Factors that Influence Customer Purchase Intention: A Case of Shopping Mall Customers

Customer purchase depends on various factors including the context where the purchase takes place. Customer purchase through online platforms differs greatly from customer purchase that takes place at physical premises. Even at the physical premises, the extent of purchase might vary depending on the products offered, the environment, the value received by customers and the price charged by the retailers. The present study is important to identify factors that lead to customer purchase intention by looking at selected factors consisting of products offered, the environment, the value received by customers and the price charged. These factors are hypothesized to influence customer satisfaction that will subsequently lead to purchase intention. This study used correlational research design to answer the research question. Using a hierarchical regression analysis to analyze 157 responses collected via online survey from customers at a particular mall in Malaysia, the findings indicate that price and product offerings are directly related to purchase intention and customer satisfaction does not mediate the relationship between these factors and purchase intention. The findings contribute to the existing body knowledge in terms of the factors the influence purchase intention among customers of a shopping mall. Future studies are encouraged to confirm the findings of the present study using different study settings.


Introduction
Going to shopping malls during the weekends has become a common phenomenon. But this activity does not apply to all shopping malls since customers are becoming more choosy in deciding where they should spend their time together with their family members during the weekends. It is evident when some shopping malls are so crowded but some others are not able to attract customers to their premises. There must be explanations for this scenario. Therefore, this study was carried out to investigate the factors that lead customers to purchase products at certain shopping malls.
Customers have various options when engaging in purchase behavior (Isa et al., 2020;Mumin, & Grace, 2021). They can choose to purchase their desired products via online platforms or perform conventional purchasing activities by visiting the retailers' physical premises (Mumin, & Grace, 2021). For the second option, customers can decide to go to smaller retail outlets or visit a shopping mall where there are many retail outlets pooled together at one big location. A variety of products are offered at this shopping location with different price tags. This paper will discuss the important factors that will influence customer purchase decision.
The first important factor is product offerings. At shopping malls, many retailers are offering a variety of products ranging from electronic devices to clothes and daily necessities. Therefore, shopping malls can be regarded as a one-stop center for those who want to purchase many items simultaneously. Studies have shown that customers are satisfied with their shopping experience when they can find what they want during the visit and their satisfaction will lead to purchase intention (Watanabe et al., 2019). Satisfied customers will return as evidenced in many previous studies (Phan et al., 2021).
The second factor that is worth to consider is price. Most customers prefer to shop when there are sales promotion, especially during festive seasons, and during the weekends (Vranceanu et al., 2020). Retailers have use this strategy effectively to attract customers to their shops. The strategy includes discounts, free gifts, vouchers, and others that they think will lure customers to purchase their products (Kaveh et al., 2021). Studies have shown that sales promotion will lead to purchase intention, regardless of the types of sales promotion (Mkedder et al., 2021;Rachmawati et al., 2019;Xiao et al., 2019).
The next factor is value of the product purchased. Previous researchers have linked value with price of product purchased. High priced products are perceived to have high value. Conversely, low priced products are perceived to carry low value (Salem, & Chaichi, 2018). Since shopping malls offer a variety of products with various price tag, customers have options to choose products that they prefer. Previous studies have proven that the product value will lead to customer satisfaction and subsequently will affect their purchase intention (Anwer et al., 2020;Fernandes & Barfknecht, 2020;Yusof et al., 2021;Peng, & Chen, 2019).
Another factor that should be included in the discussion is servicescape that refers to the elements of the service environment including ambiance, layout, temperature, background music and other environmental factors. Customers prefer the shopping environment to be conducive so that they can make purchase decision without much interruptions. Studies have established the link between servicescape and customer satisfaction, simultaneously will lead to purchase intention (Ali et al., 2021;Mukherjee et al., 2021;Upadhyaya et al., 2018).
With regard to the relationship between customer satisfaction and purchase intention, there is a positive linear relationship between the two constructs. Higher satisfaction will lead to higher purchase intention. In the context of shopping mall, customers who are satisfied with their shopping experience will surely engage in purchase behaviour. This claim is supported by previous studies (Phan, et al., 2021;Vasquez & Vera-Martinez, 2020). However, another study found that satisfaction is not a factor of purchase intention (Garcia & Curras-Perez, 2020). These inconsistent findings open up an avenue for further studies in this area.
The influence of these four factors on customer satisfaction and purchase intention of customers in the context of the shopping mall need to be tested since limited studies have been conducted in this area. The findings are useful to the retailers and mall management to devise the right strategies to attract customers to their premises.

