An empirical comparison of small and large organizations

The purpose of this paper is to evaluate competing views of whether organization size creates conditions of rigidity or fluidity with respect to adaptation and change, this study empirically compares processes used to implement planned change and their associated outcomes in small and large organizations.

The current issue and full text archive of this journal is available at www.emeraldinsight.com/0140-9174.htm Size, structure and change implementation An empirical comparison of small and large organizations Size, structure and change implementation 303 Matthew W Ford Department of Management, College of Business, Northern Kentucky University, Highland Heights, Kentucky, USA Abstract Purpose – The purpose of this paper is to evaluate competing views of whether organization size creates conditions of rigidity or fluidity with respect to adaptation and change, this study empirically compares processes used to implement planned change and their associated outcomes in small and large organizations Design/methodology/approach – Using Lewin’s three-phase model of change as an evaluative framework, questionnaire-based data were obtained from change managers in small and large organizations Analysis of variance and profile analysis were used to investigate size-related differences in unfreezing, movement and refreezing phases of change, and in implementation success Findings – Results indicated that small organizations employed significantly lower levels of refreezing activities and realized lower levels of implementation success relative to large organizations Research limitations/implications – While cross sectional in nature, the sample’s modest size limits the extent to which findings can be generalized Future research should consider whether size related effects depend on change related factors such as intentionality or continuity Practical implications – Although managers in many large organizations seek to dismantle hierarchical structure, potential consequences of such a move should be carefully considered Reducing hierarchy may decrease capacity for managing change Conversely, small organizations may improve change management capability by adding structure that improves implementation control Originality/value – This paper offers an uncommon empirical glimpse into processes of change in the context of organizational size Empirical evidence suggesting that organizational size may not be a hindrance, and perhaps an advantage, when implementing planned change constitutes the primary contribution of this study Keywords Large enterprises, Small enterprises, Organizational change, Change management Paper type Research paper It has long been accepted that structure increases with organizational size (e.g Child, 1973; Grinyer and Yasai-Ardekani, 1981; Miles and Petty, 1977) Competing views have evolved concerning the influence of size and structure on organizational adaptation and change One perspective contends that formalization and standardization reduce inertia, signifying a negative relationship between size and adaptation (e.g Hannan and Freeman, 1984; Kelly and Amburgey, 1991) Another view posits that structural differentiation increases expertise and mechanisms for routinizing change, suggesting a positive relationship between size and change Essentially, the issue involves whether size creates conditions of rigidity or fluidity for organizational change (Haveman, 1993) The relationship between organizational size and change may depend on contextual factors such as environmental turbulence or change scope (Haveman, 1993; Kimberly, 1976) Due to lack of confirmatory research, however, general relationships between size and change cannot be ruled out For example, control systems have frequently Management Research News Vol 32 No 4, 2009 pp 303-320 # Emerald Group Publishing Limited 0140-9174 DOI 10.1108/01409170910944272 MRN 32,4 304 been cited as necessary elements of effective change processes (Burke and Litwin, 1992; Ford and Greer, 2005; Kotter and Schleisinger, 1979; Tichy, 1983) However, smaller organizations typically lack formal controls (Cardinal et al., 2004; Davila, 2005; Kotey and Slade, 2005), which may place them at a general disadvantage when implementing change (Sine et al., 2006) This study evaluates the competing perspectives on organizational size and change using an empirical approach First, Lewin’s (1947) model is employed as a conceptual framework for hypothesizing about change process differences in small and large firms, and about the influence of these process differences on implementation success Then, the hypotheses are empirically tested using data obtained from a sample of managers involved in change implementation Research and practical implications are then discussed Study of processes used by organizations to implement change, and of linkages between change processes and outcomes, can be an effective approach for generating insight into organizational change (Pettigrew et al., 2001) As such, using empirical methods to investigate general relationships between organization size, change processes, and outcomes constitutes a primary contribution of this study Hypothesis development Change processes can be viewed as sequences of individual and collective events, actions, and activities unfolding over time in context that describe or account for how entities develop or change (Pettigrew et al., 2001, p 700) While many change process models have been proposed (Burke, 1995), perhaps none has generated broader awareness than Lewin’s (1947) framework In Lewin’s view, the process of change can be divided into three phases Unfreezing is the first phase and involves questioning the organization’s current state and, if a different state is desired, then equilibrium needs to be destabilized before old behavior is discarded The second phase, movement, is a state of flux where new behavior is modified and fresh approaches are developed to replace old work patterns Refreezing constitutes the final phase and requires activities to institutionalize the new behaviors and attitudes, and to stabilize the organization at a new equilibrium Lewin’s (1947) model principally reflects processes associated with planned change (Burnes, 1996) Planned change refers to a premeditated, agent-facilitated intervention intended to modify organizational functioning towards more favorable outcomes (Lippit et al., 1958) This perspective largely reflects the teleological category of change theory advanced by Van de Ven and Poole (1995) in which organizational change is achieved primarily through the adaptive behavior of individuals in light of internally set goals Lewin’s proposition that planned change proceeds in three conceptually distinct phases has accumulated considerable support, as many change process models articulated across disciplines have been found to contain similar characteristics (Elrod and Tippett, 2002) Lewin’s (1947) model is not without its critics, however Some scholars take issue with the sequential implication of the planned, three-stage progression, arguing that change is a dynamic process that should not be treated as a linear series of events (e.g Dawson, 1994; Kanter et al., 1992) Moreover, the dynamic nature of many organizational environments is seen as rendering episodic planned change unrealistic to some who prefer instead to view change as continuous and emergent in nature (Burnes, 1996) The emergent perspective stresses the roles of culture, power, and cumulative low-level adaptations in shaping organizational change in a