Consumer Buying Behavior - Essay Example

2. Literature Review 2 Introduction The planned timeline has been providing as a means of tracking the process of the research and making sure that the literature review is elaborately planned and finished according to schedule. (Kent, 2001). The aim of this chapter is to critically analyse, review and appraise the literature that falls within the domain of motivational factors and gender differences in online clothing shopping. In order to achieve this aim, this chapter is divided into a number of homogeneous and relevant areas; where academic and commercial literature within the topic has been discussed, represented, and analyzed. The synthesis at the conclusion of the discussion summarises the principal theories encountered, identifies which are relevant for the study, and articulates the research gap which the present research shall attempt to address. 2.2 Consumer Buying Behavior The interaction between consumers and businesses has changed significantly over the last few decades. One of the primary reason for this shift has to do with the macro and micro changes within the business environment; as these have played a pivotal role (Solomon et al, 2009). It is noted that this dramatic shift has been a key function of the lifestyle changes and the use of technology by contemporary consumers. Drawing upon Bigne et al. (2005), traditional marketing concepts as well as tools and techniques have been tested due to these changes; these have also been presented as a means of explaining, gauging and forecasting the behaviour of contemporary consumers. The key objective of B2C businesses is to increase their sales to add value for their shareholders (Solomon, 2010). The link between increased sales and positive consumer buying behaviour is the reason that it has been argued by Park et al. (2006) that this is an important indicator and the basis for the development of effective and efficient marketing strategies of the business. The term consumer buying behaviour is a complex phenomenon and it is defined in multiple ways. It is however stated that the common themes that underline these diversified definitions include: 1. Uniqueness of individual consumer expectations (Ali et al, 2010); 2. Preferences for multiplicity of options (De Pelsmacker & Janssens, 2007); 3. Propensity to switch brands for higher perceived value (Neuner et al, 2005); 4. Fulfilling or satisfaction of their perceived expectations (Cunningham et al, 2005). It has been further highlighted by Chiu et al. (2006) that consumer buying behaviour is about asking key questions. For example, one might engage with the questions of why consumers buy or how consumers buy and what influences their purchasing. There is a mix of internal and external factors surrounding consumers that helps shape and define their buying behaviour and preferences. According to Pelsmacker et al. (2006), these internal factors include: perceptual filter, knowledge about products, attitude towards the brand, personality of consumer, lifestyle of consumer, perceived roles of consumer, and their overall motivation for making the purchase. It is also distinguished by the fact that the external factors include: group or segment membership of consumer and purchase situation or cultures of consumer (Bell, 2011). For example culture is one of the most important factors affecting the consumer’s buying behavior; because the consumer’s preference will be according to their beliefs and backgrounds (Lai, 2005). However, both internal and external factors are interconnected and play a vital role for the consumer’s buying behaviour. This lends the reader to understand that a consumer’s choice and buying behaviour is localised and will not be the same among individuals and businesses need to understand how to target the consumers from a various backgrounds and lifestyles (Kim, 2004).The factors that have been mentioned help to identify the main reasons why people purchase products in general (Harper, 2005). However, an in-depth research is needed to identify the motivational factors that influence people to shop online. Another factor that needs to be considered is that these studies only researched the consumer buying behaviour in relations to all products; for example, Kim (2004) studied consumer’s buing behavior of groceries and electronics, excluding the goods such as clothing. 2.3 Motivations to shop online The high degree of penetration of the Internet and the advancements in its security and reliability has led to a dramatic increase in its use as the backbone of businesses and leisure. As such, e-commerce has become an essential distribution mix element for contemporary retail businesses (Teo & Yu, 2005). It is important to understand people’s motivations to purchase items online as the phenomenon of the Internet continues to be represented. It has not been fully recognized why an individual is likely to purchase online, especially when the same products are available in stores (Payne, 2002). There are number of features that have been stated by academics and practitioners between online and traditional shopping experiences. These have been identified to influence the consumer buying behaviour (Laforet & Li, 2005). It is noted by a great number of traditional consumer behaviour literature that the key motivation for consumers is to satisfy their needs; which develops and shapes their motivation and behaviour during the buying process. However, Doolin (2005) argued that in any consumer-buying situation, there are necessities that are shared by majority of individuals and there are desires that are localised and personalised to individuals. The related academic literatures helped to identify the main motivations of consumers to shop online and to support Doolins (2005) statement that individuals have the common motivations when it comes to online shopping. Perceived control in online shopping has been identified as the key motivator for consumers (Joines, 2003; Sorce, 2005; Roberstson, 2007; Hasan, 2010). Drawing upon Soopramanien & Robertson (2007), perceived control is