
1
0
2
51%
1
Std. dev.
0,50
1,65
€ 5.245
15,83
13,51
77,72
937.078
12,44
9,35
2.665.931
58,29
11,30
12,50
0,36
0,50
2,39
24,17
2,04
Min
0
2005
€0
-106,06%
-73%
-646%
-275.067
0,32
-79,36
-3.246.821
0%
1
26
0
0
1
13%
1
Max
1
2012
€ 63.535
112,65%
69%
127%
11.161.190
90,49
78,92
35.919.608
663,52%
65
82
1
1
30
100%
18
3.2. Statistical models and approaches
3.2.1. Multivariate analyses: logistic regression analysis and econometric model adopted
In order to test the first set of hypothesis underlying the research question as to what the
determinants of the anti-mafia entrepreneurial behavior are, we performed maximum likelihood
logistic regression analyses on the original representative data set of 216 companies (three antimafia companies and, as a consequence, three neutral companies were not included in the original
sample of 222 because for these firms independent variables related to the previous financial year
were not available in AIDA). Logistic regression analyses explain the variation in the dichotomous
dependent variable (1 = anti-mafia firm vs. 0 = neutral firm) from a set of independent financial,
demographic and governance variables. We performed analyses both without and with control
variables for firm demographics (size, industry, age, legal form, and region of the firm) and for
years. We also performed. To mitigate potential endogeneity, firm-specific variables and control
variables are estimated in lagged values. The logit general model adopted is the following:
Anti-mafiait = β0 + β1Roeit-1 + β2BankDebtit-1 + β3Familyit + β4CeoAgeit-1 + 9 β5Genderi +
β6Shareholdersi + β4 7Ownershipi + β8Directorsi +2012β9Sizeit-1 + β10∑IndustryiX +
X=1
β11FirmAgeit-1 + β12∑Legal formiX + β13Regioni + β14∑YeariX + εi
X= 1
X=2006
Where:
32
Anti-mafiait = dummy variable having value 1 if the company i belongs to the Addiopizzo list, 0
otherwise;
Roeit-1 = past performance of the company i expressed in terms of return on equity;
BankDebtit-1 = leverage level of the company i expressed as percentage of bank debts on sales;
Familyi = dummy variable having value 1 if the company i is a family firm (family possesses the
majority of the shares and/or at least two members of the family sit on the Board of Directors), 0
otherwise;
CeoAgeit-1 = major owner and/or CEO’ age of the company i expressed as natural log of the number
of years;
Genderi = dummy variable having value 1 if the major owner or CEO of the company i is a male, 0
otherwise;
Shareholdersi = natural log of the number of shareholders of the company i;
Ownershipi = ownership concentration of the company i expressed in terms of percentage of shares
hold by the major owner;
Directorsi = natural log of the number of directors of the company i;
Sizeit-1 = company size of the company i expressed in terms of natural log of sales;
∑ Industryi = dummy variable having value 1 if the company i belongs to one of the nine sectors,
with wholesale and retail trade as sector of reference;
FirmAgeit-1 = age of the company i expressed as natural log of the number of years since the
foundation;
∑ Legal formi = dummy variable having value 1 if the company i belongs to one of the four main
legal forms (small limited liability company (srl), large limited liability company (spa),
small/large limited liability company with one owner (srl/spa a socio unico), or cooperative
company), with srl as legal form of reference;
Regioni = dummy variable having value 1 if the company i belongs to the region Campania, 0
otherwise (i.e., it belongs to the region Sicily);
∑Yeari = dummy variable having value 1 for each of the eight years during which a company i can
choose to entry in the Addiopizzo list (2005-2012), with 2005 as year of reference.
