Shaking Fruit out of the Tree: Temporal Effects and Life Cycle in Organizational Change Research

http://jab.sagepub.com/Behavioral Science

The Journal of Applied

http://jab.sagepub.com/content/48/3/342The online version of this article can be found at:

DOI: 10.1177/0021886312439098

2012 2012 48: 342 originally published online 9 MarchJournal of Applied Behavioral Science

Gavin M. SchwarzOrganizational Change Research

Shaking Fruit out of the Tree : Temporal Effects and Life Cycle in

Published by:

http://www.sagepublications.com

On behalf of:

NTL Institute

can be found at:The Journal of Applied Behavioral ScienceAdditional services and information for

http://jab.sagepub.com/cgi/alertsEmail Alerts:

http://jab.sagepub.com/subscriptionsSubscriptions:

http://www.sagepub.com/journalsReprints.navReprints:

http://www.sagepub.com/journalsPermissions.navPermissions:

http://jab.sagepub.com/content/48/3/342.refs.htmlCitations:

at University of New South Wales on July 25, 2012jab.sagepub.comDownloaded from

http://jab.sagepub.com/

http://jab.sagepub.com/content/48/3/342

http://www.sagepublications.com

http://www.ntl.org

http://jab.sagepub.com/cgi/alerts

http://jab.sagepub.com/subscriptions

http://www.sagepub.com/journalsReprints.nav

http://www.sagepub.com/journalsPermissions.nav

http://jab.sagepub.com/content/48/3/342.refs.html


What is This?

- Mar 9, 2012OnlineFirst Version of Record

- Jul 23, 2012Version of Record >>


http://jab.sagepub.com/content/48/3/342.full.pdf

http://jab.sagepub.com/content/early/2012/03/07/0021886312439098.full.pdf

http://online.sagepub.com/site/sphelp/vorhelp.xhtml


The Journal of Applied Behavioral Science48(3) 342 –379

© 2012 NTL InstituteReprints and permission: http://www. sagepub.com/journalsPermissions.nav

DOI: 10.1177/0021886312439098http://jabs.sagepub.com

439098 JAB48310.1177/0021886312439098SchwarzThe Journal of Applied Behavioral Science

1The University of New South Wales, Sydney, New South Wales, Australia

Corresponding Author:Gavin M. Schwarz, School of Management, Australian School of Business, The University of New South Wales, Sydney, New South Wales 2052, Australia Email: [email protected]

Shaking Fruit out of the Tree: Temporal Effects and Life Cycle in Organizational Change Research

Gavin M. Schwarz1

Abstract

This article moves beyond descriptives of how we “do” change in a test of whether there is an empirical basis for knowing where in its life cycle is organizational change research. Questioning typical assumptions about change, it indicates what progress in the field looks like by plotting the patterning of temporal effects and life cycle in articles published in eight journals between 1947 and 2008 (n = 473). Findings indicate that the publication of more on change has not equated with more developed knowledge. As a community, change researchers are overwhelmingly focused on the most conservative type of progress, resulting in research that replicates rather than extends or develops, which ranks fairly low on a knowledge development scale. This illusion of knowledge development is described and explained by researcher reliance on existing idea mobilization and on belief prisons. The article concludes with discussion of implications for research and publishing practice.

Keywords

organizational change, knowledge development, temporal effect

In 1963, Edmund Gettier published a short article about the conditions necessary for a person’s belief to become knowledge, presenting knowledge as “justified true belief.” He describes two cases in which a person has, for a given proposition P, validly



Schwarz 343

inferred from some other proposition which the person was justified in believing, but which was, in fact, false. Based on this interpretation, Gettier claimed that a person may have a belief without actually having knowledge. Earlier, in 1956, George Miller wrote about the limits of such information transmission. He argued that the span of absolute judgment and the span of immediate memory are imperfect, imposing limita-tions on the amount of information a person is able to receive, process, and remember. This knowledge limitation, he wrote, can only be resolved by chunking information into manageable sequences. Spawning intense debate, both articles highlighted restric-tions to the ways that knowledge is cultivated and progresses. With these lessons as its stimulus, this article explores how knowledge about change has developed in organi-zational change research by considering what progress in a field looks like.

Traditionally, guided by an interest in discovery, we have come to expect that knowledge in the social sciences develops along a typical trajectory: Knowledge grows as it is created, tested, and disseminated, before this rate of growth slowly declines as new or disruptive ideas are introduced. But is this assumption accurate for organizational change research? Put differently, is there an empirical basis for know-ing where organizational change research is in its life cycle? The value of asking this framing question is that it recognizes that we cannot fully appreciate the significance of a particular organizational or social variable without understanding how it got there. Given previous debate in the social sciences assuming paths of discovery and evolu-tion (Maguire, 1973; Maturana & Varela, 1987), the question prompts a philosophical judgment of whether representative organization research knowledge, in this case change research, can be plotted as a life cycle. This temporal focus on progress acknowledges Whitley’s (1984) assertion that despite its relevance, studies of researcher actions and beliefs rarely involve a comparison of historical periods. The ultimate contribution of the article, therefore, is to offer important theoretical guidance for what it means to research organizational change over time.

Progress, in the context of this article, relates to the flow of an idea as it moves from an individual, simple explanation to a more representative, shared meaning. Currently, while there is vigorous debate about change in organization studies, there is no unified or dominant stance to define progress in the field. In response, the specifics of what progress looks like—its types and patterning—will be fleshed out in the next section of the article. Practically, however, using Leydesdorff (2011), this outcome is identi-fied by how ideas are grouped together to become a more acceptable knowledge base. The research question queries if there is an identifiable cycle in this process for change research. The article assumes that fields are conceived as relatively well-bounded and distinct social organizations which control and direct the conduct of research, while accepting that there are multiple different and often contradictory opinions explaining how knowledge progresses. Recognizing the influence of this bias is important to what follows. Without conceding such an outlook, the article could end up debating what is knowledge or become a more typical, prescriptive account of the nature of publishing in the change field. Neither of these are of interest, as there are a plethora of such debates already available. Instead, in the context of progress, the focus of this current



344 The Journal of Applied Behavioral Science 48(3)

research is to contemplate whether, as change researchers we are shaking new fruit (i.e., developing ideas) out of the tree of knowledge (i.e., research process), or just dislodging its overripe fruit?

Testing the framing research question, the article is divided into four distinct parts. The first section provides the platform for evaluating this framing question and estab-lishing what progress looks like. The second and third sections detail the empirical test of the question in 473 articles on change published in eight representative journals over a six-decade period (1947-2008). The final section extends results.

The Tree of Knowledge in the Garden of ChangeGiven its breadth, there is a tendency in organizational research to assume that we “know change” (Schwarz & Huber, 2008; Woodman, 1989). To question this assump-tion, therefore, it is necessary to begin by grounding what is meant by these phenom-ena. The activity of changing is easily defined in the vernacular (“substitution of one thing for another; succession of one thing in place of another,” Oxford English Dictionary, 2009), just as change is clearly categorized in an organizational context (the fine-tuning or turnaround that modifies the organization and its parts, see reviews in French, Bell, & Zawacki, 2000). Knowledge is defined as a set of objectified and accepted beliefs, assumptions, and interpretations (Fuller, 1993), in assuming that local knowledge circulates and by doing so becomes universal. The prevailing view in organization theory is that knowledge on change is underpinned by a theory testing modus operandi, as models and propositional statements are refined and then reas-sembled into generalizable concepts. This normative outlook is broadly accepted yet heavily critiqued (see, Bartunek & Woodman, 2011; Chia & Holt, 2008). After all, Gettier’s knowledge hypothesis and Miller’s information limits proposition point to problems with the outcome of such an assumption. Without reflecting on the way we research—our tree of knowledge—any field is in danger of becoming isolated and marginalized. This possibility acts as a clarion call for this article.

Seeding the Garden: The Roots of the StudyChange is a fundamental, noticeable, and recurrent part of life. Consequently, it has become one of the grand comforts in organization theory. After all, plus ça change, plus c’est la même chose, the more things change, the more they stay the same. It is assumed that because we live in times of upheaval, organizations strive to continu-ously change and to manage its effects (Burke, 2008; Schwarz & Huber, 2008). This emphasis has seen a fascination with studying and exploring change. As a result, it is easy to assert that we do indeed know much about change, and several extensive compilations have been undertaken to consolidate or formalize this familiarity (start-ing with Bennis, Benne, & Chin, 1961). Previous annual reviews on change have variously identified and reviewed the “how” and “what” features of change. They variously evaluate change content and trends (Sashkin & Burke, 1987), categorize and



Schwarz 345

summarize change developments (Woodman, 1989), explore change introduction (Pasmore & Fagans, 1992), assess change themes (Armenakis & Bedeian, 1999), and consider change recipients’ reactions (Oreg, Vakola, & Armenakis, in press). Other reviews summarize change trends and or attempt to define the field (see, Alderfer, 1977; Faucheux, Amado, & Laurent, 1982; Friedlander & Brown, 1974; Weick & Quinn, 1999). Consequently, this article acknowledges that contemporary change research is rooted in already well-accepted and wide-ranging codified knowledge.

Community Garden: Cultivating Knowledge on Organization and on ChangeTypically, dialogue on knowledge in organization studies deals with how knowledge is created and organized by the flow of information. Interest usually is on themes to do with the way that tacit knowledge becomes created as explicit knowledge and how this knowledge is managed, dealing with its acquisition, conversion, distribution, interpretation, and representation. Knowledge creation is seen as a mechanism for facilitating this process and for dealing with information and decisions in an uncertain environment. For example, Nonaka (1994) presents this process as synergistic and embedded whereby knowledge is the creation of an upward trajectory in the search for consensus. This focus on knowledge creation and transfer has continuously been emphasized as a primary objective of organizational research. At the root of this belief is the hypothesis that knowledge always progresses—hence the chest beating when this is perceived as not so (see, Fuller, 1993; Maguire, 1973; Oswick, Fleming, & Hanlon, 2011).

Despite its pitfalls, such a growth objective is logical given the importance of knowledge in organization studies. It minimizes, however, the difficulties of dissemi-nating knowledge and the associated dissonance of research. At first glance, and con-textualizing this study, while organizational researchers regularly make claims about knowledge creation or extension, research on citation cycles and the metrics of research—typically used as markers to measure knowledge conversion patterns (Daft & Lewin, 2008)—suggests that the reality is far different. Knowledge production is usually highly structured and basic, generating a variety of pleas for more knowledge development (Gray & Cooper, 2010; Pfeffer, 1993). As Chia and Holt (2008) point out, this response to organizational knowledge creation is not unexpected given that it is based on the widespread approach whereby researchers assume that they need to provide an authoritative or compelling explanation of what they find. Given questions to do with why their research is distinctively valuable, individuals invariably draw on a corpus of schemata and generalizations that act as a constant frame of reference. Yet the knowledge represented by research is typically interrelated so that a researcher is forced to accept and transfer ideas and theories because others have done so. Researchers are often reluctant to challenge knowledge because the familiar is more comfortable than the unfamiliar, and there is not a strong history in organization the-ory of rejecting theory once it is in the public domain (Davis & Marquis, 2005). As a




result, knowledge development often takes a back seat to knowledge dependency. Using Lakatos’s (1970) assessment, it is asserted here that knowledge can be either progressing if it moves beyond this restriction and anticipates further growth, or degenerative, if its theoretical growth lags its empirical growth and its novelty wanes.

