A contingency theory approach to market orientation and related marketing strategy concepts: does fit relate to share performance?
Pleshko, Larry P. ; Heiens, Richard A.
INTRODUCTION
Contrary to the conservative image of the financial services
industry, financial service providers have begun to show an increasing
interest in marketing (Uzelac & Sudarevic, 2006). This is especially
true in the case of credit unions, many of whom have begun to pursue
differentiation through expanded service offerings in response to the
intensification of rivalry among the range of competitors (Barboza &
Roth, 2009). Nevertheless, as marketing strategy begins to play a
greater role in these organizations, researchers need to continue to
strengthen the link between marketing strategy and performance (Uzelac
& Sudarevic, 2006).
Given the complexity of markets and competitive conditions, the
fundamental assumption by researchers in strategy and related
disciplines since the 1970s has been that no universal set of strategic
choices exists that is optimal for all businesses (Ginsberg &
Venkatraman, 1985; Galbraith, 1973). In essence, corporate or business
strategy is contingency-based, with the effectiveness of an organization
being dependent upon the amount of congruence or 'fit' between
structural and environmental variables (Shenhar, 2001). The primary
focus of contingency theory, therefore, has traditionally been on the
relationship between organizational factors, environmental
characteristics, and the organization's strategic response
(Ginsberg & Venkatraman, 1985). For instance, studies looking at
organizational factors such as firm size or firm technology or
environmental factors such as environmental uncertainty have tended to
dominate the field (Birkinshaw et al., 2002).
Although the contingency perspective is less prominent today than
during the earlier stages of organization theory, researchers have
recently begun to reintroduce this important idea. For instance, Solberg
(2008) investigated the contingency factors influencing international
distributor relationships, Teasley & Robinson (2005) analyzed the
contingency factors influencing technology transfer, and Birkinshaw et
al. (2002) examined the validity of knowledge as a contingency variable
influencing organizational structure. Consistent with the recent
reemergence of contingency based studies, the current study examines the
relationship between a variety of marketing strategy concepts and one of
the most important variables guiding the practice of modern day
marketing, market orientation.
MARKET ORIENTATION
Perhaps the most fundamental philosophical assumption of modern
marketing theory is the centrality of the marketing concept. According
to the marketing concept, in order to achieve sustained success, firms
should identify and satisfy customer needs more effectively than their
competitors. Firms that adopt and implement the marketing concept are
said to be market oriented (Lamb et al., 2005). It follows then that
market oriented firms engage in activities related to the generation and
dissemination of customer and competitor related market intelligence
(Kirca et al., 2005).
Li & Calantone (1998) point out that those firms more adept at
generating market knowledge will be able to achieve better performance
because they will have better access to information about consumer
preferences. Yet market orientated firms go beyond the mere collection
of market related information. Firms with a market orientation also
actively share this information across departments. The result is to
create greater customer value and satisfaction, a prerequisite for
success (Kerin et al., 2009).
In addition, those firms exhibiting high levels of
market-orientation are likely to identify, and seek to take advantage
of, opportunities presented in their markets (Narver & Slater,
1990). For instance, Im & Workman (2004) find a relationship between
new product success and market-orientation. In fact, much of the
research investigating the market-orientation concept suggests that
firms which have better market knowledge are often more creative and
innovative overall, which should lead to better overall long-term
performance (Im & Workman, 2004).
HYPOTHESES
According to the marketing strategy literature, implementing a
market orientation provides a firm with the ability to sense market
trends and to anticipate customer needs, both of which can lead to
superior organizational performance (Hult & Ketchen, 2001; Kirca et
al., 2005). Therefore, firms should ideally operate with a high level of
market orientation. Also, research suggests that market orientation
creates an aggressive and proactive disposition toward meeting customer
needs (Kirca et al., 2005). As such, it is likely that high levels of
market orientation will work best when other related marketing strategy
decisions are more aggressive and in line with the advantages given by a
high market orientation. We call this alignment between relatively high
levels of market orientation with similar degrees of other related
marketing strategy decisions (such as more initiative, or aggressive
market and product strategies) a 'recommended fit' (RFit).
