Coping With the Uncertainty of Consumer Markets

Lauranne Buchanan, University of Illinois at Urbana-Champaign
Wanru Su, University of Illinois at Urbana-Champaign
ABSTRACT - Uncertainty of demand is a problem for managers because it limits their ability to plan the efficient and effective use of resources. Uncertainty refers to the degree to which managers cannot anticipate or accurately predict future states of the market (Pfeffer and Salancik 1978). Because it is difficult to plan under conditions of uncertain market demand, it is in the interest of managers to minimize the degree of uncertainty in their business. Two methods for dealing with uncertainty are channel relationships and marketing programs. This paper investigates the impact of these factors on the level of realized uncertainty across departments in a retail department store.
[ to cite ]:
Lauranne Buchanan and Wanru Su (1988) ,"Coping With the Uncertainty of Consumer Markets", in NA - Advances in Consumer Research Volume 15, eds. Micheal J. Houston, Provo, UT : Association for Consumer Research, Pages: 396-402.

Advances in Consumer Research Volume 15, 1988      Pages 396-402

COPING WITH THE UNCERTAINTY OF CONSUMER MARKETS

Lauranne Buchanan, University of Illinois at Urbana-Champaign

Wanru Su, University of Illinois at Urbana-Champaign

ABSTRACT -

Uncertainty of demand is a problem for managers because it limits their ability to plan the efficient and effective use of resources. Uncertainty refers to the degree to which managers cannot anticipate or accurately predict future states of the market (Pfeffer and Salancik 1978). Because it is difficult to plan under conditions of uncertain market demand, it is in the interest of managers to minimize the degree of uncertainty in their business. Two methods for dealing with uncertainty are channel relationships and marketing programs. This paper investigates the impact of these factors on the level of realized uncertainty across departments in a retail department store.

INTRODUCTION

In 1984, The Wall Street Journal ran an article on the frustrations and dangers of the fashion industry. A vivid illustration of their point was Guess? jeans. Guess? became a $200 million a year enterprise three years after persuading Bloomingdale's to carry 20 pairs of their stone-washed jeans. In comparison, Apple Computer Inc., the most talked about corporate success story of the decade, had only $117 million in sales in its third year. Why is it that Guess? is not recognized as a leading investment opportunity by Wall Street? The problem is the customer. The primary market for Guess? is teenage girls. And as a market, teenagers cannot to be trusted.

Unpredictable in their tastes and fickle in their loyalties, teen-age girls can be down right dangerous as customers. They can go through a style faster than a stick of gum, or send sales of a shampoo or snack food soaring or plunging almost overnight. Keeping up with them is a job that can humble even the most sophisticated marketer. (WSJ, 1984, p.1)

The academic view of the consumer is often far removed from the nightmare faced by managers. To academics, consumers are subjects with preference structures that can be observed, dissected, understood, and put back together. To the marketing manager, the consumer is the beguiling enemy who wrecks masterfully engineered strategic program with their whimsical responses.

It's not that the consumer is purposefully out to make life difficult for marketers. Very often, consumers just don't know what they want. Ask a consumer to describe the kind of dress she wants for a special dinner party, she may mumble vaguely "Something with style." If pressed on what she means by "style," it is unlikely that she can articulate specific product attributes. Fashion is ambiguous, and consumer perceptions are influenced by environmental cues. A dress is just a dress; but a dress advertised in Vogue, displayed in Bloomingdale's window, and priced at $579 is style. Unfortunately for the manufacturer and retailer, this requires a large commitment of resources before the consumer is able to evaluate the product. To the extent that the product isn't what the consumer had in mind or its presentation is ineffective, the resources invested in producing and marketing the product have been wasted.

When demand is lower than anticipated, the problems are obvious. But problems also result from unexpectedly high demand. Unanticipated demand may entail high costs as the manufacturer scrambles to replace stock levels, paying supernormal prices for raw materials, overtime for workers, and higher freight costs to speed delivery to retailers. The unexpected demand also poses headaches for the retailer with additional costs of transporting and restocking inventories, adding and training salespeople, and disruptions in service. Responding to unanticipated demand may be a Catch-22 for the manufacturer and retailer. If they don't respond, they lose sales; if they do, they potentially waste valuable resources. To the extent that demand can not be sustained over time, their investments in additional production, distribution, salespeople, etc., are unwarranted. When channel members react to demand as independent shocks without developing a plan for minimizing uncertainty in subsequent time periods, the logistical operation and the allocation of resources become chaotic.

