A Study of Public Perception towards Teleshopping

Transcription

1 4.1 Introduction The purpose of this chapter is to review the literature associated with teleshopping perception and factors/variables influencing teleshopping intention. The chapter is organized into six sections. The review of theories being used in literature associated with teleshopping are discussed in section 4.2. The research on factors/constructs/dimensions influencing teleshopping intention of consumers is described and discussed in detail in section 4.3. This is followed by section 4.4, which summarizes the major findings of the literature. Section 4.5 identifies gaps in the previous literature. And section 4.6 describes research questions and objectives of this study. 4.2 Review of Theories being used in literature and associated with teleshopping/e-shopping intention Several models and theories have been proposed for the purpose of understanding consumer teleshopping intention. We have found that some theories have constantly being used by various researchers in different contexts. These theories and their use in existing literature has been described as follows: Theory of Reasoned Action TRA is a general well-researched intention model that has been applied extensively in predicting and explaining behaviour across many domains and virtually any human behaviour (Ajzen and Fishbein, 1980)in both online and offline context.. Information system researchers often use this theory to study the determinants of IT innovation usage behaviour (Suh and Han, 2003). Although current models of technology acceptance have their roots in many diverse 57

2 theoretical perspectives, much literature related to technology acceptance begins studies with the Theory of Reasoned action (TRA). This theory provides a framework to study attitudes toward behaviour. According to the theory, the most important determinant of a person's behaviour is behaviour intent. The individual's intention to perform behaviour is a combination of attitude toward performing the behaviour and subjective norm. The individual's attitude toward the behaviour includes; Behavioral belief, evaluations of behavioral outcome, subjective norm, normative beliefs, and the motivation to comply. (Ajzen and Fishbein, 1980) In teleshopping context, it is observed that consumers normally form attitudes that influence purchase intention to buy products though the use of television. Therefore, tele usage and attitudes towards products teleshopping are strong predictors of the intention to purchase products from teleshopping (Salisbury et al., 2001; Eagly and Chaiken 1993). According to Theory of Reasoned Action the behavioral intention leads to behaviour and also that it determines consumer s attitudes toward purchasing or using a brand by influencing the normative value or subjective norm (Fishbein and Ajzen, 1975). In this theory, socially relevant human behaviours are under the control of the individual and the most direct powerful predictor of a behaviour is the intention to engage in that behaviour. Chung and Pysarchik (2000) has found TRA useful in predicting consumer s behavioral intention formation for a variety of consumer products such as fashion, slim tea, air sofa, yantra, multipurpose ladder and sliming instruments. Cho (2004), Chuchinprakarn, S. (2005) and Verhoef and Langerak (2001) adapted the TRA to study tele-shopping behaviour. Specifically, Cho assumed that attitude toward teleshopping is determined by perceived consequences associated with teleshopping, past behaviour and attitudes toward other shopping channels and that likelihood to abort an intended teleshopping transaction is jointly determined 58

3 by these three dimensions as well as the intention toward for teleshopping. Verhoef and Langerak (2001) who employed the TRA in a study found that outcome beliefs had a significant influence on the intention towards teleshopping. The perceived benefits of teleshopping in relation to traditional store shopping are one of the attributes are positively related to attitudes to tele shopping. In these two studies, subjective norm was not considered as a determinant of behavioral intention, in keeping with its less well-understood status (Fishbein and Ajzen, 1975). Chuchinprakarn, S. (2002).proposed four constructs in basic TRA theory to explain consumer behavior in teleshopping context. The first two constructs, i.e., trust and confidence in using a credit card, were considered elements of the attitudinal component. The subjective norm (i.e., the influence of friends) was considered a third construct. The fourth construct was past behavior, which was considered an additional element added to the TRA model by previous researchers. These four constructs were predicted to directly affect the intention to teleshop. In addition, it was also predicted that confidence in using a credit card would moderate the effects of trust and subjective norm on the intention to shop teleshop. Adapna S. (2008) used TAM and Diffusion and Innovation of theory to identify cultural consideration in India and Australia in adoption of online shopping, explored that intention of tele shopping, as measured with the perceived attributes, significantly influences the actual adoption of online shopping Theory of Planned Behavior Ajzen (1985) extended the Theory of Reasoned Action (TRA) to account for other conditions, where individuals do not have complete control over their behaviors. Similar findings are also evident in the research of Liska (1984) and Shappard, Hartwick and Warshaw (1988), who argued that TRA does not adequately deal 59

