The Effect of Technology Acceptance on Online Customers’ Repurchase Intention

 

Neeti Gupta

Senior Research Fellow, Himachal Pradesh Business School, Himachal Pradesh University,

Summerhill, Shimla (H.P).

 

ABSTRACT:

Repurchase intention is an intention to continue using an online platform for making purchases in the near future. Fierce competition, low switching cost and lack of personal selling increase the importance of repurchase intention in online retailing. Taking into consideration that online shopping revolves around information technology, this study aims to investigate the impact of components of the extended technology acceptance model on repurchase intention. Unfortunately, in India where small cities are becoming a lucrative target market for online retailers not much is known about how acceptance of technology is affecting the repurchase intention of customers. The present study tries to reduce this gap by carrying out empirical research on 160 online shoppers from Shimla city, Himachal Pradesh, India. The results of this study established the applicability of perceived ease of use and perceived enjoyment in ensuring repurchase intention. Surprisingly, perceived usefulness is not significant in influencing repurchase intention. Research results can help online retailers to make strategies to target technology-savvy online consumers, especially in small cities.

 

 

 

INTRODUCTION:

Electronic commerce (E-commerce) is doing business across telecommunication networks. In e-commerce buyers, sellers or other parties involved interact electronically and conduct business without any physical contact (Chandan and Gupta, 2018)¹. Business to Consumer (B2C) is a part of e-commerce where goods and services are exchanged online between business and consumer. B2C e-commerce or online retailing is flourishing at a blistering pace all around the world and so as in India. In the electronic age, the rapid rate of internet adoption has built a solid foundation for the Indian online retail business.

 

According to ibef report 2019², ‘India’s e-commerce revenue is expected to jump from US$ 39 billion in 2017 to US$ 120 billion in 2020, growing at an annual rate of 51 percent, the highest in the world.’

 

The virtual shopping allows a customer to easily compare features and prices of millions of products with an added advantage of place and time convenience. But on the other hand, online shopping has created a transparent online environment where switching cost is almost zero. Additionally, low entrance cost has led to severe competition among online retailers. Therefore, online retailers looking for success need to keep abreast with customers’ repurchase intention. Without ensuring customer repurchases e-business will fail apart. In addition to the above, Reichheld and Schefter (2000)³ suggested that the value of repurchase has been often greater on the internet than in the physical world as acquiring customers on the internet is enormously expensive. Moreover, profit will remain elusive unless customers stick around and make lots of repeat purchases over the years.

 

Previous studies in the literature considered customer repurchase as the main construct to measure the success in e-commerce. To understand the components of repurchase intention in electronic commerce, it is important to understand the differences and similarities between online and offline shopping. Unlike traditional shopping, where the intention to repurchase depends on trust on the person selling goods (salesperson or retailer or both), ambience and physical evaluation of goods, in the context of B2C e-commerce transaction, intention to repurchase is affected by the acceptance of information technology. Usefulness and enjoyment factors which are core components of offline shopping are also important in online shopping. In addition to these two basic motivators, as online shopping revolves around the use of technology, ease of using technology for shopping is an important factor in the acceptance and continuation of online shopping. As a result, acceptance of technology for fulfilling utilitarian as well as hedonic motives is a prerequisite to ensure repurchase intention among customers.

 

This study has been conducted to analyse the impact of extended TAM variables on repurchase intention with a special focus on experienced online shoppers with four or more than four years’ experience of using the internet from small city Shimla, Himachal Pradesh, India. In India, small cities and towns are becoming a lucrative market for online sellers. The present study is confined to Shimla as it is a small city with a high literacy rate along with  good roads, and phone connectivity. All these factors are giving a boost to online shopping in Shimla.

 

LITERATURE REVIEW:

This section elaborates on the theory base and derives the hypotheses. The proposed research model is depicted in Figure 1.

