Control within the Cultural Context of Blat: a study of Management Control Systems, Strategy,Innovation and Performance within Russian Business Organizations

ROBERT H. CHENHALLMonash University, Department of Accounting and Finance,P.O.Box 11E, Monash University, Victoria 3800, Australia

JUHA-PEKKA KALLUNKIUniversity of Oulu, Department of Accounting and Finance,

P.O.Box 4600, FIN-90014, University of Oulu, Finland

HANNA SILVOLAUniversity of Oulu, Department of Accounting and Finance,

P.O.Box 4600, FIN-90014, University of Oulu, Finland

Contact Address: Robert H. Chenhall, Monash University, Department of Accounting and Finance, P.O.Box 11E, Monash University, Victoria 3800, Australia. E-mail: Robert.Chenhall@BusEco.monash.edu.au.

Acknowledgements: We gratefully acknowledge the valuable comments and suggestions on the earlier versions of this paper provided by Kari Liuhto, Neale G. O’Connor, Tuomo Peltonen, Pia Polso, Mikko Puhakka and Henrikki Tikkanen,. We also thank the seminar participants at the Faculty Research Workshop at the Universityof Oulu .

Control within the Cultural Context of Blat: a study of Management Control Systems, Strategy, Innovation and Performance within Russian Business Organizations

Abstract

This paper investigates how the unique Russian personal networking practice, Blat, affects the relationships between management accounting control systems, strategy, innovations and performance of Russian business enterprises. We distinguish traditional Blat which is based on trust and personal relationships from modern Blat which involves more hostile relationships based on unidirectional power. Using data from a sample of 100 Russian businesses, we find that traditional Blat is positively correlated with innovation and organizational performance; while modern Blatcorrelated with performance.

We develop a path model which shows that the correlation between traditional Blat and performance is mediated by paths acting through organic controls and strategic differentiation. The correlation between traditional Blat and innovation is also mediated by paths through organic controls and differentiation, and additionally formal controls are implicated by way of paths from traditional Blat to differentiation to formal controls to innovation. The correlation between modern Blat and performance is mediated by way of a negative path through organic controls and differentiation.

From the path model, we also report that traditional Blat is positively related to the use of organic controls, while modern Blat is negatively related to organic controls. Neither form of Blat is associated with formal controls. In addition, the use of formal and organic controls is positively related to innovation, and organic controls are associated with enhanced performance.

In sum, these results indicate that in Russia, traditional Blat has an effect in motivating the adoption of organic controls which, in turn, is associated with innovation and performance. Traditional Blat is also positively associated with strategies of differentiation while modern Blat is negatively associated with differentiation. Differentiation, in turn, is associated with organic and formal controls, innovation and performance. In this study, innovation is not associated with performance.

Key words: management accounting controls, strategy, innovation, Russian Blat

JEL Classification: M41

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Control within the Cultural Context of Blat: a study of Management Control Systems, Strategy,Innovation and Performance within Russian Business Organizations

Introduction

In the management accounting literature, there has been a variety of studies that have investigated how the social

and cultural environment of the firm affects the use of management accounting control systems (MACS) (Harrison &

McKinnon, 1999). Some studies explore the diffusion of different MACS among firms in transitional countries such as

China or India (e.g. O’Connor et al., 2004; Anderson & Lanen, 1999). Others address the question of how foreign

influence affects the use of MACS in companies in transitional countries (e.g. Firth, 1996; Efferin & Hopper, 2007).

Another body of research has investigated the problems in implementing MACS when firms are expanding their

operations to countries with different social and cultural environments (e.g. Southworth 1994; O’Conner, 1995). While

the general findings of this literature are somewhat mixed as to the precise affect of culture, overall it appears that the

social and cultural environment of a country affects the implementation and use of organizations’ MACS.

A variety of approaches have been employed to study national culture and MACS. In essence they can be

classified as structural contingency and sociological approaches. (Bhimani, 1999). Cultural contingency research has

been, in the main, based on employing the cultural values of Hofstede (1984). This involves classification of cultures at a

broad national level and the impact of these dimensions on the adoption of MACS and examining the effective use of

various aspects of MACS (see Harrison and McKinnon, 1999, for a review). One criticism of this research is that the

view of culture and its analysis are too general and the nuances of culture are not considered (Baskerville, 2003;

Baskerville-Morley, 2005). Nor do studies consider why and how the cultural values emerge and how they influence

MACS. While some commentators believe that the limitations of cultural contingency approaches can only be solved by

employing sociological theories and methods (Baskerville, 2003), others acknowledge that structural contingency can

provide insights by providing finer partitioning of culture of the nation being studied, and the specific context of the

organization and the characteristics being examined (Harrison & McKinnon, 1999; Hofstede, 2003). It is not our intention

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to argue the benefits of one or other approaches, or engage in debates on various approaches to accounting research.

this study we examine the cultural dimension of Balt that is specific to Russia, not the entire national culture. We identify

this attribute of culture by examining prior literature and discussing pertinent issues with experts on Russian business and

with Russian business people. Our aim is to clarify and measure this variable endeavoring to avoid the criticism of being

superficial or naive in our consideration of this cultural dimension (Harrison & McKinnon, 1999). We see

historically specific and as being derived from socially structured contexts and processes (Thompson, 1990, 136, quoted

in Harrison & McKinnon, 1999). We then seek to identify the affects of Blat in enhancing innovation and organizational

performance within the contemporary economic context of emerging competitive markets in Russia, and then to examine

the role played by strategy and MACS.

1 For a discussion of the study of culture in accounting research, particularly the use of the cultural values developed by Hofstede (1984) and Hofstede, G. H., & Bond, M. H. (1984), see Harrison and McKinnon (1999), Baskerville (2003), Hofstede (2003) and Baskerville-Morley (2005).

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An important aspect of businesses organizations in emerging economies, such as Russia, is the development of

innovation to enable domestic firms to compete effectively within more open markets and to develop products for export

(Agapitova, 2003). Given this change to more competitive markets, Russian firms are faced with decisions on the most

appropriate strategies to develop innovation and competitive advantage. Generally, in Western economies, developing and

marketing differentiated products is associated with innovation, while competing with existing products in established

markets involves a positional approach where firms continue to do what they have been doing (Nystrom, 1990; Porter,

1985). Recent research suggests that the type of strategy developed by firms influences the extent to which managers will

use different types of MACS (Langfield-Smith, 1997, 2006). Differentiation strategies tend to encourage managers to

adopt organic controls to ensure rich information and a flexible approach, while formal controls are required to ensure that

strategies which are unlikely to be profitable are identified by way of formal financial analysis. Strategies involving less

differentiation tend to rely more on formal controls with less need for information richness and flexibility.

Recent research has indicated that both formal MACS and more open, organic decision processes can assist in

developing innovation (Chenhall, 1995, Simons, 1995; 2000; Henri, 2006; 547).2 Consequently, developing organic

controls together with formal controls is often seen as a critical challenge to ensuring innovation (Amabile, 1983; Quinn,

1980; Quinn & Cameron, 1984; Simon, 1995). As Russian firms face increasingly competitive markets, differentiation

strategy, with its inherent entrepreneurialism, would seem to be important to develop competitive advantage with

consequent positive affects on innovation (Hagedoorn, 1996; Hebert & Link, 2006). As such the role of organic and

formal controls would appear particularly pertinent to understanding how Russian firms develop competitive advantage.

2 Formal management accounting controls and organic decision processes are somewhat similar to the distinction between diagnostic and interactive controls, respectively. However, while the predicted outcomes of the parallel constructs may be theoretically similar there are differences in their constitutive meanings. Diagnostic and interactive controls refers to different types of uses of management accounting practices. Diagnostic use refers to the traditional feedback role of management accounting to monitor and provide feedback for corrective action; while interactive use employees accounting practice as a vehicle to engage superiors and subordinates in face to face interaction around issues of concern to the business (Bisbe et al, 2007; Simons, 1995). The construct formal management controls, as used in this paper, refers to the use of traditional and contemporary formal management accounting practices; while organic controls refers to controls other than formal management accounting practices that involve issues such as the free flow of information, easy access to senior managers, informal signalling, a culture that encourage the development of ideas and fast reaction to unexpected opportunities (Chenhall & Morris, 1995).

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While the adoption of MACS within Russian firms has been growing in recent years (Taylor and Osipenkova,

2003), this has been within an administrative climate that has relied on the practice of Blat. Blat is a system of

networking, embedded within Russian culture, which relies on informal, personal contacts which, when employed in

business, provides the potential to gain competitive advantage (Barnes et al, 1997). Blat has been practiced for centuries

in Russia and it still has deep roots in Russian culture and the economy. During the decades of a centrally planned

economy Blat was an unavoidable necessity and although a more lawful and institutional environment has developed in

Russia, informal contacts have not lost their significance. Blat is built into the Russian hierarchical social structures and is

especially relevant in dealings with tax authorities, customs offices, banks, and regional administration and is still

important in doing business, more generally (e.g. Barnes et al., 1997; Edwards & Lawrence, 2000; Michailova & Worm,

2003).