3.2.2. Paired t-test
In order to test the second set of hypothesis underlying the research question as to what the
effects, in terms of performance and financial structure, of the anti-mafia entrepreneurial behavior
are, we computed the difference between anti-mafia and neutral firms as averages for the following
indicators: return on assets (ROA), return on equity (ROE), return on sales (ROS), leverage, and so
on. Then we tested (using both Student t-test and Wilcozon z-statistics, paired sample) whether the
difference is significant at a 5% level; if it is not, we also considered whether it is significant at a
10% level. To avoid overdependence on a single year of data, which might be subject to specific
effects, we assessed these comparisons: i) at the same year in which a firm chose to entry in the
Addiopizzo list; ii) one year later that in which a firm chose to entry in the Addiopizzo list; and iii) at
the end of the financial year 2011, regardless the year in which a firm chose to entry in the
Addiopizzo list.
33
3.3. Empirical results
Table 4 shows logistic regression results for our four models using the full sample.
Table 4 – Logistic Regression Results of Financial, Demographic and Governance Variables Associated
with Anti-mafia or Neutral Firms (anti-mafia firm = 1; neutral firm = 0)
Independent
variables
Expected
Sign
Roe
BankDebt
Family
CeoAge
Gender
Shareholders
Ownership
Directors
Size
FirmAge
Year
Legal Form
Industry
Region
Constant
% of correct predictions
Hosmer-Lemeshow test
?
+
+/+
+
+
+/?
?
?
?
?
?
Cox & Snell R
2
Model 1
Financial and
Control Variables
Coefficient (Sig.)
-,012 (,058)*
,019 (,042)**
-,368 (,023)**
-,113 (,528)
n.s.
n.s.
n.s.
n.s.
5,478 (,020)**
61,7%
(,483)
,079
Model 2
Demographic and
Control Variables
Coefficient (Sig.)
Model 3
Governance and
Control Variables
Coefficient (Sig.)
Model 4
All Independent
Variables
Coefficient (Sig.)
,246 (,460)
,359 (,555)
,071 (,871)
-,318 (,039)**
-,043 (,811)
n.s.
n.s.
n.s.
n.s.
,556 (,203)
,016 (,096)*
,640 (,069)*
-,420 (,015)**
,115 (,544)
n.s.
n.s.
n.s.
n.s.
-,014 (,054)*
,017 (,112)
,320 (,398)
,133 (,846)
,013 (,979)
,426 (,362)
,017 (,105)
,577 (,110)
-,460(,014)**
-,110 (,613)
n.s.
n.s.
n.s.
n.s.
3,047 (,308)
55,5%
(,807)
,039
4,116 (,108)
59,4%
(,198)
,079
4,531 (,210)
65,1%
(,600)
,111
2
,105
,105
,053
Nagelkerke R
*, ** and ***indicate significance at p < 0,10, p < 0,05 and p < 0,01 or better level respectively based on two-tailed tests.
,149
In the logistic regression analyses the variance inflation factors (not shown) ever exceed the
cutoff value of 3, except for the dummy variables Y2011 and Y2012, that we decided to eliminate
from the models in order to solve multicollinearity problems. Model 1 investigates the impact of
two main financial variables, i.e. past performance (ROE of the previous financial year) and the
percentage of bank debt on Sales (Bank Debt) on the decision to adopt an anti-mafia behavior.
Model 2 considers the role of demographic variables, such as the dichotomous variables related to
the Family and to the Gender, and the continuous variable CEOAge on that decision. Model 3 uses
governance variables such as the number of shareholders (Shareholders) and directors (Directors)
and the percentage hold by the major owner (Ownership). Finally, Model 4 considers financial,
demographic and governance variables at the same time. All models include also a set of control
variables related to the size (Size), the age (FirmAge), the legal form (Legalform) and the industry
(Industry) of the company, the dichotomous variable related to the region (Region), and the years of
the period 2005-2010 (Year). The regressions carried out suggest that the Model 4 correctly
classifies 65,1% of the firms surveyed, so confirming the need to consider all three types of
independent variables, as confirmed also by the two main Pseudo R2. The Hosmer & Lemeshow
34
tests also indicate the goodness-of-fit of the model, with p-value always higher than of 0,19, and it
indicates that the binary logistic models fits well for the data. Hence, the validity of the models has
been tested and it adequately describes the data.
