Empirical analysis of relevant contextual factors for the Inclusion of risk management in the role of management accountants Master Thesis

University of Groningen Faculty of Economics and Business

M. Sc. Business Administration, Organizational & Management Control

Master Thesis

Empirical analysis of relevant contextual factors for the

Inclusion of risk management in the role of management

accountants

Student: Madlen Walfort Student number: S3575500

E-Mail: m.walfort@student.rug.nl

Thesis Supervisor: Prof. Dr. Ir. P. M. G. van Veen-Dirks

The present research paper was carried out in the period from 01.09.2018 to 21.01.2019

Abstract

This study focuses on the relationship between the influence of four different contextual factors with regard to management accountant’s involvement in risk management. In particular, the aim of this research was to explore whether environmental uncertainty, organizational structure, firm size, and the presence of a risk manager are related to accountant’s involvement in risk management. In this research, it is expected that envi-ronmental uncertainty and organizational structure are positively associated with the in-volvement in risk management. In contrast, firm size and the presence of a risk manager have a negative relationship to the involvement in risk management. Moreover, the pres-ence of a risk manager also positively moderates the relationship between firm size and involvement in risk management.

Table of content

2.3 Roles of management accountants ... 13

3. Theoretical Framework ... 15

3.1 Dependent variable: involvement of the management accountant in risk management ... 15

3.2 Independent variable: environmental uncertainty ... 16

3.3 Independent variable: organizational structure ... 17

3.4 Independent variable: firm size ... 18

3.5 Independent and moderating variable: presence of risk manager ... 19

3.6 Conceptual model ... 20

4. Methodology ... 21

4.1 Data collection and sample ... 21

4.2 Measurement of variables ... 23

4.2.1 Involvement in risk management ... 23

4.2.2 Environmental uncertainty ... 24

4.2.3 Organizational structure ... 24

4.2.4 Firm size ... 24

4.2.5 Presence of risk manager ... 24

4.2.6 Control variables ... 25

5. Results ... 25

5.1 Descriptive data and correlations ... 26

5.2 Regression results ... 28

6. Discussion and Conclusion ... 29

6.2 Practical implication ... 31

6.3 Limitation and further research ... 31

List of References ... 33

List of Tables

Table 1: Job Function ... 23

Table 2: Factor Analysis: Rotated Component Matrix ... 25

Table 3: Descriptive Statistics ... 26

Table 4: Sector ... 26

Table 5: Correlation Matrix ... 27

Table 6: Regression Analysis 1 ... 28

List of Figures

1. Introduction

“A ship is safe in harbor, but that is not what ships are for.” (John A. Shedd, 1928) This quote from John Shedd (1928) highlights the inevitable fact, that organizations au-tomatically face risks when they operate in business. The perception of and interest on risk is continuously growing due to recent events and financial scandals, most prominent the financial crisis which sheds light on the weakness of ignoring risk (Soin & Collier, 2013). Firms put an increasing effort in organizing uncertainty and over time, organiza-tional settings have become organized around risk. Consequently, official reports usually incorporate detailed sections about how the organizations manage their risks (Arena, Arnaboldi & Azzone, 2010). Simultaneously to risk, companies’ risk management also faced significant changes: it has long been regarded as a technical discipline in financial institutions; but by now, it is more promoted as a cross-industry corporate governance and management control practice (Hall, Mikes & Millo, 2015). Thus, the understanding of risk management has changed from a narrow, financial perspective to a broad concept (Power, 2007). Certainly, managers have always been confronted with uncertainty, but the range seems to have increased in the last two decades (Soin et al., 2013).

Accompanied by the increasing importance of risk management are the discussions about corporate controls and the work of management accountants (Bhimani, 2009). Recently, there has been a lot of debate on the change in the accountants’ role, mainly in professional accounting literature (Burns & Baldvinsdottir, 2015). In general, most au-thors agreed that management accountants play an important role in the development and use of controls systems in an organization. Firms design management accounting systems to serve the dual objectives of decision making and control (Indiejikian & Ma-teijka, 2006). In more detail, through these systems, information can be collected, pro-cessed, analyzed and communicated useful to plan, monitor, and control several organ-izational activities. Control systems are even used to mitigate uncertainty (Novas, 2015).

second role are expected to interpret data and advise manager, instead of only providing information. This role change is primarily driven by globalization and new management philosophies, resulting in changing demands regarding uncertainty (Goretzki, Strauss & Weber, 2013). Additionally, recent techniques and environmental changes are often con-sidered as leading controller to select a business orientation. Järvenpäa (2007) also found that innovations, modern control systems, software empowerment, and decentral-ization foster a business-oriented role. However, empirical evidence that indicates a sig-nificant change in the role of management accountants is relatively rare (Lambert & Sponem, 2012).

In this context, taking the increasing interest on uncertainty into account as well as con-sidering the role change towards a business partner role, the question arises, whether management accountants do also have to take and identify themselves with the role of a risk manager. Organizational coherence and credibility have nowadays high priority and more relevance than it has ever been before and makes management accounting and risk management increasingly intertwined (Bhimani, 2009). Nevertheless, until now, it is clear that risk management becomes an important issue of management control, but authors are not sure where the management accountant fits in this situation exactly (Soin and Collier, 2013). Moreover, a study examining the impact of risk management on the accountant’s role remains rare. By addressing this literature gap, this research would like to contribute to the professional accounting literature by empirically evaluating the in-volvement in risk management of management accountants. As mentioned before, pre-vious research of risk management has focused on the technical aspects, but other fac-tors, like the social, institutional and organizational context, need to be considered as well (Soin & Collier, 2013). Lambert & Sponem (2012, p. 584) pointed out that “capturing the actual role management accountants play within organizations, researchers should develop an understanding of the context in which they practice”. Furthermore, particular risk management characteristics in specific organizational settings was not an issue in research so far. Additionally, the relationship between management accounting and risk management has not been addressed adequately (Bhimani, 2009). In more detail, there is a need for analysis into “when, why and how accountants’ roles are changing within organizations; a need to explicitly conceptualize and empirically investigate how ac-countants carve out role change” (Burns et al., 2005, p. 753).

