A study of logistics strategies in small versus large U.S. manufacturing firms.
Spillan, John E. ; Kohn, Jonathan W. ; McGinnis, Michael A. 等
INTRODUCTION
Smaller businesses frequently make an assortment of
logistics-related decisions, relating to purchasing, customer service,
warehousing, inventory management, order management, transportation etc.
(Murphy, Daly and Dalenberg, 1995). While larger organizations make
these same decisions, there are continued questions about whether there
are any similarities or differences between the two (Evans, Feldman and
Foster, 1990).
Larger companies generally have a variety of people who are trained
in supply chain or logistics management. (Evans, Feldman and Foster,
1990). Smaller businesses, on the other hand, may have only one person
who has logistics management responsibilities and other functions to
perform (Harrington, 1995). As such, logistics management personnel at
smaller companies may have less formal logistics training, and may be
less experienced than at larger organizations. Whether this situation
causes increased logistics costs and/ or less responsiveness in small
firms has not been adequately addressed.
The majority of the logistics literature focuses on large
companies. A review of the literature identified two articles on small
company logistics. Halley and Guilhon (1997) investigated the logistics
strategies of small businesses using both anecdotal and primary data.
The results revealed that among small businesses there were no good or
bad logistics strategies. However, two key factors associated with small
business logistics strategy development were identified. They were the
role of the owner-manager involvement and the company's dependency
on other firms. In another study of selected logistics practices of
small businesses engaged in international trade, Murphy, Daley, and
Dalenberg (1995) found different types of distribution departments among
the firms studied.
The idea that small and large firms have similar logistics
management practices is probably something that the average manager
would not expect given firm size and economies of scale (Harrington,
1995). However, Pearson and Ellram (1995) discovered that there were no
statistically significant differences between small and large electronic
companies in their selection and evaluation of suppliers. Similarly,
Calof (1993) maintained that business size is not an obstacle to
internationalization nor is it a constraint in selecting a country in
which to do business.
Despite the fact that logistics strategy has been widely discussed
in the literature (Clinton and Closs, 1997), the research reported in
this paper focuses on a typology that has been examined over the last
two decades. This typology, proposed by Bowersox and Daugherty (1987),
focuses on three forms of "advanced organizational structures"
comprised of "process strategy", "market strategy",
and "information strategy". While support for the Bowersox and
Daugherty typology has been shown empirically in large firms (Clinton
and Closs, 1997; McGinnis and Kohn, 1993, 2002 and 2010; and Kohn and
McGinnis, 1990 and 1997) and across industries (Autry, Zacharia, and
Lamb, 2008) it is not yet clear whether the typology is relevant to
small firms.
The purpose of the research presented in this manuscript is to
identify similarities and differences in logistics strategies of large
and small U.S. manufacturing firms. This research compares logistics
strategies and assesses logistics strategy outcomes of large and small
manufacturing firms. Levels of logistics strategy intensity (emphasis on
process, market, and information) and outcomes (logistics coordination
effectiveness, customer service commitment, and competitiveness) are
compared.
Insights and implications for logistics practitioners, researchers,
and teachers are provided. The remainder of the paper is organized into
six sections starting with the literature review. This discussion is
followed by sections on research questions variables, and hypotheses;
methodology, analysis, findings, and conclusions.
LITERATURE REVIEW
The typology used to examine large and small manufacturing firms
was the result of a comprehensive study of logistics integration
reported by Bowersox and Daugherty (1987). Sixteen large consumer
product firms were interviewed in 1986 in order to assess organizational
structure. Bowersox and Daugherty identified three distinctly different
organizational types based on the firm's primary strategic thrust.
The first was "Process Strategy" whose primary objective was
to manage flows to gain control over activities that "give rise to
costs" ("cost drivers" in current terminology). The
second was "Market Strategy" whose primary focus was to reduce
complexity faced by its customers. Finally, "Information
Strategy" was postulated as consisting of firms whose objective was
to coordinate information flows throughout the channel of distribution
in order to facilitate cooperation and coordination among channel
members.
A literature review identified three teams of coauthors who
empirically tested the Bowersox/ Daugherty typology. In a series of
studies McGinnis and Kohn (McGinnis and Kohn, 1993 and 2002 as well as
Kohn and McGinnis, 1997a, b) sampled subjects from large U.S.
manufacturing firms regarding a wide range of topics including the
subject typology. They found that Process and Market strategies were
emphasized when logistics strategies were intense, both strategies were
present at moderate levels in balanced logistics strategies, and both
strategies were present at low levels in unfocused strategies. The scale
for Information Strategy was not included because of low scale
reliability (McGinnis and Kohn, 1993). Later they found that Process
Strategy varied with the challenge of the internal (competitive
responsiveness) and external (environmental hostility) environments
(Kohn and McGinnis, 1997). Emphasis on Market and Information strategies
did not vary.
Finally, McGinnis and Kohn (2002) factor analyzed the nine
questionnaire items (three each for Process, Market, and Information
strategies) to ascertain whether the three strategies were independent.
The results indicated that Process and Information loaded on one factor
and Market loaded on a second factor. Regression analysis for the
resulting factors indicated that the majority of variance in the
dependent variable, Logistics Coordination Effectiveness, was explained
by the Process & Information factor. Taken together, the results of
the research by Kohn and McGinnis indicate that the three dimensions of
logistics strategy (process, market, and information) are promising.
However, their results suggest that logistics strategy is more likely to
be a blend of the three strategies, rather than dichotomized as
originally suggested by Bowersox and Daugherty (1987). Further
examination of the results of this pair of researchers suggests that
cost management (Process Strategy) is more likely to be a major
component of logistics strategy with the roles of simplifying
transactions (Market Strategy) and coordinating information flows
throughout the supply chain (Information Strategy) being less
influential.
Clinton and Closs (1997) studied the Bowersox/ Daugherty typology
using a sample of U.S. and Canadian manufacturers and merchandisers.
Subjects were asked to self identify regarding their prevalent logistics
strategy. Of 818 usable responses 541 (66.1%) selected Process Strategy,
146 (17.9%) selected Market Strategy, and 92 (11.3%) selected Channel
(Information) Strategy. The balance, 39 (4.8%), selected "Other
Strategy". Clinton and Closs found that a clear overlap exists
among the three strategies. They concluded that this is to be expected
since logistics must perform the same activities regardless of
underlying logistics strategy. Clinton and Closs concluded that
logistics strategy exists and that the Bowersox/ Daugherty
classification is "promising."