Methodology
This study falls under the category of quantitative study and sub-category of correlational research design since it is meant to test the moderating role of customer satisfaction on the relationship between certain pertinent factors and customer purchase intention. The research instrument was developed by adopting and adapting the existing established items from previous studies that were used to measure the intended variables. The instrument was validated by the two experts from the marketing field at the Faculty of Business and Management, UiTM Malaysia.
The questionnaire was distributed via online platform (Google Form) to customers who recently visited shopping malls in the area of Klang Valley since many popular shopping malls are located in this area. Online data have become the new norm in research (Rahmi et al., 2020) especially during the pandemic era. A screening item was included in the questionnaire to ensure that only the right respondents participate in the survey. Whats-apps groups were utilized to get the expected number of responses. A snowballing technique was used by asking the respondents to forward the survey questionnaire to their friends and relatives who have visited shopping malls recently (within the period of one month).
After the lapse of two weeks, a total of 157 responses were received. This number is sufficient to test the assumptions made earlier regarding the associations among the variables. Factor analysis and reliability analysis were performed to ensure that the data are valid and reliable to be used in this study. Using multiple regression analysis, the factors that influenced purchase intention was confirmed. In addition, the mediating role of customer satisfaction was tested using the a series of multiple regression analysis.

Data Analysis and Findings
Descriptive analysis was performed to examine the distribution of data of the study. As shown in Table 1, male and female respondents were quite fairly represented with 76 males and 81 females. With regard to age distribution, majority of respondents or 69 respondents aged between 29 and 38 years old, followed by those aged between 39 and 48 years old, which is represented by 36 respondents. From 157 respondents, majority of them or 114 respondents (72.6%) were married. It shows that those visit the shopping malls are married and shop together with their family members.
Regarding their monthly income, most customers received monthly salary less than RM3,000.00. A total of 45 respondents received between RM3,000.00 and RM5,000.00. The next group refers to those who received between RM5,000.00 and RM7,000.00 which is represented by 28 individuals. They said that their income levels remain the same during the COVID-19 pandemic. Looking into their education levels, majority of respondents or 81 individuals had bachelor degree while 44 respondents had diploma as their highest education level obtained.
Pertaining to the employment sector the respondents were affiliated with, majority of them or 72 respondents worked in the private sector, while 32 respondents worked in the government agencies. A total of 27 respondents were self-employed while 17 respondents were students studying in the nearby higher learning institutions. These statistics show that customers who are the frequent visitors of the shopping mall are categorized in low and middle income groups. This information is useful for the shopping mall retailers and management to develop the right strategies to attract them. A series of factor analysis was performed to examine the dimensionality of items measuring the variables involved in the study. The first factor analysis was performed for the items used to measure purchase intention (the results are shown in Table 2). A principal factor analysis with varimax rotation was used. The KMO value of .833 indicates that the correlation matrix is sufficient for factor analysis to be conducted. It is supported with the MSA values that range from .774 to .880 that show that the correlation is adequate for each item. A total of five items were tested and the result of factor analysis indicates the existence of a single factor to measure purchase intention. The second factor analysis was performed on three items measuring customer satisfaction. The KMO value of .693 is above the above the threshold value of .6 indicating that the correlation matrix is sufficient to proceed with factor analysis. The MSA values ranging from .623 to .900 support the suitability of factor analysis. The variance explained in the model is 88%, which is higher that the minimum value of 60%. Correlation analysis was used to test the convergent and concurrent validity of the variables. As shown in Table 5, factors measuring the independent variables have moderate to high correlations, indicating a convergent validity of the independent variables. The lowest correlation is found between value and servicescape (r=.564; p<.01) whereas the highest correlation is discovered between value and product offerings (r=.830; p<.01).
The concurrent validity can be established by examining the relationship between the independent variables and the dependent variable as well as the mediating variables. All independent variables show low to moderate correlations with the mediating variable. The lowest correlation is found between servicescape and customer satisfaction (r=.289; p<.01) and the highest correlation is between value and customer satisfaction (r=.512; p<.01).
For the relationship between all other variables and the dependent variable, the lowest correlation is between customer satisfaction and purchase intention (r=.484; p<.01) while the highest correlation is between product offerings and purchase intention (r=.886; p<.01). The results also show the potential mediating effect of customer satisfaction on the relationship between the independent variables and purchase intention among customers of a shopping mall.
Reliability analysis was also performed on the items measuring each factor and the results are also presented in Table 5 (in the parentheses along the diagonal). The results show that all items are highly reliable to measure each of their intended constructs with the lowest Cronbach's alpha of .920 for servicescape and the highest Cronbach's alpha of .957 for value. Since all the preliminary tests show that the data are good for analysis, the subsequent analysis that is multiple regression analysis was carried out. .560 ** .767 ** .886 ** .818 ** .484 ** (.955) Notes: **. Correlation is significant at the 0.01 level (1-tailed); N=157; Cronbach's alphas are along the diagonal in the parentheses.
