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A MEASURE OF MARKET SENSING CAPABILITIES
Author: ALVARO DIAS - Email: alvaro.dias1@gmail.com
University: HIGHER INSTITUTE OF MANAGEMENT AND ADMINISTRATION
Track: Marketing Strategy and Leadership
Co-author(s):AlvaroDias(InstitutoSuperiordeGestão)
/Luis FilipeLages(NovaSchoolofBusinessandEconomics)
Access to this paper is restricted to registered delegates of the EMAC 2013 Conference.
Aknowledgements:
LuisFilipeLagesacknowledgesthefinancialsupportofFCT-FundaçãoparaaCiênciaeaTecnologia,PortugalandNovaForum.The
authorswouldliketothankJohnHuffstotforcommentsonearlierversionsofthemanuscript.
A MEASURE OF MARKET SENSING CAPABILITIES
Abstract
Market sensing is critical for sustainable competitive advantage allowing firms to
become aware of opportunities and threats. Although research on market sensing
capabilities has been performed in several managerial disciplines there is no common
agreement about its measurement. We develop a scale that measures market sensing
capabilities as a microfoundation of dynamic capabilities (cf. Teece, 2007). Results
support a four dimensional scale: (1) analytical processes for market sensing, (2)
organizational articulation supporting market sensing, (3) business knowledge sensing
capabilities, and (4) customer relational sensing capabilities. Findings also reveal that
all four dimensions are positively and significantly associated with product
development. Discussion centers on implications to theory and management.
Keywords: Market Sensing Capabilities, Dynamic Capabilities, Product Development.
Track: Marketing Strategy & Leadership
2
1. Introduction
Research on dynamic capabilities has evolved from identifiable, specific and stable patterns
of collective routines (e.g. Eisenhardt & Martin, 2000; Zollo & Winter, 2002) to a more
complex approach based on microfoundations (e.g. Teece, 2007; Hodgkinson & Healy,
2011). Considering dynamic capabilities as “those capabilities used to extend, modify,
change, and/or create ordinary capabilities” (Drnevich & Kriauciunas, 2011: 255), a major
challenge rises on a global economy: how do firms develop their market sensing
capabilities in order to sustain their decisions to create or modify ordinary capabilities? The
demand for market sensing capabilities increases on a context of growing instability, global
competition, information overload, and high innovation rates. To address environmental
uncertainty, firms must develop unique market sensing capabilities that allows managers to
better understand their decision making context.
This article aims to propose a scale to assess firm’s market sensing capabilities. To the best
of our knowledge, there is no stablished measure for market sensing capabilities. By
advancing knowledge on this topic this study enhances theoretical understanding while also
providing managerial guidance.
2. The market sensing scale
Market sensing capability can be understood as an ability which enables the firm to monitor
market needs and tendencies ahead of its competitors. It enhances the importance of
opportunity recognition and refinement as a basis for launching new venture either from
individual or corporative perspectives (Rasmussen, Mosey and Wright, 2011). The way
firms precisely identify specific market demands deserve further attention by the literature.
The decomposition of market sensing capabilities is theoretically important to bring new
insights on this matter (Foley & Fahy, 2009). As such, our scale comprises the perspective
of organizational systems to obtain and translate into organizational learning the market
information, but also includes the human experiential and relational factor. As such, the
sensing scale is composed by four dimensions: (1) analytical processes for market sensing,
(2) organizational articulation supporting market sensing, (3) business knowledge sensing
capabilities, and (4) customer relational sensing capabilities. The first two constructs are
considered because they represent an analytical perspective and systematic of
environmental scanning. The other two constructs comprises the relational and experiential
perspective that complement and provide a deeper understanding of the market context.
Next, these four constructs are explained in detail.