In the Model 1 the variables ROE and BankDebt are significantly negative at p < 0,10 (twotailed) and positive at p < 0,05 (two-tailed), respectively. The significantly negative coefficient
indicates that companies with stronger past performance are less likely to adopt an anti-mafia
behavior, by entering in an Addiopizzo list, while the significantly positive coefficient indicates that
companies with higher percentages of bank debts on sales are more likely to adopt an anti-mafia
behavior (although in the Model 4 the latter evidence is not confirmed). These two results are
consistent with the expectation that companies experiencing economic and financial difficulties are
not able to sustain the illegal payment of the pizzo. Demographic variables are never significantly
relevant, as showed in Model 2, as well as in other models. Among governance variables, the
number of directors and the amount of shares held by the major owner are both significant and
positive at p < 0,10. This means that companies where the decision-making process involves more
directors and where the ownership concentration is higher are more likely to make an anti-mafia
choice. Finally, while company size variable (Size) is always significant and negative at p < 0,05 in
all the models, so confirming that smaller companies are more likely to report and/or to adopt an
anti-mafia behavior, all other five control variables are, however, insignificant at conventional
levels. Although the impact of the governance variables is not confirmed in the full Model 4, we can
strongly support the argument that determinants of the anti-mafia behavior have mainly financial
and economic nature.
Moving now to the second research question of this paper, table 5 shows results of comparative
performance and financial structure between anti-mafia and neutral firms, using both t-student and
Wilcoxon Z-statistics (generally speaking, the latter are stronger than the former).
In order to test the validity of the variables adopted, we also performed robustness analysis by
using different measures of performance, instead of Sales. These are ROA, ROS, ROE, added value
and employee performance.
Table 5 – Comparative performance and financial structure of anti-mafia firms and neutral firms at
different times.
Panel A – Between analysis at the year of adhesion
Sub-sample
reduction
Initial sub-sample
Less
Performance measured at the same year of
the adhesion to the Addiopizzo list (N = 164)
111
11
Companies entered in the Addiopizzo list during 2012
(no data available in AIDA for this year)
35
Panel B – Between analysis at the year after adhesion
Performance measured at the year after
that of the adhesion to the Addiopizzo list (N = 98)
111
Companies entered in the Addiopizzo list during
11
2012 (no data available in AIDA for this year)
Less
6
Companies with no data available in AIDA for 2011
45
Less
6
Companies with no comparable firms (no matching)
4
6
Companies or pair companies with no data available
in AIDA for the year of the adhesion
2
Less
Final sub-sample
82
49
Means
Antimafia
Neutral
firm
firm
Indicators
Performance
Sales (€000)
ROS (%)
ROA (%)
ROE (%)
Added value
(€000)
Employee
performance
Financial
structure
Leverage
(debt/equity)
Bank Debt
on Sales (%)
Net financial
position (€000)
Companies entered in the Addiopizzo list during
2011
Companies with no data available in AIDA for the
year after that of the adhesion
Pair companies with no data available in AIDA for
the year after that of the adhesion
∆
Significance (p-value)
Wilcoxon
T-test
Z-statistics
4.012
1,51
1,53
-1,55
3.244
3,62
5,68
1,20
769
-2,11
-4,15
-2,76
,440
,092*
,055*
,779
,104
,082*
,004***
,047**
690
667
23
,765
,769
7,64
12,20
-4,56
,001***
,001***
1,53
3,06
-1,54
,183
,046**
20,47
18,29
2,19
,547
,478
879
485
394
,195
,833
Antimafia
firm
Means
Neutral
firm
∆
Significance (p-value)
Wilcoxon
T-test
Z-statistics
5.043
2,18
0,68
-4,54
920
3.721
3,72
4,83
-13,18
763
1.322
-1,53
-4,16
8,64
157
,350
,245
,309
,700
,140
,988
,216
,053*
,893
,267
9,73
11,36
-1,63
,526
,119
2,31
5,38
-3,07
,109
,082*
29,93
22,81
7,11
,397
,672
1.423
767
656
,259
,453
+/++/+++ (-/- -/- - -): Statistically significant relation in line (+) or in contrast (-) with our hypotheses (p < 0.1/0.05/0.01).
