｢정보시스템연구｣ 제18권 제4호

한국정보시스템학회

2009년 12월, pp. 105～130

A Longitudinal Analysis of the Influence Process in IT Acceptance Considering Intrinsic and Extrinsic Motivations Using the Elaboration Likelihood Model

* Department of Business Administration, Daegu University, South Korea, woong3041@empal.com, 82-53-850-6272

Woong-kyu Lee*

			<목 차>
I. Introduction II. Theoretical Background 2.1 Elaboration Likelihood Model 2.2 Intrinsic Motivation III. Research Model IV. Research Model 4.1 Measurement 4.2 Data Collection and Analysis Method				V. Data Analysis 5.1 Measurement Model 5.2 Structural Model 5.3 Discussion of Data Analysis VI. Implications and Conclusions 6.1 Discussion of Findings and Implications 6.2 Limitations of Research 6.3 Further Studies Reference

Ⅰ. Introduction

According to traditional IS theories, which are generally predicated on social psychology, IT acceptance is determined by beliefs about or attitude toward IT use. Some of these theories have been suggested as a research framework, such as the technology acceptance model (TAM) (Davis, 1989; Davis et al, 1989), which has already been theoretically revised and improved, and also applied to a variety of IT types and users (Lee et al, 2003; Legris et al, 2003). Although these studies have generated rich theoretical knowledge and compelling explanations of the determinants of adoptions and use decisions (Venkatesh and Bala, 2008), the processes of shaping and changing beliefs by external sources after or during IT acceptance, that is, the influence processes regarding IT acceptance, have been studied only rarely thus far (Bhattacherjee and Sanford, 2006).

Nevertheless, recently some studies have attempted to elucidate the processes of influence concerning IT acceptance using the elaboration likelihood model (ELM). According to the ELM, when messages are sent for the purpose of persuasion, they are processed via both a central and a peripheral route; the central route involves the comprehension and learning of the message via cognitive efforts, and the peripheral route relies on certain cues that are readily obtainable from a source, message, or situation. Elaboration likelihood-that is, the ability and motivation to elaborate on the issues in a message-determines the primary path of persuasion between the central and peripheral routes for the formation of attitudes or perceptions (Cacioppo and Petty, 1984; Petty, 2001; Petty and Cacioppo, 1981; Petty and Wegener, 1999; Wood, 2000).

What the studies for ELM-related IT acceptance have in common is that they have all explored the relationship among two persuasion routes, beliefs, or attitudes and intentions. One of their principal emphases is the analysis, in these relationships, of the moderating effects of job relevance and expertise, which may be considered proxies for elaboration likelihood (Battacherjee and Sanford, 2006; Sussman and Siegel, 2003). These trials contributed to the theoretical specifications or empirical tests of influence processes in IT acceptance (Bhattacherjee and Sanford, 2006), in addition to the integrations of ELM and IT acceptance theory, such as TAM (Sussman and Siegel, 2003).

However, despite their theoretical contributions to IT adoption, these previous studies do not explain adequately the temporal changes occurring in the relationships among persuasion routes, beliefs and intentions, as they generally focused on a static model based on a cross-sectional approach. In many cases, IT acceptance should be considered a process, since it may have some duration. For example, an IT education program can be regarded as a process of persuading program participators to accept IT. As the education program progresses-that is, during the IT acceptance process-the extent of the effects of persuasion routes on beliefs may be changed, as well as beliefs regarding intentions, because the elaboration likelihood may change with the accumulation of knowledge and experience with IT use. Thus, in order to uncover more completely the influence processes in IT acceptance, the previous research framework should be longitudinally expanded to view and assess system use over time, which will lead us to focus on a broader and more comprehensive range of behavior than the cross-sectional approach (Benbasat and Barki, 2007).

A Longitudinal Analysis of the Influence Process in IT Acceptance Considering Intrinsic and Extrinsic Motivations Using the Elaboration Likelihood Model

｢정보시스템연구｣ 제18권 제4호, 2009년 12월

Although the majority of IT acceptance studies conducted thus far have been predicated on a cross-sectional, rather than longitudinal approach (Benbasat and Barki, 2007; Lee et al., 2003), there have been several studies that have suggested that the experience of IT use can alter the role of beliefs in IT adoption frameworks (Szajna, 1996; Taylor and Todd, 1995; Karahanna et al., 1999), and the temporal relationships of beliefs can be theoretically, as well as empirically, identified (Bhattacherjee, 2001; Bhattacherjee and Premkumar, 2004; Kim and Malhotra, 2005). Similar to prior longitudinal studies, a longitudinal analysis of influence processes would also provide us with a framework for a better understanding of the dynamic roles of persuasion routes as well as beliefs during the process of IT acceptance.

While traditional views of IT adoption have generally been based on extrinsic motivations, intrinsic motivation has also recently emerged as a driver of IT acceptance (Davis et al, 1992; Kim and Lee, 2009; Moon and Kim, 2001; Ryu and Choi, 2008; Saade and Bahli, 2005; Shang et al, 2005). For example, the individual’s level of enjoyment while interacting with the technology and the manner in which time is perceived during the session were captured as constructs that determine IT acceptance (Saade and Bahli, 2005). Therefore, external sources’ influence processes on these constructs should be identified and assessed for a more complete understanding. In particular, because the variables associated with intrinsic motivation are not only based on, but also changed by the experience (Csikszentmihalyi, 1990), the functions of persuasion routes on intrinsic motivation may have changed during the process of IT acceptance, such as in an education program, in which trainees now generally enjoy multiple opportunities to experience IT use.

