Gary L. Frazier & Walfried M. Lassar
Determinants of
Distribution Intensity
Within many categories of consumer products, manufacturers differ markedly in how intensively they distribute their
brands among retailers. The authors enhance understanding of why such differences in distribution intensity occur.
Literature in the marketing and economics disciplines on brand and channel management, agency theory, and
credible commitments, combined with extensive field interviews, provides the foundation for a conceptual framework that centers on proposed moderator effects. Data collected from manufacturers in the consumer electronics
industry are used to test the conceptual framework. Credible commitments by retailers in the form of contractual
agreements and investments are shown to moderate the relationships of manufacturer brand strategy and channel
practices with distribution intensity.
W
ithin many categories of consumer products, manufacturers seek intensive distribution for their
brands. That is, the objective is to distribute brands
through every available retailer in each trade area. Distribution success for such brands is judged, in part, by their percentage of all-commodity volume, which reflects the percentage of sales volume in the product category (e,g,, coffee,
peanut butter) accounted for by stores that carry the brand
(e,g,, Folgers, Skippy), A high level of distribution intensity
is sought for a majority of consumer nondurable goods.
In many other categories of consumer products, however, desired distribution pattems are not as straightforward.
By design, some brands are distributed intensively, whereas
others in the same product category are distributed selectively or exclusively. Examples of product categories in
which distribution intensity varies widely across brands are
bicycles, cameras, golf equipment, hair care products, pet
food, stereo speakers, ski equipment, and watches. Differences in distribution intensity across brands are high within
many consumer durable goods categories.
Distribution intensity has been corrimonly defined as the
number of intermediaries used by a manufacturer within its
trade areas (cf, Bonoma and Kosnik 1990; Corey, Cespedes,
and Rangan 1989; Stem, El-Ansary, and Coughlan 1996),
Ideal distribution intensity would make a brand available
widely enough to satisfy, but not exceed, target customers'
needs, because oversaturation increases marketing costs
without providing benefits (McCarthy and Perreault 1984),
The use of too few intermediaries can limit a brand's level
Gary L, Frazier is the Richard and Jarda Hurd Professor of Distribution
Management, School of Business Administration, University of Southern
California, Walfried M, Lassar is Assistant Professor of Marketing, Whittemore School of Business and Economics, University of New Hampshire,
The authors contributed equally to the article. They thank Robert Fisher,
Bernie Jaworski, David Stewart, and Allen Weiss (University of Southern
California); Erin Anderson (INSEAD); Barton Weitz (University of Florida);
the editor; and three anonymous JM reviewers for their guidance.
of exposure in the marketplace. However, using too many
intermediaries can be detrimental to the brand's image and
its competitive position. Accordingly, Stem, El-Ansary, and
Coughlan (1996, p, 340) state, "One of the key elements of
channel management is deciding how many sales outlets
should be established in a given geographic area,"
Despite its importance, distribution intensity has
received little attention in academic research. Within marketing, the primary theoretical thrust links product class to
distribution intensity (cf, Aspinwall 1958; Copeland 1923;
Miracle 1965), On the basis of their underiying characteristics, convenience goods are associated with intensive distribution, shopping goods are proposed to require selective distribution, and specialty goods are related to exclusive distribution. The product class framework appears to have strong
face validity, but does not address the question of why
brands within many categories of consumer products differ
in distribution intensity,
"Exclusivity of distribution" in relation to intensive distribution has been examined in the economics literature. In
opposition to traditional economic theory, many economists
now argue that exclusive distribution can have procompetitive effects when intermediary support is critical to the success of the brand (cf, Lafferty, Lande, and Kirkwood 1984;
Mathewson and Winter 1984; Rey and Tirole 1986; Winter
1993), Keeping intrabrand competition low may enhance
intermediaries' support of the brands they carry, which leads
to a possible increase in interbrand competition. The economics literature thus provides insight as to why some
brands in a product category may be less intensively distributed than others. However, the focus has been on the relationship between exclusive distribution and consumer welfare, not on building or testing theory to explain differences
in distribution intensity across brands.
In preparation for our study, we conducted interviews
with manufacturers and retailers in several industries.
These interviews indicated that managers in manufacturing
firms face a highly complex and difficult decision on distribution intensity that involves several trade-offs. Low distri-
Journat of Marketing
Vol. 60 (October 1996), 39-51
Distribution Intensity / 39
bution intensity may enhance the image of the brand and
promote retailer support but may entail limited market coverage and the potential for lost sales opportunities. High
distribution intensity may promote sales in the short run,
but long-term results are less clear (Stem, El-Ansary, and
Coughlan 1996).
The purpose of our article is to promote understanding
of why brands within many categories of consumer products
differ in distribution intensity. Building on prior definitions
in the channels literature, we define distribution intensity as
the extent to which a manufacturer relies on numerous
retailers in each trade area to carry its brand (cf. Bagozzi
1986; Corey, Cespedes, and Rangan 1989). Distribution
intensity is relatively low when manufacturers are highly
selective in their choice of associated retailers and put strict
limits on the number of retailers allowed to carry their
brands in each trade area.
On the basis of foundations in the economics and marketing di.sciplines and on our field interviews, our conceptual framework centers on how credible commitments by
retailers moderate other variables' relationships with distribution intensity. Credible commitments or pledges are specific actions undertaken by channel members that demonstrate good faith and bind them to relationships with other
channel members, at least to some degree (Anderson and
Weitz 1992; Williamson 1985). The signaling associated
with such retailer actions is expected to influence managers
in manufacturing organizations as they decide on appropriate levels of distribution intensity in light of their brand
strategy and channel practices. We test our conceptual
framework with data collected from manufacturers of stereo
speakers in the consumer electronics industry.
Our study is the first in which distribution intensity is the
focal construct. The combination of our integrative conceptual framework and empirical results improves our understanding of distribution intensity and its determinants. The
moderator effects we identify are especially illuminating.
Such knowledge is important as we strive to develop more
comprehensive theories of channel structure, in which distribution intensity plays a pivotal role (Rosenbloom 1995;
Stem, El-Ansary, and Coughlan 1996). Our findings provide
a foundation for exploration of the distribution intensity
construct in additional research.
Conceptual Framework
Development
Our initial conceptual framework was based on a thorough
review of the literature. Research in the marketing and economics fields on brand and channel management and on
agency theory helped identify the role of manufacturer
brand strategy and manufacturer channel practices in shaping distribution intensity. The identification of probable
moderating effects was based on the emerging literature on
credible commitments (cf. Anderson and Weitz 1992;
Williamson 1985). We conducted personal interviews with 4
manufacturers and 15 retailers in the consumer electronics,
pet food, and hair care industries to refine the basic rationale
of the conceptual framework.
40 / Journal of Marketing, October 1996
Further refinements were based on two additional steps.
First, a series of telephone interviews were conducted with
25 manufacturers of bicycles, cameras, electronics, golf
equipment, ski equipment, and watches. We asked them
about distribution intensity and the reasons for their distribution pattems. Second, 6 more retailers in the consumer
electronics industry were personally interviewed.
