determinants of retail profit performance: a consideration of retail marketing strategies

Determinants of Retail Profit Performance: A Consideration of Retail Marketing Strategies

J. Joseph Cronin, Jr. University of Kentucky

Between 1970 and 1980, retail store sales in the United States increased 10.1 percent (computed from Standard & Poors) to a 1980 total which exceeded $956.6 billion (Department of Commerce). However, the profit performance of the retail sector has not been impressive. In 1979, retail stores in the United States had an average net profit margin of 3.3 percent (Value Line, 1983); by 1981 profits had fallen to 2.4 percent of sales, a two year decline of 27.3 percent. Retailers experienced a partial recovery as estimated net margins increased to 2.9 percent in 1983 (Value Line, 1983), a level of performance which is expected to hold through 1988 (Value Line, 1983).

Previous research offers little guidance specifically for retailers. Some literature does focus on the relationship between the strategic marketing objectives employed by a firm and their profitability in nonretail industries. This literature serves as the basis for the research presented and is reviewed in the next section. Specifically, the purpose of this study was to identify which of the marketing strategies investigated are associated with higher levels of profit performance. The intent was to identify parsimonious guide- lines for retailers to use in selecting those marketing strategies which should aid in improving profit performance.

BACKGROUND AND PREVIOUS RESEARCH

The research presented in the paper considers the impact of marketing strategies on retail profit performance. The variables used to represent the

�9 1985, Academy of Marketing Science, Journal of the Academy of Marketing Science Fall, 1985, Vol. 13, No. 4, 40-53 0092-0703/85/1304-0040 $2.00

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marketing strategies investigated are considered, followed by a discussion of the dependent variable.

Marketing Strategy Variables

For some time, sales growth has been the primary marketing objective of corporate America (Higgins and Kerin 1983). Growth in sales volume creates economies in marketing and production operations, and has been viewed as an appropriate marketing strategy. A second strategy which has gained prominence as a marketing goal is increasing market share. The relevance of market share as a criteria for success has been widely publi- cized by the PIMS (Profit Impact of Marketing Strategies) research (Schoef- tier et al. 1974; Buzzell et al. 1975; Hedley 1977; Buzzell and Wiersma 1981). Achieving a high market share increases the scale of operations for the market share leader and can lead to competitive advantages and opera- tional economies which enhance profit performance.

A third measure included in the study (average inventory per store) reflects the importance of merchandise as a strategic tool in retailing. Inven- tory is normally the largest current asset controlled by retail managers and its importance to profitable retail operations has been detailed (Broeren 1981; Rosenbloom 1981, pp. 364-366; Duncan, Hollander, and Savitt 1983, p. 644).

A fourth marketing strategy investigated is the relative promotional effort utilized by the retailer. A major objective is to increase the net profits of a store by employing promotion (Edwards and Lebowitz 1981, pp. 5-8). Promotion can enhance a retail store's profitability by (1) securing increased sales volume at a decreasing total expense percentage, and (2) by speeding turnover (Edwards and Lebowitz 1981, p. 7). The present study investigates the association between the amount spent per store on promotion and profit performance.

The final marketing strategy examined is the retailer's ratio of selling space to employees. In effect, this is a surrogate measure for the retailer's capital-to-labor ratio. Retailers can attempt to improve their profit performance by enhancing their space productivity which is measured as net sales per square foot of selling space (Rosenbloom 1981, pp. 361-362; Lusch 1982, p. 473) and labor productivity which is measured as net sales per employee (Ingene 1982). The trend in retailing has been to substitute capital for labor in an effort to control and reduce expenses (Davidson, Sweeney, Stampfl 1984, pp. 493-494). This is reflected in the larger individual stores

42 DETERMINANTS OF RETAIL PROFIT PERFORMANCE: A CONSIDERATION OF RETAIL MARKETING STRATEGIES

becoming commonplace in the retail industry and in higher capital-to-labor ratios (space productivity divided by labor productivity).

