Amsterdam Business School
The effect of Human Capital Intensity on Management Control
System in Professional Service Firms
Name: Andrej Nabergoj Student number: 10708529
Thesis supervisor: dr. ir. S.P. Sander van Triest Date: 20 June 2016
Word count: 20190
MSc Accountancy & Control, specialisation Control
Statement of Originality
This document is written by student Andrej Nabergoj who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
Acknowledgments
I am very grateful to my supervisor dr. ir. Sander van Triest for his support, encouragement, suggestions and the many pleasant meetings we had throughout the year. I would also like to thank Ms Helena Kloosterman, who introduced me to the topic of professional service firms, and made joining this project possible.
Many thanks also to my parents, Jurij and Lucija, for their unconditional support and motivation throughout the thesis process.
Last but not least, I thank my dear friend Nathan for his help with the English language.
Andrej Nabergoj Amsterdam, June 2016
Abstract
This master’s thesis uses the survey method to investigate the influence of human capital intensity on the design of MCS in PSFs. To the best of my knowledge, this is the first study which explicitly examines the role of knowledge in this organizational context. MCS was conceptualized in terms of eight construct, distinguishing between two dimension of control tightness (explicit and implicit), and four sets of controls (action, results, cultural, and personnel). Questionnaires were distributed to experienced professional workers employed in different industries within the PSFs sector. Using multiple regression analysis, the results indicate a significant positive relationship between human capital intensity and all control tightness constructs, except for implicit personnel control tightness.
Keywords: Professional Service Firms, Professionals, Human Capital Intensity, Knowledge,
Autonomy, Management Control System, Management Control System Tightness, Explicit Control Tightness, Implicit Control Tightness
Contents
1 Introduction ... 6
2 Literature Overview ... 8
2.1 Knowledge and Knowledge-Intensive Firms ... 8
2.1.1 Knowledge ... 8
2.1.2 Knowledge-Intensive Firms ... 9
2.1.3 Difference between Knowledge-Intensive and Professional Service Firms ... 11
2.2 Professional Service Firms ... 11
2.3 Professionals and Human Capital Intensity ... 14
2.4 Management Control System ... 16
2.4.1 Management Control System tightness ... 20
2.5 Development of Hypotheses ... 22
3 Methodology ... 27
3.1 Sample Selection ... 27
3.2 Survey Design ... 29
3.2.1 Preliminary Survey Testing ... 30
3.2.2 Independent Variable ... 30 3.2.3 Dependent Variables ... 30 3.2.4 Control Variables ... 32 3.3 Validity Analysis ... 33 3.4 Statistical Model ... 39 4 Results... 40 4.1 Descriptive Statistics ... 40 4.2 Correlation Analysis ... 41 4.3 Regression Analysis ... 43
5.1 Discussion of Findings ... 48
5.2 Limitations... 50
5.3 Implications for Future Research ... 51
References ... 53
1 Introduction
Over the last twenty years, the world has been moving towards a so-called “post-industrial economy” – a move led by the growth of the business service sector and increased importance of knowledge-intensive firms (Ditillo, 2004), which can be recognised in their contribution to the gross domestic product of advanced economies, as well as in the percentage of people employed in services (Verma, 1997). Regardless the increased importance, however, the services sector is yet to be studied extensively, as Ditillo (2004) suggests that research has only just begun to scratch the surface of this area of business.
The emergence of Knowledge Age and professional service firms (PSFs), as the primary example of knowledge intensity (Von Nordenflycht, 2010), has caused intellectual capital to increase in importance and replace land, physical, and financial capital as the main factor of production (Chang and Birkett, 2004; Ulrich, 1998; Fitzgerald at al., 1991). Throughout the years, different authors have tried to define PSFs, causing uncertainty around the extent of the term PSF, and leading to a variety of definitions. Despite the differences, one thing can indeed be generalised from them – PSFs’ capital consists predominantly of human capital, making it their most important resource (Ditillo, 2004).
The reason why human capital is so important in PSFs is that it embodies knowledge, which is the most critical competitive asset that a firm possesses (Grant, 1996; Hitt et al., 2001, Von Nordenflycht, 2010). Consequently, human capital is defined as the knowledge, skills and abilities residing with and utilised by individuals (Subramaniam and Youndt, 2005, p. 451), making human capital intensity an appropriate alternative label to knowledge intensity (von Nordenflycht, 2010). This reliance on human capital is what makes PSFs different from other types of firms, as they need to employ a high percentage of highly educated people, and depend on their ability to attract, mobilise, develop, and transform the knowledge of employees in order to provide value for customers (Løwendahl et al., 2001). Hence, PSFs are less capital-intensive, and more learning-intensive than other firms (Nurmi, 1998), and are therefore considered interesting to study as they face a distinctive environment, demanding distinctive theories of management (von Nordenflycht, 2010).
Little research has focused specifically on the issue of management and control in knowledge-intensive firms (Ditillo, 2004), although different authors (Alvesson, 2000; Empson, 2001; Goodale et al., 2008) suggest that management of knowledge workers, or professionals, as they are referred to in the context of PSFs, will differ from management of “ordinary” employees. This is due to the nature of professionals who resist management controls and demand more autonomy
over their work, since they believe they can work autonomously and without supervision because of the high level of knowledge they possess (Kerr et al., 1997; Raelin, 1985; Von Nordenflycht, 2010). The sheer importance of knowledge has been stressed throughout the literature on PSFs and management control, however research did not advance significantly from there, leaving the role, and the impact of knowledge in developing a management control system (MCS) somewhat overlooked (Morris and Empson, 1998).
The purpose of my master’s thesis is thus to investigate whether human capital intensity, as a main source of knowledge, plays a role in the development of MCS in PSFs. More specifically, my research question is:
Is the tightness of the management control system in professional service firms affected by the level of human capital intensity?
This study contains three contributions to the existing literature. First, it develops and adds to the scarce literature on PSFs by adding knowledge on human capital intensity and its role in developing a MCS in PSFs. As Morris and Empson (1998) point out, knowledge is central to the distinctive identity of PSFs, but its role has not been a major focus in the research on these firms. Secondly, Malmi and Brown (2008) hint that there is limited understanding in the literature about other types of control, as only accounting-based controls have been studied extensively. By using the framework proposed by Merchant and Van der Stede (2007), which distinguishes between results, action, cultural, and personnel controls, we therefore contribute to the understanding of the role of other controls, especially in PSFs. Moreover, this study contributes to the literature on control tightness, since it uses a new concept, which distinguishes between explicit and implicit tightness. Lastly, the study answers the calls for studying PSFs in various industries, as most of the previous research in this field used data from one industry, and applied the results to the whole sector of PSFs (Von Nordenflycht, 2010).
