Three Controls are Better than One: A Computational … · Three Controls are Better than One: ......

Computational & Mathematical Organization Theory, 8, 197–220, 2002c© 2002 Kluwer Academic Publishers. Manufactured in The Netherlands

Three Controls are Better than One: A ComputationalModel of Complex Control Systems

CHRIS P. LONGOlin School of Business, Washington University, Campus Box 1133, One Brookings Drive, St. Louis,MO 63130, USAemail: [email protected]

RICHARD M. BURTONFuqua School of Business, Duke University, Durham, NC 27708, USAemail: [email protected]

LAURA B. CARDINALKenan-Flagler School of Business, McColl Building, CB #3490, The University of North Carolina at Chapel Hill,Chapel Hill, NC 27599-3490, USAemail: laura [email protected]

Abstract

This paper investigates theories that integrate and extend currently accepted agency- and transaction-based ap-proaches to organizational control. We use a computational model to build three forms of control systems (market,bureaucratic, clan) and three forms of control targets (input, behavior, output). Using these models, we examinerelationships between control systems and both singular and multiple control targets. Results of this study supportthe emerging “broader” perspective on organizational control research and suggest that managers can improveorganizational performance by focusing attention on multiple control targets. In addition, findings partially sup-port posited relationships between control systems and singular control targets. The authors suggest that resultsof this study should direct scholars to refocus control research from examinations of singular forms of control toevaluations of more complex control systems.

Keywords: organizational control, organizational design, process management

1. Introduction

This paper expands the scope of control research by investigating the efficacy of focusing onspecific control targets within organizational control systems. We present several hypothesesthat integrate and extend current agency- and transaction-based theories of organizationalcontrol. Results of this study permit us to simultaneously refine accepted control theorywhile providing support for a newly emerging “broader” perspective on organizationalcontrol that describes how managers can improve organizational performance by leveragingdiverse elements of their control systems (Cardinal, 2001; Long, 2002).

We use a computational model to test several hypotheses. In the first section, we ex-amine current control theories and outline our hypotheses. We then briefly describe thecomputational model and study. Lastly, we present and discuss our results.

198 LONG, BURTON AND CARDINAL

2. Background

2.1. Control Research

Organizational control can be defined as any mechanism that managers use to direct at-tention, motivate, and encourage organizational members to act in desired ways to meet anorganization’s objectives (Ouchi, 1977, 1979; Eisenhardt, 1985; Snell, 1992). The funda-mental unit of analysis in control research is the control mechanism, the specific method bywhich individual actions are governed. Control mechanisms are generally distinguishedby the organizational referent (e.g., process, resources) they are designed to influence(Merchant, 1985; Kirsch, 1996; Cardinal, 2001; Cardinal et al., 2002b) and the level offormality that managers utilize in their application. Formal control mechanisms refer toofficially sanctioned (and usually codified) institutional mechanisms such as written rulesand procedural directives. Informal control mechanisms refer to values, norms, and beliefsthat guide employee actions and behaviors.

Researchers have utilized their understanding of organizational control to examine tworelated concepts: control targets (Ouchi, 1977, 1979; Eisenhardt, 1985; Kirsch, 1996), andcontrol systems (Ouchi, 1979, 1980; Jaworski et al., 1993; Roth et al., 1994). Below, weoutline the basic elements of control targets and control systems.

2.2. Control Systems

Control systems describe the formal and informal information-based structures and routinesthat managers “use to maintain or alter patterns in organizational activities (Simons, 1995,p. 5).” The control system describes an organization-level concept that is distinct from itsstructure (Ouchi, 1977) but serves as an integral component of an organization’s overalldesign. Specifically, an organization’s control system is comprised of various organizationdesign elements that affect managers’ abilities to direct subordinates in their tasks (Daft,1998). For example, an organization’s control system is comprised of components of anorganization’s structure, culture, incentive systems and retention mechanisms (Lewin andStephens, 1994).1

Organizations construct and manage their control systems in order to direct the behaviorand performance of individual managers and sub-units towards the production of actionsdesirable to the collective. Control systems are thus designed so that an organization’ssub-units act in a coordinated and cooperative fashion that enable resources to be ob-tained and allocated in ways that achieve an organization’s goals (Lebas and Weigenstein,1986).

Researchers have identified three types of control systems: market, bureaucratic, andclan (Ouchi, 1979, 1980) and have classified them according to their use of formal andinformal control mechanisms (Roth et al., 1994). Managers within market control systemsrely less on formal and informal organizational controls and more on performance-basedcontracts to ensure that the work of employees aligns with organizational goals. Managerswithin bureaucratic control systems apply primarily formal control mechanisms such asrules and regulations through task specialization and hierarchies. Managers within clan

THREE CONTROLS ARE BETTER THAN ONE 199

control systems direct workers using informal control mechanisms such as common values,traditions, and beliefs.

2.3. Control Targets

A control target is the portion of an organization’s production process to which individ-ual control mechanisms are applied (Merchant, 1985; Cardinal et al., 2002a; Long, 2002).Control target research has focused primarily on examining how managers apply controlmechanisms to three control targets; input targets, process targets, and output targets. Or-ganizations select input targets (“input control”) to prepare material and human productionresources. Organizations choose process targets (“process control” or “behavior control”)to ensure that individuals perform tasks in an appropriate manner. Finally, organizationsfocus on output targets (“output control”) to align the quality and quantity of outputs withpreset standards.