4 with behaviors that require resources, cooperation, or skills. Kuo and Young (2008) also found that TRA-based study shows a severe limitation in the ability of the intention to predict actual knowledge sharing behaviors. In order to reduce these limitations, incorporated an additional variable of perceived behavioral control into the model of reasoned action and called this new model, the Theory of Planned Behavior (TPB). The Perceived behavioral control refers to an individual s perception of how difficult it is for her to perform a behavior (Ajzen, 1991). The TPB postulates that an individual s behavioral performance jointly relies on and can be predicted by her behavioral intention and perceived behavioral control. Theory of Planned Behavior suggests that intentions and facilitating conditions are the direct antecedents of behavior and at the same time, behavior is also affected by habitual arousal. This extended model has a strong ability to predict behavior, even though it suffers empirically from multi-co linearity among independent variables employed in the model. TPB has been used in many different studies in the information systems literature (see Mathieson, 1991; Taylor and Todd, 1995, Harrison et al, 1997). TRA and TPB have also been the basis for several studies of Internet purchasing behavior Battacherjee, 2000; George, 2002; Jarvenpaa and Todd, 1997; Limayem et al, 2000; Pavlou and Chai, 2002; Suh and Han, 2003; Song and Zahedi,2001; Tan and Teo, 2000). Empirically, Hansen et al. (2004) applied both TRA and TPB. The researcher found that TPB, with an additional path from subjective norm to attitude, explains a higher proportion of variation in online grocery purchasing intention than does TRA. Choi and Geistfeld (2004) used perceived risk and perceived self-efficacy to measure the individual s attitude and perceived behavioral control, respectively. Limayem et al. (2000) augmented the TPB with two additional constructs: perceived consequences and perceived innovativeness. These two constructs were 60

5 assumed to influence both attitude and behavioral intention. In their models, subjective norms were evaluated by an individual s perception of the opinions of her family, friends, and media; and behavioral control consisted of site accessibility, product description, transaction efficiency, navigation ability, speed, and efficiency. Shim et al. (2001) adapted the TPB by incorporating the influence of past behavior and ignoring the attitude toward the behavior. They found that intention to use the television for product information search acts as a central mechanism through which consumer characteristics affect higherorder decision-making goals. In order of salience, consumer characteristics including previous tele purchase experience, perceived behavioral control, and attitude toward tele shopping all had indirect effects on intention to use the television for purchase. Paulov and Chai (2002) in corporate theory of planned behavior (TPB) with Hofstede s (2001) cultural dimensions (individualism/collectivism, power distance, long term orientation) to understand the determinants of tele-commerce across cultures. In their empirical study they observed that cultural differences play a significant role in consumer e-commerce adoption. Su, and Huang (2010), in their study of online shopping intention of undergraduate consumer in China explained that online shopping intentions are greatly influenced by price of goods and the students knowledge on computer and online currency clearing. Khalifa, et al. (2000) developed a model explaining the impact of different factors on non-store shopping intentions and behavior and found that subjective norms, attitude, and beliefs concerning the consequences of non-store shopping have significant effects on consumers' intentions to buy from teleshopping. Behavioral control and intentions significantly influenced teleshopping behavior. Gyan, N. 61

6 (2010) used decomposed TPB to understand the behavioral intention of Indian consumers and argued that cross cultural factors behave as a moderator to understand the relationship between the preceding factors and behavioural intention. Khaled and Bhohrai (2012) used theory of Planned Behavior (TPB) to figure out the description about mobile traveler behavior among postgraduate students in Malaysia and observed that relationship between attitudes towards behavior, subjective norms and perceived behavior control contribute were positively related to actual usage mobile traveler as hypothesized. The positive association between independent variables attitude towards behavior, subjective norms and perceived behavior control to the actual usage of student was supported The Technology Acceptance Model (TAM) The technology acceptance model (TAM) (Davis,1989); Davis et al., 1989) is also an extension of TRA, and was developed to predict technology acceptance, which can be conceptualized as an individual s psychological state with regard to his or her voluntary or intended use of a particular technology. TAM proposes that the two most important variables in explaining attitude towards system using intention are perceived ease of use (i.e. perceived complexity) and perceived usefulness. However, TAM can be modified to predict consumer teleshopping intention (Shih, 2004; Keen et al., 2004; Liu and Wei, 2003). For example, perceived usefulness can be conceptualized as the degree to which teleshopping will provide the consumer with some relative advantages in comparison to offline shopping (Gahtani SA, 2001). Also, TAM has been extended to include personality, web experiences, and perceived compatibility as possible influencing factors on consumer tele shopping adoption (O Cass and Fenech, 2003). Recent evidence, which is based on a modification of the TAM approach, suggests that both perceived usefulness and perceived ease of using the television for shopping 62

7 purposes have positive effects on consumers intention to adopt teleshopping. Liu and Wei (2003) also found that perceived usefulness and perceived ease of use (along with another variable: perceived risk) explained more than 50% of the consumers intention to adopt teleshopping for books and spiritual items. Drawing upon the TAM model, Childers et al., 2001 empirically demonstrated that research investigating consumer motivations for teleshopping behaviour may benefit from taking into account the hedonic aspects (e.g. shopping enjoyment and/or fun) of the shopping experience along with the (more utilitarian) constructs of perceived usefulness and perceived ease of use. Extending on TAM theory Noor R. Ab Hamid (2008) found that perceived risk determines consumer level of technology adoption. Technology usage experience is imperative in shaping and to some extent, reduces perceived risk. Certainly, as consumers watches the demonstration of product on television he comes to know various dimensions of use of items, knowledge about the advantages as well as disadvantages of the technology accumulates and educates the consumer about the quality of product. Venkatesh (2000) already suggested integrating additional factors like control (computer self-efficacy), intrinsic motivation (computer playfulness), and emotion (computer anxiety) into the existing technology acceptance model. These factors are proposed to act as significant determinants for ease of use, one of the basic constructs of TAM. Dabholkar and Bagozzi (2002) added the influence of two other exogenous factors, e.g. consumer traits and situational influences to the TAM framework, resulting in an attitudinal model of technology-based self-service. Similar, O Cass and Fenech (2002) have extended TAM by adding seven key consumer characteristics: opinion leadership, buying impulsiveness, satisfaction with Web sites, Web shopping compatibility, shopping orientation, Internet self-efficacy, and Web security. Monsuwe, et al. (2004) added five exogenous factors into TAM for understanding consumers intentions to use the Internet as a shopping medium: 63

