E-Commerce User Purchasing Decision Case of Palembang, Indonesia

E-Commerce User Purchasing Decision Case of Palembang, Indonesia

^¹Athirah Mohd Tan, ^²Syazwani Yahaya, ^³Rohana Sham, ⁴Noraini Ahmad, ⁵Sonia Umair

^¹Fakulti Pengurusan Teknologi dan Teknousahawanan, Universiti Teknikal Malaysia Melaka

^²School of Management & Business, MILA University

^³School of Business, Asia Pacific Universiti, Malaysia 

⁴School of Business, Asia Pacific Universiti, Malaysia

⁵Department of Management, Dhofar University, Oman

DOI: https://dx.doi.org/10.47772/IJRISS.2025.907000314

Received: 27 June 2025; Accepted: 01 July 2025; Published: 15 August 2025

ABSTRACT

In Indonesia, there are numerous e-commerce and commercial Internet users at present, and Shopee is one of the most popular e-commerce sites. The Shopee application is more in demand because of the relatively low price and the promotion that many users are waiting for. However, there is some problem face by the users such as the product received does not match the image, the product was received in poor or damaged condition, the product received does not match the order, and the product ordered did not arrive. So, this study examined the relationship between price, promotion, and quality of product on purchasing decisions among users of Shopee in Palembang, Indonesia. Other than that gender has been analyze as the moderator for this study. The data, which consisted of 103 respondents, were analyzed using SPSS. The analysis’s findings confirmed that price, promotion, and quality of product were discovered to have a significant impact on purchasing decisions among Shopee users. The findings enrich the literature on price, promotion, and quality of product, which are important factors in Shopee users purchasing decisions. It will become a valuable reference for future researchers performing similar studies to determine factors affecting users purchasing decisions.

Keywords: Purchasing Decisions, Product Price, Product Promotion, Product Quality

INTRODUCTION

As technology advances, most people utilize it globally, particularly in Indonesia, where nearly all residents use it daily. Many online services are available today, mainly online shops, often known as online stores. The current trend is that there are many online services, especially online stores or what is commonly referred to as online shops. Purchasing decisions are the selection of two choices or more consumers on purchases. Every day, consumers make decisions about aspects of daily life. Choices must be available to a person when making decisions. According to Catriona and Sukmana (2021, December 06), 83 per cent of consumers in Indonesia agree that customers find better deals when shopping online than in stores. Consumers prefer online shopping to direct shopping because online shopping is more accessible than shopping in stores. Online shopping is an e-commerce activity that entails using a credit or debit card to purchase from a seller’s website and having the things delivered to your home. E-commerce is said to significantly impact the growth of the digital economy by altering the course of social progress and global economic advancement (Yahaya, Abdul Hamid & Mohd Nafi, 2023). Other than that according to Negara, Damuri, and Azali (2019), Indonesia will account for 53% of the Southeast Asian e-commerce market by 2025.

Shopee is one of the most popular e-commerce in Southeast Asia, mainly in Indonesia, Malaysia, Vietnam, and Singapore. In Indonesia, Shopee is one of the leading online sales and buying and selling services that provide a means of buying and selling from producers to consumers. The Shopee application is in demand because of the relatively low price and the promotions customers are waiting for. Other than that, anyone can also open an online store using Shopee, which can be another source of income if they already have a business and know what to sell. They can serve buyers from all over Indonesia for single or multiple transactions. Shopee also has an advantage in its promotions because most are through social media and television advertisements. Shopee provides benefits for consumers because it is easier to continue the process of purchasing the desired product. Consumers prefer online shopping because it saves time. This is because, without leaving their house, they can buy what they want.

In this online transaction in Indonesia, there are also becoming more and more competitors, like Lazada, Bukalapak, Blibli, and others. Tokopedia and Shopee are the two largest online marketplaces in Indonesia, and both compete fiercely for traders and customers. However, Shopee is in second position behind Tokopedia, with a difference of more than 45 thousand visitors every month, according to Fortune (2022). Tokopedia is listed as the online shopping platform with the highest level of engagement. Tokopedia has benefits like reasonable prices, good products, many deals, good customer service, store ratings and reviews, and delivery services.

