Application of the Technology Acceptance Model to a Knowledge Management System

Transcription

1 Application of the Technology Acceptance Model to a Knowledge Management System Associate Professor William Money, Ph. D Arch Turner, Doctoral Candidate The George Washington University wmoney@gwu.edu/turnera@onr.navy.mil Abstract This research investigates the applicability of Davis Technology Acceptance Model to user acceptance of a knowledge management information system. It addresses two important questions: Does the Technology Acceptance Model explain user acceptance and usage of an information system implemented to support knowledge management objectives? Can previous Technology Acceptance Model user acceptance research serve as a basis for investigation of user acceptance of knowledge management information technology systems? This study provides preliminary evidence that previous information technology acceptance research based on the Technology Acceptance Model, may serve as a foundation for research of knowledge management system user acceptance. Relationships among primary TAM constructs are in substantive agreement with those characteristic of previous TAM research. Significant positive relationships between perceived usefulness, ease of use, and system usage were consistent with previous TAM research. The observed mediating role of perceived usefulness in the relationship between ease of use and usage was also in consonance with earlier findings. The findings are significant because they suggest that the considerable body of previous TAM related information technology research may be usefully applied to the knowledge management domain, and promote further investigation of factors affecting the user acceptance and usage of knowledge management information systems. I. Introduction Although business investment in information technology has declined in recent years, firms around the world still spend more than $2 trillion dollars a year on IT (Garr, 2003). It is also estimated that IT investment comprises approximately fifty percent of U.S. business capital investment, making it the top capital investment area for American businesses (Garr, 2003). With continuing enormous business resource investments, understanding and creating conditions under which information technology will be accepted and used in the human organization remains a high priority within the information technology research community (Venkatesh and Davis, 2000). Understanding why individuals accept or reject systems has proven to be one of the most challenging issues in information systems research (Doll, et al., 1998). User acceptance of information technology a phenomenon which is not yet well understood and usage are unquestionably crucial factors in the ultimate determination of information system success, since information systems that are not used are of little value (Mathieson et al., 2001). A significant body of research into - and accumulated knowledge of - the factors affecting information technology acceptance has as its foundation the Technology Acceptance Model (TAM), a model originally conceived by Fred Davis in TAM is an intentions based model derived from the Theory of Reasoned Action (TRA), but tailored to meet the broad needs of information technology research. Since its introduction TAM has enjoyed increasingly wide acceptance and has proven to be a reasonably accurate predictor of both users intentions to use an information technology and of their system usage. Evidence of the research community s growing acceptance of TAM is reflected in the fact that the Institute for Scientific Information Social Science Citation Index recently listed 335 journal citations since 1999 of the initial TAM research paper published by Davis et al. (1989). More than ten years after its original publication, TAM continues to receive heavy in fact, significantly heavier than when compared to earlier citation data by Venkatesh and Davis (2000) attention from information technology researchers. Another topic of rapidly expanding interest within the information technology research community is that of knowledge management the /04 $17.00 (C) 2004 IEEE 1