The rest of the paper is structured in the following manner: In the following section, the relevant literature is examined to provide the background for the development of hypotheses, which conclude the section. Section 3 contains the procedures of the empirical analysis, followed by Section 4, where I present my findings. Lastly, Section 5 contains the discussion of the results, the study’s limitations, and implications for future research.
2 Literature Overview
Knowledge intensive firms such as PSFs are different from manufacturing or more routinised service companies, especially when talking about their people management practices (Robertson and O’Malley Hammersley, 2000). Due to their expertise, skills, and also the nature of their work, Robertson and O’Malley Hammersley (2000) point out that managing knowledge workers requires peculiar approaches, which differ significantly from traditional methods.
In order test these assumptions, an overview of the literature will first be given as a foundation for analysing MCSs in PSFs. The first part of this section therefore summarises research to date on knowledge-intensive firms and the way they utilise and manage knowledge, followed by the investigation into PSFs, professionals and the related human capital intensity. Next, the relevant literature on MCSs is summarised and MCS tightness is defined. The section is concluded with the development of hypotheses in order to establish the relationship between human capital intensity and MCS tightness.
2.1 Knowledge and Knowledge-Intensive Firms
2.1.1 Knowledge
Change in society, work, and organisations suggests an increased importance of knowledge, which is shown by the increase in the number of knowledge-intensive organisations and increased importance of knowledge-intensive work (Alvesson, 1993). The switch in the world economy from production to services, has therefore also led to a switch in research, which has slowly turned to investigating knowledge and knowledge management. Many have tried to define and classify knowledge and knowledge intensity, but the problem with doing so, as seen by Alvesson (1993), is that it is very difficult to know where and when to stop including elements, which becomes even harder when moving from the individual to the organisational level. The literature on the subject provides many dimensions of knowledge, such as embodied versus embedded knowledge, knowledge as intrinsically versus instrumentally valuable, and explicit versus tacit knowledge (Løwendahl et al., 2001). In their research, Løwendahl et al. (2001) view knowledge as a very broad term and include both tacit and explicit knowledge, as well as an analysis on both an individual and organisational level. On an individual level, they identify three forms of knowledge:
Information-based, explicit, task-related knowledge – “know what” Experience-based, tacit, subjective knowledge – “know how” Personal knowledge; consisting of talent, abilities, creativity, etc.
On the collective level they view knowledge as the skills, routines, norms and values shared by at least two employees, their individual knowledge, and the information at their disposal. This knowledge is heavily influenced by the socialisation process and activities (Alvesson, 1993; Løwendahl et al., 2001). Furthermore, they state that such knowledge frequently involves the development of values guiding individual behaviour, and firm’s formal, as well as informal, planning, controlling, and coordinating system. Knowledge is recognised by many researchers as very difficult to define, but is nevertheless considered a robust and substantial capacity, capable of producing “good results” (Alvesson, 1993). In line with this, Morris and Empson (1998) view knowledge as information which professionals acquire through experience and training, along with judgment, which is developed over time and enables them to deploy information effectively in order to deliver client services.
2.1.2 Knowledge-Intensive Firms
Beside the decline of capital and labour-intensive industries, Empson (2001) points out another reason for the increased focus on knowledge and knowledge management – organisation’s need to identify sources of knowledge, and develop procedures to enable the spread of knowledge among all members of the organisation. In this respect, Ditillo (2004) identifies two perspectives on knowledge management found in the literature. The first perspective is related to the emergence of the knowledge-based theory of the firm, on the basis of which knowledge, and the capability to create and utilise knowledge are seen as the most important resources of competitive advantage. This view is shared by many authors (Robertson and O’Malley Hammersley, 2000; Empson, 2001; Lin et al., 2012), who advise organisations to pay careful attention to knowledge management, due to the importance of knowledge. Ditillo (2004) suggests that a management control mechanism will only be effective in knowledge-intensive firms if it is able to perform both the coordination, and the knowledge integration roles.
The second perspective found in the literature, however, focused on defining knowledge-intensive firms and explaining their organisational and management features. With regard to this, Ditillo (2004) defines knowledge-intensive firms as those organisations that use mainly the knowledge and expertise of their individuals to develop and trade innovative responses to customers’ requirements. Similarly, Alvesson (2000) describes them as companies where most work can be said to be of an intellectual nature and where well-qualified employees form the majority of the workforce. Starbuck (1992), however, takes a slightly different approach and looks at knowledge rather than people. He suggests that in such firms, knowledge is more important than other inputs, and human capital prevails over physical and financial capital. In fact, Lin et al. (2012) stress that
such firms compete on the basis of their knowledge, rather than capital or labour intensity. Analysing these definitions, Ditillo (2004) summarises the most important characteristics of knowledge-intensive firms:
Capital consists predominantly of human capital Their critical elements are in the minds of individuals Heavy demands are made on the knowledge of employees
In line with the second characteristic, he explains further that knowledge in such firms is mainly embedded in human capital, even though it can also be institutionalised in the form of work methods, routines and processes.
In fact, organisations are seen as the repositories of knowledge through routines, procedures, norms and rules (Grant, 1996; Morris and Empson, 1998), and it is therefore essential for knowledge-intensive firms to integrate and share individual knowledge throughout the organisation if they want to gain the most from their human capital, and compete effectively in the marketplace (Swart and Kinnie, 2003). Swart and Kinnie (2003) make a distinction between human capital, which incorporates individual tacit, as well as explicit, knowledge, and social capital, consisting of knowledge embedded in organisational relationships and routines. In their opinion, sharing and integrating knowledge within organisations depends on building social capital. There are, however, obstacles to this integration, as individual knowledge is often unique, and difficult to imitate, substitute, or transfer (Løwendahl et al., 2001). To overcome this problem, Løwendahl et al. (2001) propose that different types of knowledge require different knowledge transfer mechanisms, involving knowledge sharing, as well as knowledge creation processes, both necessary to augment the total knowledge base of the firm. They present the following mechanisms:
Socialisation: used to transfer tacit knowledge, which cannot be directly transferred (Grant, 1996), and can only be shared through interpersonal interaction.
Codification: used to share, transfer, and store explicit individual knowledge. Morris and Empson (1998) see it as means by which knowledge is appropriated and replicated across the organisation. In their opinion, the objective of codification is to standardise behaviour and skills, which can be done by creating manuals and databases, organizing training, etc. They, however, argue that codification only works if knowledge can be meaningfully captured and used by others in order to add value.
Personalisation: a knowledge development strategy emphasizing the development of personal knowledge, which cannot be transferred, except maybe symbolically (e.g. mimicking behaviour of others).
