International Journal of Business and Economy (IJBEC) eISSN: 2682-8359 | Vol. 4 No. 3 [September 2022]
Journal website: http://myjms.mohe.gov.my/index.php/ijbec
FACTORS INFLUENCING THE CONSUMER PURCHASE INTENTION IN E-COMMERCE
Tan Kock Lim1*, Tan Hong Hooi2 and Loo Teck Khun3
1 2 3 School of Business, UOW Malaysia KDU Penang University College, Penang, MALAYSIA
*Corresponding author: [email protected]
Article Information:
Article history:
Received date : 12 July 2022 Revised date : 10 August 2022 Accepted date : 1 September 2022 Published date : 10 September 2022 To cite this document:
Tan, K. L., Tan, H. H., & Loo, T. K.
(2022).FACTORS INFLUENCING THE CONSUMER PURCHASE INTENTION IN E-COMMERCE.
International Journal of Business and Economy, 4(3), 98-111.
Abstract: E-commerce and internet growth and development are very rapid; however, it is not well- balanced with the number of online purchase transactions which is still relatively low. The purpose of this research is to determine the factors influencing consumer purchase decisions in e- commerce.
Technology Acceptance Model is the underpinning model applied in this study. Electronic word of mouth, perceived trust, e-service quality and return policy are the independent variables whereas customer purchase decision in e-commerce is the dependent variable in this research. The data were obtained through the questionnaire with likert scale 1-5. Respondents in this study were users in e- commerce with a total sample of 215 people. Five data analysis techniques such as descriptive analysis, validity analysis, reliability analysis, correlation analysis and regression analysis are used to analyse the result. According to the findings, this research indicates that electronic word of mouth having a positive relationship with consumer purchase intention in e-commerce whereas perceived trust, e- service quality and return policy shown that there is no relationship in influencing consumer purchase intention in e-commerce. This research is helpful for many fields as references, especially e-commerce and business industry to make improvements on their online marketing strategy.
Keywords: Consumer purchase intention, E-commerce, Technology Acceptance Model.
1. Introduction
E-commerce can be defined as the activity involving purchasing and selling of products or services through electronic systems such as the internet and other computer networks. In this new era of science and technology, e-commerce has gained popularity over the world with many advanced technologies introduced in its operations (Shahjee, 2016). Nowadays, consumers can access the global market through the virtual economy on the internet and may select their favourite products, and shop according to their times and place their order in anywhere they feel cosy and convenient to them (Dan, 2014).
Developments in the commercial sector, coupled with the increasing popularity of the internet in recent years, have made Malaysian companies more aware of the importance of e-business in gaining a competitive edge in the global market. As such, a better understanding of the factors that influence online shopping intention would help in planning better marketing strategies in targeted segments.
Figure 1.1 shows the number of online shoppers in Malaysia within 7- year period. It shows that the number of online shoppers in Malaysia increases year by year. The number of online shoppers in Malaysia for 2016, 2017 and 2018 are 0.88 million, 1.08 million and 1.31 million respectively. In 2019, the number of online shoppers in Malaysia grew from 1.31 million to 1.58 million. In 2020, the numbwe of online shoppers in Malaysia is 1.88 million and estimated to continue to rise in 2021 and 2022 which are 2.20 million and 2.53 million accordingly.
Figure 1.1: The number of Online Shoppers in Malaysia from 2016 to 2022 (Source: Wadolowska, 2018)
The advancement of the World Wide Web has resulted in the creation of a new form for electronic retailers. However, web-retailers can only offer certain ranges of products and services to the web-shoppers. This includes e-banking services, technology gadgets, cosmetics, clothing and airlines e-ticketing services. Wolfinbarger and Gilly (2001) assert that webshopping presents different shopping experiences even when the same products are
purchased.
There are many researchers who have completed their analysis regarding factors influencing consumers’ purchase intention in e-commerce. Despite that, the outcome of their analysis is differenced. Some researchers agreed that electronic word of mouth have a positive impact towards consumer purchase intention (Cheung, Lee & Rabjohn, 2008). Related to trust, some researchers agreed there is positively linked with consumer purchase intention in e-commerce and risk perception has a negative impact towards consumer purchase intention (Budi Puspitasari, Nugroho W P, Nilan Amyhorsea & Susanty, 2018). The research conducted by Sinurat and Ali (2020) agreed that e-service quality have a significant impact towards consumer purchase intention. Accordingly, to Khanna, Awal and Gupta (2019), Janice, Saerang
& Pandowo (2017) agreed that return policy has a positive relationship towards consumer purchase intentions.