2 set of systematic and disciplined actions an organization can take to obtain the greatest value from the knowledge available to it (Marwick, 2001). Knowledge management is rapidly becoming an integral business function for many organizations as they realize that competitiveness hinges on effective management of intellectual resources (Davenport and Grover, 2001). Reflecting this widespread interest, recent literature is replete with research addressing a wide range of important issues related to the question of how organizations can best capitalize on their knowledge resources. Increasingly, knowledge is recognized as an organization s most valuable resource and the best foundation of sustained competitive advantage. A cursory sampling of key knowledge management issues reported recently include knowledge management and new organizational structures (Malhotra, 2000), assessments of knowledge management organizational capability prerequisites (Gold, Segar, Malhotra, 2001), knowledge management strategies and taxonomies (Earl, 2001; Zack, 1999), the relative importance of various knowledge types (Lam, 2000), general discussions of knowledge management benefits and challenges (Alavi and Leidner, 1999), the mapping of organizational knowledge (Vaill, 1999), the integration of information technology to enhance organizational knowledge management (Bourdreau and Couillard, 1999), and the development of a knowledge management research agenda (Grover and Davenport, 2001). Grant (1996) and Spender (1996) elevate the knowledge management agenda further through their discussions of a knowledge-based theory of the firm. A missing element in this ongoing discourse concerns individual acceptance and usage of information technology implemented to support knowledge management initiatives. To date, there is a surprising paucity of empirical research into the factors affecting individual acceptance and use of information technology implemented in the form of a knowledge management system. II. Knowledge Management Systems Knowledge management is widely appreciated to encompass a broad range of complex organizational, social, and behavioral factors. However, modern information technology is a critical enabler that has been the catalyst for increased interest in the knowledge management concept, and has been the center of gravity for most enterprise knowledge management initiatives (Grover and Davenport, 2001) (Alavi and Leidner, 1999). Information-related technologies that support knowledge management include collaboration and community of interest/practice support technologies, structured and unstructured data indexing, categorization, and taxonomy producing tools, common databases, data warehousing technology, search and retrieval, and document management tools, just to mention a few. As with any other information technology implementation, the success of these systems inevitably begins with the individual; individual acceptance and usage are critical. This research attempts to begin filling a critical void by linking two high interest information technology research topics: user acceptance and knowledge management. Davis TAM is used as a framework to investigate the implementation of a knowledge management system within an organizational unit of a large internationally known private consulting firm. The knowledge management system studied is a webbased document repository and management tool intended primarily to support three organizational objectives; (1) improvement of internal software development processes to achieve Software Engineering Institute Level 2 accreditation, (2) enhanced diffusion of internal research and development (IR & D) products throughout the organization by providing employees better access to IR & D products, (3) enhance business and employee professional development by providing employees convenient electronic access to current and past project information and documentation. III. Theoretical Background of the Technology Acceptance Model This section provides a very abbreviated overview of the theory and previous research findings appearing in TAM-related, and other relevant information technology acceptance literature. Davis developed the TAM to provide an explanation of the determinants of computer acceptance that is general, capable of explaining user behavior across a broad range of end-user computing technologies and user populations, while also being both parsimonious and theoretically justified (Davis, 1989). TAM cuts a wide theoretical swath which includes the adoption of innovations, the cost-benefit paradigm, expectancy theory, and self-efficacy theory (Davis, 1989). Davis s original Technology Acceptance Model is shown in Figure I /04 $17.00 (C) 2004 IEEE 2

3 External Variables 1 Attitude Toward Using Intention to Use System Usage Ease of Use Figure I Technology Acceptance Model (Davis) Note 1. External Variables include system design characteristics, user characteristics (e.g., cognitive style and other personality variables), and task characteristics, nature of the development or implementation process, political influences, and organizational structure) Beliefs and Evaluations Attitude Toward Normative Beliefs & Motivation to Comply Subjective Norm Intention Behavior Figure II Theory of Reasoned Action (Fishbein, Ajzen) TAM is derived from the Theory of Reasoned Action (TRA) model developed by Fishbein and Ajzen to explain a broader range of behaviors based on situation specific combinations of personal beliefs and attitudes, and the effects of beliefs of others close to the individual (Szajna, 1996). The fundamental premise of TRA is that individuals will adopt a specific behavior if they perceive it will lead to positive outcomes (Compeau and Higgins, 1995). TAM is a derivative of TRA tailored to the study of user behavior in the context of information technology acceptance (Davis, 1989). TAM is theorized to apply to a broad range of information technologies. A significant and growing body of subsequent research has confirmed the usefulness of TAM and various extensions and revisions as a tool for investigating and predicting user information technology acceptance (e.g., Taylor and Todd, 1995; Szajna, 1996; Chau, 1996; Geffen and Straub, 1997; Doll, 1998). IV. Research Model and Research Hypotheses The research model is shown in Figure III. It supports the specific objective of this research to assess the relationships among TAM s two primary belief constructs; perceived usefulness and perceived ease of use, and users intention to use, and their usage of the target knowledge management system. The research model is similar to Davis original TAM (Figure I), however, the attitude construct is deleted. This is in accordance with Davis, et al. (1989) who found attitude was at best a partial mediator of the effect of perceived usefulness on intention to use, and that it added little causal explanatory power. The external variables constructs are also not included in the research model since there is no immediate intention to investigate antecedents to perceived usefulness and ease of use. The research hypotheses are: H1: usefulness will exhibit a significant positive direct relationship with behavioral intention to use. H2: The effects of perceived ease of use on behavioral intention will be significant and positive but mediated by perceived usefulness. H3: ease of use will exhibit a smaller but significant positive direct relationship with behavioral intention to use when perceived usefulness is controlled for /04 $17.00 (C) 2004 IEEE 3