Shown in Figure I is the conceptual framework that
resulted from the refinement process. Two components are
seen to have significant main effects on distribution intensity: manufacturer hrand strategy, including brand positioning on quality and target focus, and manufacturer channel
practices, including manufacturer coordination efforts and
support programs. In addition, a retailer requirements component, consisting of contractual restrictiveness and retailer
investments, is seen to moderate relationships between the
other two components and distribution intensity. Certain
manufacturers require associated retailers to sign restrictive
contracts and make relatively heavy investments in support
of the brand. Such actions represent credible commitments
on the part of the retailers (Anderson and Weitz 1992; Rusbult 1980). Finally, a set of control variables was found to be
necessary in the conceptual framework.
Research Hypotheses
Manufacturer brand strategy. A brand's positioning on
quality reflects the extent to which a manufacturer attempts
to convey to consumers that the brand has superior ability to
perform its functions (Kotler and Armstrong 1993; ZeithamI
1988). Manufacturers of brands positioned near the low end
of the quality continuum are expected to rely on numerous
retailers in each trade area to promote convenience and competitive pricing for their customers. In contrast, manufacturers positioning their brands as high quality are likely to be
more diligent in screening prospective retailers, because
retailer image or reputation can influence the image of
brands within the store (Lusch and Dunne 1990; Pegram
1965). Retailers with strong store images and a reputation
for excellent operations are preferred. Such manufacturers
are less likely to align with retailers whose intemal operations and ability to sell and service high-end brands are
uncertain (Jacoby and Mazurski 1984). Relatively few
retailers are likely to surpass the standards of performance
established by manufacturers of high-end brands.
H|: The higher a brand is positioned on quality, the lower is its
level of distribution intensity.
Contractual restrictiveness reflects the extent to which a
formal agreement between a manufacturer and retailer
reduces retailer freedom of managerial choice. Standards of
conduct relating to brand sales goals, retailer behaviors, and
relationship termination can be imposed. Some manufacturers require associated retailers to accept highly restrictive
contracts, whereas other manufacturers use lenient contracts
or none at all.
Voluntarily constraining activities through contract
terms is a form of credible commitment from the retailer to
the manufacturer (Williamson 1983, 1985). Anderson and
Weitz (1992) define a credible commitment or pledge as a
specific action undertaken by a channel member that
FIGURE 1
Determinants of Distribution Intensity: Conceptual Framework
Retailer Requirements
(Credible Commitments)
Contractual Restrictions
Retailer Investments
Manufacturer
Brand Strategy
Manufacturer
Channel Practices
Positioning
on Quality
Coordination
Efforts
Target
Focus
Use of Distributors
Distribution
Intensity
Multiple Channels
Support
Programs
Brand Sales Volume
Control Variabtes
demonstrates good faith and binds it to a relationship with
another channel member. They go on to state that "contract
terms both commit the channel member and provide a convincing signal to the other party" (p, 21), Retailers agreeing
to restrictive contracts self-select themselves as channel
members, because the more opportunistically inclined ones
are likely to avoid binding themselves in this fashion (Rubin
1990).
Therefore, from the manufacturer's point of view, when
restrictive contracts are required, uncertainty about retailers'
internal operations may be reduced (Klein 1980; Mathewson and Winter 1985; Rubin 1990). Manufacturers would
have greater assurance that associated retailers will undertake behaviors that enhance the desired image of the brand.
As a result, manufacturers that position their brands as high
quality may be able to relax limits, at least to some degree,
on the number of retailers in their channel systems. Market
coverage could be enhanced with little or no sacrifice in
brand image,
H2: The inverse relationship between brand positioning on
quality and distribution intensity i,s weaker when contractual restrictiveness is higher.
Target focus is the extent to which a manufacturer concentrates on a narrow spectrum of the general market. A
manufacturer pursuing a broad cross-section of the market
for its brand must reach diverse groups of consumers that
differ in preferences and shopping pattems. An intensive
distribution approach is likely necessary in such cases to
ensure adequate availability of the brand (Levy and Weitz
1992), In contrast, a manufacturer targeting a market niche
for its brand deals with a relatively small and homogeneous
group of consumers, with at least some similarity in shopping pattems (Dickson and Ginter 1987). A more selective
distribution approach may be appropriate in serving such a
customer group, though pressures to reduce opportunity
costs associated with lost sales may lead such manufacturers
to expand the number of retailers in each trade area to some
degree (Stem, El-Ansary, and Coughlan 1996),
H3: The higher a manufacturer's target focus for a brand, the
lower is its level of distribution intensity.
Brands positioned high on quality may exhibit a tendency to be positively associated with the target focus constmct. However, the correlation is unlikely to be that high.
There are many examples of manufacturers that position
their brands as reasonably high quality and still target a
broad spectrum of consumers. Some of the "differentiators"
that Porter (1980) discusses appear to fit in that category.
For example, in the stereo speaker industry, Bose and JBL in
home speakers and Infinity in car speakers position their
brands as high quality and pursue a wide variety of market
Distribution Intensity / 41
segments. Manufacturers of brands positioned lower on
quality may focus on a narrow segment of the market for a
variety of reasons, such as low manufacturing capacity or
poor competitive position.
Manufacturer channel practices. Problems in the functioning of channel relationships are due at least partly to
differences in firms' objectives and risk preferences and
the information asymmetries between firms (Levinthal
1988), Hence, manufacturers may devise and employ
mechanisms designed to increase the likelihood that associated channel members' actions are consistent with manufacturer objectives and policies (Bergen, Dutta, and
Walker 1992; Eisenhardt 1989), Manufacturer coordination efforts and support programs are two such mechanisms, though each has different proposed effects on distribution intensity.
Coordination efforts reflect the extent to which manufacturer personnel attempt to align and influence retailer
decisions and activities (cf, Bucklin 1973; Skinner and
Guiltinan 1985), Certain manufacturers devote considerable
resources to coordinating their channel relationships with
retailers, whereas others show little interest in doing so,
partly because of the costs involved (Stem, El-Ansary, and
Coughlan 1996).
Manufacturers needing to closely coordinate their channel relationships are expected to set limits on the number of
retailers used in each trade area (Rosenbloom 1995). Coordination efforts can be hampered by a large and diverse
array of retailers (Cespedes 1988; Klein and Murphy 1988),
As the number of retailers in a channel system increases, so
do opportunities for transshipment, variation in maintenance
and repair services, different stocking levels, different pricing strategies, and inconsistent sales efforts. The likelihood
of such difficulties occurring is reduced when distribution
intensity is kept reasonably low (Cespedes 1988; Mason and
Ezell 1993), Furthermore, close coordination requires
retailer receptivity and support (Rosenbloom 1995; Stem,
El-Ansary, and Coughlan 1996), Manufacturers devoted to
coordinating their channel relationships, therefore, are likely
to try to keep levels of intrabrand competition low. Such an
approach protects retailer sales volumes and margins to
some degree and reduces the likelihood of significant freeriding activities, thus giving associated retailers some incentive to be receptive to manufacturer coordination efforts
(Jordan and Jaffee 1987; Scherer and Ross 1990),
H4: The higher a manufacturer's coordination efforts, the
lower is a brand's level of distribution intensity.