*/**/***: Statistically significant relation without specified hypothesized direction (p < 0.1/0.05/0.01 level of significance).
Panel C – Between analysis at 2011
Sub-sample
reduction
Initial sub-sample
Panel D – Within analysis pre- and post- adhesion
Performance measured at the end
of the financial year 2011 (N = 144)
Performance measured pre- and post- year
of the adhesion to the Addiopizzo list (N = 48)
111
111
Less
11
Companies entered in the Addiopizzo list during 2012
11
Less
14
Companies with no data available in AIDA for 2011
45
Less
3
Less
Final sub-sample
6
77
Indicators
Performance
Sales (€000)
ROS (%)
ROA (%)
ROE (%)
Added value
(€000)
Employee
performance
Financial
structure
Leverage
(debt/equity)
Bank Debt
on Sales (%)
Net financial
position (€000)
Pair companies with no data available in AIDA for
2011
Companies with no comparable firms (no matching)
7
Companies entered in the Addiopizzo list during
2012 (no data available in AIDA for this year)
Companies entered in the Addiopizzo list during
2011 (no data available in AIDA after this year)
Companies with no data available in AIDA for the
year preceding or following that of the adhesion
48
Means
Antimafia
Neutral
firm
firm
∆
Significance (p-value)
Wilcoxon
T-test
Z-statistics
Preadhesion
Means
Postadhesion
5.614
2,65
2,22
14,06
5.165
4,20
2,14
-3,54
-449
1,56
-0,08
-17,61
,245
,426
,971
,176
,837
,518
,626
,800
911
944
33
,515
,154
∆
Significance (p-value)
Wilcoxon
T-test
Z-statistics
2.518
-0,16
0,07
-2,11
3.069
2,27
4,73
3,41
-552
-2,43
-4,66
-5,52
,105
,153
,067*
,577
,099*
,064*
,009***
,166
508
558
-49
,533
,453
7,90
11,80
-3,90
,021**
,014**
10,64
10,38
-0,26
,813
,232
0,34
3,84
-3,50
,025**
,060*
1,58
2,30
0,72
,245
,166
27,32
19,43
7,89
,185
,195
15,18
29,45
14,27
,084*
,007***
601
505
97
,382
,642
1.090
1.423
333
,111
,038**
+/++/+++ (-/- -/- - -): Statistically significant relation in line (+) or in contrast (-) with our hypotheses (p < 0,1/0,05/0,01).
*/**/***: Statistically significant relation without specified hypothesized direction (p < ,1/,05/,01 level of significance).
36
Results from the “between analysis” partly confirm different performance and financial
structure. In particular, in Panel A we compare means at the same year of adhesion to the
Addiopizzo list and we find that anti-mafia companies perform less than neutral companies (as to
ROS, ROA, ROE, and employee performance), so confirming that anti-mafia companies “pay the
piper” immediately, when they decide to adopt an anti-mafia behavior. In addition, at the same year
of adhesion leverage shows a statistically significant difference (at 0.05 level), with anti-mafia
companies to be less leveraged. However, one year after this decision, differences between antimafia companies and neutral companies (observed in a smaller sample) disappear, as showed in
Panel B where most of differences are not statically significant anymore, except for ROA and
leverage. Therefore, while in the very short term adopting an anti-mafia behavior lead companies to
underperform if compared to the companies not making the same decision, in a longer term their
performance is likely to become similar to that of neutral companies. In Panel C, we compare
performance and financial structure at the end of financial year 2011, for all companies regardless
the year of adhesion to the Addiopizzo list and results are, for sign and statistical significance, very
similar to those showed in Panel A. We also performed, in Panel D, an analysis within only antimafia companies by comparing performance pre- and post- the year of adhesion to the Addiopizzo
list. Although economic performance is not different in the two years of the comparison, differences
as to percentage of bank debt on sales and net financial position are statistically relevant, showing
that after the decision to report and to enter in an Addiopizzo list, anti-mafia companies increase
their debts.
