A STUDY TO ASSESS THE IMPACT OF FOOTFALLS AND CATEGORY MIX ON MALL PERFORMANCE STUDY TO ASSESS THE IMPACT OF FOOTFALLS AND CATEGORY MIX ON MALL PERFORMANCE.”

: Shopping centers have become a center of convergence providing an opportunity to shop, entertain, relax and socialize. The quantum of foot traffic to the mall indicates the preference of the customers to visit a specific mall as the customers believe that their interests will be best met there in terms of ambiance, shopping, facilities and convenience. Though, footfalls indicate preference but it does not anyway relate to actual conversions because there are many other parameters that influence their buying decision. On the other hand, presence of diverse categories inside the mall helps in their decision to buy as the customers want multiple engagements for his family besides shopping at one place. This study aims to find which impacts more footfalls or presence of category mix on the performance of the mall.


Introduction
Retail industry in India is expected to grow to US$ 950 billion by 2018, registering a compounded annual growth rate (CAGR) of 8.9 per cent during 2000-18. India's retail market is expected to double to US$ 1 trillion by 2020 from US$ 600 billion in 2015 driven by income growth, urbanization and attitudinal shifts. (Source: The Boston Consulting Group and Retailers Association of India's report titled, Retail 2020: Retrospect, Reinvent, Rewrite). While the overall retail market will grow at 12 per cent per annum, modern trade will grow twice as fast at 20 per cent per annum, and traditional trade at 10 per cent. (Source: The Boston Consulting Group and Retailers Association of India's report titled, 'Retail 2020: Retrospect, Reinvent, Rewrite and Retailers Association of India).
A shopping centre is an object which is centrally managed and comprises operations of at least 10 independent stores (tenants), the area (rented or useful space) allocated to them makes up at least 5 thousand sq. m., and the anchor tenant occupies up to 70 percent of the rented area (Source -International Council of Shopping Centers (ICSC), 2013).
information. Kumar & Arora, (2012) said that entertainment is an important element that the customer now-a-days expect to be in any good Mall as a basic category. This could be in the form of Multiplexes, Gaming zones, Kids Zone, large Food Courts etc where the entire family can come & enjoy. Anuradha & Manohar, (2011) said that customers see availability of entertainment facilities as a prime consideration for their decision to visit the Malls. Kaushal and Medhavi, (2011) said that the quality of service perceived by the customers at a center, irrespective of the brand is what ultimately results in a repeat visit of the customer. Burnaz & Topcu, (2011) found that scale of mall is important as it gives opportunity to place diverse product categories. Creation of additional footfalls to the mall is essential for generating revenues for the stores. Anchor brands are essential for sustainability and performance of malls. Chebat, Sirgy and Grzeskowiak, (2010) said that in order to generate higher footfalls in a mall a strong mall image is to be created that develops a strong positive perception among the shoppers to patronize the mall. Patney, (2010) observed that there are various motivators that influence shoppers to visit the shopping malls. Customers visit the malls to Socialize, for variety in Goods and Services, budget shopping, seek pleasure, to relax and enjoy. Reimers and Clulow, (2009) found that time convenience has a significant influence on consumers' patronage behavior. Rajagopal, (2009) said that mall ambience, assortment of stores, sales promotion and shopping satisfaction of the consumers help in improved retail performance, generate mall attractiveness and increased buying activities. Recreational activities provided in the Mall drives customers to the center and motivates to increase their time spends. Allard, Babin and Chebat, (2009) found that perceived differentiation from the competitors is found to positively influence customers' attachment to the mall, a determining factor in the mall's evaluation. De Nisco and Napolitano, (2006) highlighted that entertainment should be taken as strategic intent and have be synced into the traditional retail setting. There is a positive link between entertainment orientation and performance outcomes. Hunter, (2006) suggested that intention to visit a shopping centre directly impacts the frequency of visits to a shopping centre Hartet al., (2005) found that enjoyment during the shopping is an important component that brings the customer again and again to the shopping centre and this can be provided by placing recreational, leisure and entertainment facilities. These result in consumers spending more time inside the mall, increase their bill size and influence them to recommend the shopping centre to others. Sit et al., (2005) observed that the presence of entertainment segment in the shopping mall helps in consumer satisfaction and is an important driver of the shoppers to the Mall. Melody et al, (2000) stated that high performing malls are those that are located in the high trading areas. High mall productivity relates to the trade area characteristics and the size of the mall. Swinyard, (1998) said that frequent mall shoppers have higher needs for 'sense of belonging', 'warm relationships', 'entertainment 'and 'security' then casual shoppers. Kaufman, (1996) found that shoppers normally patronize a mall where they get onestop shopping for all their needs that can be provided by extended hours of operation, drive through services and providing multiple check outs for customer convenience. Bean, et al., (1988) suggested that the types, sizes, and locations of the smaller tenants play an important role in determining the financial success of any shopping center.