“What is the context in which risk management is included in the tasks of the manage-ment accountants?”

This research focuses on four contextual factors namely firm size, environmental uncer-tainty, organizational structure, and the presence of risk manager. Additionally, the influ-ence of a present risk manager will be further analyzed as a moderator variable on the relationship between firm size and accountant’s involvement in risk management. There-fore, this research contributes theoretically to the management accounting literature as it identifies context-related factors in which management accountants also perform the role of a risk manager. In the current literature, further elaboration on the relationships and statistical evidence is missing. The answer to this research question also represents a practical relevance, as management accountants can use the outcome to determine in which context their like to execute their work.

The remainder of this study is structured as follows. The next section provides the basis for the theoretical framework and the associated hypotheses, which are developed in section three. Section four focuses on the research setting and methodology, while sec-tion five presents the results. The thesis concludes with a discussion of the outcomes and limitations of this study as well as providing avenues for future research.

2. Literature Review

In the following literature review, risk is defined in the beginning to effectively discuss risk management and the related concepts. These provide a clear and understandable description of previous literature. Furthermore, the role of the management accountant is elaborated in more detail to make the discussion of a role change more visible. More-over, this research will draw on the contingency theory. From a contingency point of view, the circumstances that shape the patterns in the development of risk management prac-tices are systemic and can be explained by carefully studying the underlying streams (Mikes, 2009). As the involvement in risk management in controllers function depends on contextual factors, it is reasonable to use contingency theory as a basis.

2.1 Risk

and impact (COSO, 2004). Referring to the second part of the definition, new risk man-agement concepts, evolved in the last decade, need to optimize risk exposure. As risks are constantly changing, an organization can be affected (positive or negative) through new opportunities and threats (Viscelli, Hermanson & Beasley, 2017). In general, or-ganizations define risk by referring to negative consequences only; therefore, most of the concepts that manage risk focused on the prevention and mitigation of risk (Knight, 2012; Hubbard, 2014). However, risks can also provide and compromise an opportunity, from which organizations would benefit and the systems to manage risks should find an optimal balance.

Additionally, risks can also be present in several forms: preventable risks, strategic risks, and external risks (Kaplan & Mikes, 2012). Preventable risks can be easily controlled by rule-based management whereas strategy risks are hard to control (Kaplan and Mikes, 2012) and are more often discussed in boardrooms (Arena, Arnaboldi & Azzone, 2010). Moreover, a distinction of risk is frequently made in the literature between direct and indirect, systematic and unsystematic, inherent and incidental, internal and external, short-term and long-term, and high-impact and low-impact. For that reason, classifying risk types is not only important for creating cause and effect models, but also for design-ing risk management systems (Drew & Kendrick, 2005). The context, industry and cho-sen strategy should also be taken into consideration as risk classification depends on these factors (Drew & Kendrick, 2005). A risk is not an absolute value and depends on the information available, values, objectives, situation, and priorities of risk in different industries.

2.2 Risk Management

Similar to the term risk, risk management is frequently discussed in the accounting liter-ature. Several years ago, risk management was primarily seen as a mechanism which comprised the assumption that risks are measurable and manageable (Gallagher, 1956; Spira & Page, 2003). As a result, models and strategies were developed to protect an organization from these risks. However, risk management has undergone significant de-velopments in recent years due to several scandals as well as the financial crisis of 2007-2009. A change in understanding risk management and a change within risk manage-ment practices became visible (Huber & Scheytt, 2013; Millo & MacKenzie, 2009).

uncertainty (Soin et al., 2013). Managing risk effectively is a continuous process of find-ing the balance between risk takfind-ing and risk mitigation. As a result, Enterprise Risk Man-agement (ERM) was adopted in many organizations. Rather than managing risks indi-vidually, ERM aims to view all risks “together within a coordinated and strategic frame-work” (Nocco & Stulz, 2006, p.1). It is one process that fulfills the need of linking risk management with control activities as ERM combines the divisions of control, accounta-bility and decision making by considering company’s risk attitude (Arena et al., 2010). However, for ERM to be effective, the associated processes need to be integrated into the organizations’ core business model and the related strategy initiatives (Viscelli et al., 2017).

The most accepted and widely used ERM framework is the COSO framework. In the early 90s, the COSO framework provided a framework for internal control in the USA but is nowadays remodeled as an ERM template (Power, 2009).

COSO (2004, p.2) defines ERM as a process, effected by an entity’s board of directors, management, and other personnel, applied in strategy setting and across the enterprise, designed to identify potential events that may affect the entity, and manage risk to be within its risk appetite, to provide reasonable assur-ance regarding the achievement of entity objectives.

