Electronic-commerce has become an important channel for conducting business. Researchers as well as market executives are trying to better understand online consumer behavior. One model used by researchers to understand behavior in the information systems field in general is the technology acceptance model (TAM). The TAM variables are perceived usefulness, perceived ease of use, and intentions. In this study, we suggest the extension of the TAM for its application in the E-commerce field. The original TAM will be extended, by adding four predictor variables. The four predictor variables are process satisfaction, outcome satisfaction, expectations, and E-commerce use. In addition, the TAM will be extended by measuring actual behavior as opposed to measuring intentions as a substitute for actual behavior in previous TAM application studies. We suggest measuring actual use variable in terms of four criterion variables, namely, purchase, access number, access total time, and access average time. The extended TAM is expected to better explain actual behavior in E-commerce environments than the original TAM.
Electronic-commerce (E-commerce) is defined as all aspects of business and market processes enabled by the Internet. E-commerce is rapidly becoming a viable means of conducting business, as evidenced by the tremendous amounts of money spent online. The United States online retail sales are estimated to reach $278.9 billion in 2015 as reported by Forrester Research (Mulpuru, 2011). As a result, the economic impact of E-commerce is increasing exponentially. Web based companies, Net Enabled Organizations (NEO), and researchers are still trying to understand and predict online consumer behavior; therefore, research in this area is needed.
Information systems (IS) researchers have explored online consumer behavior in terms of online shopping adoption (Bhattacherjee, 2001; Gefen, Karahanna, & Straub, 2003b; Gefen & Straub, 2000; Koch, Toker, & Brulez, 2011; Koufaris, 2002). The most widely referenced adoption model in IS research is Davis’s (1989) technology acceptance model (TAM) (Gefen & Straub, 2000). The TAM is an adaptation of the theory of reasoned action (TRA) (Ajzen & Fishbein, 1980; Fishbein & Ajzen, 1975) for predicting IS adoption (Davis, Bagozzi, & Warshaw, 1989). The TAM has two elements, perceived usefulness (PU) and perceived ease of use (PEOU), that are correlated with the decision to adopt a new technology (Davis, 1989). Although designed to explain new technology adoption, not specifically E-commerce behavior, researchers have recently used the TAM to explore Internet consumer behavior (Bhattacherjee, 2001; Gefen et al., 2003; Gefen & Straub, 2000; Koch, et al., 2011; Koufaris, 2002).
We argue that the TAM in its current form cannot be used to fully explain online consumer behavior as Ecommerce adoption is considerably different from new technology adoption in an organization. One difference is that the decision to buy online is voluntary, while the decision to use new software in an organization is typically mandated by organizational policy. Also, shopping online is one choice among alternatives (e.g. shopping in a conventional store) for the shopper, while more often than not there is no choice among different software or systems mandated by an organization. Although the use of the TAM, as it was originally conceived, is not likely to lead to a full explanation of online consumer behavior, an E-commerce specific, extended TAM may prove useful in explaining such behavior. Hence, there is a need to extend the TAM to serve as an E-commerce adoption model.
2. Theoretical Background
Before developing our model we examined the published body of knowledge about the topic. Our review and evaluation of the literature are presented in the following section. Based on that evaluation and grounded in the literature, our new TAM extending variables are identified.
2.1. The Theory of Reasoned Action
In order to develop an extended model of the TAM with solid conceptual foundations, we need to fully understand its antecedents. The TAM’s major antecedent is the TRA (Ajzen & Fishbein, 1980; Fishbein & Ajzen, 1975). The TRA (Fig.1) is a model developed to predict human behavior in general. Two main elements, attitude towards a behavior and subjective norm, are identified as determinants of behavior (Fishbein & Ajzen, 1975). An attitude towards a behavior is “an individual’s positive or negative feelings (evaluative affect) about performing the target behavior” (p. 216). A subjective norm is “the person’s perception that most people who are important to him think he should or should not perform the behavior in question” (p. 302). A person’s attitude towards a behavior is determined by that person’s beliefs about that behavior. In addition, a person’s subjective norm towards a behavior is determined by that person’s normative beliefs about that attitude (Fishbein & Ajzen, 1975).
Researchers using the TRA as a behavioral intention model should be able to predict the performance of any voluntary act, unless intent changes between assessment and performance of that behavior. Researchers should also be able to predict whether a behavior will occur. However, choice among alternative behaviors was not included (Fishbein & Ajzen, 1975).
People have different sets of beliefs about each behavior. As such, researchers developing behavioral adoption models have to generate the behavior’s related belief set. Moreover, the performance of a certain behavior might lead to new beliefs, which might influence the attitude and, thus, performance (Fishbein & Ajzen, 1975).
A meta-analysis of past TRA research was conducted by Sheppard, Hartwick, and Warshaw (1988) to investigate the relationship between intention to perform a behavior and the actual behavior. The research reports on the TRA were published in the Journal of Consumer Research, the Journal of Marketing, the Journal of Marketing Research, Advances in Consumer Research, the Journal of Personality and Social Psychology, the Journal of Experimental Social Psychology, the Journal of Social Psychology, the Journal of Applied Social Psychology, and the Journal of Applied Psychology prior to 1987. Studies were rejected if the authors had failed to measure all the variables in the TRA, or did not include bivariate/multivariate correlation, or did not use measures that corresponded with the behavior/intention that was studied. Sheppard and his associates reported that the TRA was effective in predicting different behaviors (e.g., study a few hours, go to a weekend job, or write a letter). The frequency-weighted-average correlation was 0.53 for the intention/behavior relationship, and 0.66 for the (attitudes and subjective norm)/intention. They also reported that behavior was predicted using the TRA even in situations that fell outside the boundary conditions set for the model (e.g., behavior involving an explicit choice among alternatives) (Sheppard et al.). Thus, the robustness of the TRA was established.