Factors Affecting Spending in the Store - Case Study Example

Factors That Affect s Decisions to Spend in a Clothing Store: The Effects of Gender, Income Level, Age and Membership to Loyalty Programs onAmount Spent in a Store Name Institution Introduction Several factors are associated with the choice to purchase any kind of goods or services. This research paper investigates the role of gender, income level, age, and membership to loyalty on (1) the amount spent purchasing clothing from a selected store, and (2) the fraction of personal budget spent on purchasing clothing that is devoted to the selected store. Research Questions and Literature Review The role of gender in explaining the difference in shopping remains controversial, with sections of literature (e.g. Gillies, Kitamura & Yokota-Landou, 2005; and Ruth, Kanaan & Bramlett, 2000) pointing out some of these inconsistencies in literature. However, Alok (2009) is convinced that female shoppers are more likely to remain loyal to shops they have signed loyalty programs with. Nazia (2011) delved into the effect of income levels on shopping habits, supporting notions spread by Peter, Borle and Kadane (2003) that shoppers with higher income tend to be loyal to more shops than those with lower income. Yuping, Williams and Tam (2010) refuted this claim, noting that every individual signs up with a program based on how much they need the products offered by a store. Older buyers are shown in Rose (2013) as being less likely to make large purchases, due to their partial inability to earn at the same pace as the energetic younger cohorts. Seyhmus (2002), however, had a differing opinion, preceding Rose’s article with the assertion that age does not actually affect ability to shop (size of purchase) since there are many wealthy older persons. Based on these contradicting notes, this research poses the questions: 1) Are there differences in the amount of money spent on clothing and percentage of clothing budget spent at a store based on age? 2) Are there differences in the amount of money spent on clothing and percentage of clothing budget spent at a store based on income? 3) Are there differences in the amount of money spent on clothing and percentage of clothing budget spent at a store based on gender? 4) Are there differences in the amount of money spent on clothing and percentage of clothing budget spent at a store based on membership to loyalty program? Research Models and Hypotheses The current research is based on a model depicting the consumer as more being more loyal based on their membership to loyalty programs. Therefore, the response (percentage of clothing budget spent at the store’s clothing category and amount of money spent at the store) are affected by the age, income, gender and membership to loyalty for the participants. The hypotheses developed in response to the research questions are: H1: There is no significant difference between amount spent at the clothing category and percentage of clothing budget spent on clothing at the store for male and female participants. H2: There is no significant difference between amount spent at the clothing category and percentage of clothing budget spent on clothing at the store for participants with different incomes. H3: There is no significant difference between amount spent at the clothing category and percentage of clothing budget spent on clothing at the store for participants in different age groups. H4: There is no significant difference between amount spent at the clothing category and percentage of clothing budget spent on clothing at the store for participants signed to the loyalty program and those not signed. Results Understanding the Sample: Descriptive Statistics The sample comprised 202 participants who were all shoppers at the selected clothing store. 