First, market sensing capability is related with the existence of analytical processes that
allows a methodic scanning of changes in environmental opportunities and threats. Firms
that don’t build this kind of processes are less prepared to assess market and spot
opportunities (Teece, 2007). By continuously scanning environmental change, the
monitoring function of analytical processes are fundamental aspects to adopt corrective
actions (Kohli & Jaworski, 1990; Schreyögg & Kliesch-Eberl, 2007). The literature on this
field enhances several mechanisms such as in-house market research, formal and informal
contacts with stakeholders, customers and prospects tracking, and detection of changes in
their preferences (Vorhies, Douglas and Morgan, 2005; Harmsen & Jensen, 2004; Jaworski
& Kohli, 1993). This construct has eight items and assesses the strength of analytical
processes for market sensing in relation to competitors.
3
Second, the effectiveness of analytical processes depends of the existence of an
organizational articulation that allows the creation of a bridge between external inputs and
internal operationalization. This articulation assures a “filter so that attention is not diverted
to every opportunity and threat that ‘successful’ search reveals” (Teece, 2007:1326) being
an essential requisite to accurately change operational capabilities (Cepeda & Vera, 2007).
On a healthy organizational articulation, managerial decisions must contribute to integrate
and leverage capabilities, to establish a climate of strong collaboration and focus the
organization on common vision (Sirmon, Hitt and Ireland, 2007). Learning also plays an
important role on market sensing capabilities (Danneels, 2008). Our construct comprises 10
items and is adapted from the organizational learning construct of Hult, Snow and
Kandemir (2003). As such, it considers that previous conditions must be conjugated in an
organizational articulation that reinforces team spirit, the existence of a commonality of
purpose, a total agreement regarding the organizational vision, the comprehension how
each one work fits into the value chain of the organization, and the reconnaissance of the
importance of learning as a key to improvement.
Third, recent studies underline the complimentary importance of individual’s experience on
interpretation of the information produced by the analytical processes. It has been argued
that these processes transfer the comprehension of latent demand and industry and markets
tendencies from managers to technological processes, and consequently diminishes true
sensing, loosing several ‘human’ important capabilities such as experience, intuition and
emotions (Hodgkinson & Healy, 2011; Rasmussen et al., 2011). On our scale this is
represented by business knowledge sensing capabilities recognizing the importance of
“emotion to update mental representations and (…) skilled utilization of intuitive processes
to synthesize information and form expert judgments” (Hodgkinson & Healy, 2011:1502).
As such, after opportunity detection by analytical processes, entrepreneurs and managers
must figure out how to interpret new events and developments (Teece, 2007). Our construct
is based on the work of Morgan, Kaleka and Katsikeas (2004) and considers that sensing
capabilities must integrate firm accumulated experience. It is assessed with three items
which capture the experiential evolution, market recognition, as well as client and business
wisdom which allows a better sense when reading environmental scanning information.
Finally, the customer relational shaping capabilities dimension enhances the importance of
monitoring market demands and to translate it into organizational response (Harmsen &
Jensen, 2004). Environmental sensing can be more fine-tuned about customers’ needs and
wants as well proposals made by competitors. As capabilities “usually evolve over time in
the context of complex and partly implicit experiences, organizations often lack a well-
articulated understanding of their own capabilities” (Schreyögg & Kliesch-Eberl, 2007:
928). On this context, opportunity reconnaissance depends partially on individual and
organizational knowledge and learning capabilities in situations of existing and new
solutions (Teece, 2007; Dosi, Faillo and Marengo, 2008). While building on Parasuraman,
Zeithaml and Berry (1988) work, this construct comprises four items: (1) Employees
behavior; (2) Relationship with customers; (3) Customer assistance, and (4)
Responsiveness to customer’s needs.