Figure 1: Online platform in Indonesia

Source: Fortune (2022)

Because of this Shopee had to deal with some issues as a result of the necessity for improvement. One of the problems is product quality does not meet the customer’s requirements. The problem includes the fact that the product received does not match the image, the product was received in poor or damaged condition, the product received does not match the order, and the product ordered did not arrive (Alifia, 2022). From the data obtained by Jneewsonline (2022), the consumers rate 53 percent of the products available at Shopee as having a good quality compared to its competitor, Tokopedia’s customers rate 74 percent of the products sold were the best quality. Therefore, Shopee needs to pay more attention to the quality of its products and make them better. Other than that is the range of prices for Shopee product much higher than Tokopedia page (Laucereno, 2022). Setting a price that is too high will decrease sales while setting a price that is too low will diminish the organization’s revenues (Asmundson, 2015). Displays of prices thought to be cheap can suddenly become expensive when buyers process payments. The increase in price changes was due to additional costs not included in the initial price, such as service fees and admin fees on the Shopee checkout.  Lastly, the number of people visiting the Shopee website has declined between 2017 to 2021. Although the number of people visiting surged in 2022, it declined again by approximately 14 percent in 2023 (Barus, 2024).

Therefore, this study is carried out to determine the influence of price, promotion, and product quality on purchasing decisions in Shopee in Palembang, Indonesia. The remainder of this paper is structured as follows. Starting with the introduction in section 1.0 and the next section briefly review the literature (section 2.0). Section 3.0 presents the research methodology to be applied in the study, and section 4.0 presents the result. Lastly, sections 5.0 and 6.0 are followed by an explanation of the discussion and conclusion.

LITERATURE REVIEW

This chapter contain 6 sections. It starts with Section 2.1 which is the purchasing decisions variable reviews, followed by Section 2.2 which is product quality review, then Section 2.3 price variable review. And on Section 2.4 then continues to promotion variable review. It is then followed by Section 2.5 and Section 2.6 which is discuss Theory of Planned Behavior (TPB) and hyphotheses.

Purchasing Decisions

Fattah (2021) stated that buying a thing is a process that involves deciding what to buy and figuring out what to buy based on what you did before. This is called a purchasing decision. Other authors, Wydyanto and Ilhamalimy (2021) mention that consumer behavior looks at how each person, household, or organization acts before making a purchase decision. The decision-making process is the consumer’s phase in selecting the product they believes to be the best among other products.This decision is made by a consumer to buy an item or service with a variety of considerations. Lastly, Kartikasari, et. Al, (2025) stated that buying interest denotes an individual’s deliberate intention to acquire a product and lastly make decision to purchase the product.  Consumer behavior encompasses the processes of selecting, purchasing, and consuming products and services to fulfil consumer desires.  So, we can conclude that before a consumer buys a product, a consumer will carry out a decision-making process first.

Product Quality

According to Mahaputra and Saputra (2021), product quality is the physical condition, function, and characteristics of a product based on the quality level. Companies must always improve product quality to make customers feel satisfied with the products provided and will influence customers to repurchase these products (Wahyuni & Ginting, 2017).  This aims to ensure that the resulting product can meet the standards set so that consumers will maintain confidence in the product in question. Meanwhile, Armstrong and Kotler (2014) say that a product’s quality is how well it does its job. This includes how long it lasts, how reliable it is, how accurate it is, how easy it is to use, how easy it is to fix, and many other product qualities. As mentioned by Wydyanto and Ilhamalimy (2021), the customer experience in buying a good or bad product will influence consumers to repurchase. Product quality also important as it affects consumers’ evaluation to strength the brand of the product. So, businesses must be able to create items that satisfy customer needs.