Ultimately, the problem with market uncertainty is that it is difficult for the manufacturer and retailer to plan the efficient and effective use of their resources. And the mismanagement of scarce resources threatens the long term survival of organizations (Pfeffer and Salancik 1978). Therefore, minimizing uncertainty is a "rational" objective and can be as important as maximizing sales or reducing costs (Child 1972) [It should be noted here that market uncertainty is quite different from market growth or decline. Market growth or decline, if predictable, need not be a problem. If changes in the market are predictable, manufacturers and retailers can adjust internally to reflect the changes in the market. However, the unexpected growth or decline of demand can lead to chaos for both manufacturer and retailer.].

The question then becomes what factors contribute to minimizing uncertainty. Two major factors are the nature of the relationship forged between channel members and marketing programs. This research investigates the impact of these factors on the degree of uncertainty of 137 departments of a retail department store. The level of uncertainty characterizing the department is measured as the degree to which sales of one year cannot be predicted from the sales of the previous year. Departments with greater uncertainty are those where the pattern of monthly demand from the previous year does not accurately predict the pattern of monthly demand in the current year.

The premise of this research is that retail buyers minimize uncertainty by developing proactive and reactive strategies. A proactive strategy is one where the buyer, supported by suppliers, develops an effective marketing strategy and creates predictable demand for the goods and services of the channel. The key assumptions behind this type of strategy is that the buyer can anticipate what consumers want and that the marketing program designed in conjunction with suppliers will be effective. While this may be reasonable in some situations, it is a tenuous assumption in the situation described earlier where consumers don't know or can't articulate what they want.

Alternatively, the buyer can take more of a reactive approach or strategy. If buyers cannot identify what consumers want in advance, they need to react to developing trends in a way that minimizes uncertainty of sales. With the help of suppliers, the buyer has to: (1) identify developing trends, and (2) develop programs that are flexible enough to respond to these trends. It is the early identification of trends and the development of flexible programs which allow the buyer to achieve predicted sales levels. In this sense, the buyer is not simply capitalizing on individual, sudden shocks in demand, but instead he is developing a program which allows him to determine the pattern and timing of demand.

In the next section of the paper, we will develop the hypotheses concerning the effect of different buyer/supplier relationships and the impact of the buyer's marketing program. Following this, we will discuss the methodology employed and the results obtained in the study.

THEORETICAL BACKGROUND AND HYPOTHESES

Channel Relationships

Few organizations control all the resources needed to develop and implement marketing activities. Consequently, channel members depend on one another (Stern and El-Ansary 1977). The degree to which the buyer depends on the supplier is determined by the buyer's ability to substitute alternative sources of supply for the resources provided by the supplier (Emerson 1962). The more important the resources provided, the more difficult it may be for the buyer to replace the supplier.

Current literature suggests two perspectives regarding how buyers should organize their relationships with suppliers. One is that buyers should avoid depending on suppliers (Porter 1980). When the buyer depends on a supplier, the supplier can threaten to withhold important resources unless the buyer complies with his demand. This can create problems for the buyer if the supplier uses his influence to reduce his own uncertainty at the expense of the buyer. For example, if the supplier forces the buyer to absorb inventories that aren't selling well, it will make it difficult for the buyer to achieve predicted levels of sales.

In addition, depending on a supplier may limit the .buyer's ability to develop reactive strategies. One way of identifying trends in the market is to experiment with a number of different styles and designs. When the buyer concentrates a large part of the department's resources on only a few suppliers, the variety of product portfolios the buyer offers the consumer may be limited. Furthermore, depending on a few suppliers may increase the difficulty of implementing the marketing program. When it is difficult to substitute suppliers and these suppliers cannot deliver products as needed, the buyer may fail to achieve anticipated levels of sales.

