Maritime Policy & Management Management control

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Maritime Policy & Management

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Management control systems and performance: evidence from the Greek shipping industry

Androniki A. Triantafyllia; Apostolos A. Ballasb a Department of Accounting and Finance, Manchester Business School, The University of Manchester, Manchester M15 6PB, UK b Department of Accounting and Finance, Athens University of Economics and Business, Athens 104 34, Greece Online publication date: 20 October 2010

To cite this Article Triantafylli, Androniki A. and Ballas, Apostolos A.(2010) 'Management control systems and

performance: evidence from the Greek shipping industry', Maritime Policy & Management, 37: 6, 625 — 660 To link to this Article: DOI: 10.1080/03088839.2010.514957 URL: http://dx.doi.org/10.1080/03088839.2010.514957

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Electronic copy available at: http://ssrn.com/abstract=1829492

MARIT. POL. MGMT., NOVEMBER VOL.

37,

NO.

2010,

6, 625–660

Management control systems and performance: evidence from the Greek shipping industry ANDRONIKI A. TRIANTAFYLLI*y and APOSTOLOS A. BALLASz

Downloaded By: [informa internal users] At: 20:15 2 May 2011

yDepartment of Accounting and Finance, Manchester Business School, The University of Manchester, Booth Street West, Manchester M15 6PB, UK zDepartment of Accounting and Finance, Athens University of Economics and Business, 76 Patission Street, Athens 104 34, Greece This study explores how Management Control Systems (MCS) enhance the performance of shipping companies. Based on data collected from semistructured interviews, MCS are distinguished in three categories according to the purposes they fulfill: ‘‘Basic MCS’’ are implemented in order to set standards and support basic operations of the business, ‘‘Cost MCS’’ collect information about cost minimization while ‘‘External Information MCS’’ focus on compliance with the requirement of the cargo owners. Furthermore, evidence collected through a survey instrument addressed to shipping companies located in Greece suggests that the choice of MCS is contingent upon the strategy pursued by the shipping companies. Moreover, this paper tests whether shipping companies with an optimal fit between their strategies and their MCS experience superior business performance and a higher perceived usefulness of MCS. Results reinforce the notion that the performance of the shipping companies is contingent on the use of those control systems which are consistent with their strategies and a number of control variables such as experience of the person implemented the MCS, the size, and age of company.

1. Introduction Over the past two decades, contingency-based research in managerial accounting has focused on how large, mature manufacturing organizations design their performance measurement and control systems as a function of a number of contextual variables, or contingencies [1]. However, there is no evidence of research that examines the choice of Management Control Systems (MCS) in the shipping sector, despite its importance for the economy of most developed countries. This study investigates the performance implications of MCS in the Greek shipping industry. The investigation of control systems in the shipping industry becomes even more important due to the recent, extensive implementation of numerous rules and regulations such as the International Safety Management (ISM) Code (1997) related to safe operation of ships and protection of the marine environment, the improvement of the public control and follow-up and the improvement of contract relations among the governments (flag states). In addition, new requirements from the cargo owners in terms of safety and reliability of services *To whom correspondence should be addressed. E-mail: [email protected] Maritime Policy & Management ISSN 0308–8839 print/ISSN 1464–5254 online ß 2010 Taylor & Francis http://www.tandf.co.uk/journals DOI: 10.1080/03088839.2010.514957

Electronic copy available at: http://ssrn.com/abstract=1829492


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enhance the demand for more complete and thorough control mechanisms (i.e., TMSA controls [2]). As a result, shipping companies have started to put more emphasis in the design and implementation of those MCS that could enhance their compliance with the new circumstances. This shift towards the more detailed design and implementation of MCS in shipping companies offered the motivation for this study. Analysis of the shipping industry is important since it aims to provide a deeper understanding of the reasons that lead shipping companies to introduce and implement MCS, the nature of MCS used and the purposes MCS fulfill upon their introduction. Also, MCS were investigated in the literature so far for manufacturing and retail companies. The research of MCS in service sector is limited and the differences between the organization and function of shipping industry and manufacturing industry need to be mentioned in order to adapt the research to the specific conditions of the industry studied. Shipping is chosen for this study since it is one of the world’s most international industries. Seaborne trade is, in a sense, at the apex of world economic activity, and the first reaction of ship owners on hearing about global events would be to consider what effect they will have on the shipping market [3]. The story of the shipping industry since the Second World War was one of ingenuity, professionalism, fabulous profits, some disastrous miscalculations, and severe maritime accidents. It includes the meteoric rise of shipping superstars like Niarchos and Onassis and some miscalculations such as Tridal Marine which built up a 700 000 dwt [4] shipping fleet in the early 1970s and was subsequently indicted with a number of bankers in New York on charges of fraudulently obtaining more than $60 million in loans [3]. This phenomenon became the starting point for the inclusion of tight control systems in financial and operating departments of shipping companies. Moreover, it includes some of the most dramatic marine accidents such as the grounding of the Panamanian passenger ship Royal Majesty on Rose and Crown Shoal near Nantucket, Massachussetts on 10 June 1995. These severe marine accidents led to the need of the introduction of an appropriate legal structure that preserves issues of safety in order to avoid accidents and pollution (i.e., International Maritime Organization (IMO) regulations, ISM Code, etc.). The shipping industry has some characteristics that need to be considered and which differentiate it from other service industries. Shipping industry is a capital intensive one because it requires high investments in expensive capital goods (vessels). High capital requirements can discourage potential entrants in the aspect that they are signaling the presence of substantial scale economies that, in turn, limit the number of firms that can profitably enter an industry [5]. The freight market analysis suggests that there is a cyclical component in the shipping market generated by business circles and reinforced by the time lag taken to adjust supply to demand and the frequent miscalculation by ship owners of the future level of demand. Nowadays, most economists accept that economic cycles arise from a combination of external and internal factors. The external factors may include events such as wars, technological advances, or a sudden rise in the price of a key commodity such as crude oil, while the internal factors refer to the dynamic structure of the world economy itself, which, it is argued, leads naturally to a cyclical rather than a linear path [3]. Time lags (the delays between economic decisions and their implementation), random shocks (i.e., weather changes, wars, new resources, and commodity


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prices changes), mass psychology, and the multiplier and accelerator phenomena are the main cause for the existence of cyclicality in shipping industry. Another characteristic is the distance between the office and the ‘‘production unit,’’ the vessel. This fact causes communication problems and the existence of a capable captain that communicates smoothly the information about vessel’s and cargo’s condition to the office is of great importance. Especially for the Greek shipping companies, there exists another characteristic: the majority of Greek shipping market consists of many small-and medium-sized companies, which are family-owned. That fact constitutes our motivation to eliminate our analysis to non-listed shipping companies [6]. The technological changes in shipping industry, the high volatile economic environment of the shipping industry and the effort to find ways of managing ships more efficiently and thus reduce costs led to the development of shipping management as a discipline. Shipping management is described by Spruyt [7] as ‘‘the contracted and professional supply of all on-board services, together with their shore supervision, which would normally enhance a vessel from a bareboat into a time charter description, by a management company usually separate from the vessel’s ownership’’, but he adds immediately that his definition could be narrowed down or expanded accordingly to underline the specific services provided. Nevertheless, one can most safely assert that ship management is all about caring for the ship and its cargo, and being responsible for manning, maintaining, supplying, and navigating the ship in a safe and efficient manner [8]. However, the complexity of ship management is not only attributed to the variety of services offered, as earlier mentioned, but also to the differences in the character and structure of the ship management companies. Ocean shipping management companies have been studied based on the traditional management tools and theories [9–12] as independent and isolated elements emphasizing on their internal structures and functions. Within the strategic point of view, a number of studies exist focusing on the factors that affect the strategic decisions made by ocean shipping management companies at the corporate level [13–16]. Some of these studies focus on the identification of strategies which would enable ocean shipping companies identify and take advantage of the different business opportunities in order to become more successful and thus grow. Suggestions such as the change of the present formal planning and control mechanisms [16] and the creation of partnerships, which can provide the competitive advantage [14, 15] that companies are after appear in these studies. This study tries to examine the role of MCS and strategy as important determinants of the efficiency of Greek ocean going shipping companies. This study was conducted in two phases. Initially, field interviews were conducted followed by a survey instrument directed to shipping companies’ managers. In the first phase, the interviews were used to understand what MCS are introduced and implemented in shipping companies and why. In the second phase, the survey-based instrument was used to test whether shipping companies with a better fit between MCS and their strategies experience superior performance. The interviews reveal that shipping companies characterize their MCS in terms of the purposes MCS should fulfill, rather than in terms of individual control systems. Three categories of MCS emerged from the data: ‘‘Basic MCS’’ are common to all firms and are used to set standards and support basic operations of the business, and ‘‘Cost MCS’’ collect information about cost minimization, while ‘‘External


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Information MCS’’ focus on compliance with the requirements of cargo owners and on protecting asset integrity. The findings suggest the relationship between the strategy followed by the shipping companies and the choice of the two latter types of MCS. Finally, regarding the performance consequences of the choice of MCS results indicate that a better fit between MCS and the shipping company’s strategy and organizational structure is associated with management perception of superior firm performance and greater usefulness of MCS. The purpose of this paper is to add to the limited body of knowledge of the design of MCS in service firms and specifically in shipping. For this study, a contingency approach has been used. Contingency approach is used in this study, since it provides insights into MCS in contemporary settings, particularly in the case of service sector companies such as shipping companies where there has been limited research [1, 17]. Therefore, this study tries to provide a deeper knowledge and understanding of MCS and their context by extending contingency relationships established in manufacturing firms to profit-seeking service firms and in this case especially to shipping industry. This paper contributes to the tradition of contingency theory by, unusually, considering a broad range (29) of MCS rather than concentrating on narrow issues and by integrating simultaneously the contingent variable (i.e., strategy) and a number of other control variables that may affect the design of MCS. These variables include dimensions of the structure and the ownership condition of a shipping company and a variable that has not been considered so far at the literature of contingencies in the formation of MCS, but it is important for the shipping industry: the impact of international rules and regulations in the formation of MCS. Moreover, the study tries to reconcile both the benefits of contingency research with the advantages of field study and thus provides a more thorough and deep understanding of the way MCS are used specifically in the shipping industry. The study was conducted in two phases: first 30 field interviews [19] were conducted and then a survey instrument was directed to the managers of shipping companies. The interviews were used to understand what MCS are introduced and implemented in shipping companies and why, while responses to the survey-based instrument were used to test (1) whether the strategy pursued by shipping companies significantly determines their choice of MCS; and (2) whether shipping companies with the better fit between MCS and their strategy experience superior performance. Drawing on the strengths of this mix of quantitative and qualitative methods facilitates a systematic and comprehensive analysis of the relationship between MCS and the organizational variables tested. Specifically, while the questionnaire provides an understanding of strategy and the other organizational variables and the use of MCS mechanisms, the inclusion of interviews enables the understanding and interpretation within a rich and more meaningful context. Between methods, triangulation offers ‘‘a relatively potent means of assessing the degree of convergence as well as elaborating on divergences between results oriented’’ [20]. The remainder of this paper proceeds as follows. The Section 2 presents a literature review and the development of the hypotheses. Section 3 describes the importance of the maritime law in MCS implementation for shipping companies, while Section 4 describes the main control practices of shipping companies. Section 5 analyzes the strategies employed by the Greek shipping companies the past 30 years, whereas Section 6 describes the research design and data collection methods.