Risk appetite is the amount of risk a company wants to take (Power, 2009). In 2004, the COSO framework introduced the first cube, so that an organization can analyze risk. However, the framework was further improved in 2017 as an extension was published (COSO, 2017). The purpose of the new framework was not only to analyze possible risks but also to provide better insight into the relationship between strategy, risk, and perfor-mance (COSO, 2017). However, every company organizes risk management differently due to the calculative cultures (Mikes, 2009), and the determined focus on risk manage-ment; organizations can focus only on financial and legal risks, but also on company-wide risks. ‘Calculative cultures’ influence the attitudes towards the several methods of risk management and can be categorized in ‘calculative idealism’ and ‘calculative prag-matism’ (Mikes, 2009). The former describes risk quantification, which emphasizes the belief that the role of corporate risk management is to identify and then measure risks (Kaplan & Mikes, 2016); whereas the latter can be seen as quantitative skeptics, which encourages the view of numbers as indicators (Mikes, 2009).

behave. For instance, alternative demonstration of the same risk elements can lead to different risk-taking behaviors (Kahneman & Tversky, 1979). Moreover, researchers have also demonstrated that biases lead people to underestimate unfavorable outcomes (Hammond, Keeney & Raiffa, 2006; Kahneman, Lovallo & Sibony, 2011). One explana-tion of many can be ‘group thinking’ which hinders critical assessment and justificaexplana-tion of risks in groups. These cognitive biases can lead to inaccurate judgments and make clear why organizations overlook or misinterpret threats and fail to manage these risks (Mikes & Kaplan, 2014). This highlights the need for risk management for appropriate understanding and the usage of right controls to counter biases and promote the desired risk attitude by every employee in the company.

Besides relevant individual characteristics for a successful risk management system, Rene Stulz (2008, p. 44) stated that “In a well-functioning, truly enterprise-wide risk man-agement system, all major risks would be identified, monitored, and managed on a con-tinuous basis”. Moreover, a risk management system is not implemented efficiently into the organizational structure overnight; on the contrary, Kaplan & Mikes (2012) set up three requirements for the development of an efficient risk management system. First, an organization should agree on their own values and priorities. Second, a company should clearly communicate their attitude towards risk. Finally, ongoing monitoring of risky behavior, with regard to the firm’s own risk limit, is necessary. Additionally, the re-searcher mentioned that there should be a dialogue between managers and employees about the most relevant risks faced by the organization. Thus, not only the risk manage-ment system itself is important, but also soft factors like discussions about risks are from importance to optimize the risk exposure (Kaplan & Mikes, 2012).

In sum, many different objects need to be considered to efficiently implement a risk man-agement system that works perfectly for the organization; from defining the risk type that should be managed to consciously execute the three development stages. How exactly management accountants are linked to risk management is outlined in the next section.

2.3 Roles of management accountants

of internal control (Spira & Page, 2003); thus, the emerged role as a risk manager is further discussed.

In 1954, Simon et al. concluded that the role of an accountant was, at that time, best characterized as “bookkeeping”, a “bean counter” or “scorekeeping”. The typical tasks of a bean counter were, amongst a few other things, data accumulation, financial reporting, financial data analysis as well as calculative techniques (Morales & Lambert, 2013; Burns & Baldvinsdottir, 2005; Emsley, 2005). However, Sathe and Srinivasan (1982) describe that a desire arose already 30 years ago in the controller to be more involved in decision-making. In line with Sathe and Srinivasan, several researchers argue that the role of the management accountant moves away from a bean counter perspective to a business partner (Friedman & Lyne, 2001; Vaivo & Kokko, 2006; Cooper & Dart, 2013).

Due to globalization and fast-changing business environments, the business orientation receives more and more attention and the associated task with this role goes beyond routine and traditional accounting (Chang, Ittner & Paz, 2014; Granlund & Lukka, 1997, 1998; Parker, 2002; Ezzamel, Lilley & Willmott, 1997). Quinn (2014, p.22) defines a busi-ness partner as “a controller who has a strong embedded, supporting relationship with business managers and is providing them with insights on business challenges”. That means, the task of the controller became more analytical; they provide essential infor-mation for decisions and more added value to the key players in the organization (Siegel, 2000; Järvenpää, 2007).

As there is an ongoing discussion about these two roles, it indicates that both roles are present in organizations and that not all organizations have identical roles for the con-troller. There is also a discussion that risk management is one of the new fields of work for the accountants. It is argued that a business-oriented role increases the influence management accountants have in decision-making (Järvenpää, 2007) as well as it in-creases the involvement in the organizational processes (Byrne & Pierce, 2007); this also includes the decisions about risk management. Overall, a more business-oriented role fosters the role as a risk manager. This was also found by the authors Chang, Ittner & Paz (2014), who stated that there exist complementarities between the roles; a stronger emphasizes on one role is associated with greater efficiency in the other role. However, there is still little empirical evidence regarding the role of accountants in risk management (Lambert & Sponem, 2012).

characteristics that influence the actual role of management accountants in an organiza-tion. This research focuses on four contextual factors: firm size, environmental uncer-tainty, organizational structure, and the presence of a risk manager to examine the de-gree to which risk management is included in the task of management accountants.

3. Theoretical Framework

After introducing risk management and the current discussion about the role of manage-ment accountants, the theoretical framework will be discussed in the following chapter. As mentioned above, this research is based on contingency theory. This theory was adopted by Otley in the 1980s and states that the optimal course for an organization depends on the situation; there is no best way that suits all companies (Fisher, 1995; Chenhall, 2003; Byrne & Pierce, 2007). Especially the idea of ‘fit’ is central to contingency theory and can be widely used for a bunch of definitions (Byrne & Pierce, 2007). For instance, Chenhall (2003) describes the external environment, technology, organiza-tional structure, size, strategy and culture as contingent factors that distinguish compa-nies from each other. Additionally, Gordon, Loeb & Tseng (2009) used the contingent factors environmental uncertainty, competition within industry, firm complexity and firm size for investigating to what extent ERM fit within these variables. In general, the exter-nal factor environmental uncertainty, and the interexter-nal factors firm size and organizatioexter-nal structure are frequently used in the literature when examining the contextual variables. For that reason, they are investigated as being contingent and used in this research to examine their impact on the role of management accountants and their associated in-volvement in risk management.