122(60.4%) were male while 80 (39.6%) were female shoppers. There were no shoppers below the age of 18 years. However, 184 (91.1%) were adults aged between 19 and 50 years while 18 (8.9%) were older persons aged above 51 years. Seven (3.5%) of participants belonged to the lowest group of earners (under $20,000). Twenty two (10.9%) earned between $20,000 and $39,999; 46 (22.8%0 earned between $40,000 and $59,000; 57 (28.2%) earned between $60,000 and $79,999; 41 (20.3%) were categorized between $80,000 and $99,999; 26 (12.9%) earned in the range $100,000 and $149,999; while only 3 (1.5%) appeared in the highest class of earners ($150,000 and above). Classified based on occupations, 18 (8.9%) were categorized as professionals; 34 (16.8%) were executives; 49 (24.3%) played managerial roles; 29 (14.4%) worked as administrators; 9 (4.5%) served in technical roles; 14 (6.9%) were students; 15(7.4%) were sales persons; 12 (5.9%) were laborers; 1 (0.5%) of the participants was a secretary while 21 (10.4%) served in other job specializations. The lowest comparative spender only purchased clothing worth 12% of their total amount spent on shopping for clothes alone. This figure is quite small compared to that of the shopper who spent the largest ratio (98%) of their total shopping budget in the particular clothing store. Thirteen shoppers in the sample spent 55% of their entire clothing budgets in the store, marking the most frequent (modal value) ratio of amounts spent in the store vis-à-vis the entire budgets. The value 41% was the second most frequent ratio with 11 participants while all other ratios had representations below 10 participants. Seventy seven (38.1%) of participants were members of the store’s loyalty program while 125 (61.9%) were yet to register the loyalty program membership. Table 1. Descriptive statistics. N Min Max Mean Std. Dev. Skewness Kurtosis Statistic Statistic Statistic Statistic Statistic Statistic S.E. Statistic S.E. Age 202 23 65 37.13 8.382 .500 .171 -.102 .341 Number of times purchases visited in this store 202 1 8 4.16 1.784 .096 .171 -.553 .341 Estimated total amount spent on clothing category 202 80 2000 566.13 383.773 1.392 .171 1.908 .341 Valid N (listwise) 202 Based on Table 1 above, the average age of participants was 37.13 years (std. dev. = 8.38, minimum and maximum ages are 23 and 65 years respectively). The lowest number of purchases purchased by any participants was 1 while the highest was 8. The average number of purchases per individual were 4.16 (std. dev. = 1.78). The average estimated total amount of money spent in the clothing category was $566.13 (std. dev. = 383.77). The minimum amount spent in the category was $80 while the maximum was $2,000. Inferential Statistics Analysis of variance (ANOVA) was used to shed light on the significance of the spending rates and amounts spent by participants based on their various categorizations. The tabulated results and their interpretations are presented below. All tests were undertaken at the 5% (0.05) level of significance. Age and spending. Age was hypothesized to have impact on the amount of money spent on purchasing clothing at the store. The amounts spent by younger and older shoppers to buy cloths in the store were hypothesized to have no significant differences. Table 2. Descriptive analysis for amount and ratio of budget spent in the store and clothing based on age. N Mean Std. Dev. S.E. 95% CI for mean L.B. U.B. Estimated total amount spent on clothing category Adult (19-50) 184 572.49 379.702 27.992 517.26 627.72 Old (>51) 18 501.11 429.526 101.240 287.51 714.71 Total 202 566.13 383.773 27.002 512.88 619.37 Amount spent in this store as percentage of total amount spent on clothing category Adult (19-50) 184 54.94 20.823 1.535 51.91 57.97 Old (>51) 18 45.00 15.076 3.554 37.50 52.50 Total 202 54.05 20.544 1.445 51.20 56.90 Table 2 above (part of the important ANOVA output) indicates that adults between 19 and 50 years spent an average $572.49 (std. dev. = 379.70) to purchase cloths while those above 50 years spent $501.11 on average (std. dev. = 429.53) for the same purpose. Participants between 19 and 50 years spent 54.94% (std. dev. = 20.82) of their total clothing budget on average in purchasing cloths from the store. Those above 50 years spent 45% on average (std. dev. = 