4 Ease of Use Intention to Use System Usage Figure III Research Model H4: intention to use the system will exhibit a significant positive relationship with system usage. H5: usefulness and perceived ease of use will have a significant combined positive relationship with behavioral intention to use the target knowledge management information technology. H6: usefulness and perceived ease of use will have a significant combined positive relationship with usage of the target knowledge management information technology. V. Methodology A fifteen item survey comprised of tailored measurement scales designed to measure each of the four constructs was used in this research. Measurement scales for each of the research model constructs were drawn from previous information technology acceptance research. ease of use and perceived usefulness were measured using widely used four item measurement scales consistently demonstrating excellent psychometric qualities (Davis and Venkatesh, 1996). A four item scale measuring user s behavioral intention to use the target system was adapted from one developed by Venkatesh and Davis (2000). Subsequent research has shown it to have both high reliability and excellent psychometric qualities. Three items were used to measure user selfreported system usage. The first self-report usage item was adapted from Davis, et al. (1992). The third item was also drawn from the work of Davis (Davis, et al., 1992) and has been used widely in information technology acceptance research. Dialog boxes were included in the survey to elicit user feedback regarding perceived usefulness, perceived ease of use, and general system and, or survey comments. Employees in two major Northeastern U.S. metropolitan areas with system access were identified by the organization as survey subjects. Each was provided password access to the survey which was hosted on a university web server. Employee participation was optional but encouraged through correspondence from management which also authorized charging of time spent completing the anonymous survey. Access to survey data was strictly limited to the research team. VI. Results Fifty one employees, approximately 20% of identified survey subjects, responded. Sixteen responses had to be excluded: three due to significant incompleteness, and thirteen due to respondent comments indicating no system awareness and, or no experience using it. (This finding within the survey target group was an unhappy surprise to management.) The thirtyfive usable responses were found to constitute an acceptably representative organizational sample. VII. Data Analysis Cronbach Alpha measurement scale reliability coefficients calculated for each construct using the Statistical Analysis System (SAS) are shown in Table I. The reliability of all measurement scales was comfortably above the recommended minimum level of.70 for social science research (Hatcher, 1994), and the accepted desirable level of.80 for social science research. The overall weighted reliability of the survey instrument was /04 $17.00 (C) 2004 IEEE 4

5 Construct (Items) (4).978 Perceive Ease of Use (4).938 Intention To Use (4).952 Frequency of Use (3).896 Overall (15).944 Cronbach Alfa Table I Cronbach Alpha Reliability Coefficients Due to the limited sample size, statistical analyses were limited to correlation and regression techniques. Data analyses were performed using SAS Version 8.0. Correlation analysis results appear in Table II which includes the observed correlations and their associated pvalues (probability of observed correlation value under the null hypothesis of zero correlation) and in the context of the research model in Figure IV below. Data analysis results are now discussed in the context of the research hypotheses. Hypothesis one postulated a significant positive relationship between perceived usefulness and behavioral intention to use the target system. Evidence supporting confirmation of this hypothesis can be found in the positive correlation (.645) and highly statistically significant p value (). Hypothesis two hypothesized a significant positive relationship between perceived ease of use and behavioral intention to use the system mediated by perceived usefulness. This hypothesis was examined using multiple regression techniques. To establish usefulness as a mediator of the relationship between perceived ease of use and system usage, it is necessary to demonstrate the existence of four conditions: (1) a significant bivariate relationship between ease of use and usefulness, (2) a significant bivariate relationship between ease of use and usage, (3) a significant relationship between usefulness and intention to use when ease of use is controlled for, and (4) a reduced or weakened relationship between ease of use and usage when usefulness is controlled for (Baron and Kenney, 1986). Ease of Use Intention To Use System Usage Ease of Use Intention To Use System Usage Table II Correlation Matrix Regression analysis results relevant to hypothesis two are presented in Table III. The first two data rows illustrate necessary statistically significant bivariate relationships between ease of use and usefulness and ease of use and intention to use. Results of the regression of behavioral intention to use on perceived usefulness and perceived ease of use appear in the third row. These results indicate the absence of the hypothesized multivariate relationship in the survey data. Contrary to the required mediation conditions (conditions three and four above), the relationship between perceived usefulness and behavioral intention is not significant at nominal levels of acceptance (p value of.125) when the effects of ease of use are controlled for. Also unexpected is the fact that when the effects of perceived usefulness are controlled for, the relationship between perceived ease of use and behavioral intention is more significant (p-value of.086). Finally, perceived ease of use has a larger beta value (.384) than perceived usefulness (.341) in the multivariate regression. Although these results provide some evidence suggesting confirmation of hypothesis two (some mediation by perceived usefulness of the effects of perceived ease of use on behavioral intention) they reflect an unexpected relationship between perceived ease of use, perceived usefulness, and behavioral intention. When the effects of usefulness on behavioral intention are controlled for statistically, perceived ease of use appears to have a stronger and more significant relationship with intentions than perceived usefulness /04 $17.00 (C) 2004 IEEE 5