Swart and Kinnie (2003) see HR processes as a facilitator of social capital, helping to overcome the obstacles of knowledge sharing. These processes are designed to create complementarity between the needs of individuals (growth and development), and the organisations’ need to share knowledge, making it in employees’ own interest to share knowledge. The ability to both extract as much explicit knowledge as possible, through the process of codification, and encourage the sharing of tacit knowledge is therefore crucial for an organisation (Løwendahl et al., 2001).
2.1.3 Difference between Knowledge-Intensive and Professional Service Firms
Looking back at the definitions of knowledge-intensive firms, there is a tendency to equate them with PSFs. There is a significant overlap in the definition of the categories (Ditillo, 2004), as an expansive definition of PSF – any firm reliant on a workforce with substantial expertise – would actually equate to the definition of knowledge-intensive firms (Von Nordenflycht, 2010). However, Von Nordenflycht (2010) as well as Ditillo (2004) both emphasise that the term “profession” in PSF is defined on the basis of multiple features (e.g. code of ethics, professional association, market regulation, etc.), of which a specific knowledge base is only one. A knowledge-intensive firm may not be a PSF, just as well as an expert may not be a professional (Starbuck, 1992). The knowledge-intensive firm category is therefore broader, and does not include only PSFs, but all organisations where application of knowledge leads to the creation of customised solutions for customers (Empson, 2001). Often described as extreme examples of knowledge intensity, PSFs are regarded as models for the increasingly knowledge-based economy (Von Nordenflycht, 2010). This perspective is shared by Empson (2001) as she points out that professional services are considered the best example of knowledge management, because knowledge has long been recognised as the focus point within PSFs, representing both the input and output of the firm.
2.2 Professional Service Firms
The term PSF is used to describe organisations involved in a variety of activities from software production, engineering, and architecture, to law, audit and accounting, consulting, and advertising (Greenwood and Lachman, 1996). PSFs have been considered by several authors, but despite similarities, the literature is not completely uniform on what the term PSF exactly consists of. In fact, the differences are also present in the papers written by the same authors, as evident from Løwendahl (1997), where he describes the typical characteristics of professional services. Later,
Løwendahl at al. (2001) however, argue that the list defines only the “ideal type” professional services, and that not all the PSFs actually deliver such ideal services, implying a broader use for the term. Kerr et al. (1977) explain that this inconsistency is caused by the lack of agreement between researchers, as the label “profession” has been applied to occupations based on diverse and arbitrary criteria.
Struggling with this ambiguity surrounding PSFs, Alvesson (1993) looks at the old, strict definition of profession and identifies the following features:
Characterised by a systematic, scientifically-based theory Long formal education
Autonomy Ethical rules
Distinct occupational culture Client-orientation
Socially sanctioned and authorised
A significant amount of occupations, which are nowadays considered to be professions (e.g. lawyer), would fall short of this classification. In his opinion, only the likes of physicians, vets, dentists, and psychologists would qualify as true professionals. He suggests that the criteria for distinguishing between professionals and non-professionals have been significantly weakened nowadays, which is a view shared by Greenwood and Lachman (1996). They say that the expansion of professions, both in size and scope, has reached a point where any occupation with some claim to a level of specialised knowledge is declared to be a profession. This expansion is therefore what caused the disagreement between researchers mentioned earlier, and led to several definitions of PSFs.
Greenwood et al. (2005), for example, define PSFs as those firms whose primary asset is highly educated (professional) workforce, and whose outputs are intangible services encoded with complex knowledge. In his opinion, the ability to manage knowledge is critical for the success of the firm. PSFs are similarly defined by Chang and Birkett (2004), although their approach leans more towards the definition of knowledge-intensive organisations, as they do not explicitly include professional workforce. They define PSFs as knowledge-intensive organisations that provide expert advice and services to clients. These services often require firms to develop innovative and creative solutions, since clients have different needs and a PSF must be able to satisfy them. Løwendahl et al. (2001) however, state that PSFs must generate value not only for clients, but also
different approach, Malos and Campion (1995) define PSFs as autonomous, self-owned organisations, managing and developing human resources through a system of professional apprenticeship.
To address these differences in the definitions, and in the lists of included occupations, Von Nordenflycht (2010) identifies three key characteristics of PSFs: knowledge intensity, low capital intensity, and professionalised workforce. He does not give a singular definition, as some firms could rank high on one characteristic, but low on another one. He therefore proposes the use of degree to which a firm possess each of these characteristics, in order to embrace the broader meaning of PSF. His approach is in line with the approach proposed by Kerr et al. (1977), where occupations are classified on a professionalisation continuum and not classified as either professional or non-professional.
Von Nordenflycht (2010) identifies knowledge intensity as the most fundamental characteristic, indicating that the firm’s output relies on a substantial body of knowledge. In his study, he defines this body as the employees, implying that they are PSFs’ most important asset. Based on the fact that PSFs rely on an intellectually skilled workforce, he proposes the term human capital intensity as an alternative label to knowledge intensity. He argues that this interpretation of knowledge is most appropriate for PSFs, as a broader definition (knowledge also embedded in equipment, products and organisational routines) would lead to the inclusion of an overly extensive list of firms. Even though he views the other two characteristics as less important, they are still significant in distinguishing between PSFs and knowledge-intensive firms, as already mentioned in the first part of this section.
Low capital intensity indicates that a firm’s production does not require significant amounts of non-human capital (equipment, inventory, patents, etc.), which is not necessarily true for any knowledge-intensive firm. The professionalise workforce characteristic however, is closely related to the characteristic of human capital intensity, the way Von Nordenflycht (2010) defines them. In fact, both characteristics include the feature of a knowledge base, represented by individuals bearing the knowledge. Nevertheless, professionalised workforce consists of two other features, which are the reason behind the term professional: regulation and control, and ideology. Regulation and control, or rather self-regulation, means that professionalised occupations have control over the practice of the occupation, with central associations approving membership into the profession based on demonstrated expertise and adherence to the ethical code (Von Nordenflycht, 2010). Ideology consists of norms and ethical codes that define appropriate behaviour for professionals, imposed by professional associations. This means that only possessing
specific knowledge is not by itself enough for an employee to reach the status of a professional, as a professional workforce characterises some but not all knowledge-intensive fields (Von Nordenflycht, 2010).
