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This dissertation aims at developing profiles of Greek consumers who have already conducted purchases through the Internet and of the consumers who are willing to adopt the Internet shopping as an innovation. Measurement of the demographic and behavioural data, investigation of the trends and attitudes of the online consumers toward online apparel shopping. The research will provide insightful preliminary data based on the detailed profiles of Internet shoppers ("innovators'') and interested-to-adopt Internet shopping ("early adopters''). The empirical findings will provide valuable managerial implications while setting the foundation for future research in this topic.
The Importance of the Research
Internet gained the trust of more than 1,5 billion users around the globe (world Stats, 2009) and became the most important tool of almost every international business (Mc donald and Tobin, 1998; Rha et al., 2002; Urban, 2003). The majority of the web users is taking advantage of the globalization and the online prices.In some countries the percentage of the online shoppers is reaching the 95% according to the Nielsen Online Report (2008). The same report indicates that the users which prefer the internet for frequent purchases is 39% and about 84% of the users concluded the purchase of a product once every month through the Internet the last two years of the study. The total sales in Europe are expected to be more than 407 billion dollars by the end of the 2011. According to the same report UK, France and Germany hold more than 70 percent of the total European sales followed by Italy and Spain.
The structures of the web sites profess differences because of the culture but also common characteristics (Okazaki et al., 2006). In the next few years because of the globalization of the media there is evidence of a new global culture, the digital culture (Deuze, 2006)
Hofman and Novak (1996) described the online apparel shopping as a new kind of consumer behavior according to "computer mediated shopping environment". The researchers seek to develop the past theories of customers behavior while retailers seek to establish successful strategies by knowing better their customers (Goldsmith and Mcgregor, 1999).
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Moreover, the research will highlight the differences and similarities of these consumers groups and to the Internet online apparel shopping, and clearly will provide some of the most important success ingredients that every online retailer should take under consideration.
The Research Aims & Objective
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The Importance of Apparel Online Shopping
For years researchers examined the reasons that made shoppers to buy from home, focusing on the differences between traditional retailers and online retailers (Eastlick and Feinberg, 1999; Hawes, 1986). Authors developed a risk-taker profile of the online consumer (versus the in-store consumer) who is ready to perceive a higher risk (Donthu and Garcia, 1999; Schoenbachler and Gordon, 2002; Vijayasarathy and Jones, 2000).
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Purchasers because of their different characteristics approaching the online apparel stores with many different ways and receiving different messages, which may affect their online purchases (Cheung et al., 2003). Therefore, we will have to emphasize to these characteristics because of their importance. Previous online purchase experiences, characteristics based on their personalities and the level of their innovative thinking when they go online to shop (Cheung et al., 2003) need to be discussed.
The online shopping behaviors of the consumers are close attached to their personalities and may affect their choice of the online apparel stores and products (Wolfinbarger & Gilly, 2001). Therefore, we need to focus in two main consumers personalities: The utilitarian and hedonic personalities.
Utilitarian consumers buying online based on their goal oriented shopping behaviors. Shopping is made according to their goals and rational necessary needs (Kim &shim, 2002). They are trying to deliberate their shopping habits through rationality and efficiency and they are not searching for any kind of entertainment through shopping (Wolfinbarger & Gilly, 2001).
Main aspect is to conclude their online shopping experience efficiently and in time without any kind of unnecessary irritation (Monsuwe, Dellaert & Ruyter, 2004). Moreover, their instrumental characteristics guide their shopping experiences efficiently to a task oriented behavior (Sorce, Perotti & Widrick, 2005) They are in search for sites offering variety of products, convenience, ease of access and multiple information among others (Wolfinbarger & Gilly, 2001).
Hedonic consumers defined according to experiential buying behavior. Their concern is not to gather as many information they are able to but at first to seek happiness sensory stimulation and some sort of enjoyable experiences (Monsuwe, Dellaert & Ruyter, 2004). The hedonic consumers are trying to immerse into the experience in a greater way than achieving their goals by shopping online (Wolfinbarger & Gilly, 2001).
They are trying to combine shopping with enjoyable experiences, playful sites and uniqueness (Sorce et al., 2005). Consequently, the hedonists when they get satisfied are increasing their visits and purchases to their favorite online apparel stores (Wolfinbarger & Gilly, 2001).
Main differences between hedonic (experiential) and utilitarian (goal oriented) consumers behaviors.
