Amsterdam Business School
A Study into the Effects of Customer Reliance on Management
Control System Tightness in the Management of Professionals
Master Thesis
Name: Felix Schmidt
Student number: 11089725
Date: June 20th, 2016
Program: MSc Accountancy & Control
Specialization: Control
Faculty: Economics and Business
1st Supervisor Dr. ir. S.P. van Triest 2nd Supervisor Ms H. Kloosterman MSc
Statement of Originality
This document is written by student Felix Florian Schmidt 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.
Acknowledgements
I gratefully acknowledge the support, encouragement and inspiration I received from my supervisor, dr. ir. Sander van Triest. I also want to thank Ms Helena Kloosterman, who made joining this research project possible in the first place and provided useful support and counsel in finding and defining my research.
Finally, I would like to thank those who supported me throughout the thesis process: first, many thanks to my wonderful parents who helped me reach a significant number of survey respondents, second, my gratitude to Hugh, my dear old friend who has always endeavored to help me improve my English language and, last, to Manon, my caring and loving girlfriend who not only stood behind me in times of stress or anxiousness, but also provided me with valuable opinion on research-related issues or controversies.
Amsterdam, 20th June 2016
Abstract
The purpose of this paper is to investigate design and use of management control systems in professional service firms. Specifically, this study examines the effects of customer reliance on two newly developed management control system design characteristics: explicit and implicit control tightness, referring to the emphasis put on the amount and scope of measures and the degree to which deviance from the system is tolerated, i.e. to what extend control is enforced. The data analyzed in this study is retrieved from surveys conducted with experienced professional employees working on the operational and mid-management level at both professional service firms and professional divisions in non-professional organizations. The results provide partial evidence for the direct effects of customer reliance on management control system tightness in professional service firms. However, they also show that, in the light of customer reliance, control tightness does not differ between professional service firms and professional divisions. However, this paper only covers the surface of research in explicit and implicit control tightness and adds further value by uncovering potential directions for future scholarship.
Keywords
Customer Reliance; Management Control System; Management Control System Tightness; Implicit Control Tightness; Explicit Control Tightness; Professionals; Professional Service Firms
Table of Contents
1 Introduction ... 1
2 Theoretical Framework ... 3
2.1 Management Control Systems ... 3
2.1.1 Management Control System Dimensions ... 4
2.1.2 Management Control System Characteristics ... 5
2.1.3 Management Control System Tightness ... 6
2.2 Professional Service Organizations ... 9
2.2.1 Professionals ... 10
2.2.2 Professional Service ... 11
2.2.3 Professional Service Firms ... 11
2.3 Customer Reliance ... 13
2.4 Hypothesis Development ... 16
3 Research Methodology ... 24
3.1 Sample Selection ... 24
3.2 Survey Design and Variables ... 26
3.2.1 Independent Variable ... 26
3.2.2 Dependent Variables ... 26
3.2.3 Control Variables ... 27
3.2.4 Interaction Variable ... 29
3.3 Preliminary Survey Testing ... 29
3.4 Validity Analysis ... 30
3.5 Statistical Model ... 34
4 Results ... 36
4.1 Descriptive Statistics ... 36
4.3 Regression Analysis ... 40
4.4 Additional Analysis ... 46
5 Conclusion ... 48
5.1 Discussion of Findings ... 48
5.2 Limitations ... 51
5.3 Implications for Future Research ... 52
References ... 54
1 Introduction
Traditionally, despite the increasing dominance of the service sector in most developed economies (see, for example, Goodale et al., 2008; Otley, 1994), management control system (MCS) research has set its primary focus on the manufacturing rather than the service sector, leading to a lack of systematic research in the field of MCS design in professional service firms (PSFs) (Drury, 1998; Sharma, 2002; Shields, 1997) and calls for further investigations in this field (Chenhall, 2003; Maister, 1982). Organizational theorists have long argued that that service organizations, in particular PSFs, differ significantly from those in the manufacturing sector and that managers of such service organizations are aware of the distinct requirements to successfully manage their organization (Thomas, 1978; Von Nordenflycht, 2010). Addressing this research gap, prior studies investigating MCS design characteristics in PSFs tended to adopt a contingency-based approach (Chenhall, 2003). Ittner et al. (2003) and Auzair & Langfield-Smith (2005) examine the impact of strategy on MCS characteristics in professional services, King & Clarkson (2015) and von Nordenflycht (2007) investigate the interplay of size, organizational structure, MCS design and performance in PSFs while Sharma (2002) finds that perceived environmental uncertainty as well size and budget system characteristics find consideration in MCS design choices. One unique and influential aspect of professional services is that clients are required to contribute effort or information to the service production process, thus creating a certain reliability on the PSF side (Kelley et al., 1990). Hence, customer reliance presents a key aspect in assessing strategic and operational challenges in the service industry (Schmenner, 1986). In this sense, scholars have started to go beyond Chenhall's (2003) traditional contingency variables, investing customer-related implications for MCS design in PSFs. Von Nordenflycht (2010) suggests that high levels of specific knowledge (Jensen & Meckling, 1992) are the natural result of the service characteristics themselves, specifically customer involvement. High levels of active customer involvement have been referred to as co-production (Auh et al., 2007) and argued to cause uncertainty at the organization-client interface (Gluckler & Armbruster, 2003; Larsson & Bowen, 1989) and to have a decisive impact on both the cost and quality of the service (Homburg & Stebel, 2009). One further, distinctive characteristic of PSFs is that the majority of their workforce consists of professionals (Løwendahl, 2005). Professionals are considered to be distinctive in the way they create and use knowledge (Brivot, 2011) in a non-repetitive work environment (Pinnington & Morris, 2002).Both their work and personality drives their demand for professional autonomy (Covaleski et al., 1998;
Goodale et al., 2008), resistance to conformity and ideology of social and self-regulation instead of formal controls (Brivot, 2011; Von Nordenflycht, 2010). Investigating the challenge of bureaucratizing a PSF through the imposition of administrative controls, Brivot (2011) suggests that, despite the application of formal controls, processes remained largely informal and calls for further researchin this field.
This study explores implications of customer reliance on MCS design and enforcement in the management of professionals. It links to the paradox that, although extensive control mechanisms might be implemented in PSFs, these might not be enforced at all or be used in a flexible way when facing unexpected, customer-related situations. This leads to the first research question of this paper:
RQ1: How does customer reliance impact management control system design and enforcement in professional service firms?