2.3 Professionals and Human Capital Intensity
Existing theories have recognised the importance of expert knowledge in the formation and survival of PSFs, but have not fully explained its role, as Morris and Empson (1998) mention in their paper, while arguing that knowledge is a key determinant of the organisational structure and performance of PSFs. Knowledge, together with skills and abilities, is defined as the human capital of PSFs, since it resides within, and is applied by, professionals (Subramaniam and Youndt, 2005). Hitt et al. (2001) argue that professionals obtain knowledge from their education, as well as through work experience. In their opinion, professionals coming from the best universities are expected to have more and better knowledge, and also more potential to learn and accumulate new knowledge. Besides, professionals are self-motivated, self-directed, and self-supervised (Covaleski et al., 1998), based on which they demand high levels of autonomy (Robertson and Swan, 2003, Goodale et al., 2008). Alvesson (2000) points out that, contrary to general belief, professionals are as committed and loyal as any employee, on the condition that organisations meet their expectations. He further argues that professionals are ideal employees, especially with regard to their work motivation and compliance. In line with this, Kerr et al. (1977) identify the following characteristics of an “ideal” professional, which have mostly been used in the literature:
Expertise: arising from specialised training and education Autonomy: right to make choices
Commitment: to work and the profession
Identification: with the profession and fellow professionals
Ethics: obligation to provide services without self-interest and without becoming emotionally attached to client
Collegial maintenance of standards: perceived commitment to control the conduct of fellow professionals
Professionals, as the human capital of PSFs, generate the social and economic capital for the firm. They carry and generate the knowledge encoded in the services being offered and develop relationships with clients, critical for a sustained flow of work (Greenwood et al., 2005). The knowledge they possess is actually both an input and an output of the PSF. It is an input in the
term of the expertise residing in the firm, and an output in the form of products or services generated to solve client problems (Grant, 1996).
As Hitt et al. (2001) claim, human capital is PSFs “most important resource”. This importance of human capital intensity causes management dilemmas because firm’s assets walk out of the door each day, leaving some questions whether they will return (Coff, 1997). Unlike tangible assets, firms cannot own employees, who are free to quit at will if they become dissatisfied, underpaid, or demotivated (Coff, 1997). Professionals are aware of their high mobility and consequent dependence of PSFs on them (Greenwood et al., 2005), which gives them a strong bargaining position when it comes to the issue of management control.
Raelin (1985) reveals that professionals do not like being controlled, and in fact resist controls and demand high levels of autonomy over their work. After examining their education and early socialisation experiences, he identifies five features that lead professionals to such behaviour and that require special attention by managers:
Autonomy over end as well as means: Professionals wish to decide on their own, without external pressure from people outside the profession, including their managers, as they believe they possess superior knowledge and can therefore work independently, without supervision.
Overspecialisation of technical skills: Professionals tend to become overspecialised in their role, which makes them distinct. Management may make things worse by specializing jobs, which hinders the integration process of professionals into the organisation. Furthermore, if there is a change in the required skills, due to a change in the market, the professionals might find themselves redundant because they only possess very specialised skills
Overemphasis on professional standards of evaluation: Professionals wish to be evaluated based on the outcomes of their activities and not on conformity to the rules and regulation of the organisation. Furthermore, they believe they should be assessed based on conformity to professional standards, making only their peers qualified for evaluating their work.
Lack of interest in real-world practices: The transition from school to work is difficult for professionals, as the conditions of professional education are often not reflected in the working world, where their pursuit of knowledge is interrupted by bureaucracy.
Disregard of organisational procedures: Professional tend to disregard procedures implemented to standardise decision making, when these procedures constrain their practice.
Raelin (1985) argues that these features set professionals apart from other employees. This shows that the attributes that make employees the most important assets also make them difficult to manage, as their characteristics conflict with the organisation’s need for control. This is supported by Von Nordenflycht (2010) who suggests that professionals have preferences that conflict with the nature of bureaucratic organisation. Furthermore, he stresses that the preference for autonomy is not just one of the central professional norms, but is theorised to arise from knowledge intensity, independently of formal professionalisation.
The preference for autonomy and bargaining power of professionals make authority more problematic (Von Nordenflycht, 2010), and result in a complex managerial dilemma around how to balance autonomy with control and flexibility with efficiency (Robertson and Swan, 2003). This dilemma needs to be addressed by the firm if it wants to achieve a sustainable advantage (Coff, 1997). Resolving the dilemma should involve a subtler form of control based around normative processes and cultural control, rather than around hierarchy and structure (Robertson and Swan, 2003). Hitt et al. (2001) argue that, in turn, professionals will produce the highest-quality services to clients and thereby contribute significantly to the performance of the firm.
2.4 Management Control System
MCS is a system used to exert control over the attainment of organisational goals, while also enabling employees to search for opportunities and solve problems (Mundy, 2010). Control systems are crucial for all organisations, as Merchant (1982) points out that employees are not always able, or even willing, to act in the organisation’s best interest. If individuals always did that, management control would not be required. Control is therefore used by managers to increase employees’ goal congruence, and influence behaviour towards the achievement of desired objectives (Jaworski et al., 1993; Malmi and Bown, 2008).
MCSs have been heavily researched in the past, offering many categorisations of controls, such as: formal and informal controls; market, bureaucratic, and clan controls; action, result, personnel, and cultural controls; belief, boundary, diagnostic, and interactive controls; administrative and interpersonal controls; etc. (Ouchi, 1979; Jaworski et al., 1993; Simons, 1994; Merchant and Otley, 2007). In this paper I will not present all of them, as they are all related up to a certain point, but
will focus just on the categories most relevant for my research on professionals and management control.
Because of professionals’ desire for autonomy, managers find themselves in a dilemma, where adjusting the MCS for professionals could actually lead to positive outcomes for both sides. Robertson and O’Malley Hammersley (2000) state that conventional control approaches have not really addressed the issue of retaining a degree of managerial control, while encouraging creativity, autonomy and innovation.
In this sense, Adler and Borys (1996) distinguish between enabling and coercive bureaucracy, as the first one enables employees to perform their task better by providing guidance and clarifying responsibilities, while the later stifles creativity, fosters dissatisfaction and denies autonomy to individuals. In coercive bureaucracy, jobs are strictly defined, procedures are described in detail, and deviations from procedures are not allowed and punished. Enabling bureaucracy, meanwhile, allows employees to use creativity and to work outside the scope of their job. It also allows them to improve procedures and use them flexibly, since deviations from procedures are seen as learning opportunities. Applying this distinction in the use of bureaucracy to PSF, managers would need to apply the enabling bureaucracy in order to satisfy their employees’ need for autonomy and thus prevent them from leaving the firm.
Studying MCSs in service organisations, Auzair and Langfield-Smith (2005) recognise that the choice of the MCS is dependent on the type of service firm, business strategy, and stage in the organisational life-cycle. They conceptualise a MCS based on five dimensions: action versus result controls, formal versus informal controls, tight versus loose controls, restricted versus flexible controls, and impersonal versus interpersonal controls. Using these dimensions, they construct a MCS bureaucracy continuum, where one end is considered more bureaucratic and involves action, formal, tight, restricted, and impersonal controls, while the other end is less bureaucratic and involves result, informal, loose, flexible, and interpersonal controls. They find that mass service, cost leader, and mature firms put greater emphasis on more bureaucratic forms of MCS, than professional service, differentiator, and growth firms.