An alternative view is that buyers should maximize the supplier's dependence on the buyer (Pfeffer and Salancik 1978). When the supplier depends on the buyer, the buyer is able to influence the supplier. As a result the buyer can get the supplier to support his programs. When the buyer is able to develop proactive programs, he can use his influence over the supplier to gain cooperation in developing and implementing his programs. In addition, the supplier is more likely to respond to the buyer's requests in a timely manner if the buyer is an important customer.

In order to test the above prescriptions, it is necessary to model the relative dependence between the buyer and supplier, that is, the degree to which the buyer depends on the supplier and vice versa. If, for simplicity, dependence is conceptualized as a dichotomy (high versus low), then the relative dependence between the buyer and supplier can be categorized as: (1) Asymmetric Dependence where the Buyer dominates the Supplier (ADBS), (2) Asymmetric Dependence where the Supplier dominates the Buyer (ADSB), (3) Symmetric High Dependence (SHD), or (4) Symmetric Low Dependence (SLD). In asymmetric relationships, the less dependent partner dominates the more dependent one. In symmetric relationships, both are equally dependent on one another, but the degree of dependence may vary from high to low. In ADBS, the buyer is less dependent on the supplier than the supplier is on the buyer. In this case, the buyer has the advantage of being able to substitute one supplier for another which gives the buyer greater flexibility in determining trends and implementing programs. In addition, since the supplier depends on the buyer, the buyer can influence the supplier to contribute resources as needed. Therefore, ADBS should be the most effective relationship for minimizing departmental uncertainty.

H1: As the presence of asymmetric, buyer dominated relationships increases relative to other types of buyer/supplier relationships, the lower the realized uncertainty of the department.

In ADSB, the buyer is more dependent on the supplier than the supplier is on the buyer. For the buyer, this has the disadvantage that the supplier can influence his use of resources. In addition, from the buyer's viewpoint, it is the most inflexible type of relationship.

H2: As the presence of asymmetric, supplier dominated relationships increases relative to other types of buyer/supplier relationships, the higher the realized uncertainty of the department.

There are advantages and disadvantages to both types of symmetric relationships. In symmetric high dependence relationships, the buyer and supplier cannot easily replace each other. This gives them the incentive to work together to develop and implement the marketing programs needed to reduce uncertainty. However, these relationships are inflexible in the sense that the buyer cannot easily substitute one supplier's products for another.

Symmetric low dependence relationships offer the buyer the ability to experiment with different product offerings. The variety provided by "sampling" from these suppliers allows the buyer to identify trends in consumer preferences. They also provide more flexibility in implementing these programs since the buyer can easily substitute the products of one for another. However, the buyer cannot demand special favors from these suppliers.

H3: The impact of shifting the department from symmetric high dependence relationships to symmetric low dependence relationships should not change the level of realized uncertainty in departmental sales; the impact of symmetric relationships on realized uncertainty of sales should be intermediate between asymmetric relationships .

Marketing Program

Another means available to the buyer to increase predictability of sales is through the strategic use of advertising and markdowns. Most retailers rely heavily on newspaper advertising. In part, this is because newspapers serve the same local market as the retailer, so coverage is not wasted. But newspapers also communicate a sense of news and a degree of urgency about the purchase. Many retailers judge the effectiveness of Sunday's ads by the number of calls they get regarding the advertised merchandise on Monday morning. In this case, retail ads are used more for direct response than for long term objectives such as image building.

Similarly, markdowns are planned so as to stimulate demand. Consumers are assumed to be relatively price elastic. The purchase decision can be viewed as a -tradeoff between price and the utility derived from immediate consumption. The consumer who wants to be perceived as a fashion leader is willing to pay full price at the beginning of the season in order to use the merchandise immediately. The consumer who is more interested in getting a bargain will wait until the item is marked down. Markdowns, implemented strategically to stimulate demand as needed, should increase the predictability of departmental sales. Financial support for advertising and markdowns is one of the points of negotiation between buyers and suppliers. Aggressive bargaining for dollars is encouraged by store management. The dollars available from suppliers and from store management are then allocated across months to capitalize on store events. The higher the budget for marketing programs, the more flexibility the buyer has to react to and to capitalize on trends as they develop.