Profitability

Several alternative measures of profitability exist, including net profit dollars, return on net worth, return on total liabilities, and return on total assets. Net profit dollars was not used because the measure is dependent on firm size; an inefficient large firm frequently earns a larger dollar profit than a highly efficient small firm. Because the sample includes retailers of varying size, net profit dollars is not an appropriate profitability measure for this study. Return on net worth reflects not only the productive use of a firm's assets, but also the capitalization of the firm. This measure was rejected along with the return on total liabilities criteria, because the strategic nature of the research dictated that a managerially controllable variable be used as the dependent measure. Return on total assets (ROTA) reflects the profitability of the assets available to management. The intent of the study was to analyze the relative value of marketing strategies to retail managers. Therefore, ROTA is the appropriate dependent measure.

RESEARCH HYPOTHESES

The background and previous research efforts suggest several hypotheses. Sales growth should be associated with higher levels of profitability because of the scale economics generated for the firm's marketing and production operations. Likewise, market share should be associated with improved profit performance. The PIMS research has extensively doc- umented this relationship (c.f. Schoeffier et al. 1974; Buzzell et al. 1975; Hedley 1977; Buzzell and Wiersma 1981). The average inventory efficiency measure investigated should, on the other hand, be negatively related to profit performance due to the measure used in this study. The measurement of this strategy utilizes average ending inventory per store; the larger the unsold inventory, the lower profitability expected because of the unsold merchandise. Theoretically, more efficient inventory/merchandise management results in lower ending inventories and increased profitability.

The final two marketing strategy measures examined should both be positively related to profit performance. Greater relative promotional efforts should, theoretically, be associated with improved profitability (Edwards and Lebowitz 1981, p. 7). Likewise, the substitution of capital for labor will increase the capital-to-labor ratio and should be associated with increased profit performance because of the resulting decline in expenses as

CRONIN 43

a percentage of total sales (Davidson, Sweeney, Stampfl 1984, pp. 493- 494). The hypotheses are summarized below.

H~: Sales Growt h is p o s i t i v e l y r e l a t ed to p rof i t performance.

H2: Marke t Share is p o s i t i v e l y r e l a t ed to p rof i t performance.

H3: Average Inventory Per Store is negatively related to profit performance.

H4: Relative Promotional Effort is positively related to profit performance.

H~: Capital-to-Labor Ratios are positively related to profit performance.

METHODOLOGY

Predictor Variables

The intent of the study was to determine which of the marketing strategies available to retailers are/is most highly associated with profit performance. All five variables investigated can be represented by measures readily available to retail managers. Table 1 presents the specific measures used to represent all the variables included in the study.

Sample and Data Sources

The sample consisted of annual observation for thirty-five grocery com- panies over a nine year period (1970-1978). After accounting for missing data, the number of observation for each variable was: sales growth - - 260, market share - - 239, average inventory per store - - 244, relative promotional eftort - - 114, capital-to-labor ratio - - 166, and ROTA - - 275. The data was pooled across the nine years after testing to determine if such aggregation was appropriate. Maddola (1977, pp. 320-333) indicates that pooling across sections and time is appropriate if the regression coefficients are homogeneous over the divisions. The author (Maddola 1977) suggests comparing the residual sum of squares from separate regressions for each of the periods or sectors with the residual sum of squares of the pooled regression. This test on the data utilized revealed no significant differences between each period and the pooled data base, so pooling was appropriate. The sample data was similarily examined to determine if pooling across the three types of grocery firms included in the sample was appropriate. No significant differences between the residual sum of squares of the conven-


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ience food store firms, supermarket firms, and the diversified supermarket firms (supermarket operations who also had related operations such as transportation fleets and agri-businesses) and the residual sum of squares of the pooled data were found. Therefore, pooling was again judged appropriate.

Data was gathered for the grocery industry for two major reasons. First, only one industry was chosen in order to minimize confusing cross-sec- tional variations. In addition, the retail food industry appeared appropriate because the industry seemed less susceptible to differences which might be attributable to such uncontrollable factors as fashion trends.

The data for the study were gathered from four sources. The net sales index, inventory turnover, number of sales outlets, and profitability measures were obtained from the COMPUSTAT Data Tapes. Market share was taken from the Supermarket New's Annual Distribution Study of Grocery Sales. Space and labor productivity information was gathered from The Retail Yearbook. The Securities and Exchange Commission's Supplemen- tary 10 K Reports provided the advertising to net sales measure. The thirty five firms included in the sample represent the total number of retail grocery firms common to all four sources.