Retailer investments are expenditures in resources the
retailer must make to sell the brand effectively (Corey, Cespedes, and Rangan 1989), Such investments are brand-specific and driven by manufacturer requirements. They include
investments in inventory as well as time and money spent on
training sales personnel about the brand. Only a small portion, if any, of these investments are specialized in nature
(Williamson 1985) with little salvage value. Should the relationship with the manufacturer terminate, the retailer would
be able to sell the remaining inventory, and salesperson
expertise gained through training could be used in selling
competitive brands against the focal brand.
42 / Journal of Marketing, October 1996
Retailer investments in the brand are another form of
credible commitment or pledge to the manufacturer (Rusbult 1980), They signal the retailer's good faith and its willingness to do what is required, at least in part, to sell and service the brand properly. Retailers agreeing to make heavy
investments in the brand self-select themselves as channel
members (Rubin 1990). Moreover, retailers are likely to provide better support for brands in which they have made sizable investments (cf, Dwyer, Schurr, and Oh 1987; Frazier
1983), Therefore, when required investments are high, the
manufacturer is likely to have greater confidence that associated retailers are receptive and responsive to its coordination efforts. As a result, the manufacturer may be able to
increase the number of retailers used in each trade area to
some degree, thus enhancing the market coverage of the
brand without reducing the effectiveness of its coordination
efforts,
H5: The inverse relationship between manufacturer coordination efforts and distribution intensity is weaker when
retailer investments are higher.
Support programs are means of assistance the manufacturer makes available to associated retailers (e,g., accounting support, dealer hot line). Manufacturers vary in their
reliance on support programs (Hunt and Nevin 1974; Lusch
1976), Manufacturers that provide several support programs
in the channel are trying to stimulate interest in their brands
among retailers and assist associated retailers in their operations. Retailers clearly can be motivated by manufacturer
assistance (Gaski and Nevin 1985; Hunt and Nevin 1974;
Shipley 1984), When support programs are available, the
retailer's job may be made easier. Problems associated with
carrying, selling, and servicing the brand may be reduced,
which leads to lowered retailer cost and risk levels. As a
result, when many support programs are offered by a manufacturer, retailers may be encouraged to join and remain in
its channel system. Limiting this effect is the fact that the
costs of providing support for additional retailers in the
channel system outweigh their marginal contribution at
some threshold level,
H5: The higher the number of manufacturer support programs,
the higher is a brand's level of distribution intensity.
The strength of the positive relationship between manufacturer support programs and distribution intensity is
expected to increase when retailer investments are high.
When support programs are offered in conjunction with
retailer investments, both the manufacturer and the
retailer are sending signals of their desire to make their
channel relationship work. In essence, an exchange of
pledges is taking place. As Anderson and Weitz (1992, p,
21) state, "Observing the other party's pledges causes a
channel member to be more confident in the other party's
commitment to the relationship," Therefore, when retailer
investments are high, manufacturer support programs may
be particularly successful in attracting and retaining
retailers in the manufacturer's channel system. In contrast,
when retailer investments are low, manufacturer support
programs may be of less relevance and importance to
retailers and therefore have less impact on distribution
intensity.
H7: The positive relationship between the number of manufacturer support programs and distribution intensity is
stronger when retailer investments are higher.
Control variables. Field interviews identified three con.structs as control variables. First, manufacturers that make
use of distributor's are expected to have higher levels of distribution intensity than ones that use integrated channels to
reach retailers. Distributors must consider sales of the manufacturer's brand in conjunction with sales of the other product lines and brands they carry. Hence, they are likely to add
retailers to the channel system more readily than the manufacturer would on its own.
Second, manufacturers following a multiple-channels
approach use a wide variety of types of retail establishments
(e,g,, department stores, discount stores, specialty stores),
and perhaps direct marketing (e,g,, mail order), to sell their
brands. The use of multiple channels implies that the manufacturer is seeking wide market coverage (Weigand 1977),
Accordingly, the number of individual retailers the manufacturer uses in each trade area is likely to be relatively high.
Third, a reciprocal relationship is expected between
brand sales volume and distribution intensity. On one side, a
brand with high sales volume should enable a larger number
of retailers in a trade area to surpass minimum sales threshold levels for adopting and keeping the brand (Corey, Cespedes, and Rangan 1989; Webster 1976), A brand with high
sales volume is attractive to a larger variety of retailers. On
the other side, greater distribution intensity can lead to
greater sales volume for the brand, at least in the short run
and within limits, as Corstjens and Doyle (1979) and Stem,
El-Ansary, and Coughlan (1996) have argued.
Research Method
The product category chosen to test the conceptual framework is stereo speakers in the consumer electronics industry in the U,S, domestic market. Distribution for that product category is handled predominantly by a network of
independent retail dealers. The marketplace shows a wide
range of distribution intensity levels for speakers. Significant variations also are evident in brand strategy, channel
practices, and retailer requirements. The field interviews
indicated a need to gather data from manufacturers to effectively operationalize the constructs in our conceptual
framework.
Data Collection Method
Because the number of stereo speaker manufacturers selling in the U,S, domestic market is not large, we attempted
to identify their complete population. The electronics
industry has an industry association that assists members
and other interested parties, but a complete list of manufacturers was unavailable from it. We therefore used a catalog
of the annual Consumer Electronics Show, the primary
trade meeting for the industry, which listed the manufacturers in attendance. Other manufacturers and brands were
added by going through trade magazines, advertisements,
and articles, as well as by talking to manufacturers and
retail dealers.
In a four-day period at the Consumer Electronics
Show, we made contact with managers from approximately 40 manufacturing companies. They were made
aware of the importance of the study and their firms' participation in it. The name of the manager most familiar
with marketing and distribution issues for each brand was
obtained. In all cases, a verbal commitment either to
respond to the survey or to endorse the study to qualified
respondents was pursued. For firms not contacted at the
show, we found qualified respondents either through telephone conversations or by using the conference catalog to
identify the marketing director or marketing vice-president
for the brand.
The fmal sample frame consisted of 219 brands of stereo
speakers from 209 manufacturing firms. For manufacturers
with multiple brands, only brands produced and marketed
by independent divisions were treated as separable observations. An example is Harmon/Kardon, which has several distinct brands in the market (e,g,, Harmon/Kardon, Pyle, EPI,
JBL),
The questionnaire developed for the study had three versions, one for home speakers and the other two tailored in a
format for automotive and specialty speakers, respectively.
Aside from differences in wording to anchor responses to
the type of speaker, the questionnaires were identical.
We used a four-step approach in soliciting responses.
First, we sent the identified expert for each brand an initial
letter introducing the study, its potential value, and the
importance of his or her participation. Second, we sent a
first wave of questionnaires five days later with another
cover letter and a prepaid retum envelope. Third, we called
managers who had not responded within the first ten days in
an attempt to solicit their participation. Fourth, we sent a
second wave of questionnaires with another cover letter, a
retum envelope, and a brochure introducing a new distribution management program at our university. In all four steps,
we assured participating firms of confidentiality and invited
their questions by listing our telephone numbers. More than
20 managers did call one of us.