Concerned with the balance between control and autonomy in organisations, Simons (1995; 1994) proposes the levers of control framework, consisting of the belief, boundary, diagnostic, and interactive control system. The belief system is used to define and communicate the basic values and direction of the organisation through mission and vision statements, which empowers employees and gives them a sense of desired behaviour. The boundary system establishes limits and rules to be respected, through the codes of conduct and directives. Boundary systems are
stated in negative terms, as he believes that telling employees what not to do, rather than what to do, allows for innovation within defined limits. Together, belief and boundary systems create a dynamic tension by establishing direction and motivation for employees, but at the same time also controlling undesired behaviour. The diagnostic system is used to monitor performance and correct deviations from pre-set objectives. Lastly, the interactive system is used by managers to personally involve themselves in employees’ decisions. The purpose of the interactive system is to focus on strategic uncertainties, and to foster dialogue and learning. By using levers of control collectively, to reinforce one another, Simons (1995) believes that employees are given autonomy to innovate and be creative, but not at the expense of control. His framework is however, based only on formal controls, and does not encompass informal controls, such as group norms, socialisation, and culture.
To analyse MCSs in my thesis, I will use a more holistic approach, also including informal controls, and will therefore adopt Merchant and Van der Stede’s (2007) framework. They define management control as all devices or systems managers use to ensure that the behaviours and decisions of their employees are consistent with organisation’s objectives and strategies (2007, p. 5). These systems and devices are thus called MCSs. They distinguish between four types, based on object of control: action controls, results controls, cultural controls, and personnel controls. Action controls focus on employee behaviour to ensure that employees act in a way that is beneficial to the organisation. They are mechanisms that specify appropriate behaviour and processes, as well as mechanisms that allow to evaluate, such as direct observation (Turner and Makhija, 2006; Stouthuysen et al., 2012). Turner and Makhija (2006) state that action controls are most appropriate to use when an organisation can describe individual jobs with clearly specified and specialised tasks, and when managers know what behaviour is required to achieve strategic goals (Snell, 1992). Process controls are considered by Merchant and Van der Stede (2007) to be the most direct form of management control. They encompass highly formalised, standard, operating procedures and rules, clearly established routines, behavioural constraints, specialised job descriptions, hierarchical supervisor-subordinate relationship, etc. (Rockness and Shields, 1984; Abernethy and Brownell, 1997; Turner and Makhija, 2006; Merchant and Van der Stede, 2007; Malmi and Brown, 2008; Stouthuysen et al., 2012).
Results controls define performance measures and hold employees accountable for the delivered results, by rewarding or punishing them. Results controls therefore feature mechanisms to specify targets, as well as tools to measure performance in relation to them (Stouthuysen et al., 2012). Targets can be both financial or non-financial, and the control of performance consists of
monitoring and comparing the actual results with targets (Rockness and Shields, 1984) Use of these controls is not dependent upon identifying input-output relations, but requires only that desired outputs can be determined and quantified (Abernethy and Brownell, 1997). Results controls consequently facilitate decentralisation of control and empowerment, as they provide employees with discretion in the use of means to achieve targets, since actions are not constrained (Snell, 1992; Abernethy and Brownell, 1997). Merchant and Van der Stede (2007) imply that result controls influence actions, as they make employees worry about the consequences of their actions. Cultural controls refer to shared norms and values, and social pressure exerted by groups on individuals. Similarly, Turner and Makhija (2006) define them as informal socialisation mechanisms that take place in an organisation and promote shared values, beliefs, goals and understanding among organisational members, and consequently influence employees’ thoughts and actions (Malmi and Brown, 2008). Examples of these mechanisms are the use of rituals, ceremonies, and other socialisation processes, such as meetings and peer interaction (Turner and Makhija, 2006; Stouthuysen et al., 2012). Cultural controls are designed to foster mutual monitoring and group pressure on employees that deviate from the shared values and norms (Merchant and Van der Stede, 2007). Modell (1996) argues that they are appropriate to use in situations of high intangibility and intensive personal interaction. Additionally, these mechanisms can also be used to transfer tacit knowledge between employees (Løwendahl et al., 2001). Kaše et al. (2009) agree with this, as they see face-to-face interaction as a necessary condition for tacit knowledge transfer.
Personnel controls are implemented in the selection and placement of employees, as well as by the training process. They serve three basic purposes: clarify expectations, ensure that the employee is able to do a good job, and increase the likelihood that the employee will engage in self-monitoring. Personnel controls play an important role in aligning individual interests, with the interests of the firm, as they also have a socializing influence similar to cultural controls (Ouchi, 1979; Snell, 1992). Malmi and Brown (2008) in fact place selection under cultural controls, because organisations deliberately recruit individuals whose values match those of the organisation. Snell (1992), however, proposes a broader perspective, where selection and training processes do not regulate only the values of employees, but also their knowledge, skills, abilities, and motives. Merchant and Van der Stede (2007) recognise, with regard to selection, that the main challenge is to select and employ the right people, who are motivated by their own goals, which are congruent with the firm’s objectives.
Merchant and Van der Stede (2007) state that the main task of MCS is to lead to a higher probability that corporate objectives will be achieved. With regard to this, they introduce the concept of
control tightness, by which each type of controls can be used more tightly or loosely. In their opinion, tighter controls should provide a higher degree of certainty that employees will act according to the organisation’s wishes. This means that that a tight MCS should minimise the fault tolerance and degrees of freedom for employees.
2.4.1 Management Control System tightness
Control tightness is a construct of the control system, and has been addressed by several authors in the literature, which has led to an inconsistent definition and operationalisation of the concept (Van der Stede, 2001).
Wanting to design a framework for implementing a MCS in any firm, Amigoni (1978) identifies several factors and management control features that affect the control process. One of the features he identifies is the “style of control”, which is represented by the behaviour of managers in implementing the control system. He points out two different styles of control: tight or loose. He talks about a “tight style” when more administrative controls dominate over individual controls. This is apparent when employees’ participation in setting objectives is low, when targets are imposed and considered to be firm commitments, when performance evaluation is focused on accounting measures, etc. Rather, the style is “loose” when managers are aware of the social and individual side of control, employee participation in setting objectives is high, targets are negotiated and only considered to be reference points, and when performance evaluation is also done on the basis of multiple, non-qualitative factors.
Merchant (1982) analyses controls and hints that different controls can provide varying amounts of control. He claims that in order to make control more certain (or tight), this requires detailed specification of what is expected of each employee, prevention of undesired actions, effective and frequent monitoring, and significant penalties or rewards for employees.