To date, scholarship has focused on the distinction between mass and professional services (see, for example, Silvestro, 1999) but widely ignored the different roles professionals adopt within their organization. Professional services are not solely rendered by PSFs, but also by professional support divisions in non-professional organizations (NON PSFs). Although professionals can be considered a distinctive group of employees with specific characteristics that can be found and considered equal across various industries, influences on their work potentially differ on the kind of organization they are employed by. Exploring potential differences of being at the core business in the context of a PSF or in a professional support function of a NON PSF, the following research question is proposed:
RQ2: Does the impact of customer reliance on management control system design and enforcement differ between professional service and non-professional firms?
In order to answer these research questions, this paper develops the concept of MCS tightness as a novel, two-fold composition of explicit and implicit control tightness. While explicit control tightness describes the emphasis put on control by the amount and extent of measures in place, implicit control tightness characterizes the flexibility inherent in the system, i.e. the extent to which explicit measures are enforced or regarded as stretchable and adaptable guidelines. MCS are considered a composition of four control dimensions, behavior (2) results (3) personnel and (4) cultural controls (Merchant, 1982; Ouchi, 1979; Snell, 1992), each of which will be tested for explicit and implicit control tightness.
2 Theoretical Framework
Organizational theorists have investigated organizations that employ high numbers of professionals since the 1960s. This stream of research was mainly driven by the assumption that professionals are assumed to favor aspects of their work that conflict with bureaucratic organizational controls (Barley, 2005; Blau & Scott, 1962; Von Nordenflycht, 2010).In order to achieve a comprehensive understanding of the specific and relevant characteristics companies employing professionals and specifically PSFs hold that put them into this dilemma, it is useful to take an inside out approach and disentangle the paradox into its main components: the MCS in place, the professional service, professionals, and the customer, i.e. the control environment, the product offered and the two parties responsible for the generation of this product (Auzair & Langfield-Smith, 2005; Løwendahl, 2005; Von Nordenflycht, 2010).
This section is structured as follows: First, the relevant dimensions of MCS are introduced and the concepts of explicit and implicit MCS tightness is developed. Second, the specific characteristics of professionals and professional services are elaborated and a definition of PSFs is developed. Third, customer reliance and the resulting control dilemma organizations and divisions offering professional services is explained. The section closes with hypotheses based on this dilemma and its implications on MCS design.
2.1 Management Control Systems
Back in the early 1900s, research identified control to be a core function of management (Merchant & Otley, 2006). Control, in general, can be described as an influence that is intentionally or unintentionally exerted by individuals on themselves or other members within their social social environment, effectively limiting the discretion and freedom of those upon whom it is exerted. Translated into an organizational context, intentional control is implemented through various control mechanisms in different dimensions of the company, e.g. culture or goal achievement, that are directed at coordinating employees in a cooperative way (Brivot, 2011). These mechanisms used to control attitudes and behavior potentially cover an extensive spectrum and can reach from being highly formal to being highly informal (Goodale et al., 2008). Based on the concept of control and control mechanisms, academia has started to engage in developing numerous management control frameworks, resulting in an extensive stream of research and variety of definitions. Broadly speaking, MCS are designed to address and reduce agency problems and provide assurance that employees
behave in the best interest of the company and its shareholders. In order to enhance this process, managers implement sets of controls to support their employees in attaining the desired results, protect their organization against external threats and achieve high performance (Merchant & Otley, 2006). In some contexts, however, overemphasizing structure and control may diminish employee trust and morale, thus disrupting organizational effectiveness. Hence, in order to be effective, MCS design choices must be matched with both internal and external organization-specific requirements (Goodale et al., 2008). Beyond the aforementioned basic understanding of control, control mechanisms and their interplay within an MCS, scholars have developed several frameworks to operationalize MCS. Given the maturity, broadness and complexity of management control, it is not unexpected that scholars have taken different approaches to their research that cannot be compiled to one perfect set of MCS design dimensions or characteristics.
2.1.1 Management Control System Dimensions
Essentially, organizations find themselves in a position where they can choose from a plentiful range of control mechanisms to assemble an MCS they consider best suited to their specific situation. While some literature merely focuses on one control, e.g. performance measures, it has become well acknowledged that MCS comprise multiple intertwined control systems and mechanisms (Widener, 2007). Hence, research has developed several more inclusive and comprehensive control frameworks. Ouchi, (1979), for example, identifies three major dimensions of control: behavior, outcome and clan controls. Organizations emphasize each of these dimensions depending on the extent to which favorable behavior is known, results can be measured reliably and environmental factors. Merchant (1985) and Merchant & Van der Stede (2007) take up on this approach, developing further and redefining these concepts to action, results and personnel/ clan controls. Another operationalization that has gained prominence in the field of management control is provided by Simons’ Levers of Control (LOC) framework (Simons, 1995). The LOC framework suggests that MCS are an assembly of four different control systems that work together to benefit the firm. That is, first, the beliefs system which sets and communicates the organization’s core values to motivate and inspire employees. The second, the boundary system, stands in opposition to the beliefs system, positing behavioral constraints. The third, the diagnostic system, comprises monitoring activities and intends to encourage high performance. The last, interactive system is rather forward-looking and stressing the importance of management involvement (Widener, 2007). The last and probably most extensive operationalization worth mentioning
has been developed by Ferreira & Otley (2009). They propose a holistic rather than focused view on MCS, arguing that investigating only one aspect of MCS at a time will lead to biased results as another aspect potentially balances the other. The framework builds on twelve questions (e.g. regarding mission, vision or KPIs) that provide a useful checklist for case work aimed at conducting comprehensive MCS assessments.
This small yet extensive extract is representative for the many-sidedness of dimensions and constructs in MCS research, deterring assumptions on one complete or definitive definition of MCS dimensions. This study adopts a hybrid object-of-control framework which operationalizes MCS as a composition of four control dimensions: (1) behavior, (2) results, (3) personnel and (4) cultural controls (Merchant, 1982; Ouchi, 1979). Specifically, this operationalization is considered to best suit this study as the emphasis put on these forms of control is dependent on the measurability of results and the knowledge on desirable behavior, both dimensions for which ambiguity increases with customer reliance. Furthermore, it can be assumed that this composition of controls covers the whole control environment professionals experience, from input (personnel) via throughput (culture and behavior) to output (behavior and results). Last, the model is well suited to investigate relative (dis-)advantages of each dimension and also achieve meaningful comparisons, e.g. between results and action controls.
