Behavioural theories of Technology acceptance model

        Theory of Reasoned Action and Theory of Planned Behavior  The persuasive communication is used as a strategy to change behavior and, therefore, it has been studied by behavioral scientists. The source of communication is one of the factors that may generate communication effects and change beliefs, attitudes, intentions, and behavior (Fishbein & Ajzen, 1975, p.452). In previous research the impact of source characteristics has been studied using the theory of reasoned action (TRA) (O’Hara et al., 1991, p. 307). TRA brings together such concepts as attitude, subjective norm, behavioral intention and behavior. According to TRA, behavior is predicted by behavioral intention, which in turn is determined by the attitude towards the behavior and subjective norms (Ajzen & Fishbein, 1980, p.6-8). Social psychology defines intention as a “person’s motivation in the sense of his or her conscious plan to exert effort to carry out a behavior” (Eagly & Chaiken, 1993, p. 168). Intention plays an important role in consumer behavior studies as it is a predictor of the actual behavior. Intention serves as a mediator, when attitudes influence behavior through the influence on intention (Eagly & Chaiken, 1993, p. 168).

        Attitude toward the behavior is a personal factor and it refers to the individual’s judgement that performing the behavior is good or bad (Ajzen & Fishbein, 1980, p.6). TRA is concerned with attitudes toward behaviors, not attitudes toward objects (Ajzen, 1985, p.12). Subjective norm is a social factor and it shows how opinions of important others may influence intention to perform the behavior (Ajzen & Fishbein, 1980, p.6). TRA describes behavioural and normative beliefs as antecedents of attitudes and subjective norms (Ajzen & Fishbein, 1980, p.7). However, Ajzen & Fishbein (1980, p.7) state that for many purposes, it is possible to predict a person’s intention by measuring only attitude toward performing the behaviour, subjective norms and their relative weights. Some researchers extend TRA by including external variables to their studies in order to predict behaviour better (Belleau et al., 2007, p.246). Ajzen & Fishbein (1980, p.83-84) claim that such external variables as demographics, attitudes toward targets and personality traits can influence intentions and behaviour, but only indirectly by their effects on beliefs. TRA is based on the assumption that human beings process available information rationally (Ajzen & Fishbein, 1980, p.5). Therefore, TRA can be used for the study that examines information source and its influence on attitude and purchase intention. According to O’Hara et al. (1991, p. 307) TRA offers a framework for studying source effects, because cognitive belief chain is formed by message acceptance, which in turn is influenced by source characteristics. When individuals process information from others about the product, they consider source characteristics in the process of product evaluation, forming attitudes towards the product, and product purchase intentions (O’Hara et al., 1991, p. 307).

        However, TRA states that intention is not always a good predictor of behaviour, as intentions can change over time due to various circumstances (Ajzen & Fishbein, 1980, p.47). Ajzen (1985) describes both internal and external factors that may prevent individual from performing intended behaviour. Internal factors include individual differences; information, skills and abilities; power of will and emotions (Ajzen, 1985, p.25-27). External factors are comprised of time and opportunity and dependence on other people (Ajzen, 1985, p.27-29). According to Ajzen (1985, p.29), these factors may interfere with the performance of any behaviour. To overcome this problem, another theory, the Theory of Planned Behaviour (TPB) was developed by Ajzen (1985). TPB is an extension of TRA and it is used to explain behaviours over which individuals have incomplete volitional control (George, 2004, p.199). Behaviour that is not under volitional control requires certain abilities or resources that individual do not have, or it depends on the cooperation with another person (Fishbein & Ajzen, 1975, p.371). As a result, person may be unable perform the behaviour even if he intends to do so (Fishbein & Ajzen, 1975, p.371). Therefore, TPB takes into consideration another factor that may influence both behavioural intention and behaviour, perceived behavioural control (George, 2004, p.199). Perceived behavioural control is formed by beliefs about individual’s opportunities and resources needed to perform the behaviour (George, 2004, p.199). According to TPB, successful performance of the intended behaviour depends on person’s control over factors that may prevent actual behaviour (Ajzen, 1985, p.29). Therefore, to predict actual behaviour correctly, both effects of behavioural intentions and perceived behavioural control should be assessed (Ajzen, 1985, p.30).

        In order to explain Internet purchasing behaviour researchers applied both TRA (Kim et al., 2003; Xu & Paulins, 2005; Yan et al., 2010) and TPB (George, 2004; Liang & Lim, 2011; Kang & Kim, 2012). Our research purpose is to examine effects of source credibility and information quality on attitude toward using the information source and purchase intention. Therefore, we examine only influence of these factors on behavioural intention, not actual behaviour. We have chosen to use TRA to examine relationships between variables of conceptual model. TRA can adequately predict behaviours that under volitional control (Fishbein & Ajzen, 1975). When such factors as skills, abilities, willpower and opportunities have negligible influence on successful performance of actual behaviour, this behaviour can be considered to be under volitional control (Ajzen, 1985, p.35). Researchers argue that intention to purchase an item is volitional and very few constraints exist (Belleau et al., 2007, p.246). We believe that people in Sweden have enough opportunities and resources to buy apparel online, therefore, we think that TRA can be used to predict their purchase intentions.