Thus in comparison to Western firms, Russian business entities seeking to develop differentiated strategies as a

means to improve innovation and performance are faced with the task of employing potentially useful organic and formal

MACS within cultures based on more informal processes derived from personal connections that are more consistent with

organic and informal controls. In contrast, Western firms, more typically, are faced with considerable challenges in

developing informal, organic processes within formal hierarchies and control mechanisms.

We distinguish Blat as being in two forms in contemporary Russia (Michailova and Worm 2003): traditional

that provides for informal networking based on trust and long-term personal relationships, and modern Blat

utilizing uni-directional power and domination within the networks. The approach we take in this paper is to examine the

associations between each type of Blat, strategies of differentiation, use of organic and formal controls, innovation and

performance. Of interest is the way in which organic and formal controls intervene in the association between

innovation and performance; and between differentiation and both innovation and performance. Also, this approach

allows us to examine the extent to which both forms of Blat and differentiation act as antecedents to formal and informal

controls. Figure 1 presents the model used to direct the research.

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Our empirical analyses are based on survey data drawn from 100 Russian firms. We find the following key

relationships from the analysis. The data indicate that there are significant correlations between Blat and the studied

outcomes. Traditional Blat is positively correlated with differentiation, organic controls and innovation and performance;

and modern Blat is negatively correlated with differentiation, organic controls and performance. Concerning traditional

Blat, the results of the path model that is reported in Figure 2, indicates that differentiation and organic controls act as

intervening variables mediating the positive correlation between traditional Blat and innovation. Formal controls are

implicated in that traditional Blat is associated with differentiation which is linked to formal controls which, in turn, is

associated with innovation. Similar paths are apparent that explain the correlation between Traditional

performance, although links with formal controls are not apparent. For modern Blat, a lack of use of organic controls

mediates the negative correlation between modern Blat and performance; while differentiation mediates by way of a

negative path from modern Blat to differentiation and then from differentiation to organic controls, which, as indicated

above, is associated with performance. Concerning the outcomes of MACS, within the path model, organic controls are

associated with innovation and performance, while formal controls are associated with innovation, only. Innovation is not

associated with performance.

We divide the remainder of the paper into five sections. In the next section we review the relevant literature and

develop our hypotheses. This is followed by a description of the research design and the results of preliminary data

analyses. Next, we report the empirical results. This is followed by a discussion of results, with a final section providing

concluding remarks.

Theory and hypotheses development

In this section, we first describe the traditional Russian social networking system referred to as Blat.

explain how, in post-communist Russia some businesses have employed a modern form of Blat that has lost its warm,

human face and has changed its form becoming more materialized. We then develop a path model where we present

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hypotheses that specify the relationships between traditional and modern versions of Blat and performance and

innovation. We then consider the influence of strategic differentiation on performance and innovation and how

influence the strategies. Next, we examine the association between differentiation and the use of formal and organic

management accounting controls, and between Blat and organic and formal controls. Then we consider the relationship

between organic and formal controls and both innovation and performance. Finally, we argue that traditional

negatively associated with modern Blat; and that innovation is positively associated with performance. Figure 1

summarizes the proposed model.

The meaning of traditional Blat

In Russia, a social networking system known as Blat has been practiced for centuries and it remains highly relevant

today. During the decades of the centrally planned economy, Blat was an exchange of ‘favor of access’ in conditions of

shortages where the favor of access was provided at public expense (Ledeneva, 1998; Puffer et al., 1994). Blat

needs of personal consumption and was characterized by mutual care and friendly support by persons involved.

routinely practiced by almost everybody, often being confused with obligations of friendship (Ledeneva, 1998

in order to meet the demands of the command economy, firms obtained resources to implement their official plans

through informal channels of tolkachi. Tolkachi were individuals (‘pushers’) responsible for producing supplies, obtaining

a reduction in the targets and speeding up the delivery of supplies to ensure that the planned targets were achieved

(Ledeneva, 1998). Essentially, the acceptance of Blat was a critical part of the operation of tolkachis. In contemporary

Russia, informal contacts and close personal relationships based on Blat have not lost their significance.

deeply into Russian hierarchical social structures and it is still used in all areas of society including political and business

communities.

Personal networking is an important facet of many social and individual interactions in Western societies. However,

traditional Russian Blat networking differs from personal networking as exercised in Western countries in many

important respects (Barnes et al., 1997; Chamiah & Hollinshead, 2003; Michailova & Worm, 2003; Puffer & McCarthy,

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1995). While traditional Blat is a somewhat imprecise construct we define it based on the observed characteristics of

as they have evolved over the years (see Butler & Purchase, 2004 for an overview). First, personal relationships within

Blat are largely based on collectivism, whereas the Western type of networking is based primarily on individualism.

Second, Blat involves mediated exchanges that exist not only within one’s own network but also between the

network of members. Therefore, obligatory relations may extend to people whom one does not know directly, or will

never meet. This feature of Blat considerably expands Blat networks and increases their importance in the society. The

Western type of networking is typically based on dyadic relationships, where there are no third parties involved in

exchanges between the two parties. Third, an immediate return is not assumed in Blat relationship, but parties involved in

the network accept a time lag that allows them to be owed a favor for later use and reciprocity is often disguised by the

intermediation of a third party. This creates the continuity of Blat relationships, which also further enhances the

importance and significance of Blat in society. Given these characteristics, Blat has a vital role in Russia being more

important than personal networking within Western countries (Michailova & Worm, 2003). In overview, traditional

is characterized by strong personal relationships that are based on collectivism, mediated exchanges of favors

continuity.

The meaning of modern Blat

Blat relationships are traditionally personal and based on trust, but a different form of Blat has developed in more

recent times which is used in a negative, hostile way against other parties not belonging to Blat networks (Michailova &

Worm, 2003). Modern Blat is based on utilizing uni-directional power originating from networks. This negative form of

Blat has become prevalent since the end of the communist period. The approach to networking that takes place both

within modern Blat and with parties outside modern Blat networks has lost its warm, human face and has become

increasingly materialized and focused on gaining greater wealth for the business, even if this involves rule breaking and

unlawful action. Organizations employing modern Blat attempt to avoid playing a fair market game (Michailova and

Worm, 2003). Personal interests have become business interests, and in some instances Blat has become a negative word,

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at the extreme being related to criminal activities. Ledeneva (2000: 164) notes, ‘What used to be a matter of morals and

ethics based on modest norms of Soviet society and notions of kinship, friendship and other social ties, now – in the

transitional stage of “wild capitalism” – involves material and financial capital.’ Firms practicing modern Blat

to reduce their own cost of doing business and use existing products to penetrate markets in Russia, but do so by using

Blat even if this involves unethical behavior to further their own interests at the expense of others. This often translates to

situations where any ends justify the means (Levin & Satarov, 2000).

Modern Blat has its origins in the way the current Russian legal and societal environment has developed. This has

involved a situation in which the law and order of a communist regime no longer exists and that based on Western norms

has not yet fully developed (Puffer et al., 1994). Modern Blat is reinforced in a context where people are not sure that they

are subject to or protected by the law (Michailova and Worm, 2003). This type of networking can create new forms of

dependency and abuses of political and economic power, it can increase corruption and undermine the development of an

open market economy (Bloom et al., 1998; Edwards and Lawrence, 2000; Levin and Satarov, 2000; Michailova and

Worm, 2003).

In sum, the essential aspects of modern Blat are: 1) firms try to hinder competition by not following the rules, laws

and business ethics typically found in market economies, 2) firms do not keep fair and honest relationships with their

business parties, rather they will take advantage of their business partners by any means possible; and 3) firms find it

acceptable to manipulate their financial reports and other information so they do not give a true and fair view

operations

Relationship between traditional Blat and the performance of the firm

Blat has been important in conducting business in Russia, facilitating the development of external relationships

with suppliers and customers in ways that aim to supplant arms length, market-based transactions and provide advantage

in dealings with official bodies. Blat provides the basis to develop trusting relationships with business partners and to

share ideas for mutual advantage. Michailova & Worm (2003) points out that Blat is a phenomenon anchored at the

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individual level, but becomes an important asset at the organizational level as personal relations are dedicated and used by

organizations. In addition, many inter-organizational networks are built on Blat-based personal relationships, most of

which persist for a long time, in many cases extending over a lifetime or beyond. These continuous and long-term

oriented relationships allow the transfer and assimilation of tacit knowledge. Individuals are not managers or

representatives of their institutions, but are primarily friends, relatives, or persons of unique personal importance with

special claims on emotional involvement.