Finally, Autry, Zacharia, and Lamb (2008) surveyed 254 logistics
managers from multiple industries. They identified two logistics
strategy dimensions, Functional Logistics (FL) strategy and Externally
Oriented Logistics (FOL) strategy. The former was described as similar
to Bowersox/Daugherty's Process Strategy while the latter was
described as somewhat resembling Channel (Information) Strategy.
RESEARCH QUESTIONS, VARIABLES AND HYPOTHESES
Based on the literature review, the authors' concluded that
the Bowersox/Daugherty typology provides a relevant framework for the
study of logistics strategy. However, the earlier research focused
primarily on large firms. The research reported in this manuscript
examines a sample of large firms and a sample of small firms and
evaluates their similarities and differences in Process (PROCSTR),
Market (MKTGSTR), and Information (INFOSTR) strategies.
Three dependent variables (Logistics Coordination Effectiveness,
Customer Service Commitment, and Company/Division Competitiveness)
previously used in the logistics literature (Keller, et. al. 2002) were
included in the study to assess outcomes of the independent variables.
As shown in Exhibit 2, Logistics Coordination Effectiveness (LCE) is a
scale that assesses importance of logistics coordination on internal
company relationships, company strategic planning and relationships with
customers, suppliers, and other channel members. This dependent variable
is useful for assessing whether the Bowersox/Daugherty typology is
associated with this important goal of logistics. Customer Service
Commitment (CSC) is a scale that assesses customer service's level
of importance (emphasis on employee development and training), value as
a coordinating activity, and importance in achieving competitive goals.
The third dependent variable, Company/Division Competitiveness (COMP),
evaluates the firms' overall competitiveness in the areas of
responsiveness and perceived overall competition. These three dependent
variables provide a means of assessing whether changes in the
independent variables (Process, Market, and Information strategies)
result in changes of logistics outcomes.
Based on the above questions the following null hypotheses were
developed:
[H.sub.1]: The importance of Process Strategy is equally relevant
in small and large manufacturing firms;
[H.sub.2]: The importance of Marketing Strategy is equally relevant
in small and large manufacturing firms;
[H.sub.3]: The importance of Information Strategy is equally
relevant in small and large manufacturing firms;
[H.sub.4]: The importance of Logistics Coordination Effectiveness
is equally relevant in small and large manufacturing firms;
[H.sub.5]: The importance of Customer Service Commitment is equally
relevant in small and large manufacturing firms;
[H.sub.6]: The importance of Company/Division Competitiveness is
equally relevant in small and large manufacturing firms;
The six hypotheses provide a basis for assessing logistics
strategies of small firms. If the first three hypotheses are accepted
then there is insufficient evidence to conclude that the importance of
Process, Market, and Information strategies of small firms are different
between small and large firms. On the other hand, rejection of
hypotheses 1, 2, or 3 would indicate that the logistics strategies in
small firms differ from logistics strategies in large firms. In a
similar manner, acceptance of the second group of three hypotheses would
suggest that small and large firm logistics managers' perceptions
of three outcomes (Logistics Coordination Effectiveness, Customer
Service Commitment, and Company/Division Competitiveness) were equal.
Conversely, rejection of hypotheses 4, 5, or 6 would then suggest that
logistics managers of small and large firms perceived logistics strategy
outcomes differently.
METHODOLOGY
In 2006 a four-page, 41-item questionnaire was mailed to 700 small
manufacturing firms selected randomly from the Directory of
Manufacturers. The focus was exclusively on firms with annual sales of
$5,000,000 or less. Ninety-nine (14.1%) usable responses were received.
While the response rate was low, one-way analysis of variance by order
of response quartile found no significant differences at alpha = 0.05
among the six questionnaire items that related to logistics strategy.
The authors concluded that the data was adequate for use in studying
logistics strategies in small U.S. manufacturing firms.
In 2008 a four-page, 46-item questionnaire was electronically sent
to 905 members of a large national supply chain management organization
who worked for manufacturing firms in the U.S. with sales of over
$5,000,000. Large firms of over $5,000,000 sales were selected in order
to provide a basis for comparison with the data gathered on small firms
in 2006. The members sampled typically worked for large national or
multinational organizations that have substantial manufacturing presence
in the U.S. No attempt was made to control for country of ownership. One
hundred and twenty-three were undeliverable for a net sample of 782
subjects. After two follow-ups a total of forty-nine (6.3%) usable
responses were returned. While the response rate was low, it is
understandable given the results of similar recent studies reported in
the supply chain management literature (Flint, Larsson, and Gammelgaard,
2008). As a further test the 2008 results were compared to previous data
sampled from the same organization in 1990, 1994, and 1999 (McGinnis,
Kohn, and Spillan, 2010). Mean responses did not vary significantly
using one-way ANOVA. The authors concluded that the 2008 data was
adequate as a large firm control in assessing small firm responses.
ANALYSIS
As noted earlier, three independent variables and three dependent
variables were selected for the assessment of logistics strategies in
small and large manufacturing firms. Each of the variables was a
multi-item scale that had been developed in previous logistics strategy
research and was documented in a comprehensive review of multi-item
scales reported by Keller, et al. (2002). In addition, all scales
exhibited stable levels of reliability over their use in several
empirical studies and offered adequate face validity to warrant their
continued use.
Table 1 summarizes the three independent variable scales titled
Process Strategy, Market Strategy, and Information Strategy (also
referred to as channel strategy). Each scale was comprised of three
questionnaire items that had been previously used in several empirical
studies. Further inspection of Table 1 reveals that the average
reliability coefficient (alpha) for the scale Process Strategy over
three studies in 1990, 1994, and 1999 was 0.638, above the range of 0.50
to 0.60 considered adequate by Nunnaly (1967) and just below the value
of 0.70 suggested by Nunnally and Bernstein (1994). Because the range of
alphas was 0.579 to 0.710 in the previous three studies the authors
concluded that reliability was adequate for use in the current study.
