Purchase Intention from Social Media Platform under the Integration of Money Attitude, Conformity and Price Sensitivity ()
1. Introduction
The rapid advancement of technology and internet connectivity has sped up and made it easier for the shift from traditional shopping to online shopping. In the new market environment known as electronic commerce (e-commerce), online shopping has become possible on many different platforms. As a result, online shopping has become a part of social life with the rapidly increasing use of the internet and mobile devices. Social media platforms have gained popularity as effective channels for social commerce because of their extensive user base and tools that make it easier to discover, share, and buy products. Social commerce is a branch of e-commerce that improves online business operations and transactions while promoting positive interactions between companies and a wide range of customers, even those in distant locations (Park & Kim, 2014; Pouti et al., 2020). Social commerce is an emerging trend that has transformed the online shopping experience by enabling online retailers to build long-term relationships with customers and increase sales (Dhaigude & Mohan, 2023). Social commerce customers seek an informative, transparent and engaging shopping experience at the best price (Yahia et al., 2018). In contemporary e-commerce practices, social media serves a crucial function in generating value for consumers. The COVID-19 pandemic caused a great deal of change in how businesses operate and think. Social media is viewed as a tool for facilitating communication mechanisms and drawing individuals together through sharing content.
Various studies have used user participation and purchase intention to measure social commerce intention (Liang & Turban, 2011; Hajli, 2015; Wu & Horng, 2022; Zhou et al., 2023). Platform users’ perceptions are directly related to online shoppers’ experiences and perceptions, trust and other related issues (Wang et al., 2012). the effect of behavioural Studies in different fields in the literature have revealed the effect of behavioural intention on usage behaviour (Pavlou & Fygenson, 2006; Venkatesh et al., 2012; Jeyaraj et al., 2022).
Previous research had focused on external factors, such as the ease of use and design of the website/application interface, and the comparison of differences between shopping websites/application. There has been little research on products on social platforms based on consumer internal factors. Internal factors such as consumers’ money attitude, conformity, and price sensitivity are also important factors that determine consumer purchases. Therefore, the study refers to previous scholars’ discussions on applying relevant literature to consumption on social platforms. Cambodia is a developing country, with about 80% of the population under the age of 65. In addition, digital technology is developing rapidly, and many people purchase goods through social platforms. This is an issue worth discussing.
2. Literature Review and Hypothesis
2.1. Money Attitude
Money are authority and source of influence symbol, which makes people tendent to material life (Lemrová et al., 2014; Taneja, 2012). Person gives different meanings of money, so their money attitudes are different. Attitudes towards money affect people’s life areas, such as saving, spending habits, work performances, political actions (Roberts & Sepulveda, 1982; Phau & Woo, 2008). Money attitude includes money cognition, money affection and money action (Li & Zhang, 2002; Zhou & Pham, 2004). 1) Money cognition :it refers to an individual’s personal understanding and beliefs about money, including their convictions, judgments, and perspectives on money-related matters. 2) Money affection: it involves emotional responses to money, such as feelings of love, anger, sadness, and happiness towards money-related things. 3) Money action: it refers to the inclination towards certain actions related to money, reflecting the individual’s intentions, mental state, and efforts to satisfy wants or needs. Overall, money attitude is defined as a consistent and enduring behavioral tendency towards money-related matters. Prior Scholars developed money attitude scales such as the Money Attitude Scale (MAS) was created by identifying four key factors: 1) power-prestige, where money is seen as a symbol of success and the ability to influence others; 2) retention-time, which involves money behaviors that involve planning and preparing for the future; 3) distrust, which refers to feeling uneasy about spending money; and 4) anxiety, where money is associated with feelings of insecurity and anxiety about finances (Yamauchi & Templer, 1982). The Money Beliefs and Behavior Scale (MBBS) identified six distinct factors: 1) obsession with money: being fixated on money, 2) power/spending: viewing money as a representation of power, 3) retention: focusing on managing money, 4) security/conservative attitude: using money cautiously for security, 5) inadequacy: worrying about not having enough money, and 6) effort/ability: seeing money as a reflection of personal effort and skill (Furnham, 1984). The Money Ethic Scale (MES) was used to analyze the perceptions of money among a group of full-time workers in the United States. Six key factors were discovered: (1) Good: money is seen as good, valuable, and appealing, 2) Evil: money is considered evil, shameful, and unimportant, 3) achievement: money symbolizes one’s accomplishments in society, 4) respect/esteem: money earns individuals respect from others, 5) freedom-power: money provides personal freedom and influence, and 6) budgeting: individual manage their money through budgeting (Tang, 1992). The power-prestige, distrust and anxiety dimensions of money attitude were found closely to be associated with buying behavior as well as credit card usage moderates these relationships (Roberts & Jones, 2001). It suggested that money attitudes toward power and price sensitivity affect buying behavior (Khare, 2016). Money related anxiety increases compulsive buying. Price sensitivity (distrust) decreases buying (Eroğlu & Kocatürk, 2020).