8 consumer traits, situational factors, product characteristics, previous online shopping experiences, and the trust in online shopping. On the basis of above literatures following factors were identified for further study of teleshopping perception these factors are Product and Company Attribute, Perceived Risk, Perceived Benefits, Consumer Experience, After Sales Service and Purchase Intention The Theory of Adoption of Innovations Other authors have proposed that Internet shopping/teleshopping should be regarded as an innovation, which like other innovations takes time to spread through the social system (see Alba et al., 1997; Verhoef and Langerak, 2001; Chau and Hu, 2001; Sultan, 2002). The adoption of an innovation depends on various factors (including perceived compatibility, perceived relative advantage, perceived complexity, trialability, and observability), that are related to the innovation itself and to the consumer (Rogers, 1983). The diffusion of innovations concerns the spread of a new service from its source of invention to its ultimate adopters (Verhoef and Langerak, 2001; Gatignon and Robertson, 1985), whereas the consumer adoption process focuses on the mental process through which an individual consumer passes from first hearing about online grocery shopping to final adoption. The theory of adoption of innovations shares some important characteristics with the TAM model. Although the TAM model does not include all the constructs proposed by Rogers (1983), it does include two constructs, perceived usefulness and perceived ease of use, which are quite similar to the constructs perceived relative advantage and perceived complexity (Davis, 1989); Al-Gahtani, 2001). In a study of Dutch households, Verhoef and Langerak (2001) explored that consumers perception of relative advantage and compatibility positively influenced their intention to adopt online grocery shopping. Consumers perception of the complexity of online grocery shopping has negatively influenced 64

9 their intention to adopt online grocery shopping. Also, results obtained by Hansen (2005) suggested that perceived complexity, perceived compatibility, and perceived relative advantage highly influence consumers adoption of online grocery buying. Research concerning innovation characteristics and innovation adoption suggests that in general compatibility, relative advantage, and complexity have the most consistent relationship to (offline) innovation adoption (see LaBay and Kinnear 1981; Tornatzky and Klein, 1982; Ram and Sheth, 1989) Use and Gratifications Theory Uses and gratifications (UandG) is a time-honored media use theory, helpful for understanding consumer motivations for media use, and has been applied to scenarios ranging from radio to television, cable television, direct to home television (see Eighmey, 1997 and McCord, 1998), and now the Internet(Chen and Wells, 1999; Eighmey and McCord, 1998; Korgaonkar and Wolin, 1999). Internet provides a wide range of networked telecommunications and media content delivery capabilities. The utility of the Internet as a powerful telecommunications medium is compelling, and the Internet is far more than just a conglomeration of web sites selling goods. The UandG theory has been successfully applied in order to understand Internet uses and gratifications in the United States and in the European context (Stafford, et al., 2004; Kargaonkar and Wolin, 1999). In UandG theory, word gratification is defined as feeling of satisfaction. The theory has come a long way since its inception in early 1940s (Ruggiero, 2000). The theory considers not only the pleasure people search for in a media but also the attitudes of the audience towards the medium and its contents (Fagerlind et al. 2000). Severin and Tankard (1997) state that the Uses and Gratifications theory is a psychological communication perspective that focuses on individual use and choice by asserting that different people can use the same mass medium for very 65

10 different purposes. The emphasis of this theory is on the audience and not on the effects of the media on the mass (Windahl, 1981). Researchers have tried to identify the psychological and behavioral aspect of the Internet users to identify the underlying motivations for Internet usage. Kaye and Johnson (2001) stated that internet users are more actively involved and engaged in using the Internet because of its interactivity. Since one of the major strengths of the Internet is its interactivity and since an active audience is the core concept of the uses and gratifications theory, gratifications theory is regarded as the most effective theoretical basis for studying this medium (Hangun, 2002). The immense opportunities for social interaction set the Internet apart from conventional mass media; this has been well captured in studies on Internet uses and gratifications (Song et al,. 2004). Researchers have applied the UandG theory to the case of Internet usage in order to understand the common underlying psychological and behavioral dimensions of Internet usage (Lin 1999; Larose et al. 2001). Luo (2002) further extended the Internet uses and gratifications studies and explored the effects of Internet usage motivations on attitudes towards a website and satisfaction. Roy, S. (2008) identified six gratifications factors for internet use are self-development, wide exposure, relaxation, user friendly, career opportunities and global exposure. Bhatnagar (2000) demonstrated that the perceptions that internet can meet need, is positively correlated with increased online shopping. (Foucaultn and Sheufele, 2002) used this theory to understand the online purchasing of textbooks and found that individuals would shop online for textbooks if they perceive it as a solution to a particular need and the gratification taken from online shopping will be used when deciding where to shop in future. Drawing from uses and gratifications theory, Luo (2002) explored influences of in formativeness, entertainment, and irritation on various online consumer behaviors such as attitude toward the web, web usage, and satisfaction. Particularly, web usage and satisfaction are explored as the consequences of attitude toward the web, while in formativeness, entertainment, and irritation are the antecedents of 66

