ATAQUES DIRIGIDOS

E-commerce adoption can be understood through the lens of technology adoption. There are numerous theories which have been used to investigate adoption of technologies. The most frequently applied theories in technology adoption are the technology acceptance model (TAM) (Davis 1989, Davis, Bagozzi & Warshaw, 1989), theory of planned behaviour (TPB) (Ajzen, 1985, Ajzen 1991), unified theory of acceptance and use of technology (UTAUT) (Venkatesh, Morris & Davis,2003), diffusion of innovations (DOI) (Rogers 1995) and the Technology Organisation Environment (TOE) framework (Tornatzky and Fischer 1990).

Molla & Licker (2005) explained that technological imperative models such as diffusion of innovation (DOI) and technology acceptance model (TAM) consider complexity, compatibility, relative advantage, ease of use, usefulness and other attributes as key drivers of adoption. Literature review reveals the explanatory power of adoption models that are based on the interaction perspective. Studies by Kuan & Chau (2001) have suggested a model of EDI adoption based on technology, organization and environment framework which explain differences in e-commerce adoption.

Other researchers noted that research into technology-based innovation has been productive (Elliot & Loebbecke, 2000:29) and several technology models have been developed. The Technological, Organisational and Environmental (TOE) model was developed by Tornatzky and Fischer (1990) after realizing the importance of technology adoption in order to evaluate technology adoption. Rogers (1983) Theory of Innovation Diffusion in organizations is consistent with the TOE model. The Resource-based View (RBV) theory by Caldeira & Ward, (2003) was developed to aid organizations achieve sustainable competitive advantages.

RBV is of relevance to innovation research because innovation adoption is potentially an element of competitive success. It takes an inside-out or firm specific perspective by focusing on the internal resources of the firm as the major determinant of its competitive success (Dicksen,

1996). Based on the RBV, innovation does not come simply from scanning the external environment in search for market opportunities, but from looking inside the firm to develop and build on core competencies. This indicates that the ability to innovate is related to the resources of the firm (Del Canto & Gonzalez, 1999).

Roger‟s (1993) Diffusion Theory and Davis (1989) Technology Acceptance Model (TAM) are most commonly discussed technology models on Information Technology (IT) adoption (Datta, 2011:7). In addition, to trace the impact on adoption, Roger‟s Diffusion Theory focuses on the key characteristics of technological innovations Datta (2011:7). Furthermore Davis (1989) TAM built on Azjen and Fishbein‟s Theory of Reasoned Action (TRV) model focusing on behavioral elements influencing decision making in IT adoption.

Rogers‟s (1962) model of innovation adoption can be applied successfully to a variety of innovations. Originally serving the social science area, and in particular rural innovation adoption, and directed toward the individual consumer, it has evolved throughout different decades to encompass technological innovations and to serve both consumer and business adoption units. The model is based on the innovation-decision process which is “the process through which an individual (or other decision-making unit) passes from first knowledge of an innovation, to forming an attitude toward the innovation, to a decision to adopt or reject, to implementation of the new idea, and to confirmation of this decision” (Rogers, 2003:170).

According to (Moore and Benbasat, 1991; Rose & Straub, 1998), TAM and Diffusion of Theory are similar particularly with key characteristics of perceived usefulness, perceived ease of use, social influence and facilitating conditions. Datta (2011:8) points out that when there are concerns on issues such as poverty, famine, hunger, illiteracy and endemic diseases there is high opportunity cost of e-commerce adoption. Both TAM and Diffusion Theory models allow focus on the impact of key technology specific and external factors on the adoption of IT and that both of these theoretical approaches are formulated in an attempt to achieve goals by dealing with determinants of e-commerce adoption (Datta, 2011:8).

The unified theory of acceptance and use of technology (UTAUT) model by Venkatesh, Morris and Davis. (2003) is an extension of the original TAM, taking into account several new constructs. The model was formulated based on eight competing technology acceptance models: Davis‟ Technology Acceptance Model (TAM), Innovation Diffusion Theory (IDT), the

Theory of Reasoned Action (TRA), the Motivation Model (MM), the Theory of Planned Behavior (TPB), the Combined TAM and TPB (C-TAM-TPB), the Model of PC Utilization (MPCU) and Social Cognitive Theory (SCT) (Venkatesh et al., 2003). The model aims at looking at behavioural intention and the use behaviour of technology. The three direct determinants from the first element include: performance expectancy, effort expectancy, and social influence; and the second has one direct determinant which is facilitating conditions; and four moderators which are gender, age, experience, and voluntariness of use (Venkatesh‟s et al.,2003). These determinants are discussed later in the chapter.

Table 2.3: Summary of different theories and models which have been applied in technology adoption studies.

Theory Overview Examples of studies which applied model

Technology Acceptance Model (TAM) (Davis, 1989)

Examines key characteristics of

perceived usefulness,

perceived ease of use, social influence and facilitating conditions

Klopping & McKinney(2002) Extending the Technology Acceptance Model and the Task-Technology Fit Model to Consumer E-Commerce

Gefen & Straub (2000) Relative Importance of Perceived Easeof Use in IS Adoption

Thijs, Broekhuizen & Eelko (2002)Investigating the Effect of Consumer Traits on the Relative Importance of TAM Constructs in an E-Commerce Context

Diffusion of Innovation (DOI) (Roger, 1995)

Focuses on characteristics of technological innovations to trace the impact on adoption

Zhu et al. (2005) Usage and value of e-business by organizations.

Pedersen, Methlie & Thorbjørnsen (2002) Understanding mobile commerce end- user adoption

Technological Organisational Environmental model (TOE) (Tornatzky & Fischer, 1990)

Evaluate technology adoption. TOE model is consistent with the theory of innovation diffusion in organizations by Roger‟s (1983

Kuan & Chau (2001) A perception based model for Electronic Data Interchange (EDI) adoption.

Oliveira & Martins (2010) Firms Patterns of E-business Adoption.

Zhu et al. (2003) E-business adoption by European firms

Resource-based View (RBV) (Caldeira & W ard, 2003)

Facilitate the understanding of how organizations achieve sustainable competitive advantages.

Zhu & Kraemer (2005) Post adoption variations in usage and value of e-business by organizations.

Unified theory of acceptance and use of technology (UTAUT) Venkatesh et al. 2003)

Looks at behavioural intention and the use behaviour of technology.

Louh, Kallioja & Oittinen (2006) Factors affecting the use of hybrid media applications.

Rosen, Tulsa & Hall (2002) The effect of personal innovativeness in the domain of information technology on the acceptance and use of technology.

Vijayasarathy(2002) Predicting Consumer Intentions to Use Online Shopping. Shih (2004) Extended technology acceptance model of Internet utilization behavior.