 

Online Shopping:

Online shopping is a new form of shopping using information and communication technology to complete the transaction. It involves an entire range of offline shopping actions like information searching, comparing products and prices, purchasing products and services, maintaining the customer relationship and sharing experience with the addition of using the screen with the internet. Compared with the traditional face-to-face offline shopping, the online shopping mode offers several unique benefits, such as a variety of products, detail product information, home delivery, different offers and convenience in terms of anytime anywhere shopping. As a result of busy working and social life, online shops let consumers save time while fulfilling their fundamental needs, cover a variety of products and services in a short time, and avoid traditional shopping costs (Aren et al., 2013)⁴.

 

Repurchase Intention (RI):

Repurchase intention is a tendency to act before the actual purchase. It refers to the customer’s keenness to buy from a particular e-retailer in a certain period. It is an outcome of the fulfillment of utilitarian and hedonic factors. RI is a key to success in a transparent virtual environment. The importance of loyalty is reflected in the company’s profit. Loyal customers may be worth up to ten times as much as its average customer and bring many benefits to a seller (Anderson and Srinivasn, 2003)⁵ like improving the company's profitability by frequently referring new customers (Reichheld and Schefter, 2000)³. Srinivasan et al. (2002)⁶ observed that the firms in an online environment are operating under near-perfect market conditions where large numbers of competitors are offering similar products. Additionally, repurchase intention is crucial in online shopping as in the transparent online environment the cost of switching from one retailer to another retailer is almost zero.

 

Extended Technology Acceptance Model:

In the online context, TAM is widely accepted, tested and validated. Initially, it was developed to study the adoption of technologies for utilitarian purposes using perceived usefulness (PU) and perceived ease of use (PEOU). Later, to make TAM more useful for online retailing it was extended to include hedonic purpose i.e. perceived enjoyment (PE). TAM has been considered as an important determinant of consumers’ attitude toward using new technology. It is a dominant model continuously providing a suitable theoretical base for e-commerce. Extended TAM covers both the utilitarian and hedonic motives which are important for shopping. The major variables of extended TAM are PU, PEOU, and PE. In extended TAM, PU and PEOU cover utilitarian motives and PE handles hedonic motives.

 

Perceived Usefulness (PU):  

In online shopping, PU can be defined as the customer’s subjective perception that using online shopping will enhance search and shopping efficiency. In electronic shopping, PU is directly related to enhancing productivity in searching and better selection of goods and services. Therefore, PU has an immediate effect on behaviour intentions because of its utilitarian character (Tang and Huang, 2015)^7. In previous studies, it was found that PU significantly influences RI (Aren et al., 2013⁴; Khalifa and Liu, 2007⁸; Chiu et al., 2009⁹; Al-maghrabi et al., 2011¹⁰; Wen et al., 2011¹¹; Rezaei and Amin, 2013¹²; Li, 2016¹³; Omotayo and Adeyemi, 2018)¹⁴. Contrary to all the past researches, the research result of Ali (2016)¹⁵ revealed no influence of PU on RI.

 

H₁: The perceived usefulness has a significant positive effect on repurchase intention.

 

Perceive Ease of Use (PEOU):

Using information technology is a necessary requirement for online shopping. It is the first encounter of a customer with an online retailer in the process of online shopping. PEOU can be defined as the degree of expectation of customers that online shopping is easy to learn and use. Lim and Ting (2012)¹⁶ suggested that the perception that technology is easy to use helps in forming a positive attitude towards online shopping among customers. Easy technology is easily accepted and continued by consumers. This though is supported by Chen et al. (2013)¹⁷ as their study concluded that a system that is easy to use is easily adopted by users due to its utilitarian value. Similar thoughts were advocated by Barkhi and Wallace (2007)¹⁸ that if a shopping site is convenient to use then the customer will interact more with the retailer and can further lead to intention to purchase or repurchase online. In prior research, the significant positive influence of PEOU on RI has been established (Aren et al., 2013⁴; Chiu et al., 2009⁹; Rezaei and Amin, 2013¹²; Omotayo and Adeyemi, 2018¹⁴; Ali, 2016¹⁵; Chung and Lee, 2003¹⁹; Moeeini and Fard, 2014²⁰). Contrary, no effect of PEOU on repurchase intention is established in the research results of Ashfaq et al., 2019²¹.