H1: Power-prestige of money attitude has a positive impact on purchase intention.
H2: Retention-time of money attitude has a positive impact on purchase intention.
H3: Distrust of money attitude has a positive impact on purchase intention.
H4: Anxiety of money attitude has a positive impact on purchase intention.
2.2. Conformity
Consumer conformity is formed from the relationship between social interactions and consumer purchasing decisions for products and services. Conformity can be described as the act of adjusting one’s thoughts and choices to match those of the majority within a group (Allen, 1965). Consumer conformity classifies people into two groups, namely the conformity group and the non-conformity group. The conformity group is further classified into two groups, namely normative conformity and informational conformity. Lascu and Zinkhan (1999) theorized the concept and built a conformity model that provided a framework explaining how an individual conforms to group norms to meet the group’s expectations in consumer behavior. Conformity is the result of two primary factors: normative influence, where an individual aligns their behavior with that of a group in order to gain acceptance and approval, and informational influence, which describes how individuals make decisions based on observing others when they lack sufficient information for independent judgment (Deutsch & Gerard, 1955). Baron, Branscombe & Byrne (2008), explain that conformity is also a type of social influence in which individuals change attitudes or behaviors to comply with existing social norms. Sarwono & Meinarno (2013), conformity occurs when a number of people in a group say or do something, causing a tendency for members to say and do the same thing. The model of conforming behavior includes four characteristics (individual characteristics, group characteristics, brand characteristics, task/situation characteristics), two types of norms (extreme, moderate), and two major categories (informational influence, normative influence) (Lascu & Zinkhan, 1999). Conformity has two aspects: informational influence and normative influence. First, informational influence means that individuals tend to align themselves with a certain group because of the influence of information conveyed by the group and the individual beliefs in that group based on their assessment. It can be stated that the views and information from trusted groups help individuals adjust to those groups, leading to the development of conforming behavior. The second component of conformity is normative influence, which refers to an individual’s attempt to alter their perceptions, beliefs, attitudes, and behaviors in order to gain acceptance from specific groups or, in other words, to avoid being excluded. This also causes individuals to take actions that are by the group’s expectations of them. Normative conformity involves individuals adapting their behavior to align with the choices of others in order to gain acceptance or approval from a specific individual or group. In contrast, informational conformity refers to the adjustment of one’s behavior based on relevant information received about the choices made by others. Consumer conformity arises from the connection between social interactions and the choices consumers make when buying products and services (Princes et al., 2020). Park & Yang (2010) found that celebrity conformity has a positive effect on purchase intention. Both normative and informational conformity have been demonstrated to positively influence consumer attitudes, thereby also positively impacting purchase intentions (Khandelwal et al., 2018).
H5: Normative influence of conformity has a positive impact on purchase intention.
H6: Informational influence of conformity has a positive impact on purchase intention.
2.3. Price Sensitivity
Consumers’ price sensitivity refers to the extent to which consumers respond to variations in the price of a product or service. It assesses the extent to which fluctuations in price affect consumer purchasing behavior (Dominique-Ferreira et al., 2016). Uslu & Huseynli (2018) define price sensitivity in another perspective, which price sensitivity is one of the personalities that would influences individual’s purchasing behavior. The researchers found that personality traits significantly influence price sensitivity, suggesting that individuals’ inherent tendencies towards cost-consciousness directly impact purchasing decisions when faced with price fluctuations. Price is considered as a prime factor in consumer’s evaluation of purchase decisions and it is termed as sum total of money the firm charges its customers with the addition of profitability margin in producing specific goods or services (Wang et al., 2020). Consumers who exhibit price sensitivity tend to prioritize lower prices and are less inclined to make purchases when prices increase. In contrast, consumers who are less sensitive to price fluctuations demonstrate a greater willingness to pay elevated prices for the same products and are more likely to continue purchasing even in the face of price increases (Foxall & James, 2003; Shimp, Dunn, & Klein, 2004). Previous research examined price sensitivity as moderating effect on purchase intention. Honkanen et al. (2012) support that price sensitivity influences significantly their positive attitudes and intentions to purchase products. Specifically, when price sensitivity is diminished, the correlation between positive attitudes and purchase intentions becomes more pronounced. In essence, consumers who exhibit lower price sensitivity are more readily swayed by favorable attitudes, thereby increasing the likelihood of their purchasing decisions. Congruence between brand characteristics and consumer’s personal traits plays a crucial role in consumer purchase intentions (Akbar et al., 2023).