Although the use of single respondents has been criticized in the marketing literature (Phillips 1981), the specific
nature of the responses solicited in our study seemed to justify that approach. The information necessary for our analysis related to a narrow range of the firm's activities for a single brand. We therefore sought the individual manager most
knowledgeable about the marketing strategy and distribution
for the brand. In a majority of cases, personal interviews
conducted at the Consumer Electronics Show and by telephone helped identify such qualified respondents,
A total of 85 questionnaires were retumed from 84 different manufacturers, which represented a 38,8% retum
rate. Of the 85 brands, 58 were home speakers, 22 were
automotive speakers, and 5 were specialty speakers. The
first wave yielded 68 questionnaires and the second wave 17
questionnaires.
To assess possible nonresponse bias, we compared the
responses from the first wave of questionnaires with those
from the second wave (Armstrong and Overton 1977) on
the constructs examined in the study, A MANOVA analysis showed no significant differences between the two
Distribution Intensity / 43
groups. We attempted to gain information from the industry association on market share and saies for the various
brands but were unable to do so because such data are collected and presented only at more aggregate product-line
levels.
Operationatization of Constructs
Initially, we reviewed the literature to identify scales and
items that might be adopted in our research. Several new
items and measures needed to be developed, based on the
domain of the study. No measure of distribution intensity
existed prior to our study. The same four manufacturers and
15 retailers in the electronics, pet food, and hair care product categories that we had interviewed initially to construct
the conceptual framework were used in shaping the questionnaire and its items. The questionnaire went through several iterations. The managers were instructed to respond to
the items on the basis of their domestic operations.
We followed the procedure outlined by Churchill (1991)
in arriving at the final measurement scales for distribution
intensity, brand positioning on quality, and target focus. We
examined intercorrelations among the items designed for
each scale. One item was removed from each of the three
scales because of low correlations. We then conducted
exploratory factor analysis to determine the scales' unidimensionality and discriminant validity. One additional item
for target focus was removed on the basis of that analysis.
Finally, we computed alpha coefficients; each of the scales
has strong intemal consistency. The final scales are reproduced in the Appendix.
Four items were included in the final scale measuring
distribution intensity, which is the extent to which a manufacturer relies on numerous retailers in each trade area to
carry its brand. Three Likert items related to how selective
the manufacturer is in aligning with retailers in its trade
areas. After reverse coding, a high score on each item
reflects that the manufacturer is, in a relative sense, relying
on numerous retailers in its trade areas to carry its brand.
The fourth item asked about the firm's distribution pattem in
comparison to that of competitors on a scale ranging from
"exclusive" to "intensive." Coefficient alpha is .84 for the
scale. In a validation effort, one of us traveled to a suburb of
a major city in the Southeast and visited each retail store that
carried home speakers. An altemative measure of distribution intensity was constructed by counting the number of
stores that carried each brand. The two measures are correlated at .61, which offers some evidence of convergent
validity.
The scale for brand positioning on quality—the extent to
which the manufacturer attempts to convey to consumers
that the brand has superior ability to perform its functions
(Kotler and Armstrong 1993; Zeithaml 1988)—had three
items relating to the positioning of the brand on prestige,
performance, and quality from the low end to the high end.
Coefficient alpha is .86 for the scale.
Three items made up the final scale for target focus,
which is the extent to which the manufacturer concentrates
on a narrow spectrum of the general market (i.e., the scope
of targeted customers). They pertained to the number of
potential customers, the spectrum of customers, and the
degree to which a niche strategy is used for the brand. Coefficient alpha is .74 for the scale.
Factor analysis results for the three scales after an
orthogonal rotation are reported in Table 1. Each factor has
an eigenvalue greater than one, and the cumulative variance
explained by the three factors is above 71%. The loadings of
the items on their respective factors are all above .64. The
factorial complexity of the solution is low, with only one
item having a cross loading above .40.
We measured contractual restrictiveness, that is, the
degree to which a formal agreement between a manufacturer and retailer reduces retailer freedom of managerial
choice, with a five-item index. Managers first indicated
through a yes-or-no question whether they had a formal
agreement with retailers. If they did, they were asked to
indicate which of four issues were specifically addressed
in the agreement.
A three-item index was used to measure retailer investments, which are the expenditures in resources the retailer
must make to sell the brand effectively. The index centered
on inventory and the money and time needed to make new
salespeople knowledgeable about the brand. There is no theoretical reason to believe that brands requiring a large
investment in salesperson training also require a large
TABLE 1
Factor Analysis of Measurement Scales
Factor 1
Distribution
intensity
Factor 2
Brand
Positioning
Factor 3
Target
Focus
Construct
Item
Distribution intensity
DM
DI2
DI3
DI4
.79
.72
.83
.73
-.27
-.48
-.11
-.03
-.20
-.10
-.18
-.32
Brand positioning
BP1
BP2
BP3
-.16
-.05
-.31
.80
.92
.79
.29
.04
.21
Target focus
TF1
TF2
TF3
-.15
-.27
-.19
.13
.18
.14
.80
.64
.84
44 / Journai of Marketing, October 1996
investment in inventory. Again, such investments are not
considered "specialized."
Coordination efforts were measured by the extent (low
to high) to which manufacturers exerted effort to coordinate
nine retailer decisions areas. This measure was treated as an
index rather than as a scale; simply because manufacturer
personnel choose to exert effort on certain retailer decision
areas (e.g., inventory levels) does not mean they exert effort
on others (e.g., store appearance).
To measure manufacturer support programs, we
included a total of nine possible means of assistance and an
"other" category in the questionnaire. The managers indicated on a yes-or-no basis which assistances were provided
to associated retailers. An index of support programs was
established from a count of the yes responses.
For the control variables, to measure use of distributors,
we asked managers whether a distributor-retailer-consumer
channel was used. To measure the use of multiple channels
we asked the managers to indicate which types of stores
were used in selling the brand. Furthermore, we asked
whether the manufacturer used any "direct marketing to
consumers (e.g., mailorder)."
Three items were used to measure the brand's sales volume. Two asked about the brand's .sales volume in dollars
and sales units relative to competitors. The third item asked
respondents to indicate which one of seven categories
reflected the sales volume of the brand. Coefficient alpha is
.85 for the sales volume scale.
Results
Model Specification and Test
Table 2 is the correlation matrix for the measures. Multicollinearity is evident between the interaction terms and
their underlying components. To address that problem, we
used the standardization procedure proposed by Friedrich
(1982). Compared to mean-centering, this procedure affords
better comparability of the coefficients across the additive
and interaction models. The measures for the independent
variables and the moderator variables were first standardized; then the cross-product terms were formed by multiplying the appropriate independent variable and moderator
variable together.
The method recommended by Aiken and West (1991)
for testing moderator effects was followed. Essentially, the
variance in distribution intensity explained by the additive
model is compared with the variance explained by the interaction model that includes cross-product terms representing
the hypothesized interactions between the moderators and
the independent variables. The interaction model is judged
to be superior if the variance it explains is significantly
higher than that explained by the additive model. In such
cases, the hypothesized moderating effects can be tested by
examining the sign and statistical significance of the parameter estimates of the cross-product terms.
