It is worth noting that the effects of perceived ease of use and self-efficacy on behavioral intention are marginally significant. These findings may occur as the result of the great popularity of mobile phone usage and the relatively high user-perceived ease of use and self-efficacy towards m-service systems in Taiwan. Especially, the relatively young respondent sample could have contributed to this result due to its “expertise”. Therefore, a number of limitations and issues remain to be addressed in the future.
First, investigation of m-service acceptance is relatively new to researchers in the field of IS.
The findings discussed and their implications were obtained from one single study that examined a particular technology and targeted a specific user group in Taiwan. Thus, this study suffers from problems with geographical size and location of the population. Predicting usage intention of m-service in a small, densely populated geographical area that has unlimited access to a mobile service infrastructure varies greatly from a population that is sparely located in rural areas.
If future researcher wishes to make glittering generalities, they should first randomize their sample to include other nationalities and geographical areas beside Taiwan. Therefore, continued research is needed to generalize the findings of this study and extend the discussion to include additional technologies or groups.
Second, searching for additional variables that will improve our ability to predict usage intention more accurately is necessary. It would be reasonable to add social norms, perceived
playfulness and perceived critical mass to our proposed model, further expanding the number of situations to which it applies.
Third, we did not incorporate actual usage behavior in the proposed model. This is not a serious limitation as there is substantial empirical support for the causal link between intention and behavior (Taylor & Todd, 1995a; Venkatesh & Davis, 2000; Venkatesh & Morris, 2000).
However, behavioral intentions are only partially useful as their correlation with actual behavior is low and mediated by many other variables. Thus, continued research is needed to discuss this more thoroughly.
Fourth, in order to decrease the length of the questionnaire and increase the willingness of consumers to participate in our survey, we used the simplified measures of self-efficacy, perceived usefulness, and perceived ease of use. That is, we only kept 3 of the 10 original items for self-efficacy, 3 of the 6 for perceived usefulness and perceived ease of use respectively. In addition, we used two items for three constructs respectively. This may violate the “three measures rule”for identification (Ridgon, 1995).
Fifth, this study only examined the main effect of drivers on behavioral intentions. However, m-service managers may be interested in how some of these drivers interact to affect adoption intention. For example, would perceived usefulness interact with self-efficacy or financial resources to affect consumer intention? Future research can reexamine the entire conceptual model.
Sixth, the model is cross-sectional, that is, it measures perceptions and intentions at a single point in time. However, perceptions change over time as individuals gain experience (Mathieson et al., 2001; Venkatesh & Davis, 1996; Venkatesh et al., 2003). This change has implications for researchers and practitioners interested in predicting m-service usage over time. Additional research efforts are needed to evaluate the validity of the investigated model and our findings. A dynamic model or longitudinal evidence would not only help predict beliefs and behavior over time, but also enhance our understanding of the causality and the interrelationships between variables that are important to the acceptance of m-service by individuals.
Finally, self-efficacy and facilitating conditions have been modeled as indirect determinants of intention fully mediated by perceived ease of use (Venkatesh, 2000). Venkatesh et al.’s (2003) model of Unified Theory of Acceptance and Use of Technology (UTAUT) also shows when
effort expectancy (perceived ease of use) construct is present in the model, self-efficacy and facilitating conditions become nonsignificant in predicting intention. However, this study suggests that with the presence of perceived ease of use in the model, self-efficacy and perceived financial resource are significant determinants of behavioral intention of m-service usage. Since the UTAUT has not been tested in the context of m-service, future research could compare our model with the UTAUT in predicting m-service usage intention.
9. Conclusions
Responding to Berthon et al.’s (2002) call for replication and extension research, this study, based on the TAM, TPB and Luarn & Lin’s (2005) model, respecifies and validates an integrated model for predicting consumer intention to use m-service by adding perceived credibility, self-efficacy and perceived financial resources to the TAM’s nomological structure and reexamining the relationships between the proposed constructs. The results support that the Luarn & Lin’s (2005) m-banking acceptance model can be generalized to predicting consumer intention of using m-service. The validated model provides a useful framework for managers needing to assess the possibility of success for m-service introductions, and it contributes to their understanding of the determinants of acceptance in order to pro-actively design interventions targeted at populations of consumers that may be less inclined to accept and use m-service systems.
Acknowledgements
This research was substantially supported by the National Science Council (NSC) of Taiwan under grant number NSC 93-2416-H-018-003.
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Appendix
Measuring Items Used in this Study Perceived usefulness
PU1 Using mobile services would improve my performance in conducting transactions.
PU2 Using mobile services would make it easier for me to conduct transactions.
PU3 I would find mobile services useful in conducting my transactions.
Perceived ease of use
PEU1 Learning to use mobile services is easy for me.
PEU2 It would be easy for me to become skillful at using mobile services.
PEU3 I would find mobile services easy to use.
Perceived credibility
PC1 Using mobile services would not divulge my personal information.
PC2 I would find mobile services secure in conducting my transactions.
Self-efficacy
I could conduct my transactions using the mobile service system…
PSE1 …ifIhad just the built-in help facility for assistance.
PSE2 …ifIhad seen someoneelseusing itbeforetrying itmyself. PSE3 …ifsomeoneshowed me how to do it first.
Perceived financial resources
PFR1 Financial resource (e.g., to pay for communication time, subscription, and/or service) is not a barrier for me in using mobile services.
PFR2 I have enough financial resources (e.g., to pay for communication time, subscription, and/or service) for using mobile services.
Behavioral intention
BI1 Assuming that I have access to the mobile services, I intend to use them.
BI2 I intend to increase my use of mobile services in the future.
計畫成果自評：
本計畫研究成果已刊登於 The Fourth International Conference on Mobile Business (ICMB 2005)，另外亦被 Information Systems Journal (SSCI)條件式接 受，研究成果受國際資管學術肯定。