H7: Price sensitivity has a positive impact on purchase intention.
3. Research Methodology
3.1. Research Setting
To gain insight into the usage intentions of the social media platform to purchase, this study conducted a qualitative interview method and combined it with relevant literature and expert opinion to develop the questionnaire. After accessing the pre-test, collecting samples and revising the questionnaire, this study used confirmatory factor analysis (CFA) to examine the measurements’ reliability and validity. Regression analysis approach and the SPSS 22.0 software were employed to verify the coefficients and hypotheses to meet the expectations (Figure 1).
3.2. Data Collection and Sampling
This study has targeted the usage intentions of the social media platform to purchase due to the study objective. The participation of the respondents was voluntary and they were treated as politely to fill the questionnaire. All the participants ever bought things on the social media platform. The questionnaire items were identified and designed based on literature reviews, and then modified to make them appropriate for assessing Cambodia consumers’ money attitude, conformity and Price sensitive for using social media platform (Items were measured using a 5-point Likert-type scale (1 = strongly disagree, 5 = strongly agree). The survey was held in Phnom Penh Cambodia. The data were collected over a period of one month. In Cambodia, there are around 18,000 thousand people in 2024. Under the 90% of CI and 3% of statistical error, the sample sizes are at least over 271. In total, 300 questionnaires were administered in the Phnom Penh province of Cambodia (250 questionnaires issued at facing to face, 50 questionnaires in internet) with 283 valid questionnaires returned, indicating 94% return rate. Results of the study are presented on the basis of a frequency distribution, factor and reliability analysis, ANOVA and regression analysis using SPSS (Norusis, 1999).
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Figure 1. Research framework development (The research summarizes).
4. Result
4.1. Respondent Sample
Of the 283 valid respondents who returned the questionnaires, 37.1% were male and 62.9 percent female. About 56.2% of the respondents were between 21 and 30 years old. According to the results, 70.7% of the respondents have salaries under USD$ 800 dollars per month. Moreover, an analysis of the questionnaire revealed that most participants use social media platform to purchase less than 3 years and less than 15% of their salary to spend in the social media platform each month. Cloth, accessories (glasses, watch, earrings, wristband) and cellphone items are the most to purchase on it. The most social media platform usage are Taobo, Facebook, Instagram, and e-gets.
4.2. Validity and Reliability Analysis
Principal-component factor analysis was conducted to identify underlying constructs from sets of interrelated items. Factors were extracted and interpreted using varimax rotation method. Table 1 shows the factor analysis and reliability analysis of MAS items (Yamauchi & Templer, 1982), including Power-Prestige (PP), Retention-Time (RT), Distrust (DIS), and Anxiety (ANX). In Table 1, all factor loadings of variables exceeded 0.5, while Cronbach’s α values exceeded 0.7. Table 2 shows the factor analysis and reliability analysis of conformity (Bearden et al., 1989). Factors such as Information influence (II) and Normative influence (NI) were produced using factor analysis. All factor loadings of variables exceeded 0.5, while the Cronbach’s α values exceeded 0.6. Table 3 shows the factor analysis and reliability analysis of price sensitivity (PS) (Afendi, 2023) and purchase intention (PI) (Bian et al., 2012). All factor loadings of variables exceeded 0.5, while the Cronbach’s α values exceeded 0.8. The four factors of MAS, two factors of conformity and price sensitivity appeared to be appropriate for the next statistical analysis.
Table 1. The reliability and factor analysis of MAS (The research summarizes).