Using agency theory principles (Jensen and Meckling, 1976; Fama, 1980; Eisenhardt,1989), control target research has primarily focused on determining the single best controltarget around which managers develop employment contracts (Eisenhardt, 1989; Donaldson,1990; Ghoshal and Moran, 1996). Findings of this research suggest that to resolve goalconflicts with self-interested subordinates, managers should align their control target fo-cus according to the attributes of production tasks, their knowledge of cause-effect rela-tions regarding managed tasks, and the measurability of production outputs (Ouchi, 1977;Merchant, 1985; Snell, 1992; Kirsch, 1996).

2.4. Integrating Control Systems and Control Targets

Theories on controlsystems(Williamson,1975;Ouchi,1980) and control targets(Eisenhardt,1989) each describe methods by which managers can direct boundedly rational, self-interested workers. Research on these topics, however, have independently examined theeffects of organizational control systems and control targets on organizational performance.Control researchers have, for example, separately compared the performance achieved byvarious control systems (Snodgrass and Szewick, 1990) and effectiveness of managers whofocus on individual control targets under various conditions (Snell, 1992; Kirsch, 1996).

While they outline complementary concepts, little theoretical and empirical work hasexamined how managers operating within types of control systems target the specific controlmechanisms they apply. As a result, we know relatively little about how managers withinspecific types of control systems focus their applications of individual and groups of controlmechanisms.

Computational research, which could inform our understanding of these relationshipshas primarily examined and compared the performance effects produced by various orga-nization design components and has not specifically focused on issues regarding controlsystems and control targets. For example, Burton and Obel (1980), Carley (1992), Mihavicsand Ouksel (1996), and Ouksel and Vyhmeister (2000) have examined the impact of organi-zational structures on organizational learning and performance. Carroll and Burton (2000)evaluated the effects of various communication structures on intra-organizational informa-tion exchange and performance. Phelan and Lin (2001) observed the performance effects


produced by several, common organizational promotion systems. In addition, Harrison andCarroll (1991) examined the development of organizational cultures within several types oforganizational forms.

To develop a better understanding about how managers within control systems targettheir control efforts, we need to directly evaluate these relationships. Below we describe twogeneral but distinct theories regarding how effective managers apply control mechanismswithin various control systems. Thereafter, we outline a virtual experiment we will use toexamine the efficacy of these control system/control target combinations.

2.5. Single Control Targets

One approach to understanding how managers target the controls they apply suggests thatmanagers operating within specific control systems tend to focus control mechanisms to-wards single control targets. Because managers display an interest in economizing effort(March and Simon, 1958; Eisenhardt, 1989), they leverage structural similarities betweenparticular control systems and control targets to focus control mechanisms on specific por-tions of an organization’s production process. This approach is outlined in Proposition 1.

Proposition 1. Within specific control systems, managers achieve the highest levels oforganizational performance by focusing on single control targets.

Proposition 1 posits three relationships that are outlined in Hypotheses 1 through 3.below.

Managers within market control systems tend to focus on output control targets because,in this environment, it is more efficient for managers to evaluate work after it is completedthan it is to monitor work as it is performed (Barney and Ouchi, 1986). Ouchi (1979) explainsthe relationship between market control systems and output control targets by arguing thatthe former arises directly out of managers’ capacities to measure the outcomes of actors’efforts. Lebas and Weigenstein (1986) concur and suggest that “the most important controlsystem components for a market approach include transfer pricing, lateral relationships andbargaining, and management compensation (p. 263)” all mechanisms that managers useto focus on output control targets. This relationship between market control systems andoutput control targets leads to Hypothesis 1.

Hypothesis 1. Managers within market control systems achieve the highest levels oforganizational performance by focusing primarily on output control targets.

In contrast, bureaucratic control systems that contain many of the classic bureaucratictraits described by Weber (1946), are specifically suited to situations where managers canmore readily determine the value of individual contributions to organizational tasks (Ouchi,1980). As a result, managers within bureaucratic control systems minimize risk and focuson process control targets to prescribe and closely monitor how tasks are performed. Here,managers use rules and regulations, hierarchies, and formal (codified) communications todirect the activities of organizational actors. This relationship between bureaucratic controlsystems and process control targets is outlined in Hypothesis 2.


Hypothesis 2. Managers within bureaucratic control systems achieve the highestlevels of organizational performance by focusing primarily on process control targets.

According to Ouchi (1977, 1979) and others (e.g., Snell, 1992), clan control is most ef-fective when task programmability is low and the contributions of individual employees arenot clearly measurable. Theorists suggest that, as a result, managers in clan control systemstend to compensate for their inability to program tasks and monitor subordinates by apply-ing primarily input control mechanisms (i.e., socialization) and instilling employees with ashared set of values, objectives, and beliefs about how to coordinate effort to reach commonobjectives (Pettigrew, 1979; Lebas and Weigenstein, 1986). The relationship between clancontrol systems and input control targets leads to Hypothesis 3.

Hypothesis 3. Managers within clan control systems achieve the highest levels oforganizational performance by focusing primarily on input control targets.

2.6. A Broader Perspective on Organizational Control

An alternative view to understanding how managers target controls challenges the generalpremise outlined in Proposition 1. It presents a broader perspective on organizational controland suggests that managers direct organizational controls concurrently towards multiplecontrol targets. This second view builds from arguments that traditional control theory’semphasis on singularly-focused controls presents “an overly rational conceptualization”of managerial attention and action (Folger et al., 1992, p. 130) and incorrectly assumesthat managers are able to readily develop employment contracts based on accurate, reliablemeasurements of employee task performance (Noorderhaven, 1992; Jaworski et al., 1993;Ghoshal and Moran, 1996).