11 attitude toward the web. They further discussed that internet users who perceive the web as entertaining and informative generally show a positive attitude toward the web based behavior Innovations Diffusion Theory (IDT) Compared to traditional shopping, e-shopping is an innovative application of information technology by retail industries. Therefore, IDT can be applied to explore consumers e-shopping behavior. According to Rogers (1983), diffusion is characterized by four elements contained within the process; whereby (1) an innovation is (2) communicated through certain channels, (3) over time, and among members or a (4) social system. There are five primary characteristics of innovations that help illustrate the rate of individual adoption: (1) Relative Advantage. (2) Compatibility, (3) Complexity, (4) Trialability, and (5) Observability (Rogers, 1995). The diffusion theory suggests that one's adoption of an innovation depends on how one perceives the innovation as "better than the idea it supersedes" (relative advantage), "consistent with existing values, past experiences, and needs of potential adopters" (compatibility), "difficult to understand and use" (complexity), "experimented with on a limited basis" (trialability), and "the results of an innovation are visible to others" (observability). An idea that have the following characteristics will be adopted rapidly by the individual: greater perceived relative advantage, more compatible with the values and norms of a social system, easily understood by most members of the social system, can be tried on an "installment plan", and easier it is for an individual to see the results of an innovation. Among these five characteristics, four of them relate positively to the rate of adoption: relative advantage, compatibility, trialability and observability. The fifth characteristic, complexity, is negatively related to the rate of adoption. These five characteristics of an innovation are good indicators in predicting if an innovation will be adopted or rejected in the final 67

12 stage of the diffusion process. Dearing et al. (1994) further suggested that applicability and reliability are important for diffusion of risky innovations. Adapa S. (2008) considered adoption of teleshopping as an innovative method of shopping contrast to the traditional mall shopping. The adoption rate of an innovation is further influenced by characteristics of the innovation itself; communication channels, time elapsed since the introduction of the innovation and the social system in which the diffusion of innovation takes place (Gong et al., 2007). Adapa S. (2008) also suggested that cultural situations should be considered for diffusion of the technology as well as for the development of e- commerce. Goldsmith (2001) explored that teleshopping innovativeness was positively and significantly correlated with television viewing and the teleshopping intention are more a function of innovative attitudes and predispositions than they are of sheer usage. 4.3 Review of key constructs and variables identified in literature and influencing Teleshopping Intention A number of factors/constructs influencing teleshopping behavioral intention and Teleshopping perception were identified from the literature, reviewed and discussed as follows. These factors will be tested in the focus group discussion to identify factors influencing perception of teleshopping and purchase intention in Indore. As from the technology acceptance model it is clear that perceived ease of use and perceived usefulness are the dimensions of perceived benefits Perceived Benefit (PB) As from the technology acceptance model it is clear that perceived ease of use and perceived usefulness are the dimensions of perceived benefits. 68

13 Perceived ease of use (PEOU). This construct draws its origin from the original Technology Acceptance Model. Perceived ease of use is defined as the degree, to which a person believes that using a particular system would be free of effort (Davis, 1989). It has a strong influence on behavioral intention to adopt information technology. Ease of use translates non-complexity degree and establishes the extent to which television is perceived effort- less at best (Limayem et al., 2000). If a technology is perceived as too difficult to use, a person will choose an alternative option that is easier for him or her to perform. According to the previous researches based on Technology Acceptance Model, perceived ease of use is found to have little or no direct effect on behavioral intention, but its effect is largely an indirect mediating factor of perceived usefulness (see Chau 1996; Igbaria, et al., 1995; Bagozzi et al. 1989). it is important to identify the latent dimensions of this construct. According to TAM, ease of use is particularly of influence in the early stages of user experience with a technology or system (Davis, 1989, 1993). Following this, Venkatesh (2000, p. 343) stated: with increasing direct experience with the target system, individuals adjust their system-specific ease of use to reflect their interaction with the system. Implying that if consumers give more time in watching television, they will adjust their perceptions regarding the ease of use of the teleshopping as a shopping medium in a positive direction. Difficulty of use may create in consumers a negative attitude towards using teleshopping as a shopping tool. Childers, et al. (2000) showed that perceived ease of use determines attitude towards interactive shopping. As for information systems, some researchers empirically attested for ease of use as a direct determinant of attitude (see Mathieson, 1991; Taylor and Todd, 1995; Agarwal and Prasad, 1997). Ramayah and Ignatius (2005) associated PEOU with 69