3.1 Dependent variable: involvement of the management accountant in

risk management

3.2 Independent variable: environmental uncertainty

The first contextual variable refers to environmental uncertainty. Rapid changes in envi-ronment are seen as a primary indicator of the need to expand the activities of the finan-cial departments (Chang et al., 2014). In addition, Hopper (1980) came to the conclusion that accountants take over that role which meets the expectations of the environment. Moreover, the researchers Byrne & Pierce (2007) also found that there is a link between the organizational environment and the role of the management accountant; for instance, when the business environment changes in a specific sector, the main focus in the ac-counting department refers to meeting the new expectations instead of executing tradi-tional control tasks. So, changes in the environment are seen as leading accountants to adopt a business-oriented role or further, a role as a risk manager (Lambert & Sponem, 2012).

Already in 1993, Abbott suggested to study professions in connection with changes in legal, social and economic nature as these changes have significant consequences for the role of accountants (Abbott, 1993; Dutton & Dukerich, 1991; Brouard, Bujaki, Du-rocher & Neilson 2017). For instance, managers in companies frequently mention the influence of legislation and regulation on the roles of management accountants (Byrne & Pierce, 2007). Therefore, it can also be assumed that economic changes are an influ-encing driver in the role change of controller.

Another driver of the role change is the increasing importance of environmental uncer-tainty due to globalization and institutionalization. Firms face the need to adapt to chang-ing environments quickly and effectively in order to achieve competitive advantage. High levels of environmental uncertainty are described as quick changes in technology, eco-nomic conditions, market growth, risk and cultural influences (Khandwalla, 1976). Or-ganizations which face greater environmental uncertainty are in need for greater risk management (Chang et al., 2014). The organizational environment is also mentioned as one antecedent of risk awareness (Braumann, 2018); whereas risk awareness affects employee’s behavior in terms of how quickly the organization is able to adapt to environ-mental changes (Braumann, 2018; Cormican, 2014).

function to be able to act quickly on rapid environmental changes (Hall et al., 2015). This leads to the following expectation:

H1: A higher environmental uncertainty increases the management accountant’s in-volvement in risk management.

3.3 Independent variable: organizational structure

The second factor concerns the organizational structure. Prior accounting literature pro-poses that differences in organizational structure can have a significant impact on the preferences organizations have on different roles (Chang et al., 2014). Organizational structure is mostly defined as centralization or decentralization (Chenhall, 2003). Cen-tralization refers to a process where the concentration of decision making is in few hands, the top management. On the other hand, in a decentralized organization authority is delegated to all levels of management (Juneja, 2018). Thus, the structure can vary from highly decentralized, in which leader delegate major decisions to individual employees or business units, to highly centralized structures, in which major decisions are taken by the companies’ top management (Deloitte, 2010).

Controllers are not only more involved in management decision processes when the need for their financial know-how is higher (Sathe & Srinivasan, 1982) but also require greater operating interdependencies as cost allocations are more difficult, leading to greater involvement of accountants in nontraditional roles (Zoni & Merchant, 2007). Spe-cifically, Zoni et al. (2007) empirical tests suggest that an accountant’s involvement in operational decisions rises as organizational interdependencies increase. Moreover, Deloitte (2010) found that accounting business units have a higher involvement in stra-tegic decisions when an organization put emphasizes on greater operational integration. According to Chang et al. (2014), the structure of organizations is significantly important to determining the value of risk management practices; integrated global companies place more emphasizes on risk management than less integrated multinationals.

Additionally, Granlund and Lukka (1998) noted that accountants who work in a decen-tralized organization perceived a need to enhance their business-orientation. As the roles can be complementary, it is assumed that decentralized structures have the same effect for the role of risk manager. So, it is expected that:

H2: A higher decentralized structure increases the management accountant’s involve-ment in risk manageinvolve-ment.

3.4 Independent variable: firm size

Third, firm size is a further contextual factor that influences the controller’s involvement in risk management. The size of the company has been shown to affect the activities of financial organizations, suggesting that firm size could also influence the preference of the role of management accountants (ICAEW, 2011). Furthermore, researchers found that the firm’s size has a significant correlation with the effectiveness of the involvement in risk management (Chang et al., 2014). Basically, larger firms face higher coordination requirements, which require greater regulatory and sophisticated management control systems (Chang, Ittner & Paz, 2014; Chenhall, 2003). This increases the need for pow-erful internal controls and higher-quality financial accounting in larger companies (Watts & Zimmerman, 1990). Additionally, associated with bigger firm size, are higher risk ex-posures. If firms face higher risk exposures, they pay more attention to reporting and compliance and that those risk responsibilities are effectively met (Chang et al., 2014). Taking both arguments together, larger firms are more likely to establish specific risk management departments to increase their benefit from it (Beasley, Clune & Herman-son, 2005).

Another indication for a higher involvement in risk management in smaller firms can be found in the concept of culture. In larger firms, it is more likely to find a culture of finance with high emphasizes on finances and low emphasizes disclosure of internal accounting information, whereas smaller organizations tend to have a culture of openness (Granlund & Lukka, 1998). From this, it can be derived that in smaller firms, they are more open for role changes than in bigger company.

larger firm, accountants experience a more corporate model as formal processes are needed to provide a guideline for the employees in the company (Braumann, 2018). Therefore, the role of the controller in bigger companies is more standardized and pre-defined, making it more difficult for accountants to determine their own roles. This also implies that the roles of management accountants depend on the size of the company (Byrne & Pierce, 2007).