Traditional Blat networking has a role to play in current Russian, post-communist conditions because of the

immature political system and nonexistent or poorly functioning societal mechanisms (Michailova & Worm, 2003). There

are numerous examples of how Russian firms use Blat networking in their business. For instance, Blat is important when

starting a new business, attempting to run a business more efficiently, gaining access to important customers or

technological advancements, when gaining preferential bank financing or special terms in contracts (Puffer & McCarthy,

1997; Ledeneva, 1998; Agapitova, 2003). Personal networking is also advantageous in connections with public

authorities. To illustrate, personal negotiations between taxpayers and tax officers is a norm in the local routine of taxation

(Busse, 2000). Instead of being determined by universal or transparent law, the local taxation system works to a great

extent through informal agreements. It is based on a variation of a traditional Soviet phenomenon based on the

personalization of bureaucratic structures. Blat networking, in its traditional form, has been an efficient way of getting

things done and gaining advantage within the Russian economy.

While traditional Blat is a common practice in Russia, not all Russian firms have similar access to Blat

(Ledeneva, 1998). Firms having more effective Blat networks can utilize their contacts to achieve preferential treatment

in business and official dealings, as opposed to firms having less well developed Blat connections. Firms with

connections will have an advantage in social resourcing where a wide spread network will provide preferred treatment for

the Blat partners (Ledeneva, 1998: 37). Blat networks provide for continuity of relationships where individuals support

each other over the long-term, including providing opportunities to improve the business and provide access to necessary

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resources, particularly in times of shortages (Butler & Purchase, 2004). Blat has been identified with gaining control over

markets by sharing information about trading partners, and to create a shield from purely arms length transactions

(Hendley et al 2000; Hunter, 2003).

There is limited direct empirical evidence on how Blat type networking improves the performance of the firm, but

some studies have explored how a similar type of strong social networking system works in the transitional economy of

China. A Chinese social networking system known as Quanxi has been shown to affect business entity performance (Luo

& Chen, 1997; Tsang, 1998; Park & Luo, 2001; Peng & Luo, 2000). These studies report that Quanxi has a significant

positive effect on financial outcomes (Luo & Chen, 1997) and competitive advantages (Tsang, 1998) of firms. Peng &

Luo (2000) report that the greater the extent of interpersonal ties that top managers of Chinese firms have with managers

of other firms and with government officials, the better is the performance of their firms. Also, Park & Luo (2001) argue

that organizations employing Quanxi have higher performance but this is restricted to the areas of sales growth, market

expansion and competitive positioning. Based on the foregoing literature, we hypothesize that firms having better access

to the personal networks of traditional Blat will achieve superior performance compared to Russian firms having fewer

traditional Blat connections:

Hypothesis 1a. More extensive use of traditional Blat is positively related to the performance of the firm.

Relationship between traditional Blat and innovations of the firm

The ability of firms to absorb, generate and apply knowledge to innovations is strongly influenced by the social and

institutional context within which they operate (Agapitova 2003). Innovative firms can be seen as functioning within a

complex network of co-operating and competing firms and other institutions, whose interactions initiate, import and

modify new technologies (Freeman, 1995; Nelson 1993). This view is supported by the notion that firms need outside

sources of cognition and competence to complement their own (Noteboom 1999). Empirical evidence on how networks

between organizations boost innovations is provided by Goes & Park (1997) and Pennings & Harianto (1992) who report

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that innovative capability and the adoption of innovations within organizations is strongly enhanced by inter-

organizational network links.

Support for the role of networks in enhancing innovation can be dated back to the seminal theory of economic

development as formulated by Schumpeter (1934). This theory focused on how both innovations and the sociological

framework in which innovations spread across firms are important factors generating economic development. Since then

much research effort has been devoted to conceptualizing and refining this theory. For instance, Aghion and Howitt

(1998) describe the concept of social learning in economic development as follows: '[t]he way a firm typically learns to

use a new technology is not to discover everything on its own but to learn from experiences of other firms in a similar

situation'. This view highlights the importance of inter-firm relations in generating new innovations and translating them

into good performance. In Russia, traditional Blat networking plays a crucial role in these inter-firm relations.

Network literature emphasizes the role of different networks patterns in innovation creation, and has suggested

different types of innovative networks (Powell and Smith-Doerr, 1994; Agapitova 2003). Agapitova (2003) maintains that

traditional networks, such as Russian Blat and Chinese Quanxi, are examples of networks based on social capital that

supports the process of learning through interaction. The quality of the social processes and relationships within which

learning interactions take place especially influence the quality of the learning outcomes. Supporting this view,

Agapitova’s (2003) results of analyzing the innovation process of Russian firms through case and survey studies indicate

that traditional Blat networking has an important impact on technological change and innovative activities of firms. More

importantly, she reports that since Blat networks partly replace formal innovative networks, such as alliances and

collaborative agreements, they often play an essential role in initiating innovative interactions in Russia. In sum, it can be

argued that traditional Blat networks help firms to share information and therefore create innovations within the

network. Consequently, firms that are well positioned in Blat networks have an advantage in generating product

innovations. This leads us to the following hypothesis:

Hypothesis 1b. More extensive use of the traditional Blat is positively related to product innovations of the firm

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Relationship between modern Blat and the performance of the firm

The potential for modern Blat to help managers create innovations and enhance profitability depends on the extent to

which the Russian economic and legal environment will tolerate modern Blat relationships. At early stages of the post-

communist economy Russia began to move from a command economy to one based on competitive markets and

corporate law. In such circumstances, modern Blat was employed by some Russian firms in an attempt to avoid market

and legal constraints and gain advantage from reliance on more extreme values embedded in the communist way of doing

business, such as reliance on power, operating outside the law and, in some instances, nurturing corruption.

with increasing competition and legal restraints in Russia, the practice of modern Blat may not be sustainable or be useful

in creating business advantage. Practicing modern Blat may increase firms short-term profits by exploiting their business

partners, but as customers and suppliers recognize this behaviour they may choose to trade with others not involved in

modern Blat networks. Modern Blat firms may loose their customers, and their ability to control prices and material costs.

Consequently, these firms may not gain competitive advantage or outperform other firms. The discussion above leads to

the following hypothesis regarding the relationship between modern Blat and performance.

Hypothesis 2a. More extensive use of the modern Blat is negatively related to the performance of the firm.

Relationship between modern Blat and innovations of the firm

While traditional Blat networks are based on generating social capital that support the process of learning through

interactions therefore creating innovations, modern Blat is likely to have an opposite effect on the creation of innovations.

Firms exercising modern Blat do not rely on interactive social networks based on trust, but they utilize uni-directional

power originating from modern Blat networks. Modern Blat does not encourage firms to trust their business parties and to

openly share information, both of which are essential for networks that develop new ideas and create innovations.

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Essentially, modern Blat prevents open access to information (Michailova and Worm, 2003). Therefore, we hypothesize

that modern Blat has a negative effect on innovations:

Hypothesis 2b. More extensive use of the Modern Blat is negatively related to product innovations of the firm.

Relationships between differentiation strategies and, innovation and performance

In Russia, during the period of the command economy, the diversity and quality of products and services was low

compared to Western firms. A lack of raw materials and other resources during the last years of the communist regime

yielded significant difficulties in all production. Consequently, there were general shortages of products and materials.

After the breakdown of the communist regime, Russia rapidly developed towards a market-based economy. Product

markets were opened to free competition and foreign competitors were allowed to enter the Russian market. While, it is

apparent that changing from a command to a market-economy involves a long transitional process, Russia has taken many

important steps to develop a market-orientation and to increase competition in its economy and to provide a fair corporate

legal system. For instance, administrative bureaucracy has been reduced and legislation has been developed to help new-

start businesses and to attract foreign investors. The cost of starting a new business (measured as percentage of income

per capita) declined from five percent in 2005 to 2.7 percent in 2006 (World Bank, 2006). The amount of foreign direct

investments in Russia increased from US$ 4.260 million in 2000 to US$ 13.072 million in 2005 (Federal State Statistics

Service of Russian Federation, 2006). The most difficult obstacles for Russia to join the World Trade Organization have

been resolved, and it is commonly believed that Russia will soon join this organization

The economic progress described above has increased the need for Russian firms to match their business strategies to

the new business environment. Products and services that were sufficient in the command economy do not meet the

standards required in the emerging market economy. In order to develop products to provide a competitive edge and

thereby enhance performance, firms now have to distinguish their products and services from the more standard offerings

that were produced during the prior period of the old system. In other words, Russian firms now face a situation in which

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developing diversity in product offerings will allow them to be seen as innovative, competitive leaders and to be able to

compete with foreign firms.

Theories on the effects of differentiation on innovation can be found in the area of economic development, where

the activities of entrepreneurial differentiators are seen to lead to innovation (Schumpeter, 1934; Hogedoorn, 1996).

Similarly, work in industrial economics and strategy notes that differentiation enhances innovative capacity (Porter, 1985;

Ireland et al, 2001: Danneels, 2002). Concerning links between differentiation and performance, theories in economics

and finance, with assumptions of perfect markets, claim that differentiation does not enhance performance (Smith &

Weston, 1977; Teece, 1982), rather there may be industry and market concentration effects (Chritensen & Montgomery,

1981). Strategy literature, with assumptions of strategic choice and market imperfections, tends to argue for links

between differentiation and performance, although the causes can be varied (e.g. risk reduction, market contraction for

existing products, use of excess capacity or resources, anti trust restrictions).3 Differentiation can provide for a market

orientation as firms identify and satisfy customer’s latent needs (Slater & Narver, 1999), which then provides the basis to

create superior value for customers and enhanced performance (Narever & Slater, 1990).