Product Price

Price is the amount of value that must be paid by consumers to own or benefit from a product or service. Price also communicates the company’s intended value position, to the target market, of its product and brand. According to Maria Agatha (2021), price is a way for a seller to differentiate his offer from competitors. So that pricing can be considered part of the product differentiation function in marketing. Price also is a cost that depends on how much people want a product because being able to buy in large quantities is thought to lower costs. To market an item or service, every company must set the price appropriately (Herawati, Wisika, & Kardoyo, 2019; Fadli, Rivalno & Yusman, 2022). This is because the majority of consumers see price as a key factor in the purchasing process (Jusoh & Ahmat, 2017).  After all, consumers will decide whether the price of a product is correct or not. Anggita and Ali (2017) said that a low price does not mean the product will sell, but a high price will make people feel cheated if it’s not in line with what they think the product is worth. Therefore, the pricing decisions must be oriented to the buyer (Firmansyah, 2021).

Product Promotion

Armstrong and Kotler (2014) stated that promotion is one of the tools to get buyers. In essence, promotion is a marketing communication that tries to deliver information, draw attention, and eventually influence greater sales. Promotion can also be defined as an activity that tries to get people interested in a company’s products so they can learn about them, be happy about them, and then buy them (Fadli, Rivalno & Yusman, 2022). Companies must promote their products to notify them that some new products and promotions, such as persuasive promotions, need to be emphasised. A one-way flow of information or persuasion designed to direct a person or organization to action forms an exchange in marketing (Firmansyah, 2021). Based on Yusuf (2020), effective promotion will likely boost sales, given how important it is for promotion to win over customers who want to make a profit and increase sales for the company. Every company that wants a promotion should be able to figure out which promotional tools they should use to make sales (Hadi & Huani, 2021). At the same time, consumers also get to know about the status of products through promotions (Derasit, Shariff, Hamid, Sarwani & Shaharuddin, 2020).

Gender

Gender is one of the most frequently used variables in market segmentation, as research has consistently shown that gender differ in purchasing behavior (Pahl, 1990), consumer decision-making (Bakewell & Mitchell, 2004; Mitchell & Walsh, 2004) and online shopping patterns (Ndubisi & Nelson, 2006; Kim Lehto & Morrison., 2007). However, prior studies in e-commerce often lack a strong theoretical foundation to explain observed gender differences in how consumers perceive and respond to online product presentations (Lin, Featherman, Brooks, & Hajli, 2019). One of the studied Thai online shoppers found that women were more influenced than men by prices, promotions, and product reviews, indicating stronger price moderation by gender (Adekoya & Laksitamas, 2023). While other study by Ghiuța and Nistor (2025) m-commerce study tested whether men and women differed in maximum willingness to pay for smartphones. No significant price difference emerged, but gender influenced brand choice and channel (online vs. offline), indirectly showing gender’s moderating role in price-related decisions. Other than that, studies on livestream shopping platforms (e.g., Alibaba, Taobao) highlight that promotions like flash sales, limited-time deals, and streamer cues drive online purchases. Research suggests that gender moderates how these promotions influence psychological responses and women tend to respond more strongly to hedonic atmospheres and perceived enjoyment, which boosts purchase intention (Huang, Dastane, Cham, & Cheah, 2024). For the quality and eWOM on purchase intention, Saleem, Yi, Bilal, Topor, & Capuṣneanu (2022) showing that women perceived more risk and relied more on-site quality and reviews. Gender moderated the link between these factors and purchase behavior. This support by Ravula, Bhatnagar and Gauri (2023) that found that review persuasiveness varied by reviewer gender and product type. The research suggesting gender moderates how product quality cues (like review content) impact decisions. To better understand gender-based in e-commerce product evaluations and explain further variance in important outcome variables, this research tests for gender as moderator in between price, promotion, and quality of product on purchasing decisions among users of Shopee in Palembang.