        Both TRA and TPB have been criticized by several researchers. They argue that attitudinal and normative components of TRA are not distinct as subjective norms exert effect on attitudes and vice versa, leading to overlap between these components (Park, 2000, p.163). Nevertheless, Fishbein & Ajzen (1981) proved that attitudes and subjective norms serve as predictors of intentions as they correlate more strongly with behavioural intention than with each other. Additionally, some researchers criticize TPB for neglecting particular factors, for instance affect and emotions (Conner & Armitage, 1998; Wolff et al., 2011). However, Ajzen (2011, p.1116) explains that these factors may influence behavioural, normative and control beliefs, for example person’s mood have effects on belief strength and evaluations, and therefore, not excluded from theory. Moreover, the predictive power of TRA in the context of apparel has been empirically proved by many researchers (Dickson, 2000; Yoh et al., 2003; Xu & Paulins, 2005; Summers et al., 2006; Belleau et al., 2007). Therefore, we believe that TRA can serve as a reliable theoretical framework for this study.

        Attitude Attitude is widely acknowledged as an important concept for marketing research since attitudes serve as predictors of consumer behaviour toward a product or service (Mitchell & Olson, p.318). The concept of attitude takes origins from the field of social psychology. It is defined as a predisposition of an individual to evaluate a particular entity with some degree of favour or disfavour (Eagly & Chaiken, 1993, p. 1-2). Perloff (2003, p. 39) defined attitude as “a learned, global evaluation of an object (person, place, or issue) that influences thought and action”. He emphasized the social nature of attitudes as they are formed through interaction with other people (Perloff, 2003, p. 40). Moreover, Perloff (2003, p.40) points out that attitude is first of all an evaluation, when a person makes judgement regarding some issues or people. Person evaluates some entity or thing, called attitude object, which can be abstract or concrete (Eagly & Chaiken, 1993, p. 4-5). Attitudes differ on the basis of their strength. Strong attitudes differ from weaker and ambivalent attitudes, and they are more likely to affect judgements and guide behaviour (Perloff, 2003, p. 56). Furthermore, attitudes are not always internally consistent, meaning that person can feel both positively and negatively about another person or issue (Perloff, 2003, p. 72). However, people are motivated to resolve uncomfortable inconsistency to achieve a harmonious state of mind (Perloff, 2003, p. 53).

        The concept of attitude has particular importance for marketing research as marketers want to change consumer behaviour, and they try to do so by influencing attitudes (Perloff, 2003, p. 97). Analysis of an individual’s attitude gives practitioners the opportunity to explain and forecast his/her behaviour (Mohammad, 2014, p.59). Therefore, investigation of relationships between attitudes and behavioural intention in the context of online shopping can help to develop recommendations for marketers how to influence consumer behaviour online and how to persuade consumers. Previous studies of online shopping show that attitude has significant influence on behavioural intention. George (2004) identified that attitudes toward Internet purchasing affected actual purchasing behaviour. Similarly, Wu & Liao (2011) in their study of consumers’ behavioural intention to use Internet shopping show that attitude toward Internet shopping has positive influence on intention. Therefore, the construct of attitude has been added to this study to investigate its influence on behavioural intention. TRA considers attitude toward behaviour as a determinant of behavioural intention (Ajzen & Fishbein, 1980). In this study we explore the use of information source for making purchase intention as a behavioural component. Therefore, we examine attitude toward using the information source. We argue that consumers, who have positive attitude toward using particular information source are likely to follow this information, and consequently form an intention to purchase a product that is described by information source. The attitude towards using the information source is further described in the section Conceptual model.

        Subjective norms According to Fishbein & Ajzen (1975, p.302) subjective norm ‘is determined by the perceived expectations of specific referent individuals or groups, and by the person’s motivation to comply with those expectations’. Referents can include significant other, friend, colleague, social status and media (Belleau et al., 2007, p.248). Reference groups or individuals, whose expectations are important, may vary depending on behavioural situation, and expectations of more than one reference group can be considered by individual (Fishbein & Ajzen, 1975, p.302). In order to predict behavioural intention, it is necessary to assess subjective norm together with attitude toward the behaviour (Ajzen & Fishbein, 1980, p.57). Subjective norm should be measured in correspondence to the intention in action, target, context, and time elements (Ajzen & Fishbein, 1980, p.58). In studies of purchase intention, subjective norms can be defined as ‘consumer’s perceptions of social pressures by others regarding the purchase of the product of interest’ (Belleau et al., 2007, p.248).