This broader perspective on organizational control builds from observations by some con-trol theorists that managers utilize various forms of control to achieve multiple goals andaddress a complex array of organizational contingencies (Cyert and March, 1963; Merchant,1985; Lebas and Weigenstein, 1986; Jaworski, 1988; Cardinal, 2001). For example, bothKaplan and Norton (1992) and Simons (1995) argue that managers who balance their atten-tion to multiple performance measures enable organizations to achieve range of importantperformance goals. March (1996) and Sutcliffe et al. (2000) suggest that effective orga-nizations balance exploration and exploitation activities. Similarly, Quinn (1988) arguesthat the most successful managers balance their attention to multiple “competing,” if notcontradictory values.

Cardinal et al. (2002a, 2002b) provide empirical support for this broader perspective oforganizational control. Their recently completed 10-year examination of a moving companycharts the development of an organization’s control system through several stages in whichmanagers applied control mechanisms to various configurations of multiple control targets.They observed that managers made separate, but interdependent decisions regarding controlsystems and control targets. This led them to suggest that managers operating within market,bureaucratic, and clan control systems do not focus on single control targets, but focus ondifferent combinations of multiple control targets.

This broader perspective on organizational control is summarized in Proposition 2:


Proposition 2. Managers operating within various control systems will achieve the high-est levels of organizational performance by applying control mechanisms to configurationsof multiple control targets.

In their study, Cardinal et al. (2002b) observed that managers focused on configurationsof multiple control targets as their organization evolved first as a market, then a clan, thena bureaucratic control system. When the organization exhibited traits of a market controlsystem, managers focused on output control targets and some process control targets. In ad-dition, when the organization, at different times, exhibited traits of a clan and a bureaucraticcontrol system, managers applied control mechanisms to input, process, and output controltargets. Their observations provide strong evidence that managers seek to improve controlsystem performance by focusing concurrently on multiple control targets. This leads to thefollowing hypotheses:

Hypothesis 4. Within market control systems, managers who focus on combinationsof input, process, and output control targets achieve higher levels of organizationalperformance than managers who focus on single control targets.

Hypothesis 5. Within bureaucratic control systems, managers who focus on input,process, and output control targets achieve higher levels of organizational performancethan managers who focus on single control targets.

Hypothesis 6. Within clan control systems, managers who focus on input, process,and output control targets achieve higher levels of organizational performance thanmanagers who focus on single control targets.

2.7. Research Focus

The focus of this study is to determine which theory of organizational control implementa-tion provides the most effective method for managing tasks. Below, we describe our use of acomputational model to examine how effectively organizations complete a set of tasks whenmanagers focus on various combinations of control targets within three types of control sys-tems. The outcomes produced under each condition will allow us to evaluate Propositions1 and 2 and Hypotheses 1–3 and 4–6 and determine which perspective on control describesthe most effective mechanisms for managing organizations.

3. Computational Methods

We evaluate Propositions 1 and 2 and Hypotheses 1 through 6 using the commercial softwareversion of the Vite’Project (also VITE’) computational discrete event computational modeldeveloped by Professor Ray Levitt and his research associates at the Center for IntegratedFacility Engineering at Stanford University.2 We use the 2.2 version of the Vite’Projectprogram to examine how various combinations of control systems and control targets dif-ferentially affect organizational performance. This program has been validated using case


studies (Jin and Levitt, 1996) and has been successfully employed as a organizational re-search tool to evaluate various types of communication structures (Carroll and Burton,2000) and virtual organizations (Wong and Burton, 2000).

Based on information processing theory (March and Simon, 1958; Galbraith, 1977;March, 1991), Vite’Project allows researchers to model communication and organizationalstructures and analyze projects performed by groups of boundedly rational actors. Whileother computational models have been used to examine various types of organizational forms(Harrison and Carroll, 1991), organizational structures (Ouksel and Vyhmeister, 2001), andpromotion systems (Phelan and Lin, 2001), we utilized Vite’Project for this study becausethe program is specifically designed to model how information is exchanged between actorsworking on production tasks. As we describe below, this feature of the program allowedus to effectively model types organizational control systems and various combinations ofcontrol targets.

3.1. Vite’Project

Vite’Project is developed from information-processing models of organizations (March andSimon, 1958; Galbraith, 1977). Boundedly rational actors work together in Vite’Projectorganizations to complete a multi-task project. Because these actors require informationfrom each other to complete their given tasks, they send and receive messages acrossestablished communication channels. In creating a Vite’Project organization, the modeler ischarged with developing project tasks and subtasks, identifying a task-completion sequence,assigning actors to tasks, modifying various actor attributes, and constructing an overallorganizational structure within which tasks are performed. A comprehensive discussion ofthe Vite’Project program is presented by Jin and Levitt (1996).

3.2. Actors

Boundedly rational actors within Vite’Project are distinguished by the specific skills theypossess, their abilities to implement those skills to complete tasks, and the other workerson the project with whom they are permitted to communicate. Actors can be assigned toone of a variety of roles in a Vite’Project organization. For example, an actor may serve asa project manager, team manager, or front line worker. The higher a position an actor holdsin an organization’s hierarchy affects the types of decisions they make and the amount ofinformation they are required to process. When actors lower in an organization encounterproblems in completing tasks, they generally require information from their superiors.Hence, actors in the upper levels of the hierarchy must perform their own tasks and alsospend time responding to information requests from their subordinates.

3.3. Project Tasks

How effectively actors work together to complete their tasks is determined by how effectivelyinformation flows throughout the organization. Information flows are affected by fixedcommunication channels that prescribe when and how actors attend to their tasks andexchange task-based information with other actors in the project team.