manner that may appear continuous in nature (Burnes, 2005; Dawson, 1994; Hatch, 1997) Despite the criticism, Lewin’s (1947) three-phase model remains an attractive framework for change process research Rather than binary allegiance to either perspective, utilizing a planned or emergent approach should depend on the evaluative context (Burnes, 1996) Because a substantial volume of evidence suggests that organizations frequently undertake change in a teleological manner and employ premeditated plans and actions to effect change (Huy, 2001), viewing change through a Lewin-like planned change lens appears warranted in many situations While some critics argue that Lewin’s approach applies narrowly to small group change, others have concluded the applicability of the three-phase model to be robust, and intended by the originator to be relevant to planned changes both small and large in scope (Burnes, 2004; Dickens and Watkins, 1999) Indeed, empirical studies have found Lewin’s threestep progression to be a valid representation of change process in various planned change contexts (Ford and Greer, 2006; Zand and Sorenson, 1975) Two streams of thought contrast the relationship between organizational size and capacity for implementing planned change Haveman (1993) aptly consolidated the competing perspectives in her ‘‘rigidity of size’’ and ‘‘fluidity of size’’ hypotheses The rigidity of size hypothesis contends that formalization, standardization, and resource dependence that generally increase with organization size foster inertia and hinder adaptability (Hannan and Freeman, 1984; Kelly and Amburgey, 1991) The fluidity of size hypothesis proposes that size-related differentiation spawns expertise and mechanisms for routinizing change Moreover, increased structure leads to greater resource slack and market power (Pfeffer and Salancik, 1978) that can facilitate the change process When testing these competing hypotheses on a sample of financial firms, Haveman (1993) found a positive relationship between size and change in many of the outcomes measured in the study However, the researcher concluded that a general relationship between size and change was unlikely and that organizational context was critical to understanding the relationship While Haveman’s (1993) study marked an important empirical test of the relationship between organization size and change, it possessed some limitations The sample was drawn from a single industry facing a particular change in the regulatory environment The focused design made it difficult to generalize about the relationship between size and change Examining a cross section of organizations implementing a variety of changes would improve generalizability of research findings Haveman (1993) also focused directly on the relationship between size and change outcomes rather than on processes employed by organizations of different size to implement change A comparative examination of change processes would offer better explanatory power about size-related differences in outcomes Because various stages or phases that reflect change processes are defined by groups of activities or events aimed at similar goals (Garvin, 1998), analysis of groups of activities linked to Lewin’s (1947) three phases could help delineate meaningful differences between change processes employed by small and large organizations To theorize about these differences, it is necessary to review Lewin’s unfreezing, movement, and refreezing phases in light of change process activities and structure that influence rigidity and fluidity In the unfreezing phase, change is initiated by destabilizing the equilibrium between forces that drive and restrain existing behavior (Lewin, 1947) Destabilization processes motivate learning and change by disconfirming extant expectations and redefining cognitive boundaries of the organization’s environment (Schein, 1996) Overcoming organizational inertia should play an important role in unfreezing the organization Inertia reflects limitations in an organization’s ability to adapt (Hannan and Freeman, 1977, p 930) and may relate to failure in adjusting resource patterns or organizational processes in response to environmental threat (Gilbert, 2005) It is Size, structure and change implementation 305 MRN 32,4 306 thought that inertia increases with organization size (Hannan and Freeman, 1984) Formalization that accompanies larger size should reinforce routines through structural embeddedness and repeated use (Kelly and Amburgey, 1991; Nelson and Winter, 1982) The structural inertia should make unfreezing difficult However, it is also possible that formalization facilitates unfreezing Formalization is a natural response to complexity (Child, 1973), and encourages differentiation, specialized expertise, and innovation (Briscoe, 2007) Routines can prompt organizations to regularly scan environments and question extant states relative to more desirable alternatives Goals and objectives that flow from such routines can disconfirm expectations and redefine cognitive boundaries of organizational members Structure can also reduce sensitivity to insignificant environmental signals that might otherwise cause the organization to overreact and unfreeze unnecessarily (Stensaker et al., 2002) A more focused, intentional unfreezing may result The general impact of size on Lewin’s (1947) movement phase is similarly unclear Once unfreezing has occurred, driving forces move the organization towards an improved state (Lewin, 1947; Zand and Sorenson, 1975) An important manifestation of these forces is modified behavior in the organization (Burnes, 2004) Behavioral adjustment is critical to organizational change (Goodman and Dean, 1982; Robertson et al., 1993; Tannenbaum, 1971) since the nature of behavior significantly influences organizational performance (Porras and Hoffer, 1986) As size increases, routines should make movement towards new behavior more difficult since patterns of action have become engrained and difficult to unlearn Structural complexity should also make coordination of implementation activities more difficult (Frederickson, 1986) However, formalization helps large organizations cope with complexity (Child, 1973), and organizational expertise that flows from the differentiated structure (Briscoe, 2007) generates knowledge about what needs changing and how to change it in order to achieve effective congruence with the environment It is therefore difficult to confidently hypothesize about general differences between small and large organizations relative to Lewin’s (1947) unfreezing and movement phases Small organizations seem easier to destabilize due to lack of structure, but unfreezing and subsequent movement may be haphazard and unfocused Large organizations should suffer from structural inertia, but formal processes permit focus on environmental stimuli that merit organized response, and encourage thoughtful unfreezing and movement towards behavior patterns that reflect a desirable future state It is Lewin’s (1947) refreezing phase where differences between small and large organizations are generally evident In the refreezing phase, behavior changes must be reinforced in order to stabilize the organization at improved performance levels and to avoid regression to old patterns of action (Lewin, 1947) Effective refreezing activities are confirmatory in nature (Schein, 1996) Confirmation is feedback that performance is effective, and may come from measurements, comments from others, and social comparisons as well as from rewards (Zand and Sorenson, 1975) The use of feedback processes to