Consumer Behavior Factors In Online Shopping

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Online shopping is a prevailing trend in the society, and it is growing rapidly nowadays. It has greatly changed people’s lifestyle, without stepping out the door, we can buy all kind of goods from all over the world. Nowadays, people would prefer online shopping rather than online shopping due to the convenience brought, especially generation Y, they gradually replace their shopping habits from window shopping to surfing the internet. Many retailers have foreseen this e-commerce opportunity and developed branches and shops exclusively for online shoppers for example Instagram shops, eBay, Amazon, etc. Online shopping involves in social, technological, economical and behavioral dimensions which provides different kinds of factors to drive the consumers. This study plans to present a theoretical explanation and to explore the relationship between consumer behavior and online shopping.

Keywords: Subjective Norm; Perceived Usefulness; Purchase Intention; Consumer Behavior; Online Shopping; Theory of Planned Behavior; Technology Acceptance Model

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1. Introduction

Nowadays, internet owns most of the time in people’s daily life, smartphones, computers, laptops, iCafe, etc. We can access to the internet anytime anywhere with these gadgets. According to the Digital 2019 (We Are Social & Hootsuite, 2019) report, it shows that people are spending an average of 6 hours and 42 minutes online each day. Half of the time people spent on the internet are on mobile devices. It shows that internet has already taken a large role in our lives. Internet has changed our lifestyles, especially in shopping behaviors. People starts shopping through the internet, enjoying the benefits of one stop purchase, simply with one click, we can shop groceries, clothing, electronic supplies, accessories and even auto parts. It can be totally feasible to never leave your house but having all the necessities you need to be delivered to your home. In 2018, 1.8 billion people worldwide purchased goods online (Statista, 2018) while global e-retail sales amounted to $2.8 trillion. The research also shows that the global e-retail sales are having an estimated growth up to $4.8 trillion by 2021. We can foresee a potential growth and it will not be slowing down in the upcoming years. Repeated customers also contributed a lot in the online sales, regarding to the frequency of consumers spending time on online shopping, the research shows a very often purchases for consumers, 62 percent of online consumers shop at least once per month. While 26 percent of online consumers shop once a week, and it even shows that 3 percent of online consumers claim to shop once a day. With so many people shopping online regularly, or looking for products to buy online, it provides opportunities to many e-commerce business, however, indecision due to mass information becomes a challenge to online consumers, where 46 percent of them have failed to complete a purchase online because there were too many options to choose from. How business can grab these left out customers and examining the factors contributing on consumers’ behavior in online shopping becomes a question of thought. Today, online consumers have more control and bargaining power than consumers of physical stores. The Internet offers more interactivities between consumers and product or service providers as well as greater availability of information about products and services. Consumers expect to see new products constantly. A research has received a result of 75 percent of consumers have brand new search queries each month (Salesforce, 2018). It shows that when people are browsing the internet, they are actively searching for new products, this phenomenon appears most commonly in clothing items which people tends to look for new products due to seasonal factors. Among these consumers, 69 percent agrees that it’s important or very important to see new merchandise each time they visit an online store or shopping site. E-commerce businesses need to keep up with the needs of consumers. Retailers have to provide updated information as much as they could. The ecommerce industry is more dynamic than ever before, therefore, understanding factors behind online consumers are important. As Generation X is predicted to have $44 billion in buying power, dominating 40% of all consumer shopping. Also, 95% of Generation Z owns a smartphone, which they spend almost 10 hours or more per day on, and 85% of them surf the social media for learning about new product feeds, so they are two times more likely to shop on the internet than millennials. (Ouellette, 2019) Therefore, this research is primarily to examine factors that could influence universities students’ online shopping behavior in online shopping in Hong Kong.