It is in this context that knowledge about organizational change is questioned. Change researchers regularly summarize the state of the field with grand statements on perceived opportunities for its development or risks of its inertia, based on an estab-lished understanding of what is organizational change. Yet despite common represen-tations of the concept, these statements are inconsistent. For instance, compare Pettigrew, Woodman, and Cameron’s (2001, p. 697) hopeful call to arms for a research program (“the field of organizational change is far from mature,”), with Greiner and Cummings’s (2004, p. 375) more critical account of the state of change and organiza-tion development (“today there are many troubling signs to suggest its possible demise”)and Woodman’s (2008, p. S36) more pragmatic summary (“we can introduce new wine, but some characteristics of the wine’s container are always there [i.e., the bottle is old].”). Faced with an infinite number of “facts” that have shaped what is cur-rently known about organizational change, one must wonder which one of these state-ments is accurate. More specifically, with this inconsistency as a backdrop, how exactly do change researchers convert established ideas, rules, procedures, and infor-mation into tangible outcomes? The framing question of this current research—of progress and life cycles—seeks to understand the accuracy of these varied knowledge assumptions by focusing on what change has been studied, and whether this conven-tion has resulted in progress in knowledge.

Developing Knowledge and Harvesting CyclesGiven this preceding debate, we can now return to the specifics of what exactly prog-ress in a research field looks like. As previously emphasized in the introduction, progress in the context of this article is defined as knowledge evolving and growing through interactions between new knowledge and prior, related knowledge—a devel-opmental knowledge flow (Schulz, 2003). It equates with a combination of what McKinley, Mone, and Moon (1999) delineate as the novelty, continuity, and scope of research as knowledge develops in depth and breadth. A knowledge flow represents the continuous growth in the importance of an idea characterized by its standardized acceptance and broad adoption through a process of testing, debating, and incorpora-tion by the research community. This outlook on the configuration of progress has typically been represented as part of a developmental cycle, such as in studies show-ing progress in teaching strategy (Lindgren & Bleicher, 2005), nanotechnology (Leydesdorff, 2011), and multinational corporations (Schulz, 2003).

In this context, debate about knowledge in organization studies has become preoc-cupied with philosophy of science discussions and the virtues of different styles of mapping knowledge (e.g., Bennis & O’Toole, 2005; Chia & Holt, 2008; Daft & Lewin, 2008; Pfeffer, 1993; Tushman & O’Reilly, 2007). These views variously juxtapose



Schwarz 347

progress as knowledge derived from a high degree of consensus or in seeking diversity (Colquitt & Zapata-Phelan, 2007), on developing unified paradigms or different (or no) paradigms (Pfeffer, 1993; van Maanen, 1995), on a sequence of historically related theories or a development of new theories (Kilduff, Tsai, & Hanke, 2006), and on the measurement of citation and cocitation rate differences (Tsai & Wu, 2010). These foci debate the logic, models, and epistemology of the guiding principles and systems of knowledge. There is, of course, also a rich history in the philosophy of science dis-cussing the growth of knowledge and of the roots of understanding, generated from Popper, Kuhn, Campbell, and others.

The resultant convention of progress as linear knowledge development, however, has been critiqued for being too “scientific” when it comes to the social sciences, and especially to organization studies (see, Bennis & O’Toole, 2005; Tushman & O’Reilly, 2007). The focus in this article, therefore, is less on this intrinsic debate about knowl-edge or knowledge processes and more on understanding progress in knowledge development about change. Regardless of whether the research community develops ideas scientifically within a definite, testable theoretical framework (Gross, Levitt, & Lewis, 1996; Watkins, 1970) or whether they do so by paradigm development and puzzle solving (Fuller, 1993), the end result of what progress represents for the com-munity in terms of a knowledge flow is agreed on: The process selected is inconse-quential as long as knowledge is progressing.

Building on this view, as Maturana and Varela (1987) explain, progress is ulti-mately about recognizing the phenomenon to be explained and then developing com-plementary explanations that the community builds on. At its core is the importance of community consensus. Although there are disagreements on how much consensus researchers should have, some shared core ideas or frameworks facilitate the collec-tive debate that helps define and then stabilize a field (Pfeffer, 1993; Tsai & Wu, 2010; van Maanen, 1995). In the sciences, Perrin (1988) shows this path in terms of how the overthrow of phlogiston theory and the birth of modern chemistry came about through a 20-year process of chemical experimentation and articulation within that commu-nity. Pollack (1997) illustrates the path in terms of how the practice of architecture developed through public debate and agreement between its community members.

The basic premise underpinning progress in a field, therefore, is that ideas in a com-munity eventually mature cyclically as they are grouped together and then given broader meaning by that community. In this context, it is proposed that there are three universal types of progress in knowledge development in a field that typify this process:

Type 1 (aggressive development) is progress in knowledge that can lead to the growth of new, fundamental assumptions or implications. This type is evo-lutionary and developmental, characterized by the forceful replacement of existing assumptions, such as how technology developments force behavior and lifestyle change. Given its foundation in normal science (Kuhn, 1970) and the idea that knowledge flows through the process of old ideas replaced




by new ones, Type 1 progress is the type most commonly associated with idea development and discovery.

Type 2 (neutral development) is progress in knowledge that can lead to the aban-donment of existing assumptions in favor of similar ones. This type is adap-tive and amalgamated, characterized by the overlay of like-for-like ideas, promoting the production of related knowledge, rather than the devaluation of the old. For instance, the history of research in children’s concept develop-ment shows how a child builds on and adds to past knowledge by recogniz-ing and adapting new knowledge and experiences, which result in the child knowing (or learning) how to do something (De Mey, 1982).

Type 3 (conservative development) is progress in knowledge that can lead to the strengthening of an existing assumption by providing evidence for it. This type is conformist and conservative, characterized by the replication of or reliance on existent assumptions, exemplified by theory borrowing (Whetten, Felin, & King, 2009). Such duplication or matching relies on the unmodified importation or use of fully formed ideas to explain a phenomenon, resulting in indistinct differences. This type results in two entities of the same class or category, such as when a piece of chalk or a bunch of grapes is broken into two. The resulting parts are not identical, but they belong to the same class as the original (Maturana & Varela, 1987).

Several attempts have previously been made to classify knowledge development in organization studies, with interest specifically focusing on a life cycle metaphor (Kimberly, 1979; Nonaka, 1994). The life cycle depicts how different types of prog-ress are modeled with an emphasis on how knowledge forms over time (rather than its exact sequence) as it becomes more articulated and formalized. The basic trajectory of the cycle is that all transformations are time-dependent processes of progression pos-tulated as a definite, singular, and irreversible sequence of phases from birth to decline or death. The cycle can be described in terms of the growth and decline of shared com-munity interests in certain ideas and problem solving. Typically, a life cycle in the organizational domain tends to assume the occurrence of sequential changes, referring to a pattern of generic, developmental processes that are encountered with age (Whetten, 1989). While recognizing the influence of this sequencing and its modeling, given the framing research question, for this article the life cycle characteristic of knowledge management and organizational learning literatures is adopted (Firestone & McElroy, 2004). These literatures are specifically focused on how knowledge is adapted, its sustainable development, effectiveness, and problem solving. This variant of the life cycle approach is more appropriate for this current research than the irre-versible maturation type stages model (e.g., Kimberly, 1979), which as Vasquez (1997) illustrates is not a good way of critiquing research programs.

In this context, the pattern of progress in the knowledge development cycle equates with (a) the identification of a common idea, (b) its mobilization as it is scrutinized, which involves testing and evaluating it, and (c) its diffusion in the community as it is



Schwarz 349

incorporated or rejected, before the cycle recommences. Assuming that “history mat-ters” (Pierson, 2000), the idea is that knowledge is formed and diffuses through a community over time based on what happened at an earlier point in time, and it is this cycle variant that the framing research question explores. A good pattern of progress is assumed to be a growing one, as it consistently moves through this cycle into the community. A poor or weak pattern is assumed to be a stagnant one whereby knowl-edge lags in the cycle and the idea is diminished or weakly dispersed into part of the community. As Walsh, Meyer, and Schoonhoven (2006) indicate for organization studies, and as Davis (2010) empirically confirms, selecting the wrong idea or con-tinuing to focus on the same subset of ideas can frustrate progress but does not neces-sarily stop its dissemination into a research community. Equally this point of view also suggests that the solution to a weak pattern of progress lies in the hands of the same community, made up of the decisions and choices of journal editors, conference con-tent, governing and accrediting bodies, and doctoral programs.

Understanding this knowledge life cycle is particularly relevant to organizational change research patterning given its multidisciplinary history, its broad coverage, and the plethora of different perspectives taken. This complexity has led to a convoluted picture of the field (Oreg et al., in press), and ultimately, its progress. Understanding the cycle is also useful because different forms of knowledge have the ability to induce both priming effects that limit learning or sustain established ideas, and growth effects that benefit information transfer or disrupt established ideas. That is, it is a confirmed means of plotting the type of progress a field adopts. Ultimately, the purpose of research is to create and develop knowledge informed by how its attributes are applied in a community over time. The review of six decades of change research that follows is an attempt to empirically identify what published organizational change research indicates in this regard. Is there an empirical basis for knowing where organizational change research is in its life cycle?

MethodSample and Approach

The data for this study were taken from six decades of articles (1947-2008) on orga-nizational change published in eight journals (n = 473): Academy of Management Journal (AMJ, n = 62), Academy of Management Review (AMR, n = 36), Administrative Science Quarterly (ASQ, n = 69), Human Relations (HR, n = 79), Journal of Applied Behavioral Science (JABS, n = 105), Journal of Management (JM, n = 34), Organization Science (OS, n = 61), and Strategic Management Journal (SMJ, n = 27). The selection of management specific journals was made with reference to Gomez-Mejia and Balkin’s (1992) quality of publication study and Johnson and Podsakoff’s (1994) journal influence ranking analysis. Given that this current study is primarily interested in research characterizing mainstream management journals, it selected a representative sample from this combination. Organization Science was added to the




listing given its Social Science Citation Index ranking and that it is an oft-cited source in the change literature. Each of these periodicals represent a different perspective on organization change, with some giving regular specialized focus on specific change themes (e.g., JABS) and others incorporating change as part of a more generic multi-disciplinary approach to organizational studies (e.g., AMJ).

The decision to focus on published articles as an indicator of progress was made on two common assumptions. First, organizational change research results in intellectual products in the form of journal articles (Schwarz & Huber, 2008). The principal con-sumers of the content of these products are the members of the research community. One intermediate market, and gatekeeper, in the flow of change ideas to the research community, is composed of journals. Second, the volume of research output and pub-lishing trends are indicators of life cycle (Abrahamson & Fairchild, 1999) and the rela-tive popularity of theories and themes (Colquitt & Zapata-Phelan, 2007). Researchers typically make sense of knowledge by integrating it into what we already know about a subject, measured by recording the ratio of publications appearing on specific topics in different journals.

The intent of the content analysis approach adopted was to offer representative coverage of organizational change in the journals, with articles being the unit of analy-sis. The 62-year date range reflects and acknowledges the extensive history of contem-porary organization change debate and its long-standing theoretical foundation in the applied behavioral sciences, beginning with Lewin (1947). This choice also acknowl-edges organizational change’s organization theory roots, which as Walsh et al. (2006) point out, only started to accelerate in the 1950s. Interestingly, no data were sourced for the 1950s in the selected set of journals (supporting Sashkin & Burke’s, 1987, find-ings). Although only two journals (HR, ASQ) were in existence then, the article search and cross-reference check revealed that no relevant articles were published at the time in this set of journals, as per the data collection procedure adopted.

Data, Themes, and ProceduresThe data for this study came from three triangulated steps to plot each of the parts of the framing research question.

First, to test the life cycle component of the question, given the considerable size of the organizational change literature, the sample comprised change articles published in each of the eight journals since their inception. This scope took into account the temporal limitations of previous annual reviews of change, recognizing the impor-tance of time in creating and disseminating knowledge (Olk & Griffith, 2004). It also acknowledges that the placement of paradigms is contingent on historical factors and publication outlet popularity (Starbuck, 2006). The journal coverage and six-decade spread mitigate against data limitations associated with inconsistent economic and social circumstances.

