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Presently purchasing via the internet among consumers is growing promptly. In this twenty-first century, online shopping, in some way, has become a necessity for consumers, rather than just for special occasions. In addition, online shopping has created an added opportunity for the retailers to expand their business over the traditional method of conducting businesses. However, the retailers should understand and analyze the customers’ behaviour in purchasing, in order for them to achieve greater profit from their e-business. Besides studying the behaviour and trend of buying, retailers also have to consider investing amount of money in creating an effective and efficient platform, which is the World Wide Web, for them to run their business on the internet. As stated by Brohan , A typical online buyer spends about 30 seconds to go through a web site before they decide to click away or view the products on a web site (Brohan, 1999).
Online shopping will benefit consumers in a sense that, it could minimize time and cost spent on searching or browsing thousands of products compared to the usual way of shopping. Consumers will be exposed to wide selection of retailers in a time, where it gives greater control over products offered by each retailer. Besides, it will definitely reduce time and cost. Therefore, it is crucial for retailers to build an ongoing relationship with the customers by holding a web site that is able to sustain customers’ intention and also interest in browsing the products and eventually, to make purchases.
There are several factors that encourage customers to shop online, however, this paper will only focus on five main factors that influence customer’s online shopping behaviour:-
These five factors were chosen based on the previous academic research and reviews on related scholarly journals. Referring to an extensive research conducted in the last few (Davis, 1989; Yu et al., 2005), others concentrate on the users’ experiences and emotions. (Agarwal and Prasad, 2000; Fiore and Kim, 2007) and the last group focus on the importance of socioeconomic user attribute such as gender, age, education level, income and place of residence.
The trend of online shopping first started back in 1994. This new trend of selling and buying has caught retailers’ attention because of the recognition that shopping online will be considered as a new option of shopping besides the conventional physical retail stores (Chua et al., 2006). Most important, the internet has given great opportunities to businesses by providing an efficient platform to build a good relationship with customers. A good example as illustrated by The Economist 1997 edition is The Dell Online Store where they sells their products to consumers globally through their online shopping website (The Economist, 2007), and up until today, Dell has been one of the most favorable brand for computers and has been serving millions of customers via the online store.
Although there are many online businesses with success stories nowadays, a lot of companies, mainly the smaller one are still concerned about online business. The fear of venturing into online retailing or transforming their current business to online business existed mainly due to the fact that, the internet commerce is still somewhat new. Moreover, there are no tried and tested business models to be followed (Chua et al., 2006). It is crucial for businesses to have a good knowledge of the market for their products and services before venturing in online retailing. Furthermore, with a good knowledge and understanding of their customers, retailers will be able to develop a successful online business that will meet requirements and demands of their targeted online shopping customers. This paper will provide an explanation on five factors that has been studied to be related to the behavior of customers who shop online.
Trust relationship is commonly accepted as one of the most important aspects for countless successful organizations and companies (McAllister, 1995). It can assist companies in reducing lessening the transaction costs, improving their flexibility and efficiency, and also helping them in outlining their future marketing strategies and plans more precisely (Chen and Dhillon, 2003; Dyer, 1997; Gambetta, 2000; Nooteboom, 2003; Zaheer et al., 1998). Particularly, trusted relationship signifies that the truster is confident that the trustee will be concerned about his or her benefits, and when the result is not immediately available, the truster is agree to trust or count on decision of the trustee (Kini and Choobineh, 1998). In this online shopping context, it has also been argued by Nooteboom (2003) that trust is restricted to the idea that if users decide to trust one party, then they will lower their trust in the other parties. Hence, it can be assumed that trust could decrease the trusters’ interest in using services or products provided by the competitors of the trusted company (Gambetta, 2000; Zaheer et al., 1998).
Presently, trust relationship is not only existed between people and organizations, it could also be established between people and computing systems (Lee and Turban, 2001). It has been suggested by McKnight at al. (2002) that three important leading factors to the growth of trust relationship between customers and businesses or companies are:-
Safety of the online shopping environment
The company goodwill
The value and quality of the online shopping website.
He also explained on the three type of trust in relation to the e-commerce setting:-
Interpersonal trust; the web owner
Insititional trust; the online customers
Dispositional trust; own general trust
Trust in online business has been claimed regularly by several research and literatures (e.g. Ba et al., 2003; Hoffman et al., 1999; Keat and Mohan, 2004; Kim and Benbasat, 2003; Lee et al., 2006; Lee and Turban, 2001. Different researchers have discovered different ranges of theories and hypothesis on importance of trust and how it can be developed on the internet (Chopra and Wallace, 2003; Kini and Choobineh, 1998; Kong and
Hung, 2006), involvement of third-parties (Briggs et al., 2004; Cranor, 1998; Durkan et al., 2003; Yang et al., 2005) and in the protection of privacy parties (Pavlou, 2003; Tavani, 1999; Walters, 2001), and by this means, trust relationship possess a huge influence on online customers where they will decide to partake in e-commerce or not (Lee et al., 2006).