Finally, the average alphas (Market Strategy = 0.730 and Information
Strategy = 0.605) for three previous studies indicated that those scales
would be defensible independent variables for this research. A review of
results from the 2006 (small firm) and 2008 (large firm) studies further
supported the relevance of the three scales as independent variables.
Coefficient of Reliability--Alpha
Process Strategy Market Strategy Information Strategy
1990 .626 .811 .520
1994 .710 .642 .727
1999 .579 .737 .568
2006 .726 .685 .856
2008 .609 772 .699
The three dependent variables are shown in Table 2. Two of the
scales, Logistics Coordination Effectiveness and Customer Service
Commitment were comprised of three items while the third scale,
Company/Division Competiveness, consisted of four items. Examination of
alpha averages and ranges for the three scales for 1990, 1994, and 1999
(Logistics Coordination Effectiveness average alpha = 0.632, range =
0.539 to 0.708; Customer Service Commitment alpha average = 0.708, range
= 0.673 to 0.729; Company/Division Competitiveness alpha average =
0.740, range = 0.675 to 0.862) resulted in the authors' conclusion
that these scales were adequate for purposes of this research. Further
examination of the alphas of these three scales for the 2006 (small
firm) and 2008 (large firm) did not alter that conclusion.
A second evaluation of the six scales was conducted to assess
whether there was any systematic bias between the responses to the 2006
(small firm) and the 2008 (large firm) questionnaires. As shown in Table
3 means of the scale scores did not vary significantly between the two
questionnaires. Mean responses of the nineteen items that comprise the
six scales was conducted to further assess the 2006 and 2008 data. As
shown in the Appendix, the means of six of nineteen items were
significantly different, alpha <0.05, without any systematic pattern
relative to the scales. Based on these results the authors concluded
that there was no pattern of differences that would prohibit a
comparison of logistics strategies of small and large manufacturing
firms using the 2006 and 2008 data.
From the results shown in Tables 1, 2, and 3 the authors concluded
that the 2006 data (from small U.S. manufacturing firms) and the 2008
data (from large U.S. manufacturing firms) provides a reasonable basis
for comparing logistics strategies of small and large firms.
The balance of the analysis was conducted in two steps. First
cluster analysis was conducted on the independent variables to ascertain
whether logistics strategies were homogenous within (a) small firms and
(b) large firms. Data was analyzed using SPSS 15.0 for Windows. The
program selected was Two-step Cluster. Output included cluster
frequencies, scale means and standard deviations, and the assignment of
each respondent to one of the clusters. Clusters were named using a
criteria based on means of the scale scores. "Intense Logistics
Strategy" was defined as a cluster in which one or more scale
average scores was less than 2.000, keeping in mind that low scores were
considered in agreement with item statements and high scores were
associated with disagreement. "Moderate Logistics Strategy"
was defined as a cluster in which none of the scales were below 2.000 or
greater than 2.999. Finally, "Passive Logistics Strategy" was
defined as a cluster where one or more scale averages was greater than
2.999.
In the final step of this analysis cluster membership was used to
assess respondent perceived attitudes toward the three dependent
variables, Logistics Coordination Effectiveness, Customer Service
Commitment, and Company/Division Competitiveness.
As shown in Table 4, the 2006 (small firm) respondents were
classified into three clusters. Cluster mean differences were assessed
for small firms using One-way Analysis of Variance. Post hoc analysis of
the ANOVA output revealed that all means were significantly different
with p values <0.05. The authors concluded that the three logistics
strategies for small firms were distinct with no commonality in the
independent variables. Forty-four (39.3%) respondents were classified as
having "Intense" logistics strategies. All three independent
variables (process, market, and information strategies) had scale means
that were significantly lower than the other two strategies. Average
score means for these respondents were near "agree". This
means that those respondents placed positive emphasis on all three
independent variables.
Forty-eight (42.9%) small business respondents were grouped into
"Moderate" strategies. Scale score means for all three
independent variables were between "agree" and "neither
agree nor disagree", indicating modest emphasis on the three
independent variables. Twenty respondents (17.9%) were classified as
having "Passive" logistics strategies. Scale score averages
for process, market, and information strategies were 3.0 (neither agree
nor disagree) or higher (tending toward disagreement).
Large firm respondents (see Table 4) were classified into two
logistics strategy groups. Thirty-five respondents (71.4%) were
classified as having "Intense" logistics strategies and
fourteen (28.6%) were classified as having "Passive" logistics
strategies.
Further analysis of means of small and large firm means for
"Intense Logistics Strategy" and "Passive Logistics
Strategy" provided additional insights. See the "Comparison of
Differences of Mean Scale Scores" portion of Table 4. This analysis
revealed that, when logistics strategies were "Intense" small
firms' scale score means for Process Strategy and Information
Strategy were significantly more important than large firms. Further,
the scale score means for Market Strategy did not vary by an amount
greater than due to chance. However, when logistics strategies were
"Passive" scale score means between small and large firms for
Process Strategy, Market Strategy, and Information Strategy did not vary
by an amount greater than that due to chance.
The results shown in Table 4 indicate that logistics strategies in
small firms group into three categories while logistics strategies in
large firms group into two categories. This suggests that small firms
may be able to stay closer to their markets and tailor their strategies
more closely to specific needs of those markets. In addition, small firm
"Intense" strategies emphasize cost (Process Strategies) and
coordination information flows in the channel (Information Strategy) to
a greater extent than in large firms. Again, this may be due to the
ability of small firms to better focus their strategies on the needs of
their markets.
This observation is further reinforced by the size of
"Moderate" logistics strategies in small firms, which are less
focused than "Intense" strategies but are definitely not
"Passive". Finally, comparison of "Passive"
strategies in small and large firms (Shown in Table 4) reveals a similar
focus in small and large firms.
Overall, logistics strategies in small and large manufacturing
firms differ in degree rather than type. In small firms overall
logistics strategies are more finely segmented than in large firms.
However, gradations in strategy from "Intense" to
"Passive" are similar in both large and small firms. The
following paragraphs discuss outcomes of logistics strategies in small
and large firms.