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Section 7 focuses on the development of the categorization of MCS, and Section 8 focuses on the choice of MCS according strategy and analyzes the performance implications of this choice. The conclusion and limitations of the study is presented in Section 9.

2. Literature review and hypothesis development 2.1. MCS and strategy ‘‘Management Control Systems is the process by which managers assure that resources are obtained and used effectively and efficiently in the accomplishment of organization’s objectives’’ [21]. MCS is thus the process that links strategic planning and operational control [22]. MCS have the purpose of providing information useful in decision making, planning, and evaluation [23, 24]. Simons [25] argues that ‘‘MCS are the formal information-based procedures managers use to maintain or alter patterns in organizational activities.’’ Whereas, strategic control assesses the question whether the strategy chosen by the organization is valid, management control according to Merchant and Van der Stede [26] addresses the question whether employees behave appropriately or not. MCS are therefore intended to help employees to make decisions and to take actions which are in the organization’s best interest [27]. MCS have thus two main purposes: providing information useful to management and helping to ensure viable patterns of employee behavior in order to achieve organizational objectives. In the broadest sense, control systems can be viewed as having two basic functions: strategic controls and management controls. Strategic control involves managers addressing the question: Is our strategy valid? Management control involves addressing the general question: Are our employees likely to behave appropriately? The tools for addressing strategic and management controls are quite different. Managers addressing strategic control issues have a focus primarily external to the organization; they examine the industry and their organization’s place in it. Managers addressing management control issues, on the other hand, have primarily an internal focus; they think about how they can influence their employees’ behavior in desired ways [26]. This paper focuses on management control. From a management control perspective, strategies should be viewed as useful guides to the implementation of MCS. When strategies are formulated clearly, more control alternatives become feasible, and it becomes easier to implement each form of management control effectively. The contingency approach to management accounting is based on the premise that there is no universally appropriate accounting system which applies equally to all organizations in all circumstances [28]. Rather, it is suggested that particular features of an appropriate accounting system will depend upon the specific circumstances in which the organization finds itself. Thus contingency theory identifies specific aspects of an accounting system which are associated with certain defined circumstances and demonstrates an appropriate matching [28]. Chenhall [1] discusses contingency theories from a functionalist perspective where the assumption is that (management control systems) are developed, or adopted to aid in achieving desired organizational goals and outcomes. The appropriate management accounting system is contingent on the external environment, technology, organizational structure, organizational size, organizational strategy, and

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national culture. The graphic below illustrates this functionalist perspective.

Previous studies have shown that the choice of MCS depends on a number of contingencies surrounding the firm such as structure, technology, size, and environment [29–36]. More recently, firm strategy has emerged as an important contingency in analyzing the use and usefulness of MCS. For the purpose of the study, MCS are defined as ‘‘any formal information-based procedures and statements used by managers to monitor and influence the behaviour and activities in a firm’’ [37]. Literature abounds with definitions of strategy ranging from the general to specific. ‘‘But despite their differences there is a common theme. Strategy is thought to constitute a logic underlying an organization’s interactions with environment’’ [38]. A variety of taxonomies has been used to define strategy in a way that is generalizable across firms and industries [39]. Literature abounds with definitions of strategy ranging from the general to specific. ‘‘But despite their differences there is a common theme. Strategy is thought to constitute a logic underlying an organization’s interactions with environment’’ [38]. Porter [40] described two generic strategies (cost leadership, differentiation) and argued that each of these provides a sustainable competitive advantage in an industry. For companies pursuing a lowcost strategy, their competitive advantage comes from economies of scale, low-cost raw materials, and superior technology that make them the lowest cost producers in their industry. For differentiators, emphasis is given on providing products with attributes that are highly valued by their customers such as product quality, flexibility, wide availability, and others. Following Porter’s [40] strategy categorization, the analysis of the firm’s strategy comes under two dimensions: the extent of differentiation and the extent of cost leadership. The Porter’s [40] strategic typology was used in this study for several reasons. First, it provides the richest description of organizational characteristics associated with each strategy. Second, it is the most commonly used strategic typology and as such it would provide the basis for comparison to previous studies [18, 41–43]. Finally, as suggested by Langfield-Smith [39] other frameworks (i.e., [44–46]) can be integrated under the Porter’s framework. Specifically for the


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shipping industry, the introduction of the term ‘‘quality shipping’’ [47] is important for the firms using differentiation strategies, meaning that these shipping companies focus primarily on innovation and the formulation of the attributes of the services that are highly valued by their customers. These include: . quality of services: satisfaction of charterers, terminals, and cargo owners in terms of speedy and safe delivery of cargo; usually these companies are certified by ISO 9001 on a voluntary basis in order to assure their customers about the quality of the services they offer; . safety of services: number of accidents, number of incidents, number of lost injuries, number of defects and dealing time of defects, number of port state controls, number of class recommendations, etc.; . environmental protection: use of processes, practices, techniques, materials, products, services, or energy to avoid, reduce, or control the creation, emission, or discharge of any type of pollutant or waste, in order to reduce adverse environmental impacts; . investment on new technologies: double hull vessels, new machinery, etc.; and . personnel training (i.e., participation in seminars, receipt of certifications about ISM, internal audits, new technologies, new regulations stemming from the IMO, and other international organizations, etc.). On the other hand, there is the low-cost (non-quality) shipping emphasized by shipping companies whose primary aim is to offer their services on the lowest cost. The source of this competitive advantage may arise from factors such as economies of scale, minimum investments on technology, safety, and personnel training. Researchers found empirical evidence that the choice of MCS by top managers is contingent upon the strategy the firm pursues in order to position and compete in the market [18, 34, 40–45, 48–50]. Also Chenhall [1] states, ‘‘Strategy is somewhat different from other contingent variables . . . . It addresses the criticism that an organization’s MCS is determined by context and that managers are captured by their operating situation.’’ Based on the above evidence, it is expected that the strategy pursued by a shipping company will be a significant determinant in the choice of what MCS to implement. Previous research showed that firms following a strategy of cost leadership emphasize the use of MCS that are related to financial, quality and tight cost controls, operating goals, and budgets while differentiators use more flexible structures and processes and focus on customer needs in order to respond rapidly in competition and environmental change [18, 34, 40–45, 48–50]. The above evidence leads to the following hypotheses: Hypothesis 1a: Shipping companies following low cost strategies (non-Quality Shipping) emphasize more the use of MCS focused on tight, financial and budget information, as well as information to control the firm’s quality, costs and operating goals, more intensely than those not following low-cost strategies. Hypothesis 1b: Shipping companies following differentiation strategies (Quality shipping) emphasize more the use of MCS that focused on flexible information that allow them to respond rapidly to the environment more intensely than those not following differentiation strategies.


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2.2. MCS and performance In the management accounting literature, there are a number of studies that suggest a positive relationship between MCS and organizational performance [51–58]. MCS are used to guard against undesirable behavior and encourage desirable actions [59]. Thus, they promote goal congruence between the individual and the organization, coordinate and communicate strategic priorities, direct managers to critical areas of concern, and improve the allocation of resources based on organizational goals [60, 61]. Baines and Langfield-Smith [51] argue that the provision of information offered by MCS helps support resource management and fosters performance. MCS can improve contracting and, ultimately, performance by incorporating information concerning managerial actions that are not fully captured in the financial results [56, 62–66]. In addition, following a resource-based view, MCS contribute to the development and maintenance of organizational capabilities leading to the achievement of a competitive advantage and superior performance [67]. Literature provides evidence that companies that adopt MCS according to their strategies outperform companies that do not associate their control systems with their strategy [68, 69]. Nanni et al. [70] conducted a series of case studies which provide evidence that companies align their MCS according to their strategies to realize superior performance. The measurement of performance is used not only to guide the execution of strategy through actions, but also to evaluate strategy in terms of the results of taking the required actions. However, the literature provides no evidence yet about the performance outcomes (if any) of the implementation of MCS in shipping companies. To verify whether these results apply to the Greek shipping industry, we tested the following hypothesis: Hypothesis 2: Shipping companies with a better fit between their MCS and their Strategy realize superior performance.

3. The importance of international system of maritime law in MCS implementation Maritime law is the main source dealing with rules and regulations concerning the safety of marine operations, the prevention of accidents and pollution, international labor issues, etc. The implementation (usually mandatory) of the rules and regulations stemming from international conventions leads shipping companies to introduce and implement MCS in order to keep in track with the requirements of the latest laws. Over the years, many international conventions were developed to act as a basis for nautical maritime legislation. In the recent years, this service was devolved to three agencies of the United Nations—the IMO, the International Labour Association (ILO), and the Shipping Committee of UNCTAD. Each of these organizations deals with a particular range of maritime affairs. The eighteenth IMO assembly adopted the ISM Code. The Code became mandatory in 1994 and it was revised in 1997. Its intention is to improve the use of mandatory requirements and rules related to safe operation of ships and protection of the marine environment, to improve the public control and follow-up and to improve contract relations between the governments (flag states) [71]. The ISM objectives are the prevention of human injury, damage to property, and pollution of the environment and its purpose is the establishment of a Safety Management