Their differences in personality, motivation and key aspect leads to a different interaction with the online apparel stores. The goal-oriented customers are guided from instrumental factors which may include the ease of access, the available information and the variety of selection. While the goal oriented consumers seek for control the experiential consumers seeking for fun and surprising web stores (Wolfinbarger & Gilly, 2001; Sanchez-Franco & Roldan, 2005). A summarization follows in Table 2.1
According to Wolfinbarger and Gilly (2001) more than 72% of the shoppers are goal oriented and followed some sort of plan on their recent purchases, and 28% of the shoppers are experiential and decided a purchase while they were browsing. Moreover, research has shown that even if the goal oriented customers represent the majority, the experiential consumers and their browsing attitude are welcome, because of their close connection with high impulse purchases and frequency (Wolfinbarger & Gilly, 2001).
Innovation described as "the degree to which an individual .... is relatively earlier in adopting new ideas than the other members of a system" (Rogers, 1995). Several researchers referred to the different characteristics of the innovative consumers. Most of them are:
- higher or highest education (Leung, 1998; Pepermans et al., 1996;)
- mostly young consumers (Hirschman and Adcock, 1978;)
- income is higher than the average (Pepermans et al., Summers, 1972;)
- higher social activity (Robertson and Kennedy, 1968; Roggers, 1995;)
- risk takers (Leung, 1998; Roggers, 1995;)
- opinion leaders (Darden and Reynolds, 1974; Chau and Hui, 1998;)
- women in majority (Goldsmith et al., 1987)
Researchers have tried to analyze the role of gender or/and race on innovation and clearly saw that the women are more likely to be innovative than men.
The key aspect of the innovation seems is the new products to adopted by the consumers in the market (Leung, 1998; Pepermans et al., 1996). The higher acceptance of the new innovative products as the World Wide Web, may affect as well the use of the network for purchases(Citrin et al., 2000). The apparel online shoppers described mostly as innovators from other researchers (Goldsmith et al., 1995).
Goldsmith and Flynn (2004) defined that "online apparel purchasers could not be distinguished from non-purchasers by their demographics, but they were more innovative toward clothing and fashions than the non-purchasers. Online apparel purchasers, however, did use the Internet more and were more innovative toward using the Internet than non-purchasers were". The innovative online consumers more likely will purchase apparel online instead of the non-purchasers which are less innovative.
Rogers (1995) proposed a five-stages process for the innovation to be adopted by an individual. The first one is the knowledge stage, a stage on which an individual tries upon previous experience to understand an innovation and its characteristics. The knowledge derives from the social environment, understanding of problems and general innovativeness. The Persuasion stage which is the second one, represents the development of every positive and negative attitude upon innovation as a result of the knowledge stage.
The perceived elements (Rogers, 1995) which are going to influence the adoption of an innovation are:
- The relative advantage - in other words the consumers will assume the advantageous role of the innovation and the adoption will be faster.
- The compatibility aspect - if the consumers recognize in the innovation compatibility with their lifestyle, there is a greater possibility to adopt the innovation.
- The complexity issue - the consumers will examine the innovation and if they think that is easy to use, maybe will adopt earlier the innovation.
- The trial ability - a trial of the innovation will make it easier for the consumers to adopt it.
- The observation ability - the chance of observing the results of each innovation may speed up the adopt timeframe.
Another researcher examined the five elements and discovered that the relative advantage, compatibility aspect, the trial ability and the observation ability are positively connected to adoption of every innovation and complexity issue is negatively connected to the adoption of an innovation.
In the decision stage which is the third one, the consumer decides to adopt or to reject the innovation according to his/her attitude created during the persuasion stage (Rogers, 1995).
The behavioral change will be visible during the fourth stage, the implementation stage. During that stage the consumer will act on his decision of the approval or the rejection of an innovation. Even at this stage the consumer holds a level of uncertainty about the scope of the innovation and will keep collecting information about the innovation. During the last stage according to Rogers (1995), the confirmation stage, the consumer will re-examine the innovation and will reach to a new decision whether or not he will continue to adopt the innovation.
Purchasers - Browsers and Searchers
Internet users have different aspects when they go online. Some users are online because of their intention to buy apparel online (purchasers), but the browsers may not interested to buy online. A search for extra information on the websites is what made them to go online in some of the cases. The "searcher" is a goal oriented consumer who is online to search for information in a productive way in order to fulfill his goals (Ha & Stoel, 2004). A task oriented behavior, more as pre-purchase deliberation and an intention to conclude a purchase next to the gathering of information online are the characteristics of the "searcher".
Schlosser (2004), defines the consumer known as a "browser", an experiential shopper who seeks more and more for an entertaining experience. If the websites are able to fulfill the aspects of the searchers and browsers may transform them to purchasers.
Ha & Stoel(2004), assumes that all three kind of potential shoppers (purchasers, browsers and searchers) may show different online shopping attitude on a specific site and may consider the advantages of the online apparel shopping in a different way because of their goals. The browsers and not the searchers according to schlosser (2004), affected more from vivid images.