Data Analysis

The purpose of the research was to determine which of the marketing strategies under study was associated with higher levels of profitability. Multiple regression analysis is an appropriate technique for examining the strength of the association between a dependent variable and multiple independent variables when multicollinearity among the independent variables is minimal (Hair et al., 1979, p. 90). Table 2 presents the intercorrelation matrix of the independent variables. All the correlations are well under the .8 limit imposed by the program utilized (Nie et al., 1975, pp. 340-341).

The relative contribution made by each of the strategy variables to the explanation of profit performance was examined through the use of stepwise forward regression analysis. Stepwise forward regression was appropriate for this purpose, because the procedure sorts out the variance in the dependent measure (profitability) individually accounted for by each of the predictor (strategy) variables.

RESULTS

As detailed earlier, stepwise multiple regression analysis was used to ascertain which marketing strategies were associated with higher levels of


profit performance. Table 3 presents the results of the stepwise multiple regression analysis of the five predictor variables which were used to represent the retail strategies investigated.

Table 3 presents the information needed to consider the five research hypotheses and all are confirmed. The BETA for each of the measures used to represent the five strategies investigated is in the direction hypothesized. Sales growth, market share, capital-to-labor, and relative promotion are hypothesized to exhibit a positive relationship with profit performance, while the average inventory efficiency variable has a negative beta value indicating that higher ending inventory levels are associated with lower profitability levels. Table 3 indicates that twenty-nine percent of the total variation in profit performance is explained by the five predictor variables.

However, before the data is fully interpreted, the stepwise multiple regression analysis presented in Table 3 should be considered further. The five steps presented in Table 3 imply that:

(1) sales growth exhibits the greatest initial association with profit performance;

(2) each of the four other strategies explains a statistically significant amount of variance left unexplained by the other strategies;

(3) based on the amount of independent variance explained in profit performance, the order of importance of the five strategies is sales growth, market share, capital-to-labor ratio, average inventory and relative promotional effort.

Through step four, interpretating the stepwise multiple regression analysis presented in Table 3 is relatively straight forward. The successive introduction of each of the first four marketing strategy variables explains an addi- tional portion of the variance in profit performance which is statistically significant without causing any of the previously entered variables to be- come insignificant. However, the introduction of the relative promotional effort measure in step 5 results in the sales growth measure becoming insignificant. Because increases in the promotional efforts of a retailer are designed to increase sales, it would be realistic to hypothesize that the reason behind this finding lies in a commonality in the variance in profitability explained by the two strategies. Moreover, it would appear prudent to restrict the interpretation of the BETA coefficients to the fourth step of the stepwise multiple regression analysis. Based upon that information, sales growth, whether obtained through increased promotional efforts or by any other means, has the largest relative influence on profit performance, followed respectively by market share, the capital-to-labor ratio, and average inventory.

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LIMITATIONS

This study focuses on a single segment of the retail industry-grocery firms. While studying only one segment enhanced the statistical (internal) validity of the research by focusing the study on a single strategic business unit with limited external (nonoperational) sources of variation in overall industry performance, the selection also limits the generalizability of the findings. Extensions of this study to other retail segments is needed. The discussion and implications which follow are relative only to the industry sampled, and extensions beyond that setting should be approached cau- tiously. In addition, the analysis focuses on five specific strategic marketing measures. Omitted from consideration are a vast number of environmental considerations and other strategic influences. Differing environmental con- ditions could impact the implications of these results, as could the influence of other strategic areas such as distribution and financial policies.