defined as the overall influence of individuals on their environment and actions related to shopping. Those consumers who shop because of “control” that the Internet provides are comfortable surfing from site to site and taking time to choose the products to purchase. (Richard & Chebat 2010). A study by Wolfinbarger (2011) carried out the qualitative research and gathered people’s statements on how they feel about the online shopping. During the research most people in the group stated that the reason why they purchase products online is because they are in control of their search and decision as well as they feel less pressured to buy items than in the traditional store (Wolfinbarger, 2011). The preceding study supports the theory that online control is important for customers and they enjoy knowing how long they spend on searching and regulating how much time they devote for online buying. This study also showed that by carrying out the primary research and gathering qualitative data, the individual can identify reasons for motivatation of people to shop online and more personal information can be collected when communicating face-to-face with the participants (Fisher, 2004). Another reason why consumers prefer to purchase online has to do with the fact thatit provides high degree of choice to shoppers, where they can compare and contrast different aspects of the brands, products and services provided by the online businesses (Sorce, 2005). The study also showed that online consumers understand the importance and power of their feedback; which can be used to threaten and bargain with online retailers. It is noted that the high degree of information available to shoppers online to judge different aspects of the products that they are looking to buy elevates their perceived control of the situation (Shergill & Chen, 2005). Drawing upon Cheung’s (2005) study, the lack of interaction with sales people that can pressure consumers into making a purchasing decision quickly are not present in an online scenario, which makes it an important element for consumer to feel independent to buy items without any help. The following studies have used the quantitative research to gather their information. The main advantage of this type of research is that it includes the ‘Likert scale’. These are questions that would benefit to gather greater amount of data and measure the strengths of feeling such as ‘strongly agree’ or ‘disagree’ of the participants about the online motivation. This can help to recognize the pattern in people’s answers, which can lead to identifying what motivations play the key role in online shopping behavior. Further, the intrinsic enjoyment of the online shopping experience has also been noted as a key motivator for shoppers to prefer online rather than offline shopping experience (Holzwarth et al, 2006). During the evolution of the Internet as a platform for retailing, it has been popularly believed that offline shopping is enriched due to the physical and human interaction, which is replaced by two-dimensional and computer oriented online world (Schlosser et al, 2006). It is however stated, by contemporary academics such as Holzwarth (2006) that the online shopping experience has developed over time to become an enjoyable platform for shoppers; where a number of different dynamics play an important role. It is argued by Bigne et al. (2005) that online shopping is not restricted by timings, weather or other adverse conditions of physical world and the shoppers are able to concentrate on their shopping experience rather than being distracted by other externalities. More recent studies found that both convenience and recreation play an important part in consumer’s motivations to shop online (Bailey, 2008; Richard, 2010). In addition, numerous studies have supported that convenience plays a significant role for consumers to shop online (Joines et al.,2003;Widrick, 2005;Dennis,2007). The perceived usefulness and ease of use for online shopping in comparison to traditional offline shopping has also been noted as the key motivator for the shoppers. Drawing upon Chiu et al (2006), technology acceptance model has its implications on highlighting the fact that perceived ease of use if dependent on alignment between technology-task-individual. It is argued that using internet and computers have become user friendly with the development of interactive devices like tablets and smart phones. The task of shopping online has become increasingly secure and reliable (Park & Kim, 2009). Lastly, contemporary individuals have higher technology competencies and skills that are useful for effective and efficient online shopping (Pelsmacker et al, 2006). It can therefore be argued that technology-task-individual have high degree of alignment between each other, which is the reason for very high degree of perceived ease of use of online shopping. It is also noted by Chang (2005) that online shopping is perceived as efficient due to the fact that less time is consumed in comparing and contrasting the products and more information regarding the products can be collected without a high level of resource input. However, the preceding study did not focus on the gender differences nor the younger generation. Therefore, the research needs to analyse if those motivations are applicable today and can be applied as the motivations that influence student’s online purchasing. 