        Regarding subjective norms in the context of online shopping, previous studies revealed controversial results about influence of subjective norms on behavioural intentions. Some studies found that subjective norms have insignificant effect on behavioural intention (George, 2004; Lin, 2007; Wu & Liao, 2011). However, some researchers proved positive influence of subjective norms on behavioural intentions. Gunawan & Huarng (2015) in their study of viral effects of social network and media on purchase intention discovered that influence from friends and relatives creates pressure and consequently influences consumer’s intention to purchase virally marketed product or service. Kim et al. (2009) examined role of subjective norms and eTrust in acceptance of eCommerce websites and also found positive relationships between subjective norms and behavioural intention. Therefore, subjective norms were included to this study in order to predict behavioural intention accurately. We argue that in different contexts influence of subjective norms can vary. The purpose of this master thesis is to investigate influence of three information sources on purchase intentions; therefore, for one source the influence of referents can be more important determinant of behavioural intention than for others. In order to examine this influence, we included subjective norms as independent variable to this study.

Behavioural intentions and actual behavior:

        Behavioural intention is “a measure of the likelihood that a person will engage in a given behavior” (Ajzen & Fishbein, 1980, p. 42). According to TRA (Fishbein & Ajzen, 1975), behavioural intention is predicted by individual’s attitude toward a given behaviour and subjective norms, and it serves as a predictor of actual behaviour. Ajzen & Fishbein (1980, p. 47) argue that behavioural intention can predict actual behaviour accurately if measure of intention corresponds to the behaviour. However, intentions can change over time and to predict behaviour accurately, the time interval between intention and behaviour should not be long (Ajzen & Fishbein, 1980, p. 47). At the same time aggregated intentions of many people are more stable than intentions of an individual (Ajzen & Fishbein, 1980, p. 48).

        In our study we investigate purchase intention as a behavioural intention component. Intention to purchase online can be defined as a strength of a consumer’s willingness to perform a specific purchasing behaviour by means of the Internet (Limbu et al., 2012, p.137). TRA has been commonly applied by researchers in marketing-related studies to predict purchase intentions through attitude toward purchasing and subjective norms (Summers et al., 2006). Previous studies in the context of apparel shopping show that purchase intentions are influenced by attitudes and subjective norms. Kim et al. (2003) supported TRA by proving that both attitude and subjective norms serve as important determinants of online purchase intention of clothes. Similarly, Summers et al. (2006) in their study of luxury apparel purchases found that purchase intention of luxury apparel products is significantly influenced by attitude toward the behaviour and subjective norms.  Information Adoption Model  Theoretical foundations of Information Adoption Model Information can have different impacts on individuals and generate various responses as recipients vary in perceptions and experiences (Chaiken & Eagly, 1976). In order to understand the influence of information on individuals, information adoption process was developed (Cheung et al., 2008, p.231). Information adoption process refers to the internalizing knowledge, where the information is adopted and transformed into internalized knowledge and meaning (Nonaka, 1994). To check how people are influenced when they adopt an information in online environment, Sussman & Siegal (2003) integrated the dual process theories of informational influence and the Technology Acceptance Model (TAM).

        The theoretical foundation of Information Adoption Model lies in the Theory of Reasoned Action (TRA) (Fishbein and Ajzen 1975, Ajzen and Fishbein 1980) and its derivative theory, the Technology Acceptance Model (TAM) (Davis 1989). They state that formation of the individual’s intention to adopt or reject a behaviour or technology depends on the individual’s beliefs and assessments of the consequences of adoption (Sussman & Siegal, 2003, p.49). The Information Adoption Model suggests that in a similar manner as people adopt a behaviour or a technology, they can form intentions towards adopting ideas and behaviours. Therefore, factors that affect the adoption of a behaviour or a technology, can influence the adoption of an information. Davis (1989) found that the beliefs about usefulness of adopting a particular behaviour strongly affected adoption intentions. Consequently, the usefulness of received information should predict the intentions of adopting a given information (Sussman & Siegal, 2003, p.49). In addition, social cognition research provides support for the centrality of message usefulness as it considers usefulness as an indicator that determines whether the message is noticed (Kiesler & Sproull, 1982). Information that helps to provide a solution to a task receives precedence in judgment and choice processes (Feldman & Lynch, 1988). As a consequence, the evaluation and adoption of an information can be considered as an informational influence, where the provided information influences its recipients to the degree that they consider it as a useful evidence about reality (Eagly & Chaiken 1993, p. 630; Sussman & Siegal, 2003, p.49).