2.1.2 Management Control System Characteristics
In extension of MCS design dimensions, research has intensely investigated MCS characteristics. This study differentiates MCS dimensions from characteristics in a way that dimensions describe the areas of control addressed by the MCS while characteristics refer to how these dimensions are actually used or emphasized. Essentially, this view can be summarized as: MCS dimensions answer the question what do I want to control? (e.g.
actions, results, etc.) and MCS characteristics answer the question how does the organization live these controls? (e.g. control to monitor or motivate, control everything in one but only little in another dimension, etc.). Hence, MCS characteristics originate from the behavior and
actions managers take in implementing and using MCS.
To date, research has examined MCS characteristics in many ways and derived manifold implications. Perhaps the most common feature of MCS discussed in literature is the level of formalization (or bureaucratization) inherent in the system (Whitley, 1999). Formal MCS are typically described as control systems that heavily rely on quantifiable,
mostly financial or accounting driven indicators and a preference for extensive sets of rules, guidelines and instructions. These indicators usually reduce flexibility and management discretion in evaluation and often rely on systematic, automated and IT-driven procedures. Informal systems, in contrast, emphasize personal discretion and allow for flexibility in adapting control procedures to specific situations (Amigoni, 1978; Modell, 1996; Whitley, 1999). Similarly, in the context of traditional and contemporary management practices,Otley (1994) argues that MCS can either be restricted or flexible. He suggests that a restrictive MCS is vertical, number driven and rather static while a flexible system can be characterized as horizontal, dynamic and self-regulating. Following this thought more in-depth, Adler & Borys (1996), identify two formalizations of bureaucracy: enabling and coercive. While an enabling formalization encourages creativity and employee involvement, a coercive formalization imposes rules and guidelines on employees, usually suppressing their creativity and limiting autonomy by giving clear guidance. Another MCS characteristic, namely whether a system is impersonal or interpersonal, that can be related to the above concepts is offered by Whitley (1999). Impersonal systems comprise top-down dictated, short-term performance measures and formal feedback against pre-set targets while an interpersonal system encourages bottom-up participation in the performance measurement process and long-term personal feedback.
In a nutshell, organizations are forced to exert control within a wide spectrum of characteristics for each MCS dimension. It is to be noted, though, that despite the different wording, these concepts tend to overlap or at least show similarities in certain aspects. In the further, the concept of explicit management control tightness subject to this study is developed based on these commonalities and existing research on MCS tightness.
2.1.3 Management Control System Tightness
The focal point of this paper is to examine control tightness as a specific characteristic of MCS. Bringing together the definitions and descriptions of MCS characteristics implies that one end of the control span is more bureaucratic, formal, restricted, coercive and impersonal. Accordingly, the opposing side of the span is less bureaucratic, more informal, flexible, enabling and interpersonal. Although the behavioral control dimension is usually located at the more bureaucratic end and the results control dimension at the less bureaucratic (see, for example, Auzair & Langfield-Smith, 2005), this paper takes a different approach, investigating tightness as one comprehensive characteristic for each of the four MCS dimensions.
To this intent, this paper defines control tightness as a composition of explicit and implicit tightness. To date, literature has not defined tight control consistently and few researchers have chosen to define tight or loose control as a whole. Merchant & Van der Stede (2007, 2011)suggest that tight control should increase assurance that employees act in the best interest of their organization. Amigoni (1978) describes a tight style of control as one with low participation in setting objectives, imposed targets accounting-driven performance evaluation i.e. a style that sets administrative control over several (social) and individual controls. Hopwood (1974) argues that tight MCS limit employee participation in setting objectives and targets are imposed on employees while the firm’s commitments and performance are based only on accounting measures. Loose MCS, in contrast, emphasize the social side of control encouraging high levels of employee participation. More recent studies (Anthony et al., 1992; Campbell et al., 2011) derive their definition of tight control from the extent and frequency of employee monitoring. Further, Whitley (1999), who draws back to Lerner & Wanat (1983) and Butler et al. (1998), argues that tight control implies precisely defined decision rules whereas, in loose systems, such rules might exist but deviations are tolerated given situation-specific circumstances.
In the context of this research, these existing concepts of MCS tightness and flexibility are brought together in a new interpretation of MCS tightness. MCS tightness is defined as the degree of flexibility inherent in the control system which consists of two components: (1) the scope of the MCS dimension (explicit tightness) and (2) the acceptance of deviations from the measures in place (implicit tightness). A control dimension is characterized as explicitly tight, when controls, rules, procedures and guidelines are high in number. Explicit tightness is achieved through rigid control selection, definition and completeness. Implicitly tight control, on the other hand, reduces the tolerance for deviations from the controls, rules, procedures and guidelines implemented. Implicit tightness is achieved by reducing flexibility and the tolerance for deviations within the respective control dimension. This particular separation of tightness into two elements appears specifically suiting in the context of professionals, professional services and customer reliance. While some PSFs or professional divisions in NON PSFs might have extensive sets of controls in place that let their MCS appear (explicitly) tight, high levels of tolerance for deviations from these controls might exist, implying a (implicitly) loose MCS. Mapping the two concepts of tightness into the four dimensions of control, as described in the section before, the following operationalization can be derived.
Behavioral Control Tightness
Behavioral controls, also referred to as action controls (Merchant, 1982), describe formal rules and procedures prescribing desired actions, holding employees accountable for their actions and pre-reviewing actions before they are taken. Behavioral control relies on the premise that the transaction process as well as favorable actions are understood and known (Modell, 1996). Explicit behavioral control tightness is described by the number and scope of standardized processes, rules, procedures and guidelines within the organization, where a tight system comprises a lot of controls in terms of amount and scope. Implicit behavioral control tightness describes the degree to which deviation from these processes, rules, procedures and guidelines is tolerated or even encouraged where high tightness is the result of not allowing any deviation.
Results Control Tightness
Results Controls hold employees accountable for the results they deliver. In contrast to behavioral controls, results controls focus on the outcome of work instead of the work itself and thus facilitate empowerment as actions are not restrained, i.e. it lies within the employee’s professional judgment to choose actions that they think will best produce the desired results. Results controls require the possibility to unambiguously measure and compare the results produced (Modell, 1996). Explicit results control tightness is defined by the extent to which goals, targets and performance measures are used where a tight system holds a lot of controls in terms of amount and scope. Implicit results control tightness describes the level of toleration for deviations from the pre-set goals, targets and performance measures where tightness implies not permitting any.
Cultural Control Tightness
Cultural Controls are a vital part of an organization’s MCS and are often referred to as softer parts of the system (Lecture: Management Control). Cultural controls can be compared to the beliefs system from Simons' (1994) Levers of Control Framework, presenting an explicit set of core norms, values and beliefs shared amongst employees through, e.g. vision and mission statements. Explicit cultural control tightness is the degree to which employee socialization procedures are employed and a tight system is one in which such procedures are used intensively. Implicit cultural control tightness is the degree to which organizations tolerate employee norms, values and beliefs to deviate from those prevalent in the workforce where high tightness means high congruence in these elements.