Each actor in the organization is assigned to complete one or more tasks. If an actor en-counters problems while working on a given task, they will attempt to resolve their problemby gathering pertinent information from the co-workers within whom they are connected(i.e., managers or those completing related tasks). When information flowing through theorganization is effectively managed, actors communicate smoothly and have their queriespromptly handled. When information is ineffectively managed within a given organization,actors can become overwhelmed with information requests. Under these circumstances, ac-tors who initiate queries do not receive prompt answers to information requests, are forcedto waste time waiting for information and, if information delays persist, resort to makingtask-based decisions without appropriate information.

3.4. Organizational Structure

Communications between actors are determined by the tasks each performs and the overallorganizational structure within which information exchange takes place. VITE’ permits themodeler to establish an exception-handling, organizational hierarchy to dictate the primarylevel at which organizational decisions are made (i.e., to whom subordinates must reportproduction problems) and where collaboration between actors occurs. Communicationsbetween actors are determined by these hierarchical distinctions, as well as informationexchange relationships between individual actors, and organizational meetings that areperiodically scheduled to facilitate multi-actor communications on project topics.

3.5. Organization Parameters

Information flow within a given organization can be further refined using VITE’s four “or-ganization” parameters: centralization, formalization, team experience, and matrix strength.Each of these parameters may be set to a value of low, medium or high.

Centralization denotes the level of the organizational hierarchy where exceptions are han-dled and decisions regarding tasks are made. High centralization designates project man-agers as decision-makers. Medium centralization designates team leaders. Low central-ization (i.e., decentralization) designates front-line workers as decision-makers.

Formalization determines the frequency that actors initiate ad hoc communications withother employees (i.e., project manager, team leaders, workers). In highly formalized or-ganizations, actors rarely initiate ad-hoc communications. Instead they exchange infor-mation within the communication channels of the formal organizational hierarchy. Whenformalization is low, employees frequently gather organizational information throughad-hoc communications with employees and rely less on information-gathering throughthe formal hierarchy. When formalization is medium, employees exchange informationthrough both formal and informal communication channels.

Team Experience determines the amount of experience organizational members possess onspecific projects. Employees with high team experience are used to working with eachother and are familiar with specific forms of project work. Employees with low team


experience are not used to working with each other and are unfamiliar with certain formsof project work.

Matrix Strength relates to functionalization. Actors in organizations with high matrixstrength focus primarily on their individual duties and attend little to communicationsinitiated by other employees. Actors in organizations with low matrix strength attendless to their functional duties and more routinely respond to the ad hoc communicationsinitiated by other employees.

3.6. Outcome Measures

VITE’ provides a variety of performance measures that evaluate project cost and productiontime. In addition, the program calculates the amount of time and cost various actors expendon project-related activities. For this study, we utilize overall project cost as our performancemeasure.

4. Virtual Experiment

We conducted three separate 4 ∗ 1 analyses of variance (ANOVAs) to test the efficacyof focusing on four control target combinations (singular input control, singular processcontrol, singular output control, combined input-process-output control) within each typeof control system. Table 1 outlines our experimental design.

4.1. Modeling Actors and Tasks

We modeled 3 simple control systems, consisting of one project manager, two team leadersand two teams each comprised of two workers. Project managers, team leaders, and workers

Table 1. Research design for testing the effectiveness of control target combinations within market, bureaucratic,and clan control systems.

Market control Bureaucratic control Clan controlsystem system system

Control target combinations

Input control Input control in market Input control in bureaucratic Input control in clancontrol system control system control system3

Behavior control Behavior control in Behavior control in bureaucratic Behavior control inmarket control system control system2 clan control system

Output control Output control in market Output control in bureaucratic Output control in clancontrol system1 control system control system

Input/behavior/ Input/behavior/output Input/behavior/output Input/behavior/outputoutput control control in market control in bureaucratic control in clan

control system4 control system5 control system6

1–3 indicate predictions contained in Hypotheses 1–3.4–6 indicate predictions contained in Hypotheses 4–6.


were differentiated primarily by the tasks they performed. Within each organization, eachworker performed a generic production task. While workers performed these tasks, teamleaders directed them using combinations of input, process, and output controls. Projectmanagers coordinated the work of all actors by implementing policy decisions and handlingexceptions when task problems arose.

4.2. Modeling Control Targets

We used VITE’s failure dependency function to model managerial attendance to input,process, and output control targets. Failure dependency relationships connect related tasks.When failure dependencies exist between tasks, errors that occur in one task lead the actorperforming that task to work with the actor performing the related (i.e., failure-dependent)task and correct those errors.

We modeled organizational control mechanisms by connecting managers’ monitoringactivities to workers’ production tasks. When managers detected errors that occurred inworkers’ production activities, managers collaborated with those workers to correct theerrors and solve the identified production problems (i.e., apply controls).

We manipulated a manager’s control focus by altering the position of control applicationsin the production process and the amount of time managers devoted to their application.Managers applied input controls before workers began their work. Failures to provide work-ers with appropriate inputs forced team leaders and workers to jointly improve managers’input selection and preparation processes. Managers applied process controls to workerswhile they performed their tasks. Workers’ errors during tasks forced team leaders to spendtime and effort identifying and helping workers remedy deficiencies. Team leaders appliedoutput controls to tasks after workers completed them. Here again, detected errors forcedteam leaders to spend time and effort identifying and helping workers remedy deficiencies.