2. Literature Review

2.1 Subjective Norm

Subjective norm is defined as an individual’s perception or ‘opinion about what important others believe the individual should do’ (Finlay, Trafimow, & Moroi, 1999) Subject norms affects the way people feels about the values or believes that most people mutually agree with in the society. Subjective norms are represented by normative beliefs are located within the broader construct of social norms, a social norm is usually referring to a specific behavioral act the performance of which is expected or desired under the given circumstances. (Ajzen & Fishbein, 1972) However, there shows no direct relationship between subjective norm and consumer behavior, (Ajzen, 1991) personal considerations tend to take over the influence of subjective norm. A study (Jamil & Mat, 2011) also suggested that subjective norm does not directly influence the actual purchase of consumers through the internet but on the other hand claimed that it still has a significant effect on online purchase intention before performing actual buying. Although subjective norm may not be the most significant factor of online shopping, it still shows the importance in driving one’s buying desire. A research (Talal, Charles and Sue, 2011) shows that social influences result from subject norms, which can be related to consumers’ perceptions of the beliefs of other consumers especially to the people they know and considering subjective norms only provide marginally significant contributions on online shopping intentions, while another research (Foucault & Scheufele, 2005) proven that there is a significant link between influence by friends and intention to e-shop.

2.2 Perceived Usefulness

The second variable is perceived usefulness, which is defined as peoples tend to use or not an application to the extent, they believe it will help them perform their job better. (Davis, 1989) Referring to online shopping, which means the feelings of consumers that the online website could add value and efficacy to them, it is also the individual’s point of view that by using a system would improve task performance. The perceived usefulness of the landing page greatly affects the perceptions of users, by providing the efficiency of technological characteristics especially in personalized service like real-time personal chat-box, and various information and high-quality goods’ descriptions which allowing customers to be well informed and making decisions easily (Kim & Song, 2010). The above research also proven that perceived usefulness have significant impact on the intention to purchase via internet. Perceived usefulness advocated that consumers expectations in receiving useful information and convenience for purchase. The research also suggest that online shoppers will have greater chance shifting to business competitors since similar products can be found easily on other e-commerce platform (Kim & Song, 2010).

2.3 Purchase Intention

Purchase intention refers to the decision of consumer to act for purchase a specific product after evaluation in future. (Ramayah, Lee & Mohamad, 2010) It indicates the willingness of people to perform a certain behavior, it also carries the motivational components of consumer that will influence consumer behavior, and most probably influencing the actual buying. When consumers have the intention to purchase, they have higher likelihood in gathering information, making comparisons and making decisions online. (Kotler & Armstrong, 2010) Purchase intention is most likely drive by four criteria including online trust, web experience, electronic word-of-mouth, and brand familiarity. (Tan, Yap, Lim, Ng & Kian, 2010) Purchase intention has been regarded as a significant factor of actual online shopping behavior and a few studies show that there is significant relation between consumer purchase intentions and online shopping behavior. (Lim, 2016; Lim, 2015)

2.4 Theory of Planned Behavior (TPB)

The Theory of Planned Behavior is the extension of the Theory of Reasoned Action. (Ajzen & Fishbein, 1980) The TPB model provides a better explanation of behavioral and assumption on people’s will to perform certain behavior if that person has actual control over the behavior (Ajzen, 1991), in TPB model, it defines the behavioral actions depends on both intention and control of behavior. The TPB comprised six constructs including attitudes, behavioral intentions, subjective norms, social norms perceived power and perceived behavioral control. (LaMorte, 2019) In general, the level of the above constructs is attained, the greater they are, the stronger people’s intention to drive themselves into online shopping.

2.5 Technology Acceptance Model (TAM)

Technology Acceptance Model is an emerging framework to access people’s acceptance to new technology, with primary factors measuring individual’s intention to use new technology including perceived ease of use, perceived usefulness and intention and the influence of attitude. (Davis et al., 1989) As the influence of attitude is not significant, the TAM model usually is demonstrated as a mediator to influence the relationship between perceived usefulness, perceived ease of use and usage behavior. (Venkatesh & Davis, 2000) This model has proven that perceived ease of use and perceived usefulness are the two major determinants to influence the variables.