regulate change-related behavior and outcomes at desirable levels suggests that refreezing is oriented towards control In an organizational context, control involves the use of cybernetic regulatory processes that direct or restrain activities towards a standard or purpose so that an organization can accomplish its goals (Green and Welsh, 1988) Feedback and control in small organizations are often social in nature Social control systems are largely informal and stem from common agreement about what constitutes proper behavior and attitude in the organizational environment (O’Reilly, 1989) Social control is advantageous under conditions of high performance ambiguity and low goal incongruence (Ouchi, 1980) During periods of organizational change, however, goals and objectives are often difficult to articulate (Nadler and Tushman, 1989) thereby increasing levels of goal incongruence As implementation proceeds, small organizations may be unable to marshal enough feedback and control from social systems needed to realize high levels of refreezing In large organizations, hierarchy provides a means for structuring feedback and control (Child, 1972) Specialized structure and formalization facilitate data gathering and transmission systems (Nelson and Winter, 1982) Routines are established to monitor activities and outcomes on a regular basis, and to permit corrective action if a significant performance gap is perceived (Anthony, 1965; Simons, 1995) Because hierarchy and structure are advantageous when performance ambiguity and goal incongruence are moderately high (Ouchi, 1980), feedback and control obtained from large organization hierarchies are apt to translate into relatively high levels of refreezing as the implementation of planned change progresses It therefore seems likely that: H1 When implementing planned change, small organizations will generally exhibit significantly lower levels of refreezing than large organizations The effectiveness of a change process is tied to successful outcomes realized from implementation (Pettigrew et al., 2001) In the context of planned change, implementation success can be dimensionalized by factors related to completion, achievement, and acceptability (Miller, 1997) Completion refers to the extent to which plans associated with a change have been implemented within an expected period of time Achievement characterizes the level of convergence between the actual and intended performance of implemented changes Acceptability reflects the degree to which implementation and outcomes have been perceived as satisfactory by those involved with or affected by the change A significant body of anecdotal evidence suggests that issues related to refreezing, such as poorly designed reward systems and failure of managers to monitor and follow-up, often impede implementation success (e.g Bossidy and Charan, 2002; Charan and Colvin, 1999) Change scholars have also observed relationships between refreezing-related activities and change achievement (e.g Kotter and Schleisinger, 1979; Ford and Greer, 2005) In their study of Lewin’s (1947) model, Zand and Sorenson (1975) found strong relationships between refreezing and measures of success However, they cautioned against concluding that refreezing was the primary success factor, since refreezing and success both follow and depend upon unfreezing and movement Although path dependence surely exists in Lewin’s model, refreezing’s position at the end of the process does represent a bridge of sorts to implementation success An otherwise well crafted change initiative might generate low levels of implementation success if refreezing factors are poorly structured and executed Small firms usually lack formal controls (Cardinal et al., 2004; Lawler, 1947), and often rely on the influence of individuals and social systems to manage performance (e.g Boone et al., 2000; Miles and Petty, 1977) Large organizations, on the other hand, typically possess feedback and control systems to consistently execute refreezing, thereby encouraging positive implementation outcomes Stated formally: H2 When implementing planned change, small organizations will generally achieve significantly lower levels of implementation success than large organizations Size, structure and change implementation 307 MRN 32,4 308 Method and measures Data and sample Data for this study were obtained from managers participating in change management seminars sponsored by a large industrial coalition based in the United States As part of the seminars, which were conducted in the USA and Europe during expansionary economic conditions, respondents completed questionnaires that included the items used in this study When completing the questionnaires, managers were asked to record a change initiative that their organizations were implementing or had recently implemented, and then respond with this reference change in mind The overall process yielded 98 useable responses Demographically, 53 per cent of the respondents worked for service organizations and 47 per cent worked for manufacturing organizations Sixty seven percent of respondents came from private/for-profit enterprises, followed by 19 per cent from public/for-profit organizations, and 13 per cent from public sector/government agencies Nearly 95 per cent of respondents came from organizations of more than 50 employees; approximately 25 per cent of respondents were from organizations of greater than 1,000 employees Over 90 per cent of respondents were at least middlelevel managers; more than half were upper-level managers About half of the reference changes were estimated to be at least fifty percent completed at the time of the evaluation Respondents forecast that, once implemented, nearly half of the reference changes would impact at least 60 per cent of employees, suggesting that a large number of changes evaluated in this study were strategic, second order changes rather than incremental, first order changes (Bartunek and Moch, 1987; Nadler and Tushman, 1989) Examples of higher impact changes evaluated by respondents included developing a new strategic business unit, restructuring following a corporate merger, and moving from conventional supervision-led departments to self-directed work teams on an organization-wide basis Examples of lower impact changes included streamlining an accounts payable process, improving on-time delivery from vendors, and outsourcing select product assemblies Measures Main study variables Because selectivity and focus can be a valid alternative to comprehensiveness for obtaining perspective (Pettigrew et al., 2001), the change management literature was reviewed to derive a focused set of factors and measures to reflect Lewin’s (1947) three phases The review focused particularly on the change models of Nadler and Tushman (1980), Tichy (1983), Burke and Litwin (1992) and Kotter (1996) due to their prominence in both academic and practical circles While the need to satisfy thresholds of construct validity was taken into account, the primary intent was to develop a working representation of Lewin’s framework that supported the study’s objectives The factors distilled from the literature review were: problem analysis, action planning, skill development, feedback, and management control Explanation of these factors and their linkage to Lewin’s (1947) model appears below Unfreezing: problem analysis and action planning Change initially requires destabilizing the equilibrium between forces that drive and restrain existing behavior (Lewin, 1947), and is motivated by disconfirming extant expectations and redefining