Second, to test the change research component of the question, the search for rele-vant articles was limited to research dealing specifically with organizational change



Schwarz 351

(as previously defined), rather than those that broadly dealt with change or changing entities. This step consisted of searching for variants of the term organizational change using Google Scholar’s exact phrase-matching search function. These terms included “organization and change,” “change management,” “renewal,” “transformation,” “adaptation,” “development,” and “evolution.” The decision to select this limited range of keywords was made given that an initial search for “change” articles in the business and social sciences domain yielded more than 200,000 articles, most of which were not relevant to the topic of the study. Furthermore, a review of a subset of the keywords listed in this initial search indicated the prevalence of these particular terms, rather than any specific phraseology. The selection of these terms also recognizes that the trend in organization studies research is for the grouping and refitting of a domi-nant set of keywords (Davis, 2010), suggesting the relevancy of this choice.

Third, to evaluate the patterning of change research and manage this set of articles for relevance and fit, the author and two trained research assistants read each article for title, abstract, and keywords. To be included in the sample, an article needed to be about organizational change—that is, having its primary focus or theorizing princi-pally about organizational change, and not simply featuring change. Many articles were discounted at this stage of coding. For example, Wu, Neubert, and Yi’s (2007) “Transformational Leadership, Cohesion Perceptions, and Employee Cynicism About Organizational Change” has change in its title, abstract, and as one of its keywords, yet change is a secondary, contextual feature in a discussion on transformational leader-ship, and the article was therefore discarded. Whereas other articles that appear at first glance to be out of this change context were included after consideration. For example, Huber’s (1991) “Organizational Learning: The Contributing Processes and Literatures” has added much to debate on learning, but is equally specific to how organizations learn to change, with “transformation” being a core construct. Discrepancies in opin-ion about inclusion or exclusion between the author and assistants were resolved through comparison and discussion. This stage of coding resulted in the sample of 473 articles, with an interrater agreement of 86%.

Having established an adequately reliable sample, all articles were then coded and categorized into a list of change themes by the author and one of the research assis-tants, following Bryman’s (2001) approach to data management (interrater agreement of 91%). This list captured the first step in the pattern of progress life cycle (i.e., iden-tification of the idea). Adopting a basic open coding approach, each article’s title, abstract, and keywords were first read for the central idea or primary issue to do with change. This initial reading of the article generated a list of 30 representative specific change themes incorporating a diverse set of thematic issues, listed in Table 1. Using Miner’s (1984) simple count and nomination technique for grouping and ordering organizational research themes, this set of specific themes was then labeled by adopt-ing the terms Burke (2008) uses to structure his book on change.

This set was subsequently cross-referenced with Burke, Lake, and Paine’s (2009) reader to generate five overarching change themes (Table 1): (a) theoretical foun-dations, made up of articles encompassing evaluations of change—focused on



352

Tab

le 1

. Ove

rarc

hing

and

Spe

cific

Cha

nge

The

mes

Ove

rarc

hing

cha

nge

them

eSp

ecifi

c ch

ange

the

me

Cod

ed e

xam

ples

1. T

heor

etic

al fo

unda

tions

of o

rgan

izat

iona

l ch

ange

1. F

ield

rev

iew

s

Sum

mar

ies

and

revi

ews

of t

he fi

eld,

its

theo

ry a

nd

prin

cipl

es 2

. Eva

luat

ions

and

bas

is

Con

ditio

ns u

nder

pinn

ing

and

tren

ds o

f cha

nge

rese

arch

3. G

ener

al c

omm

ent

C

omm

enta

ries

with

ove

rvie

w a

nd t

hem

atic

syn

opsi

s or

dig

est

Arm

enak

is an

d Be

deia

n (1

999)

, Con

nor

(197

7) Le

win

(19

47),

Gol

embi

ewsk

i et

al. (

1971

) G

olem

biew

ski a

nd B

lum

berg

(19

68),

Pett

igre

w,

Woo

dman

, and

Cam

eron

(20

01)

A

rtic

les

enco

mpa

ssin

g ev

alua

tions

of

chan

ge—

focu

sed

on b

road

con

side

ratio

ns

of t

he fi

eld

and

cate

gori

zing

cha

nge

(incl

udin

g th

e de

velo

pmen

t an

d ba

sis

of

chan

ge a

nd it

s hi

stor

y)

2. D

iagn

osin

g or

gani

zatio

nal c

hang

e

Art

icle

s re

late

d to

the

nat

ure

of c

hang

e—fo

cuse

d on

pro

cess

(in

clud

ing

the

natu

re

and

cond

ition

of c

hang

e ou

tcom

es)

4. C

hang

e pr

oces

s

Ma p

ping

and

exp

lain

ing

the

actio

ns a

nd p

atte

rnin

g of

ch

ange

5. P

erfo

rman

ce

Ho w

org

aniz

atio

n fu

nctio

ns a

ffect

s ef

fect

iven

ess

and

effic

ienc

ies

6. S

truc

ture

/form

(fit

)

Cha

nge

in o

rgan

izat

iona

l for

m a

nd s

truc

tura

l co

mpl

exity

7. E

nvir

onm

ent

E

n vir

onm

enta

l tri

gger

s of

and

effe

cts

on c

hang

e 8

. Tim

e/m

omen

tum

T

empo

in a

nd r

ate,

rhy

thm

or

tem

pora

l pat

tern

of

chan

ge 9

. Em

otio

ns

Effe

ct o

f em

otio

ns a

nd e

mot

iona

l sta

tes

on c

hang

e ou

tcom

es10

. Val

ues

B

elie

fs in

fluen

ce a

nd v

alue

s or

ient

atio

n ef

fect

s on

cha

nge

11. C

ultu

re

Nat

ure

and

role

of o

rgan

izat

iona

l cul

ture

on

chan

ge12

. Tec

hnol

ogy/

inno

vatio

n

Cha

nge

of t

echn

olog

y ef

fect

s an

d in

nova

tion

outc

omes

on

org

aniz

atio

n

Hre

bini

ak a

nd Jo

yce

(198

5), D

iam

ond

(200

8) M

ann

and

Mar

ch (

1978

), G

reve

(19

98)

McN

ulty

(19

62),

Lew

in e

t al

. (19

99)

Dun

can

(197

2), K

oka

et a

l. (2

006)

Am

burg

ey a

nd M

iner

(19

92)

Huy

(19

97)

Pool

e et

al.

(198

9), T

enka

si a

nd C

hesm

ore

(200

3) H

erac

leou

s (2

001)

Bald

ridg

e an

d Bu

rnha

m (

1975

), Bu

rkha

rdt

an

d Br

ass

(199

0)

(con

tinue

d)



353

Ove

rarc

hing

cha

nge

them

eSp

ecifi

c ch

ange

the

me

Cod

ed e

xam

ples

3. U

nder

stan

ding

sys

tem

s of

or

gani

zatio

nal c

hang

e

Ar t

icle

s on

cha

nge

syst

ems—

focu

sed

on c

onte

nt (

incl

udin

g ac

tions

and

ch

oice

s of

res

pond

ing

to c

hang

e)

13. B

ehav

ior

resp

onse

s

Indi

vidu

al, g

roup

, and

org

aniz

atio

nal b

ehav

iora

l ch

ange

and

cop

ing

resp

onse

s14

. Com

mun

icat

ion

C

omm

unic

atio

n ty

pe, d

isco

urse

ski

lls, a

nd

indi

vidu

al c

omm

unic

atio

n st

rate

gies

15.

Sens

emak

ing/

lear

ning

Pr

oble

m s

olvi

ng a

nd le

arni

ng t

echn

ique

s16

. Ide

ntity

(in

clud

ing

gend

er)

T

he d

eter

min

atio

n an

d ef

fect

of i

dent

ity a

nd

dive

rsity

effe

cts

17. I

nter

pret

atio

n/co

gniti

on

Cha

nge

sche

mat

a an

d in

terp

retiv

e m

echa

nism

s fo

r un

ders

tand

ing

chan

ge18

. Im

plem

enta

tion

H

ow c

hang

e oc

curs

and

the

app

roac

h ad

opte

d19

. Wor

k

Cha

nge

in w

orki

ng a

rran

gem

ents

20. D

owns

ize/

decl

ine

Si

ze e

ff ect

s of

and

dow

ntur

n re

actio

ns t

o ch

ange

Kin

g (1

974)

, Wie

rsm

a an

d Ba

rtel

(19

92)

Ford

and

For

d (1

995)

, Her

acle

ous

and

Barr

ett

(200

1) G

ioia

(19

94),

Isab

ella

(19

90)

Dut

ton

and

Duk

eric

h (1

991)

, Bro

wn

and

St

arke

y (2

000)

Bart

unek

(19

84),

Lau

and

Woo

dman

(19

95)

Gio

ia a

nd C

hitt

iped

i (19

91),

Fiol

and

O

’Con

nor

(200

2)

Edst

röm

and

Gal

brai

th (

1977

),

Car

pent

er (

2000

) C

amer

on e

t al

. (19

87),

Free

man

(19

99)

4.

The

orie

s an

d m

odel

s of

org

aniz

atio

nal

chan

ge

Art

icle

s th

eori

zing

or

conc

eptu

aliz

ing

chan

ge—

focu

sed

on m

odel

s fo

r co

nsid

erin

g ch

ange

(in

clud

ing

cond

ition

of a

nd s

chol

arsh

ip o

n)

21. M

easu

re

Eval

uatin

g an

d m

easu

ring

cha

nge,

and

mod

els

of

mea

sure

men

t22

. Rea

dine

ss

Rea

dine

ss fo

r an

d pr

oces

s th

roug

h w

hich

cha

nge

unfo

lds

Mac

y an

d M

irvi

s (1

976)

, Hel

fat

and

Pe

tera

f (20

03)

Arm

enak

is e

t al

. (19

93),

Eby

et a

l. (2

000)

(con

tinue

d)

Tab

le 1

. (co

ntin

ued)



354

Ove

rarc

hing

cha

nge

them

eSp

ecifi

c ch

ange

the

me

Cod

ed e

xam

ples

23. M

etho

d

Cha

nge

rese

arch

met

hods

and

res

earc

h pr

actic

e cr

itiqu

e24

. Pla

nned

T y

pes

of p

lann

ed c

hang

e re

spon

ses

or

cate

gori

zatio

n25

. Org

aniz

atio

nal m

odel

s

Con

cept

ual m

odel

s fo

r th

eory

and

pra

ctic

e on

ch

ange

Lind

ell a

nd D

rexl

er (

1979

), Pe

ttig

rew

(1

990)

Keg

an (

1971

), R

ober

tson

et

al. (

1993

) Va

n de

Ven

and

Poo

le (

1995

), G

eorg

e an

d Jo

nes

(200

1)

5. In

terv

entio

ns fo

r or

gani

zatio

nal c

hang

e

Art

icle

s w

ith in

terv

entio

n ty

pe

clas

sific

atio

ns a

nd im

plem

enta

tions

—fo

cusi

ng o

n ch

ange

app

licat

ion

(incl

udin

g m

anag

ing

effe

ctiv

e ch

ange

st

rate

gies

)

26. C

hang

e ag

ent

T

he fu

nctio

nal r

ole

and

func

tion

of c

hang

e ag

ent

mem

bers

in c

hang

e27

. Pow

er/g

over

nanc

e

Polit

ics

of, l

eade

rshi

p ro

les,

and

influ

ence

in

chan

ge28

. Man

agin

g/in

terv

entio

ns

How

cha

nge

is m

anag

ed a

nd t

he s

tyle

and

sca

le

of c

hang

e29

. Dec

isio

n m

akin

g

Inte

rven

tions

, cho

ices

and

sys

tem

atic

app

roac

hes

to c

hang

e30

. Str

ateg

ies

En

gagi

ng in

cha

nge

proc

esse

s an

d re

spon

ses

faci

litat

ing

chan

ge

Brys

on a

nd K

elly

(19

78),

Kah

n (1

995)

Gra

y an

d A

riss

(19

85),

Buch

anan

and

Ba

dham

(19

99)

Pres

ton

and

Post

(19

74),

Gra

ebne

r (2

004)

Gre

enw

ood

and

Sudd

aby

(200

6) N

utt

and

Back

off (

1997

), G

ordo

n et

al.