In order to model four control target combinations (i.e., input control, process control,output control, input-process-output control), we altered the amount of time (i.e., withinnine-hour work days) that managers focused on specific control targets. To generate ana-lyzable results, managers always spent some of each nine-hour work day attending to input,process, and output control targets. When managers focused on a single control target theydevoted eight hours of their nine-hour work day to that primary control target (e.g., inputcontrol) and a half-an-hour each to the other two control targets (e.g., process and outputcontrol). Under the multiple control target condition (i.e., input-process-output control),managers distributed their attention by focusing three hours each day on input, process,and output control targets, respectively. Our manipulations of control targets are outlinedin Table 2.

4.3. Modeling the Production Process

We used the same production process in each experimental condition. A diagram of thisprocess is displayed in figure 1. First (1), managers apply input controls and select resourcesfor workers to use in performing tasks. Second (2a), workers perform tasks using inputsprovided by managers. (2b) Insufficient inputs lead workers and managers to jointly correct


Table 2. Control target attributes for control target combinations.

Input/behavior/Input control Behavior control Output control output control

Control target attributes

Portions of production Before tasks During tasks After tasks Before, during,sequence when control and after tasksmechanisms are applied

Time allocateda to

Input control 8 hours .5 hour .5 hour 3 hours

Behavior control .5 hour 8 hours .5 hour 3 hours

Output control .5 hour .5 hour 8 hours 3 hours

aDuring nine-hour work day.

Figure 1. Diagram of the model production process.


errors and rework tasks. While subordinates perform tasks, managers exert process controls(3a). (3b) Inappropriate behaviors displayed by subordinates during production processeslead managers to help workers correct these deficiencies. Once tasks are complete, managersevaluate work outputs (4a). Insufficient outputs lead managers to help workers correct outputdeficiencies. Throughout (5), the project manager supervises the process while addressingexceptions, as well as the questions and requests of team managers.

It is important to note that we held all other Vite’Project parameters constant and at“medium” levels for the entire study. For instance, across subjects, uncertainty and taskprogrammability were held at this level. This helped ensure that, within subjects (i.e., controlsystems) the results of this study were not biased by unfairly advantaging a particular controlsystem/control target combination.

4.4. Modeling Control Systems

We differentiated control systems by manipulating organizational structures, the frequencyand attendance of actors (i.e., project manager, team leaders, workers) at organizationalmeetings, and Vite’Project “organization” parameters. Table 3 provides a summary of con-trol system parameters manipulated in this study.

4.4.1. Market Control System. Workers within market control systems are employed onshort-term contracts rather than as long-term employees of their organizations (Ouchi,1979). Because these workers are not established members of the organization, we did notconnect team leaders to workers within the hierarchy (figure 2). Similarly, we restricteddaily meeting participation to established organizational members (i.e., project manager,

Table 3. Control system attributes for market, bureaucratic, and clan control systems.

Market control Bureaucratic control Clan control systemsystem attributes system attributes attributes

VITE’ organization parameters

Centralization Medium High Low

Formalization Medium High Medium

Matrix strength High High Low

Team experience Low High High

Structural parameters

Hierarchy Incomplete: Workers Complete Completeand team leaders notconnected in hierarchy

Meetings Daily (1-hour): Project None Daily (1-hour): Projectmanager and team manager, team leaders,leaders are required and workers are requiredto participate to participate

Information Coupled with each failure- Coupled with each failure- Coupled with each failure-exchange dependence relationship dependence relationship dependence relationship


Figure 2. The market control system.

team leaders) and set team experience to low. We set centralization to medium to ensurethat team leaders held primary decision-making authority over workers’ activities. We alsoset formalization to medium to allow workers and managers to conduct both formal and/orinformal communications. Lastly, because workers are generally hired and retained fortheir individual contributions in market organizations, we assumed that they should focusprimarily on their individual tasks and set matrix strength to high.

4.4.2. Bureaucratic Control System. In contrast to the market system, actors within thebureaucratic control system are established members of their organizations (figure 3). Con-sequently, we connected them within the exception-handling hierarchy. Because actors inbureaucratic organizations communicate primarily through formal communication chan-nels (Ouchi, 1980), multi-actor meetings were not scheduled. To model the characteristicsof a bureaucratic control system, formalization, centralization, and matrix strength were allset to high (Weber, 1946). We also set team experience to high to capture how bureaucraticcontrol systems use elaborate, mature rule systems to specify task completion procedures.

4.4.3. Clan Control System. Actors within clan systems are generally established membersof their organizations (figure 4). Consequently, we connected them within the exception-handling hierarchy and, to simulate the process of developing norms and rules (Ouchi,1979, 1980), required their attendance at daily meetings to develop collective solutions toorganizational problems. We set formalization to medium because actors in the clan systemextensively use both informal, ad hoc communications (Roth et al., 1994) and meetings to


Figure 3. The bureaucratic control system.

exchange task information with individual and groups of other employees. Centralizationand matrix strength were both set to low to simulate how workers are trusted to make theirown decisions and freely collaborate with other employees. Because employees withinclan control systems often develop close working and personal relationships, we set teamexperience to high (Ouchi, 1981; Wilkins and Ouchi, 1983).

4.5. Procedure

We used analysis of variance (ANOVA) procedures to test the efficacy of focusing onspecific control combinations (singular input, singular process, and singular output control;combined input-process-output controls) within each control system (market, bureaucratic,clan). While Vite’Project provides several measures of project output, we opted to useoverall project duration and cost (in thousands of dollars) as the performance measuresin this study. This is consistent with traditional control research that has examined theleast expensive method that managers choose to complete organizational tasks (Barney andHesterly, 1996).