cognitive boundaries of the organization’s environment (Schein, 1996) Common destabilizing mechanisms in many prominent change management models relate to setting goals and planning actions necessary to achieve a desired future state Nadler and Tushman (1980), Tichy (1983), and Burke and Litwin (1992) identified the development of change-related goals and objectives as an early stage activity that required analysis and assessment of the organization’s relationship to its environment Kotter (1996) emphasized creating an early sense of urgency and developing a vision and strategy for directional purposes Action plans enable organizations to enact strategies that provide for better congruence with the environment (Nadler and Tushman, 1980), and for revising work during the process of change (Tichy, 1983) Because various stages or phases that distinguish change processes are defined by groups of activities or events aimed at similar goals (Garvin, 1998), the questionnaire items developed to operationalize Lewin’s (1947) three phases were designed to characterize actions associated with each phase A three-item scale was developed to reflect use of problem analysis activities; a two-item scale reflected use of action planning activities The response scale for this and other change process measures was designed to capture intensity of activity use of where ‘‘1’’ represented low use (low usage intensity) and ‘‘5’’ represented systematic use (high usage intensity) The Appendix includes all items used in this study as well as internal reliability coefficients for each factor Movement: skill development Once destabilization has taken place, driving forces move the organization towards an improved state (Lewin, 1947; Zand and Sorenson, 1975) Driving forces manifest in modified behavior (Burnes, 2004), since the nature of behavior significantly influences organizational performance (Porras and Hoffer, 1986) In many change management models, movement-related driving factors have been expressed as assessing task or work related aspects of behavior (e.g., Nadler and Tushman, 1980; Tichy, 1983), and developing and delivering new skills and capabilities as needed (Burke and Litwin, 1992) Although training programs constitute one means for developing new skills and capabilities (Goldstein, 1993), other approaches are possible including vicarious mechanisms (Bandura, 1986), trial and error (Schein, 1996), or market purchase (Kogut and Zander, 1992) Skill development was measured using a three-item scale that reflected the extent to which skills and capabilities were assessed and developed in a timely fashion to support the change effort Refreezing: feedback and management control As the organization approaches a desirable future state, new behavior requires reinforcement to stabilize the organization at improved performance levels and to avoid regression to previous patterns of action (Lewin, 1947) Refreezing activities provide confirmatory feedback that performance is effective, and may come from measurements, comments from others, and social comparisons as well as from rewards (Schein, 1996; Zand and Sorenson, 1975) Two refreezing factors were distilled from review of the change management literature One factor related to feedback on individual and group performance Such feedback can be communicated through both formal and informal channels (Tichy, 1983) Feedback about successes generates credibility that drives change to systems, policies, and structure not yet aligned with the desired future state (Kotter, 1996) Reward systems provide feedback that promotes and reinforces desired behavior during change implementation (Burke and Litwin, 1992; Nadler and Tushman, 1980) Feedback was measured using a four-item scale that reflected the extent to which change-related feedback was provided via communication and reward activities during implementation A second refreezing factor consistent with the confirmatory theme related to management control Management control involves routine monitoring of performance and taking corrective action when a significant gap is perceived between actual and desired performance (Anthony, 1965; Green and Welsh, 1988; Simons, 1995) Monitoring of behavior and outcomes provides a sense of congruence indicative of a suitable state of Size, structure and change implementation 309 MRN 32,4 310 performance (Nadler and Tushman, 1980) Various indicators of performance may be monitored at both the organizational and individual levels (Burke and Litwin, 1992; Tushman and O’Reilly, 1997) Essentially, management control helps keep initiatives on track (Merchant, 1985) Management control was measured using a three-item scale that reflected the extent to which managers used information to assess implementation progress, and took action to correct progress of the change when necessary Implementation success Because most change management models specify relationships between change processes and outcomes, a factor related to implementation success was included In their study of Lewin’s (1947) model, Zand and Sorenson (1975) employed an outcomes measure labeled ‘‘Level of Success’’ composed of five self-rated items focused on financial success of an implemented change Since implementation success can be evaluated by multiple criteria, many of them non-financial (Burke and Litwin, 1992; Tushman and O’Reilly, 1997), this investigation opted for a multidimensional measure Similar to Miller’s (1997) approach, implementation success was measured using a four-item scale meant to reflect completion, achievement, and acceptability dimensions Responses were assigned using a Likert-like scale where a ‘‘1’’ represented little or no results to speak of and a ‘‘5’’ represented highly effective results Self-reported measures of performance are often noted as concerns in organizational research due to potential for common methods variance When measures related to two or more constructs are rated by a single individual, personal or social factors might influence the rating and create artifactual covariance due to rater error (Avolio et al., 1991; Kline et al., 2000) One method for assessing the extent of common methods variance among self-reported measures is factor analysis (Podsakoff and Organ, 1986) If a substantial amount of common methods variance exists, then only a small number of factors should emerge from the analysis and account for the majority of covariance between constructs Factor analysis using principle components extraction with Varimax rotation was conducted on the 19 items representing the six primary factors proposed for this study The rotated solution (Table I) produced six factors, with all items loading on the appropriate factor as hypothesized Cumulative variance extracted was 75.1 per cent Using guidelines suggested by Stevens (2002), for N ¼ 98 only factor loadings greater than 0.518 should be viewed as significant No items significantly crossloaded on other factors One item loaded marginally on the implementation success factor Given the consistency of the item’s content with the conceptual domain of the implementation success construct, it was kept as proposed Because six factors emerged from the factor analysis, all items loaded on their proposed factors, and a large amount of cumulative variance was extracted from the factor structure, it was concluded that common methods variance was not present to a degree significant enough to influence the validity of primary constructs employed in this investigation Internal reliability coefficients for the change process factors were also determined (see appendix) All