The subsequent analysis that is a multiple regression analysis is meant to confirm the influence of the four independent variables on customer satisfaction (the mediating variable). This is to establish the first path out of the three required paths when testing the mediating effect of a variable (refer Baron & Kenny, 1986). From the summary of the regression model, the R 2 of .274 indicates that 27.4% of the variance in the model is explained by the four independent variables. This indicates that more factors should be considered when assessing customer satisfaction in the context of shopping mall customers. The regression model is significant (F(4,141)=13.312; p<.01). Table 6 shows that only value is a significant predictor of customer satisfaction (β=.377; p<.05). The other three independent variables are not significant. It shows that customers prefer value of the product purchased over other factors when visiting shopping malls. The finding is consistent with that of prior studies (Anwer et al., 2020;Fernandes & Barfknecht, 2020;Yusof, et al., 2021;Peng & Chen, 2019). Since shopping malls gather many retailers at a location, it is easier for customers to compare the products and to choose the product the gives the highest value for their money. This will lead to their satisfaction when visiting shopping malls.
Servicescape, product offerings and price of products are something that do not excite them since these factors are considered as the "must have" features of the shopping malls. Although servicescape is a unique feature of a shopping mall but customers do not regard it as an important factor that determines their satisfaction and purchase intention. Servicescape (e.g. background music) can generate both positive and negative emotions. Previous study found that only positive emotions will affect purchase intention (Hsu et al., 2021). Similarly, product offerings and price are not the predictor of satisfaction because too many products offered with different price tags might create confusion to customers. As highlighted by Demirgunes (2018) that shopping hesitation has a positive relationship with price/value consciousness, risk averseness, confused by overchoice and time pressure. The next step is to test the mediation effect of customer satisfaction on the relationship between the independent variables and purchase intention. A 2-step hierarchical regression analysis was performed. In the first step, the independent variables and the dependent variable were entered into the regression equation. Next, the mediator was entered into the equation. The results are shown in Table 7.
Looking at the direct relationship between the independent variables and purchase intention, two factors are found to be significant predictors. They are price (β=.127; p<.01) and product offerings (β=.834; p<.01). Servicescape and value are not significant to influence purchase intention. Customer purchase intention when visiting shopping malls is determined by price of products and product offerings. At shopping malls, a variety of products can be found and the price ranges from very low to very high. It is up to customers to choose. Servicescape and value, on the other hand, are hard to be quantified and might not influence customers to purchase especially in the context of a shopping mall. As found by Demoulin and Willems (2019) that poorly managed social servicescape factors are the most irritating, and customers' irritation in turn decreases satisfaction, particularly in high-involvement settings.
Examining the mediating effect of customer satisfaction on the relationship between the four independent variables and purchase intention, the third step applies (Baron & Kenny, 1986). To show a significant mediation effect, the inclusion of the mediator should significantly reduce the Beta value of the significant independent variables in the previous regression model (customer satisfaction served as the dependent variable). In this study, the Beta values of the independent variable was not significantly reduced and the mediator was not significant. Therefore, it can be concluded that customer satisfaction did not mediate the relationship between all four independent variables and purchase intention. The finding is similar with the one found by (Ilyas et al., 2020;Garcia and Curras-Perez, 2020).
It can be summed up that when examining customer purchase intention during the shopping mall visit, two factors are important to consider, which are product offerings and price. The other two factors are not significant to influence their purchase intention. However, to satisfy customers, the product value plays a significant role since customers are happy when they can optimize the return on their investment. Nevertheless, customer satisfaction does not lead to purchase intention. There are two things that need to be considered by the retailers and the shopping mall management; first, to satisfy customers; second, to make them purchase during their visit.

Conclusion
Customer purchase intention has been researched extensively since the last few decades. Still, it continues to attract the attention of marketing researchers due to the occurrence of various events including the recent phenomenon of the COVID-19 pandemic. During the pandemic, public are allowed to visit retail outlets and shopping malls only to purchase necessities. Most customers prefer to shop at shopping malls from other retail outlets. This phenomenon creates a question of why they choose to shop at shopping malls. The present study was intended to identify factors that lead to customer purchase intention by looking at certain predictors comprising products offered, the environment or servicescape, the value received by customers and the price charged. A hierarchical regression analysis was performed to analyze 157 data collected via online survey from customers and the findings established that value is a significant predictor of customer satisfaction while price and product offerings are the significant factors of purchase intention. However, customer satisfaction does not mediate the relationship between these factors and purchase intention. These findings enrich the existing knowledge on customer purchase intention especially in the context of shopping malls. Retailers and shopping mall management can develop the right strategies based on the findings to attract customers to visit their shopping malls.