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System, the commitment of top management to safety and pollution prevention, and the promotion of safe and pollution free ship management. The ISM Code applies at all levels ashore and afloat. It includes 13 articles that cover a wide range of issues such as safety and environmental protection policy, company responsibility and authority, designated persons responsibilities, Master’s responsibility and authority, resources and personnel, reports and analysis of non conformities, maintenance of the ship and equipment, development of plans for shipboard operations, documentation, company verification, review and evaluation, and certification and control issues. Another important standard for shipping companies is the Standards of Training Certification and Watchkeeping for Seafarers (STCW) which was introduced in 1978, and amended in 1995. Its main objectives are the establishment of an international system for training, supervision, assessment, and certification, the assurance that mariners have knowledge and competence to do their job, the assignment of responsibilities to all parties involved, and the establishment of control mechanisms for the verification of the above-mentioned purposes. All training, assessment of competence, certification, endorsement, and revalidation activities should be carried out through a quality standards system. Instructors, supervisors, and assessors should be qualified. Each seafarer should hold an appropriate certificate as per STCW 95. Company’s responsibilities also include the maintenance and accessibility of documentation data of the seafarers, the familiarization of seafarers with their specific duties, equipment and procedures, relevant to their routine or emergency duties, and the fact that crew can effectively co-ordinate their activities in an emergency situation and in tasks vital to safety-pollution prevention. Finally, the MARPOL Convention is the main international convention covering prevention of pollution of the marine environment by ships from operational or accidental causes. It is a combination of two treaties adopted in 1973 and 1978, respectively, and updated by amendments through the years. The Convention includes regulations aimed at preventing and minimizing pollution from ships—both accidental pollution and that from routine operations. ISM implementation is a basic auditing procedure for a shipping company. According to the Safety Manager of a large shipping company located in North Athens: ‘‘I.S.M and S.O.L.A.S are important auditing tools. The correct implementation of I.S.M is important for claims too. Insurance companies always (every time a claim happens) ask written documentation from D.P.A that ensures that company’s procedures are in accordance with the requirements of I.S.M Code. The shipping company at least once a year performs internal audits to vessels in order to ensure compliance with the safety requirements set by I.S.M Code. The relevant report is presented during the Management Review Meeting that take place at the year end. According to S.O.L.A.S several surveillances (internal audits) take place from the technical department to vessels in order to ensure the safety of constructions, the safety of the equipment existing on vessels, the safety of radio systems, the existence of statutory certifications, etc.’’

4. Control systems in shipping companies In every shipping company, especially due to the increased legislation and the claims of the charters, there are several categories of internal controls taking place all

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over the year. . Internal audits: The control takes place in key company operations and staff (usually to all departments of company). The auditors are certified and do not audit the department of the company which they are involved in. Objective evidence is a requirement; so there is always need for backup documents. The internal audit report refers to observations and non-conformities and is communicated to the General Manager of the company. . Navigational audits—vessel internal audits: The onboard personnel are never involved in the control process. There are three types of navigational audits: the audits performed by the master of the vessel, by the superintendents, and by external auditors (independent sources). . Superintendent visits: They take place on an annual or 6-month basis from the office superintendent engineers in order to examine the hull and machinery condition of each vessel. . TMSA controls (for tankers only): They are controls required by the oil majors. There are compliance levels (up to four) and each company’s compliance level with Oil Companies International Marine Forum’s (OCIMF’s) claims is renewed every 6 months. Also, shipping companies submit, once in every 6 months, their business plans to OCIMF, and these plans need to be realized in the next 6 months. . Unscheduled audits: These controls may be distanced (the office requires records in a time frame) or may be performed by an auditor unexpectedly. The extensive control systems used in the shipping companies give the motivation for exploring their relationship with strategy and their consequences on the performance of the companies.

5. Strategies of Greek shipping companies An important factor that has led Greek shipping companies to the top of the international maritime industry in the past 30 years is their ability to take advantage of the market opportunities and to face the challenges stemming from their business environment. Greek shipping companies have achieved this level of efficiency due to their strategies and most importantly due to their fleet specialization, the dominance of the low cost strategy during their operations, and their investment strategies. Greek shipping companies used to be specialists (and still are) in the management of tankers and bulk carriers. Only a small percentage of Greek shipping companies are focused on more specialized markets such as the chemical market and the LNG or LPG markets. This choice is first a result of the availability of the resources of the companies. The management of bulk carriers or tankers did become effective with the use of second-hand vessels and the management of the vessel was performed either by the members of the ship owner’s family or by external parties (i.e., management companies, etc.). Another important element of the strategic choices of the Greek shipping companies is their entrance on the market with the use of secondhand vessels. Ship owners used to acquire vessels on low prices from the second-hand market [72]. Their competitive advantage was (and still remains valuable) the contribution of Greek seafarers to the efficient operation of ships [73]. However, only during the past years, Greek ship owners have started the investments on new



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buildings, especially those companies that experience the growth phase of their life cycles. This finding is also due to the fact that the introduction of planning has taken place significantly slower than in other European countries [74]. Greek shipping companies have chosen to perform by using low cost strategies [75]. They insisted in the minimization of their operating costs. They decided to compete in the market with the use of second-hand vessels that provided shipping companies with low fixed cost but high operating cost. The Greek merchant fleet is managed by a large number of family-run and controlled firms. The archetype of Greek-owned shipping company is a small- or medium-sized firm, which has been established by a shipping entrepreneur, who is the strategic leader of the firm [76, 77]. In addition, he/she operates a family business with family members working in crucial posts of the managerial hierarchy. This archetype proved to be a successful and lasting one in the context of international shipping surviving even today amidst increasing trend towards consolidation [72]. Given that the key to business success is the long-run decisions of the entrepreneurs regarding the structure and culture of firms [78], the entrepreneurial philosophy determining both structure and culture of firms has been undoubtedly an important factor for the development of Greek-owned shipping companies. The entrepreneurial philosophy that stems from the professional origin of ship owners—as exseafarers or shipping companies employees—shapes a distinct business culture whose core values are hard work, trust, persistence, and loyalty [72]. These values formed the basis of the culture of their companies [79] and influenced their management styles. With regard to the former, the dominant culture of the Greek shipping companies was the power culture included in the Harrisson [80] and Handy [81] typology. In the power structure, companies have the ability to move quickly and react well to threat or danger. Power culture appears to fit properly the ever-changing business environment of the bulk shipping industry. Entrepreneurial philosophy and its core values led to a centralized management style that is one of the factors that explains the application of traditional models of conducting shipping business. It leads them to retain the absolute control of the business at strategic and operational levels and to refuse outsourcing what they considered as their core competency and source of their competitive advantage, i.e., technical management of ships [72]. The seafarers could serve this management style with their expertise and their hard work. At the same time, Greek shipping companies followed the adoption of mandatory-or-not safety and quality rules and regulations and the acquirement of new buildings, in an effort to improve their competitiveness in the market. Usually, Greek shipping companies adopt long-term time charters as a main investment strategy but also they used the fleet lay-up or back sales as an alternative strategy when the freight market was experiencing low levels of performance. Particularly during the twentieth century, back sales constituted one of the most successful entrepreneurial strategies of Greek shipowners [76]. Both strategies (longterm charters and sales back) may seem not to be in accordance one with another, but in the case of Greek-owned shipping companies they acted complementarily. When a company experiences a stable strategy, then deviations from the prescribed strategy model may occur that lead to emergent strategies, but the vision of the company remains the same [82]. The stable way for Greek shipping companies to compete in the market is by providing transport services. Back sales are a deviation from this strategic priority but they took place in order to reduce the fixed costs and

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give liquidity to the shipping company when needed. The greatest part of the Greek shipping companies that deal with the back sales strategy do not exit the market, but they change their fleet number over time. They sell their vessels when freights are high and they buy them back when freights reach lower levels. The annual return allows shipping companies to triple or quadruple their capital shortly [72]. Back sales strategy is a part of the conservative approach that Greek shipping companies have adopted so far in terms of their resource consumption.

6. Research design and data collection This work relies on field-collected data; exploratory interviews with experts in the shipping industry and a survey instrument completed by a sample of Greek-based shipping companies. Focusing on a single industry provides depth to the study and allows controlling for several industry—specific conditions—including regulations and environmental conditions—factors that may be relevant to the introduction of MCS in a company. Initially, information was collected from 30 exploratory interviews directed to a number of professionals with previous experience in the shipping industry. The interviewees were conducted from November 2006 to February 2007. From these interviews, arose the opportunity to obtain a qualitative description of the MCS used in the shipping industry and the circumstances leading to their implementation. Second, data from a survey of top managers in 75 shipping companies are used. The questionnaire is composed of two sections. The first section gathers information on firm’s strategy and identifies firm’s value proposition. The second part focuses on the description of MCS implemented by the firm (purpose, usefulness, etc.). The final set of questions asks managers to self-assess the overall performance of the firms they manage. After designing and pilot testing the questionnaire, it was sent to the targeted firms along with a cover letter directed to the managers of the company. The population of firms targeted by this survey consists of all Greek-owned oceangoing merchant marine shipping companies that own more than four ships each at the time of study, a total of 190 [83] companies. These criteria were chosen in order to ensure that the resulting sample was composed of firms that had understood and implemented MCS. Companies were identified from the Greek Shipping Publications 2007 database. Department and general managers were chosen as respondents because they are knowledgeable about the MCS of the firms. In addition, they occupy a position in which they have knowledge about strategic issues and other items asked in the survey. The letter briefly described the motivation for the study and offered him/her a copy of the results. This mailing was followed up with two rounds of e-mails to non-responding firms requesting the same information and at least five telephone calls. The respondents had the option to complete the survey on line or on paper and even through a telephone or face-to-face interview. Confidentiality was guaranteed to all respondents. Out of the 190 companies targeted, 75 companies replied; i.e., a response rate of 40% approximately. Table 1 provides an overview of the respondents in the survey. The completion of questionnaires took place between September 2007 and February 2008. In most cases, the respondent was a top manager from one of the

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Management control systems and performance Table 1.

Sample description. Number of respondents

Percentage of respondents

Managing director Technical managers Operations managers Safety managers Fleet managers Finance managers Others [130]

10 8 10 10 13 8 16

13.3 10.6 13.3 13.3 17.3 10.6 21.3

Total sample

75


Position of respondents

100

Table 2.

Descriptives of the sample.