The Theory of Planned Behavior (TPB)

The theory of Planned Behavior is a theory that explains human behaviour. This theory is structured to assume that humans behave consciously and consider all available information (Simanjuntak & Halim, 2021). Several considerations, including the attributes inherent in the product, influence consumer purchasing decisions. In this case, a person’s behaviour is a purchase decision from purchase intention.  Behavioural intention denotes a strategy and resolves to engage in the desired behaviour. In general, a person’s desire to conduct a given behaviour increases as his excellent attitude towards the behaviour increases. According to Changjoon (2021), understanding consumers’ purchase intentions is critical because customers can predict their final purchase behaviour from their intentions. Customers decide whether to purchase depending on the information at their disposal. According to the idea of planned behaviour, buy intentions influence consumer behaviour, in this case purchasing decisions. Consumer purchasing decisions include how people, groups, and organizations choose, buy, and use goods, services, ideas, and experiences to meet their needs and want. When buying something, a person will think about the price, promotion, and product quality.

Consequently, the following hypotheses were proposed:

H1: There is a relationship exists between price and purchasing decisions among user of Shopee application in Palembang.

H2: There is a relationship exists between promotion and purchasing decisions among user of Shopee application in Palembang.

H3: There is a relationship exists between product quality and purchasing decisions among user of Shopee application in Palembang.

H4: Gender moderates the relationship between price and purchasing decisions among user of Shopee application in Palembang.

H5: Gender moderates the relationship exists between promotion and purchasing decisions among user of Shopee application in Palembang.

H6: Gender moderates the relationship exists between product quality and purchasing decisions among user of Shopee application in Palembang.

The research framework for this study is shown in Figure 2.

Figure 2: Research Framework

METHODOLOGY

This study employed quantitative research to gain a comprehensive understanding of SME’s antecedents and This study used quantitative research, which is appropriate for assessing how product quality, price, and promotion relate to decisions made on what to buy at Shopee in Palembang, Indonesia. The data used in this study is primary data because a researcher provided it to address a research question. Online, self-administered surveys obtained via Google Forms served as the primary data source for this investigation. Links to the survey forms were shared on social media sites such as Facebook, Twitter, Instagram, and WhatsApp. To answer the research questions and ascertain the impact of pricing, promotion and product quality on Shopee purchase decisions, data from cross-sectional surveys is gathered. This study uses convenience sampling, often known as non-probability sampling, since it is a quick and simple method of gathering. The sample size for this study was determined using Tabachnick and Fidell’s (2013) method, which is N>50 + 8m, and m is the total number of independent variables. This study’s sample is ( 50 + (8*3) = 84. Using this method, the minimum sample size is calculated to be 84. For the final data collection, 114 Shoopee users responded to the survey. However, 11 questionnaires were unusable because of inconsistent responses given by the respondents. Hence, the final sample size for this research was 103 respondents. All the raw data have been coded and keyed into the IBM SPSS Statistic Version 28 (SPSS) software. Data coding is the initial stage of data preparation, where it is required to allocate participant replies into a numeric form so they may be used in data analytics. Once the data coding had been altered, data editing was required to check the correctness of the data, find any outlier responses, and correct them. Also, the data was validated and tabulated meaningfully using a computer, resulting in data transformation to the best format for statistical analysis. The survey was divided into two sections. The first section of the questionnaire consisted of several demographic questions to determine the user’s gender, age, income level, and frequent use of the Shopee platform. Meanwhile, the second section comprised the items for all variables measured using a 5-point Likert scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). The instruments that were examined were the price (6 items), promotion (8 items), product quality (7 items), and purchase decision (8 items).

RESULTS AND DISCUSSION

Descriptive Analysis

The valid data is 103 respondents were gathered and collected. There were 62 females, or 60.2 per cent, and 41 males, or 39.8 per cent (Figure 3). The age group is separated where below 17 years old (9 respondents or 8.7 per cent), 18 to 25 years old (63 respondents or 61.2 per cent), 26 to 35 years old (30 respondents or 29.1 per cent) and above 35 years old (1 respondent or 1 per cent) (Figure 4). From the data collected, most participants are 18 to 25 years old.  Therefore, the majority of the respondents’ income level range (Figure 5) is 1.000.000 – 3.000.000 Rp, with around 48 respondents (46.6 per cent). This is followed by the income level range 3.000.000 – 5.000.000 Rp with 31 (30.1 per cent) respondents, then more than 5.000.000 Rp with 14 (13.6 per cent) respondents, and the minor income level is less than 1.000.000 Rp with 10 (9.7 per cent) respondents. From the results gathered (Figure 6), 37 (35.9 per cent) respondents use Shopee daily, 43 (41,7 per cent) respondents use Shopee weekly, and 23 (22.3 per cent) respondents use Shopee monthly.