20.54). We now investigate whether the higher amounts spent in the clothing category and the higher percentage of total clothing budget spent in the store for the age group 19 to 50 translates into significant spending differences for the two age groups. Table 3. ANOVA table for the differences in clothing spending and percentage of budget spent in store. Sum of Squares df Mean Square F Sig. Estimated total amount spent on clothing category Between Groups 83534.897 1 83534.897 .566 .453 Within Groups 29520143.756 200 147600.719 Total 29603678.653 201 Amount spent in this store as percentage of total amount spent on clothing category Between Groups 1620.059 1 1620.059 3.894 .050 Within Groups 83212.342 200 416.062 Total 84832.401 201 Based on Table 3 above, the amount of money spent in the clothing category for the two groups is not statistically different (F = 0.566, df = 201, p = 0.453). Therefore, shoppers from either age groups spent significantly similar amounts for purchasing from the clothing category. On the other hand, we find that the percentage of entire clothing budget spent at the store is not significantly different for the two groups (F = 3.89, df = 201, p = 0.05). The p-value for the test was not lower than the chosen level of significance (0.05). Again, we conclude that there was no significant difference in the percentage of total clothing budgets for shoppers under the two age categories. Gender and spending. The effect of spending patterns among male and female participants was investigated. The presumed hypothetical relationship between amounts spent by females and males is that females spend significantly more in clothing than males; and that there is no significant difference in percentage of budget spent by members of both gender in shopping at the clothing category. Table 4. Descriptive analysis for amount and ratio of budget spent in the store and clothing based on gender. N Mean Std. Dev. S.E. 95% C.I. for mean Min Max L.B. U.B. Estimated total amount spent on clothing category Male 122 567.47 389.259 35.242 497.70 637.24 80 2000 Female 80 564.09 377.683 42.226 480.04 648.14 100 2000 Total 202 566.13 383.773 27.002 512.88 619.37 80 2000 Amount spent in this store as percentage of total amount spent on clothing category Male 122 54.51 21.544 1.951 50.65 58.37 12 98 Female 80 53.36 19.029 2.128 49.13 57.60 20 96 Total 202 54.05 20.544 1.445 51.20 56.90 12 98 Based on Table 4 above, males spent higher average amounts (mean = $567.47, std. dev. = 389.26) in the clothing category than did the female shoppers (mean = $564.09, std. dev. = 377.68). Similarly, males spent a larger percentage of their clothing budget in the store (mean = 54.51%, std. dev. = 21.54) than did the female shoppers (mean = 53.36%, std. dev. = 19.03). The significance of this difference is tested in Table 5 below. Table 5. ANOVA table for the differences in clothing spending and percentage of budget spent in store. Sum of Squares df Mean Square F Sig. Estimated total amount spent on clothing category Between Groups 551.897 1 551.897 .004 .951 Within Groups 29603126.756 200 148015.634 Total 29603678.653 201 Amount spent in this store as percentage of total amount spent on clothing category Between Groups 63.422 1 63.422 .150 .699 Within Groups 84768.979 200 423.845 Total 84832.401 201 The results in this section are surprising in that males appeared to spend more on clothing than did the females. However, the difference between the two groups’ spending rates in the clothing category is not statistically significant (F = 0.004, df = 201, p = 0.951). Males are therefore likely to spend equal amounts to females. As hypothesized, the percentage of the total individuals’ clothing budget spent in the clothing category was not statistically different for male and female shoppers (F = 0.150, df = 201, p = 0.699). Income and spending. It was hypothesized that persons with higher incomes tend to shop with significantly higher amounts than persons with lower income. Similarly, persons with higher income are able to afford membership to several