Variable

Mean

SD

Lower quartile

Median

Upper quartile

Size (number of vessels) Age (number of years) EXPERIENCE PERCPERFORM USEFULMCS

15.94 23.44 0.37 3.72 2.85

17.96 16.07 0.49 0.97 3.42

6.00 10.00 – – –

8.00 21.50 – – –

17.00 37.50 – – –

technical, operations, or finance departments of the firm. 40% of the respondents in the survey include companies owning dry bulk carriers, whereas 21.3% of the companies own only tankers, and 20% of the participating companies own both dry bulks and tankers. 6% of the participating companies own LPGs, 4% of companies own containers, and 8% of the participating companies own reefers. The average number of dry bulk carriers is 9.13 vessels per company, whereas the average number of tankers is almost 12 vessels per company; shipping companies owning LPGs have an average of 11 vessels per company, and shipping companies owning containers have an average fleet of 6 vessels per company. As for the average tonnage, companies owning dry bulk carriers manage in average vessels with a total tonnage of approximately 1006 700 dwt, whereas for the tankers the tonnage increases to 1617 800 dwt; for the companies owning LPGs the average tonnage of their fleet is 966.666 m3, whereas the average size of the containership owners is 4364 TEU. Descriptive statistics of the sample presented in Table 2 include the size and age of companies and the control variables used for testing the hypothesis developed. In order to test for non-response bias, a two-step analysis was conducted. First, respondents were compared with non-respondents in terms of the sample characteristics size and age; t-tests did not reveal significant differences between respondents and non-respondents in terms of size and age. Then, the main construct measures (MCS variables, strategy, and performance) were checked for dissimilarities between the immediate respondents and the respondents to the follow-up surveys. Independent samples t-tests did not reveal differences. As a result, nonresponse bias is not a major concern in this sample.


638


7. Value-based categorization of MCS 7.1. Categorization of MCS according the informational purposes of shipping companies Initially, we explored whether there is a variation in the nature of MCS introduced and used by shipping companies. Qualitative and quantitative analyses were performed on the basis of the interviews with shipping industry’s experts and the survey responses. After learning the two main purposes of MCS from the exploratory interviews and identifying the 29 individual control systems used in the shipping industry, we explored whether the two major purposes affected the frequency of introduction of any specific individual control system. The first set of questions in the survey explored which MCS were introduced in each firm. A second set of questions in the survey asked about the type of information sought through the MCS. Managers were asked the extent to which their companies utilized MCS to capture the different dimensions of information identified in the academic literature (internal vs. external, financial vs. non-financial, learning vs. monitoring, and tight vs. flexible), as well as those that emerged through interviews (minimize costs, use of externally oriented information). Each dimension was ranked in a Likert scale from 1 to 5, where 1 indicated that the particular MCS was ‘‘not used at all’’ and 5 indicated that it was used ‘‘to a great extent’’ for the informational purpose in question. In order to test whether there is a variation in the nature of MCS introduced and used by shipping companies, a factor analysis [84] (where factors are allowed to be correlated [85]) procedure was estimated. Results indicate that several dimensions of information are pursued simultaneously. The two factors solution was determined using a scree plot of the eigenvalues (total communality between all variables and each factor). The two factors selected had eigenvalues greater than 1 (thus satisfying the Kaiser criterion) [86]. The two basic informational purposes of MCS that have been identified are either to externally orient information, i.e., to analyze external information based on customer satisfaction, competition, and economic events, or to minimize cost and achieve operational efficiencies, i.e., to achieve internal learning by constantly setting targets and comparing actual performance against these targets. The values of variance explained by factors 1 and 2 (each taken in isolation) are 3936 (43.73%) and 1083 (12.03%) [88], respectively. The factors identified confirm the two types of information purposes that emerged through the interviews, thereby providing support for the two categories of MCS described above. In fact, the first factor focused on externally oriented information coming from databases other than those which collect details on charterers and suppliers, while the second factor focuses on information to minimize costs and relates this dimension to operating efficiencies. To complement the analysis, an evaluation needs to take place whether the dimensions of information captured by the two factors explain the choice of MCS (i.e., for each of the 29 MCS, the choice of whether or not to implement it as MCS). The canonical correlation between the MCS (29 dummy variables) and the two dimensions of information (collect externally oriented information and minimize costs) as reflected in the factor scores was calculated. The resulting canonical correlation is 0.687 ( p ¼ 0.000). This result indicates that a linear combination of the two dimensions of information emphasized by management explains 47.2% (squared value of 0.687) of the variance in a linear combination of the choices of MCS.



639

This result reveals that the choice of MCS differs across shipping companies contingent upon their preferences for information. As a final step toward understanding the dimensions of information that constitute the different categories of MCS, an in-detail examination of the association between the two dimensions (external information and cost efficiency) and the implementation of MCS was performed. To achieve this objective, two analyses were conducted: (1) for each MCS identified, an examination of correlations [91] between a dummy indicating whether it was used as MCS and the values of the two factors (as declared by the factor scores) corresponding to the dimensions of information pursued by management was performed; (2) then, for each MCS, a logistic regression was estimated where the dependent variable is the same dummy as in (1) and the independent variables are, again, the values of the two factors. The results of these analyses suggest a determination whether each of the 29 MCS relates to the needs to collect externally oriented information or to the needs to minimize costs or to none of these (Basic MCS). To construct the proposed categorization, the following procedures took place: . A given MSC was assigned to a factor (information purpose)—only if that factor is significantly associated with the implementation of that particular MCS across the two analyses conducted (i.e., correlations and logistic egressions). . MCS, not assigned on the basis of the previous criterion, were classified as Basic MCS [92], if used in more than 60% of the sample firms, since we expect that this category should include MCS commonly adopted by most firms. 7.2.

The interpretation of the value-based categorization of MCS in shipping companies Based on the findings, a categorization of MCS is proposed that includes two sets of systems; Basic MCS implemented by most shipping companies, regardless of the dimension of information emphasized by the company, to establish a basis for their operations and MCS chosen by shipping companies based on their specific information needs. This latter set includes ‘‘External Information MCS’’ and ‘‘Cost MCS’’, which help shipping companies to achieve distinctive purposes. These categories are described in Table 3. The Basic MCS enable shipping companies to establish a basis for their operations. For example, controls on long-term assets owned by the shipping company or assets that the company plans to own in the future (i.e., new vessels or second-hand vessels) are crucial because the greatest assets of shipping companies are their vessels (whose value is usually high). The interviews also confirmed the importance of establishing capital budgeting controls as a means to provide the basic MCS of the business (since the business is capital oriented due to the high acquisition costs of vessels). Subscription in international databases gives the opportunity to shipping companies to learn about trends in the market, freight rates, and prices of the vessels. The next two types of MCS help shipping companies to achieve distinctive purposes. Systems to ‘‘externally orient information’’ are focused on internal risks and are implemented when the firm feels the need to inform cargo owners about the reliability of its services and operations and also about protection of asset integrity

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A.A. Triantafylli and A.A. Ballas Table 3.


Purpose Associated MCS

Purpose

Associated MCS

Purpose Associated MCS

Value-based categorization of MCS.

Basic systems Basic systems implemented to set standards and support basic operations Externally oriented information systems (e.g., subscription to databases such as Lloyd’s lists, fair play, Equasis, etc.) Capital budgeting controls Quality standards’ controls Sales productivity standards Credit rules and controls Off-hire analysis (e.g., off-hire ratios, profit/ship ratios) Information systems’ controls (IS services) Check of bids for repairs Check of bids for spare parts Controls on selection criteria for the purchase of second-hand vessels Control for investment in long-term assets Performance-based compensation systems Externally oriented information Collect information related to: Avoiding internal risks Protecting asset integrity Financial data available to cargo owners Comply with cargo owners’ requirements Budget controls Inventory control systems to optimize stock levels and replenishment Onboard inspections Planned maintenance system (computerized) Controls on employee behavior and development (turnover, training, etc.) Internal audits, transactions’ record, information control Code of business conduct Procedures (specified and recorded) Key performance indicators (KPIs) Statement of purpose/mission/credo New buildings control Reports for the performance of each department Risk assessment procedures Information to minimize cost Collect information related to: Cost minimization Cost controls

and/or establishment of rules of conduct. It is important to state that contrary to other sectors, i.e., retail sector or manufacturing sector, the shipping industry does not incorporate marketing databases or benchmarking with competitors as MCS. This is explained due to the nature of the shipping industry where customers are cargo owners. Freights are a result of supply and demand; however, ‘‘customer’’ satisfaction is important; otherwise shipping companies will be obliged to offer their vessels to cargo owners that pay less or miss important major customers. Since shipping companies are frequently inspected by cargo owners through vetting inspections, or quality controls, etc., they try to implement MCS that allow them to control for the issues that affect their credibility. These systems include onboard inspections where usually superintendent engineers inspect vessels in order to assure compliance with safety rules and regulations, and planned maintenance system [93].


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Finally, firms searching for data to ‘‘minimize costs’’ use cost controls more heavily than the other firms, to achieve higher operating efficiencies. Several of the managers interviewed explained that cost minimization should not be attained at the expense of quality, but on the contrary, it is necessary due to the cyclicality of the business and reassures the viability of the company even when freight rates fall down. Since basic expenses of the shipping companies (i.e., fuels, repairs, dry-dockings, etc.) are not fixed, but are susceptible to market pressures, the control of these costs is of great importance [94]. The different emphases that firms place on their implemented MCS appear to reflect the two key components of the value creation process; i.e., to minimize cost and collect information readily available to cargo owners. Even when shipping companies choose one of the components at the time they implement MCS, most of them acknowledge the importance of eventually integrating the two components.

8. Empirical results: performance implications of the choice of MCS 8.1. The strategy model of MCS Hypothesis 1 examines a specific relationship between the strategy followed by a shipping company and its choice of implementation of MCS. To operationalize the test of this relationship, Hypotheses 1a and b were rephrased in terms of the categories of MCS identified in Section 4: Hypothesis 1a: Shipping companies following low cost strategies will implement MCS to ‘‘Minimize Costs’’ more intensely than shipping companies not following low cost strategies. Hypothesis 1b: Shipping companies following differentiation strategies will implement MCS to ‘‘Externally orient information’’ more intensely than shipping companies not following differentiation strategies. 8.1.1. Univariate analysis. To test H1a in a univariate setting, the sample of companies is split into Low Cost and no Low Cost shipping companies and contrast was made in order to realize how the two groups differ (1) in terms of their emphasis on the information dimensions corresponding to the two categories of MCS; and (2) in terms of their frequency of adoption of the specific MCS assigned to each category. This exercise is repeated for H1b by splitting the sample into shipping companies following differentiation strategies and shipping companies not following differentiation strategies. 8.1.2. Results from univariate analysis. Pearson Correlations among the variables report that Differentiation and Low Cost strategies are negatively correlated consistent with Porter [95]. Shipping companies pursuing Low Cost strategies place more emphasis on Cost MCS (consistent with H1a) and less emphasis on External Information MCS. Shipping companies pursuing Differentiation Strategies put more emphasis on External Information MCS and less emphasis on Cost MCS although this result seems to be not statistically significant. Not surprisingly, subsidiaries tend to follow differentiation strategies and they have a positive correlation with strategy search, perhaps reflecting the fact that subsidiaries are still defining their specific differentiation strategy.