The principal objective of this study was to improve our understanding of the influence processes relevant to IT acceptance via the longitudinal expansion of the relationship between the IT adoption model and ELM, the inclusion of intrinsic motivation in addition to extrinsic motivation, and the modification of the roles of persuasion routes. In service of this objective, we have developed a research model to explain the relationships among two routes of persuasion (central route and peripheral route) in ELM, extrinsic and intrinsic motivation-related constructs, and intentions to re-use. Duration time is also included in our model as a moderation variable. For empirical validation, our model was analyzed and tested longitudinally via a survey of business administration majors who participated in an Excel class.

Ⅱ. Theoretical Background

2.1 Elaboration Likelihood Model

The ELM is a type of dual-mode processing model which seeks to account for message-based persuasion-that is, the process of the individual’s attitude or perception changes resultant from being influenced by the messages (Cacioppo and Petty, 1984; Petty 2001; Petty and Cacioppo, 1981; Wood 2000). In the ELM, the determinants and processes of attitude change depend on people’s motivation and capacity to process issue-relevant information (Wood 2000). We term this motivation and ability to elaborate contents in messages as the “elaboration likelihood”. People with high degrees of elaboration likelihood depend principally on the central route, in which the quality of the argument inherent to the given message is scrutinized and assessed carefully, and then processed thoughtfully. In the central route, the relative merits and relevance of the provided arguments are the principal foci, the primary criterion for judgment is rational processing, and ability and motivation are sufficient to compel the individual to exert the requisite cognitive efforts to elaborate on the arguments contained within a message (Cacioppo and Petty, 1984; Petty, 2001; Petty and Cacioppo, 1981; Wood, 2000). In the context of IT acceptance, reviewing the potential benefits of IT acceptance is a typical processing mode within the central route (Bhattacherjee and Sanford, 2006).

Conversely, because people with low elaboration likelihood do not evidence the requisite ability and motivation to exert such cognitive efforts, rather than considering such arguments in the message, they depend on the peripheral route, and are thus dependent on simple cues regarding the target behavior, thus requiring significantly less cognitive effort (Cacioppo and Petty, 1984; Petty 2001; Petty and Cacioppo, 1981; Wood 2000). Such cues may include endorsements from IT experts, as well as the individual’s like of or affinity toward the endorser (Bhattacherjee and Sanford, 2006).

What is theoretically noted in the core of ELM is that the elaboration likelihood plays a more prominent moderating role than does determination in the relationship between influence routes and perception or attitude changes (Bhattacherjee and Sanford, 2006; Sussman and Siegel, 2003). People with high degrees of elaboration likelihood do not depend wholly on the central route, but their dependence on the central route is predominant over their dependence on the peripheral route. This implies that the higher the elaboration likelihood, the stronger will be the effects of the central route on perceptions or attitude changes, and the less profound will be the effects of the peripheral route. Similarly, in cases of lower elaboration likelihood, the influence of the peripheral route tends to predominate over the influence of the central route.

Only a few previous studies have been conducted thus far regarding the process of IT acceptance from the perspective of ELM, but these have provided critical theoretical implications. For example, Sussman and Siegel (2003) assessed knowledge workers’ adoption of advice via the integration of TAM with ELM. In particular, they assessed the moderating effects of knowledge workers’ expertise and involvement with regard to the relationship between the two routes and usefulness. Their contribution was to show that the two persuasion routes would shape usefulness, although their target is the adoption of knowledge rather than IT. Like Sussman and Siegel, Bhattacherjee and Sanford (2006) also assessed the effects of two persuasion routes on usefulness and attitude with the moderating effects of job relevance and user expertise. Contrary to the results reported by Sussman and Siegel, their target was document management system acceptance by administrators and staff personnel during an education program. They demonstrated that ELM can provide new insights in IT acceptance by suggesting messages from external agents as external variables, and by evaluating the moderating effects of elaboration likelihood on the relationship between these messages and perceptions (Bhattacherjee and Saford, 2006).

2.2. Intrinsic Motivation

Traditionally, the principal focus of studies of IT acceptance has been the extrinsic motivation which drives an individual to perform a behavior in pursuit of specific goals or rewards that differ from the behavior itself (Davis et al, 1992; Deci, 1975; Moon and Kim, 2001; Venkatesh 2000). In particular, perceived usefulness (PU), which is defined as the belief that IT use will result in improved job performance in the TAM, which is a typical extrinsic motivation-related construct (Davis 1989; Davis et al, 1989; Venkatesh and Davis, 2000), has been demonstrated to exert significant effects on IT adoption in many early-stage TAM-related studies (Gefen and Straub, 2000).

However, with the overall generalization of IT in the Internet era, many people have adopted IT not only in order to achieve certain tasks, but also simply for the purpose of using IT itself. Although some studies have considered it to be an antecedent, rather than a driver, of extrinsic motivation (Venkatesh 2000), intrinsic motivation has emerged as another driver of IT acceptance (Chung and Tan, 2004; Moon and Kim, 2001; Saad and Bahli, 20005; Shang et al, 2005). Intrinsic motivation refers to the performance of an activity for the sake of the activity itself (Davis et al, 1992; Deci 1975; Moon and Kim, 2001; Venkatesh, 2000). The majority of variables for intrinsic motivation are predicated on the flow theory proposed by Csikszentmihalyi (1990). Flow is a state in which people are so engrossed and involved in an activity that nothing else seems to matter; the experience itself is so enjoyable that people will seek to perform it even at great cost, for the sheer sake of doing it (Csikszentmihalyi, 1990). As these flow experiences tend to be remembered as the best moments of peoples’ lives, people who experience flow tend to wish to experience it repeatedly, however difficult and hard the achievement of that state proves to be (Csikszentmihalyi,1990; Mannell et al, 1999).