Even though larger companies have more resources available to implement changes in management accounting roles (Cooper & Dart, 2009), management accountants in a smaller organization have much more flexibility in designing and implementing manage-ment control procedures. One reason among others is that controller in a bigger com-pany experience a higher impact of regulations which entail a more control orientation to the roles of management accountants (Byrne & Pierce, 2007). Being more involved in business operations strengthen the effectiveness of control systems as well as the un-derstanding of accountants at what time and situation the control function is required to design a more comprehensive role (Byrne & Pierce, 2007). Therefore, it is expected that:

H3: An increase in firm size decreases the management accountant’s involvement in risk management.

3.5 Independent and moderating variable: presence of risk manager

H4: The presence of a risk manager decreases the management accountant’s involve-ment in risk manageinvolve-ment.

Second, the presence of a risk manager influences the relationship between firm size and controller’s involvement in risk management. If a company has a risk manager pre-sent, the involvement of management accountants in risk management will be lower. In addition, as the firm size increases, the involvement in risk management decreases. However, if a risk a manager is present in an organization, even in small or big compa-nies, the effect of firm size on involvement is weakened. Therefore, the following is ex-pected:

H5: The presence of a risk manager positively moderates the relationship between firm size and involvement in risk management.

3.6 Conceptual model

In sum, the contextual factors environmental uncertainty and organizational structure are positively and directly related to the degree to which risk management is included in the task of management accountants. Firm size is negatively related to the accountant’s in-volvement in risk management. The presence of a risk manager has a negative direct impact on the involvement of risk management as well as a positive moderating impact on the relationship between firm size and the involvement of risk management. Sector, management accountants’ business unit size and the relative size are used as control variables. Developed from the literature, the following conceptual model can be pre-sented (Figure 1):

4. Methodology

The research applies a quantitative research approach to analyze relevant contextual factors that influence the extent to which risk management is included in the task of management accountants. As this topic is not investigated to a sufficient extent, this research will explore the context in a quantitative way. In particular, this research follows a theory testing approach as relevant literature streams are already elaborated, but there is still a need for further theoretical explanations (Van Aken, Berends & Van der Bij, 2012). In the following the data collection and sample are discussed, the survey is intro-duced, and the measurement and analysis are outlined.

4.1 Data collection and sample

The data were gathered in the form of a web-based survey. This methodology was se-lected to collect important internal data from the person working in the financial depart-ment. When processing a quantitative questionnaire, responses from many people to many items can be recorded in a short time (Bortz & Döring, 2006). Especially, it has been increasingly popular for some years to conduct internet-based surveys, and the trend continues to increase as the Internet has become more and more influential since its introduction in the 1990s. Furthermore, one advantage of many is that a record of the respondent behavior can be made so that their reactions can be detected. By means of the online survey, for example, it is possible to see who only looks at the questionnaire without giving answers and how long the average processing time is (Diekmann, 2010).

The questionnaire is a shared survey which was developed with two other students to achieve more meaningful results. Particularly, the survey consists of several subsections and serves the basis for three master theses. First, the survey started with a common general section in which the demographic data of the company and the individual re-spondent were collected. This included the current function and age as well as several firm characteristics. Second, each student had an individual subsection; the relevant questions for this analysis are presented in the next section.

The data were collected from all kind of firms especially in Germany and the Netherlands. Regarding the distribution of the survey, it was crucial to gain access to key individuals within each organization, meaning the persons who are in a position dealing with ac-counting or controlling; for instance, management accountants, controllers, financial manager and people in an executive leadership position.

way, it was possible to identify potential technical and programming problems and incon-sistencies of the questionnaire, with the advantage that they can be corrected before the start of the actual data collection. It is important that the interview is carried out under realistic conditions; furthermore, a small number of participants representing the target group of interest in the questionnaire is sufficient (Jonkisz, Moosbrugger & Brandt, 2012).

After small adjustments, the actual data collection started with different approaches. Po-tential respondents were contacted through Xing and LinkedIn, and the survey was shared with each personal profile to increase the visibility and possible responses. After two weeks, reminder e-mails were sent to increase the response rate. Additionally, an agency (TestingTime) was instructed to look for additional participants. Nonetheless, the several approaches also represent a significant limitation regarding the response rate because the non-response bias cannot be analyzed without any doubts. All in all, the data collection lasted about one month and was completed in January 2019.

Finally, the link to the survey was clicked 201 times. However, 167 respondents actually filled out the questionnaire. From the 167 participants, 39 were contacted through the hired agency. Overall, 67 respondents have not been used in the analyses because of several reasons. First, to ensure that the survey was filled out only once by a participant, 19 had to be removed as the IP address occurred more than once. Second, another four respondents were deleted because there were more than 15% missing data. Nonethe-less, the highest proportion was deleted because of the wrong job function (44 Partici-pants). This can be explained by the fact that people participated in the questionnaire without noticing the specific target group for which the survey was intended. In the end, the final sample consists of 100 participants. The exact distribution of the respondents and their corresponding job function are shown in Table 1.

4.2 Measurement of variables

After the questionnaire has been presented as a whole, the individual variables and their measurements are outlined below. The measurement will be based on existing academic literature. First, the measures for the dependent variables are introduced and second, the independent and control variables are presented. Finally, for each variable, a factor analysis has been conducted (see Appendix) as well as one factor analysis for all varia-bles (Table 2). The main reason for doing a factor analysis is to reduce a large number of correlated, manifested variables to a small set of latent variables (factors) that explain as much of the variance as possible (Klopp, 2010).