642


The impact regulations have on the adoption and implementation of MCS is positively correlated with decentralized firms and shipping companies pursuing differentiation strategies. Differentiators also tend to adopt vertical diversification as a way to diversify their activities. Moreover, shipping companies adopting External Information MCS tend to be in the process of defining their strategies (positive correlation between External Information MCS and strategy search).

8.1.3. Multivariate analysis. In a multivariate setting, the following choice model has been developed (a binomial logit model [96]), which is the ‘‘Strategy Model of MCS’’:


PrðCHOICEMCSi ¼ MCS categoryÞ ¼ fðLOWCOSTi , DIFFERENTIATIONi , CONTROLVARIABLESi Þ CHOICEMCS is a categorical variable describing the two categories of MCS. This variable is coded 1 and 2, respectively, for firms emphasizing mostly Cost MCS and External Information MCS, respectively. To determine what category of MCS each firm most emphasized, a survey question was used where the respondents were asked to rate the emphasis placed on each of the corresponding information dimensions based on a Likert scale. Specifically, for each firm, ‘‘most emphasized’’ MCS is the one that received the highest Likert value. Firms with ties between the two MCS were excluded from the analysis, resulting in a sample size of 42 observations [97]. The main independent variables in the model consist of the strategy variables, LOWCOST and DIFFERENTIATION. Both variables are constructed as composite measures from a set of survey questions that characterize the strategy of the firms. The LOWCOST measure reports higher values for strategies emphasizing low price, and lower values for firms and customers indifferent to prices. This measure is constructed through principal components analysis and captures 60% of the variation in two questions: (1) please define the extent to which your company follows the above criteria for spare parts acquisition: lowest transportation cost; and (2) how you would you characterize price sensitivity of your characters. The corresponding Cronbach alpha in this case is 0.665. The DIFFERENTIATION measure reports higher values for strategies putting more emphasis on customer’s satisfaction and uniqueness. It is also constructed through principal components and captures 74% of the variation in two questions: (1) ‘‘the extent to which shipping companies consider charterers’ satisfaction’’; and (2) ‘‘the extent to which shipping companies place the relative emphasis on the following attributes to attract and retain charterers: tailor made services.’’ The corresponding Cronbach alpha in this case is 0.905. To ensure consistency between ‘‘intended’’ and ‘‘realized’’ strategy [98], both LOWCOST and DIFFERENTIATION combine questions on the firm’s stated strategy (emphasis on prices and customization) and questions on the strategy ex post (as reflected in charterers’ behavior). Also, two sets of control variables are included in the multivariate analysis, one consisting of a number of organizational variables identified as important



643

determinants of the choice of MCS systems in previous studies, and another one describing the ownership structure of a shipping company. In particular, at an organizational level, the control of DECENTRALIZATION [99] of a shipping company is controlled, the degree of DIVERSIFICATION of its activities and whether the firm is still developing its strategy or not (SEARCHSTRAT). Literature suggests that the more decentralized firms use formal operating control systems more heavily [32, 100]. Thus, we expect that decentralized companies use Cost MCS more intensely to achieve tighter control over units. Accounting theories also predict that higher diversity in company’s activities leads firms to use more sophisticated cost allocation systems [101]. Thus, we expect shipping companies with more diverse assortments to use Cost MCS more intensely. Other studies have indicated that MCS are utilized differently depending on whether they are used for strategy formulation or strategy implementation [37, 102–104]. We hypothesize that firms in the process of developing their strategies will use more intensely Cost MCS and External Information MCS, in an attempt to learn more about the business. Ownership structure is also controlled in the multivariate setting. Previous studies suggest that ownership structure affects the control structure of the firms [105, 106]. Two dummies are introduced in order to indicate the ownership structure of a shipping company—SUBSIDIARY indicates whether a shipping company was a subsidiary or spin-off of another company and STOCKEXCHANGE indicates that a shipping company is listed on a stock exchange market. We expect STOCKEXCHANGE shipping companies to emphasize External Information MCS over Cost MCS as these types of companies are focused on building the brand while relying on the incentives provided by the ownership structure to achieve cost efficiencies. Moreover, they need to attract and retain investors through the stock exchange market. Presumably, SUBSIDIARY firms will use External Information more intensely to protect the parent’s company image. Finally, we control for the effects regulations probably have in the adoption and implementation of MCS in shipping companies. I expect that regulatory demands (those included in ISM Code, STCW, MARPOL Convention, SOLAS Convention, etc., mandatory controls imposed by Stock Exchange Markets for the shipping companies, controls imposed by the national law) are positively associated with Cost MCS and External Information MCS since they are mandatory for all shipping companies. To control for other factors expected to affect the implementation of MCS, in a multivariate setting [107] the ‘‘Strategic Model of MCS’’ is analyzed [108]. Table 4 presents the results of the binomial logit model in two columns (expressed in the form A/B) where the coefficients represent the log-odds of outcome ‘‘A’’ versus outcome ‘‘B’’ [109]: ln

PrðCHOICEMCS ¼ ‘‘A’’Þ PrðCHOICEMCS ¼ ‘‘B’’Þ

For example, column 1 expresses the log-odds that a shipping company chooses COST MCS versus EXTERNALINFO MCS [111]. 8.1.4. Results from multivariate analysis. Because of the small sample size, the strategic determinants of the choice of MCS are first examined (Panel A).

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A.A. Triantafylli and A.A. Ballas Table 4.

Binomial logit: strategic choice of management control systems. COST MCS/EXTERNAL INFO MCS Coefficient


Panel A: Strategic determinants of MCS (N ¼ 42, Pseudo R2 ¼ 0.237) INTERCEPT 4.425 (3.215) LOWCOST 1.652 (0.687)*** DIFFERENTIATION 0.059 (0.506) Panel B: Add organizational controls (N ¼ 42, Pseudo R2 ¼ 0.359) INTERCEPT LOWCOST DIFFERENTIATION DECENTRALIZATION SEARCHSTRAT VERTICALDIVERSIFICATION

3.870 2.325 0.107 1.379 1.805 0.062

(3.905) (0.956)*** (0.596) (1.573) (0.978)* (1.404)

Panel C: Add ownership controls (N ¼ 42, Pseudo R2 ¼ 0.370) INTERCEPT LOWCOST DIFFERENTIATION DECENTRALIZATION SEARCHSTRAT STOCKEXCHANGE SUBSIDIARY REGULATIONS VERTICALDIVERSIFICATION

3,944 2.339 0.027 1.165 1.868 0.795 0.537 0.124 0.097

(4,081) (0.976)*** (0.658) (1.628) (1.074)* (1.426) (1.791) (0.954) (1.423)

Notes: The values in bold represent statistically significant variables. Dependent variable: It was constructed utilizing the categorical variable CHOICEMCS, which indicates what MCS the firm emphasizes: Cost MCS or external Info MCS. Strategy variables: LOWCOST: Composite measure that proxies for the firm’s emphasis on cost leadership, as proxied by the extent to which shipping companies consider charterers’ satisfaction and the extent to which shipping companies place the relative emphasis on tailor-made services as an attribute to attract and retain customers. DIFFERENTIATION: Composite measure describing the emphasis the firm places on a differentiation strategy. It summarizes two questions, one of the extent to which shipping companies consider charterers’ satisfaction, and the other of the extent to which shipping companies place the relative emphasis on tailormade services as an attribute to attract and retain customers. Control variables: DECENTRALIZATION: Composite measure describing the extent of decentralization in the firm. SEARCHSTRAT: Dummy indicating whether the firm defined its strategy after introducing its MCS or not. STOCKEXCHANGE: Dummy indicating whether the shipping company has been listed on a stock exchange market (1) or not (0). SUBSIDIARY: Dummy indicating whether the shipping company is/was a subsidiary or spin-off from a larger company. REGULATIONS: Dummy indicating whether the shipping company has introduced its MCS due to law requirements (1) or not (0). VERTICALDIVERSIFICATION: Dummy indicating the level of heterogeneity of activities in the firm. *p50.10; **p50.05; and ***p50.01.

Then, Panel B adds three organizational characteristics as control variables: extent of decentralization of the shipping company, diversification of activities and whether the firm is in a phase of strategy formation. Panel C adds the ownership variables (whether the firm is a subsidiary of a larger company or not and whether the shipping company is listed on a stock exchange or not) and the importance of regulations in the implementation of MCS, presenting the complete set of hypothesized determinants of



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the choice of MCS. Results show that shipping companies following a Low Cost strategy place more emphasis on Cost MCS than External Information MCS, consistent with H1a. For one unit increase in Low Cost strategy, the log odds of selecting a Cost MCS (vs. selecting External Information MCS) increases by 1.657 in case where only strategic determinants are taken into account, by 2.246 in case organizational controls are added to the model and 2.366 in case ownership controls and regulations are added to the model. Logistic regression reveals that shipping companies pursuing Low Cost strategies and shipping companies that are in the process of defining their strategies (SEARCHSTRAT) are significant predictors of whether to adopt a Cost MCS versus an External Information MCS. This result is consistent with literature, where cost leadership firms use more cost controls MCS [40, 42, 44] Shipping companies that are still in the process of defining their strategies tend to choose Cost MCS, presumably to learn more about their business. The binomial logistic regression does not provide support for H1b, i.e., that differentiators place more emphasis on External Information MCS versus Cost MCS. Actually, for one unit increase in External Information strategy, the log odd of selecting an External Information MCS (vs. selecting Cost MCS) decreases by 0.059 in case where strategic determinants are taken into account and by 0.216 in case organizational controls are taken into account and by 0.077 in case ownership controls are taken into account, but these results seem to be not statistically significant. The multinomial model predicts correctly the choice of MCS in 81% of the cases. As for the other control variables, the relationships are not statistically significant but their direction is generally consistent with the predictions. Panels B and C show that decentralization leads shipping companies to place more emphasis on the use of Cost MCS versus External Information MCS. This result is consistent with a number of studies that have suggested a greater emphasis on the use of tight (less subject to discretion) control systems in decentralized organizations [100, 112]. Shipping companies listed on a stock exchange are positively associated with Cost MCS consistent with the notion that these companies need to keep their costs in a low level in order to report higher profits each year for their investors. Shipping companies that apply vertical diversification to their activities are more likely to adopt External Information MCS in order to provide communication between the diverse activities of the organization. 8.1.5. Summary of results for Hypothesis 1. To summarize, shipping companies following Low Cost strategies put significantly greater emphasis on the use of MCS to Minimize Costs (consistent with Hypothesis 1a) and are more likely to adopt cost controls and credit controls as MCS. A possible explanation for the use of these control systems is that the set of ‘‘Basic Controls’’ already includes important elements that support low cost strategies (i.e., check of bids, operational controls), decreasing the need of the cost leaders to use additional MCS to achieve lower costs. As for the relationship between the pursuit of a Differentiation Strategy and the emphasis on MCS to Externally Orient Information (Hypothesis 1b), it is generally weaker. While the univariate tests indicate that shipping companies have a higher propensity to use Externally Oriented MCS, in the multivariate tests differentiation strategies do not appear to be significantly associated with a more intense use of Externally Oriented MCS. A possible explanation is that shipping companies pursuing differentiation strategies use externally oriented information systems and sales standards as Basic MCS and as a result, the need to implement additional MCS

646



to externally orient information is decreased. Multivariate tests also show that shipping companies in the process of defining their strategy are more likely to adopt Cost MCS over External Information MCS. Overall, the results provide evidence that the choice of MCS is tailored to fulfill management information needs based on the firm’s strategy. As stated by the General Manager of a medium-sized shipping company located in Athens: ‘‘Control systems are crucial to learn about prospects of a new technology, emergent markets, and charterers. Controls should be implemented early in the company in order to understand business. In our office we manage different types of vessels (tankers, bulk carriers, etc.) and so we need to know about the entrepreneurial actions of our competitors, the number of new buildings that come into the market and influence the freight rates, the price of goods in the international markets, etc. This is according to company’s strategic positioning in the market: the quality of our services and the satisfaction of our charterers constitute our primary goal as cargo transporters.’’ 8.2.