3. Research Model and Hypothesis

3.1 To Investigate the Effects of Subjective Norms in Online Shopping

There are diverse views in the effectiveness of subjective norms as a consumer behavior in affecting online shopping. However, a mutual agreement on subjective norm is that it is definitely one of the factors. Subjective norms can give consumers an impression on a certain product or services, for example, when the consumer is considering buying a smartphone, they see that most of the people in his/her social circle use iPhone, they will most likely purchase an iPhone. Increasing usage of social network sites, such as Facebook, Instagram, and Twitter have emphasized on users’ point of views and comments, the development of Key Opinion Leader (KOL) industry has the ability to create subjective norms and made these subjective norms more persuasive. (Al-Swidi & Hafeez, 2014). As generation Z and Millennials are major users in social media, they are easily influenced by subjective norms which their consumer behavior will likely to be affected. Hence, the hypothesis is as follow.

H1: Subjective Norms provides positive effect in purchase intention

H2: Subjective Norms provides positive effect in consumer behavior

3.2 To Measure the Effects of Perceived Usefulness in Online Shopping

Perceived usefulness provides information on users’ feelings based on their experience on a certain technology. Applying this definition to online shopping, perceived usefulness refers to the degree of consumers point of view to the Internet as a medium will help to improve their shopping experience. During the process of online shopping, users will encounter different stages, like searching for information, comparisons, add to cart, payment and delivery. Perceived usefulness plays a great role in these stages, it will affect the willingness of users to whether continue their shopping or not. (Khalifa & Limayem, 2003; Shim, Shin, & Nottingham, 2002). In short, perceived usefulness is related to the outcome of the shopping experience. Hence, the hypotheses is as follow.

H3: Perceived usefulness provides positive effect in purchase intention

H4: Perceived usefulness provides positive effect in consumer behavior

3.3 To Measure the Effects of Purchase Intention in Online Shopping

Purchase intention often viewed as the major contributor in consumer behavior. Purchase intention is the initial feeling of the consumers toward a product or service, often deeply rooted in their mind and not easily get changed. A few variables are the factors of purchase intentions, including online trust, web experience, electronic word-of-mouth, and brand familiarity. (Tan, Yap, Lim, Ng & Kian, 2010) which happens to directly influence consumers’ behavior.

H5: Purchase intention provides positive influence consumer behavior

4. Research Design

4.1 Data Collection

The population we wish to study is universities students in Hong Kong. With the aid of Academic Registry and Business School, we will have a sampling frame of Hong Kong Baptist Universities students. Questionnaires will be sent to students through email. We will apply both probability and non-probability sampling. For probability sampling, we will apply simple random sampling, which all possible subsets of a sampling frame are given an equal probability of being selected. For non-probability sampling, we will apply convenience sampling and snowball sampling. For convenience sample, it is a technique in which a sample is drawn from that part of the population that is close to hand, readily available, or convenient. We will give out questionnaire to Business School students and also students who live in hall of residents. For snowball sampling, we identify respondents who are universities students in Hong Kong and through recommendations, the questionnaires will be sent to their friends who are also universities students in Hong Kong.

4.1.1 Questionnaire Design

This questionnaire will be conducted in both English and Chinese versions to facilitate people with different language needs. We will adopt a closed format questionnaire to facilitate us to collect data and keep the questionnaire easy and quick to complete. (Gault, 1907) The questions will be arranged according to the dependent and independent variables, and logically arranged according to the sequences.

4.2 Pilot Test

Pilot test will be arranged to test the validity of the questionnaire. We will select 20-30 respondents to conduct the pilot test. The purpose of pilot test is to evaluate whether the questions will achieve the desired results, placed in the best order, understandable by all respondent, additional or specifying questions are needed, should some of the questions be eliminated and the instructions are clearly provided and adequate. (Crawford, 1990)

4.3 Working Schedule

The questionnaire will be designed in January 2020, and the pilot test will be conducted in late January 2020. The revised questionnaire will be conducted in February 2020 and the data collection process will last for 1 month. The final analysis of data will be conducted in March 2020.


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