Research Methodology
A descriptive study was undertaken and stratified sampling technique was used to select the samples across categories on random basis. The entire universe of shopping malls in Jaipur was  [25] studied which was eleven (11) in numbers. The gross leasable area (GLA) of the shopping malls was approximately between 1 Lac sq ft to 13 Lac sq ft and the malls were dispersed across all the corners of the city. The catchment of the malls was mid-to-high income group of residential colonies and areas with commercial activities. These malls were situated within the city limits thus have good reach, accessibility and approach for the customers. Total samples selected for the study was 105.

Limitations of the Study
This study was carried out in Jaipur and samples were drawn from the respondents in the malls based out of the city only. Thus the findings of the data may not be considered universally applicable to other cities as well. This study may encourage examining the phenomenon in other cities also to gauge the impact of the two variablesfootfalls and presence of category mix on the performance of the mall.

Descriptive Statistics
The findings regarding the mean and standard deviations of the scores on responses of respondents are presented in below table.

Validity of Data
However, before carrying out hypotheses testing, the overall significance of the correlation matrix and its factorability needed to be tested with the help of Bartlett's test of sphericity and Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy.

Reliability of Data
From the above table we can see that Cronbach's alpha is more than 0.700 which indicates a high level of internal consistency for our scale with this specific sample. In the conceptual framework (figure), footfall and category mix factors influence sales both directly and incidentally. The framework shows that mall productivity is predicted through sales of mall in terms of footfall and category mix.  The above table and figure revealed that there is a statistically significant relationship between Footfall and Sales of Mall. It has found that Pearson correlation 'r' value 0.799 and sig value (p value) is 0.000 which indicates that there is a statistically significant strong positive correlation between footfall and sales of mall. The "R" column represents the value of R, the multiple correlation coefficients. R can be considered to be one measure of the quality of the prediction of the dependent variable. The "R Square" column represents the R 2 value, which is the proportion of variance in the dependent variable that can be explained by the independent variables.
In the Model Summary in above table, R Square is 0.638 which means that Footfall explain 63.8% of the variability with significant effect on Sales of mall.
Above table shows the multiple linear regression model summary and overall fit statistics. It has found that R² of our model is0.638. This means that the linear regression explains 63.8%of the variance in the data. The Durbin-Watson value is1.724, which is between the two critical values of 1.5 < d < 2.5. Therefore, we can assume that there is no first order linear auto-correlation in our multiple linear regression data. The F-ratio in the ANOVA table tests whether the overall regression model is a good fit for the data. The table shows that different footfall (independent variables) statistically significantly predict the sales (dependent variable). In the above table F sig. value is less than 0.05, which means the regression model is a good fit of the data. The F-test is highly significant, thus we can assume that the model explains a significant amount of the variance in sales of mall. Unstandardized coefficients indicate how much the dependent variable varies with an independent variable. From the above table it shows that footfall is significant predictor as a sig. value is less than 0.05 indicate that null hypothesis is rejected. In other words it can say that there is a statistically significant impact of footfall on sales of mall. The above table and figure revealed that there is a no statistically significant relationship between Category Mix and Sales of Mall. It has found that Pearson correlation 'r' value 0.226 and sig value (p value) is 0.530 which indicates that there is a no statistically significant low positive correlation between category mix and sales of mall.  The "R" column represents the value of R, the multiple correlation coefficients. R can be considered to be one measure of the quality of the prediction of the dependent variable. The "R Square" column represents the R 2 value, which is the proportion of variance in the dependent variable that can be explained by the independent variables.
In the Model Summary in above table, R Square is 0.051 which means that category mix explain 5.1% of the variability with significant effect on Sales of mall.
Above table shows the multiple linear regression model summary and overall fit statistics. It has found that R² of our model is0.051. This means that the linear regression explains 5.1%of the variance in the data. The Durbin-Watson value is1.58, which is between the two critical values of 1.5 < d < 2.5. Therefore, we can assume that there is no first order linear auto-correlation in our multiple linear regression data. The F-ratio in the ANOVA table tests whether the overall regression model is a good fit for the data. The table shows that different category mix (independent variables) do not predicts the sales (dependent variable). In the above table F sig. value is more than 0.05, which means the regression model is not good fit of the data. Unstandardized coefficients indicate how much the dependent variable varies with an independent variable. From the above table it shows that category mix is not significant predictors as a sig. value is more than 0.05 indicate that null hypothesis is accepted. In other words it can say that there is no statistically significant impact of category mix on sales of mall.

Conclusion
The study helped to conclude that footfalls to the mall have a significant impact on the mall performance as more the customers visiting a property more will the probability of conversion to sales. However, this doesn't mean higher actual conversions to sales. In the city of Jaipur where the study was carried out, it was seen that the footfall impact on sales was significant implying that those malls with low footfalls are delivering low sales per sq ft whereas malls with higher footfalls have comparatively better sales per sq ft. Thus, the effort of the mall management team should be to make the malls as destinations focusing on experiential retailing incorporating motivators giving customers all the reasons for more visits and patronize. On the other hand, the diversity of category mix ensures that customer gets choice of their brands, provide them variety in shopping, give them options of entertainment, gaming, F & B, cinema so that they can bring their entire family for spending quality time. However, its direct impact on mall performance is not seen. All the malls studied were having almost similar category mix but the sales per sq ft were different implying thereby that category mix doesn't have significant impact on the performance of the mall.