Complex adaptive system mechanisms, adaptive management practices, and firm product innovativeness

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Complex adaptive system
mechanisms, adaptive
management practices, and
firm product innovativeness
Ali E. Akgün1, Halit Keskin2, John C. Byrne3 and
Özgün Ö. Ilhan4
1

Science and Technology Studies, Gebze Institute of Technology, Gebze- Kocaeli, Turkey.
aakgun@gyte.edu.tr; alieakgun@gmail.com
2
keskin@gyte.edu.tr
3
Lubin School of Management, Pace University, New York, New York, USA. jcbyrne@optonline.net
4
oozturk@gyte.edu.tr

As a fascinating concept, the mechanisms of complex adaptive system (CAS) attracted many
researchers from a variety of disciplines. Nevertheless, how the mechanism-related variables, such as strategic resonance, accreting nodes, pattern forming, and catalytic behavior
of organization, impact the firm product innovativeness is rarely addressed empirically in
the new product development (NPD) literature. Also, there exist limited studies on the
antecedents of the mechanisms of CAS in the NPD literature. In this respect, we identified
and operationalized the adaptive management practices, which involve bonding, nonlinear,
and attractor behaviors of management, as antecedents of mechanisms and firm product
innovativeness. By studying 235 firms, we found that (1) strategic resonance and accreting
nodes are positively related to firm product innovativeness, (2) bonding, nonlinear, and
attractor behaviors of management positively influence the mechanism variables, and (3)
market and technology turbulence impact the adaptive management practices. We also
found that mechanisms of CAS partially mediate the relationship between adaptive management practices and firm product innovativeness.

1. Introduction

C

hanging trends in technology and customer
needs in turbulent and unpredictable environments require firms to become more aware of their
adaptability for sustainable competitive advantage
in general, and the development of successful new
products, product innovativeness, in particular
18

(Hansen and Serin, 1993). In this sense, scholars
emphasize the importance of complex adaptive
systems (CAS) view, which in general indicates a
system that emerges over time into a coherent form,
and adapts and organizes itself without any singular
entity deliberately managing or controlling it
(Holland, 1995; Buckley, 2008), to gain insights for
successful product development efforts under the
© 2013 RADMA and John Wiley & Sons Ltd

System mechanisms, management practices, and firm product innovativeness
turbulent environmental conditions in the new
product development (NPD) literature (Brown
and Eisenhardt, 1998; McCarthy et al., 2006). For
instance, McCarthy et al. (2006, p. 439) wrote that
‘[a] CAS framework views individual NPD processes
as adaptable or malleable systems capable of producing a range of behaviors to suit different innovation
expectations, levels of market uncertainty, and rates
of change’. Nevertheless, studies on the CAS in the
NPD context are limited, and most of them are theoretical arguments on how the CAS view is generally
applied to product development process or stages
(e.g., Cunha and Comes, 2003; Chiva-Gomez, 2004;
McCarthy et al., 2006). While these studies show
how a CAS works in product development efforts in
projects or organizations, we need a greater understanding of the enabling conditions and the mechanisms of CAS in particular to adequately examine or
exploit the viewpoints of its theory. The mechanisms
of CAS in general indicate the dynamic behaviors
that produce complex outcomes, such as innovation,
as found in the management literature (Uhl-Bien
and Marion, 2009). The mechanisms of CAS enable
people, groups, or departments in the organization to
move beyond thinking about individualistic efforts
(Harkema, 2003; Buffington and McCubbrey, 2011),
and offer them a way to generate an understanding of
the dynamic practices and processes to implement
adaptiveness during product development activities
(Garud et al., 2011). However, given the importance
of mechanisms of CAS, interestingly, little attention
was given to the operationalization and the empirical
implications or validation of these mechanismrelated variables on the success of new products in
the NPD context. In this respect, Pathak et al. (2007,
p. 564) also wrote:
A model of CAS behavior should precisely
state how to measure the relevant constructs,
how the constructs are related, and how certain
mechanisms affect those constructs. Only
when these issues are clearly stated can the
theory be validated and examined for consistency with the phenomena under study across a
wide range of situations.
Also, from a managerial point of view, a study on the
antecedents or drivers of the mechanisms is missing
– which warrants an empirical analysis, in addition to
the consequence of mechanisms on firm product
innovativeness.
To solve the above issues, we primarily adapt the
CAS model of Uhl-Bien et al. (2007), which provides a theoretical framework for mechanism of
CAS. It should also be noted that while the CAS

model of these authors is argued in the leadership
context (i.e., at the individual level), it is highly
abstract, implicit, and not operationalized. We leverage their views to an organizational level and in the
product innovation context. Here, mechanisms of
CAS are the dynamic behaviors, processes, and practices that occur within the product development
efforts to leverage the firm innovativeness. The
mechanisms of CAS include resonance (i.e., agents
acting in concert), accreting nodes (i.e., the collection of many small ideas and inputs that rapidly
expand in importance), pattern formation (i.e., adaptive and dynamic interpretations of events and situations), and catalytic behaviors (i.e., behaviors that
speed up or enable certain activities) (Uhl-Bien
et al., 2007). For antecedents of the CAS mechanisms, based on the complexity leadership (CL)
theory of Uhl-Bien and Marion (2009), we use the
‘adaptive management’ practices. The rational is
that an adaptive management perspective does not
restrict management with hierarchical positions or
roles; instead, it views management as a key element
of the organizing process in adaptive efforts throughout the organization, such that adaptive management
can be viewed as a social influence practice and
behavior of management through which emergent
coordination (i.e., evolving social order) and change
(e.g., new values, attitudes, approaches, behaviors,
and ideologies) are constructed and produced to
cope with turbulent conditions in the CL perspective
(Brown and Eisenhardt, 1998; Uhl-Bien et al.,
2007). Based on the theoretical study of Uhl-Bien
and Marion (2009), we operationalize adaptive management as practices involving bonding behavior
(i.e., creating dynamic linkages and interactions),
nonlinear behavior (e.g., derived by an asymmetrical, dynamic, and chaotic attitude), and attractor
behavior (i.e., acting as tags and creating attractors)
of management.
Therefore, the aim of this study is to operationalize
and empirically test the impact of mechanisms of
CAS and adaptive management practices on firm
product innovativeness to further enhance the
literature on organizational innovation and complexity science. Also, this study attempts to improve
the precision of CAS and CL theories through
expanding and refining their existing theoretical
conceptualizations in the innovation context.
Specifically, as shown in Figure 1, this study investigates (1) the role of mechanism variables on
firm product innovativeness, (2) the impact of the
adaptive management practices on the mechanism
variables, (3) the mediator role of mechanisms
of CAS between adaptive management practices
and firm product innovativeness, and (4) the
R&D Management 44, 1, 2014

19

Ali E. Akgün, Halit Keskin, John C. Byrne and Özgün Ö. Ilhan

H9

Adaptive management practices
• Bonding behavior
• Nonlinear behavior
• Attractor behavior

Env. turbulence
• Market
• Technology

H8 (mediator)
Firm product
innovativeness

H5-H7

H10

•
•
•
•

Mechanisms of CAS
Strategic resonance
Accreting nodes
Pattern formation
Catalytic behavior

H1-H4
Control variables
• Size
• Age
• Industry

Figure 1. Proposed model. CAS, complex adaptive system.

triggering/enhancer role of environmental turbulence
(including market and technology turbulence) on
the adaptive management practices and mechanism
variables.

2. Mechanisms of CAS and adaptive
management practices
The mechanisms of CAS show the necessary conditions under which complex and dynamic behavior
will occur in organizations, and include resonance,
accreting nodes, pattern formation, and catalytic
behavior (Uhl-Bien et al., 2007). Resonance, following CAS researchers, for example, Uhl-Bien et al.
(2007, p. 308), is defined as ‘acting in concert . . .
more specifically to situations in which the behaviors
of two or more agents are interdependent’. In the
innovation management literature, a similar definition of resonance can be found in the study of Brown
and Fai (2006), addressing the automobile and computing industries, and is labeled as ‘strategic resonance’. Here, we believe that the well-established
concept of ‘strategic resonance’ can be applied to the
product innovation efforts in the organization and can
illuminate the abstract definition of resonance in the
CAS literature. Brown and Fai (2006), for instance,
mention that strategic resonance is a dynamic,
organic, ongoing, and strategic process that is about
ensuring continuous linkages and harmonization
between the market and the firm’s operation capabilities, firm’s strategy and its operations capabilities,
and within all functions and all levels within the firm.
Another mechanism variable is the accreting
nodes. Accreting nodes indicate the notion of ideas
that rapidly expand in importance and which accrete
20


related ideas (Uhl-Bien et al., 2007, p. 308).
Pavlovich (2009) expands that notion of accreting
nodes based on the unfoldment/enfoldment principle
of information or knowledge, and mentions that
accreting nodes indicate the self-organization and
reciprocal creation of ideas, information, and knowledge. Here, the idea is that information/knowledge
is developed and self-regulated through a procedural
memory and transactive memory system (Boal and
Schultz, 2007). No matter how much information/
knowledge is developed, core information/knowledge is inherent in each, despite an ongoing flow
and change of components (Pavlovich, 2009). Within
this process, new information/knowledge evolve
through complex, flexible, and nonlinear modes of
self-organization in an organizational and learning
context as can be seen in the fuzzy front end or
concept development stages of the product development process (Reid and de Brentani, 2004). Scholars
(e.g., Cacioppe and Edwards, 2005; Boal and
Schultz, 2007; Pavlovich, 2009) note that accreting
nodes are manifested in organizations through how
an idea or information/knowledge (1) is magnified
iteratively or successively, as in a recurring growth
pattern, (2) proceeds through self-consistency and
fancy complementary beliefs, and (3) reweaves
through the web of organizational metaphors, stories,
symbols, and rhymes.
Pattern formation is another mechanism of CAS.
It illustrates the process of crystallizing ideas, and
making sense of events, information, and complex
situations in the organization and its environment,
to enhance the explanatory and/or design capability
of people (Kurtz and Snowden, 2003). It is obvious
that this definition of pattern formation is broad
and overlaps with the definition of ‘organizational

sensemaking’ (Weick, 1995). In this regard, we
adapted the concept of ‘patterning of attention’ from
Hunt et al. (2009) and Osborn et al. (2002) to clarify
and better operationalize the concept of pattern formation for the CAS view of product innovation. The
patterning of attention, as a sensemaking mechanism,
indicates the collective process whereby people identify what is important and relevant in moving toward
desired ends (Osborn et al., 2002). Especially, Hunt
et al. (2009, p. 514) wrote that:
From a traditional viewpoint, patterning of
attention . . . stimulates social construction to
create new information and knowledge from
the dialog and discussion of all participants.
From a complexity perspective, these influence
attempts may alter N, K, P and C. That is, new
individuals within the system may be included
(a change of N), new combinations of interaction may be fostered (a change in K), new
schema may emerge (a change in P), and new
connections with those traditionally outside the
system may be made (a change in C).
Based on this view, we believe that it is the process of
selecting what is important for product development
process, and how this is to be achieved in the organization is a critical aspect of firm strategy and product
development efforts in the CAS perspective. Pattern
formation or patterning of attention can be seen in
the organization when people (1) build a coherent
structure or a description of a successful solution
to product-related problems; (2) emphasize selfadjustment and development of the firm strategy to
address the concurrent environmental turbulence,
and expand the notion of influence patterns, such as
patterning which revolve around the issues of efficiency, quality, innovation, and profitability, etc.; and
(3) seek understanding of the situation via dialogue,
storytelling, and discussions, and use different viewpoints to make their ideas/information prolific and
vibrant (Hunt et al., 2009).
The last mechanism variable is the catalytic
behavior. Catalytic behavior shows the ability of
accelerating and enabling activities by the addition of
catalysts in the organization (Marion and Uhl-Bien,
2001; Morse, 2010). Catalysts are parts of the social
interaction system that enable adaptive actions, such
as seeing the bigger picture, understanding interrelationships, and bridging the communication gap
among people or functional units (Holland, 1995;
Uhl-Bien et al., 2007). From the CAS perspective,
catalysts are also considered as internal and external
new information or knowledge that prompt firms to
recognize new options, reevaluate existing options,

or revisit previously discarded options (Morris,
2005). Further, catalysts in an organization are
people, ideas, dreams, new technologies, symbols,
group myths, or beliefs, which provide filtering as
well as cooperation and speeding up of events and
actions (Morse, 2010).
In addition to the mechanisms of CAS, we also
discuss the term of adaptive management. Adaptive
management from the CL perspective is a social
influence practice that occurs within an organization
in order to provide sufficient structure and enable
managerial behavior in favor of firm adaptability and
innovation (Marion and Uhl-Bien, 2001; Uhl-Bien
et al., 2007; Uhl-Bien and Marion, 2009). Based on
the CL theory, adaptive management involves practices of bonding, nonlinear, and attractor behaviors of
management (Uhl-Bien and Marion, 2009). Bonding
behavior, a function of the network dynamics of
CAS theory, is the ‘linking up’ practice through
which social networks and network structures form
and evolve (Uhl-Bien and Marion, 2009). As Barczak
et al. (1987) mention, bonding behavior forms
knowledge worker communities, cultivates greater
sense of community, trust, respect, and shared vision,
and leverages knowledge transfer and generation.
From an operationalization perspective, a bonding
behavior of management is manifested by to what
extent management (1) fosters the development of
moderately coupled structures in which ideas can
emerge freely and match, (2) encourages information
flows by building personal networks of interconnectivity and linkages, (3) injects ideas and information into the system for its members to ponder and
process, and (4) embraces diversity indicating its
level of comfort with divergent or conflicting ideas
(Uhl-Bien and Marion, 2009).
Nonlinear behavior is another adaptive management practice. In the CL context, nonlinearity indicates the asymmetrical relationships embodied in the
organization, feedback loops among the people, as
well as recurrency, which means that any activity of
people can feed back onto itself (Uhl-Bien and
Marion, 2009). We believe that nonlinear behavior
demonstrates the dynamic and sometimes chaotic
attitude of the management in the organization. This
is such that management maintains the organization
at the edge of chaos, seeks to spawn emergent behavior and creative surprises rather than to specify and
control organizational activities, and creates organized disorder in which dynamic events happen at
multiple locales within the organization (Uhl-Bien
and Marion, 2009). Nonlinear behavior of management also incorporates the idea that time and history
matter, such that the past is co-responsible for the
present behavior as well as the future (Osborn et al.,

21

2002; Boal and Schultz, 2007; Mischen and Jackson,
2008). In this way, management connects the past,
present, and projects the future through storytelling
(Boal and Schultz, 2007; Uhl-Bien et al., 2007).
The last adaptive management practice is attractor
behavior. Attractor behavior of management from
the CL perspective is related to the use of attractors
to enhance adaptiveness in the organization. It should
be noted here that attractors come in different
‘flavors’ in the complexity theory, such as point, periodical, and strange attractors (Kauffman, 1993;
Merali, 2006). Consistent with the scholars in the
CAS literature (e.g., Osborn et al., 2002; Boal and
Schultz, 2007), we focus on the strange attractors in
this study. Strange attractors describe a system that
functions in complex but inherently unpredictable
ways, but that concurrently self-organizes into emergent order and structure (Pryor and Bright, 2007). In
this way, the possibilities of evolution, adaptability,
and change are associated with strange attractors
(Boal and Schultz, 2007). In the management literature, strange attractors define the boundaries within
which system behavior can occur and are analogous
to the culture and climate of an organization (Cox
et al., 2009). In a sense, a strange attractor is defined
as a trajectory of behaviors (although the exact path
is unknown) that draws people into it and influences
their behaviors in the organization (Osborn et al.,
2002; Uhl-Bien and Marion, 2009). For example,
values, fads, identity, vision and mission, social
assumptions, relationships, and structures function as
attractors in an organization (Barczak et al., 1987;
Pryor and Bright, 2007). Here, using attractor behavior, management becomes aware of the potential of
such dynamic behavior, and works to repeat and/or
enhance attractors’ potentials. Recognition of the
effects of such attractors may be seen and act as tags
(e.g., a flag or symbol around which everyone rallies)
(Boal and Schultz, 2007; Uhl-Bien and Marion,
2009).

3. Hypothesis development
3.1. Mechanisms of CAS and firm
product innovativeness
We argue that strategic resonance leverages product
development efforts by amplifying the meaning of
the information, and leads to an increase in its
content and receptivity. For example, Mann (2002,
p. 88) notes that ‘resonance is a potent force lever
capable of amplifying small inputs into large
outputs’. In particular, people can develop new concepts and information through exposure to diverse
22


and opposing views, ideas, and capabilities, and validate the re-creation of new information, knowledge,
and capabilities with strategic resonance (Bennet and
Bennet, 2008). Strategic resonance also provides
‘mutuality’ in the organization to improve product
development efforts. As the people or departments
performing different functions interact, they both
give and receive resources (e.g., ideas, information,
capability, etc.) during the product development
process; continuous linkages and harmonization
among their actions, capabilities, resources, etc. are
created so that they are able to adapt to the challenges
they face individually together in a mutually beneficial manner. In a sense, people or departments work
together, albeit with their potentially conflicting
views, capabilities, and competition for the same
resources (Brown and Fai, 2006), synchronize their
emotions and enhance their collective energy
(Humphrey et al., 2008), and develop an appreciation
of each other’s knowledge/capability limitations and
responsibilities (Taylor et al., 2002) through strategic
resonance. Strategic resonance further helps people
or departments take different functional approaches
simultaneously – leveraging product development
efforts (Brown and Fai, 2006). For instance, resonance among departments or functional units
provides a dynamic view of technology and marketrelated information, and helps them see taken-forgranted events in a new light, based on the perceived
similarities with their domains (Turner, 2007). In
addition to viewing events in a new light, people
recognize that information/knowledge regarding the
technical or marketing aspect of the tasks may be
located anywhere in the organization (Burns and
Stalker, 1994). Therefore, we hypothesize that:
H1: Strategic resonance is positively related to firm
product innovativeness.
Accreting nodes (e.g., expanding information or
knowledge iteratively) impact product innovativeness by effectively gathering information or knowledge in the organization. For instance, through
accreting nodes, project-related new information
or knowledge develops within the interrelations
among people/functions, and it is then structured in
a manner that allows people to achieve multiple
courses of action during the product development
process (Hawes, 1999). This is such that people
develop new perceptions, views (i.e., mental
models), and knowledge bases to respond
unpredicted changes about projects, its environment,
and organization in a flexible manner (Tharumarajah
et al., 1996). Accreting nodes also enhance the crossfunctional integration and collaboration, improving
product innovation efforts. For example, when

product-related new information is disseminated verbally throughout the organization, new engagements
among people may be realized. This is because
people create recursive relations and interactions for
product-related information expansion and dissemination (Hawes, 1999). Also, social interactions
among people reproduce, mediate, and transform
information, and create cohesion where people are
simultaneously autonomous and cooperative for
information expansion (Pavlovich, 2009). This way,
people better understand the whole product development process and discover product-related problems
more effectively in order to improve its success in the
marketplace. Therefore:
H2: Accreting nodes are positively related to firm
We put forward that pattern formation (i.e., patterning of attention) enhances product development
efforts by improving the problem-solving abilities of
people. For example, pattern forming makes productrelated problems and issues more visible to more
readily allow people to take the needed actions, and
aids people against ill-prepared product-related problems (Kurtz and Snowden, 2003). Pattern formation
also helps people see the product development
process in a holistic way, thereby enhancing the
success of the new product. Specifically, pattern formation provides opportunities for people to shape,
form, expand, and adjust their understandings
about product-related concepts, objects, and events,
thereby placing and seeing them in a larger NPD
context and making sense of the ‘whole’ innovation
process (Eoyang, 2007). Additionally, pattern formation reduces the tension inflicted upon product development efforts. For instance, when the task-related
conflict evolves during the product development
project, the pattern formation channels the mental
and behavioral experiences of people to a narrow
range of behavior, and reduces the number of projectrelated parameters, forming a logically coherent
product development process (Cindea, 2006). Therefore, we hypothesize that:
H3: Pattern formation is positively related to firm
Catalytic behavior of an organization also influences the product development activities by seeding
positive feedback, creativity, and entrepreneurial
activities. This is such that creating an environment
where feedback, creativity, and entrepreneurship are
expected and approved energize the innovative
behavior. Indeed, as Latour (1992) noted, ideas need
‘energy’ to diffuse throughout the organization, and

that people, whether users or creators of the idea,
must transform their idea into actions. Here, for
instance, a lack of sufficient support (e.g., product or
idea champion) during all the phases of innovative
activities can cause new ideas and models to be abandoned (Hannah and Lester, 2009). Catalytic behavior
of an organization also improves the collective learning efforts during the product development efforts.
Specifically, people learn to supportively reason in a
direction to formulate inferences that lead to the
envisioned product-related solutions and outcomes
(Latta and Kim, 2010), foster collective discussions
and communication flow about how meaningful
learning could take place due to limited time and
resources (Hannah and Lester, 2009), and unlearn or
eliminate previous information or knowledge to
create new knowledge for better product development endeavors. Therefore:
H4: Catalytic behavior is positively related to firm

3.2. Mechanisms of CAS and adaptive
management practices
We posit that adaptive management practices influence the mechanisms of CAS. For instance,
bonding behavior of management leverages the
mechanism variables, for example, strategic resonance, by helping people act in a unified and interdependent manner (Barczak et al., 1987; Brett,
1996). Consequently, people (1) share their workloads with each other, and help each other in their
tasks, (2) develop mutual personal friendship and
empathy, as well as a high team spirit, and (3) tend
to make better decisions than any single individual
or department would make in a given situation
(Haque, 2004). Indeed, bonding behavior of management does limit functional autonomy in formulating its working rules since people’s judgments
are constrained by bounded rationality. Also,
bonding behavior of management fosters social ties,
and thereby speeds up the socialization process,
enhancing catalytic behaviors and accreting nodes
(Peppard, 2007). For example, people exploit information or knowledge through direct exchange with
their colleagues by tapping each other’s networks.
In this way, people also recognize each other’s
values and routines, and appreciate each other’s
abstract and tacit know-hows (Peppard, 2007).
Further, bonding behavior of management enhances
commitment among people to improve the effectiveness of pattern formation, such that people
develop a mind-set that identifies them to their
objects and courses of action (Torka et al., 2005).

23

As people have varied interests, abilities, and personal commitments, their identification, association,
and commitment are also likely to vary. In this
respect, bonding behavior of management provides
the ability for people/departments/groups to carry
out their strategic direction successfully and to
maintain their means to implement. Therefore:
H5: Bonding behavior of management is positively
related to the development of mechanisms of CAS.
Nonlinear behavior of management also influences
the mechanisms of CAS (e.g., strategic resonance)
by leveraging reciprocal, mutually causal, and interweaving influences among people and events
(Mendenhall et al., 2000). For example, a reciprocal
influence is the process through which each perception is concomitantly the outcome of the preceding
action, and is the condition for the following action
creating personal knowledge (Champagne et al.,
2007). In this way, nonlinear behavior of the
management creates a synergistic mind-set in the
organization. Nonlinear behavior of management
also offers a multiplier and recycling effect of
information/knowledge generation, enhancing the
mechanisms of CAS (Holland, 1995). For instance, a
multiplier effect occurs when knowledge pass from
people to other people, and possibly (likely) being
transformed along the way, producing a chain of
changes (Holland, 1995). Here, knowledge is recycled effectively, taking potentially new forms, with
knowledge sharing supported with a diverse set of
knowledge flows and a possibility for creating ad hoc
knowledge flows. Finally, due to its historical perspective (e.g., connecting past, present, and projected
future of the firm), nonlinear behavior of management helps people see the dynamic nature of work
and business-related experiences of the firm, and
offers an opportunity for them to frame experience
in a way that opens up behavioral risk taking and
expands the potential for creativity (Bussolari and
Goodell, 2009). Therefore, we hypothesize that:
H6: Nonlinear behavior of management is positively
We argue that attractor behavior of management
leverages the mechanisms of CAS by providing
people with visual images of the organization and
environment (Boal and Schultz, 2007). For example,
a compelling corporate vision represents an assertion
that the adaptive efforts take their meaning from the
whole firm and cannot be understood in isolation
(Barczak et al., 1987). In this way, the management
stabilizes divergent thoughts, feelings, and actions
within and between them to enhance strategic resonance and knowledge expansion or accreting nodes
24


(Coleman et al., 2007). Attractor behavior of management also influences the mechanisms by acting as
a tag (i.e., a flag or symbol around which everyone
rallies and the philosophy that binds people together)
(Marion and Uhl-Bien, 2001), such that management, as a tag, serves as a form of reference and a
signal with which behavior can be compared, and
mutual adjustment can occur, coordinates the activities of different people or departments, channels
knowledge flows throughout the organization,
promote and articulate an idea and an attitude, and
provides organizations a long-term behavior or an
identity for adaptiveness (Waldrop, 1992; Holland,
1995; Boal and Schultz, 2007; Pryor and Bright,
2007). Therefore:
H7: Attractor behavior of management is positively

3.3. Mechanisms of CAS, adaptive
product innovativeness
We argue that as a driver of CAS mechanisms, adaptive management practices also influence the firm
product innovativeness. For example, as a component
of adaptive management practices, attractor behavior
cultivates an innovative climate and orientation by
enabling the encouragement of individual initiatives
and clarifying the individual responsibilities (UhlBien et al., 2007; Carmeli et al., 2010). In this regard,
people are able to solve product-related problems
effectively, and enhance the capacity to respond technological and market-related changes. Nonlinear
behavior also generates creative and adaptive knowledge that can impact product innovativeness. Here,
people in the organization recognize the meaning of
a given exchange, and adjust their own behavior as
they respond to that meaning within the organization
(Friedrich et al., 2009). That is, when people adjust
themselves according to the new information, they
expand their own behavioral repertoire, which in
effect broadens the behavioral repertoire of the
organization itself (Kauffman, 1993). Further, bonding behavior influences firm product innovation
efforts by fostering interactions within and between
social networks in such a way as to create and diffuse
information across the organization. As people from
different departments frame product-related issues
according to their perspectives, the adaptive management practice of bonding behavior forms an organizing network to build their coalition and ally their
complementary interests as well as resources
(Hargrave and Van de Ven, 2006).
We should also note that CAS mechanisms influence firm product innovativeness. In this respect, we

argue that these mechanisms mediate the adaptive
management practices–product innovativeness link,
which we empirically know little about so far. Specifically, the mechanisms allow adaptive management practices to function effectively for enhanced
product innovation efforts, and actualize those practices and atmosphere into product innovation efforts.
Therefore, we hypothesize that:
H8: The mechanisms of CAS mediate the relationship between adaptive management practices and
firm product innovativeness.

3.4. Environmental turbulence, adaptive
mechanisms of CAS
We put forward that environmental turbulence has a
triggering role on the adaptive management practices and CAS mechanisms in organizations. Specifically, the management literature indicates that
environmental turbulence provides little reliable
information, leading to ‘causal-ambiguity’ (Celly
and Frazier, 1996). In this sense, when the external
environment becomes more turbulent, and thus less
predictable, organizations adjust their practices,
processes, and routines to meet the challenges by
aligning management practices and mechanisms
(Beckman et al., 2004). For example, increasing
changes in the market and technology-related information or knowledge (1) requires firms to acquire
new information and then distribute it into organization quickly (Sawy and Majchrzak, 2004), (2)
entails an effective information sharing using stories
and feedback mechanisms, pattern forming, and
sensemaking (Dougherty et al., 2000), and (3)
increases the need of bonding and attractor behavior
(Perrott, 2008). Also, quickly changing markets and
technologies require quick responses and fast decisive actions for firms to take advantage of the external opportunities. Especially, catalytic behavior and
strategic resonance of organization, for example,
can facilitate a sense of agility, real-time, multidisciplinary analysis and prompt people to work more
closely together in an attempt to buffer the unpredictability (Majchrzak et al., 2000). Therefore, we
hypothesize that:
H9: Environmental turbulence (i.e., market and technology turbulence) influences the adaptive management practices.
H10: Environmental turbulence (i.e., market and
technology turbulence) influences the mechanisms of
CAS.

4. Research method
4.1. Measures and sampling
To test the above hypotheses, multi-item scales either
adopted or developed from prior studies for the
measurement of the variables were used. All variables were measured using 5-point Likert scales
ranging from ‘strongly disagree’ (1) to ‘strongly
agree’ (5). Appendix A contains the questionnaire. A
brief summary of the measures is presented in the
following section.
For strategic resonance in the organization, we
developed new question items based on the past theoretical study of Brown and Fai (2006). We asked 14
question items indicating to what extent there are (1)
continuous linkage and harmonization among people
and departments, (2) people act in concert, and (3)
there is cohesion and alignment between the firm’s
capability and the market segment and technology.
Regarding the pattern formation variable, we developed nine new question items, modified from the
theoretical arguments of Osborn et al. (2002). The
questions were designed to determine (1) to what
extent people seek understanding of the situation via
dialogue and discussion, (2) isolate and communicate which information is important, and (3) develop
interpretive system to collectively pattern the situations. We used the theoretical study of Hannah and
Lester (2009), Morse (2010), Uhl-Bien et al. (2007),
and Marion and Uhl-Bien (2001) to operationalize
the catalytic behavior variable. We modified and
asked 11 question items to address the organizational
view, including (1) to what extent people bridge communication gaps, (2) eliminate old knowledge, (3)
facilitate continuous participation, and (4) construe
social behavior in a multidimensional way for speeding up or enabling certain activities in the organization. For accreting nodes, we developed six new
question items based on the arguments of Cacioppe
and Edwards (2005) and Pavlovich (2009), including
to what extent ideas and information/knowledge are
magnified iteratively and disseminated throughout
the organization.
We asked seven question items to assess the
nonlinear behavior of management derived from
Uhl-Bien and Marion (2009) and Boal and Schultz
(2007), including to what extent management stimulates dynamism, connects the past, present, and
future of the firm, and creates organized disorder, etc.
For bonding behavior of management, we asked nine
question items derived from Uhl-Bien and Marion
(2009), involving to what extent management fosters
interconnectivity and diversity, provides a structure
for information flow, and injects new ideas and

25

information into organization. We asked seven question items to assess the attractor behavior of management derived from Uhl-Bien and Marion (2009),
Osborn et al. (2002), and Boal and Schultz (2007),
including to what extent management acts as a tag
(e.g., a flag around which everybody rallies), and
recognizes attractors and understands the nature of
the movement they create.
The firm product innovativeness was assessed by
asking five established question items adapted from
Wang and Ahmed (2004), including to what extent a
firm is first to market by new product and service
introductions, firm’s new products and services
are often perceived as novel by customers, and new
products and services of firm put it up against its
competitors.
Environmental turbulence questions were adapted
from Jaworski and Kohli (1993). Three question
items each were asked for market and technology
turbulence. Technology turbulence question items
indicate the changes associated with new product
technologies, and market turbulence question items
show the changes in the composition of customers
and their preferences.
We should also note that although it is not the
focus of our study, some variables were included as
controls because they were shown to affect key variables in our study. For instance, researchers suggest
that firm size and age can have significant influence
on firm product innovativeness (e.g., Weiner and
Mahoney, 1981). Firm size was indicated by the
logarithm of the number of employees, and firm age
was assessed by the logarithm of the number of years
since the firm was founded. Also, as the product/
service development activities are perceived differently in different industries or sectors, we asked if
the organization operates in the manufacturing/
production industry or in the service industry.
After developing the new question items in English,
three academics from US-based universities, who
have industrial experiences of more than 10 years,
evaluated the content and meaningfulness of the items
to establish face validity. They did not note any difficulty in understanding the items or scales. These new
and adopted question items were first translated into
Turkish by one person and then retranslated into
English by a second person using the paralleltranslation method. The two translators then jointly
reconciled all the differences. A draft questionnaire
was developed, and then evaluated and revised in
discussions with three academics from Turkey, having
knowledge on organizational behavior and innovation
as expert judges. The suitability of the Turkish version
of the questionnaires was then pretested by 10 parttime graduate students who are full-time employees
26


working in the industry. In addition, eight senior managers, randomly selected from a diverse cross-section
of firms located in Istanbul, evaluated the content and
meaningfulness of the items. Respondents did not
demonstrate any difficulty understanding the items or
scales. After confirming the questionnaire items, the
questionnaires were distributed and collected by the
authors, applying the ‘personally administrated questionnaire’ method.
We used a stratified random sampling plan from
the directory of Istanbul Chamber of Industry. The
Istanbul district was chosen in order to decrease sampling error of the study because this district is the
center of the Turkish economy for manufacturing and
service sectors. A list of 350 eligible firms was generated from the directory of Istanbul Chamber of
Industry. The firms were selected because they (1)
develop new products and export them to other countries, such as United Kingdom, Germany, Arabic
countries, Central Asia, and Russia; (2) are organized
and managed based on a Western management style
(e.g., they operate in accordance with ISO and European quality standards); (3) are affiliated with
Western firms; and (4) have at least 30 employees, as
suggested by Akgün et al. (2009).
First, we contacted the firms’ general managers by
telephone and explained them the aim of the study. Of
the 350 firms contacted, 310 agreed to participate in
the survey study. By using the procedure of Kumar
et al. (1993), we asked for at least two respondents
from each firm, who are the most knowledgeable
about the organization’s operations, culture and
employees, to fill out our surveys in order to reduce the
single source bias. Those respondents are expected to
serve as ‘key informants’ for others who work in the
same organization (Kumar et al., 1993). In particular,
we believe that those key informants are likely to
assess the social interaction, relations among people,
organizational knowledge, past experiences, and
innovativeness more accurately due to their ‘bird’seye views’ of the organization. Also, we asked that the
respondents have top-level positions in their respective areas and to be from different functions of the
organization. Further, they should have been working
in the firm for an average of over 5 years and have a
college or graduate degree. Following the procedure
of Podsakoff et al. (2003), we informed each participant that his/her responses would remain anonymous
and would not be linked to them individually, nor to
their companies or products. In addition, we assured
respondents that there were no right or wrong
answers, and that they should answer questions as
honestly and forthrightly as possible.
Of the 310 firms that agreed to participate, 259
completed our questionnaires. However, 24 firms

responded with only one survey, resulting in 235
firms. Since we asked for multiple responses from
firms, we discarded these surveys from our analyses.
Thus, our analyzable sample consisted of 235 firms
with 497 surveys (some firms supplied more than two
surveys). We compared the mean of variables, firm
size, and ages of the eliminated surveys with the
surveys used for the analysis, and found no statistical
difference among them. In our sample, the respondents were senior employees/staffs (54%), senior
engineers (22%), functional/department managers
(11%), technical leaders (6%), product/project managers (3%), general managers (2%), and owners of
the firm (2%). The respondent departments were
finance (31%), engineering and design (28%), marketing (22%), manufacturing (12%), and human
resources (7%). The participating industries included
finance (22%), service (21%), machinery and manufacturing (15%), chemistry (9%), automotive (6%),
metal (5%), information technologies (5%), pharmaceutical (3%), communication (3%), food (3%), electronics (3%), and textile (2%).

4.2. Common method variance assessment
Since data for the independent and dependent variables are collected from the same informants,
common method bias may lead to inflated estimates
of the relationships between the variables (Podsakoff
and Organ, 1986). We checked for this potential
problem using the Harman one-factor test (Podsakoff
and Organ, 1986). The results of an unrotated principal component analysis indicate that common
method variance does not pose a serious problem
in our investigation because several factors with
eigenvalue greater than 1 were identified – explaining
69.46% of the total variance – and because no factor
accounts for almost all the variance (i.e., highest
single variance extracted is 37.21%). In addition, following Lindell and Whitney (2001), we partialled out
the smallest correlation of the remaining correlations
in order to remove the effect of common method bias.
Given that all unadjusted correlation coefficients
remain statistically significant at P < 0.05 after
adjusting for common method bias, we feel more
confident that a serious threat of common method
bias does not exist in this study.

5. Analysis and results
5.1. Measure validity and reliability
We evaluated the reliability and validity of our variables using confirmatory factor analysis (CFA)

(Fornell and Larcker, 1981; Anderson and Gerbing,
1988). By using AMOS 4.0 (Arbuckle and Wothke,
1999), we investigated all 10 variables (involving
74 question items) in one CFA model using all
surveys (n = 497). After the elimination of problematic items, which have cross loads, the resulting
measurement model was found to fit the data reasonably well: χ2(989) = 2606.68, comparative fit
index = 0.90, incremental fit index = 0.90, TuckerLewis index = 0.89, χ2/df = 2.67, and root mean
square error of approximation = 0.05. Also, the parsimonious normed fit index = 0.77 is above the
cutoff point of 0.70. In addition, all items loaded
significantly on their respective constructs (with the
lowest t-value being 2.50), providing support for
convergent validity.
To assess discriminant validity, a series of twofactor models, recommended by Bagozzi et al.
(1991), were estimated in which individual factor
correlations, one at a time, were restricted to unity
by using AMOS 4.0. The fit of the restricted models
was compared with that of the original model. In
total, we performed 45 models – 90 pairs of comparisons – using AMOS 4.0. The chi-square change
(Δχ2) in each model, constrained and unconstrained,
were significant, Δχ2 > 3.84, which suggests that
constructs demonstrate discriminant validity.
Table 1 reports the reliabilities of the multiple
items, along with construct correlations and descriptive statistics for the scales. Table 1 shows that there
are some moderate to high correlations (ranges from
r = 0.60 to r = 0.73) among some of the variables.
However, we should note that we were expecting
these scores because, in practice, for instance, developing information or knowledge through reciprocal
interconnection is highly related to how people
bridge the communication gap among others to speed
up or enable certain activities (e.g., concept testing,
prototype development, etc.). Table 1 also demonstrates that all the reliability estimates – including
coefficient alphas, average variance extracted (AVE)
for each construct, and AMOS 4.0 based composite
reliabilities – are close to or beyond the threshold
levels suggested by Fornell and Larcker (1981). As
a check for discriminant validity, as suggested
by Fornell and Larcker (1981), the square root of
AVE for each construct is greater than the latent
factor correlations between pairs of constructs (see
Table 1). After conducting these tests, we conclude
that our measures have adequate discriminant and
convergent validity. Finally, skewness ranges from
−0.74 to 0.23, and kurtosis ranges from −0.72 to
0.78. These values are well below the level suggested
for transformation of variables, skewness of 2, and
kurtosis of 5, as indicated by Ghiselli et al. (1981).

27

28
10

11

12

13


Composite reliability
Variance extracted
Cronbach’s α
Inter-rater agreement
(rwg)

Diagonals show the square root of AVEs.
*P < 0.1.
**P < 0.05.
***P < 0.01.

9
10
11
12
13

8

7

0.88
0.64
0.88
0.74

0.90
0.56
0.90
0.73

0.88
0.65
0.89
0.86

0.86
0.54
0.86
0.75

0.89
0.56
0.89
0.76

0.86
0.55
0.85
0.76

0.79
0.51
0.79
0.75

0.90
0.68
0.91
0.74

0.77
0.53
0.77
0.72

0.87
0.70
0.86
0.76

NA
NA
NA
NA

NA
NA
NA
NA

NA
NA
NA
NA

0.77
0.89
0.87
0.43
NA

9

3.74
3.73
2.56
1.29
NA

8

0.88

7

3.07

6

0.79

5

3.28

4

Product innovativeness (0.80)
Strategic resonance
0.55*** (0.75)
Accreting nodes
0.50*** 0.70*** (0.81)
Pattern formation
0.43*** 0.73*** 0.70*** (0.74)
Catalytic behavior
0.41*** 0.71*** 0.73*** 0.70*** (0.75)
Bonding behavior of
0.52*** 0.68*** 0.66*** 0.65*** 0.72*** (0.74)
management
Nonlinear behavior of
0.51*** 0.67*** 0.57*** 0.61*** 0.67*** 0.69*** (0.71)
management
Attractor behavior of
0.47*** 0.65*** 0.61*** 0.62*** 0.67*** 0.70*** 0.70*** (0.82)
management
Market turbulence
0.10**
0.17*** 0.29*** 0.21*** 0.29*** 0.21*** 0.22*** 0.19*** (0.73)
Technology turbulence 0.11**
0.18*** 0.23*** 0.19*** 0.26*** 0.17*** 0.21*** 0.23*** 0.54*** (0.84)
Firm size
0.11**
0.11**
0.10**
0.04
0.10**
0.08*
0.13**
0.08*
−0.01
0.13*** –
Firm age
0.07*
0.07
−0.01
−0.04
0.007
−0.08*
0.08*
−0.01
−0.09
0.01
0.46*** –
Industry
−0.06
0.05
0.05
0.07
0.11**
0.08*
0.09*
0.06
0.14*** 0.26*** 0.16*** −0.08 –

1
2
3
4
5
6

3

0.89
0.74
0.85
0.74
0.79
0.83

2

3.59
3.52
3.37
3.28
3.26
3.32

1

Variables

Mean Standard
deviation

Table 1. Correlations and descriptive statistics




5.2. Hypothesis testing
To test our hypotheses, we performed a structural
equation modeling (SEM). However, before using the
SEM analysis, as our unit of analysis is the ‘firm’, we
first aggregated the question items of respondents,
such that we got the average of each question item
answered by the respondents in each firm. In our
analysis, we found that all inter-rater agreement (rwg)
values range from 0.72 to 0.86, well above the 0.60
benchmark (Hurley and Hult, 1998), indicating a
satisfactory level of inter-rater agreement for
each aggregate variable in a firm (see Table 1). After
aggregating question items from individual (respondent) level to organizational level, we calculated the
composite score for each of our variables and then
used them in the SEM analysis. Also, consistent with
CAS theory, we allowed the parameters representing the covariances across adaptive management
practice-related variables and across CAS-related
mechanism variables to be free during the analysis.
Our analysis showed that most of the covariances
are significant, indicating that there is a covariance
among variables. This means that the variables occur
simultaneously. These results also present an explanation for the moderate to high correlations among
our variables.
Table 2 indicates that strategic resonance
(β = 0.39, P < 0.01) and accreting nodes (β = 0.29,
P < 0.01) are positively related to the firm product
innovativeness, supporting H1 and H2. However, we
could not find any statistical relationship between
pattern formation (β = 0.04, P > 0.1) and catalytic
behavior (β = −0.13, P > 0.1), and firm product
innovativeness; thus H3 and H4 are not statistically
supported.
Regarding the antecedents of mechanisms of CAS,
Table 3 shows that bonding behavior of management
is positively associated with strategic resonance
(β = 0.30, P < 0.01), accreting nodes (β = 0.52,
P < 0.01), pattern formation (β = 0.29, P < 0.01), and
catalytic behavior (β = 0.42, P < 0.01), supporting
H5. Also, our results demonstrated that nonlinear
behavior of management is positively associated with
strategic resonance (β = 0.29, P < 0.01), pattern formation (β = 0.16, P < 0.05), and catalytic behavior
(β = 0.29, P < 0.01). However, we could not find any
statistical association between nonlinear behavior of
management and accreting nodes (β = 0.06, P > 0.1),
partially supporting H6. Further, we found that
attractor behavior of management is positively associated with strategic resonance (β = 0.23, P < 0.01),
accreting nodes (β = 0.27, P < 0.01), pattern formation (β = 0.31, P < 0.01), and catalytic behavior
(β = 0.22, P < 0.01), supporting H7.

Regarding the role of environmental turbulence on
the adaptive management practices and mechanisms,
we found that market turbulence is positively related
to bonding behavior (β = 0.20, P < 0.01), nonlinear
behavior (β = 0.20, P < 0.01), and attractor behavior
(β = 0.13, P < 0.1). We also found that technology
turbulence is positively related to nonlinear behavior
(β = 0.13, P < 0.1) and attractor behavior (β = 0.21,
P < 0.01), partially supporting H9. However, we
could not find any statistical relationship between
environmental turbulence variables and mechanism
variables of CAS, thus not statistically supporting
H10.
In order to test the mediating effect of mechanisms between adaptive management practices and
firm product innovativeness, we employed the
Baron and Kenny (1986) procedure, where a variable (M) mediates the relationship between an independent variable (X) and a dependent variable (Y) if
(a) X is significantly related to Y; (b) X is significantly related to M; (c) after X is controlled for, M
remains significantly related to Y; and (d) after M is
controlled for, the X – Y relationship is zero. Steps
(b) and (c) are the essential steps in establishing
mediation, and step (d) is only necessary to prove a
fully mediated effect. Also, the presence of the
mediator (M) must reduce the impact of the independent variable on the outcome compared with
when M is not present. Further, entering the mediator into the AMOS-based SEM model should also
result in a significant increase in R2. To address
these issues, we performed three different SEM
models, as shown in Table 3:

•

•

•

(a) model a, including all of the adaptive management variables (X) and the product innovativeness
(Y), indicates that bonding behavior (β = 0.28,
P < 0.01), nonlinear behavior (β = 0.15, P < 0.1),
and attractor behavior (β = 0.16, P < 0.1) are positively related to the product innovativeness, and
R2p.innov. = 0.32.
(b) model b, covering the adaptive management
variables (X) and mechanism variables (M), shows
that all adaptive management variables are positively associated with all mechanism variables,
except the relationship between nonlinear behavior and accreting nodes (β = −0.04, P > 0.1).
(c) after adaptive management variables (X) are
controlled, as shown in model c, it was found
that strategic resonance (β = 0.27 P < 0.01) and
accreting nodes (β = 0.27 P < 0.01) are positively
associated with product innovativeness, whereas
catalytic behavior (β = −0.31, P < 0.01) is negatively related to the product innovativeness.
Also, mechanisms of CAS reduce the effects of

29

Table 2. Results of hypotheses
Hypothesis

Relationship

Path value

Stg. resonance → Product innovativeness
Accreting nodes → Product innovativeness
Pattern formation → Product innovativeness
Catalytic behavior → Product innovativeness
Bonding behavior → Stg. resonance
H5
Bonding behavior → Accreting nodes
Bonding behavior → Pattern formation
Bonding behavior → Catalytic behavior
Nonlinear behavior → Stg. resonance
H6
Nonlinear behavior → Accreting nodes
Nonlinear behavior → Pattern formation
Nonlinear behavior → Catalytic behavior
Attractor behavior → Stg. resonance
H7
Attractor behavior → Accreting nodes
Attractor behavior → Pattern formation
Attractor behavior → Catalytic behavior
Market turbulence → Bonding behavior
Market turbulence → Nonlinear behavior
H9a
Market turbulence → Attractor behavior
Technology turbulence → Bonding behavior
Technology turbulence → Nonlinear behavior
Technology turbulence → Attractor behavior
Market turbulence → Stg. resonance
Market turbulence → Accreting nodes
Market turbulence → Pattern formation
H9b
Market turbulence → Catalytic behavior
Technology turbulence → Stg. resonance
Technology turbulence → Accreting nodes
Technology turbulence → Pattern formation
Technology turbulence → Catalytic behavior
Control var.
Firm size → Product innovativeness
Firm age → Product innovativeness
Industry → Product innovativeness
χ2(34) = 91.86, CFI = 0.97, IFI = 0.97, χ2/df = 2.70, RMSEA = 0.08
H1
H2
H3
H4

Results

0.39***
0.29***
0.04
−0.13
0.30***
0.52***
0.29***
0.42***
0.29***
0.06
0.16**
0.29***
0.23***
0.27***
0.31***
0.22***
0.20***
0.20***
0.13*
0.12
0.13*
0.21***
−0.03
0.08
0.03
0.06
0.04
0.03
0.005
0.06
0.07
0.03
−0.09*

Supported
Supported
Not supported
Not supported
Supported

Partially Supported

Supported

Partially Supported

Not supported

Path coefficients are standardized.
*P < 0.1.
**P < 0.05.
***P < 0.01.
CFI, comparative fit index’ IFI, incremental fit index; RMSEA, root mean square error of approximation.

adaptive management variables on the product
innovativeness, and inclusion of the strategic
resonance, accreting nodes, pattern formation,
and catalytic behavior in the model increased the
R2 of product innovativeness (R2innov. = 0.38).

management practices and product innovativeness,
partially supporting H8.

Based on the above results, it is seen that strategic
resonance, accreting nodes, and catalytic behavior
partially mediate the relationship between adaptive

This study empirically showed that the mechanisms
of CAS are related to firm product innovativeness, as
shown in Figure 2. Specifically, we demonstrated

30


6. Discussion and implications


Table 3. Results of mediating hypothesis
Relationship

Model A

Bonding behavior → Product innovativeness
Nonlinear behavior → Product innovativeness
Attractor behavior → Product innovativeness
Bonding behavior → Stg. resonance
Bonding behavior → Accreting nodes
Bonding behavior → Pattern formation
Bonding behavior → Catalytic behavior
Nonlinear behavior → Stg. resonance
Nonlinear behavior → Accreting nodes
Nonlinear behavior → Pattern formation
Nonlinear behavior → Catalytic behavior
Attractor behavior → Stg. resonance
Attractor behavior → Accreting nodes
Attractor behavior → Pattern formation
Attractor behavior → Catalytic behavior
Stg. resonance → Product innovation
Accreting nodes→ Product innovation
Pattern formation → Product innovation
Catalytic behavior. → Product innovation
Firm size → Product innovativeness
Firm age → Product innovativeness
Industry → Product innovativeness

Model B

0.28***
0.15*
0.16*
0.29***
0.54***
0.30***
0.43***
0.29***
−0.04
0.16**
0.21***
0.24***
0.28***
0.32***
0.24***

0.07
0.05
−0.11**
χ2(11) = 39.22, CFI = 0.94,
IFI = 0.94, χ2/df = 3.56,
RMSEA = 0.10

Full
model

Model C
0.16
0.15
0.08
0.29***
0.54***
0.30***
0.43***
0.29***
−0.04
0.16**
0.21***
0.24***
0.28***
0.32***
0.24***
0.27***
0.27***
0.03
−0.31***
0.05
0.03
−0.09*
χ2(33) = 50.89, CFI = 0.98,
IFI = 0.98, χ2/df = 2.21,
RMSEA = 0.07

Path coefficients are standardized.
*P < 0.1.
**P < 0.05.
***P < 0.01.
CFI, comparative fit index; IFI, incremental fit index; RMSEA, root mean square error of approximation.

Environmental
conditions

Adaptive management
practices

Mechanism of CAS

Innovativeness

Strategic resonance
Bonding behavior
Accreting nodes

Market turb.
Nonlinear behavior

Firm product
innovativeness

Technology turb.
Attractor behavior
Pattern formation
Catalytic behavior

Figure 2. Actual model. CAS, complex adaptive system.



31

that strategic resonance of a firm positively impacts
its product innovation efforts. This finding leverages
the previous studies on the concept of ‘strategic resonance’. For instance, while previous studies showed
the significant role of strategic resonance, for
example, aligning technological and organizational
capabilities with firm strategic implementation, on
the success of process innovation efforts (Brown and
Fai, 2006), we illustrated the critical role of strategic
resonance on the success of product innovations,
as suggested by Rodríguez-Pinto et al. (2008). This
finding also improves our understanding on the alignment of organizational capabilities with strategic
management in the NPD context. Specifically, while
past studies showed the effects of alignment of technological, market, and NPD-marketing activities
with a firm’s strategy on the market performance of
new products (Acur et al., 2012), there are few
studies investigating the effects of harmony between
functional capabilities and strategic planning and
formulation on the market success of new products.
We showed that firm product innovativeness will be
improved when firms’ R&D, marketing, and technological capabilities work in harmony and resonate
with business-level strategy. Our results also empirically indicated that accreting nodes positively impact
the firm’s chance to develop better and successful
new products. This finding especially elevates our
understanding on the fuzzy front-end stage of
product development efforts, where user needs are
discovered and product ideas generated, in the NPD
literature (Reid and de Brentani, 2004). In particular,
while previous studies argued that fuzzy front-end
fits the CAS perspective, and proposed fewest strategies for effective management of it (see, Reid and
de Brentani, 2004), we empirically showed that when
ideas, information, and knowledge (1) are magnified
iteratively or successively, as in a recurring growth
pattern, (2) accumulation proceeds through selfconsistency and complementary beliefs, and (3)
rapidly expand in importance throughout the organization, that firm develops better and successful new
products, a product with a competitive advantage.
Also, this finding expands the notion of the critical
elements of effectiveness for information processing
for successful product design and development
efforts, such that we showed that people combine
quality and speed of information, and enhance informal processes of networking and information sharing
with the notion of accreting nodes, as argued by
Brentani and Reid (2011).
Interestingly, in this study, we could not find any
statistical association between pattern formation and
product innovativeness. One reason might be due
to the significant covariances among mechanism
32


variables. That is, pattern formation affects product
innovativeness via strategic resonance and accreting
nodes. This finding empirically supports the theoretical arguments of Kraaijenbrink (2012), who discussed that pattern formation acts an agent role on
the interactions among knowledge creation, application, integration, and retention, which have significant impact on product development project success.
Another reason for the non-significant relation
between pattern formation and firm innovativeness
may be related to sensemaking process in the product
development process. As noted by Weick et al.
(2005), pattern formation (e.g., patterning of attention) is a part of the sensemaking process. For
example, when people seek to understand the situations via dialogue and discussions, they end up with
a fragmented organization of knowledge during the
product development process. It appears that people
need to integrate these patterns and to make them
part of organizational knowledge base (e.g.,
organizational memory, project-related databases,
etc.), engineering, or human factors for a successful
product development process. In this study, we were
also unable to find any statistical association between
catalytic behavior and firm product innovativeness.
The effects of the catalytic behavior on the product
development efforts may be explained by the
covariant role of strategic resonance and accreting
nodes. Indeed, consistent with CAS literature, we
showed that catalysts serve as executioners to enable
actions, such as transforming strategic resonance and
information/knowledge accreting into product development effectiveness (Lee and Sukoco, 2011; Mu
and Di Benedetto, 2011).
This study also demonstrated that adaptive management practices impact the mechanisms of CAS in
the organizations. For example, when management
fosters interconnectivity, creates linkages, develops
moderately coupled structures in the organization,
etc. (i.e., bonding behavior of management), people
or departments (1) resonate and coordinate their
actions, (2) expand their information/knowledge, (3)
accelerate their actions, and (4) interpret and create
patterns for new information. This finding leverages
our understanding on the term of ‘dynamic networks
of interaction’ in the innovation context, as highlighted by Uhl-Bien et al. (2007). In particular,
unlike the static view of networks of interaction in
the NPD literature (Allen et al., 2007; Ngai et al.,
2008; Bstieler and Hemmert, 2010), we highlight the
evolutionary nature of networks facilitated by management (Benson-Rea and Wilson, 2003). Also, we
empirically illustrated that when management recognizes attractors and understands the nature of
the movements they create, and acts as tags (i.e.,

attractor behavior of management), that organization
will implement adaptive mechanisms more successfully. This finding increases our understanding of the
concept of ‘organizational ambidexterity’ by highlighting the dynamic aspect of ambidexterity, as
recommended by Raisch et al. (2009), and showing
how organizations achieve ambidexterity, as noted
by Gibson and Birkinshaw (2004). Specifically,
previous studies focused on the balanced view of
ambidexterity (March, 1991; Cao et al., 2009), which
is largely ‘static’ in nature, and indicates the optimal
mix of exploitation and exploration at a point in time.
With a CAS perspective in general and attractor
behavior of management in particular, we showed
that management can both sustain stability and
respond to perturbation and initiate change in this
study (Pryor and Bright, 2007). Attractor behavior of
management also leverages our understanding on the
role of management in the sensegiving process,
which is the process of attempting to influence the
sensemaking and meaning construction of people,
in organizations (Gioia and Chittipeddi, 1991).
Sensegiving perspective has an assumption that sense
can be owned by top management and that it can be
given to people through active stages of influencing
(Gioia and Chittipeddi, 1991), or articulating that
vision to others (Hill and Levenhagen, 1995) in
the traditional writings. Here, we demonstrated that,
especially with the tagging behavior of management,
sense provided by management is produced with
interactions with people, as people recognize management as a symbolic reference for their corresponding message (Holland, 1995; Boal and Schultz,
2007; Pryor and Bright, 2007). Further, we illustrated
that nonlinear behavior of management where management connects the past, present, and projects the
future of the firm through storytelling; stimulates
dynamism, etc.; and improves the effectiveness of
CAS-related mechanisms. This finding advances our
understanding on the time aspect of improvisational
behavior in the NPD literature (Moorman and Miner,
1998). While past studies reconcile linear and cyclical perspectives of time in organizations through the
concept of improvisation (Crossan et al., 2005), they
did not specify how to converge the time aspect of
improvisation (Boal and Schultz, 2007). In this study,
we showed that with organizational storytelling,
managers blend past and expected future together in
a deep experience of the present to become more
adaptive to conditions. This finding also highlights
the importance of counterfactual thinking (i.e.,
thoughts about what might have been), which
was relatively understudied in the NPD context
(Hsu et al., 2009). The literature indicates that
counterfactual thoughts explore alternative realities

to past events, involves a reconstruction of the past,
and have a powerful impact on how individuals
approach the future. We showed that through storytelling and converging past, present, and projected
future, management helps people see the dynamic
nature of organizational experiences and offers a
way to frame experience in a way that generate new
possibilities, leading organization to become more
adaptive.
Next, our findings illustrated that the adaptive
behavior of management is determined in a sense
by the environmental context, such that management interacts and engages with the dynamic and
complex market and technological conditions in
which they operate to produce adaptive change for
an organization. Interestingly, our results did not
show any significant statistical relationship between
environmental turbulence variables and mechanism
variables. This finding shows that quickly changing
technology and market information or knowledge
stimulate the management for fostering adaptive
efforts, and those efforts lead to strategic resonance,
accreting nodes, catalytic behavior, and pattern
forming. In a sense, adaptive management practices
look like the ‘transmission mechanism’.
This study, finally, enriched the view of firm
adaptiveness in the literature by the use of CAS theory.
It is seen that a CAS perspective provides flexible and
responsive organizational structures (e.g., organic
organizational structure), and fractal organizational
design (e.g., a living organism). Also, by the use of CL
theory, this study upgraded our understanding regarding the role of management in the turbulent conditions
in the literature. Here, consistent with the theoretical
argument (Uhl-Bien et al., 2007; Uhl-Bien and
Marion, 2009), it appears that adaptive management
occurs in the face of adaptive challenges (e.g., turbulent market and technological conditions), rather than
technical problems, such as the application of proven
solutions to known problems.
From this research, the implications for managers
are that the management should provide sufficient
structure as well as enabling conditions to promote the
adaptability and product innovativeness. Specifically,
management should develop a master product innovation plan and then link the functional capabilities to
that plan. Management should also blur some roles
of R&D, manufacturing, and marketing functions so
that they are diffused across the whole organization
beyond functional-specific myopia. Also, the knowledge and understanding of what each function does
need to be diffused throughout the organization.
Indeed, functional specific myopia and core rigidities
are issues that require insight and a concerted effort
not to follow. Management further should provide

33

enough resources (e.g., funding, information, and personnel) needed for product innovation efforts to the
different departments and individuals (e.g., the usual
guideline is to use an X percent of sales for funding
such efforts), and foster a sense of unity and purpose
(e.g., project vision) for them.
Management should also develop transactive
memory system in the organization by creating
yellow pages, and a central database about the expertise of people for information and knowledge expansion. Management should also give some autonomy
to people/functions, and form alliances and integration for information/knowledge expansion by
creating advice and friendship networks. Next, management should allow experimentation and improvisation, and give freedom to people for the synthesis
of new information/knowledge. Further, management could foster feedback culture, which indicates
management’s support for feedback, including nonthreatening and behaviorally focused feedback, as
well as coaching to help interpret and utilize feedback, throughout the organization.
Management, next, should encourage storytelling,
iterative dialogue, and collective problem solving;
develop common languages; and use metaphors and
symbols in order to generate new understandings
about product innovation endeavors. Further, management should take the position of role model for
the actions and adaptiveness. Indeed, when the
environmental threat becomes overwhelming,
people look at management to centralize authority
and take action. This effect is particularly true when
people feel they lack adequate resources or structure to address the threat. Finally, management
should generate surprise (e.g., creating artificial
crisis and anxiety) and select some people as
knowledge catalysts (e.g., gatekeepers, informal
leaders, who have social influence in the organization) in any learning initiative since management
has limited time.

7. Limitations and future research
There are some methodological limitations in this
study. Specifically, due to the nature of the data, the
generalizability of sampling is a limitation of this
study. The study was conducted in a specific national
context, Turkish firms in general and Istanbul district
in particular. It is important to note that the readers
should be cautious when generalizing the results to
different cultural contexts. A Turkish sample involving the Istanbul district, like that of any culturally
bound research, be it a major industrialized city in the
United States, Europe, or Asia, etc., imposes some
34


constraints on the interpretation and application of
the results. Utilizing a cross-sectional design with
questionnaires was also one of the limitations of this
study. Even though ‘surveying is a large and growing area of research in the natural environment’
(Graziano and Raulin, 1997), the method used (only
a questionnaire) may not provide objective results
about the flow of information or knowledge, which is
an inherently dynamic phenomena, throughout the
organization. However, we should also mention that
as a cross-sectional field study, this research provides
some evidence of associations.
We believe that the mechanisms of CAS and
adaptive management practices of CL present
opportunities for future researches in the NPD literature. For instance, the mechanisms of CAS can
be expanded by including the variables of generation of both dynamically stable and unstable behavior, dissipation and phase transitions, and nonlinear
change, etc. Also, the antecedents of the mechanisms can be studied in great detail. For instance,
how the level of loosely coupled behavior and the
number of people or departments engaged in the
iterative dialogue in the organization influence
the pattern formation of firms can be investigated.
Next, how the organizational patterns emerge from
the local agents and interactions, and the role of
organizational boundaries and historical interactions
on the pattern formation, can be studied in greater
detail. Also, the concept of catalytic behavior can be
expanded in the literature. For example, the roles
of integration and collaboration among people;
boundary experiences, which are ‘shared or joint
activities that create a sense of community and an
ability to transcend boundaries among participants’
(Feldman et al., 2006, p. 94); boundary objects ‘that
engage participants in joint deliberation’ (Schneider,
2009, p. 61); and self-reinforcing behavior that
people gain from successfully achieving a task and
from a reliance on intrinsic rewards on the catalytic
behavior can be investigated. Further, practices that
lead to the effective expansion and accumulation
of information or knowledge can be studied. For
instance, fractal organizational designs, organizational improvisation, simultaneously autonomous
and cooperative actions of people/departments, and
dialectic and dialogic communication can be examined. In addition to the positive effects of adaptive
management practices and mechanism of CAS on
the product innovation, the reverse influence of them
on the product innovation efforts should be considered in future researches. For instance, attractors can
be understood as the boundedness of organization
as they operate. In a sense, attractors are the limits
within which product development projects operate.

Also, as Waldrop (1992) noted, catalysts may reduce
regularity of systems (e.g., organization, product
development projects, etc.), and in some ways may
suffer from ‘core rigidity’ as the focus may be
too narrow or only in a field that one knows/
understands. Finally, in this study, our sample
involves a variety of sectors and industries, such as
finance, information technologies, communication,
manufacturing, automotive, metal, etc. For example,
in the finance industry, the products range from
developing new credit cards, loans, and funds to
developing a systems for home banking via computer and the internet, and shared national and international electronic transfer. For communication
industry, the products include cellular, packetswitching services, information services, voice messaging and call accounting services, communication
switching equipment and devices, etc. In future
studies, our model and its related variables can
examine specific types of industries, such as software, high-tech manufacturing, chemistry, etc.
To conclude, in this study, we addressed the relevance of CAS and CL theory, which deals at a level
of abstraction, and is mainly used in the physical and
life sciences rather than in the social sciences like
innovation management. We operationalized the
mechanisms of CAS and adaptive management variables, and then tested the role of those variables on
firm product innovativeness. The results showed that
environmental turbulence triggers the adaptive management practices, and then adaptive management
practices influence the CAS-related mechanisms,
which impact the firm product innovativeness. This
research just scratches the surface of this important,
but understudied, subject. Future researchers will
find the area of CAS and CL theory rich and fruitful
for NPD literature.

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Organizing and the process of sensemaking. Organization Science, 16, 4, 409–421.
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Ali E. Akgün is a Professor of science and technology studies in the School of Business Administration
at Gebze Institute of Technology, Turkey. He
received his PhD in technology management from
Stevens Institute of Technology and his MS in Engineering Management from Drexel University. His
research areas are new product/technology development, learning and complexity, and cognitive and
social psychology in innovation management.
Halit Keskin is a Professor of science and technology studies in the School of Business Administration
at Gebze Institute of Technology, Turkey. He
received his PhD in management and organization
38


from Gebze Institute of Technology. His research
interests include technology and innovation management, knowledge management, and human resource
management in high-tech firms.
John C. Byrne is a Professor in the Department of
Management and Management Science in the Lubin
School of Business of Pace University. He received
his PhD in technology management from Stevens
Institute of Technology. His research interests
include leadership, affect, mood, and emotion in the
workplace; emotional intelligence; and personality
influences in teams and managerial personnel.
Özgün Ö. Ilhan is a PhD Student at the Department
of Business Administration at Gebze Institute of
Technology, Turkey. Her research focuses on new
product/technology development, system dynamics,
and manufacturing adaptability.

Appendix A. Measures
CAS mechanisms (new)
Strategic resonance

•
•
•
•
•

•
•

Customer requirements and organizational capabilities are in harmony and resonate in our firm.
There are continuous linkages and harmonization
between the market and the firm’s operational
capabilities
between all functions and all levels within the
organization.
between the firm’s strategy and its operational
capabilities.
There is mutual understanding, and appreciation
of each others’ limitations, responsibilities,
resources, capabilities, etc. among people in our
organization.
We rectify both the organization process and content of internal strategic planning and formulation.
R&D, operations, and marketing functions resonate in a process of continual feedback, consultation, and adjustments in our organization.

Dropped items

•

The roles and responsibilities of R&D, manufacturing, and marketing functions are blurred so that
they are diffused across the whole organization
beyond any technical definition or functionalspecific myopia.

Complex adaptive system mechanisms, adaptive management practices, and firm product innovativeness

Complex adaptive system mechanisms, adaptive management practices, and firm product innovativeness

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