H4: As marketing expenditures increase, the lower the realized uncertainty of departmental sales.

METHODOLOGY

Measures

Uncertainty: Uncertainty is defined as the degree to which future states of the market in which the buyer and supplier operate cannot be anticipated or accurately predicted (Pfeffer and Salancik 1978) . Departmental uncertainty was estimated using two years of monthly sales data for each department. Using OLS, current sales levels were predicted from sales of the previous year. Uncertainty in departmental sales is then operationalized as (1-R2) (see Hannan and Freeman 1983), which represents the degree that current sales cannot be predicted from previous sales level. The assumptions behind this measure are that (1) predictions based on monthly periods capture the planning horizon of the buyer, and (2) last year's sales levels are the best base of prediction for the current year's.

Departmental uncertainty is in part a function of environmental conditions, namely, the level of market uncertainty. Market uncertainty refers to uncertainty in sales of the product line and was estimated in a manner similar to departmental uncertainty using information on total market sales. Information on both departmental sales and market sales was taken from a monthly report issued by an independent financial institution that collects and analyzes sales data from all of the major department stores in the metropolitan area. The correlation between departmental and market uncertainty is .6072.

Departmental Dependence Structure: Sixty-six buyers reported on the relative dependence between the store and over 2300 suppliers in their departments. Buyers characterized each supplier relationship by one of the following statement (1) the retailer could more easily replace the manufacturer than the manufacturer could replace the retailer (ADBS), (2) the manufacturer could more easily replace the retailer than the retailer could replace the manufacturer (ADSB), (3) it is difficult for both the manufacturer and retailer to replace each other (SHD), or (4) it is easy for both to replace each other (SLD). The buyers' reports were validated for a sample of 119 supplier relationships by both store management and the suppliers themselves. Results of the validation study show that there was a high degree of convergence among informant reports (see Buchanan 1985).

A measure of departmental dependence structure was then calculated by summing the retail dollars attributable to each type of dependence relationship (ADBS, ADSB, SHD, SLD) across the department and dividing these sums by the total retail dollars for the department. This measure represents the percentage of the department sales attributed to the four relationships.

Marketing Program: The impact of the departmental marketing program is measured using advertising and markdowns as a percentage of sales. Information on advertising and markdowns are available from the annual Profit and Loss Statement for the department. The correlation between advertising/sales and markdown/sales is only .009.

Control Variables: The following variables were added to the model as control variables: (1) the buyer's tenure in the department, (2) the market share of the department, (3) the rate of growth for the product area, and (4) the different merchandising areas within the store (e.g. women's ready-to-wear, men's and children's ready-to-wear, and the home store). All of the measures were collected from secondary data sources except the buyer's tenure which was measured by self report.

In general, buyer tenure, market share, and market growth are expected to be negatively related to departmental uncertainty. As the buyer gains more experience in the product area, his ability to effectively manage the department increases. This should be reflected in lower departmental uncertainty. Similarly, as market share and market growth increase, uncertainty should decrease. As the department's competitive position in the market increases, the risk of competition absorbing the benefits of the buyer's marketing activities decreases. As market growth increases, most of the risk stemming from managerial mistakes and strategic weaknesses is absorbed by growing demand (Porter 1980). Buyers should therefore find it easier to achieve target sales under these conditions. The three product areas are grouped according to store divisions and are represented by two dummy variables in the regression model. No hypotheses regarding the direction of these coefficients was advanced.

Statistical Model and Hypothesis Testing

The model is estimated using OLS. The model is:

DeptUnc = a + b1MktUnc - b2ADBS - b3SHD - b4SLD - b5Ad/S - b6Md/S - b7BuyDept - b8MktSh - b9MktGr + b10GMA1 + b11GMA2 + e

where:

DeptUnc = Uncertainty of Department Demand

MktUnc = Uncertainty of Market Demand

ADBS = Percent of Sales Derived from Buyer Dominated Relationships;

SHD = Percent of Sales Derived from Symmetric High Dependence Relationships;

SLD = Percent of Sales Derived from Symmetric Low Dependence Relationships;