The additive model represented in Equation 1 was tested
by multiple regression analysis; the results are reported in
the first column of Table 3. The control variables were
included to ensure an adequate test of the research hypothe-
ses, because their effects would be taken into account in the
multivariate analysis. In Table 2, we provide descriptions for
the variables in Equation I.
(1) DI = BP + TF + CE + SP + CR + RI + UD + MC + BS + e
Next, the interaction model in Equation 2 was tested.
The main effects for contractual restrictiveness and retailer
investments were still included. Results are reported in the
second column of Table 3.
(2)
DI = BP + TF + CE + SP + CR + RI + UD + MC
+ BS + BP*CR + CE*RI + SF*RI + e
The variance in distribution intensity explained by the interaction model in Equation 2 is .18 more than the variance
explained by the additive model in Equation 1, an increase of
39% (.18/.46). The increase in variance explained is significant at p < .01. Therefore, the interaction model is superior to
the additive model, which shows that further examination of
the individual moderator effects is warranted. As is evident
from Table 3, each of the moderator effects is significant.
When a significant moderator effect is found, Aiken and
West (1991) recommend assessing the relationship between
the independent variable and the dependent variable for
plus-and-minus one standard deviation of the moderator.
Such an analysis was performed for each of the three moderator effects. The results are reported in Table 4 and help
clarify the specific conditional effects of the moderators on
the relationships between the independent and dependent
variables in que.stion.
Finally, we examined the possible impact of type of
speaker, whether a home speaker brand or an automotive
speaker brand, by including a dummy variable in each equation and using home speaker brands as the holdout category.
The dummy variable was nonsignificant in each case. A
dummy was not included for specialty speaker brands
because of the small number (five) in the sample.
Hypotheses Tests
Brand positioning on quality has a significant inverse relationship with distribution intensity (b = -.20, p < .05),
thereby providing support for H|. Manufacturers of brands
positioned high on quality are attempting to convey to consumers that their brands are special in performance and
prestige. Such manufacturers are likely to be sensitive to
retailers' reputations and their ability to sell and service
high-end brands and are likely to screen accordingly. Brands
positioned near the low end of the quality continuum require
relatively wide market coverage and intrabrand competition
to enhance unit sales.
As was proposed in H2, contractual restrictiveness significantly weakens {p < .01) the inverse relationship
between brand positioning on quality and distribution intensity (refer to Tables 3 and 4). By signing restrictive contracts, retailers are making a credible commitment to the
manufacturer (Williamson 1983). Hence, manufacturers that
position their brands as high quality may be able to increase
distribution intensity somewhat more than corresponding
manufacturers that do not rely on restrictive contracts.
H3 is supported, because target focus has a significant
inverse relationship (b = -.23, p < .01) with distribution
Distribution Intensity / 45
o
o
O
O
in
.03
.27*
.48*
.23*
.86*
.48*
-.06
.10
-.32*
.22*
.40*
.98*
.81*
-.26
.04
-.02
-.27*
.08
-.01
.23*
77*
-.18
-.31*
32*
36*
-.30
-.10
o
-.08
.05
30*
.14
r
.23*
.13
in
.16
.36*
.27*
CM
«
CO
CO
33*
UJ tn
1.00
1
CM «
q
CO
26*
o
.12
(0
.20
1.00
1.00
1.00
u
CO
CM
.01
1.00
1.00
8
o
CM
u
in
in
CM
T-
o
CO
o
oq
-.27
-.02
.31*
.26*
CO
(p
-.14
.35*
(O
CO
r
-.21*
.28*
.33*
.32*
in
00
-.19
.15
-.40
-.17
.37*
-.15
.14
S
-.20
1.2
CO
-.09
5
1.00
ffi
1.00
a.
-.51*
1.00
j.
-.54*
(0
0)
Q
CJ>
CO
CM
V) O
(Q
0)
CM
CM
in
CO
T—
CO
CO
oo
CO
in
CO
CM
CO
s
CM
in
oq
00
in
o
.ill
"S c
Q .£
in
U)
CL
CO
CO o _
c o(Do
46 / Journal of Marketing, October 1996
•5 M
O <B
C
CO
r E
o CO
°-^
3
ii
CO
Q.
2 t3
ZB
<3s
o
a:
o
.2 rr
tn
CO yj"
o
E
CO h.—I
• " CU
II
Q
S
^
.^
Q.
E9-
CO
o
i
<1> CO
CO
^
=> o
..-
3
O S2I
C U * -
V
CC
II
CUrv-
LU
c iir
.9 O
t3.c
2
•"
C U ^
CU
CC
—
a
CL
c
QT
o
O
CO
'c
g
"o .c
2 ••?
CUC U ^
Is
TABLE 3
Estimation Results: Distribution Intensity
Main Effects Only
Independent Variables
Parameter
Estimate^
t-value
Main Effects and Interactions
Parameter
Estimate^
t-value
Brand positioning
-.26
(.10)
-2.73***
-.20
(08)
-2.37**
Target focus
-.25
(.10)
-2.35**
-.23
(09)
-2.68***
Contractual restrictiveness
-.07
(.07)
-.91
-.08
(06)
-1.21
Coordination efforts
-.18
(.10)
-1.80**
-.13
(08)
-1.56*
Support programs
.13
(08)
1.64*
.10
(07)
1.37*
Retailer investments
.04
(.11)
.39
.05
(09)
.58
Use of distributors
.22
(07)
3.21***
.23
(.06)
4.07***
Multiple channels
-.01
(09)
-.14
-.004
(07)
-.06
Brand sales volume
.24
(09)
2.55***
.17
(08)
2.08**
Brand positioning x
contractual restrictiveness
.30
(07)
4.10***
Coordination efforts x
retailer investments
.37
(.10)
3.59***
Support programs x
retailer investments
.18
(.09)
1.93**
adjusted R2 = .46
Overall model
Fg 64 = 8.00
p'< .0001
adjusted R2 = .64
delta R^interaction-main = -18
Fi2,6i = 11.53
p < .0001
^Standard error is in parentheses.
*p-values < .10 based on one-tailed tests.
**p-values < .05 based on one-tailed tests.
***p-values < .01 based on one-tailed tests.
intensity. Manufacturers going after the mass market must
attempt to serve customers with widely varied needs and
shopping pattems. A relatively large number of retailers is
needed in each trade area to cover such a diverse mix of customers effectively.
Some support is provided for H4, because manufacturer coordination efforts are related inversely, though
weakly (fo = -.13, p < .10), to distribution intensity. When
close coordination is needed, manufacturers are likely to
limit distribution to reduce potential difficulties in channel
operations and foster a supportive atmosphere in their
exchange relationships. Retailer receptivity to manufacturer coordination efforts should be enhanced when safeguards against intrabrand competition are provided
(Scherer and Ross 1990).
Retailer investments significantly weaken (p < .01) the
inverse relationship between manufacturer coordination
efforts and distribution intensity. H5, therefore, is supported.
Retailers making heavy investments in a brand are signaling
to the manufacturer their willingness to sell and service it
effectively. This may enable manufacturers desiring close
coordination to increase distribution intensity to some
degree.