DISCUSSION AND IMPLICATIONS

Discussion of Results

Sales growth is the marketing strategy which exhibited the greatest level of association with profit performance. The BETA coefficient of .356, exhibited by sales growth in the fourth step of the stepwise multiple regression analysis presented in Table 3, is the largest exhibited by any of the five marketing strategy variables. This indicates that retailers should place the greatest emphasis on tactics which will result in sales growth. In fact, one of the tactics likely to result in such growth and improved profit performance was probably identified in this study. The confusion caused by the introduction of the relative promotional eflbrt variable in identifying the relative influence which sales growth has on profitability is probably the result of promotional effort measure being a tactic which influences profit performance through the resultant sales growth. Support for this interpretation lies in the comparison of the fourth and fifth steps of the stepwise multiple regression analysis (see Table 3). When the relative promotional effort enters significantly, the sales growth variable becomes insignificant, indicating that much of the variance in profitability explained by the relative promotional effort measure is also explained by the sales growth variable. That the later variable was entered first in the stepwise multiple regression analysis indicates that the sales growth strategy explains a greater portion of the total variance in profit performance, as is also indicated by the relative magnitude of its BETA coefficient in Step 4.


The interpretation of the remainder of the results presented in Table 3 is relatively straight forward. The fourth step in Table 4 suggests that an increase of one unit in market share will be accompanied by an increase of .255 profitability units. An identical increase in the capital-to-labor ratio should be accompanied by a profit performance improvement of .189 units. On the other hand, an increase in the average ending inventory per store of one unit is associated with a decline of .169 units in profitability. The incremental variance explained by the introduction of each of the four statistically significant strategies and the total variance in profit performance explained by the entire set of five predictors are statistically significant (p < .05).

Implications

The purpose of this study was to ascertain whether a parsimonious set of marketing strategies which are associated with profit performance could be identified to serve as criteria for evaluating and selecting the marketing tactics of retailers. The research reveals such a set does exist, as four of the predictors have a significant association with profitability which is readily intrepretable and combine to explain nearly 22 percent of the variation in profit performance. Specifically, sales growth, market share, and the ratio of capital-to-labor were found to have a significant and positive influence on profit performance, while average inventory per store exhibited the hypothesized negative relationship. Any attempt to interpret the implications of the relative promotional effort strategy is confounded because of the apparent communality its relationship to profit performance shares with the sales growth measure. Therefore, the later variable is omitted from any further consideration. However, the results presented do yield several important implications.

The first implication is that retailers should emphasize sales growth. When any strategy or tactic is considered by a retailer, a major consideration should be the impact on future sales. Obviously, the strategies or tactics which offer the greatest potential increase in sales should be preferred. As indicated in Table 3, sales growth accounts for the largest independent amount of the variance in profit performance. This implication suggests the traditional retail strategic marketing objective of sales growth is still fun- damentally sound.

A second implication is for retailers to also emphasize market share management. In recent years, the PIMS research (Schoeffier et al., 1974; Buzzell, et al. 1975; Hedley 1977; Buzzell and Wiersma 1981) has increas-

CRONIN 51

ingly turned attention towards market share as possibly the most important goal for guiding the evaluation and selection of marketing strategies. While the present research confirms the significant positive influence which market share has on profitability, it also reveals sales growth to be a better criteria for judging retail marketing strategies.

A third implication for retailers who aspire to earn higher profits is to substitute capital for labor. The positive BETA coefficient exhibited for the capital-to-labor ratio in Table 3 suggests a higher portion of capital, as opposed to labor, is associated with improved profit performance. This would indicate that retailers who have larger square footage facilities with lower use of labor should be more profitable. Thus, grocery and other volume oriented retailers should endeavor to stress self service assortments, and to utilize such capital intensive-labor saving strategies as warehouse automation, bulk price-marking, and electronic checkout scanners. Service dominated retailers, such as fashion clothing outlets, probably can enhance their project performance by employing the latter strategies as well. How- ever, self-service assortments are obviously not relevant to all retail segments.

The final implication inherent in this study results from the consideration of the average inventory per store measure. The negative relationship exhibited suggests that all efforts designed to reduce a retail store's ending inventory level should be considered. A need for better forecasting of customer demand is an obvious implication this finding holds for retail managers. In addition, there is also an implication that retailers should not take too many chances on new products. Should the new products not sell and thereby be added to ending inventories, a decline in profit performance might result. Not all low volume items can ever be eliminated without injury to customer satisfaction, but with proper planning, the inventory of these items can be minimized.