In the case of IT acceptance, while it has been recognized as an important antecedent (ex; Hoffman and Novak, 1996), flow has constituted a theoretical basis for the formulation of intrinsic motivation constructs. Perceived playfulness (PP) is one of the flow-based constructs in IT acceptance. PP is defined in terms of three dimensions: “the extent to which the individual perceives that his (her) attention is focused on the interaction with the WWW; is curious during the interaction; and finds the interaction intrinsically enjoyable or interesting” (Moon and Kim, 2001). Cognitive absorption (CA), which is defined as a state of deep involvement with software, is also a construct predicated on flow with absorption and cognitive engagement, a condition which is characterized by five dimensions: temporal dissociation, focused immersion, heightened enjoyment, control, and curiosity (Agarwal and Karahanna, 2000).

Flow-based constructs such as PP and CA have been proposed previously in an effort to explain the end user’s experience on web services such as general web use (Agarwal and Karahanna, 2000; Moon and Kim, 2001), online gaming (Hsu and Lu, 2004), online shopping (Shang et al, 2005), and online learning (Saade and Bahli, 2005). However, according to flow theory, people can become deeply involved not only in leisure but also in work when one’s skills are adequate to cope with the challenges at hand (Csikszentmihalyi, 1990). Similarly, many programmers may have an experience in deep involvement in programming to the exclusion of the external world. Therefore, this study defines PP as the extent to which people are involved in working with a given IT development tool, such as Excel.

Ⅲ. Research Model

In order to account for the IT acceptance process in an education program, this study suggests a research model like the one shown in Figure 1. Similar to the previous study (Bhattacherjee and Sanford 2006), in order to apply ELM to the IT acceptance context, adopting the tripartite model, we expanded the concept of attitude as a broader construct consisting of three components: cognition, which is related with rational judgment; affect, which refers to emotional responses or beliefs; and behavior, which corresponds to intention (Breckler, 1984; Petty, 2001; Wood, 2000). In our model, the dependent variables was reuse intention as behavior and the mediate variables were: perceived usefulness (PU) as cognition; perceived playfulness (PP) as affect, while the independent variables were: argument quality (AQ) for the central route; and source credibility (SC) for the peripheral route. Moreover, we adopted time duration as a moderating variable. The relationships of variables are depicted in solid lines and the moderation effect of IT education time in dotted lines, which relate to the longitudinal analysis of the relationship between variables.

Since the TAM was first proposed by Davis (1989), many TAM-related studies have demonstrated that PU influences the intention to use IT in diverse IT types and users (Benbasat and Barki, 2007; Gefen and Straub, 2000; Lee et al, 2003; Legris et al, 2003). Whereas previous studies have delineated the relationship between intrinsic motivation and intention to use IT (Moon and Kim, 2001; Heijeden, 2004), under our new definition of PP, playfulness can also be experienced when working with IT development tools. The experience of playfulness in working with IT development tools is a mode of perceiving an optimal experience that might lead to the intention of reuse.

Figure-1 Research Model

Hypothesis 1(H1): Perceived usefulness in an IT development tool positively influences the intention to use IT.

Hypothesis 2 (H2): Perceived playfulness in an IT development tool positively influences the intention to use IT.

Because it requires a person to think critically regarding issue-related arguments, the central route is typically operationalized as argument quality (AQ), which refers to the persuasive strength of arguments in a message (Bhattacherjee and Sanford, 2006; Sussman and Siegel, 2003). In the case of IT education, argument quality is a subjective evaluation of issues and contents provided by instructions in a class.

Although ELM studies have generally focused on attitude as a dependent variable (Petty, 2001; Wood, 2000), previous studies of the IT acceptance domain have demonstrated that AQ influences PU by reinforcing or improving potential users’ extant beliefs regarding system acceptance, since message arguments are directed at users’ rational judgments (Bhattacherjee and Sanford, 2006). Like PU, PP may also be influenced by AQ, although it is an emotional belief: In order to experience deep involvement in programming or development, the prerequisite skills and knowledge to handle an IT development tool must be possessed, and can be enhanced by direct instruction in how to use such tools.

Hypothesis 3 (H3): Perceived argument quality in instruction for IT development tool use positively influences perceived usefulness in working with development tools.

Hypothesis 4 (H4): Perceived argument quality in instruction for IT development tool use positively influences perceived playfulness in working with development tools.

There are many potential peripheral cues in ELM: the number of messages, the number of message sources, the source likeability, and the source creditability (SC). Among them, we have adopted SC, which is defined as the extent to which an information source is perceived to be believable, competent, and trustworthy by the recipient of the information (Bhattacherjee and Sanford, 2006), referring to a message recipient’s perception of the credibility of a message source, reflecting nothing regarding the message itself (Sussman and Siegel, 2003). For example, in the case of IT education, the students’ perception of an instructor’s ability and expertise would be a typical SC.

Whereas peripheral cues are likely to appeal to human affect or emotional belief such as PP, they may occasionally directly influence rational judgment such as PU. For example, if the recommendation of a system is offered by a well-recognized and well-trusted IT expert, usefulness is perceived to be relatively high (Bhattacherjee and Sanford, 2006).

Hypothesis 5 (H5): Perceived source credibility of instruction for IT development tool use positively influences perceived usefulness.

Hypothesis 6 (H6): Perceived source credibility of instruction for IT development tool use positively influences perceived playfulness.

The relationship between SC and AQ has not been the focus of the majority of ELM studies, as most issues in ELM have focused on comparisons between two persuasion routes in persuasion processes (Petty and Wegener, 1999). However, many studies in education have demonstrated that students’ evaluations of teachers determine the perceived quality of instructions (Daivdovitch and Seon, 2006). In ELM, whereas the elaboration likelihood determines the main persuasion route, the directions of the two persuasion routes may be independent of the elaboration likelihood (Petty et al, 1995). Therefore, similar to the relationship with usefulness, source credibility is likely to exert direct influence on argument quality. For example, comments or recommendations provided by more trusted instructors can be considered more relevant in the scrutiny and assessment of issues than would be the case with less trusted instructors. Therefore, source credibility may significantly influence and shape argument quality.