3. Method
The research setting is SMEs from a European country (Portugal). We developed a survey
instrument to capture market sensing capabilities. A preliminary survey was developed and
4
evaluated by two academic judges. A pretest on a small sample was also conducted. In
order to avoid translation errors, the items were back-translated into English by a different
researcher (cf. Douglas & Craig 1983). Respondents were asked to assess all the items (see:
Appendix 1 and Appendix 2) using a 5-point Likert scale (ranging from “1- Much worse”
to “5- Much better”), while taking in consideration the competitive position of their firm in
relation to their competitors. The anchorage based on competitors relative position is in line
with the market sensing capability “which enables the firm to track the way that the market
is moving in advance of its competitors through an open approach to market information
development and interpretation, and the capture of market insights” (Foley & Fahy, 2009:
16).
The final data was conducted in loco with SMEs directors during an eleven month period
between 2009 and 2010. Out of the 207 questionnaires filled out, a final valid sample of
187 users was used. We assured confidentiality and the delivery of a final summary. Non-
response bias was tested by assessing the differences between early and late respondents of
the filled-in questionnaires with regard to the means of all the variables (Armstrong &
Overton 1977). No significant differences between the two groups of questionnaires were
found, suggesting that response bias was not a significant problem in the study.
4. Measurement analysis
After exploratory factor analysis (EFA) the items are subjected to Confirmatory Factor
Analysis (CFA) using full-information maximum likelihood (FIML) estimation procedures
in LISREL 8.8 (Jöreskog & Sörbom, 1993). In this model, each item is restricted to load on
its pre-specified factor, with the four first-order factors allowed to correlate freely. After
CFA purification, the initial list of 43 items was reduced to a final list of 25 items. The 25
final items and their scale reliabilities is included in Appendix 1. The chi-square for this
model is significant (χ
2
=1097.79, 269 df, p<.00). We also assessed additional fit indices:
the NFI, CFI, IFI, and NNFI, that computed .91, .93, .93, and .92, respectively.
Convergent validity is evidenced by large and significant standardized loadings (average
loading size was .80). Coefficients alpha for the variables in the model are good (.87 or
greater) and all four constructs present the desirable levels of composite reliability (over
.70) (cf. Bagozzi, 1980). The Fornell and Larcker (1981) test also indicates that the level of
average variance extracted compares well to accepted levels in the field (e.g. Lusch &
Brown, 1996; Johnson, 1999). Discriminant validity among the constructs is also evidenced
by the correlation estimates between any two constructs (Jöreskog & Sörbom, 1993). No
correlation includes a value of 1 and none of the correlations is sufficiently high to
jeopardize discriminant validity (Anderson & Gerbing, 1988). As such, all constructs
demonstrate discriminant validity. Overall, these results suggest unidimensionality, internal
consistency, and adequate reliability for these measures.
To demonstrate nomological validity we tested our measures with respect to another
construct to which our construct is supposed to be theoretically related (cf. Churchill,
1995). In order to test nomological validity, we considered “product development”
(PROD)1
(α= .96). The construct relies on Vorhies and Morgan (2005) work, and measures the
1
Product development was adapted from Vorhies and Morgan’s (2005) work and was measured on a 5-point scale (1=Much worse; 5=
Much better) in relation to the statements, “Ability to develop new products/services”; “Developing new products/services to exploit
R&D investment”; “Test marketing of new products/services”; “Successful launching new products/services”, and “Insuring that
product/service development efforts are responsive to customer needs”.
5
capabilities on “the processes by which firms develop and manage product and service
offerings” (p. 82). Product development integrates knowledge resulting from the
identification of customers expressed and latent needs (Tsai, Chou and Kuo, 2008). So, the
accurate reading of market tendencies and necessities ensures that the firm is capable of
materializing them of concrete products (Harmsen & Jensen, 2004). As such, market
sensing capabilities play an important role on the identification of those needs, a
fundamental information for product development. So, by focusing on this capability the
firm is able to create more value to the customer through is offering (Drnevich &
Kriauciunas, 2010).