Figure 3: Gender

Figure 4: Age

Figure 5: Income Level (Rp)

Figure 6: Frequently use Shopee

Reliability Analysis and Normality Analysis

Data reliability testing is done to determine if a set of items consistently reflects the construct to be measured. The scale’s internal consistency is the most widely used indicator of reliability. In this study, test reliability results were analyzed using Cronbach’s Alpha. The Cronbach’s Alpha test was used to gauge each variable’s degree of correlation with the items. A Cronbach’s Alpha value between 0 and 1.0 suggests that the item has high internal consistency reliability. A result of 0.8 or higher is regarded as good, 0.7 or below as acceptable, and less than 0.6 as poor. Based on Table 1, every variable satisfies the reliability threshold of more than 0.7.

Table 1: Reliability Testing

There were various methods to conduct the normality test, and one famous is skewness and kurtosis. According to Hair et al. (2010), the value for kurtosis between -7 and +7 is considered acceptable to prove normal univariate distribution. For skewness, data is considered normal if skewness is between -2 + 2.  The skewness and kurtosis for all variables have been analyzed. Starting with price, the skewness is -0.229, and the kurtosis value is 0.114. Secondly, the promotion variable, the skewness, is -0.491, while the kurtosis value was 0.164. Thirdly, the product quality, the skewness is -0,769, and the kurtosis value is 1.089. The last variable was purchasing decision; the skewness is -0.753, and the kurtosis value is -0.535. Following this, it could be concluded that all the variables are normally distributed, and the skewness and kurtosis were in an acceptable range.

Correlation Analysis

A statistic used to determine the direction and degree of linear correlations between pairs of continuous data is the correlation coefficient. The correlation coefficient has a range of -1 to 1.

There is no linear link between the two variables when the correlation value is 0.00, whereas a correlation value of +1.00 implies a perfect positive correlation. When one variable’s positive correlation increases, the other variables will also increase, whereas the other variable will decrease when one variable’s negative correlation increases. In Table 2 below, the Pearson correlation result is shown. Through this result, the correlation value between price and purchasing decision is 0.519, indicating a significant positive relationship. A significant correlation for this variable is 0.001 level, and it can be concluded that the variable will influence the purchasing decision. Following promotion, the correlation value between promotion and purchasing decision is 0.554, showing a significant positive association between the two variables. The significance correlation for this variable is 0.001 level. Hence, it can be concluded that the variable will influence the purchasing decision. The last independent variable is product quality. The correlation value between product quality and purchasing decision is 0.639, which indicates the strongest relationship compared to other independent variables. The significance correlation for this variable is 0.001 level. This means the variable will influence the purchasing decision.

Table 2: Correlation Result 

Regression Analysis

Multiple regression analysis is used in this study to examine the relationship between the independent and dependent variables at the same time. The model summary table and coefficient Table 3 display the multiple regression outcome.  The multiple regression model summary is shown in Table 3.

Table 3: Model Summary of Multiple Regression

With an R-value of 0.702, there is a strong degree of association. The R square is 0.592, indicating the dependent variable’s total variation. This means that 59.2 percent of the total variance in purchasing decisions has been explained, which is very large.  Furthermore, the 59.2 per cent variations in purchase decisions are explained in the independent variables.  The adjusted R-square, or the variation of the sample results from the population in multiple regression, illustrates how the results can be applied more broadly. R-square and Adjusted R-square minimum must differ from one another. This is an excellent result because the value, at 0.577, is not too distant from 0.592. The coefficient table provided information on how to predict price from income and determine whether income contributes statistically significantly to the model. As the table above shows, the independent variables impact the dependent variable.