The issue of control tightness is again addressed by Merchant (1985), and he similarly acknowledges that tight control limits the degrees of freedom of employees. He proposes the following attributes of tight control:
Definition of goals – more complete, specific goals that are congruent with organisational objectives
Communication of goals – communicate in a way that employees will better understand and accept organisational objectives (more effectively, timely, frequently, and convincingly) Monitoring – more frequent, detailed, and timely monitoring
Rewarding – enhance the value of reward and provide a stricter relationship between rewards and performance.
In studying tightness, however, Van der Stede (2001) takes a narrower approach, and focuses solely on tight budgetary control. He summarises Merchant’s (1985) and Anthony and Govindarjan’s (1998) views on tightness and determines the following features of tight budgetary control:
Much emphasis placed on meeting the budget
Budget revision not easily accepted during the budget period Detailed interest in individual line-items
Deviation from interim targets is not tolerated Intensive budget-related communication
Auzair and Langfield-Smith (2005) also use the concept of tight controls in their study. They define tight controls as ones where employees’ actions and targets are precise, timely, and frequently monitored. On the other hand, they describe loose controls as ones where employees’ actions and targets are infrequently monitored, and allow for discretion in achieving standards.
In this study, I will use a different concept of control tightness, which distinguishes between the distinct nature of attributes used in the aforementioned literature. On the one hand, a tight system can be defined as one that uses a lot of controls measures, which are frequently monitored. On the other hand, however, a tight system can be defined as one that puts a lot of emphasis on achieving the target and does not allow for deviations. This implies that control tightness is structured on two dimensions referred to here as explicit tightness and implicit tightness
Explicit tightness represents the extent of a MCS. A control system will be considered explicitly tight if it uses a large amount of result, action, cultural or personnel controls, complemented with frequent monitoring and supervision. Conversely, loose explicit controls will be achieved when there is a low number of controls in place and the supervision or monitoring is not frequent or constant.
Implicit tightness, on the other hand, is based on the degree of tolerance for deviating from the imposed controls. Implicit tightness is achieved when the emphasis on achieving the target is high, and tolerance for deviation is minimised. On the other hand, loose implicit tightness implies that controls and targets are thought of only as reference points, and the system allows for flexibility and deviation from controls and targets. An implicitly tight organisation is therefore closely related to what Butler et al. (1998) identify as a fuzzy organisation due to errors of looseness. In such a structure decision rules are seen as flexible and open to interpretation and change.
Van der Stede (2001) suggests that all types of control can be used more or less tightly, and that not all alternatives are equally effective. In order to study control tightness in the context of PSFs I therefore distinguish between eight tightness measures, based on Merchant and Van der Stede’s (2007) framework of MCSs. These measures are described as following:
Explicit action control tightness: the extent of use of standardised processes, procedures, rules and routines as part of the MCS
Implicit action control tightness: the degree to which deviation from established processes, procedures, rules and routines is tolerated and/or encouraged
Explicit results control tightness: the extent of use of goals, targets and performance measures as part of the MCS
Implicit results control tightness: the degree to which deviation from goals, targets and performance measures is tolerated and/or encouraged
Explicit cultural control tightness: the extent of use of employee socialisation procedures as part of the MCS
Implicit cultural control tightness: the degree to which the employees’ norms, value and beliefs are congruent with the norms, values and beliefs of the organisation
Explicit personnel control tightness: the extent of use of employee selection procedures as part of the MCS
Implicit personnel control tightness: the degree to which deviation from human resource standards is tolerated
Tightening the controls may ensure that employees follow organisations’ wishes, however, it may also constrain creativity and result in dysfunctional behaviour (Auzair and Langfield-Smith, 2005). MCS tightness represents a managerial decision, which should especially be considered in PSFs, because of the “unique” importance of employees to the firm. In this case it is not necessary that a tighter control system will provide higher certainty of the desired outcome, as some controls might have to be loosened, if PSFs are to operate efficiently.
2.5 Development of Hypotheses
PSFs face a distinct operational challenge due to the type of their work and the nature of their employees (Goodale et al., 2008), which are central to the distinctive identity of PSFs because of the knowledge they possess. As Robertson and Swan (2003) suggest, knowledge is generally accepted as the primary asset of PSFs, and many authors stress the importance of managing knowledge. Nevertheless, Morris and Empson (1998) claim that the role of knowledge has not
been the focus of research in these firms, meaning that there is still no evidence if human capital intensity is taken into consideration, when developing a MCS.
There are several reasons why managers would adapt the MCS to the needs of professionals. Firstly, the main reason is potentially increased performance. Effective management of human capital is crucial for a firm seeking to increase performance (Lin et al., 2012). Knowledge needs to be integrated and managed in order to be productive and create value (Ulrich, 1998; Hitt et al., 2001). Secondly, as Greenwood et al. (2005) point out, it is expensive for PSFs to lose employees, especially seniors. This is not just because it reduces the ability of the firm to deliver customised services, but also because it could lead to losing clients, which might follow the employee (Alvesson, 2000). Lastly, losing employees also concerns investors, since the main asset is leaving the firm and making their investment vulnerable (Von Nordenflycht, 2011).
Action Control Tightness
Professionals are hard to direct and have a strong preference for autonomy, arising from knowledge intensity, as stated by Scott (2008) and Von Nordenflycht (2010). Consequently, they have a distaste for supervision, and do not feel obliged to follow formal organisational processes, since knowledge provides them with high levels of skills and employment opportunities should they want to leave (Goodale et al., 2008). In fact, firms may display more informality in organisational processes and give professionals more freedom to satisfy their preference for autonomy (Von Glinow, 1983; Von Nordenflycht, 2010). Merchant (1982) and Whitley (1999) explain that firms trust employees’ competence, as they can be expected to perform satisfactorily without the need for tight control over their behaviour. Implementing tight action controls impedes professionals from applying their knowledge and creativity, and consequently prevents organisational innovation (Chang and Birkett, 2004). The same opinion is shared by Campbell et al. (2010), who provide results that tight monitoring prevents organisations from learning. He further adds that tighter monitoring leads to increase in employee termination, which was also found by Robertson and O’Malley Hammersley (2000). Based on this, it seems necessary for PSFs to allow professionals autonomy over their work, and I therefore predict the following:
H1a: Human capital intensity is negatively related to explicit action control tightness H1b: Human capital intensity is negatively related to implicit action control tightness
Results Control Tightness
Drawing on his research and consulting activities, Raelin (1985) found that professionals understand management’s need to establish organisational goals and to specify how the units in
the organisation will interact to accomplish these goals. However, once the goals are set, professionals wish to proceed independently, as they will by nature object to any constraints. If anything, they prefer control to be exerted at the point of output. He states that managers in many cases understand professionals’ need for autonomy and often decide to selectively apply controls in order to satisfy their needs. In line with this, Merchant and Van der Stede (2007) state that result controls are a necessary system to empower, but also control the behaviour of professional employees. Similarly, Coff (1997) indicates that supervisory monitoring is not a viable option for managing human assets, but can however be substituted by making employees’ earnings contingent on profitability or performance outcomes. This directs their efforts toward the interests of the firm, without the need to incur high monitoring costs in dealing with the managerial dilemma. Merchant and Van der Stede (2007) provide another benefit of using result controls for professionals. They hint that result controls will also help attract employees confident of their abilities, because such controls usually offer high rewards for good performers. Ouchi and Maguire (1975) furthermore highlight the preference of professionals for output controls by suggesting that they will attempt to present as many objective measures as possible, in order to support their claim of satisfactory performance when they feel that superiors are only vaguely able to evaluate them. It seems that PSFs will therefore compensate the given autonomy to professionals by applying more, and stricter results controls. Accordingly, I anticipate the following:
H2a: Human capital intensity is positively related to explicit results control tightness H2b: Human capital intensity is positively related to implicit results control tightness
Cultural Control Tightness
A major challenge for PSFs involves extracting and codifying as much explicit knowledge as possible from employees, and simultaneously encouraging them to also share tacit knowledge among co-workers (Løwendahl et al., 2001). Subramaniam and Youndt (2005) suggest that individual knowledge by itself provides little benefit to organisations, which therefore need to facilitate communication among individuals, as well as encourage interaction in groups and networks. Managing social activities will also increase the satisfaction of employees with their co-workers, as stated by Coff (1997), which may otherwise be reluctant to share knowledge, because they might see it as helping their direct competition (Morris and Empson, 1998). Socialisation processes do not just allow organisations to gain knowledge from employees, but also provide for a certain degree of control over employees (Raelin, 1985; Ditillo, 2004), contribute to creation of new knowledge (Andreeva and Kianto, 2011), and may also positively affect firm performance (Greenwood et al., 2005).