We found out that there is a significant positive correlation between all market sensing
scale dimensions and product development. Overall, we may conclude that the market
sensing scale constructs present nomological validity as the four dimensions operate
somewhat independently on the different outcomes. Given that all of the coefficients are
positive and significant (at p<.05 or better) - a much greater proportion than would be
anticipated by chance - we may conclude market sensing has a positive impact on product
development, hence, the nomological validity of the four proposed measures is supported
(Cadogan, Diamantopoulos, and De Mortanges, 1999; Cross & Chaffin, 1982).
5. Research implications
This study contributes to extend existing knowledge on dynamic capabilities. First, altough
a remarkable number of articles expresses the importance of dynamic capabilities as a
research field, there is a lack of “sufficient empirical testing of the contributions of dynamic
capabilities” (Drnevich & Kriauciunas, 2011: 255-6). Moreover, to our knowledge, there is
no established measure to access market sensing capabilities. To do so, we built on the
work of microfoundations of dynamic capabilities developed by Teece (2007). We also
contribute to the entrepreneurship research by establishing a measure of market sensing
capabilities. On this topic, the opportunity recognition plays an important role either from
the individual or the corporative view (Hoskisson et al, 2011). Recent entrepreneurship
research brought important insights on how to define organizational structures, resources
and capabilities to develop corporate entrepreneurship (Hornsby et al., 2009; Ireland et al.,
2009). Our research permits a deeper knowledge on this subject by defining how to
measure the firm’s awareness to opportunity recognition and by enhancing the link between
the individual and organizational dimensions, as well the articulation that must be
considered within the firm. This new scale also presents managerial implications. The
market sensing capabilities scale gives some guidance to better pursue a more focused
business strategy. In order to improve product development and, as such, may also be used
for benchmarking purposes. A managerial holistic perspective of the four dimensions
suggests to structure the organization in a flat order to monitor market evolution.
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APPENDIX 1. The Market Sensing Capabilities Scale - constructs, scale items and reliabilities
… Please indicate relative to your competitors, how would you describe the level of changes in:
AnaPrc– Analytical Processes for Market Sensing (
α
= .88;
ρ
vc(n)
= .84; ρ= .98) adapted from Vorhies et al. (2005) and
Jaworski and Kohli (1993)
V1 In-house market research
V2 Detection on changes in our customers' product preferences
V3 Contact with or survey those who can influence our end users' purchases (e.g., retailers, distributors)
V4 Collection of industry information through informal means (lunch with industry friends, talks with trade partners)
V5 Gathering information about customers and competitors
V6 Identification of prospective customers
V7 Using market research skills to develop effective marketing programs
V8 Tracking customer wants and needs
OrgArt-Organizational Articulation Supporting Market Sensing (
α
= .94;
ρ
vc(n)
= .91;ρ= .99) Adapted from Hult et al.(2003)
V9 Team spirit pervades to the ranks in the organization
V10 There is a commonality of purpose in the organization
V11 There is total agreement regarding the organizational vision
V12 There is a commitment to sharing the organizational vision with each other
V13 There is a good sense of inter-connectedness of all parts of the organization
V14 There is a understanding of how work fits into the value chain of the organization
V15 There is a understanding where all the activities fit-in in the organization
V16 There is a agreement that the ability to learn is the key to improvement
V17 Basic values of the organization include learning as a key to improvement
V18 There are specific mechanisms for sharing lessons learned in the organization
BusKno –Business Knowledge Sensing Capabilities (
α
= .87;
ρ
vc(n)
= .85; ρ= .95) Adapted from Morgan et al (2004).
V19 Knowledge of the market
V20 Knowledge about customers
V21 Industry experience
CusRel – Customer Relational Sensing Capabilities (
α
= .87;
ρ
vc(n)
= .84; ρ= .95) adapted from Parasuraman et al. (1988)
V22 Employee’ behaviours
V23 Relationships with customers
V24 Customers’ assistance
V25 Responsiveness to customer needs
The scale format for the 25 measures is 1 = Much worse and 5 = Much better