The logistics strategy clusters developed from the independent
variables and shown in Exhibit 4 were used to assess respondent
perceptions of the dependent variables. As shown in Table 5
"Logistics Coordination Effectiveness" (LCE) and
"Customer Service Commitment" (CSC) are highest in importance
when logistics strategies are "Intense" and lowest in
importance when logistics strategies ware "Passive" for both
small and large firms. However, the effect of logistics strategy on
"Company/Division Competitiveness" (COMP) is less clear. As
shown in Table 5, in small firms the means of COMP were not
significantly different between "Intense" and
"Moderate" logistics strategies but were significant for
"Passive" logistics strategies.
Further examination of Table 5 reveals that the outcome differences
between small and large firms were modest. There was one significant
difference at alpha = 0.05 for CSC when logistics strategies were
"Intense" (CSC was more important to small firms). Overall,
logistics strategy outcomes in small and large firms were similar. It
was concluded that differences in logistics strategy outcomes were
modest when comparing small and large manufacturing firms.
FINDINGS
Any analysis and findings must be presented as tentative but forms
the basis for additional testing. However, these findings provide
insights into similarities and differences in logistics strategies
between small and large U.S. manufacturing firms
Similarities
The similarities of logistics strategies in small and large U.S.
manufacturing firms were extensive. The coefficients (alphas) of the six
scales, as shown in Tables 1 and 2, varied between small firm and large
firm respondents by amounts comparable to or less than the variation
among those of large firms respondents in four (1990, 1994, 1999, and
2008) empirical studies (McGinnis, Kohn, and Spillan, 2010). Mean
responses to all six scales did not vary significantly between small and
large firm respondents (see Table 3). This indicates that the subjects
in both small and large manufacturing firms have similar perceptions of
logistics strategy and of logistics strategy outcomes. The authors
concluded that the scales used in this research are applicable to U.S.
manufacturing firms regardless of size. This finding is consistent with
insights from Clinton and Closs (1997) that responses (on a different
set of questionnaire items regarding logistics strategy) from Canadian
manufacturing firms and merchandising firms did not vary substantially,
which suggests that the scales used in this research may be robust in
applications beyond U.S. manufacturing firms.
Examinations of Tables 3 and 4 reveal that Process Strategy is
perceived as most important overall, in each logistics strategy cluster
in small manufacturing firms, and each logistics strategy cluster of
large manufacturing firms. This finding is consistent with the results
of research discussed in the literature review and suggests that the
control of costs and rationalizing complex logistics activities is a
priority of logistics strategy regardless of firm size.
Additional examination of Table 4 indicates that logistics
strategies of both large and small U.S. manufacturing firms can be
clustered into similar categories. Further examination of Table 4
reveals that, with one exception, the values of the three logistics
strategy dimensions (Process, Market, and Information) do not vary
between small and large firms regardless of logistics strategy
intensity. The exception is that, when logistics strategy is intense,
Process Strategies are significantly more important in small firms than
in large firms. Based on these results the authors concluded that
perceptions of logistics strategy do not differ substantially between
logistics managers in small and large manufacturing firms.
The effect of logistics cluster grouping on dependent variables,
Logistics Coordination Effectiveness (LCR), Customer Service Commitment
(CSC), and Company/Division Competitiveness (COMP), as shown in Table 5,
is similar for small and large manufacturing firms. Further examination
of Table 5 reveals that, with one exception, when strategy intensity
levels are the same the values of the three outcome variables do not
vary significantly between small and large firms. The exception is that,
when the logistics strategy is intense, logistics managers in small
firms place greater emphasis on Customer Service Commitment, apparently
because of its importance as a source of competitive advantage to small
firms.
In summary, logistics strategies and perceived logistics strategy
outcomes appear to be similar in small and large firms except when the
logistics strategy is "Intense". In this scenario logistics
managers in small firms are more likely to place greater emphasis on
cost management (Process Strategy) and have higher levels of commitment
to customer service (Customer Service Commitment).
Overall, no systematic patterns of differences in means of scale
score means for Process, Market, and Information strategies or Logistics
Coordination Effectiveness, Customer service commitment, and
Company/Division Competitiveness were found that would lead to the
conclusion that small and large U.S. manufacturing company logistics
strategies are fundamentally different. This supports a conclusion that
small and large U.S. manufacturing firms' logistics strategies are
not fundamentally different.
Differences
The most significant difference between small and large U.S.
manufacturing firms, as shown in Table 4, is the number of logistics
strategy clusters. Respondents in small firms grouped into three
strategies. They were "Intense" (39.3% of respondents),
"Moderate" (42.9%), and "Passive" (17.9%) logistics
strategies (percentages do not add to 100 due to rounding). Large firm
respondents grouped into two logistics strategies, "Intense"
(71.3%) and "Passive" (28.6%). Again, percentages do not add
to 100 due to rounding. The greater gradation of logistics strategies of
small firms may be due to (a) greater small firm awareness of market
subtleness, and/or (b) greater variations of overall strategies among
small firms, and/or (c) an ability of small firms to tailor logistics
strategies more closely to customer requirements.
Forty four (39.3%) small firms were grouped into the "Intense
Logistics Strategy" category while thirty-five (71.4%) of large
firm respondents were grouped into that category. This may suggest that
(a) small manufacturing firms are less sophisticated in their logistics
management, and/or (b) logistics is of less overall importance in small
firms, and/or (c) small firms face less supply chain complexity. The
authors suspect that (c) is the reason that small firms are less likely
to need an "Intense Logistics Strategy".
Examination of the results shown in Table 5 indicate that, when
logistics strategies are "Intense" small firms place greater
emphasis on "Customer Service Commitment" (CSC) than do large
firms. This suggests that small firms may place greater emphasis on
customer service than large firms because (a) high levels of customer
service may differentiate some small firms from their larger
competitors, (b) of the need to focus on the needs of a limited number
of important customers, and (c) of a response to the demands of their
customer base.
Overall Findings
Based on an assessment of the similarities and differences of small
and large manufacturing firms the following conclusions were reached
regarding the six null hypotheses:
[H.sub.1]: The importance of Process Strategy is equally relevant
in small and large manufacturing firms. This hypothesis was partially
supported by results shown in Tables 3 and 4. The means of Process
Strategy were not significantly different between small and large firms
overall (Table 3) nor when logistics strategies were "Passive"
(Table 4). Process Strategy was significantly more important in small
firms when the logistics strategy is "Intense" (Table 4).