Darwin (1872) mentioned the attitudes as a physical action of a thought. Fishbein and Ajzen (1975) through their work "Belief, Attitude, Intention and Behavior : An introduction to Theory and Research" focused on the prediction of the human behavior through their theory of the reasoned actions. Ajzen (1987) developed the theory of the reasoned actions to the theory of planned behavior. The model suggested by Fishbein still is the most popular among researchers but among psychologists is Fazio's (1986) "attitude accessibility model".
Fishbein's Multi-attribute Model
Fishbein's claims that the consumers form attributes towards objects on the basis of their beliefs (perceptions and knowledge) about these objects. Since a consumer may hold different beliefs about an object it may be difficult to get the overall perception of a product such as the McDonalds if they are good or bad for the consumers (Perner, 2006).
Within this framework a person's attitude toward an object is a "function of his beliefs about an object and the implicit evaluative responses associated with those beliefs" (Karjaluoto, 2006). Beliefs are acquired by the processing information, which are obtained from direct experiences with objects and from interaction with other sources. Moreover, if there is a need to understand consumer's attitudes adequately, a determination of the beliefs that form the basis of these attitudes is necessary (Fishbein and Steiner, 1965).
The model focus in three attributes of the attitude:
- The salient beliefs people hold about an attitude object, e.g. those beliefs which are the first to come in mind;
- Object-attribute linkages, or the probability, that a particular object has an important attribute.
- Evaluation of each one of the important attributes.
Upon any case, the model created on assumptions that may prove wrong on everyday practice. At first assumes that exists the ability to specify adequately all the relevant attributes. This model also assumes that he/she will go through the process (formally or informally) of identifying a set of relevant attributes, evaluating them and measuring the overall outcome.
Without any attempt of questioning this model, which is clearly a high-involvement subject, it is still possible that the consumer's attitude will be formed by an overall affective response (Solomon et al., 1992).
Since any kind of object, such as a product or a brand, has numerous attributes (size, features, shape etc), an individual will collect information and develop beliefs quite different according to the provided individual attributes. Positive or negative feelings are also formed on the basis of the beliefs held about the attributes.
Thus, the person's overall attitude toward an object is derived from the beliefs and feelings created by the various attributes of the model and that is why the model is referred as a Multi attribute model or as the Fishbein's attitude model (Newman and Foxall, 2003).
The Multi attribute model tries to summarize the overall attitudes by using the following equation (Hawkins et al., 1998):
Ao = the person's overall attitude toward the object-Characteristics of the attitude object (e.g. Reputation of a College)
bi = the strength of his belief that the object is related to this attribute (e.g. the strength of belief that Wrangler Jeans are durable, or the belief that on line shopping is a convenient way to shop)
ei = the evaluation or intensity of feelings (liking or disliking) toward attribute-the priority consumers place on an object. Some A (attitudes) will be more important than others. i.e. (Library resources, social environment...priorities).
n = the number of relevant beliefs for that person ( Loudon and Bitta, 1994)
According to the above mentioned formula the weight of importance of a belief towards an object (bi) is multiplied with the evaluation i.e. of` the product. For example, a consumer believes that the taste of a refreshment is moderately important or a 4 in a scale of importance from 1 to 7.He/she also believes that drinking coffee feels very good, or 6 on a scale from 1 to 7.Thus the product overall grade here is 4*6 =24.The customer also believes that the potential of a drink to stain is extremely important (7), and coffee fares moderately badly at -4 on this attribute (since this is a negative belief, for this purpose we are taking numbers from -1 to -7 with -7 being worst). The total score for this belief is 7*(-4) =-28.If we hold these two beliefs the aggregated attitude would have been 24+(-28)=-4.In real life, it is obvious that consumers tend to have many more beliefs and their summary will provide an accurate measurement (Perner, 2006).
Based on this multi-attribute model, marketers may consider four strategies when attempting to affect behavior:
- Change the value placed on a particular product attributes (a change in an ei component)
- Change beliefs (a change in a b1 component)
- Change the attitude toward the brand (A change in Ao)
- Change behavioral intentions (a change in BI) or behavior change in B (Assael, 1992)
The Fishbein's attitude-towards object model has been relatively successful in predicting, behavioral intentions arising by various cognitive variables to which they refer (Birtwistle and Shearer, 2001; Doyle and Fenwick, 1974; Fishbein, 1967; Bass and Talarzyk, 1972). For example, excessive usage of the model to measure different advertisements or store brands. The tangible attributes and the utility versus the intangible ,symbolic attributes. However, this approach has not always been useful results for the retail management, as the knowledge of a customer's attitude about a brand is not always a safe predictor of their actual behavior (Wicker, 1967).
Furthermore, the model allows marketers to focus on the important issues of their consumers. Examines the effectiveness of their brand in providing the necessary attributes, and how marketers stack up against their competitors (Karjaluoto, 2006). By all means a negative response of the consumers to one feature of a brand does not necessarily eliminates the consumers connection with the specific brand.