Just as high levels of market orientation may facilitate the
success of an aggressive strategy, low levels of market orientation may
be appropriate when a firm chooses to pursue less aggressive strategies.
For instance, a follower brand that is not in the position to risk
valuable resources may choose to be less aggressive overall, especially
given the high cost of implementing a market orientation (Rust et al.,
2002). Therefore, combining low levels of market orientation with less
aggressive strategies may be another consistent approach favored by some
firms, which we refer to as 'other fit' (OFit). These less
aggressive fit firms would not be expected to match the same levels of
market share of the more aggressive firms with higher market
orientation, simply because these firms would not be in position to take
advantage of the many opportunities available in the market (Jaworski
& Kohli, 1993).
Finally, there are firms which, either through choice or inability,
do not to match their marketing strategies to their market orientation.
These firms, which have an unmatched strategy profile and do not exhibit
a 'fit' (NoFit), will implement less aggressive strategies
with high levels of market orientation or more aggressive strategies
with lower levels of market orientation. As with the OFit firms, it is
not expected that NoFit firms will match the RFit companies in terms of
market share, in this case due to possibly, inefficient activities,
wasted efforts, or lack of support for important marketing decisions
that result from ill-fitted strategies.
We expect that consistency between market orientation and other
related marketing strategy decisions will be relevant to a firm's
market share, especially when an appropriate alignment is evident
between higher levels of market orientation and more aggressive
marketing strategies. This leads to the following set of research
hypotheses.
H1: Market shares will differ among the market orientation-Miles
& Snow 'fit' groups with RFit having the largest share.
H2: Market shares will differ among the market orientation-market
growth 'fit' groups with RFit having the largest share.
H3: Market shares will differ among the market orientation-service
growth 'fit' groups with RFit having the largest share.
H4: Market shares will differ among the market orientation-services
focus 'fit' groups with RFit having the largest share.
H5: Market shares will differ among the market orientation-market
coverage 'fit' groups with RFit having the largest share.
H6: Market shares will differ among the market orientation-Porter
'fit' groups with RFit having the largest share.
H7: Market shares will differ among the market
orientation-marketing initiative 'fit' groups with RFit having
the largest share.
DATA COLLECTION
A sample of chief executives from credit unions was taken in the
financial services industry. Data for the study were gathered from a
statewide survey in Florida of all the credit unions belonging to the
Florida Credit Union League (FCUL). Credit unions are cooperative
financial institutions that are owned and controlled by their members.
Credit unions differ from banks and other financial institutions in that
the members who have accounts in the credit union are the owners of the
credit union. Credit union membership in the FCUL represented nearly
ninety percent of all Florida credit unions and included three hundred
and twenty-five firms. A single mailing was directed to the president of
each credit union, all of whom were asked by mail in advance to
participate. A four-page questionnaire and a cover letter using a
summary report as inducement were included in each mailing. This
approach yielded one hundred and twenty-five useable surveys, a
thirty-eight percent response rate. Of those responding, ninety-two
percent were presidents and the remaining eight percent were marketing
directors. Further analysis revealed that the responding firms differ
from the sampling frame based on asset size ([X.sup.2]=20.73, d.f. =7,
p<.01). Consequently, medium to larger firms are represented in the
sample to a greater degree than smaller firms.
MEASUREMENT
In addition to perceived market share, respondents were also asked
for their perceptions regarding their firm's position relative to a
variety of marketing strategy constructs. These constructs include (i)
market orientation, (ii) Miles & Snow strategy type, (iii) market
growth, (iv) services growth, (v) services focus, (vi) market coverage,
(vii) Porter strategy group, and (viii) marketing initiative. The
precise methodology used to measure these variables is explained in the
following paragraphs.