Table 4: Coefficient of Multiple Regression

In Table 4, (B) or unstandardized beta represents the slope of the line between the predictor variable and the dependent variable. In this case, the product price is shown as 0.509, the product promotion is 0.652, and the product quality is 0.627. So, for the price variable, this would mean that for every one-unit increase in price variable, the purchasing decisions increase by 0.509 units. Also, similarly, for promotion variable, for every one-unit increase in the promotion variable, the purchasing decisions increase by 0.652 units. For the product quality variable, for every one-unit increase in the promotion variable, the purchasing decisions increase by 0.627 units. The next symbol is the standardized beta (β). This works very similarly to a correlation coefficient. It will range from 0 to 1 or 0 to -1, depending on the direction of the relationship. The closer the value is to 1 or -1, the stronger the relationship. With this symbol, the researcher compared the variables to see which had the strongest relationship with the dependent variable, since all of them are on the 0 to 1 scale. In Table 4, the Product quality variable had the strongest relationship. Furthermore, the significant value in the last column from the table above has been displayed for all variables. The regression coefficient’s sig p-value column displays the statistical significance of each predictor on the outcome variable, where a p-value of less than 0.05 is considered acceptable. Given that all the significant values were smaller than 0.05, purchase decisions were significantly influenced by product price, product promotion, and product quality.  While for the moderation part, the moderation effect of gender was tested between price, promotion, and product quality to purchasing decisions among user. From Table 4, results show that the corresponding interactions coefficient were statistically significant. The gender significantly moderates the influence of price, promotion, and product quality on purchasing decisions among user because the p value is less than 0.05, which support H4, H5 and H6, respectively.

Based on the results below were the summary for hypotheses testing result:

Table 5: Hypothesis Testing Result

DISCUSSION

This part explaining the discussion and the conclusion for this research.  The discussion part divided three parts based on each hypothesis discussion.

The first hypothesis in this research is “There is a relationship between price and purchasing decisions among users of Shopee in Palembang, Indonesia”, which shows a significant predictor of the price on the purchasing decision. The result of a significant value is 0.007, lower than 0.01 with a P-value < 0.01, which states that the price has a significant positive relationship with purchasing decisions. This result is supported by previous studies from Ambarwati, Selviasari, and Dewi (2022), who also found that pricing has a positive and significant direct effect on Shopee for students in Kediri. Similar studies have been done in the past, whereby price is one of the main factors in purchasing a product. Consumers will typically compare identical products with more affordable prices. Because the item is more cost-effective, consumers will choose to purchase it at a lower price than one that is significantly higher. To attract customers to make a purchase, online retailers compete to offer low prices (Mbete & Tanamal, 2020).

The second hypothesis in this research is that “There is a relationship between promotion and purchasing decisions among users of Shopee in Palembang, Indonesia”. The result of a significant value is 0.001 lower with a p-value < 0.01, which states that promotion has a significant positive relationship with purchasing decisions. This result is supported by Astuti and Pulungan (2021), who also found that promotion has a significant and positive effect on purchasing decisions. According to Rasyadi and Sutrisna (2017), the provided promotion influences the purchase decision of the customer.  Promotion is an essential element of the marketing mix for any organization. Marketing influences purchasing decisions. This demonstrates that a company must consider promotion to attract the attention of consumers. Additionally, promotions are conducted to persuade prospective purchasers to conduct business with sellers to achieve the company’s profit-making objective.

The third hypothesis in this research is that “There is a relationship between product quality and purchasing decisions among users of Shopee in Palembang, Indonesia”. The result of a significant value is 0.001 lower with a p-value <0.01, which shows that product quality influences purchasing decisions. This result is supported by Suhaily and Darmoyo (2017) and Rahim et al., (2024) who also found that product quality has a positive and significant impact on the purchase decision because consumers, in making a purchase decision, will take the consideration the quality of the product. According to Brata, Husani, and Ali (2017), product quality is a comprehensive customer evaluation of the excellent performance of goods or services.  A product can be sold, used, or consumed to satisfy a want or need, and that can be presented to the market to attract attention.