Manufacturer support programs are related positively,
though weakly (b = .10, p < .10), to distribution intensity,
which provides some support for Hg. When a manufacturer
provides many support programs, retailers may have some
incentive to join and remain in the channel system. Such
programs can lower retailer costs and risks while making it
easier to do business with the manufacturer.
Distribution intensity / 47
TABLE 4
Conditional Effects of Moderators on
Distribution Intensity^
Distribution
Intensity
Effects of Brand Positioning on Quality
High contractual restrictiveness
Low contractual restrictiveness
.10
-.50
Effects of Coordination Efforts
High retailer investments
Low retailer investments
.24
-.50
Effects of Support Programs
High retailer investments
Low retailer investments
.28
-.08
^These are the estimated standardized effects of brand positioning,
coordination efforts, and support programs on distribution intensity
when the moderator variables of contractual restrictiveness or
retailer investments are either one standard deviation above (high)
or one standard deviation below (low) the mean.
Finally, H7 is supported, because retailer investments are
shown to strengthen the positive relationship between support programs and distribution intensity (p < .05). When
manufacturer support programs and retailer investments are
both at a relatively high level, each firm is sending a signal
of its commitment to the exchange. In such cases, the support programs offered by the manufacturer may be particularly successful in attracting and retaining retailers in its
channel system.
Control Variables
Two of the three control variables have significant relationships with distribution intensity. The manufacturer's use of
independent distributors is related positively (b = .23, p <
.01) to distribution intensity. Distributors are likely to be
more liberal in adding retailers to the channel system than
are manufacturers. Brand sales volume also has a positive
relation with distribution intensity (b = .17,p < .05). A highvolume brand is able to support more retailers in a trade area
than is a low-volume brand. Furthermore, higher distribution intensity may contribute to greater sales of the brand.
Discussion
We modified the traditional approach taken in research on
distribution intensity in the marketing literature. Previous
theoretical research has focused on distribution intensity
across different classes of goods. Although such work is
important, we address instead why distribution intensity
varies markedly across brands within many categories of
consumer products. Our field interviews indicate that managers in manufacturing organizations face a complex and
difficult decision on distribution intensity for their brands
and have little, if any, secondary information to assist them
with their decision. Therefore, systematic research on distribution intensity across brands has the potential to afford
considerable insight, both theoretical and managerial. No
such research has been reported previously.
48 / Journal of Marketing, October 1996
Our integrative conceptual framework provides an initial
theoretical explanation of why distribution intensity varies
across brands. Our empirical results strongly support the
conceptual framework and are the first direct evidence of the
determinants of distribution intensity. Prominent among the
empirical results is support for three moderator effects that
are based on credible commitments made by retailers to
manufacturers. Our study therefore enhances our understanding of the distribution intensity construct and establishes a foundation of knowledge on which others can build.
Manufacturers positioning their brands as high quality
have reason to follow a highly selective distribution policy.
Such a policy has potential disadvantages, however, including a poor bargaining position with associated retailers,
weak market coverage, and lost sales opportunities, Intemal
pressures can arise to increase sales of the brand by increasing distribution intensity. Restrictive contracts appear to
give manufacturers of high-end brands the means to intensify distribution in response to such disadvantages and
pressures. Manufacturer uncertainty about retailer intemal
operations is likely to be reduced when retailers accept the
terms of a restrictive contract. As a result, the manufacturer
has greater assurance that retailer behaviors at least reinforce, if not enhance, the desired image of the brand, even
as intrabrand competition increases to some degree. Retailers on the "margin" in terms of reputation and quality of
operations are likely to be among the beneficiaries. In contrast, when restrictive contracts are not used or agreed to by
retailers, manufacturers positioning their brands as high
quality are likely to keep distribution intensity relatively
low. Manufacturer fears of misalignment in the channel are
likely to dominate, which leads to a necessary sacrifice of
market coverage.
Manufacturers desiring to closely coordinate their channel relationships have reason to limit the number of retailers
used in each trade area as well. However, they are likely to
face the same disadvantages of selective distribution and the
same intemal pressures to increase brand sales. By making
heavy investments in inventory and training of sales personnel, retailers provide a credible commitment to the manufacturer, thereby signaling their good faith and willingness
to support the brand. Retailers clearly have an incentive to
make such channel relationships work. Retailer receptivity
and responsiveness to coordination efforts should be facilitated as a result, thus enabling manufacturers in need of
close coordination to increase distribution intensity to some
degree. Such expansion should enhance market coverage
while enabling the manufacturer to maintain desired levels
of channel coordination, at least as long as intrabrand competition does not become problematic. Without such retailer
investments, the leverage of the manufacturer is reduced and
distribution intensity is likely to be kept at a relatively low
level.
From one perspective, the moderator results may
appear somewhat counterintuitive. Retailers make credible commitments, and the manufacturer's response is to
relax limits on distribution intensity to enhance market
coverage for its brand. Two points identified in our field
interviews are relevant. First, that retailers make credible
commitments or pledges does not mean they have high
commitment in the relationship with the manufacturer
(see Anderson and Weitz 1992). Retailers often make
credible commitments to acquire the brands they desire,
but the channel relationships involved may be of only
moderate strength, if that. Second, though retailers' credible commitments appear to enable manufacturers to
increase distribution intensity levels from what they
would otherwise be, the manufacturers in question still
offer associated retailers some protection from intrabrand
competition. In other words, the floodgates are not being
opened.
Manufacturers that provide many support programs are
likely to have a relatively high level of distribution intensity.
Retailer investments appear to further strengthen that positive relationship. Manufacturer support programs and
retailer investments appear to complement one another, as
each represents a commitment in resources. The manufacturer provides assistance to the retailer while the retailer
invests in inventory and training to support the brand. Therefore, both the manufacturer and the retailer are taking supportive actions and sending signals of their desire to make
the channel relationship work. As a result, when retailer
investments are high, the support programs offered by the
manufacturer may be particularly effective in attracting and
retaining retailers in the channel system. When required
retailer investments are low, on the other hand, the manufacturer's support programs may be seen as relatively unimportant by retailers. As a result, they may help attract fewer
retailers into the manufacturer's channel system. Many
retailers attracted into the channel system may not be
retained because of relatively weak channel relationships
with the manufacturer.
The level of target focus for the brand also must be taken
into account. Brands targeted to a broad spectrum of consumers need high distribution intensity to facilitate market
coverage. A smaller and less diverse group of retailers is
needed when manufacturers target a relatively small and
homogeneous group of consumers for their brands.
Limitations
Two limitations of our study must be addressed. First, specification error could be a problem, even given the strong
explanatory power of our interaction model. Our study represents a first attempt to build and test a conceptual framework of distribution intensity. Despite the time and effort
devoted to developing it, important factors may have been
omitted. More comprehensive conceptual frameworks relating to the distribution intensity construct need to be developed and examined empirically in the future.