factors exhibited strong internal reliability except for action planning, which fell slightly below the commonly cited 0.70 benchmark Given the strong factor analysis results noted previously, it was concluded that slight weakness in the action planning reliability value did not significantly impair validity of the measurement model Organization size A personnel-related measure of size was used Respondents estimated the number of individuals employed by their organizations according to five categories (1 ¼ to 50 employees; ¼ 50-100; ¼ 100-500; ¼ 500-100; ¼ more than 1,000) To provide a categorical backdrop for analysis of the hypothesized differences between small and large organizations, responses were split into two general Analysis1 Analysis2 Analysis3 Actionplan1 Actionplan2 Skill development Skill development Skill development Feedback1 Feedback2 Feedback3 Feedback4 Mgtcontrol1 Mgtcontrol2 Mgtcontrol3 Impsuccess1 Impsuccess2 Impsuccess3 Impsuccess4 0.869 0.826 0.826 0.645 0.899 0.804 0.833 0.814 Size, structure and change implementation 311 0.582 0.844 0.842 0.720 0.853 0.720 0.688 0.524 0.845 0.783 Note: Cumulative variance extracted ¼ 75.1% groups Organizations were categorized as ‘‘small’’ if a questionnaire response of through was given, implying that the organization employed 500 or less The organization was categorized as ‘‘large’’ if a response of or was given, implying that the organization employed 500 or more A 500 employee threshold is commonly used for defining small organizations (e.g National Institute of Standards and Technology, 2007; US Small Business Administration, 2006) The categorization process divided the sample pool into 44 small organization respondents and 54 large organization respondents Context and control variables Percent completion To capture and control for the temporal nature of change process, we employed a self-rated measure of the extent to which the reference change had been implemented similar to those used by Miller (1997) and others The respondents were asked to estimate the reference change’s percentage towards completion (1 ¼ implementation not yet begun; ¼ 75-100 per cent implemented) Change Scope Scope of a change might also influence the choice of a particular change process factor as well as the potential impact on organizational outcomes (Haveman, 1993) Changes with a broader scope might be more difficult to implement or be more influential on organizational outcomes when compared to narrow, incremental changes (Hannan and Freeman, 1984; Nadler and Tushman, 1989) Respondents were asked to estimate the percentage of the organization that would be affected once the change was implemented (1 ¼ 0-20 per cent ¼ 80-100 per cent) Descriptive statistics and bivariate correlations for all variables used in this study appear in Table II Results To evaluate general differences between change processes employed by organizations of different size, multivariate analysis of variance (MANOVA) was conducted using the Table I Factor analysis (Factor loadings less than 518 suppressed) MRN 32,4 Skill Mean development Size 1.55 0.500 Complete 3.30 1.186 Impact 3.13 1.423 Analysis 2.58 0.835 312 Action plan 2.51 0.886 Skill development 2.71 0.937 Feedback 2.12 0.824 Mgt control 2.55 0.932 Table II 0.938 Descriptive statistics and Imp success 2.21 bivariate correlations of Notes: *p < 0.05; **p < 0.01 study variables 0.09 À0.10 À0.13 0.11 0.13 0.18 0.19 0.11 0.01 0.09 0.07 0.16 À0.05 0.11 0.31** 0.11 0.24* 0.12 0.29** 0.41** 0.54** 0.22* 0.24* 0.12 0.29** 0.40** 0.52** 0.50** 0.21* 0.35** À0.06 0.38** 0.44** 0.54** 0.63** 0.64** study’s change process measures as dependent variables, and the categorical variable separating small organizations from large organizations as a fixed factor independent variable Results indicated significant differences between the small and large organization groups (Wilks’ Lambda ¼ 0.874, F ¼ 2.195, p ¼ 0.050) Univariate ANOVA results in Table III indicated that the mean of the refreezing factor related to management control was significantly lower for small organizations (p ¼ 0.028) The mean of the other refreezing factor related to feedback was also lower for small organizations but not significant ( p ¼ 0.274) Generally, these findings support lower use of refreezing-related change process factors by small organizations as proposed by H1 The mean of the implementation success factor was also found significantly lower for small organizations ( p ¼ 0.037) This result supports the notion that small organizations generally achieve lower levels of success when implementing change as proposed by H2 To complement the quantitative analysis, profiles of small and large organization change process factors appear in Figure The visual nature of graphical profiles can add depth to analysis of change dynamics (Ford and Greer, 2006) The top graph arranges the factors in Lewin’s (1947) general sequence so that the change processes of small and large organizations can be viewed holistically The bottom graph rearranges the factors so that levels of use in small and large organizations can be compared Table III Means and main effects of organizational size N Problem analysis Action planning Skill development Feedback Mgt control Implementation success % complete Impact Note: aOne way ANOVA Small Large Diff Fa p-value 44 2.70 2.41 2.63 2.02 2.32 1.99 3.19 3.28 54 2.48 2.60 2.77 2.20 2.73 2.39 3.39 3.00 0.22 À0.19 À0.14 À0.18 À0.41 À0.40 À0.20 0.28 1.684 1.148 0.531 1.120 4.959 4.478 0.737 0.919 0.198 0.287 0.468 0.274 0.028 0.037 0.393 0.340 Size, structure and change implementation 313 Figure Change process profile comparisons side-by-side From these graphs, note the generally lower usage intensity of change process factors employed in small organizations These differences appear to widen as implementation moves through the refreezing phase The visual perspective adds texture to the statistical analysis, and lends further confirmation to this investigation’s hypotheses Discussion Findings from this study cast some doubt on the notion that small organizations are generally more adaptable than large organizations – at least in the context of implementing planned change A common view is that small organizations should be proficient at change due to lack of structure, which should reduce inertia (Hannan and Freeman, 1984) and facilitate unfreezing and movement However, results here indicated no significant difference in unfreezing and movement levels between small and large organizations Plausibly, structural inertia in large organizations is offset by expertise, slack and market power flowing from differentiated structure and hierarchy (Briscoe, 2007; Haveman, 1993) that helps large firms focus on the unfreezing and movement tasks at hand It is the refreezing stage where general size-related differences in change processes can be observed Lack of control structure in small organizations may reduce capacity MRN 32,4 314 for obtaining confirmatory feedback necessary for refreezing at new and improved levels The hierarchical structure of large organizations, on the other hand, is built for control (Child, 1972) This study’s finding that small organizations generally exhibit lower levels of refreezing is consistent with the ‘‘We’re great starters but terrible finishers’’ lament by managers in many small firms Moreover, the lower observed levels of implementation success in small organizations support scattered empirical findings suggesting that smaller size is not strongly related to change outcomes (e.g Dean and Snell, 1991; Haveman, 1993; Kelly and Amburgey, 