Personnel Control Tightness
Last, Personnel Controls describe the procedures and criteria during the employee selection process. Contrasting Behavioral Controls, Personnel Controls do not impose any bureaucratic pressure on employees and are aimed at achieving self-regulation through strict selection, getting people with the right fit to join the company (Abernethy & Brownell, 1997). This paper will refer to personnel controls as controls implemented at the stage of hiring, educational and retention measures are neglected. Explicit personnel control tightness is thus defined as the extent and use of selection criteria where a tight system is characterized by extensive selection criteria as the company actively targets people with certain attributes. Implicit personnel control tightness describes the level of deviation from human resource standards, where a tightness is achieved through little tolerance.
2.2 Professional Service Organizations
The target group of this study consists of professional employees who are frequently considered to hold special characteristics and attitudes towards management control. Factually, this distinctive group of employees can be found across various industries. Although influences on their work potentially differ on the role of the organization they are employed by – core business in the context of PSFs vs. support function in the context of NON PSFs – distinct operational challenges arise from the type of work that is conducted by these employees, and due to the nature of the employees themselves (Goodale et al., 2008). Hence, this research sets the assumption that personal characteristics as well as the service produced can be considered equal for both roles and does not require separate definitions.
To date, though, research has not come to a consensus on the boundaries of professionals, professional services or PSFs, leading to ambiguity in the terminology relevant for this paper (Von Nordenflycht, 2007, 2010). The following section hence focuses on two specific elements: (1) professionals, (2) professional services, i.e. the product provided by PSFs. From these two concepts, the traits of PSFs compared to NON PSFs relevant for this paper are derived. Subsequently, the influence customer reliance has on the work of professionals and how this influence is assumed to differ between PSFs and NON PSFs is elaborated upon in more detail.
2.2.1 Professionals
Professionals are considered to be distinctive in the way they create, accumulate, share and use knowledge (Brivot, 2011). Pinnington & Morris (2002) suggest that the work of professionals is frequently non-repetitive due to unique client requests which drives the character of their work. Throughout their career, they grow a large body of codified, abstract and expert knowledge that, coupled with professional discretion, presents the input (resource) to their work in addressing the usually complex problems of their clients (Abbott, 1988; Freidson, 1988). Goodale et al. (2008) suggest that professionals hold abstract knowledge which they apply expertly to cases their clients present them with. They further argue that this high density of expert industry knowledge and heuristics puts professionals under pressure to achieve customer satisfaction, high word of mouth reputation and act in an entrepreneurial way which drives their demand for professional autonomy and resistance to conformity. Accordingly, Covaleski et al. (1998) suggest that this individual pressure and autonomy present a source of resistance to conformity. Moreover, professionals are considered the most important intangible resource for their organization, holding greater potential to generate a competitive advantage than tangible resources. The logical consequence is that their employing organization is heavily reliant on its professionals, resulting in a people-centric business view. For organizations to effectively exploit this resource, professionals are required to have passed extensive education and firm- or industry- specific training before working on the job. Through further education possibilities, continuous trainings and gaining experience, professionals build onto their formal education and increase their value to the firm through unique, hard to copy knowledge (Hitt et al. 2001). Knowing their role and importance provides professionals with a high bargaining power that reaches down to the operational level, driving an ideology of social and self-regulation, in contrast to formal controls (Brivot, 2011; Von Nordenflycht, 2010). In more detail, Løwendahl (2005) suggests that this ideology of self-regulation can be explained by the tendency that professionals show higher levels of loyalty to their peers and profession than devotion to the company itself.
In summary, professionals are considered highly educated individuals, who increase their human capital through building expert knowledge and networks in the course of their career (Hitt et al., 2001; Løwendahl, 2005; Raelin, 1985; Von Nordenflycht, 2007). Academic literature on Professionals widely agrees that the most problematic features for MCS design choices are their resistance to bureaucracy, wish for autonomy and high bargaining power presenting the major asset and basis for competitive advantage (Brivot,
2011; Hitt et al., 2001; Kerr et al., 1977; King & Clarkson, 2015; Løwendahl, 2005; Raelin, 1985; Von Nordenflycht, 2007)
2.2.2 Professional Service
A professional service describes the product offered by PSFs that is distinctive from products offered by manufacturing or mass-service companies. At the point of sale, a professional service is neither a ready-made nor one hundred percent pre-defined product the quality of which can be reliably assessed beforehand. Prior research has characterized the work performed by professionals as distinctive, largely due to the defining role of output (professional service) and throughput processes (application of knowledge and experience from professionals) (Brivot, 2011; Wallace, 1995). Significantly designing features of professional work are the requirements to and the quality of outputs which are neither easy to define nor measure by both clients and the professional service provider themselves. Researchers have argued that when ambiguity in the measurement of output quality is high, formal administrative controls are likely to be useless if not counter-productive (Brivot, 2011; Merchant, 1982). Additionally, Perrow (1967) suggests that professionals’ work is to be considered non-routine and that the production technology employed is incompatible with administrative controls. The cost and quality of a professional service is further dependent on the production process which is characterized by high levels of customer involvement resulting in a co-production of the output itself (Homburg & Stebel, 2009). Hence, the production of output is driven by client work and highly dependent on their willingness and ability to share information and collaborate with the professionals (Brivot, 2011; Mills et al., 1983).
Summarizing, the most distinctive traits of professional services are high customer contact times, high dependency on customer input, high levels of specific knowledge, discretion and value creation with frontline-workers. Furthermore, product heterogeneity in professional services offers little potential for standardization and the service is delivered by individual professionals rather than their company (Auzair & Langfield-Smith, 2005; Brivot, 2011; Hausman, 2003; Homburg & Stebel, 2009; Stouthuysen et al., 2012; Von Nordenflycht, 2007, 2010; Wemmerlöv, 1990).