In Russia, imperfect emerging markets would appear to provide a context within which the benefits from

differentiation and a customer value perspective to a particular business are likely to be ‘private and unique’ and

‘inimitable’ and, as such, provide opportunities to enhance performance, at least for a short period of time (Barney, 1991).

Overall, these benefits from differentiation may provide a basis to gain superior customer value and enhanced

performance (Porter, 1985; Govindarajan, 1988; Slaver & Narver, 1990). The following hypothesis summarizes the

relationship between differentiation strategies and the outcomes of innovation and performance:

Hypothesis 3. In Russian firms the strategy of differentiation is positively related to:

3a) innovation, and 3b) performance.

3 See Hoskinson & Hitt (1990) for a review of the association between differentiation and performance from different theoretical perspectives.

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The role of Blat and differentiation strategies

One of the main functions of traditional Blat has always been to provide firms with networks that can impart preferred

treatment in the supply of resources and the sharing of ideas for advantage within the network. (Ledeneva, 1998). Firms

that maintain strong traditional Blat networks will have relatively well-developed networks that should provide

possibilities to gain market and technological ideas that can be employed to differentiate their strategies. However,

modern Blat is likely to have a different influence on differentiation strategy. This follows because firms practicing

modern Blat aim to prevent free competition and open access to information (Michailova and Worm, 2003), with the aim

of limiting the opportunities for competitors to enter their targeted markets (Barnes et al., 1997). Consequently, modern

Blat firms have less need to follow differentiation strategies to be competitive and to achieve targeted performance.

Instead, they tend to promote existing products using their power and influence to lower labor and material costs. In

summary, firms employing modern Blat are likely to be focused on promoting existing products, perhaps focusing on cost

reduction. It is also possible that these firms will pay little attention to formally developing either differentiation or low

cost strategies as they attempt to use coercion to market their product. The following hypotheses specify the relationship

between traditional and modern Blat and differentiation strategy:

Hypothesis 4a: More extensive use of the traditional Blat is positively related to the strategy of differentiation .

Hypothesis 4b: More extensive use of the modern Blat is negatively related to the strategy of differentiation.

Relationships between differentiation strategies and the use of organic and formal controls.

There has been considerable research examining the role of strategy as an antecedent to MACS in Western firms

(Langfield-Smith, 1997; 2006). There is a body of research that has found that organizations employing more

differentiated strategies tend to deemphasize formal budgetary goals for performance evaluation (Govindarajan, 1988),

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rigid budgetary controls (Van der Steede, 2000), and employ more open, interactive, organic controls (Chenhall & Morris,

1995; Dent, 1990; Guilding, 1999; Simons, 1987). However, some research has shown that in addition to organic

controls, firms with more differentiated strategies also use more formal controls to identify potentially unprofitable areas

of business (Ahrens and Chapman, 2004; Chenhall & Morris, 1995, Henri, 2006; Simons, 1987).

In Russia, it may be expected that firms developing differentiation strategies will generate the circumstances where

their markets become more diverse, competitive and complex which creates a need for richer and more timely

information that can be provided by organic controls. Following from evidence on Western firms it may be expected that

more formal controls will also be pertinent to understanding which strategies are likely to be financially viable. We

examine if the relationships identified in Western firms between differentiation strategies and MACS are apparent in

Russia by proposing the following hypotheses

Hypothesis 5: In Russian firms the strategy of differentiation is positively related to:

5a) organic controls, and 5b) formal controls.

Relationship between traditional Blat and organic controls

Our next hypothesis examines how traditional Blat affects the use of organic controls in Russian firms. The role of

traditional Blat as an antecedent to organic controls follows from the notion that traditional Blat is based on reciprocal

social networks. Firms employing traditional Blat have well entrenched practices involving informal communication and

decision processes upon which to develop more organic controls. For instance, Ledeneva (1998) describes how traditional

Blat networks play an important role when firms are recruiting employees. Firms do not recruit ‘outsiders’, those who do

not belong to existing employees’ Blat networks, as they want employees to work not only under official administrative

directions but also under the social norms of the firm. In other words, traditional Blat networks establish informal links

within the firm, which creates a basis to develop and employ organic controls.

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Given the characteristics of traditional Blat, the use of informal controls is a natural way of operating for firms

that are involved in the informal social networks of traditional Blat. Traditional Blat encourages trust between parties,

information sharing and non-authoritarian operating policy, which are important aspects of organic controls. This view is

also supported by Michailova & Hutchings (2006) who maintain that social relations built on trust within the in-group and

vertical collectivism results in intensive knowledge sharing among in-group members in Russian organizations. In sum,

we hypothesize that traditional Blat and organic controls are complementary and as such there is a positive association

between traditional Blat and the use of organic controls:

Hypothesis 6a: More extensive use of traditional Blat is positively related to the use of organic control.

Relationship between traditional Blat and formal controls

Much of the traditional organizational and strategy literature suggests that formal controls are not suitable for high

performing organizations as they inhibit flexible responses and focus on the short-term (Burns & Stalker, 1961;

Mintzberg, 1994; Quinn, 1980). This literature argues that more open structures and systems are needed for high

performance, particularly for firms facing high uncertainty (Burns and Stalker, 1961, Mintzberg, 1995; Quinn, 1980).

Recently, some management accounting research has noted that open structures and systems are required as a response to

uncertainty but more formal systems are needed to ensure that the commercial or resource implications of responses to

uncertainties are identified (Chenhall, 1995; Simons, 1995; 2000). In Russia, firms that rely on traditional Blat

have highly open communications and decision processes, compared to firms without extensive Blat networking. It is the

firms with a high emphasis on Blat networking that have a need to achieve a balance between the benefits of informal

Blat networks and the commercial requirements set by the modern business environment. For instance, in

networking, prices in a given transaction between firms that belong to the same traditional Blat circle are not necessarily

true market prices, because the prices can be settled by using favors or other non-monetary paybacks (e.g. Michailova,

18

2000). Moreover, the cooperation embedded in longstanding Blat transactions are highly valued even if this involves

noncommercial interactions.

Given the complexity of Blat networks (e.g. mediated exchanges of favors, a focus on continuity), firms using

traditional Blat are likely to be involved in a complex system involving numerous non-commercial, business transactions

with many of their business partners. At the same time, an increased emphasis on market-based business practices forces

these firms to pay attention to factors affecting their performance that originate from outside their Blat networks (e.g.

pricing, costing, competition from non Blat firms, including international competition.). In other words, firms extensively

using traditional Blat need formal controls to counter the potential for Blat arrangements to be uneconomic when

positioned within the wider commercial market. Formal controls can help ensure that managers understand the

commercial implications of using Blat arrangements and that they can make any adjustments to ensure that business

practices do translate to enhanced performance. In summary, in contemporary Russia with increasingly competitive

markets, the more a given firm is using traditional Blat, the more it will be likely to use formal controls to ensure that it

understands the costs and benefits of Blat arrangements and the consequent effects on performance. The following

hypothesis summarizes the relationship between formal controls and performance for firms exercising traditional

Hypothesis 6b. More extensive use of traditional Blat is positively related to the use of formal controls.

Relationship between modern Blat and organic controls

Given the nature of modern Blat, it seems unlikely that firms would use organic controls. In fact, many of the

characteristics of modern Blat are opposite to those of firms that are likely to use organic controls. Modern

based on trust and it prevents the free flow of information, within and outside the organization, both of which are

important to developing organic controls. Modern Blat does not encourage firms to employ non-authoritarian operating

policy nor is it consensus-seeking. In sum, we propose the following hypothesis regarding the relationship between

modern Blat and the use organic controls:

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Hypothesis 7a. More extensive use of modern Blat is negatively related to the use of organic controls

Relationship between modern Blat and formal controls

Traditional and modern Blat should have a different influence on the use of formal controls, because firms

practicing modern Blat position themselves differently from traditional Blat firms. Modern Blat firms aim to prevent free

competition and open access to information (Michailova and Worm, 2003). As a result, modern Blat firms aim to develop

a form of monopoly power, because their competitors have fewer opportunities to enter their targeted markets (Barnes et

al., 1997). The smaller the competition, the smaller the need to control costs, and to evaluate whether production,

marketing, finance and other functions of the firm are operating in highly efficient ways. Establishing formal controls is

costly, and if the firm does not gain from using these systems, it will not implement them. This implies that Russian firms

practicing modern Blat are unlikely to use formal MACS. The following hypothesis specifies the relationship between

modern Blat and formal management controls:

Hypothesis 7b. More extensive use of modern Blat is negatively related to the use of formal controls.

Relationships between organic and formal controls and outcomes of innovation and performance

There is a body of research reporting that certain types of MACS are positively related to innovations and subsequent

performance in Western countries (e.g. Bisbe & Otley, 2004; Chenhall, 1995; Henri, 2006; Simons, 1995, 2000), but to

our knowledge, there is no published evidence on this in Russia. Taylor and Osipenkova (2003) maintain that despite the

fact that developing MACS in Russian firms involves challenging obstacles, there is an increasing level of adoption of

various management accounting techniques like variance analysis, budgeting and more contemporary practices such as

activity-based costing.

