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H4: Experienced eBay sellers will be more likely to have Power Seller status than inexperienced eBay sellers as measured by the variable POWSEL. POWSEL H5: Experienced eBay sellers will be more likely to have a “Me” page than inexperienced sellers as measured by the variable MEPAGE. H6: H6: Experienced Experienced eBay sellers sellers will be more likely likely to to sell items with with higher higher prices prices than than inexperienced sellers as measured by the variable PRICE. The six hypotheses were tested using ordinary least squares multiple regression analysis with the variable YRS entered as the dependent variable and RATING, STORE, POWSEL, MEPAGE, VOLUME and PRICE as predictor variables. H1 was tested by examining the correlation between YRS and VOLUME. H2 was tested by examining the correlation correlation between between YRS and and STORE. STORE. H3 was tested tested by examining the the correlation correlation between YRS YRS and and RATING. RATING. H4 H4 was was tested tested by by examining examining the correlation between between YRS and and POWSEL. POWSEL. H5 H5 was was tested tested by examining examining the correlation between YRS and MEPAGE. HH6 H was tested by examining the correlation between YRS and PRICE. RESEARCH RESULTS Journal of Management and Marketing Research A A presentation of relevant relevant descriptive statistics for the data can can be found in in Figure 3 (Appendix). . As As indicated indicated by by the the differences differences between the the means means and and medians medians for for the th variables variables VOLUME VOLUME and and PRICE, PRICE, these these two two variables are somewhat somewhat skewed. Nonetheless, Nonetheless, the statistical techniques used to analyze these data are robust (Hair 1992). Figure 4 shows the correlation between the dependent variable, variable YRS, and each of the independent variables. The ranking of these correlations are: (1). PRICE, (2). MEPAGE MEPAGE, (3) RATING, (4) VOLUME, (5) POW, (6) STORE STORE. . Note that the most highly correlated variables PRICE, MEPAGE and RATING are associated with a seller’s pricin pricing, g, differentiation and volume, respectively. Multicollinearity is an important consideration in this study and it does not appear to be present. The highest correlation between independent variables shown in Figure 4 (Appendix) is .448, which is moderate. When comparing different regression models equations using STEPWISE, , the size and direction of the coefficients remain consistent. In addition, the rank of the coefficients based on their p-value is very similar to the ranking of the correlations shown in YRS column in Figure 4. Lastly, the variance inflation factor (not shown in Figure 4) for for all all independent variables is is less less than than 3. 3. All All of of these these indicators indicators lead us us to believe that multicollinearity is not present present, , and therefore individual coefficients may be interpreted. The assumptions made by ordinary least squares regression model appear to hold for our our data data set. set. The The plot plot of of residuals against predicted value shows shows a random scatter pattern. A histogram of the residuals and normality plot show the distribution to be symmetrical and mound-shaped, , however some departure from the theoretical normal shape. However, as mentioned mentioned earlier ordinary least least squares regression regression model model is is robust with with respect respect to this assumption (Hair 1992). Thus, these hese indicators lead us to believe the data does not violate the least squares assumptions. The multiple regression equation based on 6 independent variables yielded a multiple correlation coefficient, R, , of .334 and a coefficient of determination, R-square, R of 11.2 percent suggesting there are other variables beyond these that might be related to ee-tailer longevity. The entire model, , however, was regarded as strongly and significantly predictive of YRS (F=34.2, p-value=.4.49E 4.49E-39 as shown in Figure 5).