14 the user-friendliness of the teleshopping. They found to have a positive influence on the teleshopping intention. This suggests that the ease of use of the technology and the degree in which the shopper is satisfied with the teleshopping experience are imperative in predicting the potential e-shopper s intent. If the hassle proves to outweigh the benefit of purchasing through the television, then potential teleshoppers would prefer to purchase through conventional channels. One of the factors that contribute towards the unfriendliness of some teleshopping channels is their telecast are late in night. Additionally, poorly designed advertisement might cause potential e-shoppers to lose focus of their carts and purchases. In other words, these barriers reduce the perception on the ease of use of teleshopping, therein, allowing tele user s to develop a negative attitude. In turn, this leads to teleshopper s unwillingness to engage in teleshopping. Gefen and Straub (2000) proposed that PU and PEOU directly affect intention to use and ignored the influence of the mediating variable, attitude toward using. The table below summarizes the findings of existing literature as related to PEOU dimension of teleshopping. Table 4.1: PEOU AS A DIMENSION OF E-SHOPPING Construct Variables Authors Perceived ease of use has a positive influence on the teleshopping intention/attitude. PEOU has no direct effect on the teleshopping intention/attitude. Easy and convenient ordering layout Clear, precise and easy buying information Easy, quick and convenient buying/ Delivery promise. Easy to Oder, Advertisement easy how to explain the use of product, Advertisement Appeal. Ramayah and Ignatius, 2005; Mathieson, 1991; Taylor and Todd, 1996; Agarwal and Prasad, 1997; Venkatesh, 2000; Childers, et al., 2000, Gefen and Straub, 2000, Leelayouthayotin,L.2004;Heijdenet.al.,2003; Zarradand Debabi, 2012, Lee et.al,2000. Chau 1996; Igbaria, et al., 1995; Bagozzi et al

15 Perceived Usefulness (PU). This construct has also been adopted from the Technology Acceptance Model. This factor is well documented and consistently proven in many empirical studies to have a high impact on the behavioral intention to adopt technological products Horton, 1976; Chau and Hu, 2001; Davis, et al.,1989; Hu et al., 1999; Igbaria, et al., 1995; Mathieson, 1991; Moon and Kim, 2001; Ramayah et al. 2002; Venkatesh and Davis, Koufaris (2002) have validated the construct of PU and they were found to influence the intention of potential tele-shoppers. Perceived usefulness is defined as the degree to which a person believes that using a particular system would accelerate his or her personal growth and would enhance his or her job performance (Davis, 1989). Perceived usefulness is the most important factor influencing behavioral intention especially when making an adoption decision. Perceived usefulness is generally associated with convenience and ease of use. Most of the prior studies on perceived usefulness focused mainly on the usage or adoption of information technology. Convenience as a construct is linked to ease of use to describe the utility of the television as a shopping medium. According to Hofacker (2001), consumers perceptions of convenience as manifested by the opportunity to shop at home twenty- four hours a day and seven days a week is expected to influence the adoption of teleshopping. Teleshopping was also considered to be convenient by providing place-convenience since customers can shop without leaving their location and allow them to take advantage of time-convenience. ( Kaufman-Scarborough and Lindquist, 2002). Since consumers rarely visit multiple physical retail stores prior to purchase (Childers et al., 2001) interactive shopping can lower the costs of acquiring prepurchase product information while at the same time increase search benefits by providing a broader array of product alternatives at a small incremental cost (Bakos, 1991). These benefits in the reduction of search costs accrue particularly 71

16 when the consumer is under time pressure (Beatty and Smith, 1987) making the accessibility advantage of interactive shopping especially advantageous to consumers. Lynch and Ariely, (2000) explored that tele shopping reduces search costs for products and search costs for product related information. Convenience was also described as a utility of the television as a shopping medium. Consumers are curious about the convenience factor across multiple channels (Burke, 2002). Customers see the utility of the television through various ways like unique products, promotion activities and inventory in the closest retail store. Ease of navigation was found to be the most likely variable to lead to teleshopping (Montoya-Weiss, et al, 2003). In addition, Spake, et al. (2003) suggested that convenience and ease of use would help a service provider develop and maintain a relationship with a customer, and are part of a broader concept of consumer comfort Monsuwe, et.al (2004) included two latent dimensions of the usefulness construct: consumer return on investment (CROI), and service excellence (Mathwick, et al., 2001). If teleshopping meets this ideal by enabling the consumer to accomplish the shopping task he or she has set out to perform, then consumers will judge the teleshopping performance positively (Mathwick, et al., 2001). This leads to positive perceptions regarding the usefulness of teleshopping. Kurnia and Chien (2003) found that perceived usefulness has positive influence towards teleshopping. Ramayah and Ignatius (2005), observed in their studies that perceived usefulness (PU) was not a significant factor in determining the purchase intention to teleshop. The notion that individuals are more influenced by the usefulness of the products instead of its ease of use had been challenged. This study believes that this surprising result is contingent upon variables such as the type of products. Tele purchases are believed to be more common in familiar products (e.g. Slim Tea, Yants etc), while shoppers still prefer conventional means for apparels and household items. This may be due to the fact that the former has a lower quality 72