|
Factor analysis |
Reliability |
Eigenvalue |
Factor loading |
Cronbach’s α |
Power-Prestige (PP) |
|
|
|
I use money to influence other people to do things for me. |
2.35 |
0.53 |
0.71 |
I purchase things because I know they will impress others. |
0.63 |
People that know me tell me that I place too much emphasis on the amount of money. |
0.77 |
I tend to judge people by their money rather than their deeds. |
0.78 |
I try to find out if other people make more money than I do. |
0.69 |
Retention-Time (RT) |
|
|
|
I do financial planning for the future. |
4.15 |
0.77 |
0.88 |
I put money aside on a regular basis for the future. |
0.83 |
I save now to prepare for my old age. |
0.82 |
I keep track of my money. |
0.78 |
I follow a careful financial budget. |
0.79 |
I am very prudent with money. |
0.68 |
I have money available in the event of another economic depression. |
0.69 |
Distrust (DIS) |
|
|
|
It’s hard for me to pass up a bargain. |
1.353 |
0.56 |
0.72 |
I show signs of nervousness when I don’t have enough money. |
0.70 |
I show worrisome behavior when it comes to money. |
0.74 |
Anxiety (ANX) |
|
|
|
I complain about the cost of things what I buy. |
3.83 |
0.84 |
0.89 |
It bothers me when I discover I could have gotten something for less elsewhere. |
0.82 |
After buying something, I wonder if I could have gotten the same for less elsewhere. |
3.83 |
0.81 |
|
It automatically say, “I can’t afford it”, whether I can or not. |
0.80 |
I worry about not being financially secure. |
0.82 |
When I make a major purchase, I have a suspicion that I have been taken advantage of. |
0.67 |
Table 2. The reliability and factor analysis of conformity (The research summarizes).
|
Factor analysis |
Reliability |
Eigenvalue |
Factor
loading |
Cronbach’s α |
Information influence |
|
|
|
I rarely purchase the new products until I am sure my friends approve of them. |
3.88 |
0.83 |
0.83 |
It is important that others like the products and brands buy. |
0.87 |
When buying products, I generally purchase those brands that I think others will approve of. |
0.92 |
I like to know what brands and products make good impressions on others. |
0.88 |
I achieve a sense of belonging by purchase the same product and others purchase. |
0.90 |
Normative influence |
|
|
|
To make sure I buy the right product or brand I often observe what others are buying and using. |
1.78 |
0.58 |
0.64 |
If I have little experience with a product, I often ask my friends about the product. |
0.86 |
I often consult other people to help choose the best alternative available from a product class. |
0.85 |
Table 3. The reliability and factor analysis of price sensitivity and purchase intention (The research summarizes).
|
Factor analysis |
Reliability |
Eigenvalue |
Factor loading |
Cronbach’s α |
Price sensitivity |
|
|
|
I bought things /services on a special discount in social media platform/website. |
2.90 |
0.74 |
0.81 |
I am more likely to purchase things/services when there is a promotion in social media platform/website. |
0.68 |
The price difference between actual store and in social media platform/website significantly impacts my purchasing decisions. |
0.87 |
It is acceptable to buy things/services in social media platform/website. |
0.83 |
I am willing to buy things/services in social media platform/website. |
0.66 |
Purchase intention |
|
|
|
I will recommend others to buy products from social media platform/website |
1.72 |
0.93 |
0.84 |
If I were go shopping in actual store, I would still purchase from social media platform/website. |
0.93 |
4.3. Multiple Linear Regression Analysis
To verify the research framework and hypotheses, this study used SPSS statistic software to test multiple regressions. Multiple regressions was conducted to determine the extent to which the independent variables affect the dependent variable is a free .Variable PP, RE, DIS, ANX, II, NI and PS. Thus, multiple linear regression analysis showed the PP, RE, DIS, ANX, II, NI and PS. to the PI. Multiple linear regression equation is as follows:
Information:
Y = User intention (PI);
X1 = PP,
= regression coefficient of PP;
X2 = RE,
= regression coefficient of RE;
X3 = DIS,
= regression coefficient of DIS;
X4 =ANX,
= regression coefficient of ANX;
X5 = II,
= regression coefficient of II;
X6 = NI,
= regression coefficient of NI;
X7 = PS,
= regression coefficient of PS;
= Residual.
Table 4 shows the value of tolerance and variation inflation factor (VIF) value for intention to use banking application towards PP, RE, DIS, ANX, II, NI and PS. The result shows that there is no multicollinearity exists in the model since all the tolerance value is greater than 0.1 and VIF value is less than 10 respectively.
Table 4. Result of collinearity statistics (The research summarizes).
Variable |
VIF |
Tolerance |
PP |
2.539 |
0.394 |
RE |
2.643 |
0.378 |
DIS |
1.369 |
0.731 |
ANX |
2.580 |
0.388 |
II |
2.750 |
0.364 |
NI |
3.110 |
0.322 |
PS |
3.262 |
0.307 |
After all the assumptions have been fulfilled, the multiple linear regression analysis was performed. The regression analysis yielded a multiple correlation coefficient (R) of 0.857 which means that there was strong relationship between the mean score of PI and the seven of predictor variables (PP, RE, DIS, ANX, II, NI and PS). Based on Table 5, the value of R2 = 0.734 indicates that 73.4% of the variation in PI is explained by PP, RE, DIS, ANX, II, NI and PS. The balance 26.6% is explained by other factors. The overall regression model was significant since the significance value (0.000) and less than 0.05 with F-Ratio of 39.8. The standard error of the estimate is 0.48097 which is low indicates that the error is quite small.