For performance, perceptual measures were used to evaluate relative
market share. Perceptual measures avoid errors associated with
variations in accounting methods and also have been shown to strongly
correlate with objective measures within the same firm (Varadarajan,
1986; Miller, 1988). In particular, respondents were asked about their
market share performance on a scale from (1) poor to (5) excellent
regarding five market share baselines: [1] versus competitors, [2]
versus goals/expectations, [3] versus previous years, [4] versus firm
potential, and [5] growth of share. A principal axis factor analysis
indicated that the five items load highly on a single dimension
explaining 66.4% of the original variance. Therefore, an overall
indicator of perceived market share was constructed by summing the five
items from the questionnaire. A reliability of 0.872 was found using
Cronbach's (1951) coefficient alpha. The constructed measure of
perceived market share had a possible range from five to twenty-five
with a mean of 14.64 and a standard deviation of 3.56.
Market orientation is conceptualized as including two factors
common in the marketing literature: customer focus and competitor focus
(Kirca et al., 2005). The respondents were asked to evaluate their
perceptions of the firm's efforts in the marketplace on a scale
from (5) true to (1) not true, across seven items: [1] we are committed
to our customers, [2] we create value for our customers, [3] we
understand customer needs, [4] we are concerned with customer
satisfaction, [5] our employees share competitor information, [6] we
respond rapidly to competitors' actions, and [7] management is
concerned with competitive strategies. The items were subjected to
principal axis factoring. The results indicated that two factors,
customer focus and competitor focus, explain 69.7% of the original
variance. The items for each of the two factors were summed separately.
Reliabilities of0.789 for customer focus and 0.834 for competitor focus
were found using coefficient alpha. An overall indicator of market
orientation was then constructed by summing these two factors. The
resulting market orientation variable had a possible range from eight to
forty with a mean of 31.38 and a standard deviation of 4.51. Then, a
median split was used to group the firms into those exhibiting high
relative levels of market orientation and those exhibiting low relative
levels of market orientation. In total, 48% of responding firms were
classified as having a low market orientation and 52% were classified as
high in market orientation.
For the Miles & Snow strategy groups, firms were classified
utilizing the scheme popularized by Miles and Snow (1978). Respondents
were asked to check the box which best describes their firm's
strategy from the following four descriptions. [1] Defenders--"We
attempt to locate and maintain a secure niche in a relatively stable
market environment. We try to protect our markets by offering
high-quality, well-target services. We are not at the forefront of
industry developments". [2] Prospectors:--"We typically
concentrate on many diverse markets, which we periodically help to
redefine. We value being first-in with new services and in new markets
even when these efforts are not highly profitable initially. We respond
rapidly to most new opportunities". [3] Analyzers "We attempt
to maintain a stable and secure position in the market while at the same
time moving quickly to follow new developments in our industry. We are
seldom first-in with new services or in new markets, but are often
second-in with better offerings". [4] Reactors--"We appear to
have an inconsistent approach to our markets and services and are often
indecisive. We are not aggressive in attacking new opportunities, nor do
we act aggressively to defend our current markets. Rather, we take
action when we are forced to by outside forces such as the economy,
competitors, or market pressures". This procedure resulted in one
hundred and nineteen respondents answering the question, with 38% of the
firms being classified as Defenders (45/119), 5% as Prospectors (6/119),
44% as Analyzers (53/119), and 13% as Reactors (15/119).
For market growth strategy, one of the most popular and well-known
theoretical models in marketing is the matrix developed by Ansoff
(1957). Extending Ansoffs conceptualization of available market growth
strategies, Pleshko and Heiens (2008) suggest that market growth
strategies initiated by a given firm may focus on [1] existing market
segments, [2] new market segments, or [3] both existing and new market
segments. Consequently, our questionnaire asked respondents to indicate
their particular market growth strategy by marking the box next to the
appropriate descriptor. Respondents could check either [1] we target
market segments presently served by the firm, or [2] we target market
segments new to the firm. They could also check both of the boxes,
indicating they use both new and current markets for growth. One hundred
thirteen respondents answered the question with 65% (74/113) classified
as focusing on current segments, 11% (13/113) classified as emphasizing
new segments, and 23% (26/113) classified as targeting both new and
existing market segments in their efforts at growth.