Hypothesis 4, Hypothesis 5, and Hypothesis 6 are “Gender moderates the relationship between price, promotion and product quality to purchasing decisions among user of Shopee application in Palembang”. Indonesia”. The result of a significant value is 0.001 and 0.000 lower with a p-value < 0.01, which states that gender has a significant positive as moderator for price, promotion and product quality to purchasing decisions relationship. This result is supported by Lee et al. (2015) (price), Adekoya and Laksitamas (2023) (price and promotion), Moshary et al. (2023) (price), Lin, Featherman, Brooks and Hajli (2019) (promotion), Mammen and Bharathi (2024) (product quality), and Saleem, Yi, Bilal, Topor, and Căpuṣneanu, (2022) (product quality). Adekoya & Laksitamas (2023) and Lee et al. (2015) identified that price and promotions influenced women’s purchase decisions significantly more than men’s, reflecting gender-driven differences in price sensitivity. The results showed perceived risk and cost concerns impacted purchase likelihood differently for men and women. Other study showed that promotional cues such as interactivity and vividness affected purchase intentions differently by gender: women were more influenced by vivid content and social signals, while men were more responsive to functional, interactive promotions (Lin, Featherman, Brooks and Hajli, 2019). Lastly, the also results supported by Aziz, Khan, and Haque (2024) that gender significantly moderates how product-related factors (including perceived quality) influence purchase intentions, with different moderating effects on men and women. Women were found to develop higher purchase intentions than males when exposed to unfamiliar brands that have less quality (Karpinska-Krakowiak, 2021).

CONCLUSIONS AND RECOMMENDATIONS

This study provides a reference for the organization to focus on the factors that are important for increasing the purchasing decisions of their user’s expectations related to price, product quality, and promotion. Shopee must have an attractive promotion to encourage buyers to repeat the purchase as well as the purchase decision of the customers. Shopee can also enhance product quality by expanding the number of sellers with high product ratings, as the study’s findings indicate that product quality influences consumers’ decisions to buy on the Shopee marketplace.  This might reinforce the belief among consumers that the things they own are of high quality. Regarding the price variable, more customers will make purchases if the Shopee marketplace keeps providing products at reasonable costs that are in line with their quality and benefits. Regarding the promotion variable, customers will be more inclined to make purchases if the Shopee marketplace keeps running different promotions each month since they will believe that they are receiving a lot of benefits from the promotions

This study also provides an initial insight into how price, promotion, and product quality influence purchasing decisions among users of Shopee in Palembang, Indonesia, with product quality having the highest impact on customer purchasing decisions. The price has shown 0.475, the promotion is 0.602, and the product quality is 0.634. This explained that the highest standardized coefficient was product quality, and the lowest was price. It will become a valuable reference for future researchers who are performing similar studies on determining factors that affect purchasing decisions. As Shopee continues to mature, more studies will be required to address the expectations of different age groups, and this study would support future research. Hence, theoretical implications clarified the understanding of the research concept and findings that would be useful for future research.

Furthermore, certain limitations will be faced in doing this research. First, the target audience focuses on Palembang within a single province, which would have a lower adoption rate than other provinces in Indonesia. For future research, a larger age cohort of members can be expanded. It is also suggested that the scope, location, and demographics be expanded to include other cities in Indonesia, such as Jakarta, Bali, and Medan, to enable comparisons between identified differences. In addition to obtaining more precise results and a deeper understanding of how price, promotion, and product quality influence purchasing decisions among users of Shopee in Palembang, future researchers are advised to increase the sample size as this research sample size was small. Lastly, in this research, only three independent variables, one dependent variable and one moderator were used. Future researchers should be able to increase the number of variables of interest. Including other moderator or any mediator in addition to independent variables such as trust, service quality, features, and so forth would be highly advised. It is hoped that more research will yield superior results.

ACKNOWLEDGMENT

The authors are grateful to Universiti Teknikal Malaysia Melaka (UTEM) for providing the academic support required for this research. We also extend our appreciation to our colleagues and peer reviewers whose insightful suggestions improved the quality of this manuscript.

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