6 Condition 1. Bivariate: Intention to Use = ƒ (Ease of Use) 2. Bivariate: = ƒ (Ease of Use) 3. Multivariate: Intention to Use = ƒ (Ease of Use & ) Ease of Use (pvalue).645 () ().384 (.086) (p-value) R 2 N/A.428 N/A (.125).472 Table III Regression Results (Hypotheses 2, 3, 5) Hypothesis three predicted a reduced but significant positive relationship between perceived ease of use and behavioral intention when the effects of perceived usefulness were controlled for. Evidence suggesting confirmation of this hypothesis can be found in Table IV which shows that the effect of ease of use on behavioral intention is substantially reduced when the effects of perceived usefulness are controlled for in the multiple regression. This effect is reflected in the reduction of the beta value from.645 (p-value ) in the bivariate case to.384 (p-value.086) in the multivariate regression. Hypothesis four hypothesized a strong positive and significant relationship between behavioral intention to use and system usage. Table II presents evidence suggesting confirmation of this hypothesis in the.412 correlation (p-value <.017) between these constructs. This relationship is not as strong as expected. While some TAM research has yielded weaker intention-behavior correlations (e.g., Szajna, 1995) many have found evidence of a stronger tie between these variables. Hypothesis five hypothesized a positive and significant combined relationship between perceived usefulness and perceived ease of use and intention to use the system. Table III indicates 47% of the observed variation in intention to use the system is explained by perceived usefulness and perceived ease of use. This finding is also consistent with previous TAM research. Hypothesis six hypothesized a positive and significant relationship between the combined effects of perceived ease of use and perceived usefulness and usage. (Table IV) usefulness and perceived ease of use combine to explain 34% of the variation. This constitutes something of a departure from previous TAM research which has found perceived usefulness and perceived ease of use to explain 40% to 60% of the variability in system usage. However, the regression results shown in Table IV suggest that perceived usefulness does mediate the effects of perceived ease of use on system usage. Required statistically significant bivariate relationships (rows 1 and 2) between perceived ease of use and perceived usefulness and perceived ease of use and usage are confirmed. Multiple regression results presented in the third row indicate that when the effects of usefulness are controlled for, the strength and statistical significance of the relationship between perceived ease of use and usage is reduced considerably and that a significant relationship between perceived usefulness and usage exists. This is consistent with previous research that characterizes usefulness as a mediator of the effect of ease of use on usage. A summarization of the conclusions relative to the research hypotheses are presented in Table V. Condition 1. Bivariate: Usage = ƒ (Ease of Use) 2. Bivariate: = ƒ (Ease of Use) 3. Multivariate: Usage = ƒ (Ease of Use & ) VIII. Ease of Use (pvalue).515 (.002) ().154 (.529) (p-value) R 2 N/A.265 N/A (.068) Table IV Regression Results (Hypothesis 6) Discussion.344 The only finding in this research inconsistent with previous TAM research concerns the behavioral intention construct. usefulness and perceived ease of use combine to explain a percentage of the variation in behavioral intention that is very consistent with earlier research (approximately 47%). However, the individual relative effects of the two belief constructs are not consistent with previous findings. When the effects of perceived usefulness and perceived ease of use are decoupled in multiple regression analysis, perceived ease of use emerges as having a greater influence on behavioral intention than perceived usefulness /04 $17.00 (C) 2004 IEEE 6