Retaining employees is also a particular problem for knowledge intensive organisations (Alvesson, 2000). Due to their high level of knowledge, professionals are constantly courted by competitors trying to tempt them away from their firm. Robertson and Swan (2003) propose that companies have the best chance of retaining employees, and solving managerial dilemmas, by using normative controls, built around social and professional norms, that encourage collaboration and knowledge-sharing. Sharing knowledge and cooperation will help individuals adapt and commit to the organisational culture, identity, routines and norms, as they effectively eliminate goal incongruence (Ouchi, 1979; Coff and Kryscynski, 2011). Establishing goal congruence is crucial for PSFs, since employees might otherwise perform poorly, even though they possess the knowledge to do the job well (Merchant, 1982). Commitment to the organisations will result in increased loyalty and will make it easier for firms to retain their high-knowledge workers (Coff, 1997; Alvesson, 2000; Coff and Kryscynski, 2011). In order for PSFs to retain professionals and gain as much knowledge as possible from them, I therefore propose the following:
H3a: Human capital intensity is positively related to explicit cultural control tightness H3b: Human capital intensity is positively related to implicit cultural control tightness
Personnel Control Tightness
Greenwood et al. (2005), as well as Coff and Kryscynski (2011) identify the need of PSFs to employ highly educated (professional) workforce, as a higher level of human capital may result in a competitive advantage. Ouchi (1979) identifies two ways firms can develop the desired level of human capital intensity. Firms can either initially select people who fit their needs exactly, or can employ people who do not exactly fit the needs, and provide them with the necessary training to develop the skills and knowledge. Lepak and Snell (1999) suggest that hiring the right people will allow firms to realise significant cost savings, as well as creating value for the firm, and it will therefore be more likely that managers will focus on recruiting employees who already possess the necessary level of knowledge. Investing in personnel controls creates many diverse benefits for PSFs – among others it focuses management concern on where the core competency is (Nurmi, 1998), it improves organisations’ effectiveness and performance (Abernethy and Brownell, 1997), and it makes human capital increase in value and be more firm-specific (Lepak and Snell, 1999). Furthermore, Hitt et al. (2001) explain that obtaining human capital with a high level of knowledge may be costly for a PSF, therefore high quality personnel controls need to be in place to prevent choosing a wrong person. Since PSFs need to constantly employ people with a high level of knowledge, I predict the following:
H4b: Human capital intensity is positively related to implicit personnel control tightness
3 Methodology
This thesis has been written in the context of the PSF thesis survey project 2015-2016 at the University of Amsterdam, led by Helena Kloosterman. My decision to join this project was based on the following reasons.
Firstly, the project offered the use of a pre-developed survey with clearly defined constructs, which fit the purpose of this paper and helped operationalise the variables used in the proposed hypotheses. Secondly, it provided a large sample of respondents to perform the analysis, which would otherwise be difficult to obtain through my own professional network. Besides, it allowed me to focus more on the research of the literature and to get a deeper understanding of the topic. Lastly, as pointed out by Von Nordenflycht (2010), previous research mostly focused on a single industry within the field of PSFs, from which results were applied to the entire sector. The data collection for this project was however, intended to obtain information from various industries, which should consequently lead to more reliable results for the PSFs sector in general.
Sample selection will be discussed next, followed by the description of survey design, which includes the report on two pre-tests conducted to assess the quality and effectiveness of the survey. Afterwards, the process of constructing relevant variables is presented, and a statistical model is developed, which also concludes this section.
3.1 Sample Selection
The objective of the data collection was to obtain a diverse sample of employees working in different industries around the world. Not only were professionals working in PSFs targeted, as the overall project is also concerned with professionals working in a non-PSF environment, e.g. an accountant working in the finance department of a manufacturing firm. The following requirements were imposed on respondents, to assure that the sample conformed to the purpose of the research:
Respondents must understand and use English on a business level
Employees working in NGOs, non-profit, publicly owned (e.g. education), government and social work agencies are not deemed valid respondents, with the exception of medicine/physician practitioners.
Respondents must have at least three years of experience in the current field, and preferably less than ten
Respondents must work in a medium/large-size company (i.e. more than 50 employees) These were required to make sure respondents were able to work autonomously, and are at the same time directly affected by the MCS but not in the position to design or direct it. Furthermore, small companies and organisations listed under the second requirement were excluded due to peculiar characteristics of their MCSs.
The initial sample consisted of 372 respondents, out of which 220 were removed due to the following reasons. Firstly, 47 respondents were removed because they did not answer most of the questions relevant for this study (i.e. questions about human capital intensity and MCS tightness). Next, 82 invalid respondents were omitted, of these: 12 because they were in a superior position, able to exercise power in the firm (e.g. partners, CFOs, senior managers, etc.); 17 due to their occupation not complying with the survey requirements or the PSFs field (e.g. teachers, salespeople), or because there was insufficient information to determine their occupation; 42 because their experience in the field was insufficient (i.e. working in the field for less than three years); and 11 for not complying with the second requirement (e.g. working in a non-profit organisation, etc.) Finally, 91 respondents were excluded because their job represented only a support function in a non-PSF firm. The final dataset used for analysis therefore consisted of 152 respondents working in PSFs, as seen in Table 1 below.