Hypothesis 7 (H7): Perceived source credibility of instruction for IT development tool use positively influences argument quality.

While intrinsically motivated behavior is self-determined, most extrinsically motivated behavior is prompted by external sources (Deci, 1975; Vallerand, 1997). A person who has optimal experiences seeks the opportunity to engage in more challenging and skillful activities by self-determination (Csikszentmihalyi, 1990; Deci, 1975). To a person who is externally motivated, whether or not an activity is engaged in is dependent on rational judgment regarding the activity via thoughtful scrutiny and cognition (Vallerand, 1997). In the context of IT acceptance, a person who has the experience of deep involvement in working with an IT development tool consistently seeks the opportunity to engage in more playful experiences. However, he (or she) does not seek the experience of the perception of usefulness, which may rather require cognitive efforts than provide enjoyment as a playful activity. Thus, as time progresses, the extent of PU’s influence on intention would be reduced, whereas PP’s influence would be increased.

Hypothesis 8 (H8): The extent of the effect of perceived usefulness on intention of working with IT development tools becomes higher as an education program progresses.

Hypothesis 9 (H9): The extent of the effect of perceived playfulness on intention of working with IT development tools becomes higher as an education program progresses.

Since an intrinsically motivated person selects an activity via self-determination, he (or she) may wish to acquire the required skills and knowledge to engage in playful experience by himself (herself). Initially, the experience of playfulness may prove to be dependent on external sources, as the required skills and knowledge may not be sufficient. However, as the accumulation of experience, ,necessary for playful experiences learning on the basis of self-determination, rather than external sources such as guidance by instruction, which would reduce the dependence of playful experience on instructions. In contrast with playfulness, as an education program progresses, the effect of instructions on usefulness should be influenced more profoundly, since pre-perceived usefulness can shape extrinsic motivation for the use of IT, which may also improve the elaboration likelihood.

Hypothesis 10 (H10): The extent of perceived argument quality’s effect on perceived usefulness in working with IT development tools become lower as an education program progresses.

Hypothesis 11 (H11): The extent of perceived argument quality’s effect on perceived playfulness in working with IT development tools become lower as an education program progresses.

Ⅳ. Research Methodology

4.1 Measurement

Items used to measure the constructs are shown in Appendix. The scale of AQ and SC was adopted from previously conducted ELM-related IT acceptance studies (Bhattacherjee and Sanford, 2006; Sussman and Siegel, 2003), the scale of PP is adopted from the studies of Moon and Kim (2001) and Agarwal and Karahanna (2000), and the PU scale is derived from the studies of Davis (1989) and Davis et al. (1989). The items were validated in a pilot study and some wording was altered for adaptation to our contexts. All items were measured on a five-point Likert-type scale with anchors from “Strongly disagree” to “Strongly agree”.

4.2 Data Collection and Analysis Method

In order to assess our hypotheses, a sample was selected from a population of undergraduate students at Daegu University, Korea. They were attending a course called “Business and Computers”, a primary course on the proper use of Excel in the business environment. All of the study group subjects were freshmen in the business administration department, and none had any previous experience with similar IT applications. Prior to the midterm exam, the students were introduced to and trained on certain features of Excel, including basic calculations on spreadsheets, some primary concepts such as relative reference, and certain other basic functions. Following the midterm, a variety of Excel applications were provided and practiced with advanced features, including some macros. Whereas the early stages of that class focused on some basic technical issues, application issues were emphasized in later stages.

For the longitudinal analysis of hypotheses 8 to 11, the surveys from the sample were conducted utilizing the same questionnaires just prior to the midterm and final exams. The number of responders in the first survey was 141 (male : 112, female: 29), and, in the second survey, 144 (male: 110, female: 34) .

The partial least squares (PLS) method was adopted for data analysis. PLS is one of the principal analysis methods utilized in structural equation modeling, and has the ability to model latent constructs under conditions of non-normality and with small sample sizes (Chin 2000). In particular, the PLS approach has been adopted in IS studies in which multi-group analyses were conducted with relatively small sample sizes (ex: Bhattacherjee and Premkumar, 2006; Gefen et al, 2003; Karahanna et al, 1999; Keil et al, 2000; Lee, 2007).Therefore, the PLS approach has been recognized as appropriate for our study, which required comparative analyses of paths with relatively small sample sizes. All analyses for the measurement model and structural model were conducted on the 1st and 2nd survey samples.

Ⅴ. Data Analysis

5.1 Measurement Model

The measurement model was analyzed by demonstrating convergent and discriminant validity. Convergent validity is the level of the relationship between each measure and its assumed theoretical construct, whereas discriminant validity is indicated when each measurement item is weakly correlated with all other constructs, except for the one to which it is theoretically associated (Gefen and Straub, 2005).

We demonstrated convergent validity by assessing the loadings of all measurements, composite reliability (CR) and average variance extracted (AVE) of each construct in the 1st and 2nd surveys, as is shown in Tables 1 and 2. Whereas they evidence significant path loading at a level of 0.01, all of our measures yielded composite reliability at 0.888 or above and average variance extracted at 0.671 or above, which fulfill the recommendation levels (higher than 0.5) (Fornell and Larcker, 1981).