In this study, we examine how much it costs managers operating within each controlsystem, using various combinations of organizational control mechanisms, to produce 100production units. For each control system, VITE’ calculated how much it cost (in thousands


Figure 4. The clan control system.

of dollars) the organization to complete a full production run. To develop statistical measures,the overall production cost of 10 complete production runs were recorded and averaged foreach control system/control target condition.

We then tested Propositions 1 and 2 and Hypotheses 1 through 6 by comparing the costof producing 100 units within each control system when managers focused on applyingeach control combination.

5. Results

The results for this study are presented in Table 4.Market Control System. A 4 ∗ 1 ANOVA yielded a significant effect for control combi-

nations F(3, 36) = 182.49, p < .001. Within the market control system, the application ofinput/process/output controls obtains the lowest overall production cost (M = 32.9, SD =.60). Managers using this combination produced 100 units more cheaply than those apply-ing input controls (mean difference = 4.2, s.e. = .31), output controls (mean difference =5.2, s.e. = .31), or process controls (mean difference = 6.8, s.e. = .31). Each of the threeforms of singular controls obtained significant differences in production cost (p < .05).

Bureaucratic Control System. A 4 ∗ 1 ANOVA obtained a significant effect for controlcombinations F(3, 36) = 212.76, p < .001. Within the bureaucratic control system, theapplication of input/process/output controls obtained the lowest overall production cost


Table 4. Mean project cost (in thousands of dollars) when managers use specificcontrol target combinations within market, bureaucratic, and clan control systems.

Market control Bureaucratic control Clan controlsystem system system

Input controlM 37.1a 35.0 38.7a

SD .67 .58 .68

n 10 10 10

Behavior control

M 39.7 33.7a 42.5

SD .73 .50 1.3

n 10 10 10

Output control

M 38.1 33.7a 50.0

SD .71 .33 1.4

n 10 10 10

Input/behavior/output control

M 32.9b 30.1b 33.4b

SD .60 .35 .38

n 10 10 10

aIndicates lowest total project cost among applications of singular control targetswithin control system.bIndicates lowest total project cost within a control system.

(M = 33.1, SD = .35). Managers using this combination produced 100 units more cheaplythan those applying process controls (mean difference = 3.6, s.e. = .20), output controls(mean difference = 3.6, s.e. = .20), and input controls (mean difference = 4.8, s.e. = .20).Managers did not obtain significant differences in production costs when applying eitheroutput controls or process controls (p > .10). Both of these sets of managers, however,did obtain significant differences in production costs when compared to managers whoapplied only input controls (p < .001).

Clan Control System. A 4 ∗ 1 ANOVA obtained a significant effect for control combi-nations F(3, 36) = 435.36, p < .001. Within the clan control system, the applicationof input/process/output controls obtained the lowest overall production cost (M = 33.4,SD = .38). Managers using this combination produced 100 units more cheaply than thoseapplying input controls (mean difference = 5.3, s.e. = .47), process controls (mean dif-ference = 9.1, s.e. = .31), or output controls (mean difference = 16.6, s.e. = .31). Eachof the three forms of singular controls obtained significant differences in production costs(p < .001).

The results of this study support Proposition 2 and Hypotheses 4–6, and those who sug-gest that managers who focus on multiple control targets are more effective than thosewho focus on single control targets. Specifically, when managers focus on multiple control


targets they help workers produce less expensively than when they focus controls on indi-vidual control targets. By demonstrating the efficacy of focusing on multiple control targets,the study strongly supports the broader perspective on organizational control.

There are several reasons why a focus on multiple control targets results in increasedproject performance. First, because problems may arise at any point in the production pro-cess, the open flow of information between front-line workers and managers who maintainthis varied focus make them more ready to deal with problems whenever they happen todevelop (Merchant, 1985). Second, because managers exchange information with workersat multiple points, they can remedy problems that occur in various areas of the productionprocess and not just individual sections of it. Third, because managers work an equal amountof each day addressing problems regarding production inputs, processes, and outputs, theydo not sit idle waiting for problems (i.e., that may never appear) at only one productionpoint. When problems on a particular production segment are corrected, managers whofocus on multiple control targets can move on to work at other production segments whereproblems may exist.

The results obtained from this study also partially support Proposition 1, Hypotheses 2and 3, and those who suggest that managers within specific control systems should focuscontrol mechanisms towards single control targets. Specifically, theorists who suggest thata single control target focus is effective within certain types of control environments arecorrect only when they compare results obtained between single control applications. Whencomparing managerial attention to individual control targets, input control is most effectivein clan control systems. Within the bureaucratic control systems, process controls and out-put controls rank equally as the most effective, singular forms of control. In addition, inputcontrol is the most effective control in the market control system. While the first two resultsdo respectively support Hypotheses 2 and 3, the last result, contradicts Hypothesis 1.

These results suggest that relationships between specific control systems and controltargets place information flows between managers and subordinates where they are mostneeded. In all three control systems, the level of decision-making centralization appears tobe a key factor in determining this best single control target choice. Managers who focus oninput controls within both market and clan control systems obtained lower costs primarilybecause these two types of control systems rely on fairly decentralized decision-making.Because front-line workers in these control systems make many of their own decisionsand follow few established rules (i.e., moderate formalization), managers must exchangeinformation with workers before they begin working on their tasks. This allows managersto provide them with the best resources to address problems early in a production cycle,before workers begin making production decisions (Barney and Ouchi, 1986; Eisenhardt,1989).