 

H₂: The perceived ease of use has a significant positive effect on repurchase intention.

 

Perceived Enjoyment (PE):

Online shopping is a voluntary shopping. Customers are self-determined and intrinsically motivated in e-shopping only when they are interested in it or perceived it to be personally enjoyable and fun (Chiu et al., 2009)⁹. Consumers who are hedonists have experiential shopping behaviour. They want a thrilling experience by seeking for fun and excitement while shopping. PE can be defined as the degree of possibility that in the shopping process they feel involved, good and excited to shop.

 

In the study conducted by Atchariyachanvanich et al. (2008)²² intrinsic factor which included pleasure, novelty and fashion involvement was statistically significant in influencing intention to continue purchasing on the internet. Al-Maghrabi et al. (2011)¹⁰ suggested that managers should work on a level of enjoyment to increase continuance intention among older consumers. Significant influence of PE on repurchase intention is established in prior research (Chiu et al., 2009⁹; Wen et al., 2011¹¹; Li, 2016¹³; Omotayo and Adeyemi, 2018¹⁴;  Ali, 2016¹⁵; Chen et al., 2013¹⁷; Ashfaq et al., 2019²¹; Koufaris and Hampton-Sosa, 2002²³; Li and Zhang, 2002²⁴; Ramayah and Ignatius, 2005²⁵; Cheema et al., 2013²⁶; Tatang and Mudiantono, 2017²⁷).

 

H₃: The perceived enjoyment has a significant positive effect on repurchase intention.

Based on hypothesis, research model is presented in figure 1

 

Figure 1: The Proposed Research Model

 

Research Gap:

The need to study repurchase intention among experienced online consumers of a small city with internet experience of four or more years arises because in India small cities are driving e-commerce growth. According to RedSeer report (2019)²⁸, 'Tier 2 plus cities in 2017 contributed nearly 41 percent of the overall online shoppers'. Tier-II and tier-III cities are the fastest growing online market. But unfortunately, not much is known about how acceptance of technology is affecting the repurchase intention of customers from small cities. Moreover, to date, no study was found to check the applicability of TAM among internet-savvy customers.

 

The present study tries to address these gaps by establishing a linear relationship between variables of extended TAM and repurchase intention with special reference to small city Shimla, Himachal Pradesh, India. The objective of this research is to develop a prototype online repurchase research model based on the hypothetical relationship suggested in past studies related to PU, PEOU, and PE.

 

Research question:

Research question framed to conduct comprehensive research in this area is: What is the impact of Extended TAM variables i.e. Perceived Usefulness (PU), Perceived Ease of Use (PEOU), and Perceived Enjoyment (PE) on Repurchase Intention (RI) of experienced online consumers from small cities?

 

RESEARCH METHODOLOGY:

The present research is a systematic empirical investigation of the influence of extended TAM variables on repurchase intention. The measurement instrument was developed as a result of several studies on TAM and repurchase intention about online shopping. The questionnaire included close-ended questions. It was divided into following two sections: The first section of the survey instrument was designed to get information about the respondents’ demographic profile. The next section counted on a five-point Likert rating scale from “1 (strongly disagree)” to “5 (strongly agree)”. Overall, 18 items using a reflective scale was applied and the multiple regression model is used to measure the relationship proposed in the research. PU and PEOU items were adapted from Gefen et al. (2003)²⁹ and Childer et al. (2001)³⁰. PE and RI items were adapted from Childer et al. (2001)³⁰.