17 uncertainty that governs them, while the latter requires much personal interaction with the products. The table below summarizes the findings of existing literature as related to POU dimension of e-shopping. Table 4.2: PERCEIVED USEFULNESS AS A DIMENSION OF E-SHOPPING Construct Variables Authors Perceived usefulness has a positive influence on the teleshopping purchase intention. POU has no direct effect on the online shopping intention. Shopping convenience Boon for emergencies Convenience for life Entertaining and informative Fun Variety Time saving Wolfinbarger and Gilly, 2003; Leelayouthayotin, 2004; Kurnia, S. and Chien,2003; Lynch and Ariely 2000; Kaufman- Scarborough and Lindquit, 2002; Montoya- Weiss, et al, 2003; Koufaris, 2002; Chau and Hu, 2002; Davis, et al., 1989; Hu et al., 1999; Igbaria,et al. 1995; Mathieson, 1991; Moon and Kim,2001; Ramayah et al., 2002; Venkatesh and Davis,2000. Ramayah and Ignatius Perceived Risk Perceived risk has been taken as important factor influencing teleshopping. The term perceived risk means the individual s subjective belief about potentially negative consequences from his/her decision. In other words, perceived is used as opposed to objective outcome distributions of an alternative or a product class with that a consumer is associated. Although some early researchers suggest that risk perception may play a minor role in the adoption of teleshopping (Jarvenpaa and Todd, 1997), recent results from several studies have identified that consumers risk perception is a primary obstacle to the future growth of teleshopping (Culnan, 1999). The consumer makes his choice under condition of uncertainty and television is perceived to be quite risky (Bhatnagar, et al., 2000). Consumer risk perceptions and concerns regarding teleshopping are mainly related 73

18 to aspects involving the privacy and security of personal information, the security of online transaction systems and the uncertainty of product quality (Shergil and Chen, 2005). Samadi and Najadi (2009) found that that consumers perceived more purchasing risk from television than from the store as generally the product are manufactured by local vendors so quality may not be up to the mark. A more positive teleshopping experience led to consumers less perceived purchasing risk level in teleshopping. And a higher perceived risk led to less future purchasing intention from teleshopping (Samadi and Najadi, 2009). Tan (1999) explored that perceived risk is higher when purchasing products through teleshopping than when purchasing by in-store means. However, perceived risk decreases with higher the television viewing and teleshopping experience which in turn result in higher purchase rates. (Miyazaki and Fernandez, 2001). Researchers including Vijayasarathy and Jones (2000) found perceived risk to be a significant factor affecting consumer behaviour. Liebermann and Stashevsky (2002) and Forsythe and Shi (2003) provided empirical evidences to support a relationship between perceived risk and frequency of use. Perceived risk is likely to have the greatest impact on sporadic tele-shoppers, which precludes the conversion of teleshopping viewers into teleshopping customers (Forsythe and Shi, 2003; Cunningham, et al., 2005). Risk perceptions and lack of trust have been identified as two major obstacles to the adoption of teleshopping (Mukherji and Thomson, 2007). According to Lee and colleagues (2001), two main categories of perceived risk emerge in the process of teleshopping. The first is the perceived risk associated with product/service and includes functional loss, financial loss, time loss, opportunity loss, and product risk. The second is the perceived risk associated with context of online transactions, and includes risk of privacy, security, and non- 74

19 repudiation. Among them, the influence of financial risk, product risk, and concern for privacy and security is significant (Senecal 2000; Borchers, 2001; Bhatnagar, et al., 2000). Cases S. A. (2002) proposed four potential risk sources in the context of electronic shopping; risk associated with the product, risk ensuing from a remote transaction, risk associated with the use of television as a mode of purchase and risk related to the payment transaction takes place. Similarly Zhang L, et al.(2012) identified that perceived health risk, perceived quality risk, perceived time risk, perceived delivery risk and perceived after sale risk affect significantly teleshopping consumer purchasing behavior while perceived privacy risk, perceived social risk and perceived economic risk are the less relevant factors. Roselius (1971) have identified other types of consequences (physical, time and money loss). Jacoby and Kaplan (1972) indicate five types of consequences (physical, psychological, social, financial, and performance) by cross-validating these dimensions. Performance risk tends to explain more variance than doe any other type of consequence. Their results were supported and completed by Kaplan et al. (1974) who validated the existence of financial, performance, psychological, physical, social, and time consequences. Hence, the perceived risk can be conceptualized in psychological/social dimensions, or in economic/functional dimensions, or in some combination of both forms (Taylor 1974). According to Azadavar, et al. (2011), an anxiety regarding security of personal information had a negative influence on teleshopping and decreases frequency of teleshopping. Doolin et.al. (2005) also observed that privacy risks have a negative association with teleshopping purchasing behavior and deter teleshopping users from shopping frequently and from spending significant amounts of money. Researchers including George (2002), Furnell and Karweni (1999), Hoffman et al. (1999) and Wang et al.(1998) also found that unauthorized acquisition of personal information during purchases from teleshopping and internet use or the provision 75

20 of personal information collected by companies to third parties was the major consumers concerns about privacy. Hoffman et al. (1999) suggested that with increasing privacy concerns, the likelihood of purchasing online decreases. Swaminathan, et al. (1999) found that consumers who purchased more on television were more concerned about the creation of privacy laws. Adapa, S (2008) studied that security issues such as disclosure of credit card numbers were major concerns for Indian women. Similarly for Malayasian consumers the issue of security and trust over television was found to be the most overwhelming barrier that limits the adoption of electronic commerce (Delafrooz, et al., 2011). Widely publicized security lapses on Internet, where hackers have access to personal financial information being sent electronically, have done little to boost consumer confidence in Internet as a conduit for commerce (Petronas and Seri, 2001). Hirst and Omar (2007) explored that UK women who purchase apparel online are more willing to provide credit card and purchasing information over Internet if the retailers were deemed reliable and the researchers concluded that perceived risk features like lack of security, privacy of information and online fraud do not deter them from teleshopping. Perceived risk also differs according to gender. Garbarinoa and Strahilevitzb (2004) observed in their study that compared to men, women will be more likely to increase their willingness to teleshop if they receive a advertisement or specific product for their personal use recommendation from a friend and having a site recommended or advertisement by a friend leads to both a greater reduction in perceived risk and a stronger increase in willingness to buy from television among women than among men. Hirst and Omar (2007) also observed that female are more positively to teleshop with interest and confidence as compared to male. Females are more cautious about their health and certain products are available in teleshopping which they cannot directly go and purchase from market. 76