Managers in bureaucratic control systems, however, generally rely quite heavily on cen-tralized decision-making and formalization. Because these workers will be more reliant ondirections from superiors, the most effective managers in these control systems exchangeproduction information with workers during or immediately after the production processhas been completed. By focusing managers’ efforts at these points, managers can directworkers as problems arise. As a result, the most efficient workers in bureaucratic controlsystems do not wait long for managerial direction and waste production time.


6. Discussion

This study simultaneously broadens and deepens our understanding of organizational con-trol. The results we obtained suggest that managers who focus on multiple control targetsare more effective than managers who focus on single control targets within a variety ofcontrol systems. Results of the study also partially support more traditional control theorythat has posited structural similarities between specific types of control systems and con-trol targets. Within this section, we discuss several theoretical and empirical contributionsof this research effort and present suggestions for future research.

6.1. Control Combinations

Results of this study provide empirical support for those who have argued that the effectiveimplementation of multiple controls is important to control system functioning (Merchant,1985; Simons, 1995; Cardinal et al., 2002b). Established control theory suggests that man-agers’ most important control decisions involve choices about applying control mechanismstowards individual control targets (Ouchi, 1977, 1979; Barney and Ouchi, 1986; Eisenhardt,1989). However, by comparing the results when managers apply multiple controls to thosethat they achieve when they apply singularly-focused controls, this study provides strongevidence that the most effective managers distribute their attention across multiple controltargets.

Organizations are complex systems and by focusing on multiple control targets, managerscan address a wide variety of problems that may arise within an organization (Merchant,1985) and effectively direct employees towards multiple goals (Cyert and March, 1963;Merchant, 1988; Simons, 1995). In addition, because managers who focus on multiplecontrol targets develop competencies across an entire production process, they are betterequipped to capitalize on a wide array of production-related opportunities to achieve greaterefficiency and effectiveness (Simons, 1995).

By identifying structural complementarities between specific types of control systems andcontrol targets, the results of this study also increase our understanding about some posited,but not previously tested propositions regarding singularly-focused controls (Barney andOuchi, 1986; Eisenhardt, 1989). The identification of relationships between input controlsand market and clan control systems and between process controls and bureaucratic controlsystems suggests that specific control targets are more effective within certain control sys-tem environments. This indicates that control target researchers should account for controlsystem context in their studies of control targets. This also implies for practicing managersthat, when resources are very low or multiple control targets cannot be monitored, attentionshould be focused on portions of the production process that are structurally related to theoverall control system.

We note however, the relationship between input control targets and market controlsystems. While contradicting Hypothesis 1, this represents an interesting result. It suggeststhat input control is an important factor in the successful operation of a market controlsystems. While Lebas and Weigenstein (1986) and Ouchi (1979) highlight the importanceof output control in market control systems, this result indicates that managers should spend


at least as much time making sure their employees are properly trained and equipped asthey do creating effective incentive systems.

6.2. Control Classifications

Within this study, we rely on distinct conceptualizations of control systems and controltargets. Consistent with other researchers (Ouchi, 1979, 1980; Lebas and Weigenstein,1986; Roth et al., 1994), control systems are classified as an organization-level concept.In addition, we suggest that control targets describe the efforts managers make to directcontrol mechanisms at specific portions of their organization’s production process (Ouchiand Maguire, 1975; Ouchi, 1977, 1979; Eisenhardt, 1985).

These distinctions build on existing theory and clarify some inconsistencies regardingconceptualizations of control systems and control targets. Cardinal et al. (1999), for example,argue that control scholars have failed to clearly define the use of the term “clan” in previouscontrol research. In some cases the “clan” has been defined as a control system (Ouchi, 1979,1980; Jaworski et al., 1993; Roth et al., 1994), in other cases as a control target (Ouchi,1977; Eisenhardt, 1985), and in still others, as merely a form of input control (Ouchi, 1975;Snell, 1992).

We, however, identified the clan as a control system and differentiated it from a manage-rial use of input control mechanisms. We created similar distinctions with all three controlsystems (market, bureaucratic, clan) and four control target configurations (singular input,singular process, singular output, combined input-process-output). These clear conceptu-alizations allowed us to easily integrate the concepts of control systems and control targetsand create identifiable combinations of each.

6.3. Performance Measures and Controls

While these classifications of control systems and control targets were derived from previousresearch on control (Ouchi, 1977; Merchant, 1985; Kirsch, 1996), the VITE’ environmentallowed us to develop control mechanisms that adhered to our classification scheme. Thisapproach also permitted us to examine the effects produced by these control mechanismswithin three “ideal” types of control systems (i.e., market, bureaucratic, clan) that researcherssuggest are difficult to clearly identify in field research contexts (Ouchi, 1979; Bradach andEccles, 1989). By comparing and contrasting the overall production performance of variouscontrol target combinations within specific types of control systems, we were able to evaluatetwo general theories of organizational control application.

It is also important to note that VITE’ allowed us to manipulate aspects of both controlsystems and control targets while holding external and internal variables constant. Thisprovided us an advantage over field research on organizational control where externalinfluences such as managerial differences or, for example, differences in employee moralecan dramatically affect measured dependent variables (Ouchi, 1977; Snell, 1992). As aresult, we were able to examine the effects produced by different configurations of controlsystems and control targets while ensuring that we did not positively or negatively bias anyspecific control system/control target combination.