 

A questionnaire survey was carried out through a printed and online questionnaire using non-probability convenience sampling. Data was collected from colleges, universities, offices, and self-employed people based on the criterion of having internet experience of four or more than four years.  The pilot survey was conducted on 20 respondents for checking the reliability of the scale. Later data were collected from 160 respondents. Out of 160 responses, 152 responses were usable. Data were analysed using descriptive and multiple-regression in SPSS 16.0.

 

Reliability:

The pilot study was conducted on 20 respondents and internal consistency was evaluated using Cronbach's alpha. Cronbach’s reliability coefficient for all the constructs presented in Table 1 is higher than the minimum cut-off score of .70.

 

Table 1: Cronbach’s alpha

Source: Primary Data

 

Data Analysis:

Demographic Profile:

The total number of responses obtained was 160 out of which 152 were valid and useful for analysis. Table 2 represents the descriptive analysis of demographical variables. Out of 152 valid responses, 95 (62.5 percent) are male and 57 (37.5 percent) are female. In the present research, the maximum respondents are male. With respect to age, 45 (29.6 percent) respondents are in the age bracket of 25 or below, 55 (36.2 percent) in the age bracket 26-35 and 52 (34.2 percent) are above 35 years. For education qualification, maximum respondents 66 (43.4 percent) are postgraduate followed by graduates 46 (30.3 percent) and others 40 (26.3 percent) respectively. With respect to occupation, maximum respondents 53 (34.9 percent) are government sector employees, followed by 43 (28.3 percent) students, 40 (26.3 percent) private sector employed, and 16 (10.5 percent) self-employed respectively. Maximum respondents are in the income bracket 20001-40000 (53, 34.9 percent) followed by up to 20000 (50, 32.9 percent) and dependent on others (33, 21.7 percent).

 

Table 2: Demographic Profile

Source: Primary Data

 

Inferential Analysis:

Overall regression equation of repurchase intention with PU, PEOU and PE as antecedents is found to be statistically significant F (3; 148) = 27.132, p<.001. To verify the hypothesis multiple regression is used. Collinearity has been checked using VIF. As all the values are below 5, it is concluded that there is no collinearity among variables.

 

The coefficient table gives a constant term and regression coefficient (b) for each explanatory variable. The constant value .977 represents the intercept; which is a predicted score when TAM=0. From the table 3, PU is statistically insignificant to influence RI with negative beta value -.031, p> .000. The regression coefficient indicates that for every unit increase in PU the model predicts .031 decreases in RI, which is insignificant. Thus, the first hypothesis H₁ is rejected and it is concluded that there is no significant influence of PU on RI. The second hypothesis H₂ reveals significant results with beta value .346, p<.000. The regression coefficient indicates that for every 100 percent increase in PEOU the model predicts a 34.6 percent increase in RI. Thus, H₂ is accepted and it is concluded that there is a significant positive influence of PEOU on RI. The third hypothesis H₃ also reveals significant results with beta value .434, p<.000. The regression coefficient indicates that for every 100 percent increase in PE the model predicts a 43.4 percent increase in RI. Thus, H₃ is accepted and it is concluded that there is a significant positive influence of PE on RI.

 

 

The model summary represents .596 (59.6 percent) relationship between dependent i.e. RI and predictors i.e. PU, PEOU and PE. R² which represents the amount of variation in the outcome that can be explained by the model is .355 which indicates that 35.5 percent variance in RI is explained by PU, PEOU, and PE. However; there is still a 64.5 percent variation in repurchase intention that is not related to TAM variables.

 

Table 3: Regression Model of Repurchase Intention

Source: Primary Data

 

Based on the Table 3, the equation for regression line is: RI=.977 +.346 PEOU+.434 PE after removing insignificant PU from the final equation.

 

FINDINGS AND DISCUSSIONS:

Online shopping is a voluntary shopping using information technology as a medium. Therefore, acceptance of technology among customers is vital in a virtual environment. The research paper aimed to understand the effect of extended TAM variables; i.e. PU, PEOU and PE on RI. The results obtained help in understanding the influence of variables under study on RI by verifying the established hypothesis.