Second, the generalizability of our empirical results is in
question. The conceptual framework appears to be broadly
applicable to any category of consumer product in which
wide variation exists in desired distribution pattems for
brands, though this must be verified. Although intended
variation in distribution intensity for brands is likely to
occur primarily in durable goods categories, significant differences exist in some consumer nondurable categories as
well, such as in pet food and hair care categories. In product
categories in which intensive distribution is sought for most
brands, such as for the majority of consumer packaged
goods, our conceptual framework does not apply well, if at
all. Whether our findings hold in business-to-business product and service categories must be explored as well.
Future Researcti Needs
Several other research issues should be addressed. Retailers' credible commitments appear to enable manufacturers
following a selective distribution policy to relax limits on
distribution intensity to some degree to promote market
coverage. The question of how far limits on intensity can
be relaxed before levels of intrabrand competition become
unmanageable for those manufacturers must be examined.
More broadly, the actual performance implications of
decisions on distribution intensity should be explored.
Research on the degree to which retailers actually fulfill
their pledges would be illuminating. Especially useful
would be the development of models that predict the likelihood of retailers reneging on their commitments under various conditions (e.g., downturn in the economy or the industry). Whether manufacturers react more to the signaling
associated with retailers' credible commitments than to the
reality of the situation, including actual retailer behaviors
and levels of support for their brands, must be researched as
well.
In general, we would expect that as manufacturers associate with a greater number of retail outlets, the corresponding channel relationships would become less close. There
may be ways to circumvent such a tendency, however, such
as through infonnation sharing and the frequent introduction
of new products. The 3M Company has a reputation for
using such mechanisms to build strong channel relationships
even though it u.ses an intensive distribution approach. An
examination of how strong channel relationships can be
developed and maintained in the face of intensive distribution could prove useful.
We examine distribution intensity as it is generally
established across trade areas by manufacturers for their
brands. Research that examines how characteristics of individual trade areas affect distribution intensity also could
prove fruitful. Our field interviews indicate that individual
trading areas differ to some degree on such factors as strategic importance and competitive intensity. Manufacturer personnel indicate that such factors did not sway their firms'
general approach to distribution intensity but did induce
some variation.
We are the first to develop a measure of distribution
intensity. Although the measure is internally consistent and
is shown to have a promising level of convergent validity,
improved measures of distribution intensity need to be
developed in further research. Empirical research also is
needed on how distribution intensity varies across product
categories and different classes of goods. How frequency of
purchase and other product characteristics affect distribution
intensity could be explored in the process.
In conclusion, though our conceptualization and empirical findings are encouraging, other studies must be conducted to afford an adequate understanding of the distribution intensity construct. Our study provides a useful foundation on which future research studies can build.
Distribution Intensity / 49
Appendix
Measures
Distribution intensity. Three of the items were measured
on a five-point Likert scale ranging from 1, "strongly disagree," to 5, "strongly agree";
1. We are highly selective in our choice of retailers who carry
our brand in each trade area (reverse coded).
2. Only a select few retail outlets per trade area are allowed to
carry our brand (reverse coded).
3. We try to keep the number of retailers carrying our brand
in each trade area to a minimum (reverse coded).
The fourth item was measured on a five-point scale ranging
from 1, "exclusive," to 5, "intensive":
4. Compared to your competition, how would you describe
your brand's distribution pattern for each trade area?
Brand positioning on quality. The three items were measured in the following format on a five-point scale ranging
from 1, "low end," to 5, "high end";
How do you position the brand on the following product
characteristics?;
1. Prestige or image of the brand?
2. Product performance?
3. Overall product quality?
Target focus. The three items were measured on a fivepoint Likert scale ranging from 1, "strongly disagree," to 5,
"strongly agree";
1. By design, our brand has a small number of potential
cu.stomers.
2. By design, our speaker brand appeals to a narrow spectrum
of consumers only.
3. We use a niche strategy for marketing our brand.
Contractual restrictiveness. The manufacturers were
first asked. "Do you have a formal contractual agreement
with your retailers conceming the sale of your brand?" They
responded "yes" or "no."
If yes, they were asked "Which of the following issues
are addressed in your contractual agreement with retailers?"
1. Product displays for brand
2. Brand sales goals for store
3. Brand sales promotions
4. Contract termination
The index ranged from 0, no formal contractual agreement,
to 4, all four issues were addressed.
Retailer investments. The three items were measured on
a five-point scale ranging from 1, "much lower" to 5, "much
higher."
Relative to all other speaker brands in the market,
how does your brand compare on brand specific dealer
investments?
1. The amount of money dealers have to spend on training
new salespeople in order to handle our brand is ...
2. The amount of time new salespeople have to spend on
training in order to handle our brand is ...
3. The level of inventory needed to be adequately stocked for
our brand is ...
50 / Journal of Marketing, October 1996
Coordination efforts. The index was based on the following measure using a five-point scale ranging from 1,
"low," to 5, "high";
Please indicate the extent to which you as the manufacturer directly or indirectly (i.e., through your distributors)
exert effort to coordinate the following retailer activities.
1. Implementation of sales promotions.
2. Use of promotional aids (e.g., brochures, posters).
3. Use of product displays.
4. Dealer retum goods policy.
5. Dealer service standards.
6. Dealer pricing.
7. Dealer sales presentations to customers.
8. Dealer inventory levels.
9. Store appearance (e.g. layout, shelf-design).
Support programs. Manufacturers were asked, "Which of
the following assistances do you provide to your retailers?"
1. Promotional allowances.
2. Promotional material.
3. Product displays.
4. Dealer hot-line.
5. Consumer hot-line.
6. Inventory management.
7. Inventory financing.
8. Over-the-counter warranty policy.
9. Accounting support.
10. Other.
Use of distributors. Manufacturers were asked whether
they used a "Distributor-Retailer-Consumer" channel of
distribution.
Use of multiple channels. Manufacturer responded "yes"
or "no" to the following items;
Indicate which of the following types of stores your firm
uses for selling your brand in the U.S.
• Audio-Video Electronic Stores
• Department Stores
• Discount Stores
• Warehouse Style Discount Stores
• Variety Stores
• Catalogue Showrooms
• Other
Furthermore, whether the manufacturer did any direct marketing to consumers (e.g., mail order) was incorporated into
the index.
Brand sales volume. Two items were measured on a fivepoint scale ranging from 1, "low," to 5, "high";
Relative to your competition, the sales volume for your
brand in the domestic market;
1. ...calculated in US Sis ...
2. ... calculated in units is ...
The third item was measured on a seven-point categorization from low to high levels of U.S. dollars.
3. What was the approximate sales volume (in US $) of your
brand in 1991?
REFERENCES
Aiken, Leona and Stephen West (1991), Multiple Regression: Testing and Interpreting Interactions. Newbury Park, CA: Sage Publications,
Anderson, Erin and Barton Weitz (1992), "The Use of Pledges to
Build and Sustain Commitment in Distribution Channels," Journal of Marketing Research, 29 (February), 18-34,
Armstrong, J, Scott and Terry S, Overton (1976), "Estimating Nonresponse Bias in Mail Surveys," Joumal of Marketing Research,
14 (August), 396-^02,
Aspinwall, Leo (1958), "The Characteristics of Goods and Parallel
Systems," in Managerial Marketing, Harold Kelley and William
Lazer, eds, Homewood, IL: Richard D, Irwin, 434-50,
Bagozzi, Richard P, (1986), Principles of Marketing Management.