4. DISCUSSION, LIMITATIONS AND CONCLUSIONS
This study was exploratory in nature as anti-mafia behavior at the firm level has not received
much attention. As a result, there was no ready-made theory to be tested. We started from two
different research questions: what are the determinants of anti-mafia entrepreneurial behavior? 2)
what is the impact of this decision on firm performance?
Since there is not specific theory about anti-mafia behavior of the firm, to address these issues
we firstly analyzed the literature trying to develop hypotheses based on different approaches and on
literature about topics that are similar to our focus. As for the first research question the hypothesis
was that performance, leverage, ownership and some personal/firm characteristics (age and gender
of CEO or major owner, number of directors) are the main determinants of the anti-mafia behavior.
In relation to the second research question the hypothesis was that the firms adopting an anti-mafia
behavior have different performance and financial structure than neutral firms and that the adoption
37
of this behavior leads to a change in performance and financial structure. To test these hypotheses
we built two sub-samples, the first related to anti-mafia firms (using the Addiopizzo lists) and the
second related to neutral firms (using a matched-pair design). Statistically different methods have
been used: logistic regression (first research question) and paired t-test and Z-statistic (second
research question).
The results show that for the first research question the two variables statistically more
significant are ROE and the percentage of bank debt on sales. Specifically, there is a negative
correlation between ROE and the adoption of anti-mafia behavior and a positive correlation
between the amount of bank debt and the adoption of anti-mafia behavior. The first result confirms
our hypothesis H1, based on the behavioral agency theory, according to which past performance
influences the adoption of an anti-mafia behavior. This can be explained by two possible
motivations (highlighted in the Figure 1). The first is related to the situation D (entrepreneur that
paid the pizzo in the past): in this case the payment of the pizzo becomes unsustainable for the firm
that choices to entry in an anti-racket network. A different motivation is related to the situation C
(entrepreneur that did not pay in the past and without threats): a low performance can lead the firm
to seek a reputational advantage by entering in an anti-racket list. The second result confirms our
hypothesis H2, based on the agency theory, that the leverage has a positive correlation with the antimafia behavior. In this case, the motivations for not to pay the pizzo could arise from financial
difficulties for a high debt or from an increased risk of bankruptcy.
In addition of these financial variables, there are weak signs of a correlation between the number
of directors and anti-mafia behavior and between high concentration of ownership and anti-mafia
behavior. In the first case, the result confirms our hypothesis H7b and, therefore, the resource
dependence theory approach (Pfeffer and Salancik, 1978; Dalton et al., 1999; Hillman et al., 2000),
according to which the number of directors positively influences the anti-mafia behavior by virtue
of the many resources, advices and relationships with stakeholder and external organizations on
which to rely. This could be related to another of the motivations presented (indicated in the
situations B and D of Figure 1), that is an attitude of trust in institutions since the directors may
have some links with key actors (members of professional associations, of anti-racket associations,
etc.) which favors the reaction to the mafia. In the second case is confirmed our hypothesis H3 that
the anti-mafia behavior is more likely to occur when the ownership is concentrated; a small number
of large shareholders has, in fact, the power to take a decision as difficult and controversial like to
not pay the pizzo. Summarizing the results about the first research question, the more relevant
determinant that lead to adopt an anti-mafia behavior is the financial condition of the firm. Firms in
38
a bad situation are more motivated to change due to the difficulty to sustain the pizzo payment and
they attempt to improve their results. On the contrary, the age and gender of the CEO or major
owner seem do not have any correlation with the adoption of anti-mafia behavior.