According to Wilkie and Pessemier (1973) the most important aspect of the multi-attribute model is:
"The advantage of multi-attribute models is in gaining understanding of attitudinal structure. Diagnosis of brand strengths and weaknesses on relevant product attributes can then be used to suggest specific changes in a brand and its marketing support."
The retailers tried to take advantage of the Multi attribute model in a way to predict the behavior of their consumers. Although, the use of the model was inappropriate and in some of the cases unacceptable. As a result, the forecast of the consumers behavior was not accurate (Sheppard, 1988):
- The model was developed to deal with the actual behavior (e.g. taking an aspirin), not with the outcomes of behavior (e.g. allergy), which is assessed in some studies (Solomon et al., 2002)
- Consumption situations may vary and this is going to influence the strength of the attitude behavior relationship (Bearden and Woodside, 1976). In fact, evidence suggests that consumer's attitudes toward brands can actually vary depending on the situation (Miller and Ginter, 1979).
- Time usually elapses while consumers forming attitudes and when they are ready to act on these. During that time, many variables expected and unexpected may intervene to affect behavior. For example, an unexpected need for a new family car could quickly postpone, or cancel, plans to purchase a new motorcycle (Loudon and Bitta, 1994).
- The consumer's attitudes toward some types of behavior are influenced by his evaluation of the perceived consequences (positive or negative) of taking such action. Therefore, these attitudes are more relevant for predicting consumer's attitudes toward the objects themselves (Loudon and Bitta, 1994).
- Consumers are often influenced by their perceptions of what others will think of their actions. Thus, even though a consumer may have a favorable attitude toward making a purchase, he may refrain from doing so because of his perception that other people, who are very important to him (such as his/her friends) might not approve his action. This influence noted as subjective norm (Loudon and Bitta, 1994).
New models able to adjust to the formed complexity introduced and the above-mentioned factors were used as a guide. As a result, Fishbein introduced the Behavioral Intentions model (Loudon and Bitta, 1994) in an attempt to escape from the traditional attitude toward object model to a more attitudes towards behavior model (Thoradeniya, 2006).
Fishbein's Behavioral Intentions Model
This revised model presented by Fishbein and contributed by Ajzen (1975), was designed to include the person's evaluation about performing certain behaviour. Their attitude toward the behaviour and additionally the social pressure experienced when performing the behaviour, like the subjective norm (Stephen, 2002).
The theory of reasoned action is different from the traditional attitude theories in a manner of introducing normative influences to the overall model and a causal relationship between the two antecedents and intention (Ha, 1998).
Subjective norms are determined by the consumer's beliefs about the actions of the others regarding his intended behaviour and his motivations to comply with their standards of behaviour (Fishbein and Ajzen, 1980). The subjective norms reflect as well the individual's sense to behave in an acceptable manner (Teo and Loosemore, 2001).
Normative beliefs in general involve specific individuals or groups rather than generalised important others(Fishbein and Ajzen, 1980). In addition, the person's behaviour is a function of his/her intention to behave in a certain manner (Loudon and Bitta, 1994). For example, a woman's attitude towards birth control pills maybe favourable, but the pressure exerted by family and friends could represent the subjective norm, which may result in a negative attitude towards using them (Johnson and Fishbein, 2003).
Fishbein's expressed relationships in equation form as:
As the model indicates, in order to predict the consumers behavior, the researcher must determine the consumers attitude toward the specific behavior in question (AB) and his subjective norm (SN).
Each of these will be weighted by w1 and w2 respectively (which add up to 1.0) to reflect their relative importance in influencing the behavioural intentions (Loudon and Bitta, 1994).
The consumers attitudes toward performing a specific behaviour has the same structure as in the Fishbein's Multiattribute model. The important change here is that beliefs and evaluations concern certain actions, and the consequences of these actions, affect the attributes of the object (Ha, 1998). These beliefs are called behavioural beliefs. An individual will attempt to perform certain behaviour because of his evaluation upon beliefs. Attitudes are determined by the individual's beliefs about the consequences of performing according to a specific behaviour (behavioural beliefs) and his concerns about the above mentioned consequences (outcome evaluations).Those attitudes have a direct effect on behavioural intention and are linked with subjective norm and perceived behavioural control (Brown, 1999).
A number of issues and limitations of the Fishbein Behavioural Intentions model need further examination, since the potential number of factors affecting attitude are infinitive.
Other researchers are involved with the thoughts of the consumers before their decision upon action. We are not able to apply these theories in the organisational buyer behaviour because of the complexity of the influencing factors which affect this kind of behaviour (Thompson and Panayiotopoulos, 1999).