Table 5. Model summary and anova analysis (The research summarizes).
(a) |
Model |
Sum of Squares |
df |
Mean Square |
F |
Sig. |
Regression |
66.766 |
7 |
9.538 |
39.800 |
0.000b |
Residual |
60.631 |
256 |
0.240 |
|
|
Total |
127.397 |
263 |
|
|
|
(b) |
Model |
Unstandardized Coefficients |
Standardized Coefficients |
Std. Error |
t |
ρ |
R |
R2 |
Std. Error of the Estimate |
Beta |
Beta |
(Constant) |
0.230 |
|
0.307 |
0.748 |
0.045 |
0.857 |
0.734 |
0.481 |
PP |
−0.032 |
−0.028 |
−0.045 |
−0.715 |
0.475 |
RT*** |
0.897 |
0.748 |
0.058 |
15.446 |
0.000 |
DIS |
0.032 |
0.026 |
0.043 |
0.751 |
0.453 |
ANX |
0.049 |
0.046 |
0.043 |
1.130 |
0.259 |
II** |
−0.108 |
−0.071 |
0.048 |
−2.261 |
0.025 |
NI** |
0.160 |
0.033 |
0.057 |
1.048 |
0.013 |
PS** |
0.129 |
0.114 |
0.054 |
2.384 |
0.018 |
significance level; *: ρ < 0.1,**: ρ < 0.05, ***: ρ < 0.01.
5. Conclusions and Implications
From a theoretical perspective, this study found that flow experience had a significant effect on social media platform/website for purchasing intention. Previous studies have mainly applied information technology adoption theories such as UTAUT to examine the factors affecting social media platforms/websites usage behavior. These factors, which are mainly instrumental, include perceived usefulness (Chen et al., 2021), task technology fit (Wu & Song, 2021) and relative advantage (Chetioui et al., 2021). However, the effect of flow experience on user behavior is seldom examined. Our results indicated that flow Social media platform/website users’ intention to purchase 283 experience did significantly affect user intention, as was expected. Thus, social media platform/website commerce user behavior is not only influenced by extrinsic motivations such as perceived ease useful, it is also influenced by facilitating conditions. Kim and Benbasat (2006) stated that the adequate construction of trust-assurance arguments, which are disclosed on websites, is another factor that affects customers’ trust. Future research can integrate trust and UTAUT when exploring social media platform/website for purchasing intention user behavior, and compare their relative effects on user behavior. We found that Retention-Time of MAS, Conformity and price sensitivity have obvious effects on user’s intention. Previous research has found the effects of conformity and price sensitivity on purchasing on the website (Rashid et al., 2020), price sensitivity (Sumeru & Balqiah, 2022) and sense of community (Zhang, 2010). Our research found their effects on flow experience. This shows that presenting a higher Retention-Time of MAS of users are more like to use social media platform/website for purchasing intention, which provides further support for previously made arguments (Phau & Woo, 2008). From a managerial perspective, our results show that selling social media platform/website needs to be concerned with users’ flow experience if they wish to develop and increase their users’ loyalty. Due to the constraints of social media platform/website, presenting users with a compelling experience is critical, if they wish to encourage their behavior and loyalty (Novak et al., 2000). Therefore, the sellers of social media platform/website need to focus on that aspect when providing competitive price or special offer to users. If consumers’ friends often buy things on social media platforms/websites, they will also increase their intention to buy things on social media platforms/websites. This requires that consumers’ price sensitivity will also affect their intention to use social media platforms/websites. They also need to maintain information accuracy, timeliness and comprehensiveness. With these measures users’ trust can be built and their experience can be improved, which will further enhance their intention towards social media platforms/websites usage.
6. Limitations and Future Research
Limitations in this study could be considered and improved in the further research. First, our research in Cambodia, where mobile commerce is developing rapidly around the world. In the future, author could compare the different countries what they care in purchasing of social media platform. Second, it might be other factors to affect their usage behavior such as culture, living level, personality and so on. Third, the online questionnaire method used in this research is probably unable to represent all the population in Cambodia. Furthermore, the conceptual framework in this study may be imperfect with three variables. Future research could add more variables to complete the framework