21 Perceived risk has been found to have a negative influence on consumers attitudes or intentions to teleshop (Novak et al., 2000; Molina-Castillo and Lopez- Nicolas. (2007) these researchers suggested that computer knowledge and consumer literacy does moderate the relation between perceived risk in tele shopping and consumer purchase intention. Consumers with greater computer experience and high literacy level are found to be more favorably inclined to shopping in cybermalls in particular (Bhatnagar, et al., 2000). Table 4.3: PERCEIVED RISK AS A DIMENSION OF TELESHOPPING Construct Variables Authors Perceived Risk has a significant impact on the teleshopping intention. Perceived Risk has no direct effect on the teleshopping shopping intention. Privacy and security of personal information Security of online transaction systems Uncertainty of product Risks from using credit cards Risk about the quality of the product, Non return ability of the product Loss of social interaction Unauthorized use of personal information Delivery of goods damaged in transportation Extra money charged Liang and Huang, 1998; Delafrooz, et al Adapa, S.,2008;Petronas and Seri, 2001; Hirst and Omar 2007; Samadi and Najadi, 2009; Vijayasarathyand Jones,2000; Forsythe and Shi (2003). Jarvenpaa and Todd, 1997; Novak et al., 2000; Molina- Castillo and Lopez- Nicolas., Consumer Attitude An attitude in marketing terms is defined as a learned predisposition to respond in a constant favorable or unfavorable manner, in respect to a given object (Khan, M.2004). An attitude satisfies a personal motive and at the same time, affects the shopping and buying habits of consumers. Perner L. (2010) defines consumer attitude simply as a composite of a consumer s beliefs, feelings, and behavioral intentions toward some object within the context of marketing. A consumer can hold negative or positive beliefs or feelings toward a product or service. A 77

22 behavioral intention is defined by the consumer s belief or feeling with respect to the product or service. Consumer s attitudes toward teleshopping have gained a great deal of attention in the empirical literature. Attitude toward the transaction is defined as the overall evaluation of the desirability of a potential transaction with a specific tele retailer. Taylor and Todd (1995) described attitude as the attitudinal belief that a behavior will lead to a particular outcome, weighed by an evaluation of the desirability of that. Attitude has been proposed to influence behavioral intentions in multiple theories, such as TPB (Ajzen 1991), the TRA (Fishbein and Ajzen 1975), and the TAM (Davis et al, 1989). Hence, applied to the tele consumer innovative behavior. Attitude is an overall consumer's evaluation of a tele retailer's characteristics. For example, consumers would trust tele-service providers with transmitting their personal information online are necessary for them to shop over the television. Hence, attitude is likely to influence all transaction activities with a tele retailer. Therefore, favorable attitude is expected to facilitate innovative teleshopping behavior of consumers. Consistent with the literature and models of attitude change and behavior (e.g., Fishbein and Ajzen 1975), it is believed that consumer attitudes will affect intention to teleshop and eventually whether or not a transaction is made. This is a multidimensional construct that has been conceptualized in several different ways in the existing literature. First, it refers to the consumers acceptance of the television as a shopping channel (Jahng et al,. 2001). Secondly, it refers to consumer attitudes toward a specific tele-store (i.e., to what extent consumers think that shopping at this store is appealing). These first two dimensions are negatively associated with the third, customer s perceived risk. However, the fourth dimension of attitude, consumers trust in the stores, can reduce perceived risk. In addition, perceived control/users empowerment, 78

23 enjoyment/playfulness, and perceived real added-value from membership have also been shown to be important dimensions of consumers attitudes towards tele shopping (Koufaris et al,. 2002; Cho et al., 2001). Jarvenpaa and Todd, 1997 proposed a model of attitudes and shopping intention towards Internet shopping in general. The model included several indicators, belonging to four major categories; the value of the product, the shopping experience, the quality of service offered by the website and the risk perceptions of Internet retail shopping. In a research conducted by Vellido et al. (2000), nine factors associated with users' perception of online shopping were extracted. Among those factors the risk perception of users was demonstrated to be the main discriminator between people buying online and people not buying online. Other discriminating factors were; control over, and convenience of, the shopping process, affordability of merchandise, customer service and ease of use of the shopping site. In another study, Jarvenpaa et al. (2000) tested a model of consumer attitude towards specific web base stores, in which perceptions of the store's reputation and size were assumed to affect consumer trust of the retailer. The level of trust was positively related to the attitude toward the store, and inversely related to the perception of the risks involved in buying from that store. Jarvenpaa et al. (2000) concluded that the attitude and the risk perception affected the consumer's intention to buy from the store. Consumer risk perceptions and concerns regarding online shopping are mainly related to aspects involving the privacy and security of personal information, the security of online transaction systems and the uncertainty of product quality. (McAllister, 1995) observed that trust is interwoven with risk. One of the consequences of trust is that it reduces the consumer s perception of risk associated with opportunistic behaviour by the seller (Ganesan, 1994). Lack of trust is frequently reported as the reason for consumers not 79