As for the second research question, we found evidence that in the year of adhesion to
Addiopizzo neutral firms have better performance than anti-mafia firms (partially confirming our
H8a hypothesis); in the year after the adhesion to Addiopizzo lists there are no significant
differences of performance between anti-mafia and neutral firms (not confirming our H8a
hypothesis); in the short term the decision to entry into the Addiopizzo list does not entail change in
the performance of the anti-mafia firms (not confirming our hypothesis H8b); anti-mafia firms have
a lower leverage than neutral firms (confirming our hypothesis H9a); the decision to entry into the
Addiopizzo list leads to an increase of debt (not confirming our hypothesis H9b).
In reference to the different performance between anti-mafia and neutral firms, in the very short
terms seems that the possible negative effects of the decision to adhere to an anti-racket association
prevail on the positive effects. Problems such as the reprisal of mafia, the difficulties in the
relationships with colluded or scared people, seem to be stronger in the very short period, while the
anti-mafia “identity” of the firm could be perceived more weakly in the later periods. The decision
to adopt an anti-mafia behavior in spite of the financial variables seems to be the more significant to
explain this behavior, does not entail strong effects in performance (except for the year of adhesion)
both in the between analysis (comparison between anti-mafia and neutral firms) and in the within
analysis (analysis among the anti-mafia firms). This could support the idea that the decision to
adopt an anti-mafia behavior should have in the ethical and social aspect its main pillar.
The difference in the leverage between anti-mafia and neutral firms confirms our H9a
hypothesis.
In the comparison between anti-mafia and neutral firms, it is useful considering the substantial
lack of “reward” for the anti-mafia behavior (on the contrary a penalty in the very short term) and of
“penalty” for the neutral behavior. As for the lack of a recognition of the anti-mafia behavior, there
are two possible explanations. The first is that the anti-mafia behavior is not recognized as a
virtuous behavior, that is the market and the society do not consider this choice so much relevant to
be rewarded. This would be an evidence of a problem of moral imagination in the context in which
these firms act (Vaccaro, 2012). The second, instead, is related to the “visibility” of this choice: the
market and the society do not recognize the relevance of the anti-mafia behavior only because they
do not know this choice. In this case, the problem is an inadequate strategy of communication by
the firms.
39
In relation to the neutral firms, the problem of moral imagination is more complex. These firms
do not adopt an explicit anti-mafia behavior and so they can include both firms paying the pizzo and
firms that do not pay (according to the more validated assessments the first group should be more
numerous). Karpoff et al. (2010) showed the penalty of the market for a illegal or undesirable
behavior is not equal but there are differences based on the evaluation of the different behaviors. In
this sense, the neutral approach of the anti-mafia strategy is not considered an undesirable behavior
maybe because it is impossible to distinguish firms paying (situation A in the Figure 1) from firms
that do not pay (situations E, F and G in the Figure 1).
Our study is subject to several limitations. First, while in our models we control for factors we
believe are associated with the decision to report and to adopt an anti-mafia behavior, our results
could be due to correlated omitted variables. Second, the power of our tests is limited by the small
sample size of firms entered in an Addiopizzo list. Third, the analysis of effects in terms of
performance are limited to the short time due to the fact that many firms entered into Addiopizzo
lists only in the 2011 or 2012, making difficult the statistical analysis of longer periods. Finally, we
have to acknowledge the difficulty to clearly identify firms paying the pizzo.
However, in order to overcome these main limitations and to improve the answers of our two
research questions, in the next stages of our research we aim at implementing our analysis. As for
the first research question, by using more qualitative methods to gather data (such as questionnaires
or interviews) we will try to consider other determinants of the anti-mafia behavior related to
cultural, ethical, social and educational factors that can affect this choice testing in a complete
manner the theoretical scheme represented in Figure 1. In order to better assess the consequences in
terms of performance, we will increase our observations for both the number of firms and the
number of years analyzed when it will increase the number of firms listed for a long period of time.
From a statistical point of view it would be interesting to investigate non-linear effects, for example
a U-shape correlation between the adoption of anti-mafia behavior and the performance.
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