2.2.3 Professional Service Firms
As described in the foregoing sections, this paper aims at investigating the impact of customer reliance on MCS design in PSFs, and how this effect differs between PSFs and
NON PSFs. Hence, this study requires a framework to set boundaries around the term PSF. However, research in the field of PSFs has not come to one vivid definition of the actual terminology of a PSF (Von Nordenflycht, 2010). Auzair & Langfield-Smith (2005), for example, argue that PSFs are organizations that have few transactions which are yet highly customized and process oriented. Furthermore, PSFs are characterized by high customer contact times and value creation in the front office. Table 1 summarizes the main features of PSFs relevant to this study:
Table 1 Characteristics of PSFs adapted from Løwendahl (2005) Dimensions of Professional Service Firms – adapted from Løwendahl (2005)
• Majority of employees are professionals
• High priority of professional goals and client-oriented problem solving • High degree of respect for professional culture
• Emphasis on creation, adaptation and application of theoretical knowledge • High degree discretion over decisions and activities with professionals
These characteristics, however, may also be transferred to certain divisions of NON PSFs. NON PSFs do not only rely on purchasing external expertise from PSFs, they usually employ large numbers of professionals themselves. These groups of professionals can majorly be found within professional service divisions of NON PSFs, e.g. in the law, marketing, accounting or in-house consulting department. Essentially, these professionals hold the same characteristics as those employed by PSFs. Nonetheless, they can be considered to differ in three major aspects: (1) the professional service they produce is not the core product of their employing organization, (2) they render services exclusively for one customer, i.e. their employing organization and (3) control mechanisms for their (professional) division are usually aligned with the overall MCS of their employing organization.
In order to be able to set the boundaries on what a PSF or professional department in a NON-PSF context is, this study draws on Von Nordenflycht's (2010) literature review on developing a taxonomy and theory of PSFs. Table 2 presents the professional occupations considered in this study, adapted the literature review, counting cited examples of PSFs.
Table 2 Professional Occupations adapted from Von Nordenflycht (2010)
Accounting & Auditing External & Internal Actuarial Science Risk Management Architecture
Biotechnology
Consulting Engineering, HR, IT, Strategic, Management, Technology Design Fashion Design, Graphic Design, Media Production Engineering
Executive Recruiting Talent Management
Finance Advisory, Insurance Brokerage, Investment Banking & Management, Real Estate, Risk Management
General Project Management Law
Marketing Advertising, Public Relations Medicine & Physician
Pharmaceutical
R&D Software Development
For this study, the core elements of professional work undertaken by professionals employed in a NON PSF context are considered equal to the work of professionals in a PSF occupation. Despite similar characteristics of their work, MCS design in PSFs and professional departments in NON PSFs is assumed to differ under the influence of customer reliance.
2.3 Customer Reliance
The above paragraphs show that a core influence for professional work is customer reliance, i.e. the dependency of service cost, quality and customer satisfaction on customer input and collaboration throughout the process. It has been argued, that the extent to which the customer is involved in the service process presents the most profound impact on service operations issues (Kellogg & Nie, 1995). Service operations literature has long recognized and elaborated on the importance of customer involvement (Auh et al., 2007; Chase & Tansik, 1983; Chase, 1978, 1981; Goodale et al., 2008; Hausman, 2003; Kelley et al. , 1990; Kellogg & Chase, 1995; Larsson & Bowen, 1989; Lovelock, 1983; Mills & Margulies, 1980; Silvestro, 1999; Solomon et al., 1985; Stouthuysen et al., 2012; Wemmerlöv, 1990) and, in some cases, even referred to customers as temporary employees (Hsieh et al., 2004; Mills & Morris, 1986).
Customer reliance has been referred to in many ways, such as customer contact, customer interaction, involvement, participation or co-production. Each terminology comes with slightly differing connotations. Chase & Tansik (1983) and Chase (1981), for example, develop the term customer contact and define it as degree to which the customer is in contact with the service provider. They suggest that for pure service companies, such as PSFs, the majority of production takes place in the presence of their customers. In his earlier work, presence was defined as physical presence of client in the system and processes entailed in creating the service (Chase, 1978). Relating this to today’s business world, presence does not necessarily rely on physical appearance or face to face time, but rather on modern communication mediums such as email or phone. Goodale et al. (2008) take customer contact to an interactive level, using the term customer interaction. They suggest that customer interaction describes the managerial actions taken by customers in the context of a service transaction, aimed at governing the exchange, reducing ambiguity about performance and developing enduring relationships. Skaggs & Youndt (2004), in contrast, describe customer interaction as the dependency on customer actions where high interaction supports non-programmed decision-making in the service production. Hausman (2003), similar to customer interaction, argues that customer involvement is a critical aspect of the service encounter, setting the basis for extended and intimate exchange. This intimate relationship can take very special characteristics, so that customers – through intensive participation in the service production – might even be considered partial employees of the service provider (Mills & Morris, 1986). Regarding the actual production of the professional service, Auh et al. (2007) describe the concept of co-production. They define co-production as meaningful, cooperative and constructive customer input delivered by the customer in order and necessary to develop the professional service.
Despite the difference in the exact terminology and definition of customer reliance, all of the above mentioned concepts have one common implication: customers purchasing a professional service play a crucial role in the production of the service itself. In this line of reasoning and based on their customer contact model, Chase & Tansik (1983) argue that the extent of customer contact with the service organization is a determinant of service quality, i.e. the more customers are involved in the production of services, the greater their impact on service provider system performance. For professional services with high levels of contact, customer impact on performance presents a major source of uncertainty – mainly caused by the provision of incomplete information through changing tasks as well as the quality and
completeness of input (Larsson & Bowen, 1989). Hence, the client becomes a critical success factor in the service production. If customers fail to provide sufficient access to their person or corporate information, the successful production of a professional service become less likely (Hausman, 2003).
Bringing together these concepts, one unique aspect of professional services is that customers regularly have to be included in the production process (Kellogg & Nie, 1995). Usually, the customer is also required to contribute information and effort as an input to the service transaction (Kelley et al., 1990). Therefore, this paper defines customer reliance as the extent to which the professional involved in the production of the professional service is required to include their client. In particular, customer reliance refers to the extent to which the professional is dependent on client input throughout the production process.
Service scenarios with intensive customer contact are hard to control or rationalize, as customers have a constant effect on the time and nature of demand and, ultimately, the quality of the service (Chase, 1978). Additionally, prior research (Gluckler & Armbruster, 2003; Homburg & Stebel, 2009) indicates that tight client-organization collaboration potentially increases transactional uncertainty. Further, with the client being considered a partial employee who is out of reach for the service provider’s control system, professional service providers find themselves facing a distinct challenge for their MCS (Larsson & Bowen, 1989; Mills & Morris, 1986; Silvestro, 1999; Wemmerlöv, 1990). Auh et al. (2007) even suggest that service companies which rely on customer ability to provide high quality, timely, meaningful and cooperative input to the service production require a shift to a customer-centric business model. High levels of customer contact do not necessarily have to challenge the provider’s business model but may also come with benefits, both for the professional service provider and the client. So far, research in this field has identified three main advantages which appear logical consequences of high interaction: (1) knowing the customer and what they make of the service, thus enabling customization and adaption to customer needs, (2) creating customer loyalty and (3) realizing cost savings (Auh et al., 2007; Lovelock, 1983). It is thus evident that the client interface is an important factor for professional service providers and their front-line employees that requires distinct management and control practices.