Table-1 Psychometric Table of Measurements (1st Survey)

Construct		Item	Loading	Standard Error	t-Value
Argument Quality	AVE=0.776 CR=0.933	AQ1	0.860	0.039	22.196
		AQ2	0.913	0.020	46.395
		AQ3	0.891	0.031	28.528
		AQ4	0.859	0.037	23.469
Reuse Intention	AVE=0.726 CR=0.888	INT1	0.898	0.026	34.798
		INT2	0.820	0.067	12.315
		INT3	0.837	0.054	15.531
Perceived Playfulness	AVE=0.664 CR=0.922	PP1	0.802	0.034	23.879
		PP2	0.775	0.048	16.204
		PP3	0.843	0.040	21.275
		PP4	0.826	0.042	19.750
		PP5	0.806	0.041	19.527
		PP6	0.835	0.040	20.877
Perceived Usefulness	AVE=0.863 CR=0.962	PU1	0.926	0.020	47.559
		PU2	0.948	0.011	85.502
		PU3	0.926	0.023	40.555
		PU4	0.915	0.025	36.567
Source Credibility	AVE=0.837 CR=0.939	SC1	0.877	0.037	23.914
		SC2	0.944	0.016	57.602
		SC3	0.924	0.025	37.130

Construct		Item	Loading	Standard Error	t‐Value
Argument Quality	AVE=0.776 CR=0.933	AQ1	0.904	0.025	36.772
		AQ2	0.880	0.033	26.631
		AQ3	0.924	0.021	43.242
		AQ4	0.811	0.049	16.568
Reuse Intention	AVE=0.814 CR=0.929	INT1	0.924	0.017	54.093
		INT2	0.900	0.030	29.815
		INT3	0.881	0.036	24.567
Perceived Playfulness	AVE=0.671 CR=0.925	PP1	0.799	0.046	17.379
		PP2	0.836	0.028	30.306
		PP3	0.831	0.036	22.892
		PP4	0.796	0.087	9.170
		PP5	0.847	0.051	16.692
		PP6	0.805	0.080	10.101
Perceived Usefulness	AVE=0.900 CR=0.973	PU1	0.955	0.017	56.768
		PU2	0.945	0.021	45.930
		PU3	0.963	0.012	83.265
		PU4	0.932	0.022	42.314
Source Credibility	AVE=0.834 CR=0.938	SC1	0.847	0.035	24.348
		SC2	0.960	0.008	118.425
		SC3	0.929	0.018	51.939

Table-2 Psychometric Table of Measurements (2st Survey)

Discriminant validity was verified in two ways. Whereas the square root of AVE for each construct was higher than the correlations between it and all other constructs as shown in Tables 3 and 4 (Fornell and Larcker, 1981), the measurement items loaded highly on their theoretically assigned factor and not highly on other factors, as is shown in Tables 5 and 6 (Gefen and Straub, 2005).

Table-3 Correlation between Constructs with Square Roots of AVE (1st Survey)

	AQ	INT	PP	PU	SC
Argument Quality (AQ)	0.881
Reuse Intention (INT)	0.582	0.852
Perceived Playfulness (PP)	0.539	0.516	0.815
Perceived Usefulness (PU)	0.587	0.606	0.461	0.929
Source Credibility (SC)	0.562	0.338	0.314	0.215	0.915
Diagonal Elements: Square Roots of the Average Variance Extracted

Table-4 Correlation between Constructs with Square Roots of AVE (2nd Survey)

	AQ	INT	PP	PU	SC
Argument Quality (AQ)	0.881
Reuse Intention (INT)	0.563	0.902
Perceived Playfulness (PP)	0.443	0.530	0.819
Perceived Usefulness (PU)	0.658	0.507	0.398	0.949
Source Credibility (SC)	0.628	0.380	0.356	0.334	0.913
Diagonal Elements: Square Roots of the Average Variance Extracted

Table-5 Loading and Cross-Loadings for Measurements (1st Survey)

	AQ	INT	PP	PU	SC
AQ1	0.860	0.497	0.458	0.465	0.497
AQ2	0.913	0.542	0.479	0.547	0.567
AQ3	0.891	0.546	0.494	0.523	0.451
AQ4	0.859	0.462	0.468	0.530	0.462
IN1	0.541	0.898	0.483	0.599	0.337
IN2	0.376	0.820	0.368	0.381	0.234
IN3	0.541	0.837	0.453	0.535	0.277
PP1	0.462	0.461	0.802	0.467	0.211
PP2	0.451	0.393	0.775	0.327	0.297
PP3	0.402	0.384	0.843	0.337	0.287
PP4	0.469	0.449	0.826	0.438	0.252
PP5	0.443	0.438	0.806	0.386	0.268
PP6	0.393	0.385	0.835	0.269	0.223
PU1	0.573	0.587	0.457	0.926	0.212
PU2	0.540	0.575	0.454	0.948	0.190
PU3	0.535	0.516	0.396	0.926	0.221
PU4	0.530	0.571	0.401	0.915	0.176
SC1	0.437	0.279	0.322	0.129	0.877
SC2	0.503	0.282	0.283	0.174	0.944
SC3	0.588	0.358	0.265	0.271	0.924

Table-6 Loading and Cross-Loadings for Measurements (2nd Survey)

	AQ	INT	PP	PU	SC
AQ1	0.904	0.459	0.409	0.610	0.556
AQ2	0.880	0.485	0.369	0.664	0.489
AQ3	0.924	0.506	0.377	0.569	0.561
AQ4	0.811	0.535	0.406	0.471	0.610
IN1	0.533	0.924	0.478	0.475	0.350
IN2	0.529	0.900	0.424	0.443	0.366
IN3	0.464	0.881	0.526	0.452	0.316
PP1	0.453	0.449	0.799	0.366	0.289
PP2	0.381	0.441	0.836	0.313	0.349
PP3	0.319	0.433	0.831	0.269	0.245
PP4	0.318	0.421	0.796	0.336	0.245
PP5	0.351	0.462	0.847	0.317	0.322
PP6	0.340	0.394	0.805	0.353	0.291
PU1	0.640	0.506	0.384	0.955	0.329
PU2	0.592	0.418	0.355	0.945	0.244
PU3	0.653	0.476	0.365	0.963	0.331
PU4	0.610	0.520	0.406	0.932	0.358
SC1	0.509	0.280	0.319	0.206	0.847
SC2	0.596	0.364	0.336	0.315	0.960
SC3	0.610	0.389	0.323	0.377	0.929

5.2 Structural Model

Figure-2 PLS Result of Structural Model (1st Survey)

The explanatory power of the structural models can be evaluated by assessing the R2 value in the final dependent construct. In this study, the final dependent construct (reuse intention) had an R2 value of 0.439 and 0.385 in the 1st and 2nd survey, respectively (See Figure 2 and 3).