For services growth strategy, again drawing from Ansoff (1957),
Pleshko & Heiens (2008) suggest that product, or in this case
service, growth strategies initiated by a given firm may focus on [1]
existing services, [2] new services, or [3] both existing and new
services. Our questionnaire asked respondents to indicate their
particular services growth strategy by marking the box next to the
appropriate descriptor. Respondents could check [1] we emphasize
services presently offered by the firm, or [2] we emphasize services new
to the firm. They could also check both of the boxes, indicating they
emphasize both new and current services in their growth efforts. One
hundred seventeen respondents answered the question with 54% (64/117)
classified as focusing on existing services, 14% (17/117) classified as
emphasizing new services, and 30% (36/117) classified as utilizing both
new and existing services in their growth efforts.
Services focus is defined as the similarity or consistency of
services offered by the firms. Firms were classified on the basis of
services focus by asking respondents to check the box next to the
appropriate response. The options were (i) we emphasize a line of
related services or (ii) we emphasize many unrelated services. One
hundred twelve respondents answered the question with 73% (82/112)
classified as offering related services and the remaining 27% (30/112)
offering unrelated services.
Market coverage is defined as the number of customer markets
targeted by the firms. Firms were classified in their degree of market
coverage by asking respondents to check the box next to the appropriate
response. The options were (i) we specialize in one or two market
segments or (ii) we target many market segments. One hundred ten
respondents answered the question with 52% (57/110) classified as
targeting just one or two segments and the remaining 48% (53/110)
targeting many segments.
For the Porter (1980) strategy groups, firms may compete by either
investing in systems to become the low-cost producer or rather engaging
in efforts to differentiate and distinguish their offerings from other
similar products. Based on Porter's generic strategies, our
questionnaire asked respondents to classify there firms into one of two
categories: (i) we compete by differentiating our services from others
or (ii) we compete by keeping our costs lower than others. One hundred
seven respondents answered the question with 34% (36/107) classified as
differentiating firms and the remaining 66% (71/107) classified as
low-cost firms.
For strategic marketing initiative (SMI), the authors focus on the
aggressiveness or leadership of the firms as it pertains to marketing
strategy controllables. Specifically, Berger & Dick (2007)
demonstrate that the earlier a bank enters a market, the larger its
market share relative to other banks. Extending previous research on
first-mover advantages, the concept of 'strategic marketing
initiative' encompasses the totality of a firm's first-mover
efforts (Heiens et al., 2004, Pleshko et al., 2002). Strategic Marketing
Initiative (SMI) is conceptualized as inclusive of six relevant areas:
(1) introduction of new products or services, (2) introduction of new
advertising campaigns or other promotions, (3) initiation of pricing
changes, (4) employment of new distribution ideas, (5) adoption of new
technology, and (6) seeking out of new markets. Respondents were asked
to evaluate on a scale from (1) not true to (5) true whether their firm
is "always the first" regarding the six items. The overall
indicator of SMI was constructed by summing the six items. A reliability
of 0.903 was found using Cronbach's (1951) coefficient alpha.
Scores on the SMI scale ranged from six to thirty with a mean of 13.72
and a standard deviation of 5.72. A median split was then used to
classify firms by degree of strategic marketing initiative. This
technique resulted in 49% (61/123) of firms classified as exhibiting low
levels of SMI, while the other 51% were classified as having high levels
of SMI (62/123).
The measures of 'fit', the primary predictor variables
used in the analyses, are proposed alignments of market orientation with
each of the seven marketing strategy constructs previously described,
including (1) the Miles and Snow strategy type, (2) market growth, (3)
services growth, (4) services focus, (5) market coverage, (6) the Porter
strategy group, and (7) strategic marketing initiative. Remember that
each 'fit' indicator has three possible categories or groups,
depending on the expected correspondence to market orientation: (i)
recommended fit (RFit), (ii) other fit (OFit) and (iii) no fit (NoFit).
A 'fit' would be recommended (RFit) in those circumstances
where relatively high levels of market orientation would be most
desirable, such as with aggressive growth or high levels of initiative.
Other fit refers to those combinations where lower relative levels of
market orientation would be acceptable, such as with lower levels of
initiative or strategies that are more reactive or defensive in nature.