(200

0)

Tab

le 1

. (co

ntin

ued)



Schwarz 355

categorizing and reviewing change; (b) diagnosing organizational change, made up of articles related to the nature of change—focused on process and phenomena; (c) understanding systems of change, made up of articles on change systems—focused on content and response; (d) models of change, made up of articles theorizing or con-ceptualizing change—focused on models for considering change; (e) interventions for organizational change, made up of articles using intervention type implementations or classifications—focusing on change application or problem solving. Change theme popularity was derived by summing the thematic count across all articles in the sam-ple. Both author and trained coder then reread each article in its entirety for the accu-racy of broad and specific coded themes. To code for the life cycle and patterning of themes, data were reviewed in terms of nine operational measures.

Publication ratios. Data were coded for publication, citation, and publication distri-bution number trends (after Cano & Lind, 1991). Given that citations offer a visible footprint of the evolution of knowledge (Bendersky & McGinn, 2010), the impact of the article and an indication of its usefulness to community were assessed using (1) citation counts. This measure has been used as an indicator of the research for several decades (see Johnson & Podsakoff, 1994) and was a count of the total number of cita-tions an article had received since publication, using Google Scholar’s citation data. This content provider offers a far larger record of citations than other abstract and citation databases of peer-reviewed literature, such as Social Science Citation Index or Scopus. Google Scholar was selected in keeping with the broad spirit of the research question. Presumably, adapting Laband (1986), the greater the number of citations an article elicits, the more valuable that idea or its theme is judged to be in the commu-nity. For this reason the most extensive possible citation patterning was sought, and therefore, were not controlled or manipulated.

The knowledge life cycle was coded by indexing a count of publishing trends. This impact was measured by a ratio of the (2) total number of articles published by each journal per year, (3) the total number of pages published in each journal per year, and the (4) total number of pages per article. The use of this index follows convention established by Lockett and McWilliams (2005) and Miner (1984) in comparing tem-poral publication trends. The citation data were therefore offset by the publication pattern, as an indicator of progress.

Given Woodman’s (1989) assertion that organizational change and development research is traditionally constrained by imbalances in its methodological orientation, each article’s method of analysis was coded in two ways. The article’s (5) primary method was initially coded to identify its epistemological approach (i.e., quantitative, qualitative, mixed, literature review). This approach was followed by a more refined delineation of each of the (6) specific methods, made up of five quantitative types (survey, experiment, simulation, archive/database, modeling), five qualitative meth-ods (action research, interviews, case, ethnography, grounded theory), and two alter-native codes (literature review, mixed).

Temporal trends. Data were coded for features of time and its life cycle variants, including spread, sequence, and stages (after, Abrahamson & Fairchild, 1999). All




articles were coded by (7) year of publication to plot temporal patterning. Following Gomez-Mejia and Balkin (1992) research output was measured by recording the arti-cle count in each year. These data were recoded as a control variable with each arti-cle coded by its (8) cumulative year (coded year), coding 1947 as 1 through 2008 coded as 62.

Research orientation. Data were also coded for researcher intent and objectives. Arti-cles were classified according to Newman and Cooper’s (1993) research plots of research recognition, specifically to identify the patterning of idea mobilization. This approach is a mechanism for classifying the extent of a research contribution, and of whether its (9) research intent matches the popularity of an idea. This measure is a means of gauging the level of recognition received by published articles. Newman and Cooper identify three research plots as a means of mapping researcher intention when undertaking research, with an article coded (a) as adopting a refinement plot (i.e., refining linkages already tested before), (b) as an extension plot (i.e., previously stud-ied but develops news linkages), or (c) as an exploration plot (i.e., developing a

Figure 1. Research output per published year



Schwarz 357

fundamental change in part of an existing area, with new causal linkages). For this study, these plots give an indication of how research is undertaken and how its themes unfold, identifying the type of progress.

Using these nine measures, the separate parts of the research question—knowledge progress, patterning, and life cycle—were tested by evaluating the data in terms of how change has been researched, what are changed, and why change research may be viewed as effective or not in relation to the specific time periods of the database. This approach encompassed plotting the coded data by year and by decade, compared across decade and by journal. Such data mining was undertaken using the statistical package SPSS, utilizing its descriptive and bivariate statistics functions, which included analyzing data for frequency, cross-tabulation, and ratio statistics, and under-taking correlation and cluster analysis.

ResultsFertilizing the Tree: Publication Ratios

Figure 1 reveals the steadily growing interest in change in terms of research output. These data confirm the growth trend argued for or shown in previous reviews of aspects of change (such as Armenakis & Bedeian, 1999; Oreg et al., in press; Woodman, 1989). Simply put, there is empirical support for the development of the field when viewed through a publication ratio lens. This trajectory is characterized by an initial and relatively slow growth in interest in the early years of publication. As the field took shape, in the midyears of publication, the rate and pace of growth gradually increased, followed by a noticeably steep and steady escalation in the num-ber of articles published in later years, as the rate of publishing interest matures. Such a trend indicates the accumulative tendency of the field—the tendency to reinforce and refine through sheer mass.

By empirically connecting publication ratios with change themes, these data map the knowledge flow in the field. Figure 1 shows that cumulatively more articles on change have been published from 1993 onward than at any time over the past six decades. These data reveal not only a positively skewed, rapidly accelerating slope in the number of articles published but one also dominated by recent research output, and with no indication of a pending or dramatic decline up until 2008. Supporting a ratio-based pattern as an indicator of progress, although publishing rates are regular, they are somewhat intermittent until 1993. Articles published in the 1970s and 1980s saw a continued and steady rise in publishing rates—12% and 14% of total articles pub-lished respectively—followed by exponentially steep rises in interest in the 1990s (31% of the total) and into the 2000s (40%). From 1993, 68% of article totals were published, with a mean of 18 publications a year, peaking in 2006 (27 articles) and then dropping back to 1998 output levels (12 articles) in 2008.

This falling off reflects the reduction in cumulative publication space donated to change articles in the set of journals, with only five of the outlets publishing these




articles during this period, and the majority of the articles (42%) published by one journal (JABS). These results are not to suggest that the set of journals did not publish anything to do with change, only that they did not do so in terms of parameters of this current research. The drop-off in 2008 also highlights that the spike in publication growth in 2005 (21 publications) through 2007 (23) is characterized by special issues specifically focused on single-change themes (e.g., HR 2007, Issue 10, special issue on transformation; JABS 2007, Issue 1, special issue on organization development and change) followed by a return to a more regular publication average (12 articles). Furthermore, all journals progressively grew in size while their allocation of space to change articles remained constant. In 1947 (Year 1 of the sample) journals averaged 280 pages per year and published an average of 11 pages on change. In 1978 (year 31), journals averaged 603 pages and 14 on change. Although by 2008 (Year 61) that size had expanded to 849 pages, yet only 21 on change. For the entire sample these num-bers are consistent with 809 pages per journal per year and 21 change pages.

The profile that emerges from plotting this publishing trend illustrates that less than 3% of all articles appeared in the first two decades of the study. Not unexpectedly these 13 articles also represent the highest and most consistently well-cited publica-tions with a mean citation count of 316 (SD = 57) compared with a mean of 136 for the whole sample (SD = 48), suggesting the extent of the impact on the field of this set of articles despite its size. By way of comparison of this impact on change research that followed, the most highly cited article in this set is Lewin (1947, mean = 1,647), which dwarfs the five other articles published in the same issue of Human Relations (mean = 31, SD = 22), of which the next highest cited article is Curle and Trist (1947) with 75 cita-tions. A one-way analysis of variance supported this ratio-based patterning indicating a significant effect of year of publication on overarching themes, F(4, 803) = 6.60, p < .001, and on specific themes, F(29, 293) = 2.52, p < .001, sug-gesting that, as expected, the growth in publication is grounded in a temporal effect. These ratio findings corroborate a basic reading of the three (previously listed) steps in plotting the life cycle pattern of progress. That is, progress as a consistently growing exchange of ideas as publications move from identifying an initial set of underpinning ideas (1947 through early 1970s articles) followed by idea mobilization and develop-ment (1970s through early 1990s) and then their diffusion across the community (1993 onward). These data confirm the assumption of previous reviews of the field (e.g., Pasmore & Fagans, 1992; Weick & Quinn, 1999) that change is a root foundation of organization studies, in this case based on the sheer scale of research being published.

Shaping the Tree: Temporal TrendsTable 2 deconstructs this publishing pattern further, breaking down each theme and its publication range data. It shows that despite assertions that all fields need some degree of consensus (Colquitt & Zapata-Phelan, 2007) and notwithstanding multiple calls for developing such consensus in change research (Woodman, 1989), change themes are



Schwarz 359

Table 2. Change Themes and Publication Ratios

Overarching and specific theme N

Percentage of total

Mean citation count (SD)

Mean publication

datePublication

rangeDominant

year (by total)

Theoretical foundations 17 3.6 237 (494.60) 1982 1948-2007 1968, 2004 (2) 1. Field reviews 10 2.1 59 (89.75) 1990 1963-2004 2. Evaluations and basis 2 0.4 832 (1152.58) 1959 1947-1971 3. General comment 5 1.1 357 (595.31) 1978 1948-2005

Diagnosing organizational change

116 24.5 163 (235.37) 1995 1962-2008 2001 (9)

4. Change process 34 7.2 189 (186.96) 1996 1980-2008 5. Performance 13 2.7 163 (139.37) 1995 1978-2005 6. Structure/form (fit) 33 7.0 95 (115.78) 1995 1962-2007 7. Environment 11 2.3 257 (515.78) 1993 1972-2007 8. Time/momentum 3 0.6 653 (869.94) 1997 1992-2004 9. Emotions 3 0.6 114 (72.50) 1990 1973-2002 10. Values 8 1.7 101 (78.60) 1998 1989-2006 11. Culture 3 0.6 17 (12.22) 2000 1995-2006 12. Technology/

innovation7 1.5 161 (178.70) 1996 1975-2006

Understanding systems of change

165 34.9 103 (173.75) 1994 1965-2008 2005 (13)

13. Behavior responses 48 10.1 102 (160.92) 1991 1967-2008 14. Communication 8 1.7 99 (118.59) 2000 1990-2008 15. Sensemaking/

learning27 5.7 84 (115.29) 1998 1965-2008

16. Identity (including gender)

14 3.0 152 (269.12) 1999 1989-2008

17. Interpretation/cognition

16 3.4 177 (271.83) 1998 1984-2008

18. Implementation 24 5.1 58 (139.01) 1993 1969-2007 19. Work 10 2.1 83 (142.51) 1990 1968-2007 20. Downsize/decline 15 3.2 122 (142.51) 1994 1982-2003 Theories and models 99 20.9 193 (438.06) 1993 1970-2008 1993 (11) 21. Measure 7 1.5 157 (236.78) 1986 1976-2007 22. Readiness 6 1.3 84 (115.67) 1998 1979-2008 23. Method 37 7.8 183 (641.24) 1993 1970-2007 24. Planned 7 1.5 99 (77.47) 1984 1970-2001 25. Organization models 46 9.7 223 (277.31) 1995 1975-2008 Organizational change

interventions76 16.1 68 (101.85) 1991 1961-2008 2002 (6)

26. Change agent 14 3.0 49 (57.32) 1988 1971-2006 27. Power/governance 9 1.9 107 (165.22) 1990 1961-2007 28. Managing/

interventions30 6.3 70 (121.90) 1990 1969-2008

29. Decision making 4 0.8 113 (73.14) 1998 1982-2006 30. Strategies 19 4.0 49 (279.56) 1992 1972-2007 Total 473 100.0 136 (279.56) 1993 1948-2008 2006 (27)




widely distributed over time. Viewing mean publication date and publication range data indicates that this spread overshadows any cogent temporal groupings across themes. The patterning profile shows understanding (34.9%), diagnosing (24.5%), and modeling (20.9%) themes receiving the bulk of community interest. Although highly cited, foundations themes only received 3.6% of publication totals (and within this theme 59% of these articles focused on one specific theme—field reviews). This skewed trend indicates that while there is growth, there is also a trend in researchers progressively focusing on mapping the conditions of change—of attempting to under-stand it and its outcomes—and less of an interest in strategies for facilitating change or shaping new theory. Within each overarching theme, there are clear markers that lead specific themes: for diagnosing, change process (30% of the general theme total) and structure (29%) dominate other themes (all single-digit percentages); for understanding themes, behavior responses (29%) dominate, with only sensemaking (16%) and inter-pretation (15%) receiving any other significant or noteworthy attention; for modeling

Figure 2. Thematic spread overlaid onto publication clusteringNote. Specific change theme numbering corresponds to listing in Table 1. Coded year indicates cumulative years of publication (1947-2008). Clustering scale indicates the number of publications per theme, per year: • >10 articles, • 8-10 articles, • 6-8 articles, • 3-5 articles, •indicates 1-2 articles.