After the estimation of path coefficients using the entire sample, PLS employed a bootstrapping technique to obtain the corresponding t-value. Some hypotheses (H1 to H7) are assessed in terms of the sign (positive and negative) and the statistical significance of the t-value for its corresponding path, whereas other hypotheses (H8 to H11) associated with longitudinal analysis were assessed via multi-group analysis (Chin 2000). In the case of H1 to H7, as is shown in Figures 2 and 3, the majority of hypotheses were supported in the 1st and 2nd surveys, but the source credibility (SC)-related hypotheses, H5 (SC->PU) and H6 (SC->PP), were not supported in either of the surveys.

Figure‐3 PLS Result of Structural Model (2nd Survey)

Before the test of hypotheses regarding longitudinal analysis (H9 to H11), the manipulation of the differences in elaboration likelihood in both surveys was assessed by perceived ease of use (PEOU). PEOU refers to the degree to which a person believes that using a particular system would be free of effort (Davis, 1989), and the scale for PEOU is as shown in Appendix. As is shown in Table 7, PEOUs in the 1st survey (mean = 2.523, deviation= 0.388) and the 2nd survey (mean=2.719, deviation=0.419) differed significantly (t-value of their difference; 2.605). This implies that elaboration likelihood at the 2nd survey was increased as compared to the 1st survey.

Table-7 t-Test of difference of perceived ease of use (PEOU) in two surveys

	1st_PEOU	2nd_PEOU
Average	2.523	2.719
deviation	0.388	0.419
number of Observes	141	144
degree of Freedom	283
t-Statistics	2.605
p-value	0.0048

H9 to H11 were tested via statistical comparison of paths in both surveys (Chin 2000; Keil et al, 2000). As summarized in Table 8, H9 to H11 were supported by the statistical results. That is, the effect of usefulness on intention (H8) in the 1st survey was demonstrated to be significantly weaker than in the 2nd survey (t-value = -10.164), whereas the effect of playfulness on intention (H9) was stronger (t-value = 8.546). Similarly, the effect of change in argument quality on usefulness (H10) in the 1st survey were stronger than the 2nd survey (t-value = 4.782), whereas the effects of argument quality on playfulness (H11) were weaker (t-value = -11.689).

Table-8 Summary of Longitudinal Analyses

Hypothesis	Path		1st Survey	2nd Survey	*t-Value of difference
H8	PU -> INT	PC	0.352	0.352	-9.405**
		SE	0.124	0.119
H9	PP -> INT	PC	0.301	0.390	8.059**
		SE	0.084	0.102
H10	AQ -> PU	PC	0.682	0.741	4.783**
		SE	0.106	0.104
H11	AQ -> PP	PC	0.530	0.363	-11.805**
		SE	0.105	0.132
*t-value of difference = PC(i):(the ith survey) path coefficient SE(i): (the ith survey) Standard Error n(i): (the ith survey) Sample Size **: Significance level < 0.01

5.3 Discussions of Data Analysis

Source credibility-related hypotheses (H5 and H6) were not supported. In particular, the failure of hypothesis 5 (the relationship with usefulness) to be supported is not consistent with the results of the previous study (Bhattacherjee and Sanford, 2006). Although this may be attributable to certain methodological problems such as sample size or stratification issues, this contrary result may be explained most appropriately by assessing the differences in the subjects’ controllability with regard to IT use. Whereas the previous study collected the data at the end of the 3-day training program (Bhattacherjee and Sanford, 2006), the 1st survey of this study was conducted at the midterm exam and the 2nd survey at the final exam, two months and four months after opening the class, respectively. Therefore, the students in our study can be supposed to be more experienced and practiced in using Excel and to have a higher controllability of handling it than the subjects in the previous study, which is indicative of a substantially higher elaboration likelihood. According to the ELM, as the argument scrutiny is increased, peripheral cues become relatively less important determinants of persuasion, as there may exist a tradeoff between the impact of central and peripheral mechanisms on judgments along the elaboration likelihood continuum (Petty and Wegener, 1999). In our experimental setting, the majority of students were believed to have the ability to handle Excel sufficiently that they could ignore the effects of source credibility on usefulness and playfulness. However, although we noted no direct effects, we clearly noted an indirect effect of source credibility on two beliefs through argument quality.

Ⅵ. Implications and Conclusions

The principal objective of this study was to improve our understanding of the influence process of IT acceptance, not only in the dynamic features of persuasion routes and beliefs with their effects on adoption, but also with regard to the roles of the influence processes of intrinsic motivation. In service of this objective, we proposed a research model for the IT acceptance process focused on playfulness as well as usefulness, including two persuasion paths in ELM. In particular, to analyze the change in the role of usefulness and playfulness during IT education, the suggested research model was assessed longitudinally, just after the midterm and final exams. As a result, the majority of the hypotheses were supported.

