Search results

E‐learning is becoming a major component in academia today. Therefore, the success of e‐learning online communities is crucial in order to ensure their permanency and effectiveness. There is a need for formalized guidelines in e‐learning that instruct the designer (course instructor) on how to design, maintain, and manage a course. Some research has been done on the subject, but none proposes formalized guidelines, and none draws the results from the users’ perspectives. The users, students in this case, should be at the heart of the design and their thoughts, wishes, and needs should be implemented in the user‐centered design. In this study, through an iterative testing approach, the researchers formalized and validated a set of design heuristics that instruct an online educator on how to design, manage, deliver, and nurture an e‐Learning online community.

Development of mobile commerce (m‐commerce) environments that have user‐friendly features is important to accelerate the adoption of m‐commerce. The current research studies web‐based features that are crucial to the success of mobile air ticketing commerce.

There are two phases involved. In the first phase, the current research develops a web‐based mobile airline ticketing (W‐MAT) model to study usability features necessary to perform mobile air ticketing commerce. Thirty‐six features are mapped and identified based on the W‐MAT model. In the second phase, the air ticketing web sites for 27 most popular airline companies and online air travel agencies are examined to analyze their existing implementation patterns on these 36 features. The pattern analysis is based on web site features analysis and web site versatility analysis.

The analysis of web site features resulted in the development of an adoption feature pyramid that classified the 36 features into three categories. The analysis of web site versatility was based on multivariate cluster analysis that classified these 27 web sites into four groups.

The findings on web site features and web site versatility analyses in the current research are beneficial to future m‐commerce airline companies and air travel agencies, mobile device developers, and air ticketing m‐commerce interface designers.

The study concludes that the W‐MAT model‐based air ticketing features with usability emphasis are crucial to develop efficient mobile air ticketing web sites; and thereby, accelerating the adoption of m‐commerce for the air travel industry in the near future.

The purpose of this study is to explore the current usage and acceptance of classroom technologies by secondary math/science education teachers in one community.

Forty‐seven secondary education math and science teachers in one American city responded to a survey about their use and perceptions of technology in their lives and classrooms.

Results indicate teachers use technology more for personal instructional reasons, such as class preparation, than for interactions with their students whether inside the classroom or outside the classroom. Primary factors inhibiting the use of technology relate to time, training, and preparation. Teachers can see the benefit of using technology to promote students’ learning experience. However, teachers are neutral about technology being advantageous for improving in‐class activities.

A significant connection between teachers’ technology acceptance and usage is presented.

The purpose of this study is to provide a data mining approach for classifying Taiwanese healthcare institutions based on customer value assessment. Each institution type has developed its own marketing strategy along with relationship management strategies.

Real transaction data from 88 pharmaceutical companies were the study samples. Expert interviews were conducted to analyze industry knowledge. The frequency, money, and contract term (FMC) model was developed to assess and segment the healthcare institutions. ANOVA and the Scheffe post-test were used to explore the test effects of each FMC indicator among the groups. The C5.0 decision tree was then used to generate the behavioral rules of various segmentations. Finally, this study combined the related variables with the purchasing behavioral rules to propose specific strategies for each type of healthcare institution.

A total of 663 health care institutions in Taiwan were divided into four types: loyalist, intellectualist, nitpicking, and churn. The terms frequency (F), money (M) and contract term (C) were all significant indicators for determining the differences among the four customer categories at the 0.01 level of significance. The behavioral rules related to the four categories were determined by using the C5.0 algorithm.

This FMC model can provide a strategic development method for the pharmaceutical industry to conduct market segmentation. The findings may assist pharmaceutical companies provide customized services to health care institutions and to manage their downstream demand effectively.