Schwarz 361

themes, organization models (47%) and research measures (37%) lead that landscape, whereas for interventions, managing (40%) towers over other themes.

Figure 2 graphically indicates this diffusion, highlighting the thematic spread for the 62-year period. Its clustering scale denotes publication grouping whereas its interpola-tion line depicts the temporal nature of this patterning, showing how themes scatter. Read in conjunction with Figure 1 and Table 2, these results depict the influence of thematic subset groupings on a growth-oriented research community. Since 1947, pro-gressively more research on change is being undertaken. Typically, classes or conceptu-ally connected groups group together in some meaningful way. But rather than strongly cluster thematically, and thereby create a more regular thematic adoption and devel-opment cycle, change researchers have adopted a set of disparate and stratified themes. The cycle is inconsistent, offering a segmented and diverse body of ideas. Few themes overlap or nest together in any significant way, maintaining a weakly rooted knowledge tree.

In the 1940s and 1960s researchers developed the field with a concentrated period of research focused on categorizing change and content type research, and the inten-tion of refining subject matter. In the 1970s, however, this trend shifted, so that while a refining plot still dominated research content, the focus of this research became understanding type themes, with more attention paid to empirical data collection. The 1980s continued this pattern, mobilizing the organizational change community beyond its initial psychology, sociology, and organization development roots. Yet researcher attention then shifted, so that by the 1990s this trend changed once more, typified by more of an interest in extending existent knowledge, with far more of a spread over time and across the full set of journals in the study. Researchers overturned this approach in the 2000s, reverting once again to refining ideas and rationalizing change type themes. There is rich diversity to these trends with its focus on attempting to understand and explain individual, group, and organizational change. Plotting these data (Figure 2) indicates that far from presenting a uniform knowledge flow path, with its pattern of clustered themes at distinct time periods, or collective understandings based on shared thematic anchors, this pattern is weak and disorganized. The conse-quence of this dispersion is that after a slow gestation in research, when publication numbers increased the thematic narrative was too widely distributed to progress iso-lated themes to become more representative phenomena.

In support of this finding, data show that popular issues continue to receive interest, reflected in citation growth over time. Table 3 corroborates the typical spread of citation life cycles, with a small subset of extremely highly cited articles extending over time, and a mix of high- and low-cited articles with finite life span, in keeping with the transitory nature of publishing fads. It also corroborates that page number totals for change articles remained constant, with a positive correlation in space provided across all journals (r = .22, p < .001). Digging deeper, however, results indicate that judging progress based purely on publication growth and citation rates is problematic. Although foundation themes domi-nate citation rates, they also represent the smallest total publication (and growth trend). In contrast, relatively few articles were published in environment (n = 11) and time/



362

Tab

le 3

. Dec

ade

Publ

ishi

ng R

epor

t an

d C

ycle

Dec

ade

Art

icle

s pu

blis

hed

Jour

nal s

prea

d (n

)K

ey y

ears

(n)

Ran

ked

them

e (n

)Pr

imar

y ar

ticle

in

tent

(n)

Prim

ary

met

hod

(n)

Mea

n ci

tatio

n co

unt

Mea

n pa

ges

(Per

cent

age

of jo

urna

l to

tal i

n ye

ar)

1940

s2

HR

(2)

1947

(1)

Foun

datio

ns (

2)R

efin

e (2

)Et

hnog

raph

y (1

)1,

528

16 (

6.0)

19

48 (

1)A

rchi

ve/h

isto

rica

l (1)

19

60s

11A

SQ (

5)19

68 (

3)Fo

unda

tions

(4)

Ref

ine

(8)

Lite

ratu

re r

evie

w (

4)96

22 (

4.7)

JA

BS (

4)19

69 (

3)D

iagn

osin

g (4

)Ex

plor

e (3

)G

roun

ded

theo

ry (

2)

A

MJ (

2)U

nder

stan

ding

(1)

Ethn

ogra

phy

(2)

Inte

rven

tions

(1)

19

70s

56A

SQ (

20)

1977

(10

)U

nder

stan

ding

(17

)R

efin

e (3

4)Li

tera

ture

rev

iew

(18

)85

16 (

2.6)

JA

BS (

15)

1976

(8)

Mod

elin

g (1

5)Ex

tend

(14

)Su

rvey

(14

)

A

MJ (

9)19

79 (

8)In

terv

entio

ns (

13)

Expl

ore

(8)

Cas

e st

udy

(7)

HR

(7)

1971

(6)

Dia

gnos

ing

(9)

AM

R (

5)Fo

unda

tions

(2)

19

80s

66JA

BS (

15)

1989

(12

)U

nder

stan

ding

(24

)R

efin

e (2

9)Li

tera

ture

rev

iew

(28

)14

518

(2.

9)

ASQ

(14

)19

85 (

11)

Inte

rven

tions

(17

)Ex

tend

(28

)M

odel

ing

(11)

AM

J (12

)19

82 (

10)

Dia

gnos

ing

(12)

Expl

ore

(9)

Cas

e st

udy

(10)

JOM

(9)

1987

(8)

Mod

elin

g (1

1)

A

MR

(8)

Foun

datio

ns (

2)

H

R (

6)

A

MJ (

2)

1990

s14

8H

R (

33)

1993

(21

)M

odel

ing

(44)

Exte

nd (

71)

Lite

ratu

re r

evie

w (

58)

221

23 (

2.5)

A

MJ (

25)

1996

(18

)U

nder

stan

ding

(43

)R

efin

e (4

9)C

ase

stud

y (2

2)

O

S (1

9)19

95 (

16)

Dia

gnos

ing

(41)

Expl

ore

(28)

Arc

hiva

l (17

)

A

SQ (

17)

1990

(15

)In

terv

entio

ns (

19)

Mod

elin

g (1

5)

JO

M (

17)

1991

(15

)Fo

unda

tions

(1)

Surv

ey (

13)

JABS

(16

)19

95 (

15)

(con

tinue

d)



363

Dec

ade

Art

icle

s pu

blis

hed

Jour

nal s

prea

d (n

)K

ey y

ears

(n)

Ran

ked

them

e (n

)Pr

imar

y ar

ticle

in

tent

(n)

Prim

ary

met

hod

(n)

Mea

n ci

tatio

n co

unt

Mea

n pa

ges

(Per

cent

age

of jo

urna

l to

tal i

n ye

ar)

SM

J (11

)19

99 (

14)

AM

R (

10)

20

00s

190

JABS

(55

)20

06 (

27)

Und

erst

andi

ng (

77)

Ref

ine

(91)

Lite

ratu

r e r

evie

w (

55)

6922

(2.

4)

OS

(42)

2001

(25

)D

iagn

osin

g (5

3)Ex

tend

(74

)C

ase

stud

y (4

1)

H

R (

31)

2002

(24

)M

odel

ing

(29)

Expl

ore

(25)

Arc

hiva

l (24

)

A

MJ (

14)

2007

(23

)In

terv

entio

ns (

25)

Surv

ey (

21)

SMJ (

14)

2005

(21

)Fo

unda

tions

(6)

AM

R (

13)

2003

(20

)

A

SQ (

13)

2000

(19

)

JO

M (

8)20

01 (

25)

Tab

le 3

. (co

ntin

ued)




(A)

(B)

Figure 3. Change theme plots



Schwarz 365

momentum (n = 3) specific themes, yet these articles are well received by the community with mean citations at 257 and 653, respectively, well above the field’s average (136).

The thematic plot (Figure 3A) and box-plot representation (Figure 3B) give another perspective on this temporal trend distribution. They each point to the skewness of the publication range for specific change themes, showing that the range of interest is widely spread across time, rather than consolidated. Furthermore, it reiterates the out-come of the weak clustering evident in Figure 2—that the pattern of progress in the field is held back by not realizing this distribution trend. The box plot shows the broad distribution of themes, with the boxes for each theme indicating the average spread of articles published over the 62-year period, and the lines of the tails showing the disper-sion of the earliest and latest published article. Read together, both theme plots and box plots underscore the inconsistency in assuming a developmental cycle in change research. The plot visually illustrates that the narrow band of overlap across all themes—when all themes are connected—only occurs at the outer range of the scale (in 1990). Similarly, the time when all median publication range overlaps only occurs in 1997. These findings highlight that the growth in publication ratios over time is not necessarily representative of progress in the type of research undertaken. For instance, general comment (foundations) theme articles only elicited 5 publications, yet these articles have a mean citation count of 357 spread across a 57-year period, whereas behavior responses (understanding) theme articles, with 48 publications and the larg-est article count, had a mean citation count of 102 spread over 41 years. This finding underscores the importance of paying attention to how themes cluster and overlap as an indicator of progress, rather than solely accounting for progress in terms of ratios or citation counts.

Picking Ripened Fruit: Research OrientationData reveal that as a community, change researchers have not made obvious inroads in consistently and progressively developing a cycle that leads one theme into another and so on, in the way that other social sciences have developed (e.g., see debate on the development of sociology by Williams in 1958 and its follow-up by Portes in 2000). This trend is patently illustrated in the finding that despite the spread of specific themes as totals (Table 2, % totals), each decade is heavily influenced by a consolidation research plot (Table 3). This type of plot highlights the influence of researcher intent on progress, with thematic popularity driving research agendas, rather than the explicit double-loop learning building path associated with knowledge development.

The community is overwhelmingly focused on a refinement (45% of total articles) intent and to a lesser extent an extension (40%) one, yet neglects exploration (15%) plots. Refinement research joins together previous, already tested and established ideas with vari-ations in study characteristics or new variables. Extension research is focused on strength-ening linkages to established ideas, or extending existing knowledge by linking new variables, whereas exploration research develops fundamental change to existing linkages. Across each theme, this intent trend is dominant, with foundations (77% refinement, 12% extension), diagnosing (41% and 50%), understanding (42% and 50%), modeling (46% and 33%), and intervention (49% and 37%) highlighting this path. Moreover, as Table 3 shows,



366

Tab

le 4

. Top

10

Cita

tions

Tre

nd

Year

Cita

tions

Cita

tions

pe

r pa

geC

itatio

n tr

enda

Aut

hor(

s)A

rtic

leO

vera

rchi

ng

them

eSp

ecifi

c th

eme

Inte

ntM

etho

d

1991

3,73

813

3.5

101.