4.2.1 Involvement in risk management

Regarding the measurement of the dependent variable (IRM), the survey referred to the existing survey of Chang et al. (2014). They asked the respondents about the importance of different responsibilities within the organization to measure the involvement of an em-ployee in risk management activities. Here, this design is used as an indicator while simultaneously using the instrument generated by Sax and Torp (2015). The authors measured the importance of risk management, in which they refer to relevant tasks ex-ercised by the organization. These tasks were transformed to the individual level of a management accountant so that they indicated on a seven-point Likert scale how im-portant certain statement are in their work (1= really unimim-portant, 7= really imim-portant). From the factor analysis, it appears that all six items load on one factor (see Appendix). The value for the KMO measure is 0.862, indicating that the factor analysis is appropri-ate. The scores for the items were summed, and the average was taken to obtain the results for the involvement in risk management (IRM).

Frequency Percent Cumulative Percent

Controller 27 27 27

Management Accountant 14 14 41

CEO 13 13 54

Financial Manager 12 12 66

Head of Finance and Controlling 10 10 76

CFO 8 8 84

Assistant Financial Advisor 7 7 91

Project Manager Controlling 3 3 94

COO 2 2 96

Risk Manager 2 2 98

Board member 1 1 99

Internal Auditor within Finance Department 1 1 100

Total 100 100

Job Function

4.2.2 Environmental uncertainty

With respect to the measurements of environmental uncertainty (ENVU), the instrument of Cadez & Guilding (2008) was used. The respondents were asked to indicate the pre-dictability of the firm’s environment on a seven-point Likert scale regarding customer demands, competitors’ activities, technology, suppliers’ actions, and development of new products in the industry. The factor analysis illustrates that all items load into one com-ponent (see Appendix) and a KMO-value of 0.805 indicate, that the factor analysis is appropriate. However, when looking at the factor analysis for all variables in Table 2, the item ENVU_5 (development of new products) loaded into two components: environmen-tal uncertainty and firm size. That’s why ENVU_5 was removed from the analysis. Item ENVU_1 to ENVU_4 also load into one factor in the analysis with all variables; thus, the four scores were summed, and the average was taken to generate one factor ENVU to indicate the level of environmental uncertainty.

4.2.3 Organizational structure

Concerning organizational structures (ORGSTRUCT), questions developed by Aber-nethy, Bouwens & Lent (2004) were used in this survey. Specifically, people needed to compare on a seven-point Likert scale (1= business unit has all influence, 7= superior has all influence) their influence with the influence of their superior on the following de-cisions: strategic, investment, internal processes, human resources and marketing deci-sions. As with the variables before, conducting a factor analysis is appropriate due to the KMO-value of 0.834. The individual factor analysis (see Appendix), as well as the factor analysis with all variables, reveals that all five items load into one factor. Therefore, the five scores were summed, and the average was taken to generate one factor ORGSTRUCT to measure organizational structure.

4.2.4 Firm size

Particularly, firm size was measured through the total number of employees, which par-ticipants needed to indicate. Factor analysis for firm size showed a value of 0.902 (Table 2), which only loaded into one factor.

4.2.5 Presence of risk manager

4.2.6 Control variables

Lastly, in terms of the control variables, the business unit size was measured through the number of employees in the management accountant department. Moreover, relative size was analyzed by dividing firm size with business unit size. In addition, prior studies suggest that accountants’ roles differ in terms of a sector; that’s why this variable is in-cluded as a control variable. As previous literature assumes that differences exist be-tween the sector financial services and all other business types, a T-test was conducted. No significant differences could have been found; therefore, participants from the sector financial services were included in the analysis.

5. Results

After the factor analysis was conducted, several steps for the data analysis were exe-cuted. First, an exploratory factor analysis was conducted to identify common character-istics among related survey items, which was mentioned and illustrated above in Table 2. Second, this section provides a description of the data in the beginning to create an overview including means and deviations of the construct, followed by reliability meas-urements for the items that remained. For this purpose, Cronbach’s alpha is used to measure internal consistency (Bortz & Döring, 2006). Subsequently, the correlation be-tween the variables will be outlined to investigate the relationship bebe-tween the dependent and independent variables. Finally, multiple regression analysis will be presented to ex-amine the interaction of several variables and to test the hypotheses (Bortz & Döring, 2006).

Involvement Environmental Uncertainty Organizational Structure Firm Size Presence of Risk Manager

IRM_4 0,869 0,001 0,175 0,116 -0,006 IRM_2 0,754 0,201 0,124 0,27 0,061 IRM_3 0,741 -0,144 0,247 -0,175 0,059 IRM_5 0,737 -0,051 0,237 -0,133 -0,199 IRM_1 0,735 0,032 -0,063 0,123 -0,017 IRM_6 0,709 -0,03 0,356 -0,121 -0,089 ENVU_2 0,191 0,778 -0,123 -0,107 -0,085 ENVU_4 0,129 0,756 -0,042 0,319 0,059 ENVU_1 0,188 0,755 0,05 -0,064 -0,214 ENVU_3 0,181 0,666 -0,1 0,038 0,275 ORGSTRUCT_5 0,019 -0,022 0,877 -0,129 -0,018 ORGSTRUCT_1 0,092 -0,099 0,867 0,074 0,114 ORGSTRUCT_2 0,06 -0,061 0,864 0,081 0,139 ORGSTRUCT_4 -0,013 -0,084 0,796 0,169 -0,156 ORGSTRUCT_3 -0,256 0,055 0,554 0,084 -0,297 Firm Size 0,052 0,145 0,061 0,902 -0,091 CRM -0,136 -0,012 -0,007 -0,08 0,898 Eigenvalue 4,569 3,435 1,633 1,157 1,038 Variance explained 26,875 20,208 9,608 6,805 6,107

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

Rotated Component Matrixa Component

5.1 Descriptive data and correlations

In Table 3 and 4, the descriptive statistics for the variables used are presented. In more detail, the mean, median, standard deviation, variance, minimum, maximum, and Cronbach’s Alpha can be seen in Table 3. Cronbach’s alpha is one of many methods to quantify reliability and measures the internal consistency. If a test is reliable, it will mini-mize the random measurement error. In this study, all factors have a Cronbach’s alpha, which is sufficiently high (see Table 3). For instance, involvement in risk management has an alpha of 0,871, which means that 12,9% of the variance is random and not mean-ingful. In addition, Table 4 represents the division within the variable sector, in which most respondents (24) were from the sector Industry.