The research objectives are as follows:
i. To examine the relationship between electronic word of mouth and consumer purchase intention in e-commerce.
ii. To determine the relationship between perceived trust and consumer purchase intention in e-commerce.
iii. To study the relationship between e-service quality and consumer purchase intention in e-commerce.
iv. To investigate the relationship between return policy and consumer purchase intention in e-commerce.
2. Literature Review
Technology Acceptance Model (TAM) theory was developed at 1989 by Davis which has a purpose of predicting the acceptance of system and behavior of users when using the system.
TAM explains that individual behaviour when using a system is affected by perceived ease of use and perceived usefulness. (Davis, 1989). Previous studies also using technology acceptance model as a guiding theory such as in the field of online banking information systems acceptance (Chandio, Abbasi, Nizamani & Nizamani, 2013) and cloud computing adoption by companies (Dachyar & Prasetya, 2012) which both of the research area related to technology adoption. A website, in general, can be considered as an information system which give information to its users. (Shih, 2004). Nowadays, TAM is the most suitable theory in order to explain the acceptance of technology in the information system research (Gefen, Karahanna & Straub, 2003). Thus, online purchase intention, as an appropriate measurement for intention to use a website, should be explained as a part of technology acceptance model. As guiding theory in this research, the two factors of TAM (perceived usefulness perceived ease of use) are included.
Perceived ease of use is explained to an extent when a user experienced a particular website as easily operated and effortless (i.e., time and energy) to learn using the website (Chen & Ching, 2013). When websites interfaces are easy to use, buyers will find the meaningful and useful information easily, which improve their perception of usefulness.
Figure 2.1: Theoretical Framework of Technology Acceptance Model (Source: Davis, Bagozzi & Warshaw, 1989)
2.1 Purchase Intention
The intention to transact or purchase intention is defined as the intention of buyers to engage in the exchange relationship at shopping websites, such as sharing information, maintain business relationships, and create business transactions (Zwass, 1998). Intention to purchase online is based on the relationship between behavioral intention and actual behavior.
Behavioral intention of individual to do action will determine the actual individual behavior.
Thus, purchase intention to particular online shopping websites is a factor that predicts the actual behavior or the purchase decision of customers (Kim, Ferrin & Rao, 2008). The research observing online purchase intention is an appropriate measurement for intention to use the website because online transaction involves sharing information process and actual purchase so that online purchase intention will depend on many factors (Pavlou, 2003).
According to Mirabi et al. (2015), purchase intention is a type of decision-making that discover the factor to purchase a brand by consumer. Furthermore, researchers also defined purchase intention as a situation where consumers tend to buy a certain item in certain condition.
Purchase intention usually linked to the consumer behaviour, perceptions and attitudes. It can be considered as an effective tool to forecast the buying process of consumer.
2.2 Electronic Word of Mouth (eWOM)
Electronic word of mouth defined as any attempt by a former, potential, or actual consumer to highlight the positive or negative features of a product or company through an online platform (Almana and Mirza, 2013). Electronic word of mouth acts as a vital role in consumer’
perception of a particular brand name (Amblee and Bui, 2012). One of the differences between electronic word of mouth and traditional word of mouth is electronic word of mouth have the capability to reach an unprecedented number of people all at once. Researchers stated that consumers rely on online consumer reviews regarding products or services before they proceed to make their purchase intention. This is because electronic word of mouth serves as decision aids, consumer feedback mechanism and a recommendation system in e-commerce (Almana and Mirza, 2013).
eWOM information on various social networking sites highly influences purchase intention of consumers (Evans and Erkan,2018). eWOM via social media significantly influences consumers emotional, affective and cognitive responses (Yan et al,2018). Information quality is available to consumers in the form of reviews significantly influences consumers purchasing
intention (Baroom et al.,2020). eWOM information or consumer reviews helps in buying decisions of consumers (P.Y Michelle,2018). eWOM plays an important role in developing brand image in the minds of consumers. Besides, eWOM and brand image have certain influence on buying intention of consumers (Haun et al,2017).