Any and all other possible combinations of market orientation with the
strategy variables would be classified as NoFit, including for example
high levels of market orientation with passive growth and low levels of
market orientation with aggressive growth. The specific fit categories
related to each marketing strategy construct are revealed in Table 1.
ANALYSIS AND RESULTS
First, univariate analysis of variance (Anova) was used to
determine if the seven 'fit' constructs are relevant to the
perceptions of market share performance. Each of the seven hypotheses
were tested using this method, with significant findings further
investigated using least-squared distances to determine if the means of
any of the specific groups differed significantly. Second, a correlation
was performed to determine if the number of recommended strategic
alignments ('Fits') is related to market share. The second
analysis should reveal how important it is for companies to implement a
strategic 'fit' across many subcategories of marketing
strategy.
A summary of the Anova is provided in Table 2, which shows the
number of firms in each 'fit' group, the average perceived
market share for each group, the "F" statistic, the
"p" value, and the findings of the group mean comparisons. The
Anova tests revealed that only one set of relationships was truly
insignificant. On the other hand, five of the seven analyses were
significant at the 'p'=0.05 level and another test was
significant at the 'p'=0.08 level. The specific analyses are
discussed in the following paragraphs.
As shown in Table 2, the 'fit' between market orientation
and the Miles & Snow strategy was significant (p'=0.000).
Consistent with H1, it was found that the perceived share of the RFit
group was larger than that of the other firms. On the other hand, the
perceived share of the NoFit group was larger than the OFit firms.
Therefore, it appears that high levels of market orientation, when
combined with the more aggressive strategies of the Miles & Snow
typology, are associated with higher levels of market share than is the
case for firms with other combinations. Additionally, a mixed
combination, such as low levels of market
The 'fit' between market orientation and market growth
strategy is also significant (p=0.005). Somewhat consistent with H2, the
firms with a recommended 'fit' tended to have larger market
shares, yet not all of the differences between the recommended fit group
and the other groups were statistically significant. For instance,
although RFit firms exhibited larger share than that of the OFit firms,
the level of significance was only at the p'=.07 level. It was,
however, found that the perceived share of the NoFit group was larger
than that of the OFit firms. Thus, it appears that the less aggressive
strategy combinations, that is low levels of market orientation combined
with a focus on current markets, exhibited the lowest levels of market
share. Higher market share was more evident in firms combining high
market orientation with aggressive market growth or rather in firms
exhibiting mixed 'fit' combinations.
The 'fit' between market orientation and service growth
is also significant ('p'=0.023). Consistent with H3, the firms
with a recommended 'fit' tended to have larger market shares,
yet once again not all of the differences between the various
'fit' groups were statistically significant. Specifically, it
was found that the perceived share of the RFit group was significantly
larger than that of the OFit firms. Therefore, it appears that high
levels of market orientation, when combined with the more aggressive
services growth strategies, exhibited larger market shares than firms
exhibiting a 'fit' combining low levels of market orientation
with less aggressive services growth.
Contrary to H4, the 'fit' between market orientation and
service focus was insignificant ('p'=0.148). No mean
differences were evident, regardless of the combinations regarding
market orientation and service focus.
The 'fit' between market orientation and market coverage
is significant ('p'=0.035). Consistent with H5, the firms with
a recommended fit tended to have larger market shares. Specifically, it
was found that the perceived shares of the RFit and NoFit groups were
larger than that of the OFit firms. Thus, it appears that the less
aggressive strategy combination, that is low levels of market
orientation combined with smaller market coverage, exhibited the lowest
levels of market share. Higher market share was evident in firms
combining high market orientation with larger market coverage or rather
in firms exhibiting mixed 'fit' combinations.
The 'fit' between market orientation and the Porter
groups is insignificant ('p'=0.086). In evaluating H6, it can
be seen that the recommended 'fit' group had the highest
market share. No mean differences were evident at the strict p-value
criterion. However, RFit was greater than OFit at a lesser p-value
('p'=0.08). While weaker evidence, this still supports the
general idea that combining high levels of market orientation with a
strategy that fits better, in this case a differentiating strategy, will
lead to high market shares.