[H.sub.2]: The importance of Marketing Strategy is equally relevant
in small and large manufacturing firms. This hypothesis was supported by
the results shown in Tables 3 and 4.
[H.sub.3]: The importance of Information Strategy is equally
relevant in small and large manufacturing firms. This hypothesis was
partially supported by results shown in Tables 3 and 4. Information
Strategy was not significantly different between small and large firms
overall (Table 3) nor when logistics strategies were "Passive"
(Table 4). Information Strategy is more important in small firms when
the logistics strategy is "Intense" (Table 4).
[H.sub.4]: The importance of Logistics Coordination Effectiveness
is equally relevant in small and large manufacturing firms. This
hypothesis was supported by the results shown in Tables 3 and 5.
[H.sub.5]: The importance of Customer Service Commitment is equally
relevant in small and large manufacturing firms. This hypothesis is
partially supported by Tables 3 and 5. The means of Customer Service
Commitment were not significantly different overall (Table 3) nor when
logistics strategies were "Passive" (Table 5). Customer
Service Commitment was significantly more important in small firms when
logistics strategy was "Intense" (Table 5).
[H.sub.6]: The importance of Company/Division Competitiveness is
equally relevant in small and large manufacturing firms. This hypothesis
was supported by the results shown in Tables 3 and 5.
The results suggest more similarities between small and large firm
logistics strategies and outcomes than differences. Two independent
variables (Process Strategy and Information Strategy) were more
important; one dependent variable (Customer Service Commitment) was of
greater importance in small firms when strategies were
"Intense" (note that in this study 1 = strongly agree, 5 =
strongly disagree); the three independent and three dependent variables
did not vary overall (Table 3); and nine of twelve comparisons (Tables 4
and 5) were not significant at alpha = 0.05.
When differences between logistics strategies of small and large
U.S. manufacturing firms occur, they are likely to occur when logistics
strategies are "Intense". According to the results when
logistics strategies are "Intense" small firms are likely to
place more importance on Process and Information strategies and have a
better Customer Service Commitment outcome than large firms. When
logistics strategies are "Passive" the levels of importance
placed on Process, Market, and Information strategies and the outcomes
of Logistics Coordination Effectiveness and Competitiveness are likely
to be similar.
CONCLUSIONS
When considered within the context of previous research into the
Bowersox/Daugherty typology the findings of this research contribute to
a further understanding of logistics strategy. First, logistics
strategies in small and large U.S. manufacturing firms differ in degree
rather than type. Process (control costs), Market (reduce complexity
faced by competitors), and Information (facilitate coordination in the
channel) strategies are evident in small and large firms. While the
roles of these three dimensions are not perfectly aligned, the
similarities are great enough to conclude that logistics strategies in
small and large U.S. manufacturing firms are similar. Second, perceived
logistics strategy outcomes of small and large manufacturing firms are
similar. Increased levels of Logistics Coordination Effectiveness,
Customer Service Commitment, and Company/Division Competitiveness were
(with one exception) associated with greater intensity of logistics
strategy in small and large firms. This suggests that outcomes of
logistics strategies do not differ substantially as firm size varies.
Given that logistics strategies and logistics strategy outcomes are
similar between small and large U.S. manufacturing firms it was
concluded that the Bowersox/Daugherty typology is applicable to
manufacturing firms regardless of size.
This research implies that the focal points of logistics in small
and large firms are cost management (Process Strategy), reducing
complexity faced by customers (Market Strategy), and coordination within
the channel (Information Strategy). While the emphasis on these three
components of logistics strategy may vary due to factors such as overall
strategy of the firm, the degree of competition faced, and the relative
importance of the firm's competitive advantages (cost,
differentiation, or both), these factors may affect logistics strategy
more than firm size.
Implications for Practice
Balancing the relationship among process strategy, market strategy,
and information strategy, is challenging. It will require substantial
coordination of logistics/ supply chain managers with firms'
management team, channel members, suppliers, and other stakeholders. It
will also require that the firm's management constantly read and
re-read its environments over time to understand competitive threats and
opportunities for logistics strategy innovation. Logistics/supply chain
managers in firms of all sizes (small and large) can benefit from
understanding the dynamics of cost management, reducing the complexity
faced by customers, and using information to better coordinate channel
activities when tailoring logistics strategies for their firms.
Small businesses can benefit from a greater understanding of
logistics strategy's components and how they can be exploited to
improve competitiveness in their markets. Overall, logistics strategy
consists of managing costs (Process), simplifying complexity faced by
customers (Market), and coordination of information flows (Information)
to improve logistics coordination and customer service as a means of
maintaining (or improving) competitiveness. This research suggests that
the small firms manage the logistics strategy to maximize customer
service through emphasis on Market (reduce complexity faced by
customers) and Information (close coordination with customers and
suppliers) strategies. While Process (cost control) is also likely to be
important to small businesses, it is unlikely to be paramount, relative
to Market and Information strategies.
Implications for Education, Training, and Research
Logistics/supply chain educators can use the insights from this
research to focus on three dimensions of logistics/supply chain
management and their relevance regardless of the firm's size. At
the basic level emphasizing the three components of logistics strategy
(Process, Market, and Information) provide fundamentals that should
serve the student well whether or not they pursue further studies in
logistics/supply chain management. At the advanced level; process,
market, and information strategies can be the basis for integrating
logistics/supply chain management with other areas of the firm. Finally,
graduate students should benefit from the insights provided by the
Bowersox/Daugherty typology in developing research agendas and teaching
strategies.
Future research opportunities include extensions of logistics
decision making by including antecedents and moderating factors (such as
competition, market turbulence, and differences in business environment)
into the design. Future research should also examine the relevance of
the Bowersox/Daugherty typology to small and large firms in
nonmanufacturing industries including retailing, healthcare, financial
services, transportation firms, and food service. These industries may
provide different perspectives on process, market, and information
strategies as well as logistics coordination, customer service, and
competitiveness.