2.3 Perceived Trust
Trust defined as a belief that the counterparty will meet the expectations without exploring the vulnerabilities of the trustee (Aziz, Md Husin, Hussin & Afaq, 2019). Trust refers to a feeling of security and willingness to depend on someone or something. Researchers considered that trust and consumer satisfaction is a dynamic process and it is built over a particular period of time contribution in order to satisfy beyond the effects of the economic outcome. There are two methods distributed by researchers. The first method is defining trust as a belief, confidence, expectation or attitude regarding another individual’s trustworthiness. The second method is trust as behavioral intention or behaviour of reliance and includes vulnerability and uncertainty (Kim, Chung & Lee, 2010). Researchers stated that users feel fearful making transactions through the Internet with e- vendors. Consumers are afraid of disclosure of their personal data, lack of standards for secure payment and lack of profitable business models. Thus, perceived trust helps decrease fear of consumers and facilitate transaction in e-commerce.
In internet-based consumer behavior, trust is crucial, because, in virtual networks, understanding cannot be increased through face-to-face interaction. Trust can enhance consumers’ intentions to shop online and promote more shopping behaviors (Zhao et al., 2019). In context to social commerce, trust is generally defined as a belief state that submits to the vulnerability created by the actions of another party without monitoring or exercising control over the other party (Al-adwan & Kokash, 2019).
2.4 E-Service Quality
Service quality refers to the degree to which a website facilitates effective and efficient purchasing. Researchers stated that on the beginning e-service quality consists of 11 dimensions. Nonetheless, the figure lowered to 7 dimensions in the later studies. Moving on, the service quality dimensions distributed into three segments such as tangibles, responsiveness, reliability, assurance and empathy. E-service quality comprises four dimensions such as website design, customer service, privacy or security, and fulfillment.
Researchers stated that perceived e-service quality has a significant impact on consumer satisfaction (Cristobal, Flavia´n and Guinalı´u, 2007). Other researchers stated that e-service quality refers to online travel customers’ overall judgment of the excellence and superior quality of e-service offerings in the virtual marketplace (Tsang, Lai & Law, 2010). E- commerce may provide the tailor-made service and delivery product within the promises time in order to influence consumer intention to purchase in e-commerce. E-service quality positively influences consumer purchase intention in e-retail. (Kalia, Arora & Kumalo (2016).
2.5 Return Policy
Return policy can be defined as the availability and its return management offers the psychological benefit for solving consumer’s remorse such as security awareness.
Furthermore, return policy refers to the minds of buyers as an increase in the service quality of an organization, and the perceived quality of an organization affects consumer purchase decisions (Kidane and Sharma, 2016). In addition, researchers stated that return policy also linked to the level of consumer loyalty and increased consumer confidence to a store (Oghazi, Karlsson, Hellström & Hjort, 2017). Therefore, the availability of return policy enhances consumer consumption decisions to purchase via online channels.
Several important findings that describe the relationship between return policy and consumer purchase intention. Return policies have a positive impact on consumer purchase intention in e-business (Hsiao & Chen, 2012; Pei, Paswan & Yan (2014, Oghazi et al. 2017).
2.6 Theoretical Framework
Figure 2.2: Theoretical Framework of this Study
The summary of hypothesis statement as follows;
H1 Electronic word of mouth is positively related to purchase intention in e- commerce.
H2 Perceived trust is positively related to purchase intention in e-commerce.
H3 E-service quality is positively related to purchase intention in e-commerce.
H4 Return policy is positively related to purchase intention in e-commerce.
3. Research Methodology
Research design, construct measurement and questionnaire design, and data analysis methods.
The research design consisted of research population and sample size, sampling method, data collection method, unit of analysis
Quantitative method is the method applied in this research for collecting data. The sample size in this study is 215. The questionnaire will be delivered to individuals who fit the criteria of this study. SPSS software is used to analyzed the data.
The unit of analysis is individuals who are experiencing and having intention to purchase in e- commerce. Questionnaire will be used to collect the relevant information from the respondents.
There are five data analysis techniques in this research such as descriptive analysis, validity analysis, reliability analysis, correlation analysis and regression analysis.
Descriptive analysis refers to identify, describe, compare and clarify all data collected.
Standard deviation, frequency distribution, percentage distribution and central tendency are applied to present the collected information from questionnaire. Standard deviation and frequency distribution is a display of the numbers of observations. The representation of a frequency distribution can be tabular or graphical so that it is easier to understand well.
Furthermore, the demographic background of respondents.
Validity analysis refers to the accuracy of a method measurement and relates to what the survey intended to measure (Messick, 1987). In this research Kaiser-Meyer-Olkin (KMO), Bartlett’s test of sphericity and factor analysis is applied to discuss the data. KMO is applied to test how the data is suited factor analysis and ensure that sampling is adequacy and should the result of KMO should more than 0.5 (Crane, Busby and Larson,1991). Besides, Bartlett’s Test of Sphericity is applied to test whether any redundancy between variable and the result (p <0.05) is significant (Zach,2019).