92G

. P. H

uber

Org

aniz

atio

nal L

earn

ing:

The

Con

trib

utin

g Pr

oces

ses

and

the

Lite

ratu

res

Mod

elin

gM

etho

dEx

tend

Lite

ratu

re

revi

ew19

721,

777

118.

419

.10

R. B

. Dun

can

Cha

ract

eris

tics

of O

rgan

izat

iona

l En

viro

nmen

ts a

nd P

erce

ived

En

viro

nmen

tal U

ncer

tain

ty

Dia

gnos

ing

Envi

ronm

ent

Expl

ore

Surv

ey

1997

1,65

147

.17

35.1

4S.

L. B

row

n,

K. M

. Eis

enha

rdt

The

Art

of C

ontin

uous

Cha

nge:

Lin

king

C

ompl

exity

The

ory

and

Tim

e-Pa

ced

Evol

utio

n in

Rel

entle

ssly

Shi

ftin

g O

rgan

izat

ions

Dia

gnos

ing

Tim

e/m

omen

tum

Exte

ndC

ase

stud

y

1947

1,64

714

9.7

2.23

K. L

ewin

Fron

tiers

in G

roup

Dyn

amic

s II.

Cha

nnel

s of

Gro

up L

ife; S

ocia

l Pla

nnin

g an

d A

ctio

n R

esea

rch

Foun

datio

nsEv

alua

tion

Ref

ine

Ethn

ogra

phy

1948

1,40

967

.110

.32

L. C

och,

J.

R. P

. Fre

nch

Ove

rcom

ing

Res

ista

nce

to C

hang

eFo

unda

tions

Gen

eral

co

mm

ent

Ref

ine

Arc

hiva

l

1990

1,37

252

.834

.85

A. M

. Pet

tigre

wLo

ngitu

dina

l Fie

ld R

esea

rch

on C

hang

e:

The

ory

and

Prac

tice

Mod

elin

gM

etho

dR

efin

eLi

tera

ture

re

view

1995

1,08

434

.920

.31

A. H

. Van

de

Ven,

M

S Po

ole

Expl

aini

ng D

evel

opm

ent

and

Cha

nge

in

Org

aniz

atio

nsM

odel

ing

Mod

els

Expl

ore

Lite

ratu

re

revi

ew19

961,

044

31.6

24.8

0R

. Gre

enw

ood,

C

. R. H

inin

gsU

nder

stan

ding

Rad

ical

Org

aniz

atio

nal

Cha

nge:

Bri

ngin

g Tog

ethe

r th

e O

ld a

nd

the

New

Inst

itutio

nalis

m

Mod

elin

gM

odel

sEx

tend

Lite

ratu

re

revi

ew

1991

1,03

527

.221

.50

J. E.

Dut

ton,

J.

M. D

uker

ich

Kee

ping

an

Eye

on t

he M

irro

r: Im

age

and

Iden

tity

in O

rgan

izat

iona

l Ada

ptat

ion

Und

erst

andi

ngId

entit

yEx

plor

eC

ase

stud

y

1995

1,02

137

.829

.81

K. E

isen

hard

t,

B. N

. Tab

rizi

Acc

eler

atin

g A

dapt

ive

Proc

esse

s: Pr

oduc

t In

nova

tion

in t

he G

loba

l Com

pute

r In

dust

ry

Und

erst

andi

ngIn

terp

reta

tion/

cogn

ition

Expl

ore

Mod

el

a. A

vera

ge c

itatio

ns p

er y

ear

(sin

ce 1

996,

usi

ng S

copu

s ci

tatio

n tr

acke

r).



Schwarz 367

while perhaps not unexpected, given philosophy of science type debate on how knowledge is shaped through induction, the predominance of refinement research throughout each decade of the research is surprising, especially the prevalence of the plot at times when other fields were extending (e.g., 1970s and institutional theory, population ecology).

Indicative of this situation is the foundations theme. This set of articles encompasses debate fundamental to the development and history of change, such as Coch and French (1948) and Greiner and Cummings (2004), and as such it has a positively skewed citation count. Yet as the data indicate, the theme is being used more as a consensual accessory to other research than being developed. Foundation themes mostly appeared early in the data (mean 1982) and were then intermittently scattered until the last 10 years of data when they consistently reappeared, reflected in their citation trend (Tables 2 and 3). From a life cycle perspective, the knowledge development pattern has absorbed the theme into other themes and it is now primarily background thematic detail or used to support a refinement trend. As such it is no longer a significant, stand-alone stage in the cycle.

This reliance on consolidating themes through refinement and extension chal-lenges the assertion that knowledge development is a factor of more time and more publication space or that citations reflect the extent of impact of an article on progress in the field. With a mind to the research question, these data show that the life cycle of change research is made up of multiple breaks in or interruptions, rather than con-tinual and cumulative thematic trend development. As a set, change research offers a conservative account, with research progressively becoming more interested in ratio-nalizing specific change themes and its outcomes, and then letting this progress go in favor of another. This aspect of the cycle is well illustrated by the 10 most cited articles in the sample (Table 4). These articles indicate that in change research themes, one view tends to detach from another rather than to develop each other around a common frame.

In truth, apart from perhaps three articles, this particular set is hard to make sense of. A glance at the next 10 most popular articles gives a far more comforting and familiar impression of what we might expect the field to look like (i.e., Bartunek, 1984; Burgelman, 1991; Edström & Galbraith,1977; Gersick, 1991; Gioia & Chittipedi, 1991; Helfat & Petraf, 2003; Kiesler & Sproull, 1982; Meyer, 1989; Wartick & Cochran, 1985; Wiersema & Bantel, 1992). On one hand, the disparate set may be taken as healthy progress given its breadth and span, with 7 of the top 10 articles pub-lished in the 1990s. On the other hand, beyond publication ratios, these articles almost appear to disregard the general sample trend, with the majority opposing a refinement orientation, and only two articles focused on an understanding-systems-of-change theme. This difference indicates precisely the progress that epitomizes the field—rooted in an idea consolidation pattern, indicative of the broad spread and weak clus-tering of research. The field does not yield a general sentiment or approach as the different themes vie for individual attention from other researchers, rather than join in developing the same specific phenomenon.




Consequently, with a refining and extension orientation, the research community is focused on progress that leads to the strengthening of existing assumptions. Read in conjunction with Figure 2 and Figure 3B, this finding indicates that there is less of an organized sequence in idea mobilization and more of a random consolidation process to change research. Although this patterning may signal the diversity of change researchers and may have advantages, given the steady growth in the field’s ratios, these data show that this randomness is a weakness because it impedes the fuller adop-tion of other types of progress patterns. The finding that the research community is becoming increasingly reliant on idea dependence is worth noting for its risks. A con-servative research orientation may ultimately diminish the value of an idea in its own right over time. Evidence of this outcome is manifest in a comparison of citation trends in Table 2 and Table 4. Logically, the citation trends of articles published in the 1970s and 1980s should be receiving far more attention, and yet citation counts are domi-nated by foundation 1940s’ articles and big-impact 1990s’ articles.

DiscussionIn opening their book on the biological roots of human understanding, Maturana and Varela (1987) offer an insightful observation:

In the Bronx Zoo in New York City there is a special pavilion for primates. There we can see chimpanzees, gorillas, and many monkeys of the Old and New Worlds. Our attention, however, is drawn to a separate cage at the back of the pavilion. It is enclosed with thick bars and bears a sign that says: “The Most Dangerous Primate in the World.” As we look between the bars we see with surprise our own face . . . From being observers we go on to be the observed . . . But what do we see?” (p. 23)

Reflection is a process of knowing how we know, and it is this activity that is the focus of this current study in the context of considering what progress in the field of organizational change looks like. What do we see?

In response to asking whether there is an empirical basis for knowing where orga-nizational change research is in its life cycle, findings confirm that the publication of more and increased citation rates in change research—often used as markers of progress—has equated with this least constructive form of developed knowledge. As a community, change researchers are overwhelmingly focused on the most conserva-tive type of progress—Type 3 (conservative development). The reliance on this type illustrates the difficulty that change researchers have created for themselves. In Type 1 (aggressive development) progress, knowledge develops incrementally based on paradigm identification, discovery, and idea replacement. Conversely, Type 2 (neutral development) progress reflects a systematic upgrade of theories in the context of defi-nite and mostly common frameworks. Findings indicate, however, that these two



Schwarz 369

approaches have been minimized in the adoption of a halfway response—relying on sustaining categories and refinement of what has become a massive, broad area of interest. Consequently, change research knowledge has developed as an intermittent process of idea confirmation and idea dependence, but this progress is based on con-stantly looking backward, rather than vigorously clearing a path forward.

This outcome is important for what it represents—that the constant growth in pub-lishing of a disparate subset of similar change themes ultimately increases the overall level of uncertainty, and makes the long-term coordination of new knowledge diffi-cult. As such it may be appropriate to think of the field in the plural—of organizational changes—because there appears to be multiple change entities rather than a singular “change” phenomenon. Perhaps we need to more readily think of (and therefore research) organizational change as a multifaceted endeavor in much the same way that modern psychology evolved into sets of specializations (e.g., Kantor, 1963).

But so what? Editorial reflections, special issues, and commentary pieces in orga-nization studies all regularly critique the nature of knowledge and our research rele-vancy. Equally, there is plenty of divergent debate evaluating the progress of a research field based on how much or how little consensus researchers should have (Kilduff et al., 2006; Tsai & Wu, 2010). One could even argue that contemporary science fields such as chemistry or medical science are equally characterized by such findings yet still considered progressive. Like organizational change, these fields are just as reliant on fragmented knowledge development and are going through their own debates on what such patterning represents for its community (as commentators in Gross et al., 1996, reveal). More than yet another stock-take, however, this article ties progress far more directly to the influence of the individual researcher on a field’s development, in the context of community affect. As such, it offers an alternate view in identifying the cycle of progress in knowledge development as heavily influenced by the pursuit of researcher preferred ends rather than with theory development, as is often assumed. In this context, findings hold four specific implications for future research on organiza-tional change.

Illusion of Knowledge DevelopmentRecalling Gettier’s (1963) knowledge hypothesis and Miller’s (1956) information limits proposition, the study finds an illusion of knowledge development: Findings show that change researchers assume that they know about change and undertake research accordingly. The depth of this knowledge, however, is shallow, limited by decade, restricted by established belief, and reliant on already established commit-ment boundaries. Borrowing from Chabris and Simons’s (2010) selective attention and blindness thesis, even after knowing that something is not quite right or needs to be different, this illusion still persists.

As a result, knowledge development in change research is hazy given that it is overwhelmingly predicated on making sense of what is already known (i.e., published) and thus hard to let go of. Of course, it is entirely possible for a field to replace ideas




without actually rejecting its source (Vasquez, 1997), and of course change ideas are continuously being extended and refined, as well as being borrowed (Davis, 2010; Whetten et al., 2009). Yet what stands out most from findings is that as a community, change researchers are knowingly cultivating divergent thematic perspectives while reviews of the field tend to promote the impression of thematic progress built on con-solidation. This approach is an intellectual paradox. By its very nature, change knowl-edge does not stray too far from existing conceptions or it risks being branded an oddity. Yet at the same time, by staying too close to established views, such knowl-edge tends to simply add to recognized debate, encouraging an idea assimilation that limits its study. As Maguire (1973) shows in social psychology, the risk to the field is the tendency for researchers to continuously demonstrate the idea, rather than test and advance it.

Results confirm the extent of this maturity but are far more circumspect than the conclusions drawn in previous reviews (e.g., Pettigrew et al., 2001; Sashkin & Burke, 1987; Woodman, 1989). Unlike these commentaries, findings leave us a bit confused and uncertain. Rather than necessarily assured about the phenomenon, we have mul-tiple fixed points of reference to which we can anchor change. This conclusion reveals that prior knowledge is a key factor affecting future learning because what a researcher already knows or believes interacts with a new conception to which he or she has been exposed. Perhaps individual researcher preferences mean that we retain a legitimate, sentimental attachment to established constructs which constrains progress. If so, this fondness needs to be better recognized in how we undertake change research.