Kim and Prabhakar (2000) claimed that whenever the customer is the in the initial stage of buying products or using services online, the most crucial factor for success is the first trust in the seller and the website. Besides, customers are exposed to the possible risks that might be caused both by electronic systems and people. For example, staggered information due to the system failure, safety of payment made online and so on. All of these fears will increase the risk of online shopping and demode the customer’s interest in conducting shopping online.
Age is regularly associated with difficulty in processing stimuli (Morris and Venkatesh, 2000) and strongly linked with the amount of time needed by the inexperienced user to become familiar with the computers (Gomez et al., 1986). Therefore, as argued by Trocchia and Janda (2000), the lack of experience among the older people is the factor that prevents them from considering the advantages of the online shopping, thereby hindering their participation. According to some studies conducted in the IT field, younger group of people has been found to be savvier in computer skills (Czara et al., 1989; Hubona and Kennick, 1996). In addition, younger people normally have more experience with the internet and they considered usefulness and attitude as vital, whereas older people observe greater risk and measured perception of self efficacy as important (Morris and Venkatesh, 2000; Trocchia and Janda, 2000).
Basically these studies lead to a question whether age is not the factor which hinders the involvement or interest in online transaction or the lack of user experience that is commonly apparent among older group of people. Due to the skepticism towards the internet, older people are not keen to practice this new option. Assuming that an older person is able to overcome the barrier of first online purchase, most likely that he or she will perceive the benefits and the purchasing behavior will be similar to any other customers, regardless the age.
The impact of gender in decision-making and online shopping behavior has been a popular topic of in the marketing field. It has been examined with concern to the process of acceptance of new Information Technologies. It has been concluded that the usage of Information Technologies are differently evaluated between men and women (Gefen and
Straub, 1997; Venkatesh and Morris, 2000). As stated by Sun and Zhang (2006), there are three traits determining these dissimilarities:
Men are more pragmatic.
Women will face greater anxiety when encountered with new activities
Women are more heavily and easily influenced by their immediate environment.
Regardless of these differences, Eurostat suggested in their 2009 survey that number of women using the internet is increasing and the gender differences in this issue is decreasing. Furthermore, based on recent studies, no statistically massive differences between men and women have been found with regard to the usage of internet (Zhang, 2005; Shin, 2009). In one of the classic research has stated that gender-related dissimilarities are only apparent to the first anticipation of the activity, and it does not have effect on the actual usage (Deaux, 1984; Chen, 1985; Venkatesh et al., 2000). As stated by Chen (1985), as long as men and women hold similar levels of experience, they will have same interest in computers. Therefore, the arising of gender contrasts is pointed following the gaining of specific technological experience or the use of generally accepted Information Technologies (Shashaani, 1997; Kirkpatrick andCuban, 1998; Wong and Hanafi, 2007).
Income is considered as one of the variable that may encourage or restrain the use of e-commerce or online shopping. In addition, income is also another aspect that has drawn extensive research attention in the subject of technology acceptance (Serenko et al., 2006; Allard et al., 2009; Shin, 2009). Several studies have incorporated income as an explanatory variable of customer’s shopping behavior, however the results found to be contrast with its significance Miyazaki and Ferna´ndez, 2001; Raijas and Tuunainem, 2001; Lu et al., 2003; Al-Somali et al., 2009).
Customers with higher income is more likely to conduct online purchase as they perceived online shopping comprise of lower risks, whereas customers with lower income somehow disapproved online shopping due to the risk of financial losses. More often than not, income reflects ones professional standing or social class, whereby different professional group are come with different income and different level or experience in IT (Hubona and Kennick, 1996; Chau and Hu, 2002). Therefore, such categories might create various user behavior and approaches IT, particularly in online shopping.
This factor has a direct influence on the customer’s behavior and intention to shop online (Monsuwe et al., 2004). It is important to have a knowledge on how the past purchase experience affects customer’s buying behavior is crucial since they behaves in a different way compared to a new customers. However, there’s hardly any comprehensive research on the relation of past purchase and buying intention had been done, thus the relationship between these two entities are nevertheless vague.
For instance, is SP more significant to new customers who are unconcerned of an unknown website or it more crucial to the established customers who are prepared for full experience? The contrast between them might need different designs of social context. In addition, the barriers to entry might be higher in comparison to the potential threats of attrition and for that reason, investing in producing a supportive social circumstances for potential customers is extremely advantageous (Weisberg, Te’eni, Arman, 2011).
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