2.4 Demographic Differences in Motivations to Shop Online As compared to the other studies and approaches which have thus far been referenced, there are far fewer studies that research the gender differences in online shopping behaviour (Kim, 2004). Little is known about the demographics of online consumer and even less is known about the motivations that influence the purchase decision. However, drawing upon Riedl et al. (2010), demographic variables are important and should be counted as the first layer in defining homogeneous groups and segments of the markets; which have similar attributes and characteristics within buying behaviour. It has been argued by Dittmar (2005) that demographic differences exist within traditional offline shopping consumer buying behaviour. These differences have been tested within the online setting and a number of predicators have been found that can be seen from the choices made by men and women during their shopping behaviour in online settings. It is noted that the male internet penetration within OECD countries among men have increased by more than 60% in last ten years, while for the same duration of time internet penetration among women increased by more than 200% (Hernández et al, 2011). It has been noted that due to this jump within women online users the demographics within OECD countries have balanced the two genders. It is argued by Soopramanien & Robertson (2007) that although the internet penetration gap between the two genders has narrowed, however there remains differences in terms of their attitude and activities online. It is argued that traditional research has highlighted that women are less likely to use internet for shopping as compared to men (Doolin, 2005; Utz, 2011; Bailey, 2007). It has additionally been noted that women are likely to spend less time online as compared to men, which implies that women are likely to use internet shopping in a very similar pattern as traditional high street shopping (Van den Poel & Buckinx, 2005). There are number of studies that have argued based on empirical investigations that women are less likely to buy online as compared to men (Bruwer & Wood, 2005). It is also stated by the study conducted by Sorce et al (2005) that women on average spend less money online as compared with their male counterparts. It should be illustrated that this behaviour, though changing, still provides an useful observations; due to the fact that in traditional shopping settings, women account for more than 70% of overall shoppers (Yang, 2005). Gender-based differences were also sought on how consumers perceive the quality of online services as such perception is determinative of the overall online shopping experience that influences shoppers’ attitudes and behaviours (Zhang, et al., 2012, p. 639). On this topic, Sebastianelli et al. (2008, p. 445) observed the existence of gender-based differences in online shoppers’ perception of seven electronic retailing quality dimensions: reliability, accessibility, ordering services, convenience, product content, assurance, and credibility. The most significant finding exhibited within the preceding research was that women placed greater significance than men on the qualities pertaining to assurance, relating these to trust, privacy, and security (Kim, et al., 2013, p. 377-378). This is consistent with the findings on shopping orientation (shopping confidence in Seock and Bailey, 2008, Nirmala and Dewi, 2012, Yi-Wen and Yi-Feng, 2012, and Awad, & Ragowsky, 2008) as well as the finding of greater risk aversion among women by Bae and Lee (2008). Women were found to evaluate assurance in terms of four dimensions: (1) privacy policies in the home page, (2) availability of online help or toll free number, (3) no bad links, and (4) security of orders (Sebastianelli et al. 2008, p. 445). The findings revealed that women have a constant need to research new trends and seek assurance in an online retailer’s website, or those elements that contribute to greater shopping confidence (Sebastianelli, 2008) The following research into the scope of gender differences helps provide potential research subject matter and their analysis format supplies insight into how a more topic specific study can be organized. However, the studies lacked the focus of what are the gender differences when it comes to purchasing clothing products online. Therefore, due to the absence of academic research on those specific products, it is useful to identify the key motivational differences among males and females in fashion sector. The increased demand of online clothing shopping has increased which suggests that both genders are the constant buyers of clothing items online. This suggests that females might be more comfortable with the internet security and trust the internet with purchasing than before. This also shows that the studies are inconsistent with findings that women don’t shop online as much a men due to importance of social contacts and security issues (Bailey, 2008; Hassan, 2008; Dewi,2012; Yi-Wen, 2013). However, by means of contrast, Robertson (2007) said that the gender online gap has vanished and women prefer online shopping to the same level as to men. This supports studies that state that females, just like males, perceive online shopping as less risky than men did several years ago (Dennis, 2007; Payne, 2002). Therefore it is important to carry out further research to find out what are the gender differences in online shopping motivations today, and if the previous findings are relevant in 2014. 2.5 Student Online Shopping Motivation Only a few studies have researched the student’s motivations in online shopping. As such, the research is particularly important due to the lack of the investigations; especially when the students are becoming the important consumers of fashion products online (Baldwin, 2014) A survey-based study by Kim (2004) that researched on predicting online purchase intentions has predicted that the younger generation will become the core consumer base for online fashion retailers in the near future. This study has suggested to carry out further research, concentrating specifically on younger consumers and analysing their general shopping behaviour, as well as to identify the main motivations that influence their online purchase behaviour. This is especially important in light of new innovations; such as virtual dressing rooms that keep attracting young buyers and encourage them to shop online. Numerous studies have showed inconstancy in findings, particularly in student’s online consumer behavior (Foulcault, 2002; Bailey, 2008). It has been argued that there are number of characteristics of students that set them apart from the rest of the market (Chiu et al, 2005). Students are seen as unique market segment