There are clear action outcomes of this finding for the way we research and publish in change. For researchers, recognizing that this illusion is built on assumed knowl-edge, thematic borrowing, and citation counting, it highlights the need to take a step back and reevaluate age old questions on topic choice and of “what to study?” and to do so explicitly in the context of progressing, rather than recontextualizing knowledge. This strategy is easier said than done given university systems and tenure controls. An alternate path, therefore, could be to focus on research outlets and for journal editors to respond to the question. One way to encourage altered research behavior could be for editors to invest more effort to cultivate contrast-type research. That is, to encour-age contrasts that point toward new constructs or relationships or can invigorate older ideas, such as foundation themes in comparison with others. Together both author and publisher parties can focus more intently on thinking about how our research links the new and the old.

Recognize True BeliefA second implication relates to recognizing that organizational change is consistently justified as a different entity, by different researchers, in different decades based on a doctrine of assumed knowledge (evident in how foundation themes are borrowed for corroboration). Previously the pattern of progress in a field was identified as a cycle of how community members collectively identify, mobilize, and diffuse an idea.



Schwarz 371

Knowledge development in change research, however, appears to be far more scat-tered. Having moved beyond an initial stage of identifying and legitimizing new ideas, it now oscillates primarily between idea mobilization and idea diffusion. Lehrer and Paxson (1969) refer to this outcome as basic knowledge, made up of continuously reconstructing and refining established ideas. The irony of this outcome is that it facilitates a degree of comfort and little urgency to alter behavior, evident in the dis-tribution of change themes. Findings show the field in a neutral holding pattern, with an interest in sense making over foundation strengthening, given the scattered nature of trends, whereas the bulk of the research community publicly support unmitigated progress. Consequently, knowledge in change can be thought of as a form of “justified true belief” in the Gettierian sense—of having a belief in organizational change with-out actually having (more) knowledge of change.

This diminution of the cycle represents a dysfunctional sigmoid curve (clearly evi-dent in the interpolation line of Figure 2). Typically, an s-curve shows the advance of one variable in terms of another over time. This representation maps the cumulative growth of knowledge through a network of ideas whereby one idea progressively builds another and so on until growth eventually tapers and declines, just as a new, growing s-curve takes its place. Typically, a knowledge life cycle incorporates this upward movement in modeling the sequential phases of growth and decline of shared community interests. Findings indicate, however, that this cycle has broken down by theme, with multiple, parallel s-curves that overlap and even dominate each other, creating a breaking wavelike pattern rather than leveraging each other once a theme reaches its limit or is improved upon. In particular, change research appears to have adopted multiple, partially related paths of discovery and development, rather than consolidated ideas (and methods) in a way that would squeeze as much as possible out of the exponential function. Just as Woodman (1989) worried over two decades ago, the field is now characterized by a rich diversity that by its very existence facilitates fragmentation and constrains its ability to contribute substantially to expand beyond established thematic boundaries.

To readdress this basic knowledge outcome change researchers should concentrate on progressing competing paradigms or ideas. To paraphrase Hambrick (2007), by asking, “does my research have a likelihood of stimulating debate that will substan-tially alter or challenge existing theory?” change scholars could reformulate debate to facilitate more idea integration. Posing the question does not necessitate that it will be answered in the affirmative, but merely that it will encourage a community response to how we do research. Practically, this type of advance could be facilitated through a revision of doctoral program curricula to plant the seed for challenging entrenched knowledge silos.

Trapped by BeliefThird, by focusing specifically on progress in the field, this study indicates empiri-cally that organizational change research finds itself at a peculiar crossroad. At the




surface level, change researchers appear to have adopted a standard approach to knowledge development—that is, sharing tacit knowledge, justifying existing con-cepts, and building prototype models. This approach, however, also appears to have created a belief prison. Researcher belief serves to impose order on change ideas but in doing so also provides a research orientation that shapes this response. The emphasis is on sustaining and reinforcing positions and knowledge bases, with an overwhelming commitment to the validation of established ideas. Such belief binds researchers to themes which do not necessarily advance the field beyond its recognized parameters, but which conform with expectations. This reaction is like a blind spot that is both obvious and hard to see. The belief prison is a function of how we do research, with the primary interest among researchers being to indicate competence among our col-leagues because that is what is most highly valued in our community.

Previously, Ajzen (1991) asserts that individuals respond to a stimulus conditioned or mediated by belief, and that these salient beliefs are the prevailing determinants of a person’s actions. Without the challenge of differing beliefs, it is unlikely that an individual will change his or her perspective. Interestingly though, unlike Pfeffer’s (1993) or Gray and Cooper’s (2010) observations on the consequences of organization studies researchers ignoring inconvenient or divergent findings, this restriction has not discouraged or degraded change research. Instead, there is no hegemonic theme that ties the field together or which acts as an anchor tenant—which the field can compel-lingly build itself around in the same way that chemistry research does with the struc-ture of the atom, or physics with matter. Perhaps this diversity is to be expected given, as McKinley et al. (1999) point out, that there has never been a unified or dominant stance defining the field. For this reason, findings do not naively call for such an outcome. Still, the field is now personified by researchers who typically are more comfortable with a refining or sense-making orientation as they strive to consolidate established belief, which allows minor thematic developments to be recycled and repackaged as “new” knowledge.

A realistic way to redress this belief impact on progress could be to concentrate on combining existing knowledge when theorizing. Such combinations could include grouping themes that share common theory, combining themes that share similar assumptions, or combining themes that are unrelated. These approaches may enable changes to the current knowledge flow.

Impeded Progress, but Still (Eventually) Knowledge DevelopmentA fourth implication relates to how impeded knowledge development still generates knowledge. As Fleck (1979) argues in the context of scientific research, knowledge does not have to adopt a conventional path to advance, and ideas may lag until the community organizes itself. This long lag provides a challenge to the field in terms of the placement of recognition. It appears that this order is still in check in change research (although it is more evident within separate readings of general themes data). That the field is likely to continue down its distinctive knowledge development path



Schwarz 373

as it develops and adjusts may help redefine what a contribution in change looks like. A continuing proliferation of ideas can be seen as both an extension of boundaries and as a subdivision of existing ideas. As the sheer quantity of articles identified reveals, research on anything to do with change is popular, but findings show that the knowl-edge base is stable, evident in how the refinement plot dominates researcher interest at the base level. This outcome provides a clear challenge for change researchers: Research that replicates, rather than extends or develops existent knowledge, ranks fairly low on a knowledge progress scale.

The likelihood that all research can delve into new areas and contribute to valid knowledge all the time is unlikely. As Newman and Cooper (1993) and Laband (1986) point out, however, refinement approaches generally receive lower levels of recogni-tion. This study therefore places the typical annual reviews of the field in context. Such summaries and positive stances tend to check generic boxes—that the field is making “substantial progress,” has “better understanding,” shows “improvements,” or is “emerging” —while overlooking the tendency toward a confirmatory bias and the consequences of this narrowed stance for deeper knowledge development. Instead, findings indicate that knowledge development is qualitatively different from thematic popularity. This outcome also highlights both the source and solution to the problem. Change researchers are experiencing increased information overload. As a commu-nity, we do not have enough time to process information in any substantive manner, given the growth in research and publication. This time demand limits change scholars from exploring and developing.

Findings reveal that what we know about change today is informed by how well we understand a model, how familiar we are with its elements, and how much information we can access to test it. Apart from foundations theme research, which peaked nearly three decades ago, change researchers are not building an organized science. Perhaps we do not care for such organization though. Instead, the field is led by specialties which are further subdivided into subspecialties, even if they share common litera-tures. The risk of this approach is evident in the pieces of the pie that are neglected, leading to a low connection between themes (and theory) and creating barriers to the dissemination of knowledge across themes. Still, the idea that knowledge of change can be standardized may be unrealistic. It is therefore equally reasonable to perceive development as based on the consistent advancement of ideas. Such impeded knowl-edge development can still generate progress in knowledge as researchers make trade-offs between choices among costs and benefits of particular themes occurring at different times. This outcome requires change researchers to first acknowledge the intellectual space the field occupies.

ConclusionIn his discussion of what constitutes a contribution, Whetten (1989) suggests that the mission of theory is to challenge and extend knowledge, rather than to simply rewrite it. Results of this study indicate that this outcome is only partially met in




organizational change research. The Type 3 (conservative development) pattern of progress that currently characterizes the field suggests that it is made up of a shared but dispersed set of perspectives with no specific answer to the question of what exactly is the “change” in organizational change research. The life cycle of knowl-edge development in change has broken down by theme and by researcher orienta-tion. Perhaps these findings are something to laud and celebrate. Different researchers naturally hold different metatheoretical assumptions. But merely having knowledge or having knowledge available without sharing these outside a subfield is of no practical benefit in growing the field beyond ratios over time. This outcome is worth paying attention to because, as Pfeffer (1993) points out, “diversity in ideas and in methodology can be useful to the field as long as the diversity can be resolved at some point” (p. 616, italics added). Sixty-two years of data suggest that this outcome is still a work-in-progress for organizational change research. Shaking fruit out of the tree never seemed so complicated.

Author’s Note

An earlier version of this article was the 2011 Best Overall Division Paper for the Organization Development and Change Division at the Academy of Management Annual Meeting.

Acknowledgments

I would like to thank Bill Pasmore and the three anonymous reviewers for their academic engagement, constructive approach, and intellectual challenge, all of which helped me sharpen the argument. The majority of the article was written while I was a visiting scholar at the University of Southern California and I would like acknowledge Ed Lawler and Tom Cummings for hosting me during this time. The article also benefitted enormously from the feedback of participants at the Organization Development and Change “Nasty Friends” annual meeting con-sortium, including especially Quy Huy who provided thoughtful input and advice.

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author received no financial support for the research, authorship, and/or publication of this article.

References

A full list of all 473 articles included in this review is available from the author.Abrahamson, E., & Fairchild, G. (1999). Management fashion: Lifecycles, triggers, and collec-

tive learning processes. Administrative Science Quarterly, 44, 708-740.Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Deci-

sion Processes, 50, 179-211.Alderfer, C. P. (1977). Organization development. Annual Review of Psychology, 28, 197-223.



Schwarz 375

Armenakis, A. A., & Bedeian, A. G. (1999). Organizational change: A review of theory and research in the 1990s. Journal of Management, 25, 293-315.

Bartunek, J. M. (1984). Changing interpretive schemes and organizational restructuring: The example of a religious order. Administrative Science Quarterly, 29, 355-372.

Bartunek, J. M., & Woodman, R. W. (2011). The spirits of organization development, or why OD lives despite its pronounced death. In K. Cameron & G. Spreitzer (Eds.), Handbook of positive organizational scholarship (pp.727-736). Oxford, England: Oxford University Press.

Bendersky, D., & McGinn, K. L. (2010). Open to negotiation: Phenomenological assumptions and knowledge dissemination. Organization Science, 21, 781-797.

Bennis, W. G., Benne, K. G., & Chin, R. (1961). The planning of change. London, England: Holt, Rinehart & Winston.

Bennis, W. G., & O’Toole, J. (2005). How business schools lost their way. Harvard Business Review, 83(5), 96-104.

Bryman, A. (2001). Social research methods. Oxford, England: Oxford University Press.Burgelman, R. A. (1991). Intraorganizational ecology of strategy making and organizational

adaptation: Theory and field research. Organization Science, 2, 239-262.Burke, W. W. (2008). Organization change: Theory and practice (2nd ed.). Thousand Oaks,

CA: Sage.Burke, W. W., Lake, D. G., & Paine, J. W. (Eds.). (2009). Organization change: A comprehen-

sive reader. San Francisco, CA: Jossey-Bass.Cano, V., & Lind, N. C. (1991). Citation life cycles of ten citation classics. Scientometrics, 22,

297-312.Chabris, C., & Simons, D. (2010). The invisible gorilla: And other ways our intuitions deceive us.