Table 3: Descriptive Statistics

Table 4: Sector

The correlations between the variables can be seen in Table 5. Regarding the concep-tual model, the correlation table shows that an increase in environmental uncertainty is significantly related with an increase in involvement in risk management (r =,457; p<,01). There was no significant correlation between the other independent variables and in-volvement in risk management. Furthermore, there was no significant correlation be-tween the dependent variable involvement and the control variables. Another finding is that organizational structure positively correlates with the sector Wholesale (r=,240; p<,05), meaning that in this sector, the company has a more centralized structure than

Frequency Percent Cumulative Percent

Industry 24 24 24

Other 17 17 41

Financial Services 13 13 54

Transport & Logistics 11 11 65

Retail 9 9 74 Consulting 9 9 83 Automotive 6 6 89 Wholesale 4 4 93 Construction 2 2 95 Non-Profit 2 2 97 Government 1 1 98 Tourism 1 1 99 Insurance 1 1 100 Total 100 100 SECTOR

N Valid Mean Median Std. Deviation Variance Minimum Maximum Alpha

Involvement 96 4,7222 4,6667 1,30936 1,714 1,83 7 0,871

Environmental Uncertainty 100 4,4925 4,25 1,12953 1,276 1,5 7 0,776

ORGSTRUCT 97 3,666 4 1,4716 2,166 1 6,4 0,861

Firm Size 99 9623,5152 450 27972,54504 782463276,1 1 160000

Presence of Risk Manager 100 1,37 1 0,485 0,235 1 2

Business Unit Size 97 61,9175 12 153,21109 23473,639 1 1000

Relative Size 96 296,331 18,3344 1121,678 1258161,536 1 7272,73

in any other business type. A further correlation can be found between the sector Auto-motive and firm size (r=,524; p<,01), indicating that participated companies in the sector Automotive have a higher number of employees. Additionally, the presence of a risk manager negatively correlates with the sector financial services (r=,219; p<,05). That means the possibility that a risk manager is present is lower within the sector financial services.

Table 5: Correlation Matrix

5.2 Regression results

In the chapter before, the correlation results were presented. By means of correlation, the strength of a relationship between two different variables were calculated, without establishing a causal relationship. In the regression analysis, a causal relationship can be identified, as it has to be determined which variable is predicted by another variable (Bortz & Döring, 2006). In order to test the hypotheses, several regression analyses have been carried out.

The first regression analysis has been carried out with the control variable sector. Dummy variables had to be created to test if a sector has a significant relationship with the dependent variable (involvement in risk management). The consulting sector was used as a reference. The result illustrates no effect (see Appendix). For that reason, the control variable sector was no longer included in the subsequent regression analyses.

In Table 6, the results for the second regression are tabulated. The results for the main effects (independent variables) indicate that with higher environmental uncertainty, the involvement of management accountants in risk management increases. Therefore, hy-pothesis 1 is supported. However, no other independent variable was positively or neg-atively associated with involvement in risk management. Therefore, H2, H3, and H4 are not supported.

Table 6: Regression Analysis 1

Step and variables B SE Sign. B SE Sign.

Intercept 4.549 0.149 0 2.364 0.761 0.003

Control

Business Unit Size 0.002 0.001 0.112 0.002 0.001 0.19

Relative Size 0 0 0.387 6.98E-05 0 0.671

Main effects

Environmental Uncertainty 0.506* 0.11 0.000

Organizational Structure 0.04 0.088 0.65

Firm Size -1.62E-06 0 0.822

Presence of Risk Manager -0.141 0.262 0.592

R-Square 0.035 0.237

R-Square Change 0.035 0.202

* Significant at the level 0.01 (2-tailed)

Regression Results

Finally, a third regression was done to test for the moderator effect in Table 7. The results indicate that there is no significant interaction between the presence of risk manager and firm size on the accountant’s involvement in risk management. Therefore, the data pro-vide no epro-vidence to support H5. Overall, only the relationship between environmental uncertainty and influence in risk management is significant. The other variables are not significant.

Table 7: Regression Analysis 2

6. Discussion and Conclusion

The aim of this research was to examine a context, in which management accountants are more involved in risk management. Although the existing literature gives not enough insights about relevant factors, in this study, it was expected that environmental uncer-tainty, organizational structure, firm size, and the presence of a risk manager are influ-encing the extent to which controllers execute the task of a risk manager.

Regarding hypothesis 1, the positive relationship between environmental uncertainty and involvement in risk management was supported. As Hopper already indicated in 1980, controller act in the role that is expected by the environment. To combine risk manage-ment with the controlling function is getting more and more important in order to be able to act as fast as possible on rapid environmental changes (Hall et al., 2015). However, due to a significant finding which is consistent with the results from previous literature (Byrne & Pierce, 2007; Chang et al., 2014; Braumann, 2018; Subramaniam et al., 2011), we know by now that in a dynamic environment, accountants act more in the sense of a risk manager. In particular, it means that a higher environmental uncertainty leads to higher involvement in risk management; thus, H1 is supported. Moreover, this finding

Step and variables B SE Sign. B SE Sign. B SE Sign.

