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  • 标题:A contingency theory approach to market orientation and related marketing strategy concepts: does fit relate to share performance?
  • 作者:Pleshko, Larry P. ; Heiens, Richard A.
  • 期刊名称:Academy of Banking Studies Journal
  • 印刷版ISSN:1939-2230
  • 出版年度:2011
  • 期号:January
  • 语种:English
  • 出版社:The DreamCatchers Group, LLC
  • 摘要: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).
  • 关键词:Marketing

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.

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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
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