Reliability analysis refers to the extent to which results are consistent over time. The accuracy of a representation of the total population under research is defined as reliability (Golafshani, 2003). Cronbach’s Alpha analysis is used to measure reliability and SPSS software is computed in this research. The range is usually between 0 and 1 in Cronbach’s alpha reliability coefficient. However, there is no lower limit to the coefficient. The closer Cronbach’s alpha coefficient is to 1.0 the greater the internal consistency of the items in the scale. The increase in the value of alpha is partially dependent upon the number of items in the scale, it should be noted that this has decreasing returns. In brief, the high value for Cronbach’s alpha indicates good internal consistency of the items in the scale (Gliem and Gliem, 2003)
Correlation analysis refers to a process for determining the relationships between both independent and dependent variables. In this study, this method is applied to determine the relationship among all variables through SPSS software. The correlation coefficient normally ranges from -1 to +1. When the value establishes +1, then the data are positively correlated, and -1 has a negative correlation. If the coefficient comes down to zero, the data is considered as not related (Kristoufek, 2013).
Multiple regression analysis is performed in this study. Multiple regression is a technique that allows additional factors to enter the analysis separately so that the effect of each can be estimated. This analysis is used to predict the value of several variables (Mason and Perreault, 1991). Hence, regression analysis may help to predict consumer purchase intention in e- commerce. In addition, R-square refers to the variance of the predicted values divided by the variance of the data. Durbin-Watson test is applied to detect the presence of autocorrelation.
Durbin-Watson usually provides the values that range from 0 to 4. If the values near 0, then it is positive autocorrelation. The negative autocorrelation is presented by values near 4.
Autocorrelation is not present if the value ranging from 1.5 to 2.5. Furthermore, multicollinearity is a phenomenon when two or more predictors are correlated, if this happens, the standard error of the coefficients will increase.
4. Discussion and Conclusion
This research picked out the sample size of 215 individuals who have experience in purchasing in e-commerce in Malaysia. To ensure accuracy, researcher collected 220 sets of questionnaires, while a total 220 sets of questionnaires were collected through online. Yet, 5 set of questionnaires were unusable because they were not filled up properly.
Out of 215, 137 (63.7 percent) are female and 78 (36.3 percent) are male.
The result of KMO 0.889 is achieve the minimum required and the sampling is adequacy. The Bartlett’s Test of Sphericity value is 3157.987 and this result achieve the significant value 0.000 which (p<0.05).
KMO Test Bartlett’s Test of Sphericity (Approx Chi-Square)
Bartlett’s Test of Sphericity (Significance)
0.889 3157.987 0.000
The result of reliability analysis showed all the variable is achieved the minimum required Cronbach’s Alpha value which is 0.7 and none of the item is abandoned.
The Pearson Correlation is used to get correlation value. In this study all the variable is significant and positive. The result showed that the highest value of Pearson Correlation is 0.73 that mean that the electronic word of mouth is the most effect variable toward purchase intention, while e-service quality is 0.677, return policy is 0.607 and perceived trust is 0. 595.
Variable Number of Items Cronbach’s Alpha
Purchase intention 6 0.739
Electronic word of mouth 6 0.741
Perceived trust 6 0.778
E-service quality 6 0.760
Return policy 6 0.810
The regression analysis findings showed adjusted R2 is 0.613 which mean that 61.3% of the factor of consumer purchase intention is related to electronic word of mouth, perceived trust, e-service quality and return policy. The Durbin Watson is 1.550 which is acceptable and achieve the range 1.5-2.5 which mean that there is no autocorrelation.
Furthermore, this study is no any multi-collinearity problem. The tolerance value of this study is 0.1-1.0 and there is no any variable is overlap and the value of VIF is between 1-10 and condition index is 10-40.
Independent Variable Tolerance VIF Condition Index
Electronic word of mouth 0.546 1.830 21.639
Perceived trust 0.397 2.521 24.903
E-service quality 0.314 3.180 33.842
Return policy 0.335 2.983 39.175
Based on the result of standardized Coefficient Beta. Electronic word of mouth positively affect consumer to purchase on e-commerce because the standardized coefficient beta is 0.483 and significant level is 0.000 yet the rest of the factor is not significant. The standardized coefficient beta shows the value of perceived trust is 0.171, it stated that perceived trust is positive relationship with purchases intention yet it is not significant because the significant level is 0.120. Besides the e-service quality and return policy is positively influence consumer intention but the significant level is (p>10). In addition, the t test is used to analyze one or two sample means. The confidence interval of this study is 95%.