7 Hypothesis 1. usefulness will exhibit a significant positive relationship behavioral intention 2. ease of use will have a significant positive indirect relationship with behavioral intention mediated by perceived usefulness 3. ease of use will have a smaller direct and positive relationship with behavioral intention 4. intention will have a significant positive relationship with system usage 5. usefulness and perceived ease of use will have a significant combined positive relationship with behavioral intention 6. usefulness and perceived ease of use will have a significant combined positive relationship with system usage Comments Confirmed, consistent with previous research Smaller mediation effect confirmed Stronger ease of use relationship with intention vis a vis usefulness inconsistent with previous research Confirmed Confirmed Intention-behavior correlation not as strong as some earlier studies Confirmed R 2 of.472 consistent with previous research Confirmed, mediating effect less than anticipated R 2 of.344 below that found in some previous research Table V Summary of Research Hypothesis Findings.578 (.0004) ().645 ().654 () Intention to Use.412 (.017) System Usage Ease of Use.515 (.002) Figure IV Research Model With Observed Correlations (p-values) The behavioral intention-usage correlation observed in the survey data collected in this research was also lower than observed in most previous TAM research. The relationship between perceived usefulness and perceived ease of use and system usage observed in the analysis of hypothesis six tends to cloud questions relative to behavioral intention. In this analysis, the nature of the relationship between perceived usefulness and perceived ease of use and their relative effect on usage were consistent with previous research. When the effects of perceived usefulness and perceived ease of use on usage were isolated in multiple regression, the effect of ease of use was diminished substantially and smaller than that of perceived usefulness. The total variation in usage explained by usefulness and ease of use were slightly below the nominal 40% benchmark typical of most previous TAM research. However, the qualitative nature of the relationship was consistent with previous findings. A possible explanation for inconsistent results centering on behavioral intention may lie in the nature of the research scenario. The research data were collected long after the introduction of the target knowledge management system. Straub, et al. (1995) observe quoting Fishbein and Ajzen (1980) that the purpose in measuring intention is to predict future behavior. Thus, in those TAM research scenarios associated with the brief introduction of a technology in order to predict future acceptance and usage, the behavioral intention construct is critical. In this research, the intent was not to predict usage, but to interpret experience with /04 $17.00 (C) 2004 IEEE 7

8 the target knowledge management system through the lens of the TAM. Research by Davis, et al. (1989) developed evidence to support the claim that the strength of the link between intentions and behavior is positively correlated with user experience and negatively correlated with the elapsed time between the measurement of intentions and behavior (Venkatesh and Davis, 1996). In this case, respondents had ample prior opportunity to become familiar with, or otherwise form their beliefs regarding the usefulness and ease of use of the target system. Measurement of intentions post facto may have contributed to the ambiguous results surrounding this construct. IX. Conclusions The results of this research yield preliminary evidence that previous information technology acceptance research, and specifically the significant body of work based on the Technology Acceptance Model, may serve as a foundation for much needed research of knowledge management system user acceptance. Relationships among primary TAM constructs found in this research are largely consistent with those typical in previous TAM research. usefulness and perceived ease of use combined to explain 34% of system usage variability (Table IV). This result is not inconsistent with a large body of previous TAM research in which these two constructs were found to explain about 40% of usage variance (Venkatesh and Davis, 2000). Significant positive relationships between perceived usefulness, ease of use, usage, and the mediating influence of perceived usefulness on the effect of ease of use on usage were consistent with previous TAM research. X. Limitations This research suffers inevitable generalizability limitations of any study of one information system in one organizational environment. Additional investigation of knowledge management systems implemented in a representative range of organizational settings is essential to the understanding of those factors critical to the success of knowledge management initiatives. A second key shortcoming of this research is its limited sample size, both in absolute terms, and relative to the population of potential organizational users of the target system. With approximately twelve percent of the population providing a usable response to the voluntary survey, one cannot summarily dismiss the possibility of sample bias. However, the broad range of responses received across all of measured constructs is a factor that mitigates this concern. One other shortcoming of this research is its reliance upon self-reported usage. Previous researchers (Taylor and Todd, 1995) (Szajna, 1996) have raised credible and largely unresolved questions regarding the fidelity of self-reported usage data and its relationship to key TAM constructs vis a vis actual usage data. XI. Future Research Additional study of diverse knowledge management information technology implementations in a range of organizational settings is necessary to support the accumulation of knowledge and the development of sound theory regarding organizational knowledge management initiatives. Wherever possible, future researchers should endeavor to collect and analyze both self-report and objective usage data. This would help resolve lingering questions regarding this important construct and its effect on previous TAM research. Future knowledge management system acceptance research should also be conducted to explore the perspective on ease of use illuminated by Gefen and Straub (2000) - and which may have influenced the findings of this research. It seems plausible that, as their research suggested, ease of use may play a more important role in the determination of user acceptance when considering intrinsic knowledge management tasks. Furthermore, although this research seems to suggest that previous TAM-based user acceptance research can serve as a basis for future investigation of knowledge management user acceptance, it seems clear other factors associated with the complex socio-cultural organizational implications of knowledge sharing must be explored and potentially included in a more complete theoretical model. To increase explanatory power for example, it may be necessary to add other theory-based individual beliefs to the current TAM belief constructs perceived usefulness and perceived ease of use. Alternatively, antecedents to the current TAM beliefs may be developed which capture some of the unique cultural implications thought to surround organizational knowledge management /04 $17.00 (C) 2004 IEEE 8

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