Consistent with H7, the 'fit' between market orientation
and SMI was significant ('p'=0.000). Specifically, it was
found that the perceived shares of the RFit and NoFit groups were larger
than that of the OFit firms. Thus, it appears that the less aggressive
strategy combination, that is low levels of market orientation combined
with smaller initiative, exhibits the lowest levels of market share.
Higher market share was evident in firms combining high market
orientation with more initiative or rather in firms exhibiting mixed
'fit' combinations.
The second analysis tested the number of recommended strategic
'fits' (RFit) against market share using simple correlation
analysis. Table 3 shows the distribution of the number of RFits within
the sample along with the average market share for the specific number
of RFits. As previously shown in Table 2, seven recommended fits were
identified. Therefore, the total number of RFits for each firm can range
from zero (no RFits) to seven (all alignments are RFit). As shown in
Table 3, almost 43% of the sample firms failed to implement a
recommended 'fit' for any of the market orientation
combinations. Also, none of the firms achieved total recommended
'fit' across all the strategic marketing combinations, with
only one firm having six RFit classifications. The correlation between
RFit-Total and market share is r=0.338, with p=0.000. Therefore, the
performance of firms in terms of market share is dependent on the total
number of recommended alignments of strategy with market orientation. In
the case of the credit unions, this correlation corresponds to
approximately 11.4% of variation in share being explained by the number
of RFits exhibited by a firm. Therefore, it is important for firms to
consider the marketing strategy profile as a whole when implementing
strategic decisions.
DISCUSSION
As firms operating in the financial services industry face greater
competitive pressures, marketing strategy must continue to play a
greater role (Uzelac & Sudarevic, 2006). Contingency theory reminds
us, however, that it is the appropriate combinations of strategy,
organizational structure, and the environment which are most relevant
for success. Therefore, the purpose of our research was to determine if
the appropriate 'fit' between market orientation and other
marketing-related strategy concepts would result in higher levels of
market share.
The specific findings for credit unions suggest the following
contingent relationships may provide the best market share performance:
(i) a high degree of market orientation combined with a Prospector or
Analyzer approach, (ii) a high degree of market orientation with a focus
on either new market segments or both new and existing market segments,
(iii) a high degree of market orientation with a focus on either new
services or both new and existing services, (iv) a high degree of market
orientation and an emphasis on many market segments, and (v) a high
degree of market orientation with high levels of strategic marketing
initiative or first mover efforts. In general, it is shown that credit
unions can achieve higher relative share by combining more aggressive
marketing strategies with higher levels of market orientation.
Additionally, the total number of strategic alignments is also
relevant to share performance. It was shown that companies with a higher
number of recommended 'fits' between market orientation and
the marketing strategies achieved a larger market share. This suggests
to credit union management that the entire strategic profile should be
managed as a whole, rather than looking at each marketing strategy
decision separately.
The pattern that emerges seems to suggest that firms with a high
degree of market orientation are well advised to pursue more aggressive
marketing strategies. In fact, the findings go so far as to suggest that
it is often better to implement a no-fit combination than to combine a
low degree of market orientation with a less aggressive strategic
approach. The importance of a more proactive and aggressive strategic
posture may be at least partially explained by the increasing
professionalization of credit union management, who have been
responsible for hastening trends in the industry such as significant
membership and asset growth, industry consolidation, and higher
penetration into the overall population (Barboza & Roth, 2009).
In summary, the results of the study support a contingency theory
approach to marketing strategy in the case of credit unions, with
appropriate fits between market orientation and strategy having a
relevant impact on market share. Nevertheless, although the findings are
both analytically suggestive and intuitively appealing, our sample was
biased towards medium to larger firms that may possess superior
strategic resources to the smaller firms in the industry. Consequently,
readers should use caution when generalizing the results to all types of
credit unions or to other firms in the broader banking and financial
services sectors.
REFERENCES
Ansoff, H.I. (1957). Strategies for diversification. Harvard
Business Review, 30, 113-124.
Barboza, G. & K. Roth (2009). Understanding customers'
revealed satisfaction preferences: An order probit model for credit
unions. Journal of Financial Services Marketing, 13(4), 330-344.