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Regarding other emerging countries such as China or India, a number of published studies have investigated the

extent to which MACS that are employed in the West are adopted in these countries (e.g. O’Connor et al., 2004; Firth,

1996; Anderson and Lanen, 1999). Especially, evidence from China is pertinent to our study. Both Russia and China are

large economies that are moving towards free market economies and within China the practice of Quanxi

similar to Blat. For example, O’Connor et al. (2004) find that Chinese state-owned enterprises use Western MACS, and

that all of the MACS have moved towards greater formalization and explicitness. Firth (1996) reports that Chinese firms,

particularly those that participated in foreign partnered joint ventures, made changes to their MACS supporting the

hypothesis that sudden shocks to the economic system acts as a stimulus to the diffusion of accounting ideas.

In management accounting, some recent research related to Western countries, has indicated that the use of both

formal and organic controls can lead to increased innovations (Ahrens and Chapman, 2004; Chenhall, 2005; Henri, 2006;

Simons, 1995, 2000). The association between organic controls and innovation has been argued for some time (Burns &

Stalker, 1961; Mintzberg & Waters, 1985). This follows as informal controls provide the basis for the free flow of

information, interactive decision making with the possibility of sensitizing employees throughout the firm to the

possibility of identifying emerging adaptive innovations (Simons, 1995). Also, formal controls may be useful in providing

a platform for innovation. Haas & Kleingeld (1999) argue that formal controls can act as a base upon which to instigate

more organic controls. Formal controls can be used for motivating innovative effort by developing reward systems

targeted on managers’ effectiveness in generating innovation. Formal systems can help identify potential areas of the

business that are likely to require more innovative effort though techniques such as SWOT analysis and examining

internal capabilities (Chakravarthy & Lorange, 1999).

The arguments that formal and organic controls can assist in improving performance center on the role of formal

controls to assist managers develop a rational approach to planning and control while organic controls provide scope to

ensure sufficient flexibility in decision making and communications to be adaptive to changing circumstances (Quinn,

1980; Mintzberg, 1994). Profitable operations require that business processes are adequately controlled by employing

21

both formal controls to improve efficiency while organic controls are required to ensure that the firm is sufficiently

flexible to respond quickly to on going challenges (Chenhall, 1995; Minzberg, 1995; Simons, 1995, 2000).

While links between the use of formal and organic controls and innovation and performance have been argued, and

there is some supporting evidence for firms operating in Western economies, it is unclear whether this will occur in

Russian. We therefore propose, tentatively, that those Russian firms employing formal and organic controls will have

enhanced innovations and performance. This leads us to the following hypotheses that related formal and informal

controls to both innovation and performance:

Hypothesis 8. In Russian firms more extensive use of organic controls is positively related to: 8a) innovation, and 8b)

performance.

Hypothesis 9. In Russian firms more extensive use of use of formal controls is positively related to: 9a) innovation, and

9b) performance.

Relationship between traditional and modern Blat

Our next hypothesis defines the relation between traditional Blat and modern Blat. The literature discussed above

argues that firms relying on modern Blat have characteristics that differ from those that employ traditional

traditional and modern Blat represent different ways of doing business, and it seems probable that a given firm has to

choose between these policies. It seems unlikely that a firm using friendly, social networks when running its business will

also employ hostile means to take advantage of its business associates. Formally stated:

Hypothesis 10. More extensive use of traditional Blat is negatively related to more extensive of modern Blat.

Relationship between innovations and performance

22

Finally, our last hypothesis defines the relation between innovation and performance of Russian in Innovation is

defined as the adoption of an idea or behavior that is new to the adopting organization (Zaltman et al, 1973). In this study,

product innovation is examined. Product innovation is a form of technical innovation, as opposed to administrative

innovations, and is often perceived as being more closely related to solving an organization’s need to be more

competitive; and tend to be more visible and adopted more widely. Whereas administrative innovations are more

complex to implement and less advantageous (Damanpour, 1990: 127). At an organizational level, innovation has been

identified as necessary for organizations to remain competitive (Amabile, 1996; Kanter, 1984; Kimberly, 1981; Simons,

2000).

While studies on the link between innovation and organizational performance have been equivocal, the theory of

employing innovation to close performance gaps is particularly compelling in Russia. In the Russian economy, increased

competition presents on-going pressure for firms’ products to become obsolete and for the firm to be continually

searching for innovations to increase their competitiveness. Product innovation is a way of changing the organization so it

can adapt to its environment, become more competitive and enhance its performance. We predict a significant relationship

between Russian firms with high level of product innovation and high performance.

Hypothesis 11. In Russian firms, a high level of innovation is positively related to performance.

Research design

Sample

Data were collected by a survey questionnaire administered to 100 Chief Executive Officers drawn from

Russian industrial firms in the St Petersburg region. The companies were from a random sample of 476 independent

companies selected from the INFOWAVE data base. Chief executives were contacted by telephone to seek their

participation in the study and 100 agreed to participate in the study providing a 21 percent response rate. The survey data

23

were collected by interviewing the Chief Executives at their place of work. To investigate for non-response bias the

earliest and latest 20 responses were compared to test if responses to construct measures differed between the two groups.

For each item, levels of significance were determined using t-tests. There were no significant differences providing some

evidence for absence of non-response bias. The respondents appeared to represent the broader sample frame with no

significant differences (chi-squared at p<0.01) in industry between responding and non-responding firms. The survey data

were collected by interviewing the Chief Executives at their place of work. Table 1 provides information on the size and

industry of the sample firms.

(Insert Table 1 about here)

Measures

For variables used in our study we assume reflective measurement models and accept that for each variable there

are underlying, latent constructs that are reflected in a series of manifestations, and as such the constructs can be defined

by a sample of some of these interchangeable manifestations.4 The questionnaire used existing instruments where

possible.5 These were use of formal and organic controls (Chenhall and Morris, 1995; Khandwalla 1972), strategies of

differentiation (Govindarajan, 1984; 1988), product innovation (Capon et al,1992; Scott and Tiessen, 1999; Thomson

and Abernethy, 1998; Bisbe and Otley, 2004) and performance (Govindarajan 1984, 1988). Items used to measure the

use of formal controls in Russia were the use of accounting practices such as standard costs, budgeting, processes

controls, formal financial decision tools and systematic evaluations of personnel. Organic controls included items that

cover more open communication such as informal access to managers, an emphasis on consensus and tolerance of

4 For a discussion of the distinction between reflective and formative indicators see Bisbe et al (2007). We note that it is not always clear whether business and MACS variables are reflective or formative, however, we feel that the variables in this study exist at a deeper conceptual level than their manifestations and as such can be treated as reflective.

5 It is assumed that items derived from Western practices are relevant in Russia as it is these practices that are being imported for use (Taylor and Osipenkova, 2003)

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mistakes. Differentiation strategy was measured by asking managers the position of their firm’s products relative to

those of leading competitors in a selection of areas that provide for differentiation. Product innovation was measured as

developing and launching of products which are unique or distinctive from existing products in comparison with the

industry average. The measure of performance captures both financial and customer performance of the firm in

comparison with the industry average.

Given the novelty of the Blat construct to survey-based research a new instrument was designed for this study.

This involved the construction of items based on the theoretical nature of the constructs, as they exist within

contemporary Russia, (see the discussion of the meaning of Blat in an earlier section). This was followed by a review

process involving discussions with seven Russian speaking academics and managers. Most of these showed the

questionnaire to other persons in their organizations to get feedback.

The items, provided in the appendix, that reflect the construct of traditional Blat are: strong personal relationships

(items 1.1 and 1.6), collectivism (items 1.2, 1.3 and 1.4), mediated exchanges of favors (items 1.7 and 1.8) and continuity

(item 1.5). Similarly, modern Blat is measured by items related to its characteristics reported in earlier literature as

discussed in a previous section. These items include: the firm attempts to hinder competition (items 2.2 and 2.5); the firms

tends not to keep fair and honest relationships with their business parties (items 2.3, 2.1, 2.4); and the firm discloses

financial reports that are not based on the principle of a true and fair view (item 2.6).6

For all instruments we used a seven-point Likert scale ranging from (1) ‘Not used at all/not important’ to (7) ‘Used

to a great extent/very important’. The respondents were asked to choose the alternative that best described the situation

in their firm. The final questionnaire was tested with a group of chief accountants, financial directors and academic

colleagues to refine the design and focus the content. The appendix provides the details of the questions used to measure

constructs in the study.

6 Questions related to the modern blat are worded such that small values of the items indicate high degree of modern blat, and, therefore, we use negations of these items in empirical analyses.