Moreover, there is a significant risk between attitudes and subjective norms since attitudes can often be reframed as norms and vice versa. In practice the consumer suffer from several constraints such us limited ability, time, environmental or organisational limits and unconscious habits.
It is also very important to note, that although the theory assumes that behaviours are influenced only by intentions, other authors suggest that attitudes and past attitudes have a direct influence on future behaviour(Bargh, 1997). According to the above-mentioned frame the current behavior may be habitual and triggered by environmental stimuli and may be elicited unintentionally when an evaluative representation is present (Bargh, 1997).
However, the implications of this model are extremely important for the marketers, while there is a specific need for understanding the factors which affect the consumers intentins. Past research strengths the ability to identify the most important attributes, which forced the consumers to form negative or positive attitudes towards a purchase of a product (Ha, 1998). It is also a valuable tool to proceed with the identification of the sources of the social environment and their possible role in intention. (Ha, 1998).
These attitudinal and subjective-norm components are helpful to marketers to analyse and understand/predict the consumers behaviour. Moreover, they are useful because of their suggestions to alternative marketing strategies for the evaluation and change of the consumers attitudes and intentions to act (Loudon and Bitta, 1994).
Online Apparel Shopping Intention
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While shopping through online apparel shops increases in Europe and the USA, the increase of the female consumers increased tremendously even though male consumers characterized as early adopters in previous studies (Asch, 2001). McIntosh (2001) reported that in USA women are more than fifty percent of the internet consumers. U.K. has reached the 61 percent (shop.org, 2002b).
Internet has the power to transform simple surfers to shoppers and everyone that goes online to shop saves time and money; it is easier to conclude an order, finds quality and lower prices from trusted brands; enjoys private and secure transactions; and is able to compare products through the avalable information (Breitebach and Van Doren, 1998; Shim et al., 2000; Supphellen and Nysveen, 2001; Szymanski and Hise, 2000).
Moreover, the convenient use of the Internet (e.g. the available rich information, way of ordering) and in combination with lowest prices seems to be the most important factors in predicting intention for visiting an online apparel shop (Chiger, 2001; Supphellen and Nysveen, 2001).
In addition, some other attributes next to every online transaction affecting the online purchase behavior. The cost of shipping was the most important deterrent according to Parker (2000) for 55 percent of the Greek consumers. Of course, other online attributes like the security/privacy offered during the payment or the guarantee and the cost for returning products essentially affect the online purchasing intention (Shim et al., 2001).
These findings are quite important for apparel (feel and touch) products. The research of Then and Delong (1999) noticed an increase to total apparel purchases if the web site offered a kind of secured transaction payment, a descent return policy, focus on product images and a variety of product sizes.
Shim et al. (2000), assumed for the consumers of the apparel products that are not going to be convinced by attributes such as the time which is necessary to conclude a transaction because they are going to enjoy their shopping experience. A virtual model image and cost incentives are more valuable to motivate apparel shoppers to buy online (Verton, 2001).
The contradictory conclusions clearly showed that online shopping intentions for apparel requires different combinations of online attributes and demographic data to be predicted (Watchravesringkan and shim, 2003).
The Use of the Attitudes to Predict Behavior-Attitudes-Behavior Relationship
Decades of research have indicated the existence of a relation between attitude and behavior, which is not stable, fundamentally complex and quite dependent to the circumstances (Cialdini, 2001). In addition, many researchers attempted to elicit the corresponding behaviors like Ajzen(1991), Ajzen and Fishbein (1980), Ajzen & Madden (1986), Bargh et al (1996) and Fazio et al (1982). Recent research reviewed the effects of attitude-influence strategies and behavior (Albarracin and Kumkale, 2003).
For example, an advertisement declares the beneficial act of a new vaccine generates expectations to the marketers of immediate response of the consumers to purchase the vaccine. However, influencing and motivational important pro-vaccine attitudes may affect the consumers to avoid the purchase of the vaccine (Albarraccin and Kumkale, 2003). There is a need to refer into the vast variety of the degree to which attitudes predict behavior (So et al., 2005).
Various researchers investigated the effects of the attitude-behavior relation with the prior experiences and thoughts (Ajzen, 2001). The influence of the cognitive load and good mood (Blessum et al., 1998) the existence of both direct and indirect experience and the accessibility of alternative actions (Posavac et al., 1997) towards an object.
Recent studies indicated the two theoretical perspectives which specified the processes by which attitudes form the behaviors (Albarracin 2006). According to the first one, attitudes are easily accessible and thus increase their influence on behavior when the consumer forms them because of a direct experience (Regan and Fazio, 1977).
Furthermore, they are even more affective when the consumers are highly motivated to think about the attitude object (Cacciopo and Rodriguez, 1986). Both direct experience and personal involvement urge people to generate their attitudes. As a result this cognitive work increases the availability of attitudes as a basis for future behavior (Foxall, 1993). The consumers accessibility to attitudes enables them to take decisions about behavior and process all the necessary information (Fazio, 1989).