Ad/S = Advertising to Sales Ratio for the Department

Md/S = Markdown to Sales Ratio for the Department

BuyDept = Time the Buyer Managed Department

MktSh = Market Share

MktGr = Market Growth

GMA1 = 1 if General Merchandise Area 2 1; 0 otherwise

GMA2 = 1 if General Merchandise Area = 2; 0 otherwise

Since a linear relationship exists between the four categories of department structure, only three were represented in the equation. ADSB is taken as the base case. The estimated coefficients for ADBS, SHD, and SLD are interpreted as the difference between the base case and each relationship, respectively. To test the expected impact of different dependence relationships, the equation is expressed in terms of shifting the department from one type of relationship to another (e.g. to ADBS from SHD):

E(DDeptUnc) = [b2 (ADBS + 1) + b3 (SHD - 1)] - [b2 ADBS + b3 SHD]

                      = [b2 - b3]

The null hypothesis of equality between relationships is rejected if:

b2-b3 = 0 + t(1-a/2) s(b2-b3)

RESULTS

The results are presented in Table 1. Overall, the model is significant at the .01 level. Among the control variables included in the model, market uncertainty, market share and market growth are all significantly related to departmental uncertainty. As expected, departmental uncertainty increased as market uncertainty increased; and departmental uncertainty decreased as market share and market growth increased. The coefficient for buyer experience was not significant.

TABLE 1

REGRESSION ESTIMATES

The impact of advertising to sales ratio on departmental uncertainty is negative, as expected, but the relationship is not significant. A potential reason for this is the multicollinearity between the Ad/Sale variable and other variables included in the model. However, tests for multicollinearity indicated that this was not a problem.

The impact of markdown; to sales on departmental uncertainty is significant; however, the impact is positive. This is counter to the prediction that increasing markdown dollars would decrease departmental uncertainty.

To test the significance of the dependence structure of the department, a restricted model was run dropping ADBS, SHD, and SLD from the equation. The R2 for the restricted model was .43728. A comparison of the full versus restricted model indicates that the dependence structure of the department contributes significantly to the model (F = 3.55003, df = 3, 125; p < .05). Table 2 reports the significance tests for the comparison of different dependence relationships.

Table 2 indicates that contrary to expectations, a shift in the departmental dependence structure to buyer dominated relationships from any other type of dependence relationship significantly increased the degree of department uncertainty. Furthermore, increasing the presence of supplier dominated relationships significantly decreased departmental uncertainty. Shifting the department between symmetric high dependence and symmetric low dependence relationships did not make a difference; and these relationships were intermediate of ADBS and ADSB in terms of their impact on departmental uncertainty.

TABLE 2

COMPARISON OF DIFFERENT DEPENDENCE

DISCUSSION

Buyer/Supplier Dependence Relationships

The results strongly support the view that buyer/supplier dependence relationships impact the level of uncertainty of departmental sales.

A comparison of the full versus restricted model indicates that department dependence structure is a significant predictor of environmental uncertainty. However, the impact of different buyer/supplier relationships is counter to the predictions of extant theories.

Buyer Dominated Relationships and Departmental Uncertainty (H1): The findings do not support the hypothesis that increasing the presence of buyer dominated relationships in the department increases predictability of sales. In fact, shifting the department to buyer dominated relationships from any other type of buyer/supplier relationship significantly increased the degree of realized uncertainty in departmental sales.

The hypothesized benefits of ADBS were based on the assumptions that (1) buyers are willing and able to develop programs to reduce the uncertainty of departmental sales, and (2) by dominating the supplier, the buyer is better able to implement the programs which reduce uncertainty. However, there are situational factors which limit the effectiveness of buyer dominated relationships.

One of the factors which may affect the buyer's ability and willingness to minimize uncertainty is the store s internal promotion policy. Retail department stores rotate buyers through departments on an average of every two years. Since this is a relative short period to gain an understanding of the consumer market and competitive offerings, buyers may not be able to fully develop their expertise in the product area. This limits their ability to develop effective marketing programs. A second result of this policy is that it reduces the buyer's motivation to reduce uncertainty for the department. Buyers want to be promoted to a department with more responsibility and greater visibility within the store. Since the buyer's performance is evaluated, in part, on sales and profitability of their department, the buyer's incentive is to maximize short term gains rather than to create long term stability for the department. Problems created by uncertainty are left for some other buyer to resolve.