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Given the exploratory nature of the current study, a two-step approach was taken to assess the validity of constructs

which involved a preliminary analysis to examine the construct validity of multi-item variables and then re-examination

of construct validity within the PLS modelling. We use factor analysis, with oblique rotation, to explore the construct

validity of the measures of formal and organic controls, differentiation strategy, innovations and performance of the

firms. The constructs used in this study are considered to be reflective and as such unidimensionality and reliability tests

based on Classical Test Theory (factor analysis and internal reliability tests) are appropriate (Bisbe et al, 2007). Items

with less than 0.5 loadings were deleted from their respective constructs and the factor structure reexamined. The

deletion of items occurred for the constructs of formal controls, 3.4 (activity-based costing), 3.5 (internal audit) and 3.6

(performance or operating auditing by outside auditors); for organic controls , 4.2 (an emphasis on adaptation without

concern for past practice); traditional Blat, 1.8 (contacts who can push through whatever needs to be pushed)

Modern Blat, 2.1 (it is not acceptable for employees to reveal and emphasize negative information about competitors)

It appears that the development of formal controls in Russia has not evolved to where activity-based costing nor the

audit function are integral part of formal controls. For organic controls, in Russia, ‘adaptation without concern for past

practices’ is not a relevant aspect of these controls. For modern Blat, perhaps item 2.1 (employees revealing negative

information about competitors) had extreme negative connotations that go beyond the conceptual specification of

modern Blat. Table 2 reports the results of the factor analysis. For each construct, survey items loaded onto a single

factor.

(Insert Table 2 about here)

7 Further analysis of construct validity within the PLS model, reported in the next section, confirmed all construct loadings with the exception of traditional Blat item 1.8 which loaded satisfactorily on the construct. Consequently, this was included in the construct for further analysis. It should be noted that table 2 reports the second factor analysis that excludes traditional Blat item 1.8, however this item is included in the final measurement model.

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Table 3 reports descriptive statistics of the constructs based on the weighted average scores of multi-item variables.

Actual ranges of all constructs correspond well with their theoretical ranges indicating high dispersion in the values of

constructs.

(Insert Table 3 about here)

Results

This section describes the partial least squares (PLS) regression method used to test our theoretical model and reports

the empirical results.

Partial least squares regressions

In the empirical analyses, the multivariate statistical method, Partial Least Square (PLS) was used. PLS is used to

examine structural models and is particularly suited to small sample size studies when data contain several dependent

variables and a large set of independent variables (Wold, 1985). PLS searches for a set of components (called latent

vectors) that performs a simultaneous decomposition of the matrix of independent variables and the matrix of dependent

variables with the constraint that these components explain as much as possible of the covariance between the dependent

and independent variables. PLS provides the measurement model that specifies the relations between the original

variables and the constructs that they represent. It also provides estimates and diagnostics of the structural model that

specifies the relations among constructs

As described by Hulland (1999), a PLS model should be analyzed and interpreted by assessing the reliability and

validity of the measurement model and by assessing the resulting structural model. As indicated above construct validity

was assessed by a preliminary examination of factor loadings of the items within their respective constructs. Items that

had loadings of less than 0.50 were deleted. Within the measurement model, construct validity was confirmed with all

27

items loading in similar ways to that found in the preliminary factor analysis, except for item 3.3 (flexible or activity level

budgeting) which was below 0.50. This item was deleted from the final measurement of formal controls. Item 1.8 (contact

who can push through whatever needs to be pushed) loaded satisfactorily on the traditional Blat construct and was

included in the construct for further analysis. The internal reliability was assessed using the composite reliability statistic

which indicated high reliability with scores in excess of 0.80 for all constructs. These statistics are reported in table 2.

Fornell and Larcker (1981) suggest that the discriminant validity of the measurement model should be examined by

testing the extent to which a construct shares more variance with its own measures than it shares with other constructs.

For this purpose, we calculate the average variance extracted (AVE) and compare with the squared correlations between

constructs. To test the discriminant validity of the measurement model, we report the correlations between the constructs

in Table 5. Squared correlations between the constructs can be compared to the AVEs reported in Table 4. All squared

correlations based on the correlations reported in Table 5 are clearly below the AVEs reported in Table 4. This attests to

satisfactory discriminant validity of the measurement model.

(Insert Table 4 about here)

(Insert Table 5 about here)

Finally, the structural model specifying relations among the constructs is assessed by examining the estimated path

coefficients and their significance levels. It is inappropriate in PLS to use any overall goodness-of-fit measures, as used in

covariance structure analysis modeling such as LISREL, because PLS makes no distributional assumptions (Chin, 1998).

Rather, fit is evaluated by the overall incidence of significant relationships between constructs and the explained variance

of the endogenous variables. R2 values are reported in Table 4. The bootstrapping sampling method is used to obtain the

confidence intervals to assess the significance of the estimated path coefficients.

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Table 4 reports the PLS regression results, while figure 2 illustrates significant associations in the path model. Within

the path model, there are no significant paths between traditional Blat and performance (H1a) nor innovation (H1b).

traditional form of Blat is positively related to differentiation strategy (H4a). The modern form of Blat is negatively

related to innovation (H2b) but not to performance (H2a). Strategies of differentiation are associated with organic controls

(H5A) and formal controls (H5b). The use of both organic and formal management controls is positively related to

innovation (H8a, H9a), while organic controls are associated with performance (H8b) but formal controls are not (H9b).

In addition, traditional Blat is positively related to the use of organic controls (H6a) but not formal controls (H6b).

Modern Blat is negatively related to the use of organic controls (H7a) but not formal controls (H7b). Traditional

not associated with modern Blat (H10). Finally, differentiation is associated with innovation (H3a) and performance

(H3b); but innovation is not related to performance (H11).

Discussion

Our aim was to explore whether the unique Russian social networking system known as Blat affects the adoption of

strategies of differentiation, organic and formal controls, product innovations and subsequent performance. Particularly,

we were interested in the extent to which the use of formal and organic controls act as intervening variables in the

relationship between Blat, differentiation strategies and both innovation and performance. Given the past and current

changes in the Russian economic and societal environments, we identified two types of Blat, both of which do not exist in

other market economies (Michailova and Worm, 2003). Traditional Blat is a friendly networking system exercised

between individuals for centuries in Russia which is currently practiced within the business community. Modern business-

oriented was identified as a more hostile form of Blat which appears in some businesses within the current transitional

Russian business environment.

The results of correlational analysis, reported in table 5, indicate that Russian firms that are practicing traditional

more extensively are able to create higher levels of innovation than Russian firms having fewer Blat contacts (

p<0.05). This supports Agapitova’s (2003) results which showed that Russian firms with strong Blat networks have an

29

advantage in creating innovations. There was a significant positive correlation between firms employing traditional

and enhanced performance, (r=0.115, p<0.10).

Of importance to the current research is the role of strategies of differentiation and organic and formal controls as

intervening variables in the relationship between Blat and outcomes of innovation and performance. Figure 2 indicates

that the correlation between traditional Blat and innovation is fully mediated by the separate paths through differentiation

strategy and organic controls (Baron & Kenny, 1986). Additionally, as differentiation strategies act as an antecedent to

organic and formal controls, explanatory paths runs from traditional Blat to differentiation strategies and from

differentiation to both organic and formal controls and finally from both forms of controls to innovation. Similar paths

are apparent between traditional Blat and performance, with paths through organic controls and differentiation; and from

differentiation to organic controls and performance. Formal controls are not involved in these paths to performance,

because of the lack of a significant path between formal controls and performance.

We find that the correlation between firms extensively using the hostile form of modern Blat and performance is

negative (r = -0.32, p < 0.01), while the correlation with innovation is insignificant (r = 0.268, NS). This suggests that the

Russian economy is sufficiently competitive that firms practicing modern Blat, which involves coercive rather than

competitive business practices, are not able to compete as well as firms not relying on modern Blat. It would seem that

the opening of the Russian economy to more competitive pressures places these firms at a disadvantage to those not

prepared to adopt the more coercive style of networking characterized by modern Blat.

The negative correlation between modern Blat and performance is fully mediated by variables within the model.

Figure 2 indicates negative paths from modern Blat to differentiation strategy and then to performance; from modern

to organic controls and then performance; and modern Blat to differentiation, and then to organic controls and finally to

performance.

Regarding the importance of MACS in Russian business, within the path model both organic and formal controls

indicate significant direct paths with innovation, but only organic controls has a significant direct path with performance.

30

The strategy variable of differentiation has significant paths to organic and formal controls, indicating it is an antecedent

to both forms of controls. These findings are consistent with the view that Russian firms that employ strategic

differentiation generate business conditions that are typically diverse and uncertain and that managing this context induces

managers to employ both organic and formal controls (Ahrens and Chapman, 2004; Chenhall & Morris, 1995; Simons,

1995; 2000). The significant path from organic controls to performance but the lack of a significant path from formal

controls to performance raises issues as to the role of formal controls in Russian business. It is possible that formal

controls are used to formally scan the environment for opportunities and to identify internal capabilities for innovation. In

this way formal controls would be complementary to organic controls in assisting in the generating innovation. However,

they may not be used to formally assess the resource and productivity implications of innovation. More generally, they

may not have been used to assist in an analysis of the potential profitability of business operations aimed at innovation. It

would be of interest to identify if formal controls are used in Russian firms to reward and compensate managers. Without

links to compensation systems, the formal controls may not be effective in motivating managers to direct their energies at

profitable operations. Clearly, this is speculation as we know little about the way managers are motivated by controls

systems within Russian firms.

