Complex Project Management as Complex Problem Solving: A Distributed Knowledge Management Perspective

This article explores the concept of complex project management as complex problem solving from a distributed knowledge management perspective. It discusses the challenges of managing knowledge in complex projects and proposes a distributed coordination mechanism for knowledge management. The implications for theory, research, and practice in complex project management are examined.

See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/306344720
Complex project management as complex problem solving: A distributed
knowledge management perspective
Article in International Journal of Project Management · December 2014
DOI: 10.1016/j.ijproman.2013.06.007
CITATIONS
38
READS
1,016
3 authors, including:
Some of the authors of this publication are also working on these related projects:
CACTOS - Context Aware Cloud Topology Optimisation and SimulationView project
SIMCT - Simulation-based Contract Costing for Outsourcing EnterprisesView project
Terence Ahern
Dublin City University
5 PUBLICATIONS71CITATIONS
SEE PROFILE
P. J. Byrne
Dublin City University
82PUBLICATIONS865CITATIONS
SEE PROFILE

Complex project management as complex problem solving:
A distributed knowledge management perspective
Terence Ahern⁎, Brian Leavy, P.J. Byrne
Dublin City University Business School, Dublin City University, Ireland
Available online 2 July 2013
Abstract
Traditional project management (PM) privileges planning and downplays the role of learning even in more complex proj
paper draws inspiration from two organisations that were found to have developed complex PM expertise as a form of com
(CPS), a practice with implicit learning because complex projects are unable to be completely specified in advance (Hayek
view of complex projectmanagementas a form of complex problem solving is the governance challenge of knowledge managemunder
uncertainty. This paper proposes that the distributed coordination mechanism which both organisations evolved for this co
be characterised as a ‘common willof mutualinterest’,a self-organising process thatwas fostered around projectgoals and paced by the
project life cycle (Kogut and Zander, 1992). The implications for theory, research, and practice in complex PM knowledge m
examined.
© 2013 Elsevier Ltd. APM and IPMA. All rights reserved.
Keywords: Complex project management; Distributed knowledge management; Bounded planning; Problem solving; Common will
1. Introduction
In the project management (PM) literature, the management of
complex projectsas an importantfocusfor more intensive
research isan emerging tradition,along with theneed to
understand the particular governance challenges associated with
it (Baccarini, 1996; Miller and Hobbs, 2005; Morris and Hough,
1987;Müller, 2009).This researchpaperhighlightsand
examines knowledge management as a key aspect of governance
in the case of complex projects, based on an empirical study of
complex projectmanagementfeaturing two Irish state-owned
organisations, referred to here as GovCo-1 and GovCo-2. In the
late 1990s and early 2000s, each of these complex organisations
(Pollitt and Bouckaert, 2000; Thompson, 1967) was challenged
to take on major infrastructural development projects of a scale
and complexity well beyond what had been the norm for
organisation up to then. In GovCo-1, the stimulus was pro
by the government's National Development Plans for infr
ture investment (NDP, 2000, 2007) and the stimulus for G
was provided through EU deregulation in the energy sectIn
this context,GovCo 1&2 provided a valuable opportunity to
explore more closely in what ways the management of ‘c
projects differs most from that of other kinds of projects r
in the mainstream PM literature (APM, 2011, 2012; PMI, 2
The main empiricalfindingwas that complexproject
management(PM), as manifested in thetwo organisations
understudy,could bestbe understood as a form of complex
problem solving (CPS)thatdoesnot lend itselfto being
completelyspecifiablein advance.In the mainstream PM
literature,such projects undertaken by GovCo 1&2 tend to
viewed asjustmore ‘complicated’projects thatcan stillbe
planned and managed in the traditional way as “the appl
of knowledge,skills,tools,and techniques to projectactivities
to meet the project requirements” (PMI, 2013, p. 5, italics
In this approach,there is little learning anticipated beyond
the application of prior knowledge.In contrast,the empirical
finding that complex PM is a form of complex problem so
⁎ Corresponding author at: Dublin City University Business School, Dublin
City University, Ireland. Tel.: + 353 1 7031752.
E-mail addresses: [e-mail] (T. Ahern),
[e-mail] (B. Leavy), [e-mail] (P.J. Byrne).
www.elsevier.com/locate/ijproman
0263-7863/$36.00 © 2013 Elsevier Ltd. APM and IPMA. All rights reserved.
http://dx.doi.org/10.1016/j.ijproman.2013.06.007
Available online at www.sciencedirect.com
ScienceDirect
International Journal of Project Management 32 (2014) 1371 – 1381

(CPS) means that managing project knowledge becomes more
problematic.
In terms of governance,this alternative perspective means
that a central aspect of knowledge management in complex PM
settingsinvolvesmanaging intrinsic knowledge uncertainty.
This is manifest as incomplete pre-given knowledge in complex
projectsthat necessarilylimits complexPM to ‘bounded
planning’,which implies the need in complexPM to
continuously create knowledge over the project life cycle that
is notspecifiable atthe outset(Engwall,2002).This,in turn,
requiresthe developmentof an effectivemechanism for
coordinating this emergent knowledge.In the cases of GovCo
1&2, both were found to have evolved a distributed governance
approach to knowledgemanagementthatrevolved around
problem solving as a mode of learning and organising. In effect,
in order to create project knowledge that was unspecifiable at
the outsetin projectdesigns,plans,etc.,the projectteam
became a community of learners that was learning the project
though organisational CPS. In order to coordinate this emergent
knowledge,GovCo 1&2 harnessed the agency ofwhatthis
papertermsa ‘common willof mutualinterest’thatwas
fostered around projectgoals and paced by the projectlife
cycle.This can be thoughtof as a high-levelorganising
principle that is irreducible to individual project actors (Kogut
and Zander, 1992), by which the project team can know more
than itcan tell(Polanyi,1967)and can know more than its
individual members can know separately.
The full empiricalinquiry thatled to these findingsis
reported elsewhere (Ahern, 2013), which is an exploratory case
study investigation of two complex organisations in the public
sector using a Contextualist research perspective that includes
51 semi-structured interviews (Pepper, 1942). This longitudinal
process approach facilitates the study ofthe developmentof
organisationalprocesses thatare ‘in flight’ during periods of
importantchangein organisations(Pettigrew,1990,1997,
2012). The primary purpose of this paper is to examine some of
the main conceptualand practicalimplicationsfor the
traditionalPM literatureassociatedwith the abovetwo
importantempiricalinsights in complex PM,namely,incom-
plete pre-given knowledge and coordinating emergentknowl-
edge.This will be done by reviewing the literature on related
themesand drawingon furtherfindingsfrom the data
(Siggelkow, 2007).
The remainderof the paperis organisedas follows:
Section 2 reviews the literature on complex PM with particular
attention to the contrastin knowledge managementassump-
tions between traditionalPM and those implied by viewing
complex PM as complex problem solving (CPS).In addition,
learning modesare reviewed forgenerating knowledgein
complex PM,which can be coordinated through a distributed
organising approach.Section 3 discusses the implications for
governance in complex PM ofknowledge managementas a
process of learning and organising under ‘bounded planning’
ratherthan ‘totalplanning’assumptions.This includesthe
scaffoldingof distributedlearningand organisingusing
documented procedures as well as the fostering and pacing of
a common willof mutualinterestfor coordinating emergent
projectknowledge.In Section 4,the concluding section,the
implicationsof inherentknowledge uncertainty in complex
PM as a form of organisationalCPS are discussed in relation
to the following areas of research and practice:(i) planning,
knowledge creation,and knowledge coordination;(ii) leader-
ship; (iii) knowledge transfer; and (iv) PM complexity.
2. Complex project management as complex problem solvi
Informed by the two empirical findings highlighted earlie
section will review the literature on complex projects in rela
the managementof knowledgeunderthe traditionalPM
paradigm,which assumes full pre-given knowledge,and under
more recent pragmatist perspectives of PM, which accept t
of incomplete pre-given knowledge in projects and the nee
learning. In this, a distinction will be made between ‘compl
projectsthatcan be completelyspecifiedin advanceand
‘complex’ projects that are unable to be completely specifi
advance. Finally, different modes of problem solving learnin
discussed,including complex PM as a form of organisational
CPS, which facilitates the creation of emergent knowledge
un-specifiable at the outset; and the coordination of this em
knowledge through whatthis paperterms a ‘common willof
mutual interest’ as a distributed tacit dimension. This term
to the literature and is inspired by an interaction between t
study data and the literature to representthe synergy thatis
achieved in projects when a team spirit is successfully foste
the extentthatit becomes self-reproducing as a common will
around an interest that is mutually desired and experience
way,it becomes a self-organising process for coordinating t
behaviour and, hence, the collective learning of project tea
complex PM settings.
2.1. Complex PM as applied science — planned knowledge
In early work on the complexity of project settings, Shen
al.(1995) distinguish two dimensions of projectcomplexity—
‘technological uncertainty’ and ‘system scope’. This typolo
used in advocating a contingency approach to PM (Lawrenc
and Lorsch,1967;Shenhar,1998,2001;Shenharand Dvir,
1996), rather than the “one size fits all” approach of traditi
PM (Shenhar,2001,p. 394).In subsequentresearch,Shenhar
et al. (2002)extend the framework to encompassthree di-
mensions of projectcomplexity,namely,‘uncertainty’,‘pace’,
and ‘complexity/scope’ (UPC Model), where ‘pace’ is added
reflectthe “speed and criticality of time goals” (ibid.,p. 101).
Implicit in this research is the assumption that knowledge r
to projectcomplexity can be analysed and integrated as ‘tec
nical’ complexity underthe normsof technicalrationality
(Ashby, 1956; Cleland and King, 1968; von Bertalanffy, 195
rather than as ‘social’ complexity that requires a socio-tech
approach (Davies and Hobday,2005;Nightingale and Brady,
2011; Sapolsky, 1972; Williams, 1999, 2005). Under the for
approach, knowledge is detached from the knowing subjec
commodity and is pre-given at the outset, while, under the
knowledge is integrated with the knower as a process of kn
over time, because it is not completely pre-given at the ou
1372 T. Ahern et al. / International Journal of Project Management 32 (2014) 1371–1381

In recentliterature on complex PM,scholars have soughtto
incorporate insightsfrom research in complexity,chaos,self-
organising,and evolution with traditional PM (Cooke-Davies et
al., 2007; Geraldi et al., 2011). This emerging area in PM is termed
‘complex projectmanagement’ (Whitty and Maylor,2009).For
example,Saynisch (2010a,b) analyses complexity using the two
dimensions of ‘project complexity’ and ‘environmental complex-
ity’ and calls for a governance approach thatintegrates the two
cybernetic cyclesof traditionalPM and the managementof
complexity (evolution, self-organisation, edge of chaos). Interest-
ingly, he maintains that getting the balance right between these two
“will be the future management art” (Saynisch, 2010b, p. 8, italics
added),which suggests that,in order to dealwith situations of
project complexity, PM may have to reposition its self-image to
one of a craft with implied learning rather than an applied science
under the traditional PM paradigm with little learning anticipated
(Mintzberg, 1979, 1987).
2.2. ComplexPM as organisationalpractice— emergent
knowledge
In a paperthatrecognises the limitations ofthe planned
approachesof traditionalPM in complex projectsettings,
Berggren etal. (2008) advocate a practice-oriented approach,
termed ‘neo-realistic’,which involvesthree key managerial
practices. These include “reducing complexity by transforming
expectations”,understanding ofinterdependenciesfor better
“systemsintegration”,and,importantly,“publicarenasfor
handling theunknown amountof errors”in complex PM
settings (ibid.,p. S112,italics added).This analysis implicitly
acknowledges Hayek’s (1945) ‘specification problem’,which
here applies to complex projects thatare unable to be fully
specified in advance,by recommending organic integration
for coordinating distributed contextual knowledge.In a recent
publicationon knowledgeintegrationin a complexPM
setting,Enberg etal. (2010) also encounter Hayek's ‘specifi-
cation problem’ in terms of “unforeseeable and unimaginable
multiplying effects ofsmallchanges” (p.762).Informed by
Weick's (1995)sense-making and Polanyi’s (1967)tacitdi-
mension ofknowledge,they adopta ‘segregated team’ap-
proach to knowledge integration that relies in part on the “gut
feelings” ofseniorprojectteam members,which this paper
views as a distributed tacitdimension (Polanyi,1967,1974).
Both these empiricalpapershighlightthe need to generate
emergentknowledgein complex PM settingsthatis un-
specifiableat the outsetand theneed to coordinatethis
knowledgein a distributed approach through higher-order
principles that are self-organising (Kogut and Zander, 1992).
2.3.Complicated PM versus complex PM — planned versus
emergent
Once Hayek's (1945)‘specification problem’is acknowl-
edged in complex PM settings,it is no longertenable to
proceed under the assumption of ‘total planning’ of traditional
PM. In his classic paper on the workings of markets as complex
phenomena,Hayek (1945)highlighted a practicaldifficulty
with a centralised governance approach to knowledge.This is
because the complete data are never given “to a single m
which could work outthe implications,and can never be so
given” (ibid., p. 519), which he describes as “a problem o
utilization ofknowledge notgiven to anyone in its totality”
(ibid., p. 520). The knowledge Hayek (1945) had in mind
knowledge that was specific to the “man on the spot” (p.
which can be viewed as contextual ‘knowing’ knowledge.He
recommendedthat any solutionto this practicalproblem
needed to harnesscontextualknowledge “thatis dispersed
among many people” (ibid., p. 530).
This insight draws attention to an important difference
the terms‘complicated’and ‘complex’.An aircraftis a
complicated machine thatrelies on a large numberof servo-
mechanisms (single-loop) and crew members (double-loo
to operate the machine system within normalparameters.In
aviation history, aircraft design progressed from being a
project, when the technology was poorly understood, to b
complicated project, when detailed designs could be doc
for production assembly and, therefore, comprehensible
mind. However, like an emerging prototype that is only p
understood,a one-off complex projectmay nottransition from
complex to complicated until after it is delivered and retr
tively comprehended in its entirety (Snowden, 2002). Eve
team of planners on a complex project, if no single individ
comprehend the project interconnectivity in its entirety, t
one can preclude the possibility ofknowledge gaps between
constituentparts ofthe plan (Lenfle and Loch,2010).While
adjacent interfaces can be specified between parts of a li
like links in a chain, this approach may reduce but not eli
the potential for gaps in a complex network plan that no
individual comprehends in its entirety, e.g., PERT diagram1
Thesepotentialgapsare like untappedknowledge,or
‘unknown knowns’ (Cleden, 2009), that may exist at the
of the project or emerge over time. Using metaphors, vie
complex projectas complex problem solving (CPS)is more
like painting a landscape than the mechanicalassembly of an
elaborate jigsaw. In a jigsaw, the pieces and their connec
are known in advance but,in a landscape painting,while the
major features may be known in outline in advance,the final
connectivity has yetto emerge due to shifting light,clouds,
shadows,etc.This emphasisesthe contextualspecificity of
complex projects(Engwall,2003),which operateson the
contextualknowledge ofthe community oflearnersthatis
delivering the project by learning the project (Wenger, 20
2.4. Organisational learning under knowledge uncertainty
If complex projectsare distinguished from complicated
projects by unspecifiable pre-given knowledge thatmustbe
continuously generated overthe projectlife cycle,then,the
creation of new knowledge and its coordination become c
aspectsfor governancein complex PM. Becauseof this
incompleteness of projectplans,delivering a projectis partly
about discovering its hidden reality through “tacit forekn
1 Project Evaluation and Review Technique (PERT).
1373T. Ahern et al. / International Journal of Project Management 32 (2014) 1371–1381

(Polanyi,1967,p. 22),where “projectexecution is seldom a
process of implementation; rather it is a journey of knowledge
creation” that involves learning (Engwall, 2002, p. 277, italics
added).In this view, a projectis bettercharacterised as
‘becoming’than ‘being’,or better‘actor’than ‘object’,res-
pectively (Engwall,1998;Linehan and Kavanagh,2006;
Whitehead, 1985).
2.4.1. Complex PM knowledge uncertainty — planning to learn
the project
The level of complexity and uncertainty of the problem domain
have long been used to distinguish between differentlevels of
organisationallearning,or knowledge creation.In the learning
literature,Argyris (1977)and Argyris and Schön (1996) have
distinguished between single-loop and double-loop learning in
terms of inputs, action process, outputs, and feedback. This basic
typology is mirrored in Weinberg's (2001) systems spectrum of
simple systems (single-loop), machine systems (double-loop), and
organisedcomplexity,Fig. 1. This is furtherextended by
Snowden (2002) in a problem solving typology of problems that
are known,knowable,complex,and chaotic.In a recent
publication,Cleden (2009,p. 13) adoptsan analogous‘four
quadrants’ approach to projectuncertainty — ‘known knowns’
(knowledge),‘known unknowns’(risks),‘unknown knowns’
(untapped knowledge), and ‘unknown unknowns’ (uncertainty).
In Fig. 1, different modes of problem solving reflect different
dynamics of the problem domain in respect of knowledge change
from a previous leveland the pace of knowledge change.The
scales are indicatively logarithmic rather than linear, in order to
reflect significant changes in complexity and uncertainty in
problem domain between the differentlearning modes.These
approaches to complex problems mirrorthe seminalwork of
Knight (1935) in distinguishing between measureable unce
as ‘risk’ and unmeasureable uncertainty as ‘true uncertain
latter presenting “the greatest logical difficulty of all” (p. 2
anticipating the future.This ‘logicaldifficulty’representsa
knowledge paradox thatlies atthe heartof the traditionalPM
approach to complex projects under a general systems per
tive (Cleland and King, 1968; Ramo, 1969).
In a nutshell,if complex projectscannotbe completely
specified,how can they be completely planned in advance of
their delivery? A tentative resolution of this knowledge para
by learning the project,which involves the projectteam,as a
community of learners, creating the missing knowledge ove
project life cycle through problem solving with tacit forekno
edge (Polanyi, 1967). In this knowledge-based view, comple
comprises a community of learners based on organisationa
where CPS learning ‘is’ the practice (Wenger,2001).From the
opposite perspective, if a project can be completely specifi
advance, there is little need to regard it as complex. All the
knowledge is ‘given’at the outset,howevercomplicated,and
traditional PM governance then revolves around the applica
this prior knowledge with little additional learning required.
2.4.2. Complex PM as organisational complex problem solv
(CPS)
In complex problem solving (CPS),the problem domain is
unstructured,non-linear,with little pre-given inputs,outputs,
Extreme 10,000
High 1,000
Medium 100
Low 10
10 100 1,000 10,000 per unit time
Low Medium High Extreme
Pace of Knowledge Change
Knowledge Change
Single-Loop
Learning
Double-Loop
Learning
Complex Problem -Solving
Wicked Problems
Authors
Single-Loop Problems Double-Loop Problems Complex Problems Wicked Problems
Cleden (2009) known knowns - known unknowns - unknown knowns - unknown unknowns -
knowledge risks untapped knowledge uncertainty
Snowden (2002) known knowable complex chaos
Weinberg (2001) simple systems machine systems organised complexity
Knight (1935) risk - ‘a priori’ probability risk - statistical probability uncertainty - estimates uncertainty - estimates
Modes of Problem-Solving Learning
Fig. 1. Modes of problem solving — knowledge change & pace of knowledge change.
1374 T. Ahern et al. / International Journal of Project Management 32 (2014) 1371–1381

action process,or feedback (Argyris and Schön,1996;Newell
and Simon, 1972).As a key driver of change in organisational
knowledge, a volatile external environment can be viewed as a
stimulus with a high levelof knowledge change and pace of
knowledge change. Moreover, the volatility of the environment is
largely unknowable ex ante as a dynamic phenomenon, except in
outline or in part,even though itcan be known ex postas a
sequence of static phenomena or comparative statics (Boulding,
1956;March, 1994).The characteristicsof organisational
complex problems in Weinberg (2001),Snowden (2002),and
Cleden (2009) resonate with an earlier contribution by Swinth
(1971, pp. B68-9, italics added) as follows:
(1) Usually the solution must serve a variety of organizational
objectives.
(2) Thereis typically ahigh degreeof interdependence
between parts.
(3) Such tasks are too complex to be readily understood and
solved by one person or group.
(4) The cause of the novelty is typically a changing world …
[or] the unknowns at the frontier of knowledge or at the
interfacearising from combining existingideasand
techniques in a new way.
With complex problem solving (CPS),a key role of senior
managementis framing the problem to be resolved (Daftand
Weick, 1984; Teece et al., 1997). As Morris (1997) points out,
this is the difference between ‘projectmanagement’and the
‘managementof projects’,the latterbeing a more strategic
approach that encompasses the economic life cycle, rather than
just the project life cycle (Jugdev and Müller, 2005; Munns and
Bjeirmi, 1996). Beyond complex problems are so-called ‘wicked
problems’, Fig. 1, which are chaotic and intractable problems that
usually require crisis project management and are not considered
relevantfor complex PM in thispaper(Churchman,1967;
Mumford, 1998; Snowden, 2002).
2.4.3.ComplexPM knowledgemanagementas distributed
knowledge organising
As a way of dealing with complex problems, Swinth (1971)
proposes ‘organizationaljointproblem-solving’,based on the
‘organic’approachof Burns and Stalker(1961).In the
innovation literature,the same approach isused by Brown
and Eisenhardt (1997) for “high-velocity” (p.1) environments
of radicaland rapid change,which isanalogousto a CPS
environment with a high level of knowledge change and pace
of change,Fig. 1. This ‘organic’ approach is viewed by this
paper as one based on a common willof mutualinterestas a
distributed tacitdimension (Polanyi,1967),where the actor
participates in the overall goals to be achieved. This is akin to
Adam Smith's (1981)‘invisible hand’ of self-interestin The
Wealth ofNations,where the actoris focused on personal
economic goals rather than mutual goals.
However, in order to achieve the centralised coordination of
abstract ‘known’ knowledge (designs, plans, etc.), it needs to be
facilitatedby the distributedcoordinationof contextual
‘knowing’ knowledge (know-how,etc.) under a common will
of mutual interest. This is based on tacit pre-suppositions
following the rules of a practice (Wittgenstein, 1988). It is
self-organisingpropertyof problem solvingthroughtacit
foreknowledge,which is beyond centralised planning contro
(Kolb,1984; Orlikowski,2006; Tsoukas,1996),that provides
the requisite order for dealing with complex problems tha
“too complex to be readily understood and solved by one
personor group”(Swinth,1971,p. B69). In this way,
contextualdynamicknowledge(know-how,etc.)coalesces
any gaps in pre-given static knowledge (plans, etc.) that
overtime as ‘unknown knowns’,which are unknowable in
advanceundertraditionalPM becauseof the contextual
specificity of‘knowing’knowledge (Dewey,1966;Dewey
and Bentley, 1949; Hayek, 1945).
Temporary organisationaldynamics thatinvolve distributed
learning and organising have been investigated in compl
projectsettingsthat resonatewith the characteristicsof
organisationalCPS. This previous research revolves around a
largely unspecifiable problem situation ex ante and subse
problem solving with distributed knowledge organising us
common will of mutual interest as a distributed tacit dime
(Polanyi,1967).Thus,Meyerson etal. (1996)identify ‘swift
trust’ as a self-organising coordinating mechanism in tem
conference groups, Weick and Roberts (1993) identify ‘he
interrelating’ for coordinating on flight decks, and Weick
investigates the breakdown ofa common understanding in a
situation of novel high-level complexity. In the strategy li
Eisenhardt (1999) identifies ‘collective intuition’ as an ing
for successful strategy building and, in the PM literature,
(1996)indentifies‘team mind’in relation to localdecision-
making among projectteam membersbased on “taken-for-
granted protocols” (p. 261) that is often the result of goo
leadership.
3. Managing distributed knowledge under uncertainty —
fostering and pacing a common will of mutual interest
The empiricalfinding thatcomplex PM is a form of
organisationalCPS with knowledge uncertainty as a defining
characteristicmeansthatknowledgegovernanceis a key
challenge for the emerging research in complex PM gove
(Pemseland Müller, 2012) and this includesmanaging
incomplete pre-given knowledge under a ‘bounded plann
approach.This involves continuously creating the contextu
knowledgethat is un-specifiableat the outsetover the
remaining projectlife cycle and coordinating thisemergent
knowledge through the agency ofa common willof mutual
interest, as proposed here, or through other means.
Using a distributed organising perspective,these related
findings are now examined in the following sections as as
of learning and organising in a distributed approach to co
PM knowledge management in GovCo 1&2. In this distrib
perspective, the tools and techniques of traditional PM ar
used buttheirrole is reinterpreted in a learning approach to
complex PM as organisational CPS.For example,planning is
seen to includeplans to learn the project,documented
procedures are viewed as ‘scaffolding’ for creating emerg
1375T. Ahern et al. / International Journal of Project Management 32 (2014) 1371–1381

knowledge,and projectgoals are used to fosterand pace a
common will of mutual interest.
3.1. ComplexPM knowledgemanagementas distributed
learning and organising
In descriptive terms, the need for a common will of mutual
interest to coordinate knowledge in complex PM as a form of
organisationalCPS does not meanthatcomplexprojects
cannot,or should not,be planned butthatcomplex projects
cannotbe completely planned in advance oftheirdelivery
(Geraldi et al., 2011; Nightingale and Brady, 2011). Borrowing
from Simon (1997),this paper suggests that complex projects
may only be ‘boundedly’ planned as emergent prototypes with
incomplete knowledge. For example, not every element of the
space mission to the Moon, or the voyage of Columbus to the
New World,was planned in advance nor could it be,because
the totalcomplexity could notbe completelyspecified or
comprehended in advance by a single individual,exceptin
outline or in part (Hayek, 1945; Smith, 1981). However, in both
cases,when the abstract but static ‘known’ knowledge (plans,
etc.) of the preparatory planning was coupled with the common
will of mutualinterestof the projectteam as a mechanism of
mutual control, this ensured a convergence on the mission goals
at all times.In turn, this facilitated thegeneration,when
required,of the dynamic but contextual ‘knowing’ knowledge
(know-how,etc.)thatwas unspecifiable atthe outset,which
completed the knowledge setfor projectdelivery of ‘known’
knowledge,‘knowing’knowledge,and theircommon tacit
dimension.
Nevertheless,as with the developmentof the US Polaris
submarine projectin the 1950s,the sensibilities ofWestern
attitudes to knowledge based on technical rationality require an
emphasis on abstract‘known’knowledge atthe outsetof a
projectthatis detached from the knowing subject(Sapolsky,
1972;Spinardi,1994).This is to the detrimentof a more
realisticsocio-technicalperspectivebasedon higher-order
principlesfor organising knowledge thatare irreducible to
individuals (Kogutand Zander,1992),which is empirically
supported by this paper.It is not a choice between objectivity
based on abstract‘known’ knowledge and subjectivity based
on ‘knowing’knowledge but,rather,a necessary synthesis
of both overthe projectlife cycle,which is largely absent
from the business and PM literatures (Cook and Brown, 1999).
The bounded planning ofcomplex projectswas implicitly
recognisedin GovCo-1,by acknowledgingthe needfor
exploratory projectsto createintermediateknowledgethat
reduced overall knowledge uncertainty before undertaking major
projects (Lenfle and Loch, 2010), as observed by a Programme
Manager in GovCo-1:
[In ProjectX], if the company had undertaken pre-tender
shutdowns for a month to completely flesh-out the design …
it would have been better for the project. In [Project Y], they
did better pre-tender site investigations … so that, when the
contractorhit the site,therewereless surprises,delay,
disruption, and cost.
In normativeterms,if complex projectsare limited to
bounded planning,this recallsEisenhower'saphorism that
“plansare worthless,but planning iseverything”,2 which
suggests that Eisenhower felt that abstract ‘known’ knowle
in plansmay notbe capable ofmapping complex military
environmentsor adequate forcoordinating a response to a
changing complex environment. This might be better achie
throughthe ‘knowing’knowledgeof the lived planning
process,which impliesthatknowledgeability isdifficultto
separate from knowing subjects.Borrowing from Eisenhower
for organisations,this papersuggests that‘organisations are
nothing butorganising is everything’.And because organisa-
tions are aboutorganising and sense-making (Weick,1979,
1995),this papersupportsthe view thatsense-making in
projectsas temporary organisationsoccurslargely through
learning based on problem solving (Lundin and Söderholm,
1995;Packendorff,1995).As a manifestation ofdistributed
organising and learning from the data, the project manage
office arrangementsin GovCo-1 often changed during the
2000s,becausedelivering complex projectsleading to the
developmentof new PM expertise was more emergentthan
deliberate,althoughit was plannedon its own terms
(Mintzberg,1990;Okhuysen and Eisenhardt,2002).In this
community oflearners approach to learning and organising
based on organisationalCPS, complex PM is “as much about
doing in order to think as thinking in order to do” (Mintzber
2004, p. 10).
3.2. The scaffolding of distributed learning and organising
In GovCo 1&2, documented procedures for complex PM d
notexistto the same extentbefore the developmentof their
respective complex PM expertise. Using the lens of structur
agency (Giddens,2007),the value ofthe new documented
procedureswas their structuralrole as ‘scaffolding’for
establishing a consensus for delivering complex projects am
project team members as actors (Bruner, 1986). Over time
facilitated the developmentof PM expertise by coordinating
the behaviourof projectteam membersas a distributed or-
ganisationalpractice (Nightingale and Brady,2011).This was
underpinned by thecreation ofemergentknowledgeby a
dialectical interplay of abstract ‘known’ knowledge (proced
etc.)with contextual‘knowing’knowledge (know-how,etc.)
(Kolb, 1984; Orlikowski, 2002, 2006; Tsoukas, 1996) throug
common will of mutual interest as a distributed tacit dimen
(Polanyi, 1967). As observed by a Project Manager in GovCo
Prior to that[Procedures],if you spoke to any of our staff
about scope, or bills of quantities, or schedules of rates,
were an alien language./…/Afterthis was rolled out[Pro-
cedures] … it became the common language and it supp
the interchange of information.
Nevertheless, experienced project managers in GovCo 1&
appreciatethe limitationsof documentedproceduresand
2 Speech delivered to the NationalDefense Executive Reserve Conference,
Washington, D.C., on 14 November 1957.
1376 T. Ahern et al. / International Journal of Project Management 32 (2014) 1371–1381

understandthat expertknowledgeis embodiedin expert
practitionerswhose expertiseis on display but largely
undocumented (Wittgenstein,1988).In both GovCo 1&2,the
relative ineffability of ‘knowing’ knowledge (know-how,etc.)
compared to ‘known’ knowledge (plans,etc.) often proved to
be an impedimentto the transferof PM expertise without
transferring personnel(Szulanski,1996;von Hippel,1994).
Such individualsfill the missing gapsin documented pro-
cedures for new practitioners, “because they had the reasoning
and thought process of why things were done” in certain ways
in the procedures(ProgrammeManager,GovCo-1).What
remains invisible to the naked eye is the communication of the
tacitdimension of expertknowledge between practitioners at
different levels of expertise, which is driven by a common will
to commune their experiences as a shared identity (Czarniawska-
Joerges, 1989, 1992; Polanyi, 1969).
3.3. Pacing logic for distributed learning and organising
In a practice-oriented approach, delivering complex projects
in GovCo 1&2 that develops PM expertise can be understood
as problem solving cyclesof goals,practice,and learning,
which togetherpromote development(Brown and Duguid,
1991). The project life cycle (PLC) is a defining characteristic
that demarcatesprojectmanagementfrom otherareasof
management(Morris,2002).In this,projectgoal-setting is an
important driver of the means–end process of problem solving
that underpinsthe deliveryof complexprojectsand the
development of PM expertise throughout the project life cycle
(Van de Ven,1992).Accordingly,it is usefulto think of the
PLC as a phased meta-level goal, or metronome, or entrainment
device, which sets the pace for the goal-driven problem solving
and learning thatunderpins the developmentof PM expertise
throughout the project life cycle (Lindkvist et al., 1998; Sayles
and Chandler,1971; Söderlund,2010).This PLC pace-setting
is termed ‘PLC-entrainment’ and is manifest in the tacit pulse
of the traditionalPM process group of goal-setting,planning,
executing,and closure (APM,2012;PMI, 2013),which this
paper reinterprets from the case study data as a learning process
group, basedon problem solving,of goals, formation,
integration, and normalisation (Popper, 1979). When combined
with pace-setting,it appears thatgoals have a Doppler effect
thatfocuses problem solving learning,because approaching
goals have a higher stimulus pitch than the same goals that are
moving away towards completion.
In GovCo 1&2, the latterprocessgroup underpinsthe
development of PM expertise through cycles of goals, practice,
and learning (Enberg et al., 2006; Kreiner, 2002), where PM is
now viewed as an organisationalpractice based on learning
(Wenger, 2001) rather than an applied science (PMI, 2013). If the
projectlife cycle is divided into differentphases (Adams and
Barndt,1983;King and Cleland,1983;PMI, 2013),the
PLC-entrainment triggers in each phase a learning mini-cycle of
goals, formation, integration, and normalisation. This underpins
interactive cycles of PM developmentthrough goals,practice,
learning, and development as an organisational practice in each
phase of the project life cycle. The achievement of this collective
action asa shared commitmentreliesmore on sharing the
experience of collective action than having a shared colle
meaning in itself(Czarniawska-Joerges,1992,p. 33). For
example,people of a similar culture can share the commun
experience of its enactment but can have different interp
of its meaning, resulting in either a broad or narrow chur
GovCo 1&2,the developmentof a common willof mutual
interestas a distributed tacitdimension (Polanyi,1967)was
fostered around projectgoals thatwere challenging forboth
organisations.This enabled the convergence of multiple mea
ings,or “subuniversesof meaning” (Bergerand Luckmann,
1967,p. 86),to a narrow distribution around agreed projec
targets,which was paced by the PLC-entrainmentof ongoing
project delivery.
3.4. Fostering a common will of mutual interest
Using the lens of tacit foreknowledge, a complex probl
one that is unspecifiable, except in outline or in part, whi
be held in common by a group of people. Its detailed solu
generally notknown in advancebut, rather,relieson an
emergentdistributed foreknowledge thatis marshalled by a
commonwill of mutualinterestthatis not reducibleto
individuals(Kogutand Zander,1992).A key aspectof a
‘common will’lies in its mutualbottom–up characterrather
than in a collective top–down characterisation (Hedlund,
The latter can assume a logical sequence from family to c
society,where the individualcan become subservientto the
transcendent ‘will’ of the collective with ethical implicatio
an institutional nature (DiMaggio and Powell,1991; Giddens,
2007).Unlike Adam Smith's (1981)‘invisible hand’,which
promotes the common good through uncoordinated self-
a common will of mutual interest is more like a ‘team spi
promotes a mutual interest through coordinated actions
achieving explicit common goals.
Fostering a common will around a challenging mutual g
and pacing this common willtowards achieving the mutual
objective are two separate butcrucialingredients foroverall
projectsuccessin complex organisationalsettings.A good
exampleof this from the historicalrecordis President
Kennedy's exhortation to the American people in 19623 to
commit themselves to the tasks of sending a man to the
and back safely by the end of the decade, “not because t
easy, but because they are hard, because that goal will s
organize and measure the best of our energies and skills
challenging complex projectwas achieved in 1969.In both
GovCo 1&2, ramping-up to deliver complex projects that
the developmentof a new PM expertise wasalso a steep
organisationalchallenge whose realisation was grounded in
common will that was fostered around project goals and
by the projectlife cycle through strong communalleadership
(Enberg etal., 2006;Kreiner,2002;Söderlund,2010).The
latterhelped to create“a level of harmony and common
purpose in the team as a whole” (Project Manager, GovC
3 Speechdeliveredat Rice University,Houston,Texas,USA, on 12
September 1962.
1377T. Ahern et al. / International Journal of Project Management 32 (2014) 1371–1381

In addition,ongoing projectteam meetings in GovCo 1&2
served to maintain the entrainment of a common will of mutual
interest as a shared commitment in project goals by participants
re-enacting their experience of delivering projects for others to
absorb as a shared virtualexperience (Czarniawska-Joerges,
1989, 1992). This shared commitment was best summed up by
a Programme Manager in GovCo-1 as “the sense of ‘we're in
this together!”.
In this entrainment aspect of delivering complex projects in
GovCo 1&2, Adam Smith's (1981) ‘invisiblehand’ is
harnessed as the servant of a ‘common will’, where the former
is implicitand the latterexplicitand togetherthey actas a
higher-orderorganising principle (Kogutand Zander,1992).
This distributed coordination of complex knowledge seems to
operate through what Polanyi (1967) calls “mutual control” (p.
72). This involves self-discipline through the mutual authority
of participating in thegovernancestructurefor delivering
complex projectsand self-coordination through themutual
adjustmentbetween projectteam members(Polanyi,1969).
This complementarybehaviouralapproachresonateswith
Kant's (1983)idea of‘unsocialsociability’.In this apparent
oxymoron,the implicit and unsocial‘invisiblehand’ of
individual self-interest becomes the hand-maiden of the social
endeavour of delivering complex projects through a common
will of mutualinterest,which is entrained around explicit
project goals.
4. Implications for future research and practice
Much research on complex PM takesa traditionalPM
systemsapproach,wherecomplex projectsare viewed as
complicated projects with full pre-given knowledge available at
the outsetand where complexity impactsprimarily on the
implementation ofthe projectas a complicated task undera
‘total planning’approach(Shenhar,1998 et seq.). The
mechanical approach in traditional PM assumes little learning
beyond single-loop and double-loop learning,which does not
adequately address the inherentincompleteness of knowledge
in complex PM and the implications of this for research and
practice in PM governance. This ignores the reality of complex
PM settings in GovCo 1&2 and elsewhere,where ‘as-built’
drawings are seldom the same as initialprojectspecifications
(Morris and Hough, 1987). In contrast, the main finding of this
paperis thatcomplex PM is a form oforganisationalCPS,
where a complex project is one that is unable to be completely
specifiedin advance,exceptin outlineor in part.This
alternative perspective means thatknowledge managementin
complex PM is essentially themanagementof knowledge
uncertaintyor incompleteknowledgeunder a ‘bounded
planning’approachwith implied learningas a practice
(Wenger,2001).The rediscovery of Hayek's (1945) ‘specifi-
cation problem’,which underpins knowledge uncertainty as a
persistentaspectof complexity,and its potentialsignificance
for complex PM hasopen-ended implicationsfor ongoing
research and practice.This includesthe following areasof
governance in complex PM — planning,knowledge creation,
and knowledge coordination;leadership;knowledge transfer;
and complexity perspectives.
Beforeexamining theseimplications,it is importantto
acknowledge thatboth the research findingsand theirim-
plications should be considered as tentative at this point, a
are based on a comparative analysis of only two organisati
and will requirefurtherresearch to determinetheirwider
applicability.Nevertheless,the main themes highlighted here
were found to be consistentacrossboth casesand the
methodologicalapproach used in the study is one that is now
well supported in the literature on process research (Eisenh
1989; Pettigrew, 2013; Yin, 2003). Finally, the two case stu
are public sector government organisations for which PM is
core supporting competence ratherthan a core competence.
This may also be a limitation of the findings,pending further
research in project-based organisations in both the public a
private sectors.
4.1. Planning, knowledge creation, and knowledge coordina
For the successfuldelivery of scope, budget,and
timescale in complex projects like those in GovCo 1&2 as
formsof organisationalCPS, a ‘total planning’approach
under traditional PM is found to be untenable and, instead,
distributed approach under ‘bounded planning’ is proposed
for the coordination ofemergentprojectknowledge.The
latteris generated through problem solving as a mode of
learningand organisingthat synthesisesstatic ‘known’
knowledge (plans,etc.) and dynamic ‘knowing’ knowledge
(know-how,etc.) through a process of knowledge interplay
rather than conversion (Kolb,1984;Nonaka and Takeuchi,
1995). However,this approachrequiresa coordinating
mechanism,such as a common willof mutualinterestas a
distributed tacit dimension (Polanyi, 1967), which is fostere
around challenging projectgoals and paced by the project
life cycle (Enberg etal., 2006;Kreiner,2002;Lindkvistet
al., 1998;Söderlund,2010).By acting togetherundera
common will, the project team can know more than it can t
and can know more than its individualmembers can know
separately.
This finding of distributedknowledgeorganisingfor
complex PM extends and develops the socio-technicalview
of organisationsadvanced by Kogutand Zander(1992)as
“social communities in which individual and social expertis
transformed … by the application ofa set of higher-order
organizingprinciples… that are not reduceable[sic] to
individuals”(p. 384,italicsadded).This suggestsresearch
questionsfor PM theory and practice around the nature of
complex PM as an organisational activity and the managem
principles that underpin it,for example,whether complex PM
as strategy is deliberate or emergent (Mintzberg,1987,2004).
The lattercould investigate whethercomplex PM isbetter
viewed asa hierarchicalplanning exercisebased on full
pre-givenknowledgewith little learninganticipatedor,
alternatively, as a creative organisational practice that syn
pre-given ‘known’ knowledge (plans,etc.) with emergentand
1378 T. Ahern et al. / International Journal of Project Management 32 (2014) 1371–1381

newly created ‘knowing’ knowledge (know-how, etc.) over the
project life cycle.
4.2. Leadership
The need fora common willof mutualinterestfor the
distributed coordination ofcomplex projectknowledgein
GovCo 1&2 gave rise to a concurrent need for distributed PM
leadership to foster a common willaround projectgoals and
pace itusing the projectlife cycle (Lindkvistet al., 1998;
Söderlund,2010).By viewing complex PM as organisational
practicewith implied learningbecauseof unspecifiable
knowledgeat the outset,this suggeststhatleadership in
complex PM is about leading by consensus to deliver projects
by learning the project as a community of learners rather than
simply leading ateam oftechniciansby authority in the
application ofprior knowledge(Engwall,2002;Lindkvist,
2005).Over the projectlife cycle,this creates the contextual
knowledge that is unspecifiable at the outset,because it is not
given to anybody in its totality butto the projectteam as a
whole (Hayek, 1945). In GovCo 1&2, this leadership style was
a hybrid of top–down and bottom–up (Hedlund, 1994; Turner
and Müller,2005),which infused with communalvalue the
efforts of team members beyond the achievement of immediate
project goals (Selznick, 1957).
The findings in this study point to a new direction for future
research into the determinants of leadership effectiveness in the
areaof complex PM.In particular,futureresearch might
investigate more closely the kinds of non-hierarchical modes of
leadership that are most likely to be effective in the context of
complex PM,where the limitations of a traditionalcommand
and controlapproachto managementand leadership,as
highlighted above,are so readily apparent.In this regard,
such future studies might be fruitfully built upon a conceptual
framework thatdraws upon Polanyi's (1967,1969) insightof
‘mutualcontrol’,which is a distributed tacitforeknowledge
based on the twin principles of self-discipline through mutual
authority and self-coordination through mutual adjustment.
4.3. Knowledge transfer
The research on which this paper is based also encountered
the perennial difficulty of knowledge transfer between complex
projects in GovCo 1&2 withoutalso transferring personnel.
This difficulty flowsdirectly from thePositivistideal of
abstract ‘known’ knowledge that is detached from the knower,
which underpinsthe centralisedapproachto knowledge
managementin traditionalPM that downplayscontextual
‘knowing’ knowledge and the tacitdimension of knowledge.
However,building on Lindkvist's (2005) approach of distrib-
uted knowledge in PM as a ‘collectivity of practice’, knowledge
management in complex PM under ‘bounded planning’ can be
researched as a community of learners with inherent knowledge
uncertainty.This communityof projectpractice(CoPP)
approach could be used to examine more closely the nature of
the knowledge formation process and how this might vary over
the project life cycle by drawing on the temporal perspective of
knowledge creation offered by this paper.This is based on a
dialecticalinterplay between ‘knowing’knowledge(know-
how,etc.) and ‘known’ knowledge (plans,etc.) (Kolb,1984),
underpinnedby a commonwill of mutualinterestas a
distributed tacit dimension (Polanyi,1967).The latter ensures
a convergence on projectgoalsthrough the self-organising
propertiesof problem solving asa processof knowledge
formation based on tacitforeknowledge thatcan be paced by
the project life cycle.
4.4. Complexity perspectives
The main finding of complex PM as a form of organisat
CPS also suggests that the PM complexity spectrum can b
in terms of knowledge complexity rather than systems co
(Cleland and King,1968),Fig. 1. This hasimplicationsfor
leadershipand processin complexPM by substitutinga
knowledge-based view ofPM as a heterarchicalprocessof
knowledge formation (Hedlund, 1994) for the traditional view of
PM as a hierarchical process based on the application of p
knowledge (PMI,2013).Furthermore,by adopting a distributed
approach to knowledge management as proposed by this
complex PM,traditionalPM can ground itselfin a modelof
socio-technicalrationality,or projects as ‘rationalactors’,rather
than pure technicalrationality,or projects as ‘rationalobjects’.
Holistically,then,the PM complexity spectrum from tradition
PM to complex PM can be approached as a continuous ra
domain for the managementof projects when viewed as social
science, like neo-classical economics, rather than applied
like robotics (Morris,1997;Williams,2005).Furtherresearch
studies could elucidate more fully the subsets of this holi
spectrum and the implications of their knowledge charac
for knowledge management across the PM spectrum.
References
Adams, J., Barndt, S., 1983. Behavioral implications of the project life cy
Cleland,D.I., King, W.R. (Eds.),ProjectManagementHandbook.Van
Nostrand, New York, pp. 222–244.
Ahern,T., 2013.The Developmentof ProjectManagementCapability in
Complex OrganisationalSettings:Towardsa Knowledge-Based View.
Unpublished PhD Thesis. Dublin City University, Ireland.
APM, 2011. Directing Change: A Guide to Governance of Project Manage
second ed. Association for Project Management, Princes Risborough,
UK.
APM, 2012.APM Body of Knowledge,sixth ed.Association forProject
Management, Princes Risborough, Bucks., UK (Orig. 1992).
Argyris,C., 1977.Double loop learning in organizations.Harvard Business
Review 55 (5), 115–125.
Argyris,C., Schön,D.A., 1996.OrganizationalLearning I:Theory,Method,
and Practice. Addison-Wesley, Reading, MA.
Ashby, W.R., 1956. An Introduction to Cybernetics. Chapman & Hall, Lon
Baccarini,D., 1996.The conceptof projectcomplexity— a review.
International Journal of Project Management 14 (4), 201–204.
Berger, P.L., Luckmann, T., 1967. The Social Construction of Reality: A T
in the Sociology of Knowledge. Anchor Books, New York.
Berggren, C., Järkvik, J., Söderlund, J., 2008. Lagomizing, organic integra
systems emergency wards: innovative practices in managing comple
development projects. Project Management Journal 39, S111–S122 (S.
Boulding,K.E., 1956.Generalsystemstheory:the skeleton ofscience.
Management Science 2 (3), 197–208.
1379T. Ahern et al. / International Journal of Project Management 32 (2014) 1371–1381

Brown,J.S., Duguid,P., 1991.Organizationallearning and communities-of-
practice:toward a unified view ofworking,learning,and innovation.
Organization Science 2 (1), 40–57.
Brown,S.L., Eisenhardt,K.M., 1997.The artof continuous change:linking
complexitytheoryand time-pacedevolutionin relentlesslyshifting
organizations. Administrative Science Quarterly 42 (1), 1–34.
Bruner,J., 1986.ActualMinds,Possible Worlds.Harvard University Press,
MA.
Burns,T., Stalker,G.M., 1961.The Managementof Innovation.Tavistock,
London.
Churchman,C.W., 1967.Wicked problems.ManagementScience 14 (4),
B141–B142.
Cleden, D., 2009. Managing Project Uncertainty. Gower, Farnham, UK.
Cleland,D.I., King,W.R.,1968.Systems Analysis and ProjectManagement.
McGraw Hill, New York.
Cook, S.D.N., Brown,J.S., 1999.Bridging epistemologies:the generative
dancebetween organizationalknowledgeand organizationalknowing.
Organization Science 10 (4), 381–400.
Cooke-Davies, T.J., Cicmil, S., Crawford, L., Richardson, K., 2007. We're not
in Kansas anymore,Toto:mapping the strange landscape ofcomplexity
theory,and its relationship to projectmanagement.ProjectManagement
Journal 38 (2), 50–61.
Czarniawska-Joerges,B., 1989.Toward an anthropology of complex organi-
zations. International Studies of Management & Organization 19 (3), 3–15.
Czarniawska-Joerges, B., 1992. Exploring Complex Organizations: A Cultural
Perspective. Sage, Newbury Park, CA.
Daft, R.L., Weick, K.E., 1984. Toward a model of organizationsas
interpretation systems. Academy of Management Review 9 (2), 284–295.
Davies, A., Hobday, M., 2005. The Business of Projects: Managing Innovation
in Complex Products and Systems. Cambridge University Press, UK.
Dewey, J., 1966. Democracy and Education: An Introduction to the Philosophy
of Education. Free Press, New York (Orig. 1916).
Dewey,J., Bentley,A.F., 1949.Knowing and the Known.Beacon Press,
Boston.
DiMaggio,P.J., Powell, W.W., 1991. Introduction.In: Powell, W.W.,
DiMaggio, P.J. (Eds.), The New Institutionalism inOrganizational
Analysis. University of Chicago Press, IL, pp. 1–38.
Eisenhardt, K.M., 1989. Building theories from case study research. Academy
of Management Review 14 (4), 532–550.
Eisenhardt,K.M., 1999. Strategyas strategicdecisionmaking.Sloan
Management Review 40 (3), 65–72.
Enberg, C., Lindkvist, L., Tell, F., 2006. Exploring the dynamics of knowledge
integration: acting and interacting in project teams. Management Learning
37 (2), 143–165.
Enberg, C., Lindkvist, L., Tell, F., 2010. Knowledge integration at the edge of
technology:on teamwork and complexity in new turbine development.
International Journal of Project Management 28 (8), 756–765.
Engwall, M., 1998. The project concept(s): on the unit of analysis in the study
of projectmanagement.In: Lundin,R.A., Midler,C. (Eds.),Projects as
Arenas for Learning and Renewal. Kluwer, Boston, pp. 25–35.
Engwall, M., 2002. The futile dream of the perfect goal. In: Sahlin-Andersson, K.,
Söderholm, A. (Eds.), Beyond Project Management: New Perspectives on the
Temporary–Permanent Dilemma. Liber Abstrakt, Copenhagen, pp. 261–277.
Engwall,M., 2003.No projectis an island:linking projects to history and
context. Research Policy 32 (5), 789–808.
Geraldi, J., Maylor, H., Williams, T., 2011. Now, let's make it really complex
(complicated):a systematicreview of the complexitiesof projects.
InternationalJournalof Operations& Production Management31 (9),
966–990.
Giddens,A., 2007.The Constitution ofSociety:Outline ofthe Theory of
Structuration. Polity Press, Cambridge, UK (Orig. 1984).
Hayek,F.A., 1945.The use ofknowledge in society.American Economic
Review 35 (4), 519–530.
Hedlund,G., 1994.A model of knowledge managementand the N-form
corporation. Strategic Management Journal 15, 73–90 (Summer).
Jugdev, K., Müller, R., 2005. A retrospectivelook at our evolving
understanding ofprojectsuccess.ProjectManagementJournal36 (4),
19–31.
Kant, I., 1983. Idea for a universal history with a cosmopolitan intent. In: K
I. (Ed.), Perpetual Peace and Other Essays. Hackett, Indianapolis, pp. 29
(Orig. 1784).
King, W.R., Cleland,D.I., 1983.Life cycle management.In: Cleland,D.I.,
King, W.R. (Eds.),ProjectManagementHandbook.Van Nostrand,New
York, pp. 209–221.
Knight, F.H., 1935. Risk, Uncertainty and Profit. Houghton Mifflin, New York
(Orig. 1921).
Kogut, B., Zander, U., 1992. Knowledge of the firm, combinative capabilitie
and the replication of technology. Organization Science 3 (3), 383–397.
Kolb, D., 1984.Experiential Learning: Experience as the Source of Learning
and Development. Prentice Hall, Upper Saddle River, NJ.
Kreiner, K., 2002. Tacit knowledge management: the role of artifacts. Journ
Knowledge Management 6 (2), 112–123.
Lawrence, P.R., Lorsch, J.W., 1967. Organization and Environment: Managi
Differentiation and Integration. Harvard University Press, Boston.
Lenfle,S., Loch, C., 2010.Lost roots:how projectmanagementcame to
emphasize controloverflexibility and novelty.California Management
Review 53 (1), 32–55.
Lindkvist,L., 2005.Knowledge communities and knowledge collectivities:a
typology of knowledge work in groups. Journal of Management Studies
(6), 1189–1210.
Lindkvist,L., Söderlund,J., Tell, F., 1998.Managing productdevelopment
projects:on the significanceof fountainsand deadlines.Organization
Studies 19 (6), 931–951.
Linehan,C., Kavanagh,D., 2006.From project ontologies to communities of
virtue.In: Hodgson,D., Cicmil, S. (Eds.),Making ProjectsCritical.
Palgrave, Basingstoke, UK, pp. 51–67.
Lundin,R.A., Söderholm,A., 1995.A theory of the temporary organization.
Scandinavian Journal of Management 11 (4), 437–455.
March,J.G., 1994.The evolution of evolution.In: Baum,J.A.C., Singh,J.V.
(Eds.), Evolutionary Dynamics of Organizations. Oxford University Press
New York, pp. 39–49.
Meyerson,D., Weick,K.E., Kramer,R.M., 1996.Swifttrustand temporary
groups. In: Kramer, R.M., Tyler, T.R. (Eds.), Trust in Organizations. Sage
Thousand Oaks, CA, pp. 166–195.
Miller,R., Hobbs,B., 2005.Governance regimes for large complex projects.
Project Management Journal 36 (3), 42–50.
Mintzberg,H., 1979.The Structuring ofOrganizations:A Synthesis ofthe
Research. Prentice-Hall, Englewood Cliffs, N.J.
Mintzberg,H., 1987.Crafting strategy.Harvard BusinessReview 65 (4),
66–75.
Mintzberg,H., 1990.The design school:reconsidering the basic premises of
strategic management. Strategic Management Journal 11 (3), 171–195.
Mintzberg, H., 2004. Managers not MBAs: A Hard Look at the Soft Practice
Managing and Management Development. Prentice Hall, London.
Morris,P.W.G.,1997.The Managementof Projects.Telford,London (Orig.
1994).
Morris, P.W.G., 2002. Science, objective knowledge and the theory of proje
management. Proceedings of the Institution of Civil Engineers (ICE), UK
Civil Engineering 150, 82–90.
Morris, P.W.G., Hough, G., 1987. The Anatomy of Major Projects: A Study o
the Reality of Project Management. Wiley, New York.
Müller, R., 2009. Project Governance. Gower, Farnham, UK.
Mumford,E., 1998. Problems,knowledge,solutions:solving complex
problems. The Journal of Strategic Information Systems 7 (4), 255–269.
Munns,A., Bjeirmi,B., 1996.The role of projectmanagementin achieving
project success. International Journal of Project Management 14 (2), 81.
NDP, 2000.NationalDevelopmentPlan 2000–2006.The Stationery Office,
Dublin.
NDP, 2007.NationalDevelopmentPlan 2007–2013.The Stationery Office,
Dublin.
Newell,A., Simon,H.A., 1972.Human Problem Solving.Prentice-Hall,
Englewood Cliffs, NJ.
Nightingale,P., Brady,T., 2011.Projects,paradigms and predictability.In:
Cattani,G., Ferriani,S., Frederiksen,L., Täube,F. (Eds.),Project-Based
Organizing and Strategic Management: Advances in Strategic Managem
vol. 28. Emerald, Bingley, UK, pp. 83–112.
1380 T. Ahern et al. / International Journal of Project Management 32 (2014) 1371–1381

Nonaka,I., Takeuchi,H., 1995.The Knowledge-Creating Company.Oxford
University Press, New York.
Okhuysen,G.A., Eisenhardt,K.M., 2002.Integrating knowledge in groups:
how formalinterventions enable flexibility.Organization Science 13 (4),
370–386.
Orlikowski, W.J., 2002. Knowing in practice: enacting a collective capability in
distributed organizing. Organization Science 13 (3), 249–273.
Orlikowski, W.J., 2006. Material knowing: the scaffolding of human knowledge-
ability. European Journal of Information Systems 15 (5), 460–466.
Packendorff, J., 1995. Inquiring into the temporary organisation: new directions
for project management research. Scandinavian Journal of Management 11
(4), 319–333.
Parkin,J., 1996.Organizationaldecision making and the projectmanager.
International Journal of Project Management 14 (5), 257–263.
Pemsel,S., Müller,R., 2012.The governance of knowledge in project-based
organizations.InternationalJournal of Project Management30 (8),
865–876.
Pepper,S.C., 1942.World Hypotheses:A Study in Evidence.University of
California Press, Berkeley, CA.
Pettigrew,A.M., 1990.Longitudinalfield research on change:theory and
practice. Organization Science 1 (3), 267–292.
Pettigrew,A.M., 1997.Whatis processualanalysis? Scandinavian Journalof
Management 13 (4), 337–348.
Pettigrew, A.M., 2012. Context and action in the transformation of the firm: a
reprise. Journal of Management Studies 49 (7), 1304–1328.
Pettigrew,A.M., 2013.The conductof qualitative research in organizational
settings. Corporate Governance: An International Review 21 (2), 123–126.
PMI, 2013.A Guide to the ProjectManagementBody of Knowledge
(PMBOK® Guide), fifth ed. Project Management Institute, Newton Square,
PA (Orig. 1987).
Polanyi, M., 1967. The Tacit Dimension. Doubleday, Garden City, NY.
Polanyi,M., 1969.Knowing and Being.In: Grene,M. (Ed.),University of
Chicago Press, IL.
Polanyi,M., 1974.Personal Knowledge: Towards a Post-Critical Philosophy.
University of Chicago Press, IL (Orig. 1962).
Pollitt,C., Bouckaert,G., 2000.Public Management Reform: A Comparative
Analysis. Oxford University Press, Oxford.
Popper, K.R., 1979. Objective Knowledge: An Evolutionary Approach. Oxford
University Press, London (Orig. 1972).
Ramo,S., 1969.The Cure forChaos:Fresh Solutions to SocialProblems
Through the Systems Approach. McKay, New York.
Sapolsky,H.M., 1972.The Polaris System Development:Bureaucratic and
Programmatic Success in Government. Harvard University Press, MA.
Sayles,L., Chandler,M., 1971. The projectmanager:organizational
metronome. In: Sayles, L., Chandler, M. (Eds.), Managing Large Systems.
Harper & Row, New York, pp. 204–226.
Saynisch,M., 2010a.Beyond frontiers oftraditionalprojectmanagement:an
approach to evolutionary,self-organizationalprinciples and the complexity
theory — results of the research program. Project Management Journal 41 (2),
21–37.
Saynisch, M., 2010b. Mastering complexity and changes in projects, economy,
and societyvia projectmanagementsecondorder (PM-2). Project
Management Journal 41 (5), 4–20.
Selznick, P., 1957. Leadership in Administration: A Sociological Interpretation.
Harper & Row, New York.
Shenhar,A.J., 1998.From theory to practice:toward a typology of project-
management styles. IEEE Transactions on Engineering Management 45 (1),
33–48.
Shenhar,A.J., 2001.One size does notfit all projects:exploring classical
contingency domains. Management Science 47 (3), 394–414.
Shenhar,A.J., Dvir, D., 1996.Towardsa typologicaltheory ofproject
management. Research Policy 25 (4), 607–632.
Shenhar,A.J., Dvir,D., Shulman,Y., 1995.A two-dimensional taxonomy of
productsand innovations.Journal of Engineeringand Technology
Management 12 (3), 175–200.
Shenhar, A., Dvir, D., Lechler, T., Poli, M., 2002. One size does not fit all
projects, true for frameworks. PMI Research Conference, Seattle, Wa
Siggelkow,N., 2007.Persuasion with case studies.Academy of Management
Journal 50 (1), 20–24.
Simon, H.A., 1997. Administrative Behavior. Free Press, New York (Orig.
Smith, A., 1981. The Wealth of Nations. Penguin, Harmondsworth, UK (O
1776).
Snowden,D., 2002.Complex acts of knowing:paradox and descriptive self-
awareness. Journal of Knowledge Management 6 (2), 100–111.
Söderlund, J., 2010. Knowledge entrainment and project management:
of large-scaletransformation projects.InternationalJournalof Project
Management 28 (2), 130–141.
Spinardi,G., 1994.From Polaris to Trident:The Developmentof US Fleet
Ballistic Missile Technology. Cambridge University Press, UK.
Swinth, R.L., 1971. Organizationaljoint problem-solving.Management
Science 18 (2), B68–B79.
Szulanski, G., 1996. Exploring internal stickiness: impediments to the tr
of bestpractice with the firm.Strategic ManagementJournal17,27–43
(Winter).
Teece,D.J., Pisano,G., Shuen,A., 1997.Dynamic capabilities and strategic
management. Strategic Management Journal 18 (7), 509–533.
Thompson,J.D., 1967.Organizationsin Action: SocialScience Basesof
Administrative Theory. McGraw-Hill, New York.
Tsoukas, H., 1996. The firm as a distributed knowledge system: a const
approach. Strategic Management Journal 17, 11–25 (Winter).
Turner,J.R., Müller,R., 2005.The projectmanager's leadership style as a
success factor on projects: a literature review. Project Management J
36 (2), 49–61.
Van de Ven, A.H., 1992. Suggestions for studying strategy process: a re
note. Strategic Management Journal 13, 169–188 (Summer).
von Bertalanffy, K.L., 1950. An outline of general system theory. The Br
Journal for the Philosophy of Science 1, 139–164.
von Hippel,E., 1994.“Sticky information” and the locus of problem solving
implications for innovation. Management Science 40 (4), 429–439.
Weick, K.E., 1979. The Social Psychology of Organizing. McGraw-Hill, Ne
York (Orig. 1969).
Weick,K.E., 1993.The collapse of sensemaking in organizations:the Mann
Gulch disaster. Administrative Science Quarterly 38 (4), 628–652.
Weick, K.E., 1995. Sensemaking in Organizations. Sage, Thousand Oaks
Weick,K.E., Roberts,K.H., 1993.Collective mind in organizations:heedful
interrelating on flightdecks.Administrative Science Quarterly 38 (3),
357–381.
Weinberg,G.M., 2001.An Introduction to General Systems Thinking. Dorset
House, New York.
Wenger, E., 2001. Communities of Practice: Learning, Meaning, and Iden
Cambridge University Press, UK (Orig. 1998).
Whitehead,A.N., 1985.Process and Reality:An Essay in Cosmology.Free
Press, New York (Orig. 1929).
Whitty,S.J., Maylor,H., 2009.And then came complex project management
(revised). International Journal of Project Management 27 (3), 304–31.
Williams,T.M., 1999.The need fornew paradigms forcomplex projects.
International Journal of Project Management 17 (5), 269–273.
Williams,T., 2005.Assessing and moving on from the dominantproject
management discourse in the light of project overruns. IEEE Transac
on Engineering Management 52 (4), 497–508.
Wittgenstein, L., 1988. Philosophical Investigations. Blackwell, Oxford (O
1953).
Yin, R.K., 2003.Case Study Research:Design and Methods,third ed.Sage,
Thousand Oaks, CA.
1381T. Ahern et al. / International Journal of Project Management 32 (2014) 1371–1381
View publication statsView publication stats