Berger, A.N. & A.A. Dick (2007). Entry into banking markets and
the early-mover advantage. Journal of Money, Credit and Banking, 39(4),
775-807.
Birkinshaw, J., R. Nobel, & J. Ridderstrale (2002). Knowledge
as a contingency variable: Do the characteristics of knowledge predict
organization structure? Organization Science, 13(3), 274-289.
Cronbach, L.J. (1951). Coefficient alpha and the internal structure
of tests. Psychometrika, 16, 297-334.
Ginsberg, A. & N. Venkatraman (1985). Contingency perspectives
of organizational strategy: A critical review of the empirical research.
Academy of Management Review, 10(3), 421-434.
Heiens, R.A., L.P. Pleshko & R.T. Leach (2004). Examining the
effects of strategic marketing initiative and first-mover efforts on
market share performance. Marketing Management Journal, 14(1), 63-70.
Hult, T.G. & D.J. Ketchen (2001). Does market orientation
matter? A test of the relationship between positional advantage and
performance. Strategic Management Journal, 22(September), 899-906.
Im, S. & J.P. Workman (2004). Market orientation, creativity,
and new product performance in high-technology firms. Journal of
Marketing, 68(April), 114-132.
Joworski, B. & A.K. Kohli (1993). Market orientation:
Antecedents and consequences. Journal of Marketing, 57(July), 53-70.
Kerin, R.A., S.W. Hartley, & W. Rudelius (2009). Marketing (9th
Edition). McGraw-Hill Companies, Inc.
Kirca, A.H., S. Jayachandran & W.O. Bearden (2005). Market
orientation: A meta-analytic review and assessment of its antecedents
and impact on performance. Journal of Marketing, 69(April), 24-41.
Lamb, C.W., J.F. Hair, & C. McDaniel (2005). Marketing (8th
Edition). Mason, OH: Thomson South-Western, Inc.
Li, T. & R.J. Calantone (1998). The impact of market knowledge
competence on new product advantages: Conceptual and empirical
examination. Journal of Marketing, 62(4), 13-29.
Miles, R.E. & C.C. Snow (1978). Organizational Strategy,
Structure, and Process. New York: McGraw-Hill.
Miller, D. (1988). Relating Porter's business strategies to
environment and structure: Analysis and performance implications.
Academy of Management Journal, 31(2), 280-308.
Narver, J.C. & S.F. Slater (1990). The effect of a market
orientation on business profitability. Journal of Marketing, 54(4),
20-35.
Pleshko, L.P. & R.A. Heiens (2008). The contemporary
product-market grid and the link to market-orientation and
profitability. Journal of Targeting, Measurement, and Analysis for
Marketing, 16(2), 108-114.
Pleshko, L.P., R.A. Heiens, & L.C. McGrath (2002). A
methodology towards measuring the strategic profile of first-mover firms
in industrial markets. Academy of Marketing Studies Journal, 6(1), 1-7.
Rust, R.T., C. Moorman, & P.R. Dickson (2002). Getting return
on quality: Revenue expansion, cost reduction, or both? Journal of
Marketing, 66(October), 7-24.
Shenhar, A.J. (2001). One size does not fit all projects: Exploring
classical contingency domains. Management Science, 47(3), 394-414.
Solberg, C.A. (2008). Product complexity and cultural distance
effects on managing international distributor relationships: A
contingency approach. Journal of International Marketing, 16(3), 57-83.
Teasley, R. & R. Robinson (2005). Understanding technology
transfer effectiveness in Japanese organizations: A test of contingency
theory. Academy of Strategic Management Journal, 4, 77-97.
Uzelac, N. & T. Sudarevic (2006). Strengthening the link
between marketing strategy and financial performance. Journal of
Financial Services Marketing, 11(2), 142-156.
Varadarajan, P.R. (1986). Product diversity and firm performance:
An empirical investigation. Journal of Marketing, 50(3), 43-57.