The performance implications of the adoption of the ‘‘strategy model of MCS’’ 8.2.1. Univariate analysis. To test the hypothesis that shipping companies with a better fit between their MCS and their strategies experience superior performance, the sample firms are classified in two groups based on whether or not their choice of MCS deviates from the ‘‘optimal’’ choice predicted by the Strategy Model of MCS. For each firm, the type of MCS is identified (i.e., Cost MCS) with the highest probability of being selected according to the Strategy Model of MCS Choice and a dummy variable ‘‘FIT’’ is defined that equals 1 if the shipping company actually chose (i.e., placed more emphasis on) that type of MCS, and 0 otherwise. As a result, firms are classified into two groups: ‘High-Fit’ (FIT ¼ 1) and ‘Low-Fit’ (FIT ¼ 0). For the purpose of the univariate tests, the two groups are compared in terms of two measures of performance: . PERCERPERFORM: This is a categorical variable drawn from a survey question where managers were asked to evaluate the firm’s overall performance since its founding, relative to the shipping industry. The scale of this variable is described as (1) if the firm’ s performance is in the lower 10%; (2) if it is in the lower 25%; (3) if performance is average; (4) if the firm is in the top 25%; and (5) if it is in the top 10%. . USEFULMCS [113]: This is a composite measure based on seven survey questions where managers were asked to assess from 1 to 5 the overall usefulness of their firm’s MCS (with 5 being more useful) [116]. It complements PERCPERFORM in that it provides a more specific and direct assessment of the contribution of MCS to the firm performance. Although self-rating measures have sometimes been criticized for a potential leniency bias, this is less a concern where such bias is generic and where the ratings are needed for relative rather than absolute analysis, as is the case in this study. Measures of perceived performance are multidimensional since respondents are better suited to consider all the various dimensions of performance—e.g., the balance between revenues, growth, and profitability—as well as to assess the extent to which overall performance is satisfactory in terms of the firm’s business plan. Measures of actual performance are, in most cases, unable to capture the tradeoffs between

647

Management control systems and performance Table 5.

Univariate performance tests. Mean for sub-sample

Performance variable PERCPERFORM USEFULMCS

High-fit FIT ¼ 1

Low-fit FIT ¼ 0

Difference in means

t-Test (Pr4t)*

Wilcoxon test (Pr4z)*

3.53 3.41

4.2 2.92

0.66 0.49

0.067 0.107

0.068 0.135


Notes: FIT: Dummy equal to 1 if the firm implemented the MCS predicted as the most probable by the strategy model of MCS choice, and 0 otherwise. PERCPERFORM: This is a categorical variable drawn from a question in the survey, measuring managers’ perception of firm’s performance since founding, in a scale where 1 indicates worst performance and 5 best. USEFULMCS: This is a composite measure drawn from seven questions from the survey where managers were asked to assess from 1 to 5 the overall usefulness of MCS to their firms (with 5 being more useful). *p-Values in the univariate analysis describe two-tailed results.

different dimensions of the business and assume a definition of good performance that may differ from the firm’s definition, given its objective function at that point in time. Pearson correlations indicate that the two measures of performance are negatively correlated (0.63) though the result is not statistically significant. 8.2.2. Results from univariate analysis. The results of the parametric (t-test for differences in means) and non-parametric (Wilcoxon rank-sum) univariate tests given in Table 5 partially support the hypothesis tested. Shipping companies with a better fit to the Strategy Model of MCS Choice appear to perform less well than the other firms (Low-fit), in terms of perceived performance, whereas the contrary takes place in terms of perceived usefulness of MCS. For the variable PERCEPERFORM, the difference in mean performance across the two sub-samples is statistically significant at the 5% level. This result, though it seems surprising, is explained by the fact that the two measures of performance are negatively correlated. 8.2.3. Multivariate analysis. To perform the multivariate test, an Ordinal Logit Model [117], was run where the dependent variable is the one measure of perceived performance (PECPERFORM) and an Ordinary Least Squares (OLS) Regression [118] where the dependent variable is the other measure of perceived performance, USEFULMCS. In these regressions, the independent variables include a measure of whether the firm chose the type of MCS predicted by the Strategy Model of MCS Choice (dummy variable FIT) and a number of control variables: PERFORMANCEi ¼ fðFITi , CONTROLVARIABLESi Þ These variables are correlated both with the introduction of MCS and the performance of a shipping company and include CEO experience [119], Size, and Age. Previous accounting and entrepreneurship literature suggests that the presence of a CEO or top manager with previous experience introducing and implementing MCS in a shipping company will increase the chances of implementing effectively MCS and, thus, enhance performance [120]. Size and age were also associated to performance as well as to the emergence of MCS in companies. Older firms are more

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likely to achieve higher performance than younger firms [121–123]. On the other hand, USEFULMCS might be negatively correlated with age given that technologies have become more available and less expensive in the recent years, increasing the potential benefit younger firms can derive from MCS. Smaller firms were referred to as experiencing lower operating performance than larger firms [124], because smallsize companies tend to be riskier and larger firms improve performance through economies of scale. A more intensive use of MCS was reported for larger and older firms [31, 32, 100, 125], possibly an indication of a more effective implementation of MCS [126]. 8.2.4. Results from multivariate analysis. Multivariate results in Table 6 fail to reject the hypothesis tested. This means that data show a significant positive relation between FIT [127] and PERCPERFORM, and also they indicate a positive relationship between FIT and USEFULMCS. As for the control variables, EXPERIENCE and SIZE (though they seem to be not statistically significant) are both positive associated with PERCPERFORM. EXPERIENCE is negatively associated with USEFULMCS, meaning probably that usefulness of implementation of MCS exists independently of managers’ experiences. AGE is positively associated with PERCPERFORM but negatively associated with USEFULMCS. The latter finding suggests that on average, mature companies rely more on systems other than Table 6.

Multivariate performance tests.

Panel A: Ordinal regression results PrðPerformance ¼ mÞ ¼ fðFITi , EXPERIENCEi , SIZEi , AGEi Þ PERFORMANCE MEASURE PERCPERFORM FIT EXPERIENCE SIZE AGE 1 2 3 4 Pseudo R2 (n) Prob42: Likelihood ratio test of proportionality of odds across response categories (test of parallel lines)

0.855 0.197 0.064 0.028 1.890 0.689 1.101 3.610 0.322 0.000

(0.839)* (0.725) (0.032)** (0.023) (1.227) (0.936) (0.856) (1.094)*** (42) [131]

Notes: The values given within parentheses represent standard errors. PERCPERFORM: This is a categorical variable drawn from a survey question, measuring managers’ perception of firm’s performance since founding, in a scale where 1 indicates bottom performance and 5 top. FIT: Dummy equal to 1 if the firm implemented the MCS predicted as the most probable by the strategy model of MCS choice, and 0 otherwise. EXPERIENCE: Dummy indicating if CEO or whoever was responsible for the implementation of MCS had experience in introducing and implementing MCS in shipping companies (1) or not (0). SIZE: Equals the number of vessels owned by the company. AGE: It is the number of years since the date of founding. j: Cutoff point ‘‘j’’ predicted for the ordinal logit. *p50.10; **p50.05; and ***p50.01.


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formal MCS in order to ensure viability (such as informal MCS, interpersonal relations, everyday routine, etc.) [128]. For the measure USEFULMCS, an OLS Regression was performed, where the dependent variable was USEFULMCS and the independent variables included FIT, EXPERIENCE, SIZE, and AGE. The results indicate that FIT, and SIZE presented a positive association with USEFULMCS, whereas the contrary took place in the case of the rest of the independent variables. Results are statistically significant for the relationship between FIT and USEFULMCS at p50.10 [129]. 8.2.5. Summary of results for Hypothesis 2. The performance results reinforce the notion that shipping companies should adapt their MCS to their strategies. The CEO of a large shipping company located in Athens argued: ‘‘When my father decided to retire, I took over the company—one of the most successful in the shipping industry those years. The greatest challenge for me was to maintain the success of the business while at the same time improving the quality of its services. The first step was to redefine the strategic mission of the company; that led me to the decision to split the main company into two companies—the one comprising of the bulk carrier vessels and the other one of the tanker vessels—since we believe that these categories of vessels operate in different markets that have different needs, different trends, and different regulatory frameworks. Moreover, we decided to have an average fleet age of about 5 years old and always train the personnel to new technologies and regulations in order the firm to keep up with latest market trends. I am very proud to admit that we were recently received an award for the safety of our procedures and the pollution prevention measures we employed. Although these procedures are costly for the company, they helped us establish our good name in the market and moreover we still succeed to obtain higher freights for our services since they guarantee reliability and safety of procedures.’’ In conclusion, the evidence suggests that a good fit between the emphasis on MCS and the strategy and organizational structure of the firm is instrumental to reap the benefits that control systems can provide to the performance of a shipping company. There is no single set of successful MCS that will equally fulfil all the needs of shipping companies and thus, choosing the appropriate set of MCS can have a significant effect on firm performance. As the CFO of a well performing shipping company stated: ‘‘The success of our company does not rely exclusively on the MCS we use, but mainly is relies on the alignment of these systems with our strategy and value structure. Our operational and informational system is the base of our control systems, however I am pretty sure that even if we offered our MCS systems for free to our competitors, they would not have done them any good because they do not have the kind of commitment to the business as we do.’’

