Microblogging Reposting Mechanism: An Information Adoption Perspective

This study uses the Elaboration Likelihood Model （ELM） and social presence theory to examine the microblogging reposting mechanism. Subjective and objective data were collected from 216 respondents in a field experiment. The results indicate that information quality and source credibility of microblogging messages affect users＇ reposting intention by affecting their perceptions of the usefulness and enjoyment of the information. Perceived enjoyment has a greater impact on reposting intention than perceived usefulness. Furthermore, users are able to perceive social presence when interacting with microblogging messages. Social presence plays a full mediating role between information quality and perceived enjoyment, and a partial mediating role between information quality and perceived usefulness.

Farmers' seed choice behaviors under asymmetrical information: Evidence from maize farming in China

the financial support of the National Social Science Foundation of China （14ZDA038）;the National Natural Science Foundation of China （71222302;71373255;71573133）;the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences （2012RC102）

A Study on Idea Adoption Prediction Model Based on SMOTE-AdaBoost:Taking Salesforce Platform as an Example

In the context of information overload,companies often struggle to effectively identify valuable ideas on their open innovation platforms.In this article,we propose an idea adoption strategy based on machine learning.We used data from a well-known open innovation platform,Salesforce,and extracted characteristic variables using the Information Adoption Model.Four classification models were then constructed based on AdaBoost,Random Forest,SVM and Logistic Regression models.Due to significant differences in the number of positive and negative samples in the OIP,we used the SMOTE method to address the problem of data imbalance.The results of the study showed that the ensemble learning models were more accurate in identifying valuable ideas than the individual machine learning models.When comparing the two ensemble learning models,AdaBoost outperformed Random Forest in predicting both positive and negative class samples.The SMOTE-AdaBoost model achieved a recall of 0.93,a precision of 0.92 and an impressive AUC of 0.98 in identifying adopted ideas,which could well identify valuable ideas and has implications for improving the efficiency and quality of idea adoption in OIP.The shortcoming of this work is that it only investigated a single platform.In the future,we will consider extending this method to different platforms and multiple classification problems.

Behavioral Intention to Continue Using a Library Mobile App

To meet the needs of today’s library users,institutions are developing library mobile apps(LMAs),as their libraries are increasingly intelligent and rely on deep learning.This paper explores the influencing factors and differences in the perception of LMAs at different time points after a user has downloaded an LMA.A research model was constructed based on the technology acceptance model.A questionnaire was designed and distributed twice to LMA users with an interval of three months to collect dynamic data.The analysis was based on structural equation modeling.The empirical results show that the perceived ease of use,the perceived usefulness,the social influence,and the facilitating conditions affected the users’behavioral intention,but their impacts were different at different times.As the usage time increases,the technology acceptance model is still universal for understanding the user perception of LMA.In addition,two extended variables(social impact and convenience)also affect the user’s behavior intention.User behavior is dynamic and changed over time.This study is important both theoretically and practically,as the results could be used to improve the service quality of LMAs and reduce the loss rate of users.Its findings may help the designers and developers of LMAs to optimize them from the perspective of a user and improve the service experience by providing a deeper understanding of the adoption behavior of information systems by LMA users.

Impact of Internal Factors on Information Technology Adoption: An Empirical Investigation of Chinese Firms

Organizations differ significantly in their inclination to deploy information technology （IT）. The factors that determine the organizational inclination to deploy IT need to be classified to help firms formulate an appropriate e-strategy. This paper discusses a framework that explains the influence of internal factors on IT adoption. The framework is based on quantitative data on IT adoption from 95 firms in China. The results highlight that the internal factors of leadership, organizational learning, and IT resources positively impact IT adoption. The study also shows that these factors are correlated.

Social Networking With a Purpose

Online dating sites are growing steadily in popularity, despite challenging economic times. In addition, online dating sites are facing increasing competition for their services from free social networking sites. Despite these harsh economic times and the increasing competition, online dