International Journal of Organizational Analysis
Miles and Snow’s strategic typology redux through the lens of ambidexterity
Marc Sollosy, Rebecca M. Guidice, K. Praveen Parboteeah,
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Miles and Snow’s strategic
typology redux through the
lens of ambidexterity
Strategic
typology
redux
Marc Sollosy
Brad D. Smith Schools of Business, Lewis College of Business, Marshall University,
Huntington, West Virginia, USA
Rebecca M. Guidice
Received 21 May 2018
Revised 15 November 2018
Accepted 14 December 2018
Downloaded by Auburn University At 01:01 25 March 2019 (PT)
Cameron School of Business, University of North Carolina Wilmington,
Wilmington, North Carolina, USA, and
K. Praveen Parboteeah
College of Business and Economics, University of Wisconsin – Whitewater,
Whitewater, Wisconsin, USA
Abstract
Purpose – The purpose of this paper is to link firms’ strategic archetypes as formulated by Miles and Snow
(1978) to the more recent literature on organizational ambidexterity. Examining these obvious linkages, the
paper also addresses how these firms address their entrepreneurial, engineering and administrative problem
domains in relationship with the firm’s strategic archetype.
Design/methodology/approach – Data were collected from 503 firms across the US. Measures
previously validated were used to collect information related to the strategic archetype as well as the three
problem domains. Multiple discriminant and regression analyses were used to test the hypotheses.
Findings – Most of the hypotheses relating the entrepreneurial (exploration and exploitation), engineering
(radical and incremental innovation) and administrative problem (adaptation and alignment) to the four
strategic archetypes (defender, prospector, analyzer and reactor) were supported. Additionally, the authors
found that the firms that had the closest alignment along the three problem domains outperformed the other
firms.
Originality/value – Although the Miles and Snow typology has received considerable research attention,
the obvious links with more contemporary research on organizational ambidexterity has been neglected.
Through this integration, with more recent key strategic management concepts, this paper shows the utility
and current relevance of the Miles and Snow archetypes.
Keywords Strategic management, Ambidexterity, Corporate strategy,
Organizational ambidexterity
Paper type Research paper
Introduction
The strategic typology developed by Miles and Snow (1978) continues to receive noticeable
research attention within the business administration field (Aleksic and Rašic Jelavic, 2017;
Anwar and Hasnu, 2017; Lin et al., 2014) and within this journal (Galbreath, 2010). This
framework classifies firms into four archetypes based on their pattern of strategic decisions.
The first, Defenders, tend to emphasize a narrow domain by securing premium niches in
their industries (Desarbo et al., 2005). The second, Prospectors, place an emphasis on
exploiting new opportunities in new markets (Zahra and Pearce, 1990). Analyzers, the third
International Journal of
Organizational Analysis
© Emerald Publishing Limited
1934-8835
DOI 10.1108/IJOA-05-2018-1433
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IJOA
archetype, exhibit characteristics of both the Defender (risk minimization) and the
Prospector (opportunity maximization). Finally, the Reactor demonstrations an inconsistent
and often unstable pattern of environmental adjustments.
Although the typology has received considerable attention, inconsistent results and
incomplete methodology highlight a number of gaps our study considers. First, while
research has examined antecedents of the typology using a variety of approaches (DeSarbo
et al., 2005; Song et al., 2007), none that we are aware of have examined the typology in light
of more recent understandings of ambidexterity; a dynamic capability often encouraged in
an increasingly competitive world (D’Souza, et al., 2017).
Dynamic capabilities are the routines and processes around which firms regularly
reconfigure (i.e. shed, acquire, integrate, and deploy) their resource base to generate valuecreating strategies that capture existing and new opportunities (Grant, 1996; Holmqvist,
2004; Pisano, 1994). Central to this concept is a firm’s ability to both exploit existing assets
and strategic positions and explore new technologies and markets. Tushman and O’Reilly
(1996) designated this as ambidexterity – the capacity to simultaneously pursue two
dichotomous undertakings effectively (Gibson and Birkinshaw, 2004). Given that typologies
have greater predictive power when grounded in theory (Doty and Glick, 1994), our study
contributes to the literature by using the theoretical underpinnings of ambidexterity
(Duncan, 1976; O’Reilly and Tushman, 2008; Tushman and O’Reilly, 1996) to explain how a
firm’s approach to exploitation and exploration (or lack thereof) is related to the archetypes.
A second gap our study considers comes from Hambrick’s (1983, p. 118) commentary on
the typology’s staying power; notably, the challenges of the most complicated type, the
Analyzer. Hambrick “pitied” top managers of Analyzer firms because “they are walking a
tightrope, trying to be innovative at the same time they are trying to be efficient and
reliable”. The ability to manage this paradox is the essence of organizational ambidexterity
(Duncan, 1976) whereby successful firms are able to generate fresh competencies in support
of new products and services while simultaneously refining and improving existing
competencies (Danneels, 2002). By incorporating organizational ambidexterity into this
debate, we provide a more complete understanding of the Analyzer. Specifically, we
contribute to the literature by arguing that while Hambrick’s concern is valid, the Analyzer
is the prototypical representation of organizational ambidexterity that is the most
strategically beneficial in today’s competitive arena.
Third, over time, successful firms develop a “systematic, identifiable approach to
environmental adaption” (Zahra and Pearce, 1990, p. 751) and this adaptation is a
cornerstone of research using typologies (Gurkov and Settles, 2011). This adaptive approach
considers the actions firms take relative to the environment to address three problem
domains – entrepreneurial, engineering and administrative (Miles and Snow, 1978). While
the distinctive resources, capabilities, and resulting strategic approach needed to resolve
these problems differs across domains, firms facing comparable problems respond similarly
(Lin et al., 2014; Snow and Hrebiniak, 1980). Although these three problem domains are
critical elements of the typology, they have received very sparse coverage in the literature.
Our study therefore makes an important contribution by shedding light on useful indicators
of the three domains, thereby addressing a core component of the typology. Additionally, we
consider how consistency in domain alignment affects organizational performance.
Finally, examining the typology in light of more recent data, we contribute to the
tradition of replication to establish a theory’s usefulness. We agree with Doty and Glick
(1994) that typologies are theories, and that by subjecting the typology to rigorous empirical
testing (through, in this case, the application of ambidexterity), we provide evidence of the
theory’s utility. In addition, it is likely that the typology has become reified in the literature
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(Lane et al., 2006). By subjecting the typology to rigorous empirical testing, we provide
evidence of its value to the classroom and the managerial suite as well as evidence of its
continued theoretical utility (Wronka-Pospiech and Frączkiewicz-Wronka, 2016) by
clarifying some existing paradoxes and contradictions (Poole and Van de Ven, 1989; Van de
Ven, 1989).
Theoretical framework and hypotheses
Ambidextrous firms use their capabilities to exploit existing competencies and to explore
new opportunities (Raisch et al., 2009). Tushman and O’Reilly (1996) posit that
organizational ambidexterity is “the ability to simultaneously pursue both incremental and
discontinuous innovation [. . .] from hosting multiple contradictory structures, processes,
and cultures within the same firm” (p. 24). Developing this ability calls for unique structural
designs and reward systems to support the creation of new knowledge and major
innovations, while also facilitating exploitation of prevailing knowledge for the refinement
of existing products (goods or services).
Achieving competitive performance requires adapting to one’s environment (Zahra and
Pearce, 1990). Accordingly, firms select a configuration of technology, structure and
processes consistent with their strategy and, correspondingly, craft their strategic decisions
with the entrepreneurial, engineering and administrative problem domains in mind (Miles
et al., 1978). Configuration theory helps explain the congruence of these attributes with the
organization’s problem domains, the environment, and its strategies (Miller and Shamsie,
1996; Miller, 1986; Mintzberg, 1990; Sarason and Tegarden, 2003) such that combinations of
the various elements of the domains will be related to specific typologies. Additionally,
congruent domain configurations should result in stronger firm performance, as measured
by sales growth (Auh and Menguc, 2005; Caspin-Wagner et al., 2012; Geerts et al., 2010; Han
and Celly, 2008) and market valuation, as measured by Tobin’s Q (Goosen et al., 2012; Uotila
et al., 2009; Wang et al., 2008).
Entrepreneurial problem domain
The entrepreneurial problem focuses on the extent to which firms exploit existing productmarkets versus seek out new opportunities (Miles et al., 1978). Firms at one extreme persist
in protection mode, concentrating efforts on maintaining a stable product-market and
refining efficiencies. At the other extreme are pioneering firms, steadfastly in
entrepreneurial mode; concentrating on developing new product-markets and differentiating
themselves from the competition.
When viewed through the lens of ambidexterity, there are firms that develop the
capability for operating simultaneously to exploit what is already known and to explore
what is currently unknown by designing processes and systems that emphasize stretch,
discipline and support (Birkinshaw and Gibson, 2004; Gibson and Birkinshaw, 2004). The
ability to search for new and useful adaptations, while simultaneously exploiting via known
adaptation is critical to the ongoing survival and performance of an organization (Fang
et al., 2010). As such, exploration and exploitations function symbiotically in moving
performance (Boumgarden et al., 2012). By striving for an effective balance in exploration
and exploitation, these ambidextrous firms may achieve not only more control of risk, but
also superior performance relative to firms with a singular emphasis (Cao et al., 2009).
To achieve a competitive advantage firms often must be agile and strategically flexible
(Hitt et al., 1998). This posture requires organizational learning to perfect existing routines
as well as develop new capabilities (McCarthy and Gordon, 2011; Zahra et al., 2006). This
Strategic
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dual focus is important because without it, competitive advantage (if achieved) tends to be
temporary (Tushman and Anderson, 1986).
While many organizations strive to achieve high levels of both exploration and
exploitation, research suggests that this is not an easily achieved outcome (Abernathy, 1978;
Boumgarden et al., 2012; Christensen, 1997; Cyert and March, 1963; Duncan, 1976; Gibson
and Birkinshaw, 2004; O’Reilly and Tushman, 1997, 2004, 2008). It is often the case that
structural features that promote exploration are designed separate and apart from those
supporting exploitation (Boumgarden et al., 2012; Nickerson and Zenger, 2002). We therefore
argue below that depending on how firms approach exploitation and exploitation, levels of
these approaches will result in specific typologies.
When firms are primarily focused on identifying and introducing new products or
penetrating new markets, they are characterized as Prospectors (Miles and Snow, 1978;
Slater et al., 2006). For these firms, maintaining the reputation of a risk-seeking pioneer
can be more important than achieving abnormal short-term rents. Indeed, studies
report that Prospectors’ financial performance is often lower than Defenders
(Hambrick, 1983), while their financial distress is higher (Ittner et al., 1997). This
performance differential is reasonable given that Prospectors’ strategic roots are firmly
set in a mode of perpetual exploration, accompanied by retrenchment from older
domains.
Research indicates that Prospectors most likely acquire new knowledge and apply it in
dynamic and competitive international markets (Griffith et al., 2012). This capabilities-based
advantage provides long-term benefits for the fluid, risk-taking Prospector. Relatedly, their
on-going environmental scanning and monitoring lead Prospectors to be creators of
industry change (Miles and Snow, 1978). This emphasis also suggests exploiting existing
capabilities to maintain current product-markets is not strategically important.
H1a. Firms with high explorative and low exploitative learning orientations are
associated with the Prospector strategic type.
In contrast, the Defender is expected to resolve their entrepreneurial problem with focused
concentration on exploitation. The most cautious of the archetypes, emphasizing short-term
performance (Rajagopalan, 1997; Singh and Agarwal, 2002), Defenders direct their products
to a limited market, typically the segment perceived to be the healthiest and most viable, and
stake their success on efficiently and effectively maintaining their product-market position.
As a result, R&D efforts emphasize process improvements. Product R&D, if it occurs, is
likely an extension of existing products or services in closely related areas. Furthermore,
exploration is not critical since the Defender strives to defend its current niche.
H1b. Firms with high exploitative and low explorative learning orientations are
associated with the Defender strategic type.
Not all firms solve the entrepreneurial problem with a singular solution. Some approach it
with a bilateral solution that may at times appear to address two seemingly incompatible
objectives. These firms, known as Analyzers, embrace characteristics typical of both
Defenders and Prospectors and strive to solve the entrepreneurial problem through the use
of ambidextrous capabilities (Song et al., 2007).
Ambidexterity challenges the claim that firms pursuing both exploration and
exploitation are “stuck in the middle” (Porter, 1980) and perform at a mediocre level at best
(Ghemawat and Ricart Costa, 1993; O’Reilly and Tushman, 2008; Papachroni, et al., 2015). In
fact, research supports dual business models (Markides and Oyon, 2010) as a means towards
achieving the ambidextrous pursuit of different strategies and balancing exploration and
exploitation (Judge and Blocker, 2008; Papachroni, et al., 2015; Voss and Voss, 2013).
Where efficiency is a concern, Analyzers maintain a core set of skills, products, and
customers (Slater and Narver, 1993); participating in high levels of exploitative learning to
maintain a competitive position in their industry(s) while increasing their cost efficiencies.
For Analyzers, tackling the entrepreneurial problem also entails discovering new productmarket opportunities. Their success rests on the ability to quickly follow promising new
developments (Desarbo et al., 2005) and regularly developing new capabilities. Fortunately,
these capabilities may also enhance the Analyzer’s exploitative efforts in complementary
domains or improve the economies of existing exploitative activities. Consequently, the
Analyzer exemplifies the ambidextrous pursuit of both exploration and exploitation.
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H1c. Firms with high explorative and high exploitative learning orientations are
associated with the Analyzer strategic type.
The previous three strategic archetypes exhibit a common characteristic being consistent
in achieving fit between their perceived environment and their competitive strategy. The
fourth archetype, the Reactor, is characterized by its inconsistent and unstable strategic
responses. The Reactors’ failing with the entrepreneurial problem rests with their inability
to consistently create knowledge and skills that enable them to pursue a strategy consistent
with one of the other three strategic types. Instead, the Reactors’ response to the
entrepreneurial problem is uneven and transient, with opportunistic postures exhibiting a
proclivity towards issue-dominated reactions. This lack of a viable solution for the problem
domain often results in poor performance (Conant et al., 1990).
H1d. Firms with low explorative and low exploitative learning orientations are
associated with the Reactor strategic type.
Engineering problem domain
Whereas the entrepreneurial problem considers the “what” of strategic positioning, the
engineering problem examines “how”. Specifically, the engineering problem, as the means to
alleviate the entrepreneurial problem (Walker, 2013), focuses on the resources, processes,
and technical systems created and employed by firms to deliver products to market (Miles
and Snow, 1978). While the entrepreneurial problem is concerned with the learning that
needs to occur with respect to creating a product, the engineering problem is concerned with
the processes used in delivering the product, be it incremental and/or discontinuous
innovation (Simsek, 2009).
Innovation is the process of proposing, developing or adopting and then implementing a
new good, service, managerial practice, organizational process, policy or program
(Damanpour and Evan, 1984; McAdam and Galloway, 2005). Radical innovation requires a
fundamental change in technology accompanied by a risky, even ambiguous deviation from
existing technology, knowledge, and practice, whereas incremental innovation requires only
minor improvements or simple adjustments (Dutton and Duncan, 1987; Ettlie et al., 1984).
Thus, as the engineering domain shifts from novel and unfamiliar to relatively unoriginal
and familiar, the more incremental innovation (rather than radical) becomes appropriate.
This characterization again lends itself to understanding the strategic archetypes.
The Prospectors’ main objective is to be the leading force for industry change by being in
touch with customer needs and environmental trends. Investing heavily in technology (Dvir
et al., 1993), resources are allocated in ways that improve the firm’s distinctive R&D and
Strategic
typology
redux
IJOA
marketing capabilities (Lin et al., 2014; Moore, 2005). Prospectors focus on achieving first
mover advantages, even at the expense of short-term profitability (Snow and Hambrick,
1980; Song et al., 2007), suggests that they will engage primarily in radical innovation.
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H2a. Firms pursuing high radical innovation and low incremental innovation are
associated with the Prospector strategic type.
Defenders tend to be more risk-averse and show greater interest in satisfying current
customer needs than engendering future needs. Researchers describe Defenders as firms
that implement a reactive strategy (Song et al., 2007) and whose strategic focus centers on
controlling their industry niche (Zahra and Pearce, 1990). Being conservative investors in
technology, Dvir et al. (1993) concluded that Defenders only invest in innovative technology
when they believe it will deliver short-term results while helping maintain their competitive
position. Lin et al., 2014) similarly argued that Defenders typically invest in technology that
provides distinctive, cost reducing production capabilities. Defenders’ innovative efforts
should therefore be aimed primarily at incremental innovation. They are not expected to
engage in radical innovation because it does not serve their strategic needs. Moreover, the
learning orientation adopted to solve the entrepreneurial problem will not provide the type
of knowledge and skills useful in creating radical innovations. In fact, as radical innovation
(and explorative learning) is costly and not necessarily aimed at efficiency, it is likely a rare
means to growth and success for these firms.
H2b. Firms pursuing high incremental innovation and low radical innovation are
associated with the Defender strategic type.
Analyzers, as noted earlier, are often described as situated mid-way between Defenders and
Prospectors (Hambrick, 2003). Analyzers avoid the limitations of each archetype, while
advantageously combining their respective beneficial capabilities (Lin et al., 2014; Slater
et al., 2010; Song et al., 2007). Consistent with these features, their innovation-related
activities are considered ambidextrous as they result in a mixture of radical and incremental
innovation; the former feature to increase revenues and the latter to reduce costs.
Devoted to frequent environmental analysis (Miles and Snow, 1978), Analyzers also pay
a great deal of attention to competitors and mimic those they believe can help them create
value by increasing revenues, decreasing costs, or neutralizing a competitive threat. While
Analyzers may not always introduce as many new product innovations as Prospectors and
may not implement as many process innovations as Defenders (Hambrick, 1983), the level of
each innovation is still expected to be notable.
H2c. Firms pursuing high levels of both radical and incremental innovation are
associated with the Analyzer strategic archetype.
Firms that are not focused on either type of innovation are considered Reactors as they lack
long-term goals and fail to adequately develop the capabilities needed for implementing a
competitive strategy (Song et al., 2007). Relatedly, Reactors inconsistent behaviors are at
least partially attributed to management’s inability to articulate a viable innovation strategy
and instead, their tendency to adhere to strategies rendered impotent by changes in the
external environment (Hambrick, 1983). This tendency is often the result of deficient
technologies, structures and processes (Miles et al., 1978).
H2d. Firms pursuing low levels of radical and incremental innovation are associated
with the Reactor strategic archetype.
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Administrative problem domain
The administrative problem is concerned with development and implementation of structures
and processes that address the uncertainties that arise during the engineering phase (Slater and
Narver, 1993). Such solutions are often complex because management must establish structures
and processes that justify prior strategic decisions, while concurrently considering their impact
on the firm’s ability to evolve and adapt in a dynamic environment (Walker, 2013). Solving the
administrative problem involves both uncertainty reduction, by rationalizing existing systems,
and designing new systems that enable strategic flexibility to compete into the future.
When viewed through the ambidexterity lens, the administrative problem closely aligns
with structural ambidexterity, the form of ambidexterity concerned with an organizational
design that separates the firm into distinct units while also aligning those units to achieve
goals (Benner and Tushman, 2002; Simsek, 2009; Tushman and O’Reilly, 1996). In
particular, the modifications that address the administrative problem are alignment and
adaptability (Gibson and Birkinshaw, 2004). Alignment concerns the ability to develop
stable structures and standardized processes, while adaptation considers the ability to
develop processes that respond to new environmental conditions. Ambidextrous firms will
be equally adept at performing these two rather conflicting functions while nonambidextrous firms will address the administrative problem by emphasizing either
alignment or adaptability.
Prospectors are proactive change agents in their industries and accomplish this largely by
launching new products/services and identifying new markets (DeSarbo et al., 2005). To
succeed in their proactive initiatives, Prospectors will institute a system of loose coupling and
decentralized decision-making, which allows them to organically adapt, reconfigure activities
and be explorative in response to changing environmental demands. Because of their focus,
Prospectors’ will not consider structural stability and standardization to be a practical solution.
H3a. Firms exhibiting high adaptation and low alignment are associated with the
Prospector strategic type.
Defenders focus on maintaining a secure niche in stable product-markets (DeSarbo et al.,
2005). They do this by relying on a unique structure, set of competencies, and culture that
emphasizes alignment over adaption. In support of this strategy-structure sequence, Slater
et al. (2006) reported that successful low-cost Defenders value and emphasize cost control
and centralized decision-making and formal marketing structures to ensure risk and
expenses are held to a minimum. Tushman and O’Reilly (1996) also argued that this focus
requires an alignment of structures, competencies and culture that is completely different
from their explorative-focused counterparts.
H3b. Firms exhibiting high alignment and low adaptation are associated with the
Defender strategic type.
Analyzers will be ambidextrous in response to the administrative problem. Among their
talents, Analyzers are able to adapt quickly to take advantage of new industry conditions while
concurrently defending their position in industries where alignment is crucial. Undeniably,
these ambidextrous behaviors are complex, often requiring separate substructures, cultures,
and processes. Consequently, managers are responsible for tightly coupling activities where
needed while maintaining detachment or loose coupling when integration is not possible or
warranted (O’Reilly and Tushman, 2004; Tushman and O’Reilly, 1996).
Strategic
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H3c. Firms simultaneously exhibiting high adaptation and alignment are associated
with the Analyzer strategic archetype.
Reactors, with their lack of planning and failure to craft a consistent strategy, are less likely
to succeed in solving problems in the administrative domain. Among their troubles,
Reactors lack an effective system of control (Lin et al., 2014; Slater et al., 2006; Song et al.,
2007).
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H3d. Firms exhibiting low adaptation and alignment are associated with the Reactor
strategic archetype.
Integrative classifications. To this point, we have considered the problem domains
separately. Missing is a combined view that provides greater classification accuracy. We
argue that a firm’s strategic archetype is more accurately revealed by examining different
configurations of domain orientations. To build our logic, we rely on configuration theory.
Configuration theory considers the holistic relationships that can exist among
multidimensional phenomenon (i.e. in our case, problem domains and strategic archetypes).
Studies grounded in this theory (Chung-Min, and Jun-Ren, 2007; Tsui, 1990; Vorhies and
Morgan, 2003: Yarbrough et al., 2011) suggest that fit among the simultaneous consideration
of multiple interdependent and mutually reinforcing strategic and organizational
characteristics affects key outcomes (Ketchen et al., 1993).
The majority of studies of the Miles and Snow typology tend to focus on a particular
orientation to identify influences on firm performance (Deutscher et al., 2016). We argue that
such a single lens view is problematic in so much as firms routinely utilize multiple
orientations (Cadogan, 2012; Deutscher et al., 2016). Most organizations’ configurations are a
mosaic of conceptually different traits that seemingly occur together (Deutscher et al., 2016;
Meyer et al., 1993). This emphasis on fit of an organization’s strategic orientation is well
documented (Bhuian et al., 2005; Deutscher et al., 2016; Ruokonen and Saarenketo, 2009).
Consequently, organizational configurations are well positioned to explain performance
(Deutscher et al., 2016; Harms, et al., 2007; Ketchen et al., 1997).
Consistent with configuration theory, we propose that firms displaying high levels of the
three problem domains will categorize under the appropriate strategic archetype.
Specifically, our discussion of Prospectors suggests that those firm that exhibit strong,
consistent, and complementary tendencies of high explorative orientation within the
entrepreneurial domain, high radical innovation in the engineering domain, and high
adaptability relative to the administrative domain will be identified as Prospectors. Along
the same configuration lines, those exhibiting a high exploitative orientation, high
incremental innovation, and high alignment will be identified as Defenders. We also argue
that those exhibiting high explorative and exploitative orientations, high levels of radical
and incremental innovation, and high levels of adaptability and alignment will be identified
as Analyzers. Finally, firms exhibiting low explorative and exploitative orientations, low
levels of radical and incremental innovation and low levels of adaptability and alignment
will be identified as Reactors.
To date, no study has combined domains to determine if this approach leads to a more
comprehensive understanding and managerially relevant assessment of strategic types.
Given this theoretical foundation, we hypothesize:
H4a. The more consistent the problem domains, such that each domain plots on the
same relative quadrant, the more likely the firm represents a singular strategic
archetype.
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We also use configuration theory to argue that the appropriate fit among the three domains
will result in better firm performance. Our approach is consistent with perspectives within
configuration theory that suggests that for a set of strategic characteristics, there is an ideal
set of organizational characteristics that when suitably configured, results in superior
performance (Drazin and Van de Ven, 1985; Meyer et al., 1993; Miller and Shamsie, 1996). We
fully agree with Wiklund and Shepherd’s (2005) assertion that those firms that can configure
on many constructs (in our case, the three problem domains) are more likely to outperform
those that can align on only one or two constructs.
Research suggests high-performing firms match their strategy with environmental
demands and firms with different orientations benefit from different strategic formations
(Miles and Snow, 1978; Slater et al., 2006). With regard to strategy-environment fit, Song
et al. (2007) and Aleksic and Rašic Jelavic (2017) provided evidence of fit for the archetypes
as they relate to specific organizational capabilities. We also examine fit, but ours is between
the three problem domains and the archetypes, and how this fit relates to firm performance.
We expect each archetype to approach the three problem domains differently. For
example, because of their offensive behavior, regular questioning of the organization’s
purpose, and quest for innovation, Prospectors should solve the three problems by adopting
actions that provide the best chance to be first movers. Prospectors are predicted to exhibit
high levels of exploration, radical innovation, and adaptability, and this problem-solution fit
should be positively reflected in the firm’s performance.
The question remains as to what to expect if a Prospector exhibits say, high exploitation
and radical innovation but low adaptability? Alternatively, what are the performance
implications if a Defender exhibits high exploitation and alignment, but pursues more,
rather than less, radical innovation? We expect inconsistent solution sets to be associated
with poorer performance. This expectation is consistent with suggestions that firms
achieving fit exhibit a superior ability to migrate and reconfigure their resources and
routines to achieve a competitive advantage (Wang and Ahmed, 2007).
H4b. Firms where the three domains align with the same strategic archetype (pure) will
outperform firms where the domains do not align (random).
Method
Sample and data collection
To collect data, a pilot study assessing the quality of the survey was first conducted with
firms provided by the Amarillo Chamber of Commerce and the Amarillo Small Business
Development Center. After resolving survey ambiguity, data were collected with an online
survey administered by Qualtric’s Professional Services Division. The size and scope of
Qualtric’s participant pool, combined with our numerous qualification screens, allowed us to
ensure a large enough sample to provide quality responses and rigorous statistical analysis
(Schoenherr et al., 2015). To assess the generalizability of the typology, a total of 984 USA
firms in diverse industries were recruited to participate.
Respondents were screened against two qualifying criteria. First, respondents had to
have meaningful involvement in their firm’s strategic decisions. Second, they had to hold a
senior-level position in the firm. Of the firms recruited, 51 per cent successfully passed the
screening. Across these 503 firms, 70 per cent had less than 500 full time employees (FTEs),
with 45 per cent employing under 10 FTEs. The firms were well dispersed among major
industry sectors, with 14 per cent classified as professional, scientific and technical, 13 per
cent as retail, and 11 per cent as other. In terms of firm age, 58 per cent had been in existence
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for 20 years or less and 30 per cent under 10 years. All 50 states were represented, with the
five most populous states, providing the largest number of firms.
Variables
All variables were measured using previously published scales known to be both reliable and
valid. An added benefit to this selection is that the response format varied across the measures
thereby providing an effective and proactive means to control for method bias; a concern that
can arise when the same source is used to measure all variables (Podsakoff et al., 2012).
Strategic archetype. To measure strategic archetypes, we used Conant et al.’s (1990) 11-item
scale. This instrument provides four response options for each of the questions representing
varying facets of the three problem domains. For example, one question asks how the
competencies of the organization’s management possesses are best characterized, with the four
response options of analytical, specialized, broad and entrepreneurial or fluid. Another question
asks the amount of time the organization spends monitoring changes and trends in the
marketplace, with four possible responses – lengthy, minimal, average or sporadic.
To assign firms to an archetype, we used the modified majority rule approach detailed by
(Desarbo et al., 2005). A firm was classified as a Prospector or Defender when there was a
clear majority. Where a majority did not exist, Miles and Snow (1978) was used for
theoretical guidance. Where the Analyzer designation was most evident, the firm was so
classified. Remaining firms were considered Reactors.
Performance. Using Gupta and Govindarajan’s (1986) instrument, respondents
considered growth in sales, market share, return on equity, and return on assets over 36
months using a seven-point scale (1 = much worse to 7 = much improved). We created a
composite measure of performance (a = 0.94).
Entrepreneurial domain. The entrepreneurial domain was measured with the balanced
dimension instrument (Cao et al., 2009) using a five-point scale (1 = definitely true to 5 =
definitely false). One question measuring exploration was whether the organization had
introduced entirely new products or process over the past three years (a = 0.84). An example
of exploitation was whether, over three years, the organization improved its existing
products or processes (a = 0.88).
Engineering domain. Cheng and Shiu’s (2008) 10-item, seven-point scale (1 = strongly
disagree to 7 = strongly agree) measuring radical and incremental innovation captured the
engineering domain. Two sample questions were whether the organization sought to build
on its existing knowledge or upon its existing experiences over the past three years.
Cronbach’s alpha for radical innovation was 0.84 and 0.89 for incremental innovation.
Administrative domain. Gibson and Birkinshaw’s (2004) measure used a seven-point
Likert scale (1 = strongly disagree to 7 = strongly agree). Two sample questions ask if the
organization’s management system wastes resources on unproductive activities and if
people often work at cross-purposes because the management system holds conflicting
objectives. Cronbach’s alpha for alignment was 0.78 and 0.67 for adaptability.
Controls
Four control variables were considered. Firm size was measured using the natural log of
FTEs. Age was measured by the number of years since the firm’s inception. A dummy
variable was created indicating ownership structure. Finally, we controlled for industry
using the North American Industry Classification Code.
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Results
Table I presents descriptive statistics and correlations of the key variables.
Given that the dependent variable is categorical, multiple discriminant analysis (MDA)
was used to test H1a through H3d. This method is appropriate because it generates
discriminant functions based on the maximization of between- versus within-group
variances to enable the best distinction among the dependent variable’s different groups.
Accordingly, each set of analysis examined two separate but related variables as predictors
of strategic archetype (explorative and exploitative orientation, radical and incremental
innovation and adaptive and alignment orientation).
MDA involves two steps: validation and interpretation (Hair et al., 2010). To complete the
validation step, the classificatory accuracy of the model was compared with a pure chance
model using Press’ Q. Interpretation was then completed using discriminant coefficients,
loadings and other statistics detailed below.
The first set of analysis examined exploration and exploitation as predictors of strategic
archetype. For the combined discriminant functions, Wilks’ Lambda was l = 0.52, x 2 (6, N
= 503) = 322.5, p < 0.01. After the first function was removed, the second function was still
significant, l = 0.80, x 2 (2, N = 503) = 110.7, p < 0.01, indicating that exploration and
exploitation differentiated among the four archetypes.
The effect sizes for the functions were 0.35 and 0.20, which are acceptable given the
conceptual overlap Analyzers and Reactors share with Prospectors and Defenders. The
functions accounted for 53 per cent and 25 per cent of the total relationships between
predictors and groups. The first discriminant function accounted for 68 per cent of the
variance in the solution and the second discriminant function accounted for 32 per cent. The
correlations between discriminant variables and the first discriminant function were highest
for exploration (0.97). Exploitation (0.64) was highest for the second discriminant function.
Press’s Q (Q = 1430.06), which tests for the discriminatory power of the classification
matrix, exceeded the threshold of 6.63 (Hair et al., 2010). The potency index, which measures
the discriminatory power of each variable, was 0.66 for exploration and 0.53 for exploitation
thereby suggesting that learning orientation indeed helps predict membership into a
strategic archetype.
The results above, coupled with comparisons of subgroup means with total means (see
Table II) support three of our four hypotheses. Firms placing greater emphasis on
exploration (M = 4.60) but not exploitation (M = 3.70) tended to be Prospectors (H1a),
whereas those emphasizing exploitation (M = 4.47) but not exploration (M = 2.73) were most
often Defenders (H1b). Those placing strong emphasis on exploration (M = 4.91) and
exploitation (M = 5.20) were associated with Analyzers (H1c). Unexpectedly and
inconsistent with the hypothesis, Reactors resembled Prospectors by emphasizing
exploration (M = 4.47) and not exploitation (M = 3.69) rather than being low on both
learning orientations (H1d).
The second set of analysis examined radical and incremental innovation as a predictor of
archetype. For the combination of both discriminant functions the Wilks’ Lambda was l =
0.63, x 2 (6, N = 503) = 233.1, p < 0.01. After removing the first function, the second function
remained significant with l = 0.87, x 2 (2, N = 503) = 70.6, p < 0.01, indicating the predictors
differentiated among the four strategic archetypes.
Effect sizes for the functions were 0.28 and 0.13 and accounted for 39 per cent and 15 per
cent of the relationships between predictors and groups. The first function accounted for 72
per cent of the variance and the second, 28 per cent. The correlation between discriminant
variables and the first discriminant function was highest for radical innovation (0.98),
whereas incremental innovation (0.94) was highest for the second discriminant function.
Strategic
typology
redux
25.13
4.70
3.98
4.38
5.53
6.19
4.90
5.67
0.02
0.40
0.12
0.46
Firm agea
Performance
Exploration
Exploitation
Radical innovation
Incremental innovation
Alignment
Adaptability
Prospector
Analyzer
Defender
Reactor
23.14
1.23
1.39
1.31
1.46
1.17
1.86
1.49
0.14
0.49
0.32
0.50
SD
0.08
0.13
0.06
0.06
0.01
0.17
0.04
0.13
0.02
0.07
0.01
1
0.18
0.07
0.46
0.31
0.16
0.41
0.04
0.20
0.26
0.02
2
Notes: N = 503; p<0.05, p<0.01, p<0.000; alogarithm
Mean
Table I.
Correlations and
descriptive statistics
Variables
0.65
0.37
0.30
0.10
0.27
0.06
0.55
0.32
0.34
3
0.21
0.31
0.33
0.24
0.07
0.51
0.03
0.50
4
0.56
0.23
0.54
0.03
0.37
0.46
0.07
5
0.16
0.51
0.17
0.37
0.10
0.25
6
0.08
0.12
0.28
0.23
0.39
7
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0.01
0.32
0.34
0.10
8
0.12
0.05
0.13
9
0.30
0.76
10
0.34
11
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The analysis also showed that 56.9 per cent of the sample was correctly classified into
strategic groups. The Press’s Q test (Q = 272.29) exceeded the minimum threshold. The
potency index was 0.70 for radical innovation and 0.33 for incremental innovation,
suggesting that these two forms of innovation help predict membership into an archetype
and was not likely due to chance.
These results combined with an examination of subgroup means relative to total means
provide support for three of four of our hypotheses. As shown in Table II, firms placing
greater emphasis on radical innovation (M = 5.80) but not incremental innovation (M = 4.80)
tended to classify as Prospectors (H2a). While the emphasis on radical innovation was low
(M = 3.68), incremental innovation emphasis was also low (M = 5.88) rather than high,
thereby failing to support H2b for Defenders. Firms placing a strong emphasis on both
radical (M = 6.19) and incremental innovation (M = 6.72) tended to be Analyzers (H2c), and
those with weak emphasis on radical (M = 5.43) and incremental innovation (M = 5.87) were
typically Reactors (H2d).
The third set of analysis examined the ability of adaptability and alignment to predict
archetypes. For the combined discriminant functions Wilks’ Lambda was l = 0.67, x 2 (6,
N = 503) = 199.0, p < 0.01. The second function remained significant after removing the first
function, l = 0.83, x 2 (2, N = 503) = 92.2, p < 0.01, indicating the predictors differentiated
among the archetypes.
Effect sizes for the functions were 0.19 and 0.17 and each accounted for 24 per cent and 20
per cent of the relationship between predictors and groups. Further, the first discriminant
function accounted for 54 per cent of the variance and the second, 46 per cent. The
correlation between discriminant variables and the first function was highest for
adaptability (0.91), while alignment (0.95) was highest for the second function. Over 64 per
cent of the sample was correctly classified into the correct archetype. Press’s Q (Q = 412.54)
and the potency index (0.53 for adaptation and 0.47 for alignment) suggest that alignment
and adaptability help predict archetype membership and was not likely due to chance.
The results above, coupled with the means in Table II, support all four hypotheses. Firms
with greater emphasis on adaption (M = 5.80) but not alignment (M = 3.30) were more likely
to be Prospectors (H3a), whereas those emphasizing alignment (M = 6.05) but not
adaptation (M = 4.27) exhibited a Defender archetype (H3b). Firms with a strong emphasis
on both adaptation (M = 6.26) and alignment (M = 5.55) were mostly Analyzers (H3c) and
those with a low emphasis on both (M = 5.50 and M = 4.13) were typically Reactors (H3d).
Two-way contingency analysis was used to evaluate whether the more consistent the
domain orientations, the more likely the firm had a singular strategic archetype as proposed
in H4a. We considered a domain to be “pure” when all three of a firm’s domains plotted on
Strategic
archetype
Prospector
Analyzer
Defender
Reactor
Total
F
N
10
201
59
233
503
Exploration
M
SD
4.60 0.97
4.91 0.82
2.73 1.00
4.47 1.38
3.98 1.39
85.46
Exploitation
M
SD
3.70
1.25
5.20
0.61
4.47
0.92
3.69
1.43
4.38
1.31
68.82
Radical
Innovation
M
SD
5.80 0.92
6.19 1.11
3.68 0.80
5.43 1.46
5.53 1.46
62.24
Notes: df (3, 499); p < 0.05, p < 0.01, p < 0.000
Incremental
Innovation
M
SD
4.80 1.40
6.72 0.78
5.88 0.83
5.87 1.32
6.19 1.17
29.78
Adaptiveness
M
SD
5.80
6.26
4.27
5.50
5.67
1.14
1.13
1.35
1.55
1.49
34.38
Strategic
typology
redux
Alignment
M
SD
3.30 0.48
5.55 1.91
6.05 1.31
4.13 1.57
4.90 1.86
38.72
Table II.
Descriptives of
strategic archetypes
by problem domain
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the same quadrant. Table III presents the proportion of firms whose strategic archetype was
pure Prospector, Analyzer, Defender, or Reactor. As shown, 142 firms were identified as
having a pure domain orientation and a corresponding singular strategic archetype. The
remaining 361 firms were classified as “random”.
With regards to the strength of the relationship between consistency in a firm’s approach to
the three problem domains and its strategic orientation, Cramer’s V ( w c = 0.47) suggests a
strong association (Green et al., 2011). Additionally, and in support of H4a, Pearson x 2 (3, (N
= 503) = 110.86, p < 0.00, indicates a significant association for those firms that are pure in
their approach.
H4b proposed that firm with domains aligning with their respective strategic archetype
would outperform those firms where the domains do not align. We used a composite
measure of performance to test this hypothesis. To verify the appropriateness of this
approach, we used factor analysis to determine whether these four items load on one factor.
Analysis revealed only one factor with an eigenvalue greater than 1. Additionally, the factor
loadings for the four items were 0.90 for growth in sales, 0.89 for market share, 0.95 for ROE,
and 0.93 for ROA, with no cross loadings above 0.40. This suggests that the four items
adequately measure performance.
Analysis of variance (ANOVA) was then conducted to assess differences between pure
(M = 4.79, SD = 1.27) and random (M = 4.74, SD = 1.21) predictors and our dependent
variable. Results reported in Table IV revealed a performance difference between the groups
(F = 8.21, p < 0.00) thereby supporting H4b.
Discussion
This study coalesces a stream of research dating back to the late 1970s with contemporary
insights (Aleksic and Rašic Jelavic, 2017; Anwar and Hasnu, 2017; Wronka-Pospiech and
Frączkiewicz-Wronka, 2016). Strategy research has long recognized the importance of
strategic equifinality, whereby there are multiple paths to achieving a desired outcome.
While options are not unlimited, there are a few basic patterns firms can adopt to achieve
performance goals. This study focused on those patterns and the fit achieved between a
firm’s strategic profile and its competitive environment. The integration of the Miles and
Snow typology with more recent ambidexterity theory makes an important and updated
contribution to the dynamic Miles and Snow research stream (Anwar and Hasnu, 2017).
Strategic archetype
Table III.
Strategic archetype
by domain
orientation cross
tabulation
Table IV.
Tests of betweensubjects effects
Domain orientation
Prospector
Analyzer
Defender
Reactor
Total
Source
Pure domain
Random
Pure
Total
10
93
47
211
361
0
108
12
22
142
10
201
59
233
503
Dependent variable
Sum of squares
df
Mean square
F
Sig.
Eta squared
Performance
10.71
1
10.71
8.21
0.00
0.02
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Our first three sets of hypotheses examined different problem domains as predictors of
strategic archetype. In keeping with Brown and Eisenhardt (1997) and Tushman and O’Reilly
(1996), we found Analyzers tend to exhibit an ambidextrous propensity towards high levels of
exploration and exploitation, radical and incremental innovation, and alignment and
adaptability. We also found firms classified as Prospectors and Defenders to be generally
consistent with expectations, where the strategy pendulum swings toward exploration,
radical innovation and adaptation for the Prospector and exploitation, incremental innovation,
and alignment for the Defender. These findings support the prevailing view that Prospectors
tend to be first movers in their industries where exploration, radical innovation, and
adaptability are supportive of such leadership roles (Song et al., 2007). In contrast, Defenders
are more interested in stable markets or niches and less drastic approaches are more
appropriate. Interestingly, it was firms classified as Analyzers, not Defenders that often rated
the highest in incremental innovation. This may be a function of the ambidextrous nature of
the Analyzer, where emphasizing both radical and incremental innovation is a key element.
Although most of our hypotheses were supported, several surprising findings deserve
attention. Although we expected Reactors to show lower levels of exploration and
exploitation, our findings suggest Reactors are more likely to display higher levels of
exploration. In fact, all archetypes show a relatively high mean for exploration. We can only
speculate on these findings. Perhaps the hyper-competition characterizing most business
environments today (D’Aveni et al., 2010) makes exploration critical in all industries and
thus, reflects the high levels found even in Reactors.
Our findings highlight several important implications for theory and practice. First, by
examining the typology in concert with ambidexterity, we provide an integrative
perspective that demonstrates to scholars the utility of the typology consistent with current
research (Aleksic and Rašic Jelavic, 2017; Anwar and Hasnu, 2017). Given the minority of
pure firms, another implication is that practitioners may realize competitive benefits by
placing a greater emphasis on developing either a more ambidextrous competitive stance or
a more mutable position in dynamic markets.
One striking finding in the study is the preponderance of Analyzers and Reactors. They
comprise 86 per cent of our firms, compared to 58 per cent found in Miles and Snow’s (1978)
study. Perhaps in today’s age of hyper-competition, companies’ preference to follow a more
complex path is indeed sensible. In this environment, not only is there increased uncertainty
and discontinuity, but also a need for increased speed and adaptability in strategy
formulation and implementation (Ireland and Hitt, 2005). To their benefit, Analyzers have
the paradoxical ability to simultaneously manage independent and complementary, yet
contradictory demands and processes (Andriopoulos and Lewis, 2009; Duncan, 1976; Smith
and Lewis, 2011). We hope these insights encourage future longitudinal research to
determine the success of Analyzers and their ability to weather uncertain environments.
Our findings suggest that despite the potential for weaker performance, many firms go the
Reactor route. It is possible that Reactors represent a more desirable archetype than the oftenmaligned characterization they receive (Griffith et al., 2012). Perhaps Reactors are really another
variation of the Analyzer, in so much, as they represent the more transitory and dynamic
realignment between the Prospector and Defender archetypes. Their apparent disarray may be
the result of migrating to or transitioning between archetypes, a possibility that would be
consistent with findings in our study (H1d). From a scholarly perspective, this archetype may
actually be a good example of organizational vacillation (Boumgarden et al., 2012). Future
research that takes a longitudinal approach will help determine if this is indeed the case.
The current results also have theoretical implications. Specifically, future research needs
to examine the utility of Reactor strategies considering that Reactors often get ignored by
Strategic
typology
redux
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researchers as they focus only on the other three types (Song et al., 2007; Tang and Tang,
2012).
Regarding consistency among organizational problem domains, we found performance
differences between organizations with pure versus random problem domains. As expected,
pure organizations outperformed their random counterparts. Hence, this finding supports
the configuration perspective we adopted. As argued by Kulins et al. (2016, p. 1437),
configurational theories are “helpful in narrowing down an overwhelming mass of data into
tangible theory.” We thus address the call for more configurational models (Short et al., 2008;
Wiklund and Shepherd, 2005) thereby also providing some insights into how the various
aspects of the typologies function together.
In addition to our contribution to extant research on the Miles and Snow typology, we also
make an important contribution to the ambidexterity literature. One practical implication
stemming from this is that firms should be stronger competitors when they develop flexible
management capabilities and difficult to imitate functional and technological skills.
Furthermore, our finding that consistency of the strategic archetype across ambidextrous firms
is related to stronger performance provides evidence of the need for firms to be uniform if they
want to achieve a competitive position in the marketplace. Results also suggest that not all
firms need to be Analyzers to be successful. What is most critical for strategic decision makers
is that firms demonstrate consistency across the three problem domains.
Limitations and future research
Our study is not without limitations. First is the concern of common method bias. To
address this concern, we conducted Harman’s one factor test. To our benefit, exploratory
factor analysis resulted in multiple factors, each with eigenvalues greater than 1. We also
avoided common scales properties when designing the survey as another defence
(Podsakoff et al., 2012).
A second limitation is the sample’s composition. Ours is comprised of mostly smaller,
privately held USA firms. However, the sample also represents firms from a wide-range of
heterogeneous industries. As such, we believe the implications from our study are of
relevance to a general constituency. Nonetheless, future studies will determine whether our
findings apply to larger, non-US firms.
Finally, being a cross sectional study, it only captures a firm’s strategic archetype at a
specific moment in time. To fully understand the influential role of ambidextrous
capabilities and organizational vacillation, it is important that future research use a
longitudinal design.
Aside from future research stemming from the study’s limitations, other areas for
investigation may present themselves upon reflection of what this study did not consider.
For example, it might be useful to learn which, if any, attributes (explorative or exploitative
learning, radical or incremental innovation) have the most notable impact on performance.
Does one rise above the others, or is there some configuration that proves more significant?
Our hope is that the issues raised in our study will encourage others to pursue research
along similar lines.
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Further reading
O’Reilly, I.I.I., C.A. and Tushman, M.L. (2013), “Organizational ambidexterity: past, present, and
future”, Academy of Management Perspectives, Vol. 27 No. 4, pp. 324-338.
About the authors
Marc Sollosy earned his DBA from Kennesaw State University after more than 30
years in industry. He is an Associate Professor of Management/Strategy and
Director of the MBA programs in the Lewis College of Business at Marshall
University. His current research interests examine various aspects of strategic
planning and management. He has a number of publications, including three book
chapters. He regularly teaches strategic management, ethics and international
business at both the undergraduate and graduate levels. Marc Sollosy is the
corresponding author and can be contacted at: sollosy@marshall.edu
Rebecca M. Guidice earned her PhD from Washington State University. Her current
research interests include corporate governance, accountability, innovation and
competitive bluffing. She has published in well-respected peer-reviewed journals
including the Journal of Management, Journal of Business Ethics, Journal of Business
Research, Human Resource Management and the Journal of Personal Selling and
Sales Management. Her teaching expertise is in strategic management and research
methods.
K. Praveen Parboteeah is the inaugural COBE Distinguished Professor and Director
of the Doctorate of Business Administration program at the University of Wisconsin
– Whitewater. His research interests include international management, ethics, and
technology and innovation management. He has published over 45 articles in
leading journals including the Academy of Management Journal, Organization
Science, Decision Sciences, Journal of Business Ethics, Entrepreneurship Theory and
Practice Journal, Journal of International Business Studies and Management
International Review. He has received many awards for his research including the
Western Academy of Management Ascendant Scholar Award and best paper awards from the
Academy of Management meetings.
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