1991) Empirical evidence suggesting that organizational size may facilitate, rather than hinder, successful planned change implementation constitutes the primary contribution of this study From a methodological perspective, this research supports viewpoints about the value of empirical designs in change process research (e.g Ford and Greer, 2006) The cross sectional nature of this investigation fostered insight into a number of change process research issues identified by Pettigrew et al (2001) that would have been difficult to obtain from longitudinal methods alone, including the identification of patterns in the process of change, linking change capacity and action to organizational performance, and evaluating the strength of relationships between process patterns and outcomes While often derided for their static nature, carefully considered empirical designs can complement longitudinal methods to enrich the stream of inquiry related to change process research One caveat in interpreting the findings of this study concerns a possible selectivity or survivor bias that accompanies analysis of changes in progress Because of low levels of inertia, small organizations may attempt change more often than large organizations (Glen and Hambrick, 1995) On average, the typical change implemented in small organizations may exhibit low levels of change process activities and subdued implementation outcomes But perhaps small organizations make up for ‘‘lower quality’’ initiatives by increasing the sheer number of initiatives in play Future work that considers a quality-versus-quantity perspective when comparing small and large organizations with respect to change could yield interesting insight The nature of the change being implemented may also influence results and suggests further opportunity to extend this research This study focused on processes linked to changes that were planned or intentional in nature But changes can also be emergent in character (Burnes, 1996) and well underway before dominant coalitions realize their significance (e.g Grove, 1996) Lacking inertial structure, small organization environments seem conducive to such bottom-up, unplanned initiatives Studying unintentional change processes presents some data acquisition challenges for researchers since by definition most organizational members should lack awareness that unplanned changes are underway Nonetheless, implementation processes might significantly differ depending on whether changes being implemented are of the unintended or intended variety Organizations can also engage in change initiatives that are continuous in nature (Brown and Eisenhardt, 1997; Huy, 2001) Continuous changes may be associated with lower levels of refreezing than discontinuous change since less stabilization at new levels is likely to occur at a particular point in time Future work might examine the extent to which continuous changes relate to organization size and the consequences of such relationships on change processes and outcomes This study was subject to some limitations While the cross sectional design improves upon Haveman’s (1993) single industry study, a broader sample containing more observations would be desirable in future studies to improve statistical power and to increase generalizability The change process factors selected for this study were limited to a few widely accepted ones Additional factors would further saturate the theoretical domain of Lewin’s (1947) framework and strengthen the analytical fabric Although there has been some debate over the extent to which self-reported measures result in artifactual covariance (e.g Spector, 1987; Williams et al., 1989), use of selfrated measures invites concern about common methods variance and attribution bias Although analysis suggested that common methods variance did not weigh heavily on construct validity, procedural approaches, such as collecting data on independent and dependent variables from different individuals, offer preventive alternatives for reducing concerns about common methods variance in future studies (Podsakoff and Organ, 1986) The gauge of organizational size in this study was restricted to a categorical measure of employee-related size, using a common empirical threshold of 500 employees for separating small from large organizations (e.g National Institute of Standards and Technology, 2007; US Small Business Administration, 2006) This threshold is not universally accepted among researchers, however, and interpretation of what constitutes a small organization varies widely across studies (e.g Glen and Hambrick, 1995; Human and Provan, 1997; Verdu-Jover et al., 2006) In addition to personnel available, there are other aspects of organizational size including those related to physical capacity, inputs and outputs, and discretionary resources (Kimberly, 1976) Future work should judge the measures of organizational size most appropriate for the change process study at hand A practical implication of this study is that managers of large organizations should carefully consider the consequences of restructuring efforts aimed at emulating flatter designs of many small organizations Although mechanistic organizations are thought to be less fluid and adaptable (Burns and Stalker, 1961), a move away from hierarchy may reduce organizational capacity for managing change Managers of small organizations, on the other hand, may improve change management capability by adding structure Recent empirical research (e.g Sine et al., 2006) supports such a premise Indeed, findings from this study extend the notion of enabling bureaucracies (Adler and Borys, 1996) into the domain of change management Conclusions Small size is often viewed as advantageous for adaptation Lack of structure in small organizations is thought to reduce inertia and facilitate mobility When change is of the planned variety, however, smallness may hinder rather than help the implementation process General deficiency in formal controls reduces capacity for locking down behavior at improved levels as implementation progresses Instead, small organizations may drift during implementation with reduced prospects for effective closure Conversely, the hierarchical structure of large organizations facilitates command of the refreezing process Control systems guide closure of performance gaps necessary for effective outcomes, positioning large organizations to realize relatively high levels of implementation success from their planned change initiatives Improving our understanding of organizational change requires research questions and methods that break from historical paradigms (Pettigrew et al., 2001) This study offers an uncommon empirical glimpse into processes of change in the context of organizational size Hopefully, it will provoke further conversation on the role of size and structure in the management of change Size, structure and change implementation 315 MRN 32,4 316 References Adler, P.S and Borys, B (1996), ‘‘Two types of bureaucracy: enabling and coercive’’, Administrative Science Quarterly, Vol 41, pp 61-89 Anthony, R.N (1965), Planning and Control Systems: A Framework for Analysis, Division of Research, Graduate School of Business Administration, Harvard University, Boston, MA Avolio, B.J., Yammarino, F.J and Bass, B.M (1991), ‘‘Identifying common methods variance with data collected from a single source: an unresolved sticky issue’’, Journal of Management, Vol 17, pp 571-87 Bandura, A (1986), Social Foundations of Thought and Action: A Social Cognitive Theory, Prentice Hall, Englewood Cliffs, NJ Bartunek, J.M and Moch, M.K (1987), ‘‘First order, second order, and third order change and organizational development interventions: a cognitive approach’’, Journal of Applied Behavioral Science, Vol 23, pp 483-500 Boone, C, de Brabander, B and Hellman, J (2000), ‘‘CEO locus of control and small firm performance’’, Organization Studies, Vol 21, pp 641-46 Bossidy, L and Charan, R (2002), Execution: the Discipline of Getting Things Done, Crown Business Books, New York, NY Briscoe, F (2007), ‘‘From iron cage to iron shield? How bureaucracy enables temporal flexibility for professional service workers’’, Organization Science, Vol 18, pp 297-314 Brown, S.L and Eisenhardt, K.M (1997), ‘‘The art of continuous change: Liking complexity theory and time pace evolution in relentlessly shifting organizations’’, Administrative Science Quarterly, Vol 42, pp 1-34 Burke, W.W (1995), ‘‘Diagnostic models for organization development’’, in Howard, A., and Associates, (Eds), Diagnosis for Organizational Change, Guilford Press, New York, NY pp 53-84 Burke, W.W and Litwin, G.H (1992), ‘‘A causal model of organizational performance and change’’, Journal of Management, Vol 18, pp 523-45 Burnes, B (1996), ‘‘No such thing as a ‘one best way’ to manage organizational change’’, Management Decision, Vol 34 No 10, pp 11-18 Burnes, B (2004), ‘‘Kurt Lewin and the planned approach to change: a reappraisal’’, Journal of Management Studies, Vol 41, pp 977-1002 Burnes, B (2005), ‘‘Complexity theories and organizational change’’, International Journal of Management Reviews, Vol No 2, pp 73-90 Burns, T and Stalker, G.M (1961), The management of innovation, Tavistock Publications, London Cardinal, L.B., Sitkin, S.B and Long, C.P (2004), ‘‘Balancing and rebalancing in the creation and evolution of organizational control’’, Organization Science, Vol 15, pp 411-31 Charan, R and Colvin, G (1999), ‘‘Why CEOs fail’’, Fortune, Vol 139 No 2, pp 68-78 Child, J (1972), ‘‘Organization structure and strategies of control: a replication of the Aston study’’, Administrative Science Quarterly, Vol 17, pp 163-77 Child, J (1973), ‘‘Predicting and understanding organizational structure’’, Administrative Science Quarterly, Vol 18, pp 168-85 Davila, T (2005), ‘‘An exploratory study in the emergence of management control systems: Formalizing human resources in small growing firms’’, Accounting, Organizations and Society, Vol 30, pp 223-48 Dawson, P (1994), Organizational Change: a Processual Approach, Paul Chapman Publishing, London Dean, J.W., Jr and Snell, S.A (1991), ‘‘Integrated manufacturing and job design: Moderating effects of organizational inertia’’, Academy of Management Journal, Vol 34, pp 776-804 Dickens, L and Watkins, K (1999), ‘‘Action research: rethinking Lewin’’, Management Learning, Vol 30 No 2, pp 127-40 Elrod, P.D II and Tippett, D.D (2002), ‘‘The death valley of change’’, Journal of Organizational Change Management, Vol 15 No 3, pp 273-91 Ford, M.W and Greer, B.M (2005), ‘‘The relationship between management control system usage and planned change achievement: an exploratory study’’, Journal of Change Management, Vol No 1, pp 29-46 Ford, M.W and Greer, B.M (2006), ‘‘Profiling change: an empirical study of change process patterns’’, Journal of Applied Behavioral Science, Vol 42, pp 420-46 Fredrickson, J.W (1986), ‘‘The strategic decision process and organizational structure’’, Academy of Management Review, Vol 11, pp 280-97 Garvin, D.A (1998), ‘‘The processes of organization and management’’, Sloan Management Review, Vol 39 No 4, pp 33-50 Gilbert, C.G (2005), ‘‘Unbundling the structure of inertia: resource versus routine rigidity’’, Academy of Management Journal, Vol 48, pp 741-83 Glen, M and Hambrick, D.C (1995), ‘‘Speed, stealth, and selective attack: how small firms differ from large firms in competitive behavior’’, Academy of Management Journal, Vol 38, pp 453-82 Goldstein, I.L (1993), Training in Organizations: Needs Assessment, Development and Evaluation, Brooks, Monterey, CA Goodman, P.S and Dean, J.W., Jr (1982), ‘‘Creating long-term organizational change’’, in Goodman, P.S (Ed.), Change in Organizations, Jossey-Bass, San Francisco, CA, pp 226-79 Green, S.G and Welsh, M.A (1988), ‘‘Cybernetics and dependence: reframing the control concept’’, Academy of Management Review, Vol 13, pp 287-301 Grinyer, P.H and Yasai-Ardekani, M (1981), ‘‘Strategy, structure, size and bureaucracy’’, Academy of Management Journal, Vol 24, pp 471-86 Grove, A.S (1996), Only the Paranoid Survive, Doubleday, New York, NY Hannan, M.T and Freeman, J.H (1977), ‘‘The population ecology of organizations’’, American Journal of Sociology, Vol 82, pp 929-64 Hannan, M.T and Freeman, J.H (1984), ‘‘Structural inertia and organizational change’’, American Sociological Review, Vol 49, pp 149-64 Hatch, M.J (1997), Organization Theory: Modern, Symbolic and Postmodern Perspectives, Oxford University Press, Oxford Haveman, H.A (1993), ‘‘Organizational size and change: diversification in the savings and loan industry after deregulation’’, Administrative Science Quarterly, Vol 38, pp 20-50 Human, S.E and Provan, K.G (1997), ‘‘An emergent theory of structure and outcomes in small firm strategic manufacturing networks’’, Academy of Management Journal, Vol 40, pp 368-403 Huy, Q.N (2001), ‘‘Time, temporal capability, and planned change’’, Academy of Management Review, Vol 26, pp 601-23 Kanter, R.M., Stein, B and Jick, T (1992), The Challenge of Change, The Free Press, New York, NY Kelly, D and Amburgey, T.L (1991), ‘‘Organizational inertia and momentum: a dynamic model of strategic change’’, Academy of Management Journal, Vol 34, pp 591-612 Size, structure and change implementation 317 MRN 32,4 318 Kimberly, J.R (1976), ‘‘Organizational size and the structuralist perspective: a review, critique, and proposal’’, Administrative Science Quarterly, Vol 21, pp 571-97 Kline, T.J.B., Sulsky, L.M and Rever-Moriyama, S.D (2000), ‘‘Common methods variance and specification errors: a practical approach to detection’’, Journal of Psychology, Vol 134, pp 401-21 Kogut, B and Zander, U (1992), ‘‘Knowledge of the firm, combinative capabilities, and the replication of technology’’, Organization Science, Vol 3, pp 383-97 Kotey, B and Slade, P (2005), ‘‘Formal human resource practices in small growing firms’’, Journal of Small Business Management, Vol 43 No 1, pp 16-40 Kotter, J.P (1996), Leading change, Harvard Business School Press, Boston, MA Kotter, J.P and Schleisinger, L.A (1979), ‘‘Choosing strategies for change’’, Harvard Business Review, Vol 57 No 2, pp 106-14 Lawler, P.F (1947), ‘‘A note on control in small businesses’’, Harvard Business Review, Vol 25 No 4, pp 521-26 Lewin, K (1947), ‘‘Frontiers in group dynamics: concepts, method and reality in social sciences, social equilibria and social change’’, Human Relations, Vol 1, pp 5-42 Lippit, R., Watson, J and Westley, B (1958), The Dynamics of Planned Change, Harcourt Brace, New York, NY Merchant, K.A (1985), Control in Business Organizations, Pitman, Marshfield, MA Miles, R.H and Petty, M.M (1977), ‘‘Leader effectiveness in small bureaucracies’’, Academy of Management Journal, Vol 20 No 2, pp 238-50 Miller, S (1997), ‘‘Implementing strategic decisions: four key success factors’’, Organization Studies, Vol 18, pp 577-602 Nadler, D.A and Tushman, M (1980), ‘‘A model for diagnosing organizational behavior: applying the congruence perspective’’, Organizational Dynamics, Vol No 2, pp 35-51 Nadler, D.A and Tushman, M (1989), ‘‘Organizational frame bending: principles for managing reorientation’’, Academy of Management Executive, Vol No 3, pp 194-204 National Institute of Standards