Moreover, the specific access to the attitude increases the attitude-behavior association and the factors that increase attitude accessibility. When the consumers focus strongly on an issue the correspondence between attitude and behavior is extremely high (Cacciopo and Rodriguez, 1986). Additionally, the recurrent expression of the attitude and direct behavioral experience are associated with both the increase of attitude accessibility and attitude behavior correspondence (Fazio et al., 1982).
As a conclusion, the specific theory notes the positive relation of the amount of thought for an object to the verified expressions and reports of the attitude. Furthermore, the existence of a direct behavioral experience could increase the attitude accessibility and the connection between attitude and behavior (Albarracin and Kumkale, 2003).
According to Ajzen (1996), attitudes tend to be more stable when the data that shaped them is still relevant or exist when the consumer acts on behavior. Presumably, the formation of the information that gives way to attitudes significantly increases the attitude behavior relation. As a result when the initial information are relevant at the behavior point consumers will display greater attitude-behavior correspondence and will develop more stable attitudes and are going to experience important attitude-behavior correlations (Ajzen and Sexton, 1999). In contrast, attitudes towards objects and attitudes unrelated to behavioral outcomes may require additional cognitive work to define behavior (Glasman and Albarracin, 2003).
Attitudes are relatively a good prediction method to behavior. However the complexity of the human nature creates a number of limitations to the connection between attitudes and behavior (Hyytia and Kola, 2005):
- Attitudes are not static and on the contrary they are subject to changes. The time interval between the measurement of the attitudes affects the relation between attitudes and behavior. Attitudes based on personal experience such us the purchase of a product are more stable than information gathered from secondary sources. Moreover, the social environment may create fundamental factors with a stronger impact on behavior than personal attitudes (Engel et al., 1993).
- The easy acceptance of the attitudes as predictors of the consumers behavior demands the clear connection between these attitudes and the behavior. However, many researches focus on the formulation of behavior (Cialdini, 2001).
- Attitudes must be assessed together to create an attitude-behavior relation (Eagly and Chaiken, 1993).
- If past behaviors are still alive the recalled attitudes can not cause any affect to the recall procedure (McFarland and Fletcher, 1981).
Online Paisley Consumers Paisley behavior
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Local Culture as a marketing tool
The local culture described from the majority of the consumer behavior books as an important ingredient of the consumer behavior and moreover one of the perspectives of the segmentation (Jobber, 2007; Czinkota and Kotabe, 2001; Boyd et al., 2002; Hoyer and McInnis, 2007).
Every International or global retailer should take under consideration the local culture and the oddities which come along if the key aspect is the success (Nakata and Sivakumar, 1996;). Major researchers focused on the miscarriage of expansion plans because of the differences in culture (Ricks, 1993). If a firm is up to an entry in another country, nation or ethnos there is an extra need for studying the cultural differences based on a marketing approach (Steenkamp, 2001). There is not really a totally accepted method for the definition and the rating of the cross cultural oddities.
Hofstede (1980) focused on five elements the power distance, the individualism versus collectivism, masculinity versus femininity, uncertainty avoidance and long term versus short term orientation while he was trying to spot the oddities between the nations. A lot of criticism upon Hofstede's methods (Triandis et al., 1990; Yeh, 2005) left space for other models to be proposed (Schwartz 1994, Scwartz and Ros, 1995; Trompenaars, 1993). The hofstede's model has been used mainly by academics and for use as a guide to cultural studies (Sivakumar and Nakata, 2001).
The researchers concluded several studies and described the adjustments on the cultural oddities and local idiosyncrasies of the brands, web site design etc., essential for succeeding (Usunier, 1996; Herbig, 1998;Mooij de, 2003b).Moreover, because of the differences of the Greek Culture any online apparel retailer who wish to approach the Greek consumers may emphasize in the Hofstede's model (Zahir et al, 2002).
Through the study of the Zahir et al., was clear the connection between the Hoftsede's elements and the differences of the web site design in other countries than the origin. In addition, Kumar and Baack (2005) declared that the Internet sites represent the ethic and cultural values of their native countries.