6.1 Discussions of Findings and Implications

The implications of our study are summarized as: the inclusion of intrinsic motivation- playfulness-in influence processes as well as usefulness and the longitudinal expansion of the previous research framework, which not only differentiates this study from previous studies (Bhattacherjee and Sanford, 2006; Sussaman and Siegel, 2003) but also serves to enlarge our views of IT acceptance studies. More specifically, the findings and implications of this study are as follows.

We demonstrated that the extent of AQ’s influence on shaping perceptions would change during acceptance. That is, as time passes, which leads to improvements in the elaboration likelihood, the effects of AQ on PU are strengthened (H10), whereas the effects of AQ on PP are weakened (H11). Hypothesis 10 implies that PU can be consistently enhanced by cognitive efforts, as the effect of the central route on rational judgment is predicated on the relatively deliberate and thoughtful considerations of relevant arguments (Petty and Cacioppo, 1986). Contrary to hypothesis 10, hypothesis 11 implies that PP is shaped principally by experiences rather than by cognitive efforts (Agarwal and Karahanna, 1999; Csikszentmihalyi, 1990; Moon and Kim, 2001), whereas it may be dependent on cognitive efforts when IT is unfamiliar, for example, during the early stages of the educational program.

Our findings also involve temporal changes of the relationship between the two beliefs and intentions. As time passes, that is, the elaboration likelihood is improved, whereas the effect of PU on intention is reduced (H8), the effect of PP is increased (H9), which implies that IT adoption becomes dependent on intrinsic motivation rather than extrinsic motivation. Hypotheses 8 and 9 can enhance our understanding of traditional views of IT adoption or continuous use. According to traditional IT acceptance theories, the experienced users’ considerations for IT adoption or continuous use have been demonstrated to be more rational than the novices’ (Agarwal and Karahanna, 1999; Szajna, 1996). However, our results demonstrated that emotional beliefs might not only be included in the experienced users’ considerations, but might also dominate other considerations. Moreover, whereas roles for intrinsic motivation in IT adoption have been studied largely in hedonic systems (ex: Heijden, 2004), we demonstrated that intrinsic motivation may be a determinant factor and its influence is increased in a typical utilitarian system.

Our findings regarding the dynamic features of AQ, PP, and PU (H8, H9, H10, H11) also indicate that the function of AQ in IT adoption is reduced as time passes. The effect of AQ on PP is reduced (H11), whereas that of PP on use intention is increased (H9). Contrarily, the effect of PU on use intention is reduced (H8), whereas the effect of AQ on PU is increased (H10). Thus, the indirect effect of AQ on use intention through PP and PU would be reduced, which means that experiences of use may become more important in IT adoption than messages for acceptance persuasion as time progresses.

In addition to its theoretical implications, our longitudinal approach yielded some methodological implications. The adoption of time duration as a moderating variable can prevent the common method biases attributable to the measurement method rather than to the constructs for the measures it represents (Podsakoff et al, 2003). If moderation variables were measured on the basis of self-reports, their measurement might be based not only on respondents’ subjective evaluations but may also be influenced by other measures, which may result in common method biases (Podsakof et al, 2003). However, our moderating variable-time duration-is independent of both respondents’ subjective evaluation and other measures. Moreover, we confirmed the variance of our moderation variable by differences in PEOU, as is shown in Table 8.

The indirect effect of SC on PU and PP through AQ should also be noted among the results of our study. Although hypothesis 5 (SC->PU) and hypothesis 6 (SC->PP) were not supported, we detected a strong relationship between AQ and SC in the IT adoption framework. Our empirical test demonstrated that the impacts of SC on PP in both surveys had very high t-values (1st survey; 7.086, 2nd survey; 8.818). This implies that AQ is very strongly dependent on SC, and that this persists for some duration. Therefore, despite the fact that the notion of direct relationships is not supported, an indirect relationship exists between SC and the two beliefs, PU and PP, mediated by AQ.

In addition to its theoretical implications, our results provide some practical implications. What should be practically noted among our results is that the driver of IT adoption was shifted from extrinsic motivation to intrinsic motivation as time progresses. From the viewpoint of IT education, whereas, at the early stage, programs conducted by instructors might prove persuasive, in the later stages programs for self-directed learning would enhance IT acceptance effectiveness. Therefore, whereas the role of an instructor should shift from teaching to guidance, the trainees’ role should be from a passive recipient of messages to an active processor of messages (Rovai, 2004). For example, after providing some basic skills or related theories, enjoyable cases for practice can enhance the formation of positive beliefs on IT use. The importance of SC should also be noticeable in practice. Although the notion of direct effects on beliefs was not supported, our results demonstrated that the indirect effects of SC on beliefs through AQ would be consistently in effect. Thus, the informing instructors’ profile, which can be easily perceived by the trainees, would be anticipated to improve the persuasive strength of instruction, which would consequently positively affect usefulness and playfulness.

6.2 Limitations of Research

First, our sample was limited to the users of a specific IT development tool-namely, Excel. Although spreadsheets can be utilized by a broader range of users owing to its ease of use and flexibility (Lawson et al, 2009), there may be some questions remaining regarding the representativeness of IT development tools. For example, the applications of our model to potential Java or C++ users might provide results that differ significantly from those observed with Excel users.

Second, our model did not account for attitude. Although our model did include attitude as a broader concept based on the tripartite model (Breckler, 1984; Petty 2001; Wood, 2000), it may be considered a limitation of our study that it did not explicitly include attitude as a construct within our framework. Moreover, previous studies have included attitude in their research frameworks, where attitude was demonstrated to be affected by SC (Bhattacherjee and Sanford, 2006; Sussman and Siegel, 2003).

Third, some common method biases may have been relevant to our experimental procedures. Despite the fact that we adopted duration time as a moderating variable, there may be some potential for common method biases in our study procedure. Specifically, in both surveys, all items were measured simultaneously, and this may have led the respondents to give biased responses. For example, the response to PU might be influenced by reuse intentions.