that have less disposable income than other market segments. Additionlly, they are seen as early adopters for new technology and fashion. In contrast, Foulcault (2002) showed the opposite results that students lead a “wired lifestyle”; comparing to the rest of the market. Ultimately, Foucalt found that students tend to spend more time surfing and researching the product on the internet for products which results in purchasing online more. Bailey (2008) has supported Foulcault (2002) study and noted that students motivated to shop online because it provides a deep amount of information about the products, and they feel comfortable buying the products after spending a high amount of time researching; concluding that students most likely to purchase on the internet due to their willingness to spend time surfing online and researching the information about the products they want. Little is known of what motivates the younger generation to shop online. According to Bigne et al (2005), the perceived ease of use of the internet is the highest among students as compared to their professional counterparts. It has been observed that universities and colleges are at the forefront of technology development. Thisis one of the key reasons for the requirement and technology uptake by students. On the other hand, due to the limited disposable income and high individualistic requirements, students have an increased sense of achieving effectiveness and efficiency within their purchasing behaviour. One of the limitations of their study was that the survey looked at a broader range of items and interests other than clothing and so did not track the specific concerns of the present line of investigation. (Bigne, 2005). Due to the limitation of findings in the literature regarding the gender differences amongst students in online shopping behaviour, further research into this area would help to provide a greater level of clarity. Only one of the few studies that specifically looked at student’s gender differences when it comes to online shopping is the study by Hung (2010). This was a survey based study and revealed through the numerous t-tests calculations that gender differences do exist and that males tended to be more utilitarian (practical motivation) and females were more likely to have hedonistic (pleasure and fun) motivations (Jen-Hung & Yi-Chun, 2010). However, this study consists of limitations such as, the generalisation of this research is disadvantage since the research was only carried out in Taiwan and likely cannot be effectively applied to the a broader demographic (Grant, 2012). Another limitation is that it contradicts the research by Joireman et al (2010); who stated that gender differences are less pronounced among younger students as compared to their older professional counterparts. Therefore, due to the inconsistencies of the findings and the lack of ancillary corroborating studies, this report will concentrate to fill in the gap and investigate the student’s online motivations and how different the gender consumer behaviour towards online shopping in the present day. 2.6 Summary The literature has argued that clothing online shopping has different characteristics than traditional shopping, which should be understood by the fashion retailers to achieve effective and efficient results. It has been contended that students are more tech-savvy and are among the early adopters of key technologies, which is the reason that their motivations for using online shopping for clothing items have been found important for the development of the topic. The gender differences of student’s shopping motivations online is also an important element to research. Particularly when a study by Joireman (2010) noted that there is no gender differences among younger buyers, which contradicts numerous studies that argue that gender gap exist in all aspects of everyday life, especially in online consumer behavior (Robertson, 2007; Bailey, 2008; Hassan, 2008; Dewi, 2012; Yi-Wen, 2013). Results from the research indicate that the key motivations that influence people to shop online are; degree of information and choice, convenience, control, lack of social interactions, enjoyment, range of styles and home tendency (Jones, 2003; Swaminathan, 2004; Kim, 2004; Chen, 2005; Sorce, 2005; Dai, 2007; Bailey, 2008; Zemblyte, 2009; Richard, 2010; Punj, 2011; Dewi, 2012) The previous literature has helped to identify the direction of the research and construct the questions for the primary research. For example, the main motivations that have been recognized by the previous research, such as convenience and degree of information, will all be included in the data gathering to find out if those motivations are relevant today. However, even thought the researchers deeply looked at what motivates consumers to shop online, only a few studies targeted the younger populations. Therefore it is important to carry out the research to identify if these key motivations to shop online affect the younger buyers. The numerous studies showed (Source, 2005; Schlosser, 2006; Bailey; 2008, Park, 2009) that it is important to carry out the qualitative research to understand people’s feeling about the online shopping. However, the quantitative method can help to gather a higher level of data, therefore the mixture of both methods would provide a greater and in-depth answers for the research (Kent, 2011) The previous studies have all carried out the primary research and showed that both quantities and qualitative techniques are essential when gathering participant’s opinions and attitudes towards online shopping. The high pattern of use of ‘likert scale’ to collect the levels of satisfaction of participants towards the online shopping can be identified in most of the previous studies. (Table 1) Therefore, the primary research with the questionnaires and interviews need to be carried out in order to identify how relevant are the previous studies for today’s generation and what have changed in student’s motivations towards online shopping and if the online gender gap still exists. Read More