Attributes Paisley of Paisley the Paisley online Paisley shopping
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Paisley Perceived Paisley risk
The perceived risk is defined as the Paisley amount Paisley and Paisley the Paisley nature Paisley of Paisley uncertainty Paisley and/or Paisley the Paisley consequences Paisley experienced Paisley by Paisley a Paisley consumer Paisley through Paisley every Paisley stage Paisley of Paisley the Paisley purchase processPaisley process Paisley (Cox Paisley and Paisley Rich, Paisley 1964; PaislePaisley Cox, Paisley 1967 Paisley ;). Paisley Uncertainty Paisley is Paisley not Paisley a Paisley figure Paisley we Paisley can Paisley easily Paisley identify Paisley and Paisley measure. Paisley For Paisley example Paisley if Paisley a Paisley consumer's Paisley aspect Paisley is Paisley to Paisley buy Paisley a Paisley suit Paisley to Paisley fit Paisley his Paisley business Paisley status, Paisley it Paisley is Paisley uncertain Paisley which Paisley brand Paisley looks Paisley more Paisley professional. Paisley Consequences Paisley in Paisley most Paisley of Paisley the Paisley cases Paisley are Paisley Paisley functional Paisley or/and Paisley performance Paisley issues. Paisley Paisley It Paisley is Paisley normal Paisley to Paisley guess Paisley that Paisley if Paisley the Paisley potential Paisley consequences Paisley become Paisley really Paisley important Paisley and Paisley the Paisley perceived Paisley risk Paisley grows, Paisley the Paisley information Paisley search Paisley is Paisley larger Paisley (Urbany Paisley et Paisley al., Paisley 1989).
Many researchers published several studies and identified the following main categories of risk which may affect in some of the cases the purchase intention: economic, social, time, performance and emotional risks (Kim and Lennon, 2000; Shimp and Bearden, 1982; Garner, 1986). The economic risk is the belief that our purchase may lead to a money loss or to a product malfunction (Garner, 1986). The social risk is the belief that the product we have purchased will not be accepted by our friends or by our family (Dowling and Staelin, 1994). Time risk express the belief that the time or the effort spent for concluding a purchase may be wasted if the goods need to be repaired or replaced (Bauer, 1967). The performance risk is about the functionality of the product and the expectations of the purchaser (Kim and Lennon, 2000). The emotional risk refers to the behavioral problems that will arise next to any purchase of problematic products (Jacoby and Kaplan, 1972). Roselius (1971), mentioned as well the physical risk which describes the dangers (health or safety) which may occur by using a product.
In most of the cases, researchers argue that every risk category may lead to a specific group of products (Garner, 1986; Stone and Gronhaug, 1993). Through their researches, concluded that the purchase intention affected more from the economic, emotional and social risks for tangible goods and by time and performance for the non tangible goods like services (Ganrer, 1986).
In our early attempt to spot the main fears of the consumers, we assume that any click-shop purchase includes increased risk than the traditional brick-shop purchase (Akaah and Korgaonkar, 1988). The feel and touch inspection seems impossible through online shopping and this fact creates doubts next to any purchase (Teichgraeber, 2001).
Perceived Risk and Online Shopping
Online shopping is a quite new alternative for the majority of the purchasers and therefore firms will have to adjust their policies to attract consumers to try the online shopping experience. Researchers concluded several studies and agreed that online shopping didn't fulfilled the expectations of the marketers and therefore is necessary a major growth to meet the expectations of the online retailers (Swinyard and Smith, 2003; Anchkar and D'Incau, 2000; Prabhaker, 2000).
Shopping online has to be enriched with better and easier interaction than the ordinary shopping channels (Keeney, 1999). The consumers will decide through which online store are going to buy by using four main prerequisites: variety, screening, trust and product information (Alba et al, 1997). Because of the interactivity of the web in our days, consumers may leave references and even rate the online retailers in public(Hunt, 1999). Moreover, consumers will use the internet to compare and evaluate different products in such a large scale that could lead into a price drop (Rowley, 2000). The convenience of shopping at home without hassle seems important for the consumers as well (Jarvenpaa and Tractinsky, 1999). Findings tend to encourage online shopping as innovative and more convenient than the store shopping (Szymanski and Hise, 2000).
In addition, online shopping through several factors remains an uncertain way of shopping (Drennan et al., 2006). The consumers is impossible to feel and touch the products and must trust the information and pictures provided by the seller (Jarvenpaa and Tractinsky, 1999). The security, trust, certificates and communication protocols create even greater uncertainty (Turban et al., 1999). The above mentioned factors multiply the perceived risk of online shopping and about fifty percent of the Internet users are not using the Internet for online shopping (Teichgraeber, 2001)
The literature over the last decade defined that "perceived risk is more powerful at explaining consumers behavior since consumers are more often motivated to avoid mistakes than to maximize utility in purchasing" (Mitchell, 1999, p.163). Tan (1999) compared advantages and disadvantages of the traditional store versus the online store. Clearly the findings presented the increased perceived risk taken by consumers which shop goods online than shop in traditional stores. Moreover, Bhatnagar et al. (2000) focused on two perceived risk types: product risk and economic risk. Product risk is connected with the performance risk, which defines the quality of the purchased product (Kim and Lennon, 2000). The complexity of a product or the price increases the perceived risk and the economic risk contains the tangible and intangible aspects of the consumers. As a consequence the consumers are worried not only for losing their money but as well about their private information provided at the transaction (Szymanski and Hise, 2000). Consumers may consider the online transactions dangerous and with questionable reliability because of their parallel use of their personal information (Biswas and Biswas, 2004; Drennan et al., 2006).