2.4 Hypothesis Development
Despite this extensive body of literature on professional service providers, professionals, customer reliance and management control system characteristics and design choices, prior studies have not addressed the explicit effects of customer reliance on control tightness in professional service organizations. Based on the earlier sections, professional service providers can be assumed to find themselves in a control choice dilemma due to the prevalent importance of customer reliance and professionals seeking autonomy in their jobs. In order to assure effective and efficient operations, professional service providers must match their MCS design choices with both internal (professionals) and external (customer reliance) organization-specific requirements (Goodale et al., 2008). Hence, some logical links can be expected between the independent variable, customer reliance, and the dependent variables, explicit and implicit MCS tightness.
Although the existence of such relations appears straight-forward at the first glance, it is important to distinguish between the two roles of professional organizations: core business (PSFs) and support function (NON PSFs). Internal factors can unarguably be considered equal for both types of organizations as they majorly employ professionals, but they do differ on the external dimension. While PSFs hold the professional service they produce for varying customers at their core of business, professional divisions in a NON PSF context can be considered back-office functions, supporting the core business of one particular customer. This premise implies that in a NON PSF context, the customer as well as their demands are well known and understood while MCS characteristics are usually aligned with the overall business strategy. Hence, professional divisions in NON PSFs are expected to face less uncertainty arising from customer reliance while also being limited in making their own MCS design choices. Building on this argumentation and drawing on Auzair & Langfield-Smith (2005) as well as Silvestro et al. (1992), professional divisions in NON PSFs will be considered to show some similarities to mass-service firms.
Behavioral and Results Control Tightness
Professionals’ production technology can be considered customer-driven and professional work is frequently non-repetitive due to continuously unique questions and inputs contributed by the customer (Perrow, 1967). Hence, in Perrow’s view, successful professional work is more dependent on the professionals’ attributes, e.g. intuition, experience and discretion, than on their compliance with pre-set standards making
administrative and process-oriented controls ill-suited (Brivot, 2011). Additionally, Larsson & Bowen (1989) argue that customer reliance presents a major source of uncertainty through incomplete information and varying, unpredictable input quality. In this high contact context, uncertainty in PSFs’ day-to-day operations arises, hindering the establishment of standardized workflows (Chase, 1978). Goodale et al. (2008) suggest that professionals cooperating closely with their clients are set under pressure to act in an entrepreneurial way which underlines their demand for autonomy and resistance to inflexible conformity. Generally speaking, Wemmerlöv (1990) argues that extensive customer contact implies less management control. Dealing with human related issues, Brivot (2011) characterizes PSFs as facing high levels of uncertainty calling for risk-taking and the adaptation of theoretical knowledge while standardization might lead to catastrophic outcomes. Mills & Margulies (1980) follow this thought arguing that professionals in a PSF setting, due to their personal-interactive character, operate in a highly dynamic environment where each task requires innovative solutions and decisions tend to be complex and subjective while standards and guidelines are difficult to establish. Therefore, professional work often takes place in absence of formal controls and direct supervision. For PSFs, Mills et al. (1983) propose self-supervision as the most effective control mechanism as it focuses on client-professional relationships. They argue that self-supervision is impeded by inflexible controls, such as roles, rules, and standards. This argumentation implies that both the distinct characteristics professionals hold and high levels of customer reliance appear incompatible with extensive behavioral guidelines, rules and standards. Furthermore, based on the premise that high customer reliance brings ambiguity into the measurement of behavioral controls, the following relationship is proposed:
H1a: Customer reliance is negatively related to explicit behavioral control tightness in PSFs
In fact, some PSFs might have explicitly tight systems in place but not enforce rigid adherence to their rules and guidelines, i.e. allow for flexibility in light of specific circumstances arising from, for example, customer reliance. Brivot (2011), for example, investigates the bureaucratization of the knowledge management in a large law firm. He finds that, despite the implementation of extensive rules and guidelines, the control of knowledge production, sharing and use remained largely flexible and informal. In this context, it has been suggested that professional dependency on client willingness and ability leads to a high degree of personal task uncertainty that makes existing behavioral controls irrelevant
(Chapman, 1997). When ambiguity in the measurement of throughput quality, e.g. milestones or progress, increases due to customer-related influences, formal behavioral controls are likely to become useless (Brivot, 2011; Hofstede, 1981; Merchant, 1982). Moreover, Fitzgerald et al. (1991) found that, in order to operate efficiently, it is critical that MCS in PSFs are capable of quick responses to changing circumstances. The evidence suggests that PSFs will design their MCS in a flexible way, granting employees the autonomy they demand, rather than in an inflexible way, imposing rigid controls to minimize deviations from prescribed actions. Drawing on to the above implications, the following relation is proposed:
H1b: Customer reliance is negatively related to implicit behavioral control tightness in PSFs
Referring back to the argumentation that professional organizations in a NON-PSF context are embedded in wider corporate structures, only serving one customer, it can be assumed that they know this particular customer and the behavior that is considered desirable. Therefore, presenting a support function with less direct responsibility and discretion, due to less uncertainty and non-routine decisions required at the customer interface, professional organizations in NON-PSFs, similar to mass service providers, are assumed to have more structured and formal behavior control systems compared to PSFs (Auzair & Langfield-Smith, 2005). Consistently, Fitzgerald et al. (1991) found higher degrees of flexibility in PSFs compared to mass service firms. Hence, the following relations are assumed:
H1c: The effect of customer reliance on explicit behavioral control tightness is less negative for NON-PSFs
H1d: The effect of customer reliance on implicit behavioral control tightness is less negative for NON-PSFs
Von Nordenflycht (2007) identifies professionals as employees who take hard to observe or control actions and value autonomy. This observation is in line with Raelin (1985) who argues that one feature of professional resistance to bureaucratic controls is their overemphasis on professional standards of evaluation, i.e. their preference of compensation based on results over conformance to rules and procedures. Furthermore, a professional service is no pre-defined product and the quality of the service cannot be assessed reliably before production is finished (Gluckler & Armbruster, 2003; Homburg & Stebel, 2009). Customers pose quality and outcome requirements unique for every professional service
transaction, thus creating the necessity for professional (frontline-worker) discretion and judgment in the development process. Given this setting of unique customer requirements, being able to adapt to such changes or newly arising customer needs is at the heart of delivering desirable results. The specific knowledge and expertise regarding customer needs (desired result) and subject related issues hereby lies with those employees who are directly in touch with the customer (Auzair & Langfield-Smith, 2005; Brivot, 2011; Hausman, 2003; Homburg & Stebel, 2009; Von Nordenflycht, 2007, 2010; Wemmerlöv, 1990). Therefore, and given a setting where actions might be hard to measure, PSFs focus on the ultimate outcome of work instead of actions themselves or the measurement of progress. In this context, results controls facilitate empowerment as actions are not restrained and therefore the following relation is proposed:
H2a: Customer reliance is positively related to explicit results control tightness in PSFs
As mentioned in previous sections, MCS design in PSFs requires extensive flexibility due to uncertainties arising from customer interaction. This customer-caused uncertainty at the personal level of professionals might lead them to fail their targets or desired results, although they are doing a good job. Hence, in response to these customer-driven uncertainty leading to ambiguity in the measurement of goal achievement, the following relation is proposed:
H2b: Customer reliance is negatively related to implicit results control tightness in PSFs
Taking back onto the argumentation of H1c and especially the premise that customers are well-known for professional organizations in NON-PSFs, resulting in less ambiguity in the measurement of results. Due to the supporting role, such divisions are usually considered cost centers with their services well embeded in internal pricing structures. This setting calls for explicit controls equally tight to PSFs while any adaptation, especially as unfforeseen events caused by their customer are more unlikely and targets are considered important to be met, is potentiall considered undesirable:
H2c: There is no significant difference between the effect of customer reliance on explicit results control tightness in PSFs and NON PSFs
H2d: The effect of customer reliance on implicit results control tightness is less negative for NON PSFs
H1 and H2 found on the general assumption that where behavioral controls are inapplicable, results controls offer companies means to tackle the conflict of interest between autonomy and coaching as well as controlling expertise (Løwendahl, 2005).
Explicit Cultural and Personnel Control Tightness
Cultural controls, in general, are often referred to as less formal and aimed at creating and facilitating shared values and beliefs within a professional group. Cultural control is exerted through socialization activities and the resulting self-regulation through collegiality and employee bonding. This form of social control has been argued to be most effective in inspiring goal congruence when knowledge of the transformation process is imperfect or progress cannot be measured unambiguously (Govindarajan & Fisher, 1990; Turner & Makhija, 2006). Furthermore, professionals have been identified to show commitment to their work and profession rather than their company (Kerr et al., 1977). In this sense, organizations employing significant numbers of professionals find themselves in a professional-organizational conflict between professionals rejecting bureaucratic control and their commitment to the company (Aranya et al., 1981). In this conflict-driven setting and in light of high personal uncertainty through customer reliance, professional service providers are determined to create an environment of collegiality through a system dominated by social control dominated, with the formal controls operating in a secondary role (Jaworski et al., 1993). Additionally, highly skilled employees with substantial human capital to their organization, such as professionals, are in a strong bargaining position since their skills are scarce and they have high levels of discretion at the client-interface. Also, this discretion and extensive communication with customers provides professionals with plenty outside options, making them hard to retain (Von Nordenflycht, 2010). In this context, cultural controls provide the means to create a sense of ownership for professionals and create organizational commitment. This argumentation is in line with self-supervision being the proposed primary control mechanism in professional organizations (Mills et al., 1983). Research has suggested that professionals exercise self-regulation by taking responsibility for their task-specific activities rather than having their task activities closely monitored by a supervisor. Self-regulating professionals tend to favor substitutes for leadership, such as professional norms and cohesive work groups (Larsson & Bowen, 1989). The effectiveness of self-supervision depends strongly on the personal relationship between the professionals and can only be successful if they can identify themselves and bond with the norms and values shared by the other. Hence, the following relation is proposed:
H3a: Customer reliance is positively related to explicit cultural control tightness in PSFs
Considering the above explanation, cultural control can be located in the throughput phase of the professional service production. While professional organizations have generally been described to encounter uncertainty due to customer reliance, cultural controls hold great potential to reduce uncertainty in the throughput process by creating a collegial work environment, encouraging the exchange of experience, information and support. Nonetheless, certain levels of imperfect knowledge and uncertainty remain within the transformation process, resulting in limited ability to measure progress or milestones. For such circumstances, Modell (1996), calls for informal mechanisms such as ritual, clan or cultural control. In this line of reasoning, Lowry (1993) argues that the non-routine production of professional services is indicative of low means-ends knowledge. He concludes that formal efficiency measurement therefore becomes problematic. Acknowledging the significance of cultural controls in this context of low applicability for formal controls, professional service organizations are assumed not to encourage flexibility in this dimension. For cultural control being a driver in reducing uncertainty, the following relationship is proposed:
H3b: Customer reliance is positively related to implicit cultural control tightness in PSFs
In contrast to PSFs, mass service firms have been argued to show greater potential for the application of formal controls. Furthermore, Fitzgerald et al. (1991) found that professional service firms generally appear more flexible than mass service firms. Professional organizations in a NON-PSF context can be considered to offer more standardized service products and commonly share the culture and norms of their roof organization and thus have less imperfect knowledge of the process. Hence, changes in customer needs are not as drastic or unforeseen, making operations more applicable for formal controls and leading to the following proposition:
H3c: The effect of customer reliance on explicit cultural control tightness is less positive for NON PSFs
H3d: The effect of customer reliance on implicit cultural control tightness is less positive for NON PSFs
In pure service situations lacking an exchange of tangible goods (Homburg & Stebel, 2009), the quality of the service is hard to measure and may solely rely on the service encounter itself (Solomon et al., 1985). Hausman (2003) argues that the production process of a professional service involves repeat, frequent encounters with the same professional(s)
rendering the service. Hence, the social skills of professionals engaging in close relationships with their clients are of significant importance in order to encourage the sharing of confidential information (Hausman, 2003; Mills & Margulies, 1980). Simultaneously, while required to possess high interpersonal and social skills, professionals are expected to have passed extensive education and training to gain expert knowledge and skills to analyze and structure complex issues (Hitt et al. 2001). Abernethy & Brownell (1997) find that non-accounting controls, especially personnel controls appear to be most suited in such cases. In extension, Silvestro (1999) proposes that effective personnel controls are at the core of professional service management. Summarizing, personnel controls are directed at assuring that new hires adequately adhere to the prevalent high standards in PSFs. In line with this argumentation, the following relation is proposed:
H4a: Customer reliance is positively related to explicit personnel control tightness in PSFs
The process of hiring professionals can be considered an input to the people centric business model of professional service providers. Furthermore, the process of acquiring human capital is rather expensive (Hitt et al., 2001), associating failures in hiring with high levels of sunk cost. Knowing that professionals are the core business resource for generating a competitive advantage and that unfavorable variances in hiring quality create high costs, professional service providers will unlikely be willing to tolerate deviations in input quality. This is assumed to be reflected in the following proposed relationship:
H4b: Customer Reliance is positively related to implicit personnel control tightness in PSFs
Despite the aforementioned differences in PSFs and NON PSFs, both typologies of organizations are highly reliant on human capital in creating a competitive advantage and achieving organizational effectiveness (Abernethy & Brownell, 1997; Lepak & Snell, 1999). Therefore, professionals are to be considered an equally important resource for both types of entities, suggesting the following relations:
H4c: There is no significant difference between the effect of customer reliance on explicit personnel control tightness in PSFs and NON PSFs
H4d: There is no significant difference between the effect of customerreliance on implicit personnel control tightness in PSFs and NON PSFs
H3 and H4 summarize the premise that, if customer reliance is high, professionals are required to hold certain skills and values that let the customer perceive the service as qualitatively high standard and create a strong sense of group cohesion while.