In the path model we find that traditional Blat has a significant positive path to the use of organic controls but not

formal controls. This is consistent with the view that organic controls have become complementary with traditional

That is, firms employing traditional Blat have well entrenched practices involving informal communication and decision

processes upon which to develop, readily, more organic controls. The path model indicates that the correlation between

traditional Blat and organic controls is partially mediated by strategic differentiation. Thus, while traditional

direct effect on organic controls, it also has an influence on organic controls by way of the path through differentiation to

organic controls. Both these paths suggest that traditional Blat, as practiced in contemporary Russian firms, is consistent

with an approach to management that provides flexibility, an open approach to information acquisition and strong

networking, all of which assist in generating competitive advantage by way of differentiation. This scenario provides a

31

situation within which organic controls can develop readily. Additionally, our results indicate a lack of association

between traditional Blat and formal controls. It is possible, that in Russia, formal controls are seen to be incompatible

with planning and control based on notions of informal contacts, close and long-standing personal relationships and trust

inherent in traditional Blat. It will be of interest to observe how Russian firms manage the potential tension between

networks found within traditional Blat and the possibility for formal controls to assist in profitability analysis and to be

used to help define networks and how they operate. For example, Mouritsen & Thrane (2006) argue that in Western

‘network organizations’ formal MACS can help in constructing inter-organisational relations through self-regulating and

orchestration mechanisms. Self-regulating mechanisms allow interaction and exchange to occur unobtrusively, while

orchestration mechanisms involve structuring these interactions.

We also find that there is a negative relation between modern Blat and the use of organic controls. Also,

differentiation strategies are implicated in an indirect negative path between modern Blat and organic controls. These

results are consistent with the lack of trust within modern Blat, which may prevent the free flow of information and

inhibit the development of more participative, open information and decision processes. Modern Blat is not associated

with formal controls. Michailova & Worm (2003) point out that the most negative consequence of modern

prevents free competition and open access to information. Consequently, modern Blat aims to provide its users with a

form of strong monopoly power. In these situations they attempt to avoid competition and many perceive that they do not

need careful financial planning and control to manage product development and implementation (Barnes et al., 1997).

Traditional and modern Blat represent different operating policies of the firm, and our expectation was that firms

would choose between these policies. Our data do not support this view with an insignificant path being found between

the two forms of Blat. This suggests that some firms may employ both forms of Blat, or that some firms that employ one

form of Blat do not employ the other, however, within our sample these outcomes do not occur to a significant extent.

The way in which traditional and modern Blat may coexist in some firms represents an interesting area in the study of the

32

evolution of Blat relationships, particularly as firms respond to the way in which the Russian economy develops over

future years.

Finally, our results, based on Russian data, showed a significant positive correlation between innovation and

performance which supports the evidence from Western economies on the performance enhancing role of innovation.

(Amabile, 1996; Kanter, 1984; Kimberly, 1981; Simons, 2000). However, within our path model this association is not

significant. The observation that neither traditional nor modern Blat were associated with formal controls suggests that a

lack of attention to formal controls may impede firms’ capacities to translate innovation into overall enhanced

performance. It may be speculated that firms not using formal controls to identify the commercial implications of

transactions based on Blat arrangements would not be sensitive to transactions that involve nonmarket-based prices and

non-commercial arrangements which may damage periodic profitability. Formal controls may be important for

renegotiating transactions or more generally judging the costs and benefits of the Blat arrangements.

(Insert Figure 2 about here)

Conclusions

This paper investigates how the Russian informal, personal networking system known as Blat

relationships between MACS, strategies of differentiation, innovations and performance of Russian firms.

practiced for centuries in Russia and it still has deep roots in the Russian economy. Although the Russian economic

environment has become more competitive and the legal setting has developed, informal contacts are still very important.

Blat is built into the Russian hierarchical social structures and has been found to be important in current Russia (e.g.

Barnes et al., 1997; Edwards & Lawrence, 2000; Michailova & Worm, 2003). Therefore, Russia provides a unique setting

in which to investigate the role of management accounting, strategy, innovations and performance of the firm in a

distinctive social and cultural environment.

33

We developed a path model and used the PLS method to test several hypotheses derived from the literature. Our

empirical analyses are based on survey data drawn from 100 Russian firms operating in St. Petersburg area. The main

empirical results can be summarized as follows. The traditional form of Blat is positively correlated with the creation of

innovations and performance among the Russian firms, while the modern form of Blat is negatively related to

performance. In attempting to identify reasons for these associations we examined the intervening roles of strategies of

differentiation and both organic and formal controls. For the correlation between traditional Blat and both innovation and

performance, differentiation and organic controls act as mediators. Formal controls are implicated in the relationship

between traditional Blat and innovation by way of a path from traditional Blat to differentiation then to formal controls

and finally to innovation. Importantly, our data confirm that traditional Blat encourages differentiation strategies and

organic controls which are both linked to innovation and performance. Additionally, there is a link between differentiation

and formal controls which, in turn, is associated with innovation, only. It is clear that the strategy of differentiation and

the resulting business conditions are important in explaining the use of both organic and formal controls in Russian

businesses.

Modern Blat was negatively correlated with performance. As with traditional Blat, paths through differentiation and

organic controls helped explain why modern Blat was negatively correlated with performance. In sum, these results

indicate that recognition of the unique cultural context of Russia, as captured in Blat, is relevant in understand the role of

MACS in assisting in the development of strategies of differentiation, innovations and enhancing the performance of

Russian business enterprises.

This study is subject to several limitations that should be considered when drawing conclusions from the results.

First, the results of the analysis represent necessary but not sufficient conditions for proof of causal relationships. The paths

indicate statistical associations consistent with the theory developed in the paper. Research employing qualitative methods

that examine the evolution of MACS and Blat over time could help identify how the variables interact providing data to

assist in identifying cause and effect. We see survey-based studies of the impact of national culture as an attempt to clarify

34

the construct and measurement of cultural attributes, such as Balt, and to help disentangle the impact of local institution

arrangements, particularly MACS, from aspects of national culture (Merchant & Otley, 2007) Second, there is an issue of

the appropriate form of model to study how MACS are implicated in Russian businesses. We used a path modelling

approach where associations between studied variables are considered. It may be argued that insights could also be gained

by considering moderating variable models. For example, it can be argued that traditional Blat affects the employment of

organic controls which then enhances performance. In this case, organic controls act as an intervening variable, mediating

the association traditional Blat and performance. An alternate argument is that high performance depends on a fit between

traditional Blat and organic controls. That is, as the employment of traditional Blat increases, high performance effects

depend on matching the degree of Blat with organic controls. While we believe that path modelling was theoretically

appropriate in the current research, it is possible that alternate models could help develop theory in this area.

Third, a further limitation is the relatively low response rate to the survey, although this is not inconsistent with

other recent published survey work in management accounting (e.g. Guilding, 1999 = 23%; Kalaganam & Lindsay, 1999 =

13%; Moores & Yuen, 2000 = 15%). Collecting data for non-official, business-related research by survey is relatively

novel in Russia. Early preliminary work examining the viability of employing postal and internet methods revealed that

these approaches would not be successful. By collecting data employing a survey-interview method, we believe that while

the response rate is modest the approach provided high quality data in terms of the correct person answering the survey, the

opportunity to clarify any ambiguity in the survey and the likelihood that a level of trust could be developed between

interviewer and respondents which helped ensure that the survey was taken seriously. Fourth, there are issues concerning

variable measurement. Existing measures were used for established variables. However, the constructs of traditional and

modern Blat had to be defined from the existing literature and contemporary practice, and measures developed. As the

underlying dimensions of these constructs are likely to change through time, further work will be required to refine the

measures. The measurement of performance by way of self-assessment is often criticized for potential bias. While several

35

studies provide support for the use of self-assessment (Venkatraman & Ramanujam, 1987) it would be useful, if possible

within the research design, to confirm self-assessments with a superior’s assessments or some externally validated source.

Fifth, the study does not consider the influence of factors that may cause endogeneity problems. For example,

foreign ownership, might influence the variables of Blat and outcomes such as differentiation, MACS, innovation and

performance. In this study, within the sample, only 11 firms had direct foreign ownership. Moreover, when these firms

were excluded from the sample, the results were not significantly different from the sample without foreign ownership.

Thus, in this study we were not able to identify any effects of foreign ownership. However, it is possible that other studies

that include a higher proportion of foreign owned firm may find significant effects of this factor, as it has been identified as

important in studying the development of MACS within emerging economies (Firth, 1996). Similarly, future studies may

wish to consider the role of contextual variables that have been identified in Western studies to influence the use of MACS,

such as different types of competitive environments and advanced technologies (Chenhall, 2003; 2007). Additionally, the

use of Blat would seem to have implications for how firms are structured, with potential consequent affects on MACS.