and Technology (2007), Criteria for Performance Excellence, National Institute of Standards and Technology, Gaithersburg, MD Nelson, R and Winter, S (1982), An Evolutionary Theory of Economic Change, Harvard University Press, Cambridge, MA O’Reilly, C (1989), ‘‘Corporations, culture, and commitment: motivation and social control in organizations’’, California Management Review, Vol 31 No 4, pp 9-25 Ouchi, W.G (1980), ‘‘Markets, bureaucracies, and clans’’, Administrative Science Quarterly, Vol 25, pp 129-41 Pettigrew, A.M., Woodman, R.W and Cameron, K.S (2001), ‘‘Studying organizational change and development: challenges for future research’’, Academy of Management Journal, Vol 44, pp 697-713 Pfeffer, J and Salancik, G (1978), The External Control of Organizations, Harper and Row, New York, NY Podsakoff, P.M and Organ, D.W (1986), ‘‘Self reports in organizational research: problems and prospects’’, Journal of Management, Vol 12, pp 531-44 Porras, J.I and Hoffer, S.J (1986), ‘‘Common behavior changes in successful organization development’’, Journal of Applied Behavioral Science, Vol 22, pp 477-94 Robertson, P., Roberts, D and Porras, J.L (1993), ‘‘Dynamics of planned organizational change: Assessing empirical support for a theoretical model’’, Academy of Management Journal, Vol 36, pp 619-34 Schein, E.H (1996), ‘‘Kurt Lewin’s change theory in the field and in the classroom: notes towards a model of management learning’’, Systems Practice, Vol No 1, pp 27-47 Simons, R (1995), Levers of control, Harvard Business School Press, Boston, MA Sine, W.D., Mitsuhashi, H and Kirsch, D.A (2006), ‘‘Revisting burns and stalker: formal structure and new venture performance in emerging economic sectors’’, Academy of Management Journal, Vol 49, pp 121-32 Spector, P.E (1987), ‘‘Method variance as an artifact in self-report affect and perceptions at work: myth or significant problem?’’, Journal of Applied Psychology, Vol 72, pp 438-44 Stensaker, I., Falkenberg, J., Meyer, C.B and Haueng, A.C (2002), ‘‘Excessive change: coping mechanisms and consequences’’, Organizational Dynamics, Vol 31 No 3, pp 296-312 Stevens, J.P (2002), Applied Multivariate Statistics for the Social Sciences, 4th ed., Lawrence Erlbaum Associates, Inc., Mahwah, NJ Tannenbaum, R (1971), ‘‘Organizational change has to come through individual change’’, Innovation, Vol 23, pp 36-43 Tichy, N.M (1983), ‘‘Managing Strategic Change, Wiley, New York, NY Tushman, M.L and O’Reilly, C.A III (1997), Winning Through Innovation: A Practical Guide to Leading Organizational Change and Renewal, Harvard Business School Press, Boston, MA US Small Business Administration (2006), Table of Small Business Size Standards, US Small Business Administration, Washington, DC Van de Ven, A.H and Poole, M.S (1995), ‘‘Explaining development and change in organizations’’, Academy of Management Review, Vol 20, pp 510-40 Verdu-Jover, A.J., Llorens-Montes, F.J and Garcia-Morales, V.J (2006), ‘‘Environment-flexibility coalignment and performance: an analysis in large versus small firms’’, Journal of Small Business Management, Vol 44, pp 334-49 Williams, L.S., Cote, J.A and Buckley, M.R (1989), ‘‘Lack of method variance in self-reported affect and perceptions at work: reality or artifact?’’, Journal of Applied Psychology, Vol 74, pp 462-68 Zand, D.E and Sorenson, R.E (1975), ‘‘Theory of change and the effective use of management science’’, Administrative Science Quarterly, Vol 20, pp 532-45 Further reading Grimes, A.J (1978), ‘‘Authority, power, influence and social control: a theoretical synthesis’’, Academy of Management Review, Vol 3, pp 724-35 Jansen, K.J (2004), ‘‘From persistence to pursuit: a longitudinal examination of momentum during early stages of strategic change’’, Organization Science, Vol 15, pp 276-94 Van de Ven and Huber, G.P (1990), ‘‘Longitudinal field research methods for studying processes of organizational change’’, Organization Science, Vol 1, pp 213-19 Appendix Measurement scales Change process variables (alpha) Problem analysis (0.83) Was fact-based data used to identify the need for change? Did organizational leaders evaluate the current condition (financial, competition, labor, etc.) prior to setting goals for the change? Was the gap between ‘‘where we are’’ and ‘‘where we want to be’’ determined? Size, structure and change implementation 319 MRN 32,4 320 *For each item, ¼ infrequent use; ¼ systematic use Action planning (0.66) Was an action plan developed for making the change? Was a timeline for successful completion established? *For each item, ¼ infrequent use; ¼ systematic use Skill development (0.84) Did organization leaders identify important skills and capabilities needed to make the change? Did the organization develop necessary skills and capabilities through training, mentoring, outside acquisition or other means? Did the organization make sure that needed skills and capabilities were in place in time to complete the changes? *For each item, ¼ infrequent use; ¼ systematic use Feedback (0.83) Were employees kept informed about the ongoing status of the change process? How well were successes of the change effort communicated? Were successful change results shared in a timely fashion? Were employees rewarded for working to support the change effort? *For each item, ¼ infrequent use; ¼ systematic use Management control (0.77) Was information about the progress of the change obtained? Was information effectively used to enable corrective action when necessary? How effective were the actions taken to correct the progress of the change? *For each item, ¼ infrequent use; ¼ systematic use Implementation success (0.85) Did the change have a positive impact on business results? To what extent has the change resulted in expected behaviors? Overall, how satisfied were you with the changes? Overall, how satisfied were you with how implementation was done? a For each item, ¼ little or no results to speak of; ¼ highly effective results Context variables % Complete Overall, how far along is the change towards completion? (1 – implementation has not begun; ¼ 75-100% implemented Change impact When the change is fully implemented, how much of the organization will be significantly impacted by the change? (1 ¼ 0-20%; ¼ 80-100%) Organization size Approximately how many individuals does your organization employ? (1 ¼ 0-50; ¼ 50-100; ¼ 100-500; ¼ 500-100; ¼ More than 1,000) About the author Matthew W Ford is associate professor of management at Northern Kentucky University He earned his PhD from the University of Cincinnati His research interests include organizational self-assessment, quality management, financial market awareness and decision making, and the implementation of change He can be contacted at: fordmw@nku.edu To purchase reprints of this article please e-mail: reprints@emeraldinsight.com Or visit our web site for further details: www.emeraldinsight.com/reprints Reproduced with permission of the copyright owner Further reproduction prohibited without permission  ... complement the quantitative analysis, profiles of small and large organization change process factors appear in Figure The visual nature of graphical profiles can add depth to analysis of change dynamics... graph rearranges the factors so that levels of use in small and large organizations can be compared Table III Means and main effects of organizational size N Problem analysis Action planning Skill... Brabander, B and Hellman, J (2000), ‘‘CEO locus of control and small firm performance’’, Organization Studies, Vol 21, pp 641-46 Bossidy, L and Charan, R (2002), Execution: the Discipline of Getting