The second assumption regarding buyer dominated relationships is that they command the resources of their suppliers and can force their suppliers to implement their programs. Again, this assumption may be tenuous given the nature of many of the suppliers in ADBS relationships. In general, these suppliers are more likely to be: (1) small operations which may not be financially stable, or (2) established companies that are having an "off' season, that is, their product offerings are not attractive to retailers. In either case, these suppliers tend to be less stable than companies in other types of relationships. Their instability has several implications. First, since survival is the foremost problem, they are more likely to focus on short term sales rather than long term stability. Second, given their instability, they may not be able to contribute to the buyer's programs even if the buyer demanded it. Third, these suppliers may fluctuate more in their ability to meet contractual agreements. And finally, the financial instability of the supplier organization may limit the number and types of products they offer. To the extent that these suppliers operate under greater constraints than other companies, they may not be able to offer as wide a range of products. Furthermore, the product offerings across these suppliers may be more homogeneous in nature because of the financial constraints common to all suppliers. If the number and variety of alternative product combinations are limited by supplier homogeneity and instability, the buyer is not able to experiment with different product combinations needed to detect trends in the marketplace.

Supplier Dominated Relationships and Departmental Uncertainty (H2): The findings do not support the hypothesis that increasing the presence of supplier dominated relationships makes departmental sales more unpredictable. In fact, as the presence of supplier dominated relationships increases relative to any other type of relationship, departmental uncertainty decreases.

The problems frequently associated with supplier dominated relationships are: (1) dominant suppliers force buyers to absorb the uncertainty, (2) from the buyers viewpoint, dominant suppliers are uncooperative in developing marketing programs, and (3) these types of relationships are inflexible and therefore the buyer has less opportunity to identify and react to trends in demand.

While it may be true that dominant suppliers may be able to force the buyer to take product lines that are not selling well, it may also be the case that these suppliers simply have fewer high risk products. In contrast with many buyers, these suppliers have made their careers in the same industry. They know the competition, and they know the consumer. As a result, they have developed the expertise needed to develop products and marketing programs to reduce uncertainty. In addition, they may have a greater incentive to reduce uncertainty. They have a vested interest in growing, but in growing in a stable and predictable manner. Erratic growth disrupts the logistics of production and distribution. By anticipating trends in consumer demand, they can adjust their internal processes and external transactions to minimize the disruptive influence of unexpected turns in demand. The buyer can then indirectly benefit from the supplier's skills in reducing uncertainty.

It is also true that these suppliers, in general, are less willing to invest in marketing programs with buyers. However, they have often invested in their own marketing programs to develop demand for their brand. In many cases, consumers perceive their name to be synonymous with the product category. Consequently, the buyer is able to take advantage of the relatively stable markets these suppliers have build for their products.

Finally, these suppliers may not offer buyers a great deal of flexibility in product offerings. But again, they have often preformed the function of experimentation internally. These companies often have a portfolio of products and are able to experiment with new products and marketing programs. By monitoring the trends for their products, they can react to changes in market demand, shedding designs that aren't doing well and supporting those that are.

Symmetric Relationships and Departmental Uncertainty (H3): As hypothesized, shifting the department from symmetric high dependence to symmetric low dependence relationships does not significantly impact the level of departmental uncertainty. Symmetric high dependence and symmetric low dependence relationships offer different, but equally effective, strategies for increasing the predictability of sales.

In comparison with ADSB, however, increasing the presence of symmetric relationships increases uncertainty. Perhaps this is because the suppliers in symmetric relationships are not as strong as dominant suppliers. They do not have enough resources to develop the marketing programs to build brand demand independent of the retailer. Consequently, they are not as successful as dominant suppliers in reducing departmental uncertainty.