9. Conclusions, limitations, and directions for future research This paper provides insights about the choices made by shipping companies when deciding what type of MCS to implement and the consequences of such choices on organizational performance. Shipping companies tend to introduce and implement three categories of MCS based on the informational purposes pursued: ‘‘Basic MCS,’’ which are similar across all companies and they are used to collect information for planning and establishing basic operations; ‘‘Cost MCS,’’ which are


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implemented to minimize costs and ‘‘External Information MCS’’ which are used to collect information related to compliance with cargo owners’ requirements. Findings give the result that the choice among the categories of MCS depends on the shipping company’s strategy and structure, and that firms that choose MCS better suited to their strategies perform better than the other firms. However, findings should be interpreted with caution. First, the focus on a single shipping sector such as the ocean-going merchant marine sector rather than multiple shipping sectors may limit the generalizability of the results to other shipping companies, mainly due to the particular nature of the merchant marine shipping sector. In this respect, this study calls for more studies on the emergence of MCS in other shipping sectors such as the cruisers where different laws and regulations apply. That would be interesting to investigate the differences in the adoption and implementation of MCS due to differences in the environment and legal obligations of each sector. Second, ideally the research should have employed ‘‘real-time’’ data rather than relying on the recollections of survey respondents and should have employed triangulation (i.e., more than one respondent per firm) to minimize memory and interpretation biases. But such a study would have been particularly costly and time consuming. Finally, the study also presents potential survival and self-selection biases. In order to eliminate these biases, we tried to include firms older than 2 years and increase efforts to maximize the rate of response. Extensions of this study include more in-depth research (for instance case-study research). In-depth research can help understanding the complex interactions between MCS and strategy. This becomes even more important if we recognize that strategy is an evolving and multifaceted concept. Case-study research could evolve through the longitudinal study of one or more shipping companies in order to understand the reasoning behind the choice of certain control mechanisms and how these mechanisms change through time due to changes in the strategy and environment faced by the company. Also, many research opportunities and unresolved questions remain. It is not yet clear what role MCS play to bring intended strategies to realization, or whether MCS can minimize the disruption caused by strategic change. Research could be undertaken to explore whether the role of MCS changes as shipping companies mature. Moreover, that would be interesting to introduce more variables in our model (i.e., technology, external, and internal environment, etc.)—since strategy is not the only determinant of control systems—and test the interactions between the variables and their influence on control mechanisms of shipping companies. Notwithstanding the limitations, the results presented in this paper try to contribute to an emerging literature in accounting and control in the shipping industry by establishing the importance of contingencies in the choice of different types of MCS in shipping companies and by providing evidence on the performance implications of this choice.

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92.

93. 94.

95. 96.

97.

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dependence between two quantities is the Pearson product-moment correlation coefficient, or ‘‘Pearson’s correlation.’’ It is obtained by dividing the covariance of the two variables by the product of their SD. The Pearson correlation is þ1 in the case of a perfect positive (increasing) linear relationship, 1 in the case of a perfect decreasing (negative) linear relationship, and some value between 1 and 1 in all other cases, indicating the degree of linear dependence between the variables. As it approaches zero, there is less of a relationship. The closer the coefficient is to either 1 or 1, the stronger the correlation between the variables. If the variables are independent, Pearson’s correlation coefficient is 0, but the converse is not true because the correlation coefficient detects only linear dependencies between two variables. Note, that, as a result of our categorization criteria, 3 of the 29 MCS were not assigned to any of the three types of MCS. This should not be viewed as a limitation of the analysis, since our objective was not to categorize any MCS implemented by managers of the shipping companies, but to provide a general, intuitive framework that would capture the types of MCS most often introduced by shipping companies with different information needs. With respect to the three unassigned MCS, no convincing evidence was found of a systematic relation between their introduction among the set of MCS and the firm’s informational needs. For example, marketing databases, suppliers databases, and benchmarking of the competitors was not classified as basic MCS because shipping companies explained that since the freight rates are a result of demand for vessels by charterers and supply of vessels by shipowners and of the international freight market, it is of little interest the implementation of such MCS in a shipping company. Thus, we conclude that the nature of implementation of these two MCS was not consistent with the notion of Basic MCS that was pursuing in the survey—i.e., MCS commonly adopted because they are essential to the development of a shipping company. Certainly, the categorization criteria are partly subjective and the resulting classification should be viewed as tentative. Planned Maintenance System (PMS) is an electronic system, usually on line with the vessels, which monitors the requisitions for spare parts etc. from vessels. The robustness test of the results that link each dimension with specific implemented MCS was verified by analyzing the sub-sample of firms owning only bulk carriers. The list of MCS assigned to each category remains unchanged except that Budget controls and Capital Budgeting controls appear to be Basic MCS. PORTER, M. E., 1985, The value chain and competitive advantage. Competitive Advantage: Creating and Sustaining Superior Performance (New York: Free Press), pp. 33–61. Logistic Regression is a form of regression that allows the prediction of discrete variables (only) by a mix of continuous and/or categorical or discrete predictors. A binomial logit model is useful for situations in which you want to be able to predict the presence or absence of a characteristic or outcome based on values of a set of predictor variables. It is similar to a linear regression model but it is suited to models where the dependent variable is dichotomous. In this case, the dependent variable is dichotomous (MCS are described as a categorical variable, CHOICEMCS that describes two categories of MCS, Cost MCS, and External Information MCS). ‘‘A binomial logit model is useful for situations where one wants to be able to predict the presence or absence of a characteristic or outcome on the basis of the values of a set of predictor variables. It is similar to a linear regression model but it is suited to models where the dependent variable is dichotomous. In this case, it is appropriate because the dependent variable (CHOICEMCS) is dichotomous taking the value 0 (or, 1) for Cost MCS and 1 for External Information MCS’’. While the categories of MCS are not mutually exclusive (shipping companies may emphasize all of them to some extent), turning relative emphases into ‘‘choices’’ allows to control for biases in terms or ratings clustering (differential respondent’s propensity for rating levels, e.g., someone giving all 5’s vs. someone giving all 1’s) and in terms of ratings dispersion (differential respondents’ propensity for ratings variation, e.g., someone answering in a range 1–7 s vs. someone answering in a range 3–4 s). Moreover, to the extent that a higher emphasis on one set of MCS reflects a greater use of the firm’s limited resources (financial, human, etc.), emphases can be viewed also as ‘‘choices’’.


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98. Mintzberg [82] draws a crucial distinction between intended strategy and realized strategy. Realized strategies emerge through events and environmental interactions as they unfold over time. Thus, intended strategies may not be realized because they are based on erroneous or incomplete information, environmental circumstances may change or they may simply not be enacted [38]. Similarly, realized strategies may emerge unintentionally. 99. DECENTRALIZATION is a composite measure developed through principal components describing the extent of decentralization of the firm. It explains approximately 64% of the variation found in four questions in the survey that ask about the extent to which shipping company’s personnel has authority to make decisions about: (1) long-lived assets; (2) invoices for dry docking; (3) sales and purchases; and (4) voyage fixture confirmation. Higher values indicate higher levels of decentralization (decision making by managers rather than senior management. The corresponding Cronbach alpha is 0.664. In order to associate higher values to decentralization, the scale of question was flipped by calculating 6 minus the number indicated by the respondent. 100. BRUNS, W. J., Jr. and WATERHOUSE, J. H., 1975, Budgetary control and organizational structure. Journal of Accounting Research, 13, 177–203. 101. BANKER, R. D., POTTER, G. and SCHROEDER, R. G., 1995, An empirical analysis of manufacturing overhead cost drivers. Journal of Accounting and Economics, 19, 115–137. 102. SIMONS, R., 1990, The role of management control systems in creating competitive advantage: New perspectives. Accounting, Organizations and Society, 14, 127–143. 103. ITTNER, C. D. and LARCKER, D. F., 2001, Assessing empirical research in managerial accounting: A value-based management perspective. Journal of Accounting and Economics, 32, 349–410. 104. MARGINSON, D. E., 2002, Management control systems and their effects on strategy formation at middle management level: Evidence from a UK organization. Strategic Management Journal, 23, 1019–1031. 105. PFEFFER, J. and SALANICK, G., 1978, The External Control of Organizations: A Resource Dependence Perspective (New York: Stanford Business Classics). 106. BAKER, G., GIBBONS, R. and MURPHY, K., 2002, Relational contracts and the theory of the firm. Quarterly Journal of Economics, 117, 39–84. 107. To complement the analysis in the multinomial model and test the robustness of its results, we also conducted two binomial logistic regressions, where the dependent variable reflects the relative emphasis on each of the two MCS (Low Cost or External Information). For the independent variables, we interacted each of the strategy variables (LOWCOST and DIFFERENTIATION) with the variable 1-SEARCHSTRAT and thus we redefined LOWCOST as LOWCOSTrobust ¼ LOWCOST (1-SEARCHSTRAT) and DIFFERENTIATION as DIFFERENTIATIONrobust ¼ DIFFERENTIATION (1-SEARCHSTRAT). This means that strategy variables are set to zero in the cases when SEARCHSTRAT ¼ 1 (30% of the observations). If the shipping company has optimally chosen its MCS based on its strategy, but the strategy is not the ‘‘right’’ one, this would lead to a negative relation between strategy measures and MCS and by interacting strategy measures with 1-SEARCHSTRAT biasing against finding the hypothesized relationship is prevented. The results are generally consistent with the findings in the multinomial model. 108. Pearson correlations among variables report that Differentiation and Low Cost strategies are negatively correlated consistently with Porter [95]. Shipping companies pursuing Low Cost strategies place more emphasis on Cost MCS (consistent with H1a) and less emphasis on external information MCS. Shipping companies pursuing Differentiation Strategies put more emphasis on External Information MCS and less emphasis on Cost MCS although this result seems to be not statistically significant. Not surprisingly, subsidiaries tend to follow differentation strategies and they have a positive correlation with strategy search, perhaps reflecting the fact that subsidiaries are still defining their specific differentiation strategy. The impact regulations have on the adoption and implementation of MCS is positively correlated with decentralized firms and shipping companies pursuing differentiation strategies. Differentiators also tend to


109. 110. 111. 112.


113.

114. 115. 116.