APPENDIX 1
COMPARISON OF 2006 AND 2008 ITEM MEAN SCORES: *
INDEPENDENT VARIABLES
N/Means */
Standard/
Deviations
Items 2006 2008
Scale 1: Process Strategy
(PROCSTR) *
PS/1 In my company/division, 128/1.92/0.790 50/1.94/0.818
management emphasizes achieving
maximum efficiency from
purchasing, manufacturing, and
distribution.
PS-2 A primary objective of 127/2.15/0.746 50/2.12/0.824
logistics in my company/division
is to gain control over
activities that result in
purchasing, manufacturing, and
distribution costs.
PS-3 In my company/division, 124/2.61/0.969 50/2.50/0.995
logistics facilitates the
implementation of cost and
inventory reducing concepts such
as Focused Manufacturing and
Just-in-Time Materials
Procurement.
Scale 2: Market Strategy
(MKTGSTR) *
MS-1 In my company/division, 117/2.91/0.820 49/2.53/1.209
management emphasizes achieving
coordinated physical distribution
to customers served by several
business units. 0.093
MS-2 A primary objective of 126/2.22/.0838 50/2.36/1.139
logistics in my company/division
is to reduce the complexity our
customers face in doing business
with us.
MS-3 In my company/division, 121/2.72/0.868 49/2.31/1.158
logistics facilitates the
coordination of several business
units in order to provide
competitive customer service.
Scale 3: Information Strategy
(INFOSTR) *
IS-1 In my company/division, 118/2.83/0.840 49/2.78/0.941
management emphasizes
coordination and control of
channel members (distributors,
wholesalers dealers, retailers)
activities.
IS-2 A primary objective of 124/2.54/0.914 50/2.64/1.005
logistics in my company/division
is to manage information flows
and inventory levels throughout
the channel of distribution.
IS-3 In my company/division, 119/2.87/0.780 50/3.16.0.912
logistics facilitates the s,
management of information flows
among channel members
(distributors, wholesaler
dealers, retailers).
Mean
Differences
Significant
Items <0.05?
Scale 1: Process Strategy
(PROCSTR) *
PS/1 In my company/division, NO
management emphasizes achieving
maximum efficiency from
purchasing, manufacturing, and
distribution.
PS-2 A primary objective of NO
logistics in my company/division
is to gain control over
activities that result in
purchasing, manufacturing, and
distribution costs.
PS-3 In my company/division, NO
logistics facilitates the
implementation of cost and
inventory reducing concepts such
as Focused Manufacturing and
Just-in-Time Materials
Procurement.
Scale 2: Market Strategy
(MKTGSTR) *
MS-1 In my company/division, YES
management emphasizes achieving
coordinated physical distribution
to customers served by several
business units. 0.093
MS-2 A primary objective of NO
logistics in my company/division
is to reduce the complexity our
customers face in doing business
with us.
MS-3 In my company/division, YES
logistics facilitates the
coordination of several business
units in order to provide
competitive customer service.
Scale 3: Information Strategy
(INFOSTR) *
IS-1 In my company/division, NO
management emphasizes
coordination and control of
channel members (distributors,
wholesalers dealers, retailers)
activities.
IS-2 A primary objective of NO
logistics in my company/division
is to manage information flows
and inventory levels throughout
the channel of distribution.
IS-3 In my company/division, YES
logistics facilitates the
management of information flows
among channel members
(distributors, wholesaler
dealers, retailers).
* Scales: 1 = Strongly Agree, 2 = Agree, 3 = Neither Agree nor
Disagree, 4 = Disagree, 5 = Strongly Disagree.
DEPENDENT VARIABLES
N/Means */
Standard/
Deviations
Items 2006 2008
Logistics Coordination
Effectiveness (LCE) *
LC-1 The need for closer 130/2.53/0.900 50/2.30/0.647
coordination with suppliers,
vendors, and other channel
members has fostered better
working relationships among
departments within my company.
LC-2 In my company logistics 130/2.76/0.852 50/2.74/0.899
planning is well coordinated with
the overall strategic planning
process.
LC-3 In my company/division 128/2.57/0.829 50/2.70/0.974
logistics activities are
coordinated effectively with
customers, suppliers, and other
channel members.
CUSTOMER SERVICE COMMITMENT
(CSC) *
CSC-1 Achieving increased levels 128/2.30/0.865 50/2.60/0.926
of customer service has resulted
in increased emphasis on employee
development and training.
CSC-2 The customer service 128/2.57/0.770 50/2.72/1.089
program in my company/division is
effectively coordinated with
other logistics activities.
CSC-3 The customer service 128/2.36/0.849 50/2.58/0.992
program in my company/division
gives us a competitive edge
relative to our competition.
COMPANY/DIVISION COMPETITIVENES
(COMP) *
COMP-1 My company/division 127/2.06/0.759 49/2.53/1.023
responds quickly and effectively
to changing customer or supplier
needs compared to our
competitors.
COMP-2 My company/division 126/2.43/0.784 49/2.67/0.851
responds quickly and effectively
to changing competitor strategies
compared to our competitors.
COMP-3 My company/division 123/2.81/0.872 49/2.65/0.830
develops and markets new products
quickly and effectively compared
to our competitors.
COMP/4 In most of its markets my 123/2.34/0.848 50/1.84/0.912
company/division is a:
Very Moderately Weak
Strong Strong Competitor
1 2 3 4 5
Mean
Differences
Significant
Items <0.05?
Logistics Coordination
Effectiveness (LCE) *
LC-1 The need for closer NO
coordination with suppliers,
vendors, and other channel
members has fostered better
working relationships among
departments within my company.
LC-2 In my company logistics NO
planning is well coordinated with
the overall strategic planning
process.
LC-3 In my company/division NO
logistics activities are
coordinated effectively with
customers, suppliers, and other
channel members.
CUSTOMER SERVICE COMMITMENT
(CSC) *
CSC-1 Achieving increased levels YES
of customer service has resulted
in increased emphasis on employee
development and training.
CSC-2 The customer service NO
program in my company/division is
effectively coordinated with
other logistics activities.
CSC-3 The customer service NO
program in my company/division
gives us a competitive edge
relative to our competition.
COMPANY/DIVISION COMPETITIVENES
(COMP) *
COMP-1 My company/division YES
responds quickly and effectively
to changing customer or supplier
needs compared to our
competitors.