In conclusion, when considering potential marketing strategies, retail managers would be well advised to emphasize sales growth, increases in market share, the substitution of capital for labor, and the reduction of ending inventories. Any strategies or tactics which result in these outcomes should be accompanied by improved profit performance. Such strategies stand the best chance of improving the retailer's profitability. Present marketing strategies should also be evaluated by retailers on the same basis. In addition, this study has also pointed out a need to further explore the promotion-sales-profit performance relationship. The first two dimensions have been investigated in many areas (C.E Tull 1965; Bass and Clarke


1972; Clarke 1976), but extensions to the impact on profit performance seem necessar~

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Bass, Frank M. and Darral G. Clarke (1972), "Testing Distributed Lag Models of Advertising Effect," Journal of Marketing Research, 9 (August), 298-308.

Broeren, Mary Ann (1981), "Perspectives on Profit," Retail Control, 50 (September), 39- 46.

Buzzell, Robert D., Bradley T. Gale, and Ralph G.M. Sulton (1975), "Market Share-A Key to Profitability," Harvard Business Review, 53 (January-February), 97-106.

and Frederick D. Wiersma (1981), "Successful Sharebuilding Strategies," Harvard Business Review, 59 (January-February), 135-144.

Clarke, Darral G. (1976), "Econometric Measurement of the Duration of Advertising Effect on Sales," Journal of Marketing Research, 13 (November), 345-357.

Davidson, W. R., D. J. Sweeney, and R. W. Stampfl (1984), Retailing Management. 5th ed., New York: John Wiley and Sons.

Duncan, Delbert J., Stanley C. Hollander, and Ronald Savitt (1983), Modern Retail Manage- ment, tenth edition. Homewood, Illinois: Richard D. Irwin, Inc.

Edwards, Charles M., Jr. and Carl E Lebowitz (1981), Retail Advertising & Sales Promotion. Englewood Cliffs, New Jersey. Prentice-Hall, Inc., fourth edition.

Frank, R.E., W.E Massey, and D.G. Morrison (1965), "Bias in Multiple Discriminant Anal- ysis," Journal of Marketing Research, 2 (August), 250-258.

Hair, Joseph E Jr., Rolph E. Anderson, Ronald C. Tatham, and Bernie J. Grablowsky (1979), Multivariate Data Analysis. Tulsa, Oklahoma: PPC Books.

Hedley, Barry (1977), "Strategy and the Business Portfolio," Journal of Long Range Plan- ning, 10 (February), 9-15.

Higgins, Robert C. and Roger A. Kerin (1983), "Managing the Growth-Financial Policy Nexus in Retailing," Journal of Retailing, 59 (Fall), 19-48.

Ingene, Charles A. (1982), "Labor Productivity in Retailing," Journal of Marketing, 46 (Fall), 79-90.

Luscb, Robert (1982), Management of Retail Enterprises. Boston, Massachusetts: Kent Pub- lishing Co.

Maddala, G.S. (1977), Econometrics. New York City: McGraw-Hill Book Company. Nie, Norman H., C. Hadlai Hull, Jean G. Jenkins, Karin Stembrenner, and Dale H. Bent

(1975), SPSS, second edition. New York City: McGraw-Hill Book Company. Rosenbloom, Bert (1981), Retail Marketing. New York City: Random House, Inc. Schoeffler, Sidney, Robert D. Buzzell, and Donald Heany (1974), "The Impact of Strategic

Planning on Profit Performance," Harvard Business Review, 52 (March-April), 137-145. Tull, Donald S. (1965), "The Carry-over Effect of Advertising," Journal of Marketing, 29

(April), 46-53.

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ABOUTTHEAUTHOR

J. JOSEPH CRONIN, JR. is an Assistant Professor in the Department of Marketing, at the University of Kentucky. He received a Ph.D. from the Ohio State University with a major in marketing, and a minor in logistics. His research has been published in the Journal of Retailing, the Journal of the Academy of Marketing Science, and the Proceedings of the Academy of Marketing Science and the Southern Marketing Association.

determinants of retail profit performance: a consideration of retail marketing strategies

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