Intercept 4.555 0.148 0 4.539 0.171 0 4.412 0.211 0

Control

Business Unit Size 0.002 0.001 0.098 0.002 0.001 0.171 0.002 0.001 0.115

Relative Size 9.91E-05 0 0.393 0 0 0.454 0 0 0.216

Main effects

Firm Size -0.06 0.217 0.782 -0.395 0.392 0.316

Presence of Risk Manager -0.116 0.139 0.407 -0.191 0.157 0.227

Two-way interaction

Firm Size x CRM -0.32 0.312 0.308

R-Square 0.045 0.056

R-Square Change 0.008 0.012

* Significant at the level 0.01 (2-tailed)

Model 3

Regression Results

0.037

Model 1 Model 2

does not seem to be sector related, as it does not depend on one of the mentioned sectors.

Regarding organizational structure, scholars assumed that the structure of a company has significant impacts on the different roles’ accountants execute (Zoni & Merchant, 2007; Chang et al., 2014); more specific, in a decentralized organization, controllers have more influence and perceive the need to enhance their role (Järvenpää, 2007; Lambert & Sponem, 2012; Granlund & Lukka, 1998). However, this relationship could not be found in this research; the data provide no support for hypothesis 2. One possible reason for this finding is that participants associate with risk management only strategic risk management, which is clearly initiated by the headquarter. That’s why accounting departments which are more intertwined with the headquarter, are simultaneously more involved in risk management; whereas accounting departments which are less inter-twined with the headquarter are less involved in risk management activities. Therefore, it is possible that the two effects cancel each other out and that in this study, no signifi-cant relationship could be found.

Contrary to what was assumed in this research (Chang et al., 2014; Byrne & Pierce, 2007), the data of this study found no effect of firm size on the involvement in risk man-agement. Although Chang et al. (2014) showed a significant correlation with the involve-ment in risk manageinvolve-ment, here, there seemed to be no significant relationship. Even the indication of Granlund & Lukka (1998) that smaller organizations are more open for role changes, cannot be found. Therefore, hypothesis 3 is not supported. One explanation could be that there exist also several reasons why controllers in larger companies are more involved in risk management (Chang et al., 2014; Beasley et al., 2005). So far, it is not clear what kind of factor drives the effect of firm size in other studies. It could be possible that several factors work together or even only a few are relevant. However, the results indicate that the factor firm size alone cannot determine the influence in risk man-agement.

To conclude, the expected relationship in previous literature between firm size, organi-zational structure, the presence of a risk manager and the accountant’s involvement in risk management is not found in this research. The expected relationship between envi-ronmental uncertainty and the involvement in risk management, however, is found. Therefore, according to this research, the contextual factor environmental uncertainty does matter, whereas organizational structure, firm size, and presence of risk manager do not.

The research question “What is the context in which risk management is included in the

tasks of the management accountants?” can be partly answered. In an environment,

which is characterized as highly uncertain and dynamism, risk management is increas-ingly included in the tasks of management accountants. However, other factors can also determine the involvement in risk management, which needs to be further investigated.

6.1 Theoretical implication

The theoretical implications are not only that the assumed relationship between the three mentioned contextual factors (firm size, organizational structure, the presence of risk manager) and the involvement in risk management is not found, but also that the rela-tionship between the factor environmental uncertainty and involvement in risk manage-ment is significant. These findings can be added to the existing theory.

6.2 Practical implication

Controllers, who also want to take part in risk management activities, should look for a company, which operates in a highly uncertain environment. With regard to managerial implications, managers do not necessarily have to change the role of management ac-countants – there are also many other external and internal components that determine the inclusion of risk management in the task of controllers.

6.3 Limitation and further research

be expected. A further limitation refers to the instrument itself. Some parts of the survey were self-established. In particular, the questions for the importance of risk management were reformulated to establish questions that measure the involvement in risk manage-ment of an individual person. Although the reliability and validity from the combined ques-tions were good, it probably would be possible to develop a more comprehensive instru-ment.

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Appendix

Appendix 2: Factor analysis

1) Involvement

2) ENVU

3) ORGSTRUCT

Involvement in Risk Management 1 IRM_4 0,885 IRM_6 0,806 IRM_3 0,774 IRM_2 0,771 IRM_5 0,755 IRM_1 0,697

Extraction Method: Principal Component Analysis. a. 1 components extracted. Component Matrixa Environmental Uncertainty 1 ENVU_4 0,823 ENVU_2 0,797 ENVU_5 0,78 ENVU_1 0,722 ENVU_3 0,68

Extraction Method: Principal Component Analysis. a. 1 components extracted. Component Matrixa Organizational Structure 1 ORGSTRUCT_2 0,87 ORGSTRUCT_5 0,867 ORGSTRUCT_1 0,848 ORGSTRUCT_4 0,819 ORGSTRUCT_3 0,569

Extraction Method: Principal Component Analysis. a. 1 components extracted.

Appendix 3: Regression Sector

Model Sig.

1 B Std. Error Tolerance VIF

(Constant) 4,593 0,444 0 Industry 0,614 0,53 0,25 0,384 2,604 Construction -0,843 1,041 0,42 0,836 1,197 Automotive -0,315 0,702 0,655 0,64 1,562 Wholesale 0,116 0,8 0,885 0,722 1,384 Retail -0,426 0,628 0,499 0,552 1,812 TransportLogistics 0,483 0,598 0,422 0,508 1,968 FinancialServices -0,051 0,587 0,931 0,49 2,042 NonProfit 0,741 1,041 0,479 0,836 1,197 Government 0,407 1,403 0,772 0,909 1,1 Tourism 1,241 1,403 0,379 0,909 1,1 Insurance -0,593 1,403 0,674 0,909 1,1 AnotherSector -0,044 0,549 0,937 0,421 2,377

a. Dependent Variable: INV

Unstandardized Coefficients Collinearity Statistics