Dimensions of self-efficacy in the study of smart phone acceptance

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Abstract

This study focuses on smart phone acceptance in a major delivery service company in Taiwan. Technology Acceptance Model (TAM) was tested in two different forms, the original and with self-efficacy added. A two-dimensional improvement to the theory of self-efficacy was investigated in this research. Only assisted self-efficacy was related to both perceived ease of use and perceived usefulness, but Individual Self-efficacy was only a predictor of perceived ease of use. This result offers new evidence to the debate of the role of self-efficacy on TAM constructs. Interesting findings including a strong influence of perceived ease of use on perceived usefulness and behavioral intention were compared to prior studies to add additional insights for future research.

Research Highlights

► Smart phone adoption is verified through modified technology acceptance model. ► The two types of self-efficacy shed lights on the dimensionality debate. ► Profile analysis shows that self-efficacy greatly affects constructs relationship.

Introduction

Technology advances have made personal, technological gadgets smaller, more powerful, much easier to use, and conveniently portable. Personal communication devices have evolved from dedicated landlines for the whole household to personalized cell phone devices for individuals. As more of these personal technology devices become available and affordable for the general consumers, convenience and needs for a more integrated solution for all these devices may very likely shape the future trend. Consequently, researchers and practitioners have focused on the promising development on this technology. One great example is the emergence of smart phones that integrates cell phone and personal digital assistant (PDA) technologies into one single device.

Such a mixture of two or more technologies opens new challenges and opportunities for businesses as well as individuals. With smart phones as an integrated solution, consumers no longer have to carry multiple technology devices where each device offers only a handful of limited functions to accomplish certain tasks. One report from Jupiter Research [18] indicates that 62% of consumers prefer to carry a single technology device (such as smart phones) even if the features of the device may compromise advanced functions (e.g., size and battery life). Around 74% said the key mobile feature — telephony, should remain as one core component of the aforementioned technology. In addition, the same report predicts smart phones to have a compound annual growth rate of 29% through 2009.

The growth of smart phone sales seems inevitable, but this technology has not yet offered a converged set of features. Chang, Chen and Zhou [7] suggested eleven “must-have” and eight “desirable-to-have” features. Even their “must-haves” are not universally available on all smart phones today, pointing to current market situation that there is no one smart phone standard that is agreed upon across smart phone manufacturers. Much interest from various types of technology manufacturers (e.g., traditional cell phone vendors, PDA manufacturers and even computer software/hardware companies) has contributed to the divergence of smart phone features. Some of these manufacturers just build smart phones on top of their existing technological base and hence, making the products very diverse in the different features offered. As a rather recent example, Apple's iPhone includes features such as adding a sensor to rotate contents when the device is rotated and abandoning of keyboard/stylus user interface in favor of the use of bare fingers. The success of Apple's touch keyboard and screen rotation as a bundled feature of their iPhone and iPad has attracted interest of other device manufacturers. Similar features are becoming available on cell phones, tablet computers and other personal devices.

Another reason is that business use cases for such converged device have not yet been expanded beyond basic emailing and scheduling. A compact smart phone with loaded functions like wireless transmission (Infrared, Bluetooth, WiFi, and WiMax), email, camera and barcode/image recognition, voice command and recognition, Power Point Presentation, scheduling, Web browsing, and desktop publication tools is deserved to be seamlessly integrated and used professionally. A killer application to business areas has not been available to satisfy a broader business audience. As companies continue to uncover their new technological integrations into the smart phones area, it is becoming increasingly difficult to precisely define what a smart phone really is. Nonetheless, the trend of turning it into an “all-in-one” personal communication device may reshape the future of business communications in general and information technology area in particular.

Section snippets

Research purposes

Although the adoption of smart phones is gaining momentum, smart phone's unique position as an integrated communication device with sufficient possibilities for different hardware and software combinations has made it a viable choice for many uses. Although many features of smart phones may easily attract younger generations or people who are technology savvy, it may be an up-hill battle if it is introduced to a totally different audience. Few businesses have a majority of their employees who

Technology Acceptance Model (TAM)

Davis' [13], [14] Technology Acceptance Model (TAM) was originated from several psychological theories, including Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB). Both TRA and TAM theories agree that beliefs affect a person's attitude toward a target behavior. Attitude, in turn, may influence behavioral intention, and eventually affects the actual behavior.