Table 4.1: Standardized Coefficients Beta Independent
Variable
Sig. t-value Standardized Coefficient Beta
95% Confidence Interval Lower Bound Upper Bound Electronic word of
mouth
0.000 8.397 0.483*** 0.398 0.641
Perceived trust 0.120 2.539 0.171* 0.040 0.321
E-service quality 0.190 2.368 0.180* 0.035 0.385
Return policy 0.330 0.977 0.072* -0.74 0.218
Dependent variable: Purchase intention Note: ***p<0.01, **p<0.05, *p<10
R2 Adjusted R2 F Durbin-Watson
0.620 0.613 85.619 1.550
Figure 4.1 Result of Multiple Regression Analysis
Table 4.2 showed summary of result. All the hypothesis rejected except H1 is accepted.
Hypothesis Description Standard Coefficient Beta
Result Sig. P value
H1 Electronic word of mouth is positively related to purchase intention in e- commerce.
0.483 Accepted 0.000
H2 Perceived trust is positively related to purchase intention in e- commerce.
0.171 Rejected 0.120
H3 E-service quality is positively related to purchase intention in e- commerce.
0.180 Rejected 0.190
H4 Return policy is positively related to purchase intention in e-commerce.
0.072 Rejected 0.330
The result indicated that electronic word of mouth is having a positive relationship with consumer purchase intention in e-commerce whereas other factors which are perceived trust, e-service quality and return policy show that there is no relationship in influencing consumer purchase intention in e-commerce. Therefore, H1 is accepted and H2, H3 and H4 is rejected.
This study enables to provide a reference to future researcher and academy about the factor influencing consumer intention to purchase in e-commerce. This study prove that electronic word of mouth is positively effect consumer purchase intention in e-commerce yet the perceived trust, e-service quality and return policy is no relationship with consumer purchase intention in e-commerce. Therefore, the result may be a useful reference for future researcher.
E-service quality is not related with consumer purchase intention in e-commerce. Sometime the product information provided in the website is not sufficient, therefore consumer is really hard to make decision to purchase the product just by reading the limited information provided by the website. Moreover, the merchant website should be update regularly, the website feature which is too outdate or too new also hard to let consumer perform on the website. These is the issue that merchant should take in consider in order to influence consumer purchase intention.
Merchant should ensure that product information is updated understandable and clear. Besides that, e-commerce website should provide a user manual and tutorial to user. E-commerce website should also develop several languages to in order consumer can choose the language they are understand and this action may affect consumer intention to purchase in e-commerce.
Return policy is no affect consumer intention to purchase in e-commerce. The return policy is not attracted consumer to purchase online this is because the procedure to return the product is
too time consuming and complex. Consumer can get feedback and direct return to the seller when consumer is buying from the physical shop which is more time saving and convenient compare to return the product to e-vendor. Furthermore, some of the merchant is charging an unreasonable cost when consumer return the product, that may let consumer feel uncomfortable and not reason to return and purchase product through online.
Merchant and marketer should pay more attention to encourage consumer to leave a review on product. By reading review of the product, it may attract consumer purchase intention to purchase product in e-commerce. However, merchant and marketer should pay more effort on perceived trust, e-service quality and return policy in order to change the mind of consumer and provide a wonder purchase experience for consumer.
Merchant should improve the security of the website in order to protect consumer privacy and e-commerce platform should verify every seller in the platform to avoid scammer and increase consumer confident to purchase in e-commerce. Moreover, seller should ensure that the information of the product is sufficient and clear to ensure that consumer is clear about the product information such as the function of the product, expire date and price. E-commerce platform should provide a user manual and tutorial to ensure that consumer is understand the feature of the website. In addition, seller should explain the return policy clearly and charge a procedure fees before consumer purchase product to avoid misunderstanding.
This study also enables to provide a reference to future researcher and academy about the factor influencing consumer intention to purchase in e-commerce. This study prove that electronic word of mouth is positively effect consumer purchase intention in e-commerce yet the perceived trust, e-service quality and return policy is no relationship with consumer purchase intention in e-commerce. Therefore, the result may be a useful reference for future researcher.
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