loyalty programs, which would be expected of the higher earners in the sample. Table 6. Descriptive analysis for amount and ratio of budget spent in the store and clothing based on age. N Mean Std. Dev. S.E. 95% C.I. for Mean Min Max L.B. U.B. Estimated total amount spent on clothing category under $20 000 7 291.43 200.348 75.724 106.14 476.72 150 700 $20,000-$39,999 22 573.64 433.156 92.349 381.59 765.69 200 1800 $40,000-$59,999 46 477.04 258.675 38.140 400.23 553.86 100 1200 $60,000-$79,999 57 618.74 387.584 51.337 515.90 721.58 80 1560 $80,000-$99,999 41 599.41 409.513 63.955 470.16 728.67 100 2000 $100,000-$149,999 26 635.00 489.647 96.028 437.23 832.77 80 2000 $150,000+ 3 466.67 152.753 88.192 87.21 846.12 300 600 Total 202 566.13 383.773 27.002 512.88 619.37 80 2000 Amount spent in this store as percentage of total amount spent on clothing category under $20 000 7 29.71 29.803 11.265 2.15 57.28 12 96 $20,000-$39,999 22 46.86 18.022 3.842 38.87 54.85 21 98 $40,000-$59,999 46 58.52 19.546 2.882 52.72 64.33 20 94 $60,000-$79,999 57 56.12 20.544 2.721 50.67 61.57 20 96 $80,000-$99,999 41 53.41 19.718 3.079 47.19 59.64 18 95 $100,000-$149,999 26 55.08 19.127 3.751 47.35 62.80 20 95 $150,000+ 3 55.67 18.148 10.477 10.59 100.75 35 69 Total 202 54.05 20.544 1.445 51.20 56.90 12 98 Based on Table 6 above, the shoppers earning between $100,000 and $149,999 were the highest spenders in clothing, followed by those with $60,000 - $79,999 income. Those earning the highest (above $150,000) were the second lowest spenders in the clothing category. Persons who spent the largest proportion of their clothing budgets at the store earned between $40,000 and $59,999 (58.52%), followed by those earning $60,000 - $79,999 (56.12%), above $150,000 (55.67), $100,000 - $149,999 (55.08%), $80,000 - $99,999 (53.41%), $20,000 - $39,999 (46.86%) and below $20,000 (29.71%). Table 7. ANOVA table for the differences in clothing spending and percentage of budget spent in store based on income. Sum of Squares df Mean Square F Sig. Estimated total amount spent on clothing category Between Groups 1250708.265 6 208451.377 1.434 .204 Within Groups 28352970.389 195 145399.848 Total 29603678.653 201 Amount spent in this store as percentage of total amount spent on clothing category Between Groups 6498.299 6 1083.050 2.696 .015 Within Groups 78334.102 195 401.713 Total 84832.401 201 There were no significant differences between the amounts of money spent in the clothing category for the various income groups (F = 1.434, df = 201, p= 0.204). This was further supported by the post-hoc analysis (Appendix 1), which showed that there were no significant differences between any systematically selected pair of income groups. On the contrary, percentages of amounts spent at the clothing category of the store differed significantly across the income groups (F = 2.696, df = 201, p = 0.015). The post hoc analysis table confirms that only two of the paired income levels had significant differences between them. These include the categories under $20,000 and $40,000 - $59,999 (mean diff. = -28.807, p = 0.009); and under $20,000 and $60,000 to $79,999 (mean diff. = -26.409, p = 0.05). All other pairings did not exhibit significant differences in the percentages of their clothing budgets that they spent at the clothing category of the store. Membership to loyalty program and spending. The relationship between membership to the store’s loyalty program and amount of money and percentage of clothing budget spent at the store were investigated on the basis of the hypothesized relationship that those with membership spent more shopping for clothes than those who did not. Table 8. Descriptive analysis for amount and ratio of budget spent in the store and clothing based on membership to loyalty. N Mean Std. Dev. S.E. 95% C.I. for Mean Min Max L.B. U.B. Estimated total amount spent on clothing category No 77 586.65 413.419 47.113 492.81 680.48 80 2000 Yes 125 553.49 365.462 32.688 488.79 618.19 80 2000 Total 202 566.13 383.773 27.002 512.88 619.37 80 2000 Amount spent in this