COMP-2 My company/division NO
responds quickly and effectively
to changing competitor strategies
compared to our competitors.
COMP-3 My company/division NO
develops and markets new products
quickly and effectively compared
to our competitors.
COMP/4 In most of its markets my YES
company/division is a:
Very Moderately Weak
Strong Strong Competitor
1 2 3 4 5
* Scales: 1 = Strongly Agree, 2 = Agree, 3 = Neither Agree nor
Disagree, 4 = Disagree, 5 = Strongly Disagree.
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Flint, Daniel J., Everett Larsson, and Britta Gammelgaard (2008),
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Business Logistics, 29(1): 257-281.
Halley, Alian, and Alice Guilhon, (1997), "Logistics Behavior
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Keller, Scott B., et al. (2002), "A Summary and Analysis of
Multi-items Scales Used in Logistics Research," Journal of Business
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Kohn, Jonathan W. and Michael A. McGinnis (1997a), "Logistics
Strategy: A Longitudinal Study," Journal of Business Logistics,
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Logistics Organization Structures: Revisited," Journal of Business
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Strategy, Organizational Environment, and Time Competitiveness,"
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McGinnis, Michael A. and Jonathon W. Kohn (2002), "Logistics
Strategy--Revisited," Journal of Business Logistics, 23(2): 1-17.
McGinnis, Michael A., Jonathan W. Kohn, and John E. Spillan (2010),
"A Longitudinal Study of Logistics Strategy: 1990-2008,"
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John E. Spillan
University of North Carolina at Pembroke
Jonathan W. Kohn
Shippensburg University
Michael A. McGinnis
The Pennsylvania State University
New Kensington
AUTHORS BIOGRAPHY
John E. Spillan is Associate Professor of Business Administration
at the University of North Carolina at Pembroke, School of Business. He
received a M.B.A. degree from the College of Saint Rose in Albany, New
York and a Ph.D. from the Warsaw School of Economics. His research
interests center on Crisis Management, International Marketing,
Entrepreneurship and International Business with specific interest in
Latin America and Eastern Europe. E-mail: jspillan@uncp.edu
Jonathan W. Kohn is Professor of Supply Chain Management, John L.
Grove College of Business, Shippensburg University at Shippensburg, PA.
He received his Masters in Electrical Engineering and Ph.D. in
Industrial Engineering from New York University. His research interests
are in logistics and supply chain strategic management, structural
modeling of the housing market, and student assessment of faculty.
E-mail: jwkohn@ship.edu
Michael A. McGinnis, CPSM, C.P.M. is Associate Professor of
Business at Penn State University New Kensington Campus. He holds B.S.
and M.S. degrees from Michigan State University and a D.B.A. degree from
the University of Maryland. His research areas are purchasing, logistics
strategy, negotiations, and supply chain management. E-mail:
mam47@psu.edu
TABLE 1
INDEPENDENT VARIABLES
Scale 1: Process Strategy (PROCSTR) *
PS-1 In my company/division, management emphasizes achieving
maximum efficiency from purchasing, manufacturing, and
distribution.
PS-2 A primary objective of logistics in my company/division is to
gain control over activities that result in purchasing,
manufacturing, and distribution costs.
PS-3 In my company/division, logistics facilitates the
implementation of cost and inventory reducing concepts such as
Focused Manufacturing and Just-in-Time Materials Procurement.
Scale 2: Market Strategy (MKTGSTR) *
MS-1 In my company/division, management emphasizes achieving
coordinated physical distribution to customers served by several
business units.
MS-2 A primary objective of logistics in my company/division is to
reduce the complexity our customers face in doing business with us.
MS-3 In my company/division, logistics facilitates the coordination
of several business units in order to provide competitive customer
service.
Scale 3: Information Strategy (INFOSTR) *
IS-1 In my company/division, management emphasizes coordination and
control of channel members (distributors, wholesalers, dealers,
retailers) activities.
IS-2 A primary objective of logistics in my company/division is to
manage information flows and inventory levels throughout the
channel of distribution.
IS-3 In my company/division, logistics facilitates the management
of information flows among channel members (distributors,
wholesalers, dealers, retailers).
* Scales: 1 = Strongly Agree, 2 = Agree, 3 = Neither Agree nor
Disagree, 4 = Disagree, 5 = Strongly Disagree.
TABLE 2 DEPENDENT VARIABLES Logistics Coordination Effectiveness
(LCE) *
LC-1 The need for closer coordination with suppliers, vendors, and
other channel members has fostered better working relationships
among departments within my company.
LC-2 In my company logistics planning is well coordinated with the
overall strategic planning process.
LC-3 In my company/division logistics activities are coordinated
effectively with customers, suppliers, and other channel members.
CUSTOMER SERVICE COMMITMENT (CSC) *
CSC-1 Achieving increased levels of customer service has resulted
in increased emphasis on employee development and training.
CSC-2 The customer service program in my company/division is
effectively coordinated with other logistics activities.
CSC-3 The customer service program in my company/division gives us
a competitive edge relative to our competition.
COMPANY/DIVISION COMPETITIVENES (COMP) *
COMP-1 * My company/division responds quickly and effectively to
changing customer or supplier needs compared to our
competitors.
COMP-2 * My company/division responds quickly and effectively to
changing competitor strategies compared to our competitors.
COMP-3 * My company/division develops and markets new products
quickly and effectively compared to our competitors.
COMP-4 In most of its markets my company/division is a:
Very Strong Moderately Strong Weak
Competitor Competitor Competitor
1 2 3 4 5
* Scales: 1 = Strongly Agree, 2 = Agree, 3 = Neither Agree nor
Disagree, 4 = Disagree, 5 = Strongly Disagree.
DEPENDENT VARIABLES
Coefficient of Reliability--Alpha
Logistics Customer Service Company/Division
Coordination Commitment Competitiveness
Effectiveness
1990 .539 .723 .684
1994 .649 .729 .862
1999 .708 .673 .675
2006 .582 .706 .740
2008 .538 .653 .701
Table 3
COMPARISON OF MEANS OF SCALE SCORES *:
2006 (SMALL U.S. MANUFACTURING FIRMS) &
2008 (LARGE U.S. MANUFACTURING FIRMS)
N/
Means **/
Standard Mean
Deviations Differences
Significant
Scales 2006 2008 <0.05?