Lastly, because traditional control research has relied on efficiency measures to examinethe efficacy of control usage (e.g., Ouchi, 1977, 1979; Snell, 1992; Kirsch, 1996), we reliedon overall production duration and cost as outcome measures in this study. Using VITE’,we were able to conduct a controlled study unencumbered by the limitations experiencedby previous control researchers. While past researchers have argued from their results thatmanagers choose controls that provide them the least expensive method of directing workers(Ouchi, 1977; Eisenhardt, 1985; Barney and Hesterly, 1996), these studies have often onlymeasured the controls managers selected and simply assumed that those managers chose thelowest cost options (Ouchi, 1977; Eisenhardt, 1985; Snell, 1992). We, however, were ableto directly generate and compare the costs of applying configurations of multiple controltargets within various control systems.

6.4. Limitations

While we believe that VITE’ provided us many advantages, it also limited us in some ways.For example, we feel confident that we were able to accurately model various types ofcontrol systems and control targets but we also acknowledge the possibility that other plat-forms and models may effectively address additional aspects of organizational control. Forexample, this study is potentially limited by the fact that it focused only on the informationprocessing attributes of specific control system/control target combinations (Thompson,1967; Ouchi, 1977). While several authors (Galbraith, 1973; Ouchi and Maguire, 1975;Ouchi, 1979) have suggested that controls should be conceptualized and examined as aseries of information flows, other programs and experimental designs may have allowed usto manipulate additional facets of control not considered here.

Vite’Project is also limited because model actors do not appear to learn or allow experi-ence to help them improve their knowledge of production efforts. Ouksel and Vyhmeister(2001) and Carley (1992) have modeled how various organizational structures affect orga-nizational learning and performance. Our model, however, did not model learning processesand, consequently, we were unable evaluate how managerial experience applying certainforms of control could affect achieved performance. In order to incorporate aspects oflearning into this type of analysis, additional studies will need to be conducted.

Lastly, we did not alter the behavioral matrix that Vite’Project has developed for itsorganizational actors. Hence, we relied on Vite’Project programmers and believe that theyhave developed accurate models of human behavior. There is fairly strong evidence that thisis probably the case. Vite’Project has been used previously and successfully in organizationalresearch (examples include Carroll and Burton (2000) and Wong and Burton (2000)). Inaddition, Vite’Project has been validated through its use in the field and in examining variouscase studies (Jin and Levitt, 1996).

6.5. Future Research

Future research should conduct more complete evaluations of specific control system/controltarget configurations. These studies may examine additional combinations of single and mul-tiple control targets and control systems under alternative environmental and task conditions.


Results of this work may directly challenge existing control target research and its strongclaims that managers select specific, singular control targets largely as a result of the tasksthey manage (Long, 2002).

Organizational control systems are complex entities and future research is required toevaluate additional conditions under which managers are both restricted and enabled to ap-ply certain types of control mechanisms. For example, under certain task or environmentalconditions, it may be easier for managers to apply controls (e.g., rules or socialization) toprocess control targets and input control targets than to output control targets (e.g. perfor-mance incentives). Results from such studies may provide a much richer understanding ofthe control decisions managers employ than current theory provides.

7. Conclusion

This paper investigates aspects of complex organizational control systems. We present sev-eral hypotheses which integrate and extend agency- and transaction-based approaches toorganizational control. Results of this study support the emerging “broader” perspectiveon organizational control research and suggest that managers can improve organizationalperformance by focusing their attention on multiple control targets. In addition, this studyexamines and partially supports previously posited relationships between control systems(market, bureaucratic, clan) and control targets (input, process, output). The authors suggestthat the findings of this study should help scholars refocus control research from exami-nations of singularly-focused forms of control to evaluations of more complex controlsystems.

Acknowledgments

The authors wish to thank Professor Ray Leavitt and his Stanford University colleagues forthe use of Vite’Project computational software. In addition, the authors wish to thank TimCarroll for his assistance in programming Vite’Project software for this study. Portions ofthis research were presented at the CASOS Conference, Pittsburgh, PA and at the StrategicManagement Society Conference, Vancouver, Canada.

Notes

1. Lewin and Stephens (1990) argue that an organization’s design consists of its information and technologyand control systems as well as its structural form, production technology, human resource policies, incentives,organizational culture, and interorganizational linkages.

2. We obtained Vite’Project 2.2 through an agreement with the Vite’ Corporation, Mountain View, CA. We ranthe program on a Gateway desktop computer using Windows 98.

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Chris P. Long is an Assistant Professor of Organizational Behavior at the Olin School of Business, WashingtonUniversity in St. Louis. His research focuses on various aspects of control, trust, and fairness within both tradi-tional organizations and new organizational forms. He is currently examining how managerial systems which arecomprised of these three elements (controls, trust-building initiatives, fairness-building initiatives) evolve overtime, affect actor justice and trust perceptions, and are used to accomplish various organizational performanceobjectives. Chris received his Ph.D. from Duke University.


Rich Burton is Professor of Business Administration at The Fuqua School of Business, Duke University. Heis also Professor of Management at the EIASM (European Institute for Advanced Studies in Management) inBrussels. His research focuses on organizational design, and particularly using computational approaches. He hasDBA from the University of Illinois, as well as BS and MBA. He is active on a number of editorial boards and haspublished some sixty articles on organizational design and management science, and seven books.

Laura B. Cardinal is Assistant Professor of Strategic Management at the Kenan-Flagler Business School, Univer-sity of North Carolina at Chapel Hill. Her research interests center on managing innovation and change, particularlyresearch capabilities in new product development, the management and location of R&D, and managing control-system adaptation. She received her Ph.D. from the University of Texas at Austin. She has published in StrategicManagement Journal, Organization Science, Academy of Management Journal, and Journal of Accounting andEconomics.

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