Table 1: Sample selection process
Initial Respondents 372
Most of relevant questions unanswered 47
Not subject to the MCS 12
Occupation not in scope of PSF 17
Insufficient experience in the field 42
Public/non-for-profit organisation 11
Support function in a non-PSF 91
Total Valid Respondents 152
The majority of the sample is represented by accountants (34%), followed by medicine/physician practitioners and management/strategy consultants (10%). Other characteristics of the sample are presented in Table 2. The average age of surveyed professionals is roughly 34 years. 61% of respondents are male, and 70% of respondents hold a master’s degree or a higher level of education. The way tenure in either field or organisation is coded makes it difficult to present exact average of the sample. This is also indicated by a relatively high standard deviation compared to the mean, implying that the mean is not an accurate representation of the data (Field, 2009). It
could however, be argued that the average of years worked in the field is between six and seven years (median six years), while the average number of years worked in the current organisation is roughly five years (median four years).
Table 2: Respondents descriptive statistics
3.2 Survey Design
The complete survey was designed to gather information about antecedents, responses, and consequences of MCSs, as well as several control variables which might affect a MCS in a firm. The antecedents refer to certain features of a company and particular jobs, which are supposed to have a significant effect on the design of a MCS, such as customer reliance, capital intensity, human capital intensity, etc. MCS responses are developed with respect to control tightness of each set of controls, as previously described in the literature overview. They measure how each type of controls is implemented in order to respond to the intensity of antecedents in an organisation. The consequences thus measure the suitability of the responses to the given antecedents, and are presented in the form of performance and professional tension. Last, control variables are certain more general features of organisations, which might influence the design of MCS, such as size, strategy, environmental uncertainty, etc.
The overall survey allows for a very broad research into the topic of MCS in PSFs, however this specific study focuses on a narrower field. It investigates human capital intensity, as an antecedent of MCS, and the whole set of MCS responses, simultaneously controlling for size, reputation, strategy, ownership type, and environmental uncertainty. Survey questions relevant to this paper can be examined in Appendix A.
PSF N Min Max Mean Median Std. deviation
Age 151 24 63 33.89 32.00 7.590
Gender* 152 0 1 0.39 0.00 0.489
Education** 151 0 1 0.70 1.00 0.459
Years in the field*** 152 4 11 7.23 7.00 2.729
Years in organisation*** 151 1 11 5.93 5.00 2.953
* Male = 0, Female = 1
**Bachelor degree or lower = 0, Master degree or higher = 1
3.2.1 Preliminary Survey Testing
Two separate pre-tests were conducted on the survey before data collection started, with the purpose of maximising the quality and effectiveness of it, which consequently affected the design of the survey, as well as the content of constructs. Before I discuss variables in detail, it is thus necessary to explain how the final form of the survey was developed.
The first test focused solely on the quality of items used to measure MCS responses. Twenty professionals were asked to complete an item-sorting task, requiring them to match 52 statements designed to measure MCS tightness constructs, with their definitions. Out of twenty professionals, fourteen completed the test (four lawyers, two management consultants, one IT consultant, one security consultant, one accountant, one psychologist, one dentist, one architect, one marketing professional, one graphic designer). Based on their answers, four statements with least incorrect matches were selected for each construct. The results ranged from zero incorrect matches for explicit action control tightness, to six incorrect matches for implicit action control tightness. The second test was designed to evaluate the overall quality of the survey. A further twenty people (three medical doctors, three chemists, three lawyers, two management consultants, two marketing professionals, one dentist, one advertising executive, one architect, one graphic designer, one artist, one electrical engineer, one mining engineer) were asked to complete the survey online, and answer questions regarding the content, clarity, appearance, and also about the time taken to complete the survey. Based on the answers provided, only minor adjustments were made to the survey, mainly regarding the wording and inclusion of additional options to a few multiple choice questions. 3.2.2 Independent Variable
The independent variable used in this analysis is human capital intensity (HCI), defined as the degree of education, training and experience necessary for service provision. The definition, and the construct measuring HCI, are both adapted from Subramaniam and Youndt (2005). Respondents were asked to indicate their level of agreement with five statements on a five-point Likert scale, which were directed towards the knowledge, capabilities, and creativity of their firm employees, as well as the reputation they hold in the industry.
3.2.3 Dependent Variables
This paper makes use of the following eight dependent variables, in order to measure the response of the MCS to the degree of HCI: explicit action control tightness (EACT), implicit action control tightness (IACT), explicit results control tightness (ERCT), implicit results control tightness
(IRCT), explicit cultural control tightness (ECCT), implicit cultural control tightness (ICCT), explicit personnel control tightness (EPCT), and implicit personnel control tightness (IPCT). All the constructs measured respondents’ level of agreement with four statements on a five-point Likert scale. Most of the constructs used assertions adapted from prior survey instruments (EACT, IACT, ERCT, IRCT, ICCT)1, with two of them (ERCT, ICCT) being complemented by newly
developed items. The rest (ECCT, EPCT, IPCT) were fully based on new items, developed for the purpose of the project. In the survey, constructs were coupled based on the type of control, while Appendix A makes a distinction between explicit and implicit tightness questions, for a better presentation of each construct.
EACT and IACT constructs consisted of questions regarding rules and procedures applied in an organisation. All the questions for IACT were reverse-coded. More specifically, the questions were directed toward the extent of rules and procedures used, their coverage of tasks and various situations, frequency of monitoring, and also the degree to which employees are allowed, or even encouraged, to adjust the procedures and use them flexibly.
The content of ERCT questions was very similar to the EACT, the difference being a focus on goals and targets, instead of rules and procedures. IRCT questions, out of which three reverse coded, were concerned with the degree of expectations regarding attainment of goals, and tolerance for deviation from pre-established targets.
ECCT and ICCT constructs asked about socialisation procedures used in the organisation, and their effect on employees. In particular, ECCT involved statements with respect to the communication of core values to employees and social, team-building, and other types of events. ICCT, also using one reverse-coded element, meanwhile focused on the congruence of values between employees and organisation, and their independent social activities with colleagues. Last, for EPCT and IPCT respondents were asked to indicate their opinion about the hiring process in their organisation. EPCT was concerned with the extent of the hiring process (quantity of interviews, decision factors, and steps), while IPCT, also being based on two reverse scored instruments, dealt with the consistency of the hiring process, in terms of the competence and experience of people that were hired.
1 See Hage and Aiken (1967), Hage and Aiken (1968), Van den Ven and Ferry (1980), O’Reilly and Chatman (1986).