        While TAM and TRA are useful to provide understanding how behavioural intentions toward information adoption are formed, they do not explain the influence process itself (Sussman & Siegal, 2003, p.50). The Elaboration Likelihood Model (ELM) states that a message is able to influence human attitude and behaviour in central and peripheral way (Cheung, 2008, p.231). Central cues relate to the nature of arguments while peripheral cues refer to the issues indirectly related to the arguments that are used to evaluate content (Cheung, 2008, p.231; Sussman & Siegal, 2003 p. 50). According to information adoption model, there are two crucial propositions (Cheung et al., 2008, p.231). First, information quality as an important central cues, is able to influence the information process (Zhu et al., 2016, p.9-10), and second, source credibility as a peripheral cue has a critical role in the persuasive information process (Sussman & Siegal, 2003, p.50).

        In the scope of online buying, information quality refers to the product information and shopping advices provided by fellow consumers, which constitute to be a crucial content cue in decision making process (Zhu et al., 2016, p.9-10). Therefore, information quality describes the informational influence from online reviewers. Hence, in accordance with the IAM model, this study employs information quality as a central cue. Source credibility in context of online buying relate to other consumers that experienced the product and provide information about it online. As individuals who review products, differ in product knowledge level, their credibility is a crucial non-content related cue for potential customers during decision making process (Zhu et al., 2016, p. 9-10). Thus, in alignment with the IAM model, this work uses source credibility as an important peripheral cue. According to the IAM model, information quality together with source credibility affect the attitude toward information usefulness. Information quality refers to the persuasive strength of arguments included in the information (Bhattacherjee & Sanford, 2006). In the online environment, the purchasing decisions are affected by the customer’s perception of information quality of the received message. If customers perceive the information quality as fulfilling their needs and requirements, they are more inclined towards buying behaviour (Cheung et al., 2008, p.234).

        Even though IAM is commonly used to examine informational influence, it received criticism from researchers. Erkan & Evans (2016) claim that IAM has limited scope as it investigates influence of source credibility and information quality only on information adoption. Therefore, researchers propose to combine IAM and TRA in order to examine the influence of information characteristics on consumer’s behaviour, particularly purchase intention (Gunawan & Huarng, 2015; Erkan & Evans, 2016). As the purpose of our study is to examine effects of source credibility and information quality on attitude toward using the information source and purchase intentions, we decided to combine IAM and TRA and adapt the model from Gunawan & Huarng (2015) to the context of our study.

        Information quality is defined as “the persuasive strength of arguments embedded in an informational message” (Bhattacherjee & Sanford, 2006, p. 811). It refers to the value of the information perceived by the recipient (Negash et al., 2002; Cheung et al., 2008). From the standpoint of IAM, information quality as a central cue plays an important role in informational influence (Sussman & Siegal, 2003, p.50) and is found to have an impact on information adoption (Zhang & Watts, 2008), attitude change (Teng et al., 2014) and behavioural intentions (Zhu et al., 2016; Cheung et al., 2008). Several studies argue that information quality influences the attitude of message recipients in the context of online environment (Sia et al., 1999; Cheung et al., 2008). When online review is perceived to contain valid arguments, the recipients will develop a positive attitude towards the information. On the other hand, if an online review is perceived to have invalid arguments, recipients will develop a negative attitude towards information (Cheung & Luo, 2009, p.15). Consequently, online reviews that provide valid and strong arguments could influence the attitude towards information and its source. Furthermore, the way recipients perceive the quality of information can influence their purchasing decisions. It the information meets the user's’ needs and requirements, he/she is more inclined to follow the recommendation during decision making process (Olshavsky, 1985). Thus, the customer’s perception of information quality can determine his/her potential buying behaviour (Cheung et al., 2008, p. 234).

        Users search for information that are supported by valid and strong arguments (Cheung & Luo, 2009, p.29). To make sure that the online review is valid, users evaluate the quality of information embedded in the comment (Heinrichs et al., 2011, p.349). Information quality can be measured in terms of accuracy, timeliness, completeness, relevance, and consistency of the information provided (DeLone & McLean, 2003). Heinrichs et al. (2011, p.349) argues that measuring information quality by these dimensions is preferable because these attributes facilitate sharing the information in online environment. This study adopts dimensions used by Cheung et al. (2008) that include dimensions of relevance, accuracy, timeliness and comprehensiveness. For the purpose of the research of this work, timeliness was excluded since it was found insignificant by Cheung et al., (2008). Timeliness is also often ignored in online reviews research (Ives et al., 1983), as the website has to be regularly updated to provide valuable information. If this condition is not met, users may see the website as less helpful (Liu, 2006). Similarly, users pay more attention to websites that contain more recent online reviews (Zhao et al., 2015, p.1347). Moreover, as the scope of this study is fashion, the apparel industry launches new collections every season, therefore online product reviews regarding clothes are expected to be up-to-date (Park & Cho, 2012). Therefore, relevance, accuracy and comprehensiveness are considered as important elements of high quality online reviews.