In TAM (Fig. 1) the actual behavior is affected by behavioral intention (BI), and behavioral intention is directly

Model 1 — TAM in smart phone acceptance

In this paper, the first model is developed to closely follow the original form of TAM to examine smart phone acceptance. Based on existing studies on TAM [8], [13], [24], [25], [26], [50], [51], [53], construct relationships are hypothesized as follows. The model is graphically depicted in Fig. 2 with all proposed hypotheses labeled. Note that this is a simplified TAM model since prior studies have either suggested to remove the attitude construct from the model or directly adopted the

Research method

A survey instrument was developed based on prior TAM and self-efficacy literature. The questionnaire was reviewed by a panel of content experts to ensure clarity and some good face validity. The survey was then, conducted at seven major operating locations of a large delivery service provider in Taiwan called Hsin Chu Trans (HCT). It is one of the first and is still one of the largest delivery service companies in Taiwan. Target respondents were employees who were directly involved with the

Scale development

Items in the questionnaire were derived from existing TAM and self-efficacy literature. A 5-point Likert-type scale was employed. The scale ranges from 1 (strongly disagree) to 5 (strongly agree). Constructs were first analyzed with an exploratory factory analysis to verify their dimensionality. Sampling adequacy was then, measured by running the Kaiser–Meyer–Olkin (KMO) test, which resulted in a value of .92. Since this value exceeds the recommended value of .90, the data are considered to be

Model 1: TAM

In the first model, the relationship was tested out among TAM constructs. As with several existing TAM-based studies, the result supports similar path relationships among TAM constructs (see Fig. 4). The chi-square statistic for this model is χ2 (196) = 428.29, p < .001. Although the chi-square is significant, several prior studies (such as Kline [31]) indicate that this statistic is extremely sensitive to sample size. The value of Chi-square divided by degrees of freedom is approximately 2.20,

Kuanchin Chen is an Associate Professor of Computer Information Systems at Department of Business Information Systems, Western Michigan University. Dr. Chen's research interests include electronic business, privacy & security, online behavioral issues (e.g., interactivity, dependency, and tracking/protection), Internet frauds, usability, data mining, and human computer interactions. He has published articles in journals and other academic publication outlets, including Decision Support Systems,

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    Kuanchin Chen is an Associate Professor of Computer Information Systems at Department of Business Information Systems, Western Michigan University. Dr. Chen's research interests include electronic business, privacy & security, online behavioral issues (e.g., interactivity, dependency, and tracking/protection), Internet frauds, usability, data mining, and human computer interactions. He has published articles in journals and other academic publication outlets, including Decision Support Systems, IEEE Transactions on Systems, Man, and Cybernetics, Information & Management, Communications of the Association for Information Systems (CAIS), IEEE Transactions on Education, Journal of Database Management, Journal of Computer Information Systems and many others. He currently serves on the editorial or advisory boards of Information Resources Management journal, International Journal of Information Systems and Change Management, Journal of Website Promotion, Communications of the ICISA, IGI Global (formerly Idea Group), eWeek, and CMP.

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    Jengchung Victor Chen is an Associate Professor in the Institute of International Management at National Cheng Kung University, Tainan, Taiwan. Since graduated from the CIS doctoral program at the University of Hawaii in 2002, he has 30 articles published or accepted in refereed journals such as Information and Management, Decision Support Systems, and CyberPsychology and Behavior. His research interests are Information Ethics, Electronic Commerce, Service Quality, and Project Management.

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    David C. Yen is currently a Raymond E. Glos Professor in Business and a Professor of MIS of the Department of Decision Sciences and Management Information Systems at Miami University. Professor Yen is active in research and has published books and articles which have appeared in Communications of the ACM, Decision Support Systems, Information & Management, Information Sciences, Computer Standards and Interfaces, Government Information Quarterly, Information Society, Omega, International Journal of Organizational Computing and Electronic Commerce, and Communications of AIS among others. Professor Yen’s research interests include data communications, electronic/mobile commerce, and systems analysis and design.

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