Furthermore, Drennan et al. (2006) noticed that even when Internet users with extensive technological skills apply methods to ensure their transaction privacy it doesn't actually affect their online purchasing behaviours.
Another study clearly identified the key role of the perceived risk next to frequent online consumers versus the "trial & leave" consumers (Lu et al., 2005). Garbarino and Strahilevitz (2004) identified a rundown of the perceived risk when distributive consumers purchase online. Furthermore, studies focused on the negative effect of the perceived risk upon the advantages (Bhatnagar and Ghose, 2004) and as an obstacle to adoption (Yang and Yun, 2002).
Greek Online Facts
Greek Internet Use in the European Context
Greece is one of the member countries of the European Union counting a population of more than 11 million people and the middle GNP per capita is about €16.000 (Global-Reach, 2003; Nielsen/Nestratings, 2002; Ecoworld, 2002; Internet world stats, 2004). The users of the Internet during the past decade were quite limited but during the last five years climbed up to 38% of the total population (Eurostats, 2009;). Of course we are holding one of the last places among the rest of the European countries.
During the year 2006 the internet usage increased significantly in comparison to 2005 provided statisticss (Internet world stats, 2006). The observatory for the Greek information society conducted a survey that referred to the usage of the information and Communication technologies in the Greek households for the year 2006. The main outcomes are:
- The access points, with no restrictions to the gender, age and educational level are home and workplace. This fact declares that users don't prefer to access the net through "Internet cafes" or by using the laboratories of the educational institutions.
- The use of the Internet mostly is for the collection of information. Among the most important activities was the exchange of e-mails, some sort of amusement, online games, travel information, weather forecast and reading newspapers or magazines.
- The males make wider use of the pc's and the internet. The use among the males reached the 32% instead of the female which was 21%. Females have chosen the University at first for internet usage and males preferred home and the workplace.
- Males mostly use the Internet for purchasing online goods or services, e-banking and software downloads. Females make an extensive use of the internet for job seeking or CV submission. Furthermore, females seek for travel information and travel services more than the males.
Internet Usage and Age
In 2008, according to the global reach (2008) the age of the people which used more the Internet was between 16-24 (80,6 and 58,6 accordingly). It is more than obvious the existence of a negative connection between internet usage and Users age in Greece. we will have to mention that only 2.5% of the people from 65 to 74 have used the Internet in 2008 (Internet World Stats, 2008).
During the years 2005 and 2006 the statistics presented a significant increase of the internet usage in the age groups 35-44 and 55-64. During the same period of time the internet usage among the age 16-24 increased for more than 10%. A special focus to the place of access provides data which show that 71,5% of the users accessed the Internet at home, 28,3 % in Internet cafes, 17,4 in educational institutions, 10,1 at the workplace, 15,3 at school and finally at friend's houses 11,8% (Nielsen/Netratings, 2007).
Greek people from 16-24 age made use of the Internet mostly for entertainment reasons (61,2%), downloads of games (67,8%), software downloads (33.3%), chat and messaging in general (52.5%) and finally music downloads for more than 37% (Global reach, 2007).
Level of Education
Most of the Internet users are people with a higher or highest educational level (Internet world stats, 2008). The internet usage of the senior high school graduates increased for more than 4,5% while the usage of the Internet increased for just 2,5 % high school graduates. One of the most important facts is the higher ever Internet usage by the senior high school graduates and the university graduates according to the survey conducted by the Vprc (2008) for the Greek ministry of economics and finance.
The usage of the Internet daily increased in general in both online time and number of the users. The biggest increase was in Internet usage by senior high school graduates and university graduates (Vprc, 2008).The senior high school graduates and high school graduates have chosen internet cafes, home and workplace for accessing the Internet (Internet world stats, 2008). The major use of the of the Internet for the high school graduates is dowloading games or participation to online games.
Regions and Internet Usage
According to the survey conducted by the Vprc (2007) for the Greek ministry of economics and finance the Greek regions tremendously increased the Internet Usage and their Internet access . A more detailed analysis reveals:
- Increase of the Internet usage in Attica for more than 46% and the Peloponnese for about 34,5%.
- Internet access increased in Northern Aegean 23,4% and in the Western Greece for 24,5%.
- The regions of the Attica , Macedonia, Ionian islands and Peloponnese used the Internet for electronic purchases of products and/or services. The regions of Southern Aegean and Crete used the Internet mostly for email exchanging and communication.