Figure 1 shows an overview of the proposed logical links between customer reliance and control tightness for each MCS dimension:
3 Research Methodology
This section describes the research method applied in this study. This paper is developed in the context of Helena Kloosterman’s online survey project on MCS tightness in PSFs at the University of Amsterdam. Collaborating in this research project offers numerous advantages: First, this paper explicitly focuses on professionals with three or more years of relevant experience in their field. Despite growing personal networks and the ease of connecting via professional online networks, it is challenging, if not impossible, for one single person to obtain a representative sample within the thesis period. Second, joining an existing project offered access to a ready developed survey that uses construct sources meaningfully supporting the operationalization of the theoretical framework this study develops. Third, the survey method is the most prevalent in PSF and MCS research (see, for example, Auzair & Langfield-Smith, 2005)and appears the best suited in order to investigate MCS design in the management of professionals. Last, generating a comprehensible set of original data offers the best possible prerequisite for investigating the newly developed concepts of explicit and implicit MCS tightness and to address the research question.
3.1 Sample Selection
This study draws on Von Nordenflycht's (2010) taxonomy of PSFs comprising both traditional professional services (audit, consulting, law) and other knowledge-based organizations reliant on their workforce (e.g. advertising and marketing agencies). The sample population is further extended by employees rendering professional services as a support function within large organizations (e.g. law department of a car manufacturer). Given their special implications for management, organizations from the non-profit, education or social work sectors as well as government organizations are excluded. Furthermore, respondents are required to have to worked in their field for more than three years to assure the meaningfulness of survey results. Although MCS research has frequently focused on a top-management perspective, addressing issues of monitoring, compensating or motivating employees (Wouters & Wilderom, 2008), this study investigates professionals who both interact with the customer and are directly affected by the MCS imposed by management. Hence, respondents actually need to be affected by the control system and may thus neither be owners, partners nor board members. Last, the MCS respondents are affected by needs to be formally developed, i.e. the company of a certain size. Therefore, this research focuses on respondents working in organizations with 50 or more employees. The fulfillment
of these requirements and quality of data is assured by asking respondents to send an email including their company signature and position to their respective person of contact within the project. The initial sample consists of 372 respondents (197 PSF, 135 NON PSF). Considering the above requirements set towards the inclusion of responses, a total of 78 responses has been excluded, leaving a final dataset of 294 respondents (176 PSF, 118 NON PSF).
Table 3 Sample Selection Process
Initial Respondents 372
Relevant Questions not Answered 53
Experience 11
Occupation 2
PSF or support function 40
Occupation Criteria not Fulfilled 9
Administrative Assistants 2
C-Position (e.g. CEO, CFO) 3
University Research or Teaching 3
Self-Employed 1
Experience Criteria not Fulfilled 16
Final Respondents 294
Panel A: PSF 176
Panel B: NON PSF 118
Considering the exploratory nature of this study and the large number of constructs involved in hypothesis testing, incomplete questionnaires were not eliminated. The proposed relationships between customer reliance and MCS dimensions are tested individually and thus do not require equal sample sizes. Further analysis of MCS as a whole or on interactions between certain dimensions would require further trimming of the sample base.
When examining the most prevalent occupations and countries of employment, 23.5% of the respondents indicated employment in the accounting sector, 20.1% in consulting, 7.1% in medicine 4.1% in marketing and 3.1% in law and risk management services respectively. The largest share, 59.5% of the respondents, indicated to be employed in the Netherlands, followed by 12.2% employed in Germany and 5.8% in Aruba. Table 4 shows further descriptives of the respondents1.
Table 4 Respondent Descriptive Statistics
Total Sample N Min Max Mean Median Std. dev
(1) Age 281 22.00 63.00 34.80 33.00 7.78
(2) Educationa 281 1.00 3.00 1.74 2.00 0.64
(3) Experience Fieldb 294 3.00 11.00 7.18 7.00 2.83
(4) Experience Company 293 1.00 11.00 5.93 5.00 3.00
a Bachelor = 1, Master = 2, PhD/ Doctorate = 3 b Max 11 = more than or equal to 11
3.2 Survey Design and Variables
The overall survey is designed to capture several antecedents presumed to affect implicit and explicit MCS tightness for each control dimension as well as several control variables based on existing MCS research. All in all, the survey offers a very comprehensive set of dependent, independent and control variables allowing several analyses. This study, however, focuses on investigating customer reliance as an antecedent (independent variable) of explicit and implicit MCS tightness for each of the aforementioned control dimensions (dependent variables) in the professional services context. In order to assure the reliance and originality of the data gathered simultaneously, variables are measured using both existing and newly developed constructs2.
3.2.1 Independent Variable
The independent variable subject to this analysis is customer reliance (CREL), i.e. the extent to which successful service provision is dependent on the client’s substantive cooperation and collaboration with the professional. CREL is constructed using both elements adapted from Homburg & Stebel (2009) and newly developed items. CREL encompasses six questions scored on a five-point Likert scale, one of which is scored reverse. Respondents are asked to indicate their dependency on customer input, the extent of coordination and collaboration required and their ability to perform tasks successfully without client input.
3.2.2 Dependent Variables
This study examines eight dependent variables in order to describe the control responses professional organizations take through explicit emphasis on or implicit reduction