Figure 6 (Appendix) shows that of the six predictor variables, only POWSEL was found to be below the .05 threshold for significance, significance however the sample showed the relationship based was positive. . The variable, STORE, was significant, but was inconsistent with the corresponding hypothesis. Of the five significant variables, t showing the greatest linearity to the dependent variable was PRICE and as indicated in Table 3 (Appendix). The ranking of independent variables based on their p-value p is PRICE, MEPAGE, RATING, VOLUME, STORE and POW similar to ranking of variables in Table 3 with the exception of POWSEL and STORE positions of 5 STORE are moderately correlated which may be the source of the position re Overall, H1 (VOLUME), H3 (RATING), supported by our analysis. Thus, supports the WO experienced retailers and inexperienced retailers in terms of differentiation pricing. However, H2 (STORE) differentiation are not supported. th and 6 th only POWSEL was , however the sample showed the significant, but was directionally Of the five significant variables, the variable showing the greatest linearity to the dependent variable was PRICE and as indicated in Table is PRICE, MEPAGE, RATING, VOLUME, STORE and POW similar to ranking of variables in Table 3 with the are reversed. POWSEL and STORE are moderately correlated which may be the source of the position reversal. versal. (VOLUME), H3 (RATING), H5 (MEPAGE) and H6 (PRICE) are . Thus, supports the WOR constructs of differences between experienced retailers and inexperienced retailers in terms of differentiation, , volume and (STORE) and H4 (POWSEL) as surrogates for the construct of are not supported. DISCUSSION Journal of Management and Marketing Research Apart from the results results reported reported in the previous section on on our six six research research hypotheses, hypotheses, there there are are a a number number of of interesting revelations regarding regarding eBay eBay and and its its evolution evolution as as an an online online retail facilitator that arose from the study. One was the degree to which larger sellers aaffect eBay’s eBay’s revenues, revenues, which which underscores the company’s shift shift in in strategic strategic direction from its traditional traditional posture posture as as an online auction auction site that that secondarily offered fixed price price merchandise, to a fixed price priced site that secondarily offers auction mercha merchandise ndise (Holahan 2008). With roughly roughly 20 20 percent percent of the the sellers sellers accounting for about about 85 85 percent percent of the the firm’s firm’s volume volume (nearly half half the volume volume being being accounted for by by the top 5 percent), it it is is not not surprising that eBay has embraced a business model that is more oriented toward maintaining price consistency and security than the turbulent and risk risk-oriented oriented marketplace that typified its earlier existence. The The fact that that VOLUME VOLUME was very significant is not surprising surprising since the the variable variable was a a ratio in which one of the components components was the dependent dependent variable. variable. However, the fact fact that it was was less significant significant than than PRICE was was very very revealing revealing since since it indicates that as sellers gain in experience experience selling selling on eBay eBay (and (and by by extension, online) they engage in more transactions at higher r average prices. This is consistent consistent with retail retail evolution predicted predicted according according to to The The Wheel of Retailing paradigm expressed in Figure 1. The fact that 43 percent of all sellers pay to maintain an eBay store (Table 2) 2), where the merchandise is inventoried longer longer-term term and sold at a fixed price, indicates that a large percentage percentage of of sellers are adapting to the new environment and and operating operating more more like like traditional retailers. retailers. This necessitates that sellers sellers maintain larger larger levels levels of working working capital and and endure higher er turnover rates in exchange for improved margins. The Wheel of Retailing provides an explanation explanation for for this this phenomenon, phenomenon, however however STORE was was not not found found to to be be significantly significantly correlated correlated to to longevity, and and in in fact fact the the model model yielded yielded a a reverse reverse relationship. One exp explanation exp is is that that eBay eBay may may more more recently recently be be attracting attracting retailers retailers that were were previously previously selling on fixed price price sites sites such as as Amazon. If this is the case, case, these retailers would would be newer to eBay but still quite experienced in online retailing. Slightly more than a third of the sellers in the study were identified as “Power Sellers.” Sellers.” In In order order to to become become a a Power Power Seller, Seller, a a seller seller must have sales consistently over one thousand thousand dollars dollars per per month, month, 98 98 percent feedback rating, and and average better than 4.5 stars (out of a possible five) ) on four service dimensions. This suggests that Power Sellers would necessarily necessarily be be more more focused focused on on the service dimensions of of their businesses businesses than other eBay sellers.
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