 

Research hypothesis H₁, which posited that there is a significant positive influence of PU on RI, is statistically rejected. The result is contradictory to maximum prior researches but similar to the research result of Ali (2016)¹⁵ which reported that PU has an insignificant negative (-.016) influence on RI. This finding suggests that PU is not considered while deciding to repurchase online. The probable reason for insignificant result might be more use of m-commerce. Online shoppers now have the application on their mobile and search online retailing sites for fun and time pass.

 

Research hypothesis H₂, which stated that there is a significant positive influence of PEOU on RI, was statistically accepted.  The result regarding PEOU is analogous to research results of Aren et al., 2013⁴; Chiu et al., 2009⁹; Rezaei and Amin, 2013¹²; Omotayo and Adeyemi, 2018¹⁴; Ali, 2016¹⁵; Chung and Lee, 2003¹⁹; Moeeini and Fard, 2014²⁰.In the present study, PEOU is the second most important repurchase determinant. In previous studies, in general, it was stated that easier technology is always easily accepted as compared to complex technology. Given this consideration, online retailers need to focus on making websites simple and easy to use to increase repurchase intention among experienced consumers from small cities.

 

Research Hypothesis H₃, which asserted that there is a significant positive influence of PE on RI, was statistically failed to reject. Result is in-line with Chiu et al., 2009⁹; Wen et al., 2011¹¹; Li, 2016¹³; Omotayo and Adeyemi, 2018¹⁴; Ali, 2016¹⁵;Chen et al., 2013¹⁷; Ashfaq et al., 2019²¹ ; Koufaris and Hampton-Sosa, 2002²³; Li and Zhang, 2002²⁴; Ramayah and Ignatius, 2005²⁵; Cheema et al., 2013²⁶; Tatang and Mudiantono, 2017²⁷. PE is found to be the most important factor in increasing the repurchase intention of customers. Therefore, marketers should work on making the online shopping process enjoyable.

 

Implications:

Based on the current research findings it is suggested that marketing strategies should focus on making online shopping enjoyable to minimize churn. To ensure enjoyment, online retailers should create an attractive website. Moreover, to enhance the shopping experience 3D webpage can be used which will give a feeling of offline shopping while browsing online.

 

Additionally, while planning website design purchase journey should be made easy to understand and simple to use. Online shopping is a process with different touch points. From landing to searching to completion the whole process should be made as simple as possible for ensuring RI. It is concluded that the need of an hour is user-friendly websites.

 

The paper contributes to the understanding of consumer behaviour of small cities like Shimla with a special focus on extended TAM variables among online shoppers with internet experience of four or more years. The present study also adds to the current literature of online retailing on how TAM variables affect RI among online consumers.

 

CONCLUSION:

The present study investigated the repurchase intention of small city customers from a technological perspective. The researcher concludes that technology is a crucial factor to continue with online shopping. The result of the study provides some useful insight. PE turns out to be the most important factor followed by PEOU in influencing RI among consumers of a small city like Shimla. However, the findings revealed that PU is not statistically significant in ensuring RI.

 

LIMITATION AND DIRECTION FOR FUTURE RESEARCH:

The limitation of this paper is that it is focused on technology-related variables only. In the present study, there is still a 65.4 percent variation in repurchase intention which is not related to TAM variables. So, future studies can extend TAM by adding other variables like products, services, security, subjective norms, etc. to make a holistic model of repurchase intention in online retailing. Past researches also emphasized the influence of PEOU on PU. Therefore, it is suggested to use SEM in the future to understand the complex relationships using multiple variables.

 

The second limitation to overcome is the general nature of present research. To overcome this, future research on the specific online retailer and product type is also recommended. The present research result suggested the insignificant influence of PU on RI. In future, researchers should examine reasons for lack of significant impact of PU which is an important utilitarian factor in online shopping. Lastly, to ensure generalization of research results, research with the same variables must be conducted in other small cities of India and outside India.

 

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