Process Strategy (PROCSTR) 124/ 50/
2.24/ 2.19/
0.665 0.660 NO
Market Strategy (MKTGSTR) 117/ 49/
2.62/ 2.41/
0.651 0.968 NO
Information Strategy (INFOSTR) 116/ 49/
2.74/ 2.85/
0.719 0.758 NO
Logistics Coordination Effectiveness 128/ 50/
(LCE) 2.62/ 2.58/
0.636 0.609 NO
Customer Service Commitment (CSC) 127/ 50/
2.41/ 2.63/
0.673 0.772 NO
Company/Division Competitiveness 119/ 48/
(COMP) 2.39/ 2.42/
0.602 0.659 NO
* Scale Scores = (Sum of item scores of items in that scale)/(Number
of items)
** Scales: 1 = Strongly Agree, 2 = Agree, 3 = Neither Agree nor
Disagree, 4 = Disagree, 5 = Strongly Disagree.
TABLE 4
COMPARISON OF CLUSTER ANALYSES RESULTS OF LOGISTICS STRATEGIES:
2006 (SMALL U.S. MANUFACTURING FIRMS) &
2008 (LARGE U.S. MANUFACTURING FIRMS)
2006--National Sample of Small U.S. Manufacturing Firms, N = 112
PROCSTR MKTGSTR INFOSTR
Mean */ Mean/ Mean/
Standard Standard Standard
Cluster ** Deviation Deviation Deviation
1. Intense Logistics 1. 674/0.397 2. 227/0.579 2.152/0.424
Strategy, N = 44
2. Moderate Logistics 2. 542/0.433 2. 625/0.387 2. 813/0.329
Strategy, N = 48
3. Passive Logistics 3. 000/0.405 3. 450/0.475 3.817/0.587
Strategy, N = 20
Significance 0.000 0.000 0.000
2008--National Sample of Large U.S. Manufacturing Firms, N = 49
PROCSTR MKTGSTR INFOSTR
Mean **/ Mean/ Mean/
Standard Standard Standard
Cluster ** Deviation Deviation Deviation
1. Intense Logistics 1.895/0.456 2.000/0.741 2.610/0.688
Strategy, N = 35
2. Passive Logistics 2.905/0.561 3.429/0.672 3.476/0.550
Strategy N = 14
Significance 0.000 0.000 0.000
* Scales: 1 = Strongly Agree, 2 = Agree, 3 = Neither Agree nor
Disagree, 4 = Disagree, 5 = Strongly Disagree.
** Cluster Classification:
Intense Logistics Strategy: One or more values of PROCSTR, MKTGSTR, or
INFOSTR <2.000.
Moderate Logistics Strategy: No values of PROSTR, MKTGSTR,
or INFOSTR <2.000 or >2.999.
Passive Logistics Strategy: One or more values of PROCSTR, MKTGSTR, or
INFOSTR >2.999 or greater.
COMPARISON OF DIFFERENCES OF MEAN SCALE SCORES
Intense Difference Between (Small--Large) Mean Scale Scores
t-value (small-large) Process Market Information
-2.265 1.487 -3.451
p-values 0.026 0.141 0.001
Conclusion Sig. * Not Sig. Sig. *
* Process strategy in small firms is more important than in larger
firms.
* Information strategy in small firms is more important than in larger
firms.
Passive Difference Between (Small--Large) Mean Scale Scores
t-value (small-large) Process Market Information
0.542 0.101 1.730
p-values 0.591 0.920 0.093
Conclusion Not Sig. Not Sig. Not Sig.
TABLE 5
COMPARISON OF OF LOGISTICS STRATEGIES AND DEPENDENT VARIALBES
2006 (SMALL U.S. MANUFACTURING FIRMS) &
2008 (LARGE U.S. MANUFACTURING FIRMS)
2006--National Sample of Small U.S. Manufacturing Firms, N = 112
LCE CSC COMP
Mean **/ Mean/ Mean/
Standard Standard Standard
Cluster * Deviation Deviation Deviation
1. Intense Logistics 2.349/0.561 2.053/0.579 2.174/0.544
Strategy, N = 44
2. Moderate Logistics 2.722/0.635 2.549/0.556 2.438/0.639
Strategy, N = 48
3. Passive Logistics 3.117/0.475 3.000/0.764 2.790/0.509
Strategy, N = 20
Significance 0.000 0.000 0.001 ***
* See Exhibit 4 for criteria for cluster classification
** Scales: 1 = Strongly Agree, 2 = Agree, 3 = Neither Agree nor
Disagree, 4 = Disagree, 5 = Strongly Disagree.
*** Means for Clusters 1 and 2 not significantly different <0.05 with
Tukey B Post Hoc Test.
2008--National Sample of Large U.S. Manufacturing Firms, N = 49
LCE CSC COMP
Mean **/ Mean/ Mean/
Standard Standard Standard
Cluster * Deviation Deviation Deviation
1. Intense Logistics 2.371/0.497 2.400/0.695 2.324/0.644
Strategy, N = 44
2. Passive Logistics 3.143/0.518 3.214/0.687 2.661/0.655
Strategy N = 14
Significance 0.000 0.001 0.108***
* See Exhibit 4 for criteria for cluster classification
** Scales: 1 = Strongly Agree, 2 = Agree, 3 = Neither Agree nor
Disagree, 4 = Disagree, 5 = Strongly Disagree.
*** Means of Clusters 1 and 2 not significantly different <0.05.
COMPARISON OF DIFFERENCES OF MEAN SCALE SCORES
Intense Difference Between Small--Large Mean Scale Scores
LCE CSC COMP
t-value (Small-Large) -0.185 -2.371 -1.101
p-values 0.854 0.020 0.275
Conclusion Not Sig. Sig. ** Not Sig.
** Customer Service Commitment in small firms was greater than
large firms.
Passive Difference Between Small--Large Mean Scale Scores
LCE CSC COMP
t-value (Small-Large) -0.149 -0.853 0.618
p-values 0.882 0.400 0.541
Conclusion Not Sig. Not Sig. Not Sig.