New York, NY: Crown.Chia, R., & Holt, R. (2008). The nature of knowledge in business schools. Academy of Manage-

ment Learning & Education, 7, 471-486.Coch, L., & French, J. (1948). Overcoming resistance to change. Human Relations, 1, 512-532.Colquitt, J. A., & Zapata-Phelan, C. P. (2007). Trends in theory building and theory testing:

A five decade study of the Academy of Management Journal. Academy of Management Journal, 50, 1281-1303.

Curle, A., & Trist, E. L. (1947). Transitional communities and social reconnections. Human Relations, 1, 240-288.

Daft, R. L., & Lewin, A. Y. (2008). Rigor and relevance in organization studies: Idea migration and academic journal evolution. Organization Science, 19, 177-183.

Davis, G. F. (2010). Do theories of organizations progress? Organizational Research Methods, 13, 690-709.

Davis, G. F., & Marquis, C. (2005). Prospects for organization theory in the twenty-first cen-tury: Institutional fields and mechanisms. Organization Science, 16, 332-343.

De Mey, M. (1982). The cognitive paradigm: An integrated understanding of scientific develop-ment. Chicago, IL: University of Chicago Press.

Edström, A., & Galbraith, J. R. (1977). Transfer of managers as a coordination and control strat-egy in multinational organizations. Administrative Science Quarterly, 22, 248-263.




Faucheux, C., Amado, G., & Laurent, A. (1982). Organizational development and change. Annual Review of Psychology, 33, 343-370.

Firestone, J. M., & McElroy, M. W. (2004). Organizational learning and knowledge manage-ment: The relationship. Learning Organization, 11, 177-184.

Fleck, L. (1979). Genesis and development of a scientific fact. Chicago, IL: University of Chicago Press.

French, W. L., Bell, C. H., & Zawacki, R. A. (Eds.). (2000). Organization development and transformation: Managing effective change (5th ed.). Boston, MA: McGraw-Hill.

Friedlander, F., & Brown, L. D. (1974). Organization development. Annual Review of Psychol-ogy, 25, 313-341.

Fuller, S. (1993). Philosophy of science and its discontents (2nd ed.). New York, NY: Guilford Press.

Gersick, C. J. G. (1991). Pacing strategic change: The case of a new venture. Academy of Man-agement Journal, 37, 9-45.

Gettier, E. (1963). Is justified true belief knowledge. Analysis, 23, 121-123.Gioia, D. A., & Chittipeddi, K. (1991). Sensemaking and sensegiving in strategic change

initiation. Strategic Management Journal, 12, 433-448.Gomez-Mejia, L. R., & Balkin, D. B. (1992). Determinants of faculty pay: An agency theory

perspective. Academy of Management Journal, 35, 921-955.Gray, P. H., & Cooper, W. H. (2010). Pursuing failure. Organizational Research Methods, 13,

620-643.Greiner, L. E., & Cummings, T. G. (2004). Wanted: OD more alive than dead! Journal of

Applied Behavioral Science, 40, 374-391.Gross, P. R., Levitt, N., & Lewis, M. W. (Eds.). (1996). The flight from science and reason.

New York: New York Academy of Sciences.Hambrick, D. C. (2007). The field of management’s devotion to theory: Too much of a good

thing? Academy of Management Journal, 50, 1346-1352.Helfat, C. E., & Peteraf, M. A. (2003). The dynamic resource-based view: Capability lifecycles.

Strategic Management Journal, 24, 997-1010.Huber, G. P. (1991). Organizational learning: The contributing processes and literatures. Orga-

nization Science, 2, 88-115.Johnson, J. L., & Podsakoff, P. M. (1994). Journal influence in the field of management: An

analysis using Salancik’s index in a dependency network. Academy of Management Jour-nal, 37, 1392-1407.

Kantor, J. R. (1963). The scientific evolution of psychology (Vol. I). Chicago, IL: Principia Press.

Kiesler, S., & Sproull, L. (1982). Managerial response to changing environments: Perspectives on problem sensing from social cognition. Administrative Science Quarterly, 27, 548-570.

Kilduff, M., Tsai, W., & Hanke, R. (2006). A paradigm too far? A dynamic stability recon-sideration of the social network research program. Academy of Management Review, 31, 1031-1048.

Kimberly, J. R. (1979). Issues in the creation of organizations: Initiation, innovation, and insti-tutionalization. Academy of Management Journal, 22, 437-457.



Schwarz 377

Kuhn, T. S. (1970). Logic of discovery or psychology of research? In I. Lakatos & A. Musgrave (Eds.), Criticism and the growth of knowledge (pp. 1-24). Cambridge, England: Cambridge University Press.

Laband, D. N. (1986). Article popularity. Economic Inquiry, 24, 173-180.Lakatos, I. (1970). History of science and its rational reconstructions. Proceedings of the Bien-

nial Meeting of the Philosophy of Science Association (pp. 91-136). Chicago, IL: University of Chicago Press.

Lehrer, K., & Paxson, T. (1969). Knowledge: Undefeated justified true belief. Journal of Phi-losophy, 66, 225-237.

Lewin, K. (1947). Frontiers in group dynamics. Human Relations, 1, 143-153.Leydesdorff, L. (2011). “Structuration” by intellectual organization: The configuration of

knowledge in relations among structural components in networks of science. Scientomet-rics, 88, 499-520.

Lindgren, J., & Bleicher, R. E. (2005). Learning the learning cycle: The differential effect on elementary preservice teachers. School Science and Mathematics, 105, 61-72.

Lockett, A., & McWilliams, A. (2005). The balance of trade between disciplines: Do we effec-tively manage knowledge? Journal of Management Inquiry, 14, 139-150.

Maguire, W. J. (1973). The ying and yang of progress in social psychology: Seven Koan. Jour-nal of Personality and Social Psychology, 26, 446-456.

Maturana, H. R., & Varela, F. J. (1987). The tree of knowledge: The biological roots of human understanding. Boston, MA: Shambhala.

McKinley, W., Mone, M. A., & Moon, G. (1999). Determinants and development of schools in organization theory. Academy of Management Review, 24, 634-648.

Meyer, A. D. (1982). Adapting to environmental jolts. Administrative Science Quarterly, 27, 515-537.

Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capac-ity for information processing. Psychological Review, 63, 81-97.

Miner, J. B. (1984). The validity and usefulness of theories in an emerging organizational sci-ence. Academy of Management Review, 9, 296-306.

Newman, J. M., & Cooper, E. (1993). Determinants of academic recognition: The case of the Journal of Applied Psychology. Journal of Applied Psychology, 78, 518-526.

Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Sci-ence, 5, 14-37.

Olk, P., & Griffith, T. L. (2004). Creating and disseminating knowledge among organizational scholars: The role of special issues. Organization Science, 15, 120-129.

Oreg, S., Vakola, M., & Armenakis, A. (in press). Change recipients’ reactions to organizational change: A 60-year review of quantitative studies. Journal of Applied Behavioral Science.

Oswick, C., Fleming, P., & Hanlon, G. (2011). From borrowing to blending: Rethinking the processes of organizational theory building. Academy of Management Review, 36, 318-337.

Pasmore, W. A., & Fagans, M. R. (1992). Participation, individual development, and organiza-tional change: A review and synthesis. Journal of Management, 18, 375-397.

Perrin, C. E. (1988). The chemical revolution: Shifts in guiding assumptions. In A. Donovan, L. Laudan, & R. Laudan (Eds.), Scrutinizing science: Empirical studies of scientific change (pp. 105-124). Baltimore, MD: Johns Hopkins University Press.




Pettigrew, A. M., Woodman, R. W., & Cameron, K. S. (2001). Studying organizational change and development: Challenges for future research. Academy of Management Journal, 44, 697-713.

Pfeffer, J. (1993). Barriers to the advance of organizational science: Paradigm development as a dependent variable. Academy of Management Review, 18, 599-620.

Pierson, P. (2000). Increasing returns, path dependence, and the study of politics. American Political Science Review, 94, 251-267.

Pollack, M. (Ed.). (1997). The education of the architect. Cambridge: MIT Press.Portes, A. (2000). The hidden abode: Sociology as analysis of the unexpected. American Socio-

logical Review, 65, 1-18.Sashkin, M., & Burke, W. W. (1987). Organization development in the nineteen-eighties. Jour-

nal of Management, 13, 393-417.Schulz, M. (2003). Pathways of relevance: Exploring inflows of knowledge into subunits of

multinational corporations. Organization Science, 14, 440-459.Schwarz, G. M., & Huber, G. P. (2008). Challenging organizational change research. British

Journal of Management, 19(Suppl. 1), s1-s6.Starbuck, W. H. (2006). The production of knowledge: The challenge of social science research.

Oxford, England: Oxford University Press.Tsai, W., & Wu, C. (2010). From the editors. Knowledge combination: A cocitation analysis.

Academy of Management Journal, 53, 441-450.Tushman, M., & O’Reilly, C. (2007). Research and relevance: Implications of Pasteur’s quad-

rant for doctoral programs and faculty development. Academy of Management Journal, 50, 769-774.

Van Maanen, J. (1995). Style as theory. Organization Science, 6, 133-143.Vasquez, J. A. (1997). The realist paradigm and degenerative versus progressive research pro-

grams: An appraisal of neotraditional research on Waltz’s balancing proposition. American Political Science Review, 91, 899-912.

Walsh, J. P., Meyer, A. D., & Schoonhoven, C. B. (2006). A future for organization theory: Liv-ing it and living with changing organizations. Organization Science, 17, 657-671.

Wartick, S. L., & Cochran, P. L. (1985). The evolution of the corporate social performance model. Academy of Management Review, 10, 758-769.

Watkins, J. (1970) Against normal science. In I. Lakatos & A. Musgrave (Eds.), Criticism and the growth of knowledge (pp. 25-37). Cambridge, England: Cambridge University Press.

Weick, K. E., & Quinn, R. E. (1999). Organizational change and development. Annual Review of Psychology, 50, 361-386.

Whetten, D. A. (1989). What constitutes a theoretical contribution. Academy of Management Review, 14, 490-495.

Whetten, D. A., Felin, T., & King, B. G. (2009). The practice of theory borrowing in organiza-tional studies: Current issues and future directions. Journal of Management, 35, 537-563.

Whitley, R. (1984). The intellectual and social organization of the sciences. Oxford, England: Clarendon Press.

Wiersema, M. F., & Bantel, K. A. (1992). Top management team demography and corporate strategic change. Academy of Management Journal, 35, 91-121.



Schwarz 379

Williams, R. M. (1958). Continuity and change in sociological study. American Sociological Review, 23, 619-633.

Woodman, R. W. (1989). Organizational change and development: New arenas for inquiry and action. Journal of Management, 15, 205-228.

Woodman, R. W. (2008). Discourse, metaphor and organizational change: The wine is new, but the bottle is old. British Journal of Management, 19, S33-S37.

Wu, C., Neubert, M. J., & Yi, X. (2007). Transformational leadership, cohesion perceptions, and employee cynicism about organizational change. Journal of Applied Behavioral Sci-ence, 43, 327-351.

Bio

Gavin M. Schwarz, PhD, is an associate professor at the School of Management, Australian School of Business, The University of New South Wales. His current research interests include organizational failure to change, the logic of structural inertia, and knowledge development in organization theory.



Shaking Fruit out of the Tree: Temporal Effects and Life Cycle in Organizational Change Research

Documents

Transcript of Shaking Fruit out of the Tree: Temporal Effects and Life Cycle in Organizational Change Research