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adopt vertical diversification as a way to diversify their activities. Moreover, shipping companies adopting External Information MCS tend to be in the process of defining their strategy (positive correlation between External Information MCS and strategy search). In each column, the constraint is imposed that the coefficients related to outcome ‘‘B’’ be zero, given that the binomial model is not identified without imposing this criterion [110, p. 153]. LONG, J. S., 1997, Regression Models for Categorical and Limited Dependent Variables (Thousand Oaks, California: Sage Publications). In panel A, results indicate that for a unit change in the ‘‘differentiation strategy’’ measure, the log-odd ratio of COST MCS versus EXTERNALINFO MCS is expected to increase 106 times [where 1.06 ¼ exp 0.059]. CHILD, J., 1972, Organization structure and strategies of control: A replication of the Aston study. Administrative Science Quarterly, 17, 163–177. When using multiple measure items for a construct, it is important to analyze the validity of the measures. This study examines validity in several different manners and is concerned with both content validity and construct validity. Content validity can be assessed by (1) the ‘‘plan and procedures of construction’’; (2) appearance or face validity; and (3) a measure of internal consistency through an empirical measure of reliability [114]. Construct validity can be assessed by (1) specifying an appropriate domain of observables underlying the construct; (2) using factor analysis to find relationships among the observables; and (3) using correlation analysis to find relationships among the constructs [114]. To satisfy these requirements several steps were taken. First, the existing literature was thoroughly reviewed to establish appropriate domains. Second, the variables tested use previously validated questions from [50]. Third, multiple site visits with shipping companies were conducted with the purpose of gaining more knowledge about the domain being studied. Fourth, the construction of the survey question follows the guidelines set forth by Dillman [115]. Fifth, pretest respondents reviewed the questions for face validity. Sixth, empirical tests suggested by Nunnally [114] for both content and construct validity were conducted on the survey responses. The empirical tests for content validity include (1) reviewing the range of responses; and (2) calculating Cronbach’s alpha which is a statistical measure of internal reliability, and for construct validity include (1) factor and (2) correlation analysis. For the variable LOWCOST the Cronbach’s Alpha is equal to 0.905, whereas for the variable DIFFERENTIATIATION is equal to 0.765 and for the variable DECENTRALIZATION equals 0.864. For the variable USEFULMCS, the Cronbach’s alpha equals 0.855 indicating an acceptable level of internal validity. Factor analyses for this measure reveals that the measure USEFULMCS is unidimensional (since only one factor has eigenvalues41) with explained variance of 67%. All variables are statistically positively associated. For the variable LOWCOST the Cronbach’s Alpha is equal to 0.905, whereas for the variable DIFFERENTIATIATION is equal to 0.765 and for the variable DECENTRALIZATION equals 0.864. NUNNALLY, J. C. and BERNSTEIN, I. H., 1994, Psychometric Theory, 3rd ed. (New York, NY: McGraw Hill). DILLMAN, D. A., 1978, Mail and Telephone Surveys: The Total Design Method (New York: John Wiley and Sons). The questions that comprise the composite measure USEFULMCS are the following: 1. Control systems facilitated my company’s growth. 2. Control reports have provided timely information for managers to respond to new threats and opportunities. 3. Control systems have protected my company from loss or excessive risk. 4. Control systems have reduced flexibility (RC). 5. Control systems provide information that is NOT useful to management (RC). 6. Control systems monitor virtually all tasks in the organization. 7. There is frequent reporting control information to senior managers. In the survey, question 1 indicates most useful and 5 least useful. For questions that are

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117.

118.


119.

120. 121. 122. 123. 124. 125. 126. 127. 128.

129.

A.A. Triantafylli and A.A. Ballas reverse coded (RC) in order to flip the scale, we calculated them as 6 minus the rating given in answering the question. Linear Regression Models (LRM) with ordinal outcomes—such as Likert ratings—can provide misleading results, since LRM assume that the intervals between adjacent categories are equal. Long [110] suggests the use of models specifically designed for ordinal variables such as the Ordinal Logit Model. Using OLS assumes that the intervals between Likert ratings are equal, i.e., that the difference between the Likert ratings of 1 and 2 is the same as the difference between Likert ratings of 2 and 3. This assumption is clearly violated in the case of PERCPERFORM, where each rating (1, 2, 3, etc.) was associated to a precise economic definition (bottom 10%performance, bottom 25% performance, medium performance, etc.) However, it is a more reasonable assumption for USEFULMCS, where respondents were simply asked to choose between five numbers placed between two opposite ends (strongly agree to strongly disagree). EXPERIENCE: Dummy indicating whether the CEO (or whoever was in charge of introducing and/or implementing MCS) had previous experience in introducing and/or implementing controls in shipping companies. AGE: Number of years since the date of founding. SIZE: Number of vessels owned by the shipping company. BRUDERL, J., PSEIDENDORFER, P. and ZIEGLER, R., 1992, Survival chances of newly founded business organizations. American Sociological Review, 57, 227–242. FREEMAN, J., CARROLL, G. R. and HANNAH, M. T., 1983, The liability of newness: Age dependence in organizational death rates. American Sociological Review, 48, 692–710. SINGH, J. V., TUCKER, D. J. and HOUSE, R. J., 1986, Organizational legitimacy and liability of newness. Administrative Science Quarterly, 31, 171–193. HANNAN, M. T. and FREEMAN, J., 1989, Organizational Ecology (Cambridge, MA: Harvard University Press). FAMA, E. and FRENCH, K., 1995, Size and book to market factors in earnings and returns. Journal of Finance, 50, 131–155. DAVILA, T., 2003, The Emergence of Management Control Systems: Formalizing Human Resource Management in Small Growing Firms (Stanford: Stanford University). Since the measure of size is based on current data, a positive association with performance can partly reflect a survivorship bias [127] or a mechanical relationship (top performers presumably have grown bigger). BROWN, S. J., GOETZMANN, W. N., IBBOTSON, R. G. and ROSS, S. A., 1997, Rejointer: The J-shape of performance persistence given survivorship bias. The Review of Economics and Statistics, 79, 167–170. Note that if the shipping company has optimally chosen its MCS based on its strategy, but the strategy is not the ‘‘right’’ one, this would lead to a negative relation between the FIT measure and performance, thereby biasing against finding the hypothesized positive relation. To assess this problem, we interact a dummy that proxies for ‘‘right’’ strategy with the variable FIT. This dummy RIGHTSTRAT equals 0 if the firm changed its strategy—an indication of ‘‘wrong’’ strategy in the past, and 1 otherwise. Results remain the same for all variables. Note that the performance effect presented in the analysis cannot be exclusively attributed to the fit between the MCS and the strategy. This is captured by the multinomial model which includes other organizational variables separate from strategy. Two additional analyses were conducted to better understand whether the fit between MCS and strategy plays an important role on performance: Results of Table 6, were replicated for the sub-sample of firms with a low cost score above median, given that low cost strategy was the only strategy variable that was a significant predictor in the multinomial model Results in Table 6, were replicated using a re-defined FIT variable, where the multinomial model is substituted for the one that includes only the strategy variables as exploratory variables. The FIT variable is positively associated with the perceived performance and usefulness of MCS in both tests.

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Management control systems and performance 130. Others include: Position of respondents


Claims and insurance managers Crew managers Chartering managers Freight collection managers Supply managers Marine managers New buildings manager Vetting officers Total

Number of respondents

Percentage of respondents

2 3 1 2 2 2 2 2 16

2 3 1 2 2 2 2 2 16

131. The proportional odds assumption implicit in the ordinal logit model is rejected at the 1% level. To verify the robustness of the PERCPERFORM results, we additionally run an OLS regression and find similar results (the FIT variable remains positively related to PERCPERFORM).

Appendix Abbreviated research questions Informational purposes of MCS. Please indicate how the main focus and use of control systems have developed inside your company (1 ¼ to a small extent, 5 ¼ to a great extent) 1. To achieve tight control and monitoring over procedures, rules and/or standards. 2. To achieve learning and flexibility to act upon information (e.g., gather information for decision making). 3. To minimize risks. 4. To increase revenue. 5. To minimize costs and achieve operation efficiencies. 6. Internally oriented information (e.g., financial results, employee development, standards and rules, input–output measures). 7. Externally oriented information (e.g., customer satisfaction, competition, economic events, etc.). 8. Financial performance measures (e.g., cash controls, financial ratios, etc.). 9. Non-financial performance measures (e.g., customer satisfaction, employee turnover, market share, etc.).

Low cost strategy. Please indicate the extent to which your company has pursued the following strategies to achieve growth (1 ¼ to a small extent, 5 ¼ to a great extent) 1. 2. 3. 4. 5.

Criteria for spare parts acquisition: lowest possible price. Criteria for spare parts acquisition: lowest transportation cost. Flag of convenience. Emphasis on charterers’ price sensitivity. Lower prices to attract and retain charterers.

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Differentiation strategy. Please indicate the extent to which your company has pursued the following strategies to achieve growth (1 ¼ to a small extent, 5 ¼ to a great extent)


1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

Compliance with the latest international shipping rules and regulations. Implementation of innovative technology on vessels. Charterers’ satisfaction. Charterers’ satisfaction. Criteria for spare parts acquisition: originality. Criteria for spare parts acquisition: prompt delivery. The officers’ training. The ratings’ well trained. Quality of services. Tailor-made services.

Decentralization. Please indicate the extent to which shipping company’s personnel have authority to make decisions about (1 ¼ employees, 2 ¼ department’s director, 3 ¼ department’s manager, 4 ¼ more than one managers, 5 ¼ senior management only): 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

Hiring and firing of personnel. Chartering policy. Selecting long-lived assets investments. Signing invoices for dry dockings/repairs. Signing invoices for spare parts. Selecting flags/classification societies. Selecting suppliers. Sales and purchases of vessels. Participating in budgeting preparation. Voyage fixture confirmation.

Usefulness of MCS. To what extent do you agree with the following statements? (RC ¼ reverse coded; 1 ¼ to a small extent, 5 ¼ to a great extent) 1. Control systems facilitated my company’s growth. 2. Control reports have provided timely information for managers to respond to new threats and opportunities. 3. Control systems have protected my company from loss or excessive risk. 4. Control systems have reduced flexibility (RC). 5. Control systems provide information that is NOT useful to management (RC). 6. Control systems monitor virtually all tasks in the organization. 7. There is frequent reporting control information to senior managers. Perceived performance. How would you categorize your firm’s performance since founding (revenue growth and profitability) with respect to the shipping industry? (A) (B) (C) (D) (E)

Top 10% Top 25% Average In the lower 25% In the lower 10%