store as percentage of total amount spent on clothing category No 77 54.42 20.766 2.367 49.70 59.13 15 98 Yes 125 53.83 20.486 1.832 50.21 57.46 12 96 Total 202 54.05 20.544 1.445 51.20 56.90 12 98 Based on Table 8, the average amount spent by the participants who did not have a membership to the program to purchase clothing was $586.65 (std. dev. = 413.42) while that of those with membership was $553.49 (std. dev. = $365.46). Participants who had not signed to the loyalty program spent 54.42% of their clothing budget in the clothing category of the store, slightly more than the participants with a loyalty membership (mean = 53.83%). Table 9. ANOVA table for the differences in clothing spending and percentage of budget spent in store based on loyalty. Sum of Squares df Mean Square F Sig. Estimated total amount spent on clothing category Between Groups 52397.889 1 52397.889 .355 .552 Within Groups 29551280.764 200 147756.404 Total 29603678.653 201 Amount spent in this store as percentage of total amount spent on clothing category Between Groups 16.228 1 16.228 .038 .845 Within Groups 84816.173 200 424.081 Total 84832.401 201 There was no significant difference (F = 0.355, df = 201, p = 0.552) in amounts spent on the clothing category by those signed to the loyalty program and those who did not. Similarly, there was no significant difference between the percentages of clothing budgets spent in the store for those in the loyalty program and those not signed to it. Discussion Clearly, gender, loyalty status, and age did not affect either of the responses: amount spent in the clothing category or the percentage of budgeted amount spent on clothing at the selected store. Therefore, we realize that in conformity to Seyhmus (2002), Ruth et al. (2000), and Yuping et al. (2010) who supported contrary opinions to those suggesting that these factors affected amount of money spent shopping at an outlet. On the other hand, income positively affects the amount spent, in line with the position taken by Peter et al (2003). It is therefore prudent to advise the store owner to stock the shop with goods that resonate well among members of the various income categories, as opposed to basing their marketing on gender, loyalty, and age. Further research is encouraged based on more diverse populations and different categorization of age groups. References Alok, S. (2009). Reward programs and loyalty behaviour in the Indian retail sector. Advances in Consumer Research. 8(10): 309- 320. Gillies, L., Kitamura, T. & Yokota-Landou, M. (2005). Adding value to hotel loyalty programs for both guest and hotel. Goteborg: Goteborg University. Nazia, C. (2011). Hospitality loyalty program effectiveness evaluation rubric. Las Vegas: University of Nevada. Peter, B., Borle, S. & Kadane, J. (2003). A model of the joint distribution of purchase quantity and timing. Journal of the American Statistical Association. 98(30): 463-564. Ruth, B., Kanaan, P. K. & Bramlett, M. (2000). Implications of loyalty program membership and service experiences for customer retention and value. Journal of the Academy of Marketing Science. 28(1): 95-108. Rose, C. A. (2013). The price of loyalty: A gendered analysis of consumer surveillance. Kingston: Queens University. Seyhmus, B. (2002). Dimensions of customer loyalty: Separating friends from well-wishers. Journal of Customer Loyalty. 43(47): 47-58. Yuping, L., Williams, E. V. & Tam, L. (2010). Not all repeat purchases are the same: Attitudinal loyalty and habit. Norfolk: Old Dominion University. Appendix Appendix 1. Tukey HSD multiple comparisons (post hoc tests). Dependent Variable (I) Income (J) Income Mean Diff (I-J) S.E. Sig. 95% C.I. L.B. U.B. Estimated total amount spent on clothing category Under $20 000 $20,000-$39,999 -282.208 165.471 .613 -775.21 210.79 $40,000-$59,999 -185.615 154.701 .894 -646.53 275.30 $60,000-$79,999 -327.308 152.716 .332 -782.31 127.69 $80,000-$99,999 -307.986 155.941 .434 -772.59 156.62 $100,000-$149,999 -343.571 162.369 .347 -827.33 140.19 $150,000+ -175.238 263.131 .994 -959.21 608.73 $20,000-$39,999 