In comparison with ADBS, increasing the presence of symmetric relationships decreases uncertainty. Again, the suppliers involved in symmetric relationships are potentially stronger than those in buyer dominated relationships. -As a result, suppliers in symmetric low dependence relationships are more likely to provide a variety of products than those in buyer dominated relationships. And suppliers in symmetric high dependence relationships are more likely to be able to help implement the buyer's marketing program with their joint resources. Consequently, they are more successful than ADBS in reducing departmental uncertainty.

Marketing Program (H4)

As advertising expenditures increased, it was expected that the uncertainty of the department would decrease. A higher budget allows the buyer greater flexibility in trying to stimulate demand in order to maintain a predictable pattern of sales. The results indicate that as expenditures for advertising as a percent of sales increase, departmental uncertainty decreases; however, the relationship was not statistically significant. Assuming ads are used effectively to stimulate sales for selected items, the retailer could reach expected demand levels through the strategic placements of ads. However, advertising does not always have the direct or immediate impact that managers expect. Furthermore, advertising also serves other purposes in addition to stimulating demand in the short run.

The results indicate that as markdowns as a percent of sales increases, the uncertainty of the department increases significantly. This result runs counter to expectation. It was predicted that markdowns are used to stimulate sales in order to increase predictability of sales. One explanation for this is that consumers perceive a "continual" markdown policy, that is, a policy where the price is first reduced by 10%, then 15%, etc., and they delay purchases as a result. Theoretically, such a policy should allow the retailer to take advantage of different price elasticities to maximize surplus and profit However, prior expectations on the part of the consumer may invalidate this quasi-price-discrimination policy. If the consumer expects the markdown to increase over some indefinite period of time, they may continue to tradeoff immediate consumption for future discounts. Markdowns may not prompt sales during the desired period, but at a later period when the consumer perceives prices to have reached a final level.

The markdown policy may also affect the consumer's image of the store and the department in the long run. By emphasizing price, the retailer sacrifices the fashion and quality image. Furthermore, he may not be able to compete effectively on the basis of price with discount houses. Trying to be both fashion and price oriented may undermine the retailer's competitive strength and increase uncertainty in sales.

SUMMARY

This study has attempted to determine the impact of marketing and channel relationships on the buyers ability to minimize uncertainty for the department. Advertising and markdown dollars are not found to be used effectively in this situation to minimize uncertainty. Perhaps this is because buyers are not skillful in the strategic implementation of these programs. On the other hand, minimizing uncertainty is only one of several objectives of the organization. Advertising and markdown programs may be more important in achieving other objectives than in minimizing the uncertainty of departmental sales.

Channel relationships, on the other hand, play a key role in minimizing departmental uncertainty. An investigation of the different types of relationships yielded results which contradict extant theories. In particular, this study challenges traditional beliefs by demonstrating that dominating a relationship does not always offer advantages, and that being dominated isn't always threatening. This leads to the conclusion that channel relationships should not be evaluated solely on the basis of who dominates whom. Instead, the relationship should be evaluated on the basis of the exchange partner's ability to provide solutions to environmental problems facing the focal partner.

REFERENCES

Buchanan, Lauranne (1985), The Organization of Dyadic Relationships in Distribution Channels: Implications for Strategy and Performance, Stanford, CA: Stanford University Unpublished Dissertation.

Child, John (1972), 'Organizational Structure, Environment and Performance: The Role of Strategic Choice," Sociology, 6, 2-22.

Emerson, Richard P. (1962), "Power-Dependence Relations," American Sociological Review, 27, 31-41.

Hannan, Michael T. and John Freeman (1981), "Niche Width and the Dynamics of Organizational Populations," Stanford University: Institute for Mathematical Studies in the Social Sciences.

Pfeffer, Jeffrey and Gerald R. Salancik (1978), The External Control of Organizations: A Resource Dependence Perspective, New York: Harper and Row.

Porter, Michael E. (1980), Competitive Strategy, New York: The Free Press.

Stern, Louis W. and Adel I. El-Ansary (1977), Marketing Channels, Englewood Cliffs, NJ: Prentice-Hall, Inc.

The Wall Street Journal (1984), "Teenage Girls, Alas, Are Big Consumers But Poor Customers," 9 November, 1.

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