Berkeley, CA: Science Research Associates,
Bergen, Mark, Shantanu Dutta, and Orville C, Walker (1992),
"Agency Relationships in Marketing: A Review of the Implications and Applications of Agency and Related Theories," Journal of Marketing, 56 (July), 548-73,
Bonoma, Thomas V, and T'homas J, Kosnik (1990), Marketing
Management: Text and Cases. Homewood, IL: Richard D, Irwin,
Bucklin, Louis (1973), "A Theory of Channel Control," Joumal of
Marketing, 37 (January) 39-47,
Cespedes, Frank (1988), Control Versus Resources in Channel
Design: Distribution Differences in One Industry," Industrial
Marketing Management, 17 (August), 215-27,
Churchill, Gilbert A, (1991), Basic Marketing Reseanh, 2d ed. Fort
Worth, TX: The Dryden Press,
Copeland, Melvin (1923), "The Relation of Consumers' Buying
Habits to Marketing Methods," Harvard Business Review, 1
(March/April), 282-89,
Corey, E, Raymond, Frank Cespedes, and V, Kasturi Rangan
(1989), Going to Market: Distribution Systems for Industrial
Products. Boston: Harvard Business School Press,
Corstjens, Marcel and Peter Doyle (1979), "Channel Optimization
in Complex Marketing Systems," Management Science, 25
(October), 1014-25,
Dickson, Peter and James Ginter (1987), "Market Segmentation,
Product Differentiation, and Marketing Su^tegy," Joumal of
Marketing, 51 (April), 1-10,
Dwyer, R, Robert, Paul H, Schurr, and Sejo Oh (1987), "Developing Buyer-Seller Relations," Joumal of Marketing, 51 (April),
11-28,
Eisenhardt, Kathleen M, (1989), "Agency Theory: An Assessment
and Review," Academy of Management Review, 14 (January),
57-74,
Frazier, Gary (1983), "Interorganizational Exchange Behavior in
Marketing Channels: A Broadened Perspective," Joumal of
Marketing, 47 (Fall), 68-78,
Friedrich, R, J, (1982), "In Defense of Multiplicative Terms in Multiple Regression Equations," American Joumal of Political Science, 26, 797-833,
Gaski, John and John Nevin (1985), 'The Differential Effects of
Exercised and Unexercised Power Sources in a Marketing Channel," Joumal of Marketing Research, 22 (May), 130-42,
Hunt, Shelby and John Nevin (1974), "Power in a Channel of Distribution: Sources and Consequences," Joumal of Marketing
Research. It (May), 186-93,
Jacoby, Jacob and David Mazurski (1984), "Linking Brand Images
and Retailer Images—Do the Potential Risks Outweigh the
Potential Benefits?" Joumal of Retailing, 60 (Summer), 105-22,
Jordan, W, John and Bruce L, Jaffee (1987), "The Use of Exclusive
Territories in the Distribution of Beer: Theoretical and Empirical Observations," Antitrust Bulletin. 32 (Spring), 137-64,
Klein, Benjamin (1980), "Transaction Cost Determinants of
'Unfair' Contractual Arrangements," Borderlines of Law and
Economic Theory, 70 (2), 356-62,
and Kevin M, Murphy (1988), "Vertical Restraints as Contract Enforcement Mechanisms," Journal of Law and Econom-
ics, 31 (October), 265-97,
Kotler, Philip and Gary Armstrong (1993), Principles of Marketing,
6th ed, Englewood Cliffs, NJ: Prentice-Hall,
Lafferty, R, N,, R, H, Lande, and J, B, Kirkwood (1984), Impact
Evaluations of Federal Trade Commission Vertical Restraint
Cases. Washington, DC: U,S, Federal Trade Commission,
Levinthal, Daniel (1988), "A Survey of Agency Models of Organizations," Joumal of Economic Behavior and Organization, 9
(March), 153-85,
Levy, Michael and Barton A, Weitz (1992), Retailing Management.
Homewood, IL: Richard D, Irwin,
Lusch, Robert F, (1976), "Sources of Power: Their Impact on Intrachannel Conflict," Joumal of Marketing Research, 13 (November), 382-90,
and Patrick Dunne (1990), Retail Management. Cincinnati,
OH: Southwestern Publishing Company,
Mason, J, Berry and Hazel F, Ezell (1993), Marketing Management.
New York: Macmillan Publishing Company,
Mathewson, G, F and R, A, Winter (1984), "An Economic Theory of
Vertical Restraints," Rand Joumal of Economics, 15 (1), 27-38,
McCarthy, E, Jerome and William Perreault (1984), Basic Marketing. Homewood, IL: Richard D, Irwin,
Miracle, Gordon (1965), "Product Characteristics and Marketing
Strategy," Joumal of Marketing, 29 (January), 18-24,
Pegram, Roger (1965), Selecting and Evaluating Distributors. New
York: National Conference Board,
Phillips, Lynn W, (1981), "Assessing Measurement Error in Key
Informant Reports: A Methodological Note on Organizational
Analysis in Marketing," Joumal of Marketing Research, 18
(November), 395-415,
Porter, Michael (1980), Competitive Strategy. New York: The Free
Press,
Rey, Patrick and Jean Tirole (1986), "The Logic of Vertical
Restraints," American Economic Review, 76 (December),
921-39,
Rosenbloom, Bert (1995), Marketing Channels, 5th ed, Chicago:
The Dryden Press,
Rubin, Paul (1990), Managing Business Transactions. New York:
The Free Press,
Rusbult, Caryl (1980), "Commitment and Satisfaction in Romantic
Associations: A Test of the Investment Model," Joumal of
Experimental Social Psychology, 16 (March), 172-80,
Scherer, F, M, and David Ross (1990), Industrial Market Structure and Economic Performance. Boston: Houghton Miffiin
Company,
Shipley, David (1984), "Selection and Motivation of Distribution
Intermediaries," Industrial Marketing Management, 13 (October), 249-56,
Skinner, Steven and Joseph Guiltinan (1985), "Perceptions of Channel Control," Joumal of Retailing, 61 (Winter), 65-88,
Stem, Louis, Adel El-Ansary, and Anne Coughlan (1996), Marketing Channels, 5th ed. Upper Saddle Creek, NJ: Prentice-Hall,
Webster, Frederick (1976), "The Role of the Industrial Distributor
in Marketing Strategy," Joumal of Marketing, 40 (July), 10-16,
Weigand, Robert (1977), "Fit Products and Channels to Your Markets," Harvard Business Review, 55 (January/February),
95-105,
Williamson, Oliver E, (1983), "Credible Commitment: Using
Hostages to Support Exchange," American Economic Review,
73 (September), 519^0,
(1985), The Economic Institutions of Capitalism. New
York: The Free Press,
Winter, Ralph A, (1993), "Vertical Control and Price Versus Nonprice Competition," Quarterly Joumal of Economics, 108 (February), 61-76,
Zeithaml, Valarie A, (1988), "Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence,"
Joumal of Marketing, 52 (July), 2-22,
Distribution intensity / 51