under $20 000 282.208 165.471 .613 -210.79 775.21 $40,000-$59,999 96.593 98.843 .958 -197.90 391.08 $60,000-$79,999 -45.100 95.708 .999 -330.25 240.05 $80,000-$99,999 -25.778 100.774 1.000 -326.02 274.47 $100,000-$149,999 -61.364 110.460 .998 -390.47 267.74 $150,000+ 106.970 234.682 .999 -592.24 806.18 $40,000-$59,999 under $20 000 185.615 154.701 .894 -275.30 646.53 $20,000-$39,999 -96.593 98.843 .958 -391.08 197.90 $60,000-$79,999 -141.693 75.576 .499 -366.86 83.48 $80,000-$99,999 -122.371 81.898 .748 -366.37 121.63 $100,000-$149,999 -157.957 93.558 .625 -436.70 120.79 $150,000+ 10.377 227.217 1.000 -666.59 687.34 $60,000-$79,999 under $20 000 327.308 152.716 .332 -127.69 782.31 $20,000-$39,999 45.100 95.708 .999 -240.05 330.25 $40,000-$59,999 141.693 75.576 .499 -83.48 366.86 $80,000-$99,999 19.322 78.085 1.000 -213.32 251.97 $100,000-$149,999 -16.263 90.240 1.000 -285.12 252.59 $150,000+ 152.070 225.871 .994 -520.88 825.02 $80,000-$99,999 under $20 000 307.986 155.941 .434 -156.62 772.59 $20,000-$39,999 25.778 100.774 1.000 -274.47 326.02 $40,000-$59,999 122.371 81.898 .748 -121.63 366.37 $60,000-$79,999 -19.322 78.085 1.000 -251.97 213.32 $100,000-$149,999 -35.585 95.596 1.000 -320.40 249.23 $150,000+ 132.748 228.063 .997 -546.74 812.24 $100,000-$149,999 under $20 000 343.571 162.369 .347 -140.19 827.33 $20,000-$39,999 61.364 110.460 .998 -267.74 390.47 $40,000-$59,999 157.957 93.558 .625 -120.79 436.70 $60,000-$79,999 16.263 90.240 1.000 -252.59 285.12 $80,000-$99,999 35.585 95.596 1.000 -249.23 320.40 $150,000+ 168.333 232.506 .991 -524.39 861.06 $150,000+ under $20 000 175.238 263.131 .994 -608.73 959.21 $20,000-$39,999 -106.970 234.682 .999 -806.18 592.24 $40,000-$59,999 -10.377 227.217 1.000 -687.34 666.59 $60,000-$79,999 -152.070 225.871 .994 -825.02 520.88 $80,000-$99,999 -132.748 228.063 .997 -812.24 546.74 $100,000-$149,999 -168.333 232.506 .991 -861.06 524.39 Amount spent in this store as percentage of total amount spent on clothing category Under $20 000 $20,000-$39,999 -17.149 8.698 .436 -43.06 8.76 $40,000-$59,999 -28.807* 8.131 .009 -53.03 -4.58 $60,000-$79,999 -26.409* 8.027 .020 -50.32 -2.49 $80,000-$99,999 -23.700 8.197 .064 -48.12 .72 $100,000-$149,999 -25.363 8.535 .051 -50.79 .06 $150,000+ -25.952 13.831 .498 -67.16 15.25 $20,000-$39,999 under $20 000 17.149 8.698 .436 -8.76 43.06 $40,000-$59,999 -11.658 5.195 .277 -27.14 3.82 $60,000-$79,999 -9.259 5.031 .522 -24.25 5.73 $80,000-$99,999 -6.551 5.297 .879 -22.33 9.23 $100,000-$149,999 -8.213 5.806 .793 -25.51 9.09 $150,000+ -8.803 12.335 .992 -45.56 27.95 $40,000-$59,999 under $20 000 28.807* 8.131 .009 4.58 53.03 $20,000-$39,999 11.658 5.195 .277 -3.82 27.14 $60,000-$79,999 2.399 3.972 .997 -9.44 14.23 $80,000-$99,999 5.107 4.305 .899 -7.72 17.93 $100,000-$149,999 3.445 4.918 .992 -11.21 18.10 $150,000+ 2.855 11.943 1.000 -32.73 38.44 $60,000-$79,999 under $20 000 26.409* 8.027 .020 2.49 50.32 $20,000-$39,999 9.259 5.031 .522 -5.73 24.25 $40,000-$59,999 -2.399 3.972 .997 -14.23 9.44 $80,000-$99,999 2.708 4.104 .995 -9.52 14.94 $100,000-$149,999 1.046 4.743 1.000 -13.09 15.18 $150,000+ .456 11.872 1.000 -34.92 35.83 $80,000-$99,999 under $20 000 23.700 8.197 .064 -.72 48.12 $20,000-$39,999 6.551 5.297 .879 -9.23 22.33 $40,000-$59,999 -5.107 4.305 .899 -17.93 7.72 $60,000-$79,999 -2.708 4.104 .995 -14.94 9.52 $100,000-$149,999 -1.662 5.025 1.000 -16.63 13.31 $150,000+ -2.252 11.988 1.000 -37.97 33.46 $100,000-$149,999 under $20 000 25.363 8.535 .051 -.06 50.79 $20,000-$39,999 8.213 5.806 .793 -9.09 25.51 $40,000-$59,999 -3.445 4.918 .992 -18.10 11.21 $60,000-$79,999 -1.046 4.743 1.000 -15.18 13.09 $80,000-$99,999 1.662 5.025 1.000 -13.31 16.63 $150,000+ -.590 12.221 1.000 -37.00 35.82 $150,000+ under $20 000 25.952 13.831 .498 -15.25 67.16 $20,000-$39,999 8.803 12.335 .992 -27.95 45.56 $40,000-$59,999 -2.855 11.943 1.000 -38.44 32.73 $60,000-$79,999 -.456 11.872 1.000 -35.83 34.92 $80,000-$99,999 2.252 11.988 1.000 -33.46 37.97 $100,000-$149,999 .590 12.221 1.000 -35.82 37.00 *. The mean difference is significant at the 0.05 level. Read More