Larry P. Pleshko, Kuwait University
Richard A. Heiens, University of South Carolina Aiken
Table 1: 'Fit' Definitions
(Recommended Fit=RFit, Other Fit=OFit, No Fit=NoFit)
Miles & Snow: prospector, analyzer, defender, reactor
RFit = prospector + high market-orientation
analyzer + high market-orientation
OFit = defender + low market-orientation
reactor + low market-orientation
NoFit = all other combinations
Market Growth: target new markets, target existing markets or target
both
RFit = new markets or both + high market-orientation
OFit = existing markets + low market-orientation
NoFit = all other combinations
Services Growth: develop new services, use existing services, or use
both
RFit = new services or both + high market-orientation
OFit = existing services + low market-orientation
NoFit = all other combinations
Services Focus: offer many services, offer few services
RFit = many services + high market-orientation
OFit = few services + low market-orientation
NoFit = all other combinations
Market Coverage: target many segments, target few segments
RFit = many segments + high market-orientation
OFit = few segments + low market-orientation
NoFit = all other combinations
Porter: emphasize low cost, differentiate services
RFit = differentiate + high market-orientation
OFit = low cost + low market-orientation
NoFit = all other combinations
Marketing Initiative: market leaders, market followers
RFit = market leader + high market-orientation
OFit = follower + low market-orientation
NoFit = all other combinations
Table 2: Analysis of Variance
Fit Construct n Share F 'p'
MO+Miles&Snow ([H.sub.1]) 10.41 .000
RFit: High MO + Pros/Anal 37 16.31
OFit: Low MO + Dfndr/Reactr 35 12.83
NoFit 47 14.85
MO+Market Growth ([H.sub.2]) 5.52 .005
RFit: High MO + New/Both 8 15.86
OFit: Low MO + Existing 42 13.38
NoFit 63 15.52
MO+Service Growth ([H.sub.3]) 3.91 .023
RFit: High MO + New/Both 44 15.75
OFit: Low MO + Existing 36 13.65
NoFit 34 14.76
MO+Service Focus ([H.sub.4]) 1.94 .148
RFit: High MO + Many 13 16.08
OFit: Low MO + Few 34 14.14
NoFit 65 15.27
MO+Market Coverage ([H.sub.5]) 3.46 .035
RFit: High MO + Many 31 15.84
OFit: Low MO + Few 28 13.57
NoFit 51 15.12
MO+Porter ([H.sub.6]) 2.51 .086
RFit: High MO + Differ. 21 16.33
OFit: Low MO + Low Cost 35 14.24
NoFit 50 14.85
MO+Marketing Initiative ([H.sub.7]) 11.03 .000
RFit: High MO + Leader 37 15.89
OFit: Low MO + Follower 34 12.39
NoFit 52 15.19
Fit Construct Findings (p<=.05)
MO+Miles&Snow ([H.sub.1]) RFit>NoFit>OFit
RFit: High MO + Pros/Anal
OFit: Low MO + Dfndr/Reactr
NoFit
MO+Market Growth ([H.sub.2]) NoFit>OFit
RFit: High MO + New/Both RFit>OFit (.07)
OFit: Low MO + Existing
NoFit
MO+Service Growth ([H.sub.3]) RFit>OFit
RFit: High MO + New/Both
OFit: Low MO + Existing
NoFit
MO+Service Focus ([H.sub.4]) none
RFit: High MO + Many
OFit: Low MO + Few
NoFit
MO+Market Coverage ([H.sub.5]) RFit/NoFit>OFit
RFit: High MO + Many
OFit: Low MO + Few
NoFit
MO+Porter ([H.sub.6]) RFit>OFit (.08)
RFit: High MO + Differ.
OFit: Low MO + Low Cost
NoFit
MO+Marketing Initiative ([H.sub.7]) RFit/NoFit>OFit
RFit: High MO + Leader
OFit: Low MO + Follower
NoFit
Table 3: RFit_Total
RFit_Total Frequency Percent Share
0 53 42.7 13.38
1 23 18.5 14.91
2 10 8.1 13.67
3 13 10.5 16.91
4 15 12.1 15.53
5 9 7.3 17.33
6 1 0.8 16.00
7 0 0.0 n/a