6.3 Further Studies

First, our model can be expanded longitudinally, and thus involve more than two surveys. Our model was based on two surveys, but three or more surveys can provide a more comprehensive and complete understanding of the relevant issues. Previous studies conducted via three surveys have been demonstrated to provide insightful implications (ex: Bhattacherjee and Premkumar, 2004). In particular, monitoring at the pre-use or initial stages may enrich our model, which involved monitoring at the mid- and later stages. The expansion of the model by more than two surveys should be accompanied by a modification of the research model to fit the number of surveys conducted.

Second, simultaneous applications of our model to both hedonic and utilitarian systems with comparative analysis would provide interesting implications. Analyses of differences by IT type and modifications of our model considering such differences may prove to be interesting issues, from both theoretical and practical perspectives.

Third, analyses of changes in beliefs might also uncover interesting research issues. Whereas crucial implications for changes in beliefs regarding the IT acceptance context have been provided in previous studies (Bhattacherjee 2000; Bhattacherjee and Premkumar 2004; Kim and Malhotra, 2005), explorations of changing AQ and SC duration of IT acceptance would help to shed light on the other side of IT adoption studies. Fortunately, these studies can be guided by the theories adopted in previous studies. For example, the exploration of mediators in changing persuasion routes can be analyzed from the perspective of expectation-confirmation theory, as in previous studies (Bhattacherjee 2000; Bhattacherjee and Premkumar 2004).

In conclusion, this study improved our understanding of IT acceptance, which may be considered a process, through the longitudinal analysis of beliefs and their relationships on the basis of well known theories such as ELM and motivation theories as well as TAM. Thus, our approach is believed to provide not only theoretically interesting findings but also broader and comprehensive views in IT adoption as a process. We hope that this study will provide a foundation for inspiring future researchers to investigate exciting topics for more completed understanding IT acceptance.

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이웅규(Woong-Kyu Lee)

현재 대구대학교 경영학과 교수로 재직 중이다. 연세대학교 경영학과를 졸업하고 KAIST에서 경영과학 석사와 경영정보공학 박사 학위를 받았고 KT에서 선임연구원으로 재직하였다. 정보기술 사용의 전유, 정보기술 수용 설득경로, 내재적 동기에 의한 정보기술 사용 등과 같이 사회심리학적 이론을 배경으로 하는 온라인 사용자 행태에 관심을 가지고 있다.

Appendix: Scales and Items

Argument Quality
AQ1	Until now the contents provided in class was informative.
AQ2	Until now the contents provided in class was helpful.
AQ3	Until now the contents provided in class was valuable.
AQ4	Until now the contents provided in class was persuasive.
Source Credibility
SC1	The instructor was knowledgeable on Excel
SC2	The instructor was trustworthy.
SC3	The instructor was credible.
SC4	The instructor was appeared to be an expert on Excel.
Perceived Usefulness
PU1	Using Excel will make me do what I want to do efficiently.
PU2	Using Excel will make me do what I want to do more effectively.
PU3	Using Excel will make me do what I want to do better.
PU4	Using Excel will be useful to what I want to do.
Perceived Playfulness
PP1	Time appears to go by very quickly when I am working with Excel
PP2	While working with Excel I am absorbed in what I am doing
PP3	Sometimes I lose track of time when I m working with Excel.
PP4	Working with Excel provides me with a lot of enjoyment
PP5	While working with Excel I often forget the other works I must do
PP6	I enjoy working with Excel.
Use Intention
INT1	I plan to use Excel in the future
INT2	I intend to continue using Excel in the future
INT3	I expect my use of Excel to continue in the future
Perceived Ease of Use
EU1	I am awkward in using Excel (Reverse)
EU2	It is not easy to learn Excel (Reverse)
EU3	It seems to be not easy to do what I want to do (Reverse)
EU4	It seems to be effortful to be familiar to use Excel (Reverse)
EU5	Excel is easy to use.

요약

내재적 동기와 외재적 동기를 동시에 고려한 정보기술수용의 설득과정에 대한 정교화가능성 기반 종단 분석

정교화가능성모형과 기술수용모형에 의해 정보기술 수용의 설득과정을 시도한 연구들이 이론적으로 미친 영향은 매우 크다. 그러나 이들 연구의 대부분은 횡단면적 접근에 기반한 정적 모형을 사용했기 때문에 시간 흐름에 따른 변수 간의 관계 변화를 적절히 설명하지 못하고 있다. 가령, 교육프로그램을 통한 정보기술 수용은 일정기간의 시간을 요하는데 설득경로가 유용성의 지각에 미치는 영향력은 달라질 수 있다. 따라서 정보기술 수용과정을 충분히 규명하기 위해서는 기존의 연구모형은 종단적으로 확장되어 시간 흐름에 따른 시스템 사용을 평가해야 한다. 한편 정보기술수용 연구에서 내재적 동기의 중요성이 강조되고 있음에도 불구하고 수용 설득과정에서 내재적 동기에 대한 고려는 별로 없었고 대부분의 연구는 유용성과 같은 외재적 동기를 중심으로 이루어졌다. 본 연구의 목적은 정보기술수용 설득과정의 이해를 넓히기 기존 연구에서 제시된 연구모형에 내재적 동기에 관련된 변수를 포함하고 전체적인 모형을 종단적으로 확장했고, 실증적 검증을 위해 정규 대학과정 과목의 학생들을 대상으로 두 번에 걸친 표본 조사를 하였다.

Key words: 정보기술수용과정, 정교화가능성모형, 내재적 동기, 종단적 분석.

* 이 논문은 2009년 11월 24일 접수하여 1차 수정을 거쳐 2009년 12월 15일 게재 확정되었습니다.