软件钱俊颖基于Android的日历系统的设计与实现外文文献翻译

services for mobile devices, and people are increasingly using Android devices to read books online. For example, university students were found to be willing to adopt mobile library services through mobile devices. Nevertheless, personal differences (e.g. age, gender, and educational level) may influence adoption and usage patterns of various information technologies.

2. Conceptual framework and hypothesis development

Figure 1 presents this study's research model, developed based on the theory of reasoned action (TRA).The intention to perform a particular behavior is mainly determined by a personal factor (e.g. an individual's attitude) and a social factor (e.g. a subjective norm). TRA has been used as the basis of several information system (IS) acceptance models, including web site usage and e-banking. TRA is a general model, which does not specify beliefs about a particular behavior. Hence, researchers need to consider other salient beliefs when adapting TRA to explain different adoption behaviors. From its initial release, Android has been constantly improved either in terms of features or supported hardware, and has been extended to an expanding range of devices. Android's open and customizable architecture allows manufacturers of Android devices to develop their hardware and software specifications with features designed to appeal to users and achieve market advantage. Hence, the research model in the study considers hardware, software, and design aesthetics as the main determinants of attitude.

The customizable nature of Android allows manufacturers of Android devices to develop functions and interfaces to satisfy the needs of their customers, primarily to offer differentiation through content and interface convenience. Android's infrastructure provides support for additional hardware, such as accelerated 3D graphics, dedicated gaming controls, USB flash drives, and USB hard disks. This infrastructure is an important hardware factor for user attitudes toward Android devices. Furthermore, previous studies have indicated user emotional reaction and product preferences are influenced by the product's aesthetic design. Thus, the model also includes aesthetic design as a key determinant for attitude.

Perceived value has been recognized as an important determinant of user intention to adopt new technologies. Perceived value is the consumer's overall assessment of the a product or service's utility as determined by the consumer's perception of what is received and given。 it can be enhanced by either increasing benefits of the product/service or by decreasing the expense of purchasing and using it. Sweeney and Soutar (2001) proposed an approach to evaluate perceived value based on four aspects: emotional value, social value, quality value, and cost value. Hence, this study proposes that these four values influence user intention to purchase mobile internet services. This study's research model proposes ten hypotheses, which are described in detail below.

Interface convenience

In this study, interface convenience is defined as the extent to which an individual believes that Android systems provided by manufacturers would provide an easy and efficient means of user–system interaction indicated that interface quality will influence the user's affect.In studying mobile internet services,demonstrated that quality of user–system interface can enhance user

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satisfaction and loyalty. Therefore, it is anticipated that increased convenience and ease of use would positively affect user attitudes toward Android devices.

Perceived content

Functions are anticipated to play an important role in Android, because the functions or software provided by manufacturers would improve operation efficiency. Perceived content can be defined as the user's perception of the quality (usefulness) of a smartphone's features provided. Linindicated that perceived content would increase positive attitudes towards adopting a smartphone, while Laurs (2009) found that embedded content is a major driver for mobile phone purchases. Thus, it is anticipated that perceived content will enhance users' attitudes toward Android devices. H2 is stated as follows:

H2. Perceived content will positively affect user attitudes toward Android devices.

Perceived infrastructure

Perceived infrastructure can be defined as the user's perception of the efficiency provided by the smartphone hardware (Lin, 2007). Android provides a range of hardware supports, such external storage, accelerated 3D graphics, and proximity and pressure sensors. This additional hardware support can help the manufacturers develop specific functions to assist their users in dealing with common tasks, providing users with a range of device specifications to meet their various needs. Past research has also indicated that device hardware spec can influence user feelings about quality and interactivity. For example, Park et al. (2018) demonstrated that hardware support for motion feedback can improve the interactivity of a mobile device and significantly influence the affective quality.

Design aesthetics

Design aesthetics have been found to be important for user acceptance of technology. Design aesthetics in this study refers to the balance, emotional appeal, or aesthetic of a smartphone which may be expressed through color, shape, or animation. Human visual sense is a key influence on cognition and thus emotion, thus aesthetically pleasing design is an crucial factor to strengthen user emotional attachment to a particular device. Nanda et al. (2008) suggested that the aesthetic design of mobile phones has an impact on users' emotional reaction, while Cyr et al. (2006) found that visual design aesthetics significantly impacted perceived enjoyment. Similarly, it is anticipated that design aesthetics will enhance user attitudes toward Android devices.

Attitude

Attitude is seen as an important factor influencing user intention for technology adoption and, in this case, can be defined as the user's favorable feeling towards an Android smartphone. Park and Chen (2007) found that behavioral intention to use smartphones was largely influenced by attitude toward the technology, while Cheong and Park (2005) found similar results in regards to mobile internet usage. Lin (2007) found that attitude positively influences user intention to continue to use various web sites.

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3. Research methodology

This study focuses on Android smartphone users in Taiwan. In the Asia-Pacific region, Taiwan's smartphone penetration rates are very high, with only South Korea, Hong Kong, Singapore, Japan and Australia having higher smartphone ownership rates. Across all markets, smartphone usage is more prevalent among younger, male and better educated groups. One in two online consumers use a Smartphone in Taiwan, with Android holding a 71 percent market share of smartphone operating systems.

A pre-test and pilot test were conducted to validate the questionnaire items. The pretest invited two smartphone experts to assess the logical consistency, ease of understanding, question sequence and contextual suitability of the items. Ten people who had been using Android smartphones for at least one year were invited to evaluate the wording of the items. Their comments resulted in a few minor changes to the wording and sequence of the questions, with the revised questionnaire presented in the Appendix.

Announcements about the online questionnaire were posted on web sites and bulletin board systems featuring smartphone-related activities in Taiwan. Potential respondents were incentivized to participate by the opportunity to win gift certificates in a lucky draw. To prevent duplicate submissions, respondent identities were checked by their e-mail and IP address on receipt of the questionnaire. An initial total of 957 responses were collected, of which 76 were either incomplete or duplicates, leaving 881 valid responses. Of the valid respondents, 30 percent were female, and 68 percent were between 20 to 29 years of age. About 45 percent of respondents were current university undergraduates.

The proposed model and hypotheses were tested using partial least squares (PLS) analysis. As in structural equation modeling (SEM), the PLS approach allows researchers to simultaneously assess measurement model parameters and structural path coefficients.Unlike covariance-based SEM, PLS focuses on maximizing the variance of the dependent variables explained by the independent ones rather than reproducing the empirical covariance matrix. The advantages of PLS are that it imposes minimal restrictions on measurement scales, sample size, and residual distributions. In our model, all items are viewed as the effects (rather than causes) of latent variables, thus they are modeled as reflective indicators. Given the relatively small sample size (Nnon–user=114), the respondents are classified into different groups according to their experience using mobile internet services.

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