24 purchasing from Internet shops, as trust is regarded as an important factor under conditions of uncertainty and risk in traditional theories. Mayer et al. (1995) developed a model which combined traditional marketing philosophy on consumer motivation to buy and the trust model. In this model, trust propensity; which is a personality trait possessed by buyers; is an important antecedent of trust. In Internet shopping, there is not much information available to the buyer regarding the seller, prior to purchase. A buyer with a high propensity to trust will more likely be a potential customer than a buyer with lower propensity. Mayer et al. (1995) proposed that ability, benevolence and integrity constitute the main elements of trustworthiness. Ability refers to skills, competencies and characteristics that a seller has in a specific domain. In this context, sellers need to convince buyers of the competence of their companies in the Internet shopping business. Benevolence is the extent to which the seller is perceived by the buyer as wanting to do good. Sellers have to convince buyers that they genuinely want to do good things for buyers, rather than just maximize profit. Therefore, it is important to recognize that numerous factors precede attitude formation and change. Consumers characteristics such as personality nature, online shopping benefits and perceptions have also been found to influence consumers online shopping behaviors and online shopping rate (Cheung and Lee, 2003; Shwu-Ing, 2003; Wolfinbarger and Gilly, 2001). Therefore, understanding consumer attitudes help marketing managers to predict the online shopping rate and evaluate the future growth of online commerce. Particularly, perceived usefulness and attitude towards website have been used exhaustively to explain purchase intention. Positive attitude towards website is the strongest factor, among all variables, for online purchase intention. 80

25 Perceived usefulness is another strong factor in explaining online purchase intention and patronage intention. Perceived usefulness is also significant for the creation of positive attitudes towards website. Koufaris et al., 2002; Cho et al., 2001 identified other dimensions of attitude such as enjoyment/playfulness, perceived control/users empowerment and perceived real added-value from membership. Table4.4: CONSUMER ATTITUDE AS A DIMENSION OF TELESHOPPING Construct Variables Authors Consumer Attitude Consumers acceptance of the teleshopping as a shopping channel Consumer s personality Consumer s nature Tele shopping benefits and perceptions Perceived control/users empowerment Jahng et al., 2001; Cheung and Lee, 2003; Goldsmith and Flynn, 2004; Shwu-Ing, 2003; Wolfinbarger and Gilly, 2001; Koufaris et al.2002; and Cho et al., Intention to Teleshop Consumer s intention to shop virtually is also studied by large number of researcher. Consumer s intention to teleshop refers to their willingness to make purchases in a tele stores. Commonly, this factor is measured by consumers willingness to buy and to return for additional purchases. The latter also contributes to customer loyalty. Belanger et al. (2002) defined e-shopping intention as an individual s cognitive beliefs with respect to adopting or using e-shopping whereas (Cho, 2004) defined e-shopping intention as an individual s cognitive beliefs with respect to planning to abort an online transaction before checkout (Cho, 2004). Chuchinprakarn S. (2002) defined on-line purchase intention as consumers intents or expectations to make an on-line purchase in the future. Researchers have adopted various scales to measure respondents e-shopping intention: a two-point scale and multi-point 81

26 qualitative scales. Among the latter, five-point scales and seven-point scales have been most commonly used in some studies intention to shop online was measured by asking a single question to ask respondents to report their e-shopping intentions (see, Chen and Tan, 2004, Goldsmith, 2002; Koufaris, 2002; Liang and Huang, 1998; Liao and Cheung, 2001; Phau and Poon, 2000; Van den Poel and Leunis, 1999; Verhoef and Langerak, 2001) whereas Jarvenpaa and colleagues (2000) assess consumers intention to shop online by asking a series of questions assessing the likelihood of returning to a stores website, the likelihood of purchasing from the store within the next three months, the likelihood of purchasing within the next year, and general the likelihood of ever purchasing from a particular store again. Li and Zhang (2002) explored that, consumer s intention to shop online is positively associated with attitude towards Internet buying, and influences their decision-making and purchasing behavior. In addition, there is evidence of reciprocal influence between intention to shop online and customer satisfaction. Bellman et al. (1999) investigated various predictors for whether an individual will purchase online. These authors concluded that demographic variables, such as income, education and age, have a modest impact on the decision of whether to buy online, whereas the most important determinant of online shopping was previous behaviour, such as earlier online purchases. This is consistent with Forrester Research which proved that demographic factors do not have such a high influence on technology as the consumers attitudes do (Modahl, 2000). Kotler and Armstrong (2000) pointed out that a person s buying choices are further influenced by four key psychological factors: motivation, perception, learning and beliefs and attitude. Gefen, et al., 2003 suggested that the combination of the Internet, and physical presence, provides more opportunities to capture business than the online-only presence, because they can provide better pre-purchase and post-sales services to 82