Notwithstanding these limitations, the results suggest that the use of path analytic modelling can be useful to

explore how MACS are implicated in the development of business within countries, such as Russia, that have unique

social structures which influence the way business is conducted

36

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Table 1Summary statistics of respondents

N

Panel A: SizeNumber of employees

1-100 19101-500 51501-1500 181501- 12

Panel B: IndustryCategory

Chemistry 7Foodstuffs and beverages 14Engineering and automotive 20Construction and mining 9Light engineering and electrical 16Computers and electronics 11Agricultural 5Clothing 4Pulp, paper and wood products 5Others 9

44

Table 2Factor loadings for traditional Blat, modern Blat, formal controls, organic controls, innovations and performance.

Panel A. 1. Traditional Blat Factor pattern (loadings)Factor 1

1.1 0.8311.2 0.6921.3 0.6771.4 0.8271.5 0.8181.6 0.8401.7 0.865

Kaiser-Myer-Olkin measure of sampling adequacy

0.893

Bartlett’s test of sphericity 0.000Variance explained by factors

0.633

Composite reliability 0.910Panel B. 2. Modern Blat

Factor 1 2.2 0.854 2.3 0.789 2.4 0.934 2.5 0.704 2.6 0.662 Kaiser-Myer-Olkin measure of sampling adequacy

0.804

Bartlett’s test of sphericity 0.000Variance explained by factors

0.632

Composite reliability 0.879Panel C. 3. Formal controls

Factor 13.1 0.6213.2 0.5643.3. 0.6353.7 0.6033.8 0.6963.9 0.7803.10 0.629

Kaiser-Myer-Olkin measure of sampling adequacy

0.789

Bartlett’s test of sphericity 0.000

45

Variance explained by factors

0.423

Composite reliability 0.817

Panel D. 4. Organic controlsFactor 1

4.1 0.5314.3 0.6734.4 0.5124.5 0.7054.6 0.7744.7 0.6574.8 0.6834.9 0.7414.10 0.615

Kaiser-Myer-Olkin measure of sampling adequacy

0.823

Bartlett’s test of sphericity 0.000Variance explained by factors

0.435

Composite reliability 0.853Panel E. 5. Innovations

Factor 15.1 0.8945.2 0.8735.3 0.8645.4 0.895

Kaiser-Myer-Olkin measure of sampling adequacy

0.832

Bartlett’s test of sphericity 0.000Variance explained by factors

0.777

Composite reliability 0.932Panel E. 6. Performance

Factor 16.1 0.9546.2 0.9436.3 0.7406.4 0.9096.5 0.9396.6 0.9316.7 0.9056.8 0.867

Kaiser-Myer-Olkin measure of sampling adequacy

0.877

46

Bartlett’s test of sphericity 0.000Variance explained by factors

0.836

Composite reliability 0.972

Panel F. 7 DifferentiationFactor 1

7.1 0.8327.2 0.5837.3 0.8157.4 0.9287.5 0.9137.6 0.926

Kaiser-Myer-Olkin measure of sampling adequacy

0.850

Bartlett’s test of sphericity 0.000Variance explained by factors

0.708

Composite reliability 0.937

47

Table 3Descriptive statistics

Variable Mean Standard deviation Actual range Theoretical rangeMin Max Min Max

Performance 3.345 1.920 1.00 7.00 1 7

Innovations 3.525 1.943 1.00 7.00 1 7

Formal controls 4.197 1.386 1.00 6.86 1 7

Organic controls 4.684 1.010 1.00 6.78 1 7

Differentiation 3.370 1.703 1.00 6.50 1 7

Traditional Blat 5.032 1.318 1.00 7.00 1 7

Modern Blat 1.886 1.162 1.00 7.00 1 7***, ** and * indicate significant at 1%, 5%, 10% respectively.

48

Table 4Results of PLS regressions: path coefficients and p-values, R2, root average variance extracted (AVE)

Paths from Paths to StatisticInnovation Formal

controlsOrganic controls

Differentiation Modern Blat Traditional Blat

Mult R2 AVE

Performance 0.04 0.08 0.139* 0.688*** -0.082 0.108 0.62 0.81

Innovations 0.237*** 0.163** 0.170*** -0.162** 0.065 0.24 0.78

Formal controls - - - 0.360*** -0.012 0.042 0.14 0.39

Organic controls - - - 0.144* -0.232** 0.276** 0.19 0.49

Differentiation - - - - -0.270** 0.250** 0.15 0.72

Modern Blat -0.197 0.04 0.71***, ** and * indicate significant at 1%, 5%, 10% respectively.

49

Table 5Correlations from PLS model between different constructs

Innovation Formal controls Organic controls Differentiation Modern Blat Traditional BlatPerformance 0.307*** 0.385*** 0.326** 0.755*** -0.320*** 0.115*

Innovation 0.352*** 0.291*** 0.321*** -0.268 0.182***

Formal controls 0.373** -0.123** 0.124**

Organic controls 0.261*** -0.273*** 0.316***

Differentiation -0.303*** 0.286***

Modern Blat -0.197***

***, ** and * indicate significant at 1%, 5%, 10% respectively.

50

Figure 1. Hypothesized path model

Traditional Blat

Modern Blat

Innovations Performance

Organic controls

H8a

H9a

H2b

H8b

Formal controls

H5b

Differentiation

H5a

H4b

H4a

H3b

H3a

H1b

H1a

H2aH9b

H11

H6a

H10

H7b

H6b

H7a

51

Figure 2. Results of estimating PLS regressions

Traditional Blat

Modern Blat

Innovations Performance

Organic controls

0.163**

0.237***-0.162**

0.139*

Formal controls

0.360***

0.276**

-0.232**

Differentiation

0.144*

-0.270**

0.250**

0.688***

0.170***

52

Notes:

The figure presents the standardized path coefficients. ***, ** and * indicate significant at 1%, 5%, 10% respectively.

Appendix . Constructs and underlying questions used in the survey.

1. Traditional Blat

Which of the following best characterizes your organization?

Success in business involves: 1.1 Personal and social network & connections1.2 Subjective recommendations based on preferences of trusted individuals1.3 Preferential contacts to gain access to information, resources, suppliers

To what extent are the following factors important to the conduct of your business?

1.4 Informal contacts and personal network1.5 Close personal and long-term relationship1.6 Friendship based on trust1.7 Contacts who can provide useful connections1.8 Contacts who can push through whatever needs to be pushed

2. Modern Blat

To what extent do the following statements represent the situation in your firm? 2.1. It is not acceptable for employees to reveal and emphasize negative information about competitors2.2. The firm plays a fair market game 2.3. The firm keeps fair partner relationships with contractors2.4. The firm’s business is based on honest (decent) relationships2.5. The firm prefers to operate in a situation of open market competition

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2.6. Accounting information fully discloses the performance of the firm, even if this discloses unfavorable performance

3. Formal controls

To what extent does your organization use the following?

3.1 . Standard costs and the analysis of cost variances3.2. Marginal or incremental costing in ‘make or by’ or pricing decisions3.3. . Flexible or activity level budgeting3.4 . Activity based costing3.5. Internal auditing3.6 Performance or operational auditing by outside auditors3.7. Use of internal rate of return or net present value in evaluating investments 3.8. Statistical quality control of production3.9. Inventory control and production scheduling by means of operations research techniques1.10. Systematic evaluation of managerial and senior staff personnel

4. Organic controls

To what extent do the following describe your firm?

4.1. An emphasis on consensus-seeking, staff participative decision making4.2. An emphasis on adaptation without concern for past practice4.3. Open channels of communications and free flow of information4.4. An emphasis on initiative, and adaptation to the local situation rather than

specialization and top level co-ordination4.5. Easy informal access to senior managers4.6. Managers encouraged to develop new ideas even if they fall outside the individual’s area of responsibility

54

4.7. Tolerance of manager’s mistakes, learning and sharing lessons from them4.8. Managers share information with colleagues4.9. Fast reaction to take advantage of unexpected opportunities4.10. Current corporate culture encourages informal signaling of potential problems

5. Innovation

In comparison with the industry average,

5.2. During the last three years, how many new products has your firm launched?5.3 During the last three years, how many modifications to already existing products has your firm launched? 5.4. In new products, how often has your firm been first-to-market?5.5. What is the percentage of new products in your firm’s product portfolio?

6. Performance

In comparison with the industry average, how would you qualify the performance of your company over the last three years in terms of the following indicators?

6.1. Rate of sales growth6.2. Rate of revenue growth6.3. Return on Investment6.4. Profit/sales ratio6.5. Customer satisfaction6.6. Customer retention6.7. Acquisition of new customers6.8. Increase in market share

55

7. Differentiation

What is the position of your products relative to those of leading competitors in the following areas?

7.1. Product selling price7.2. Percent of product sales spent on R&D7.3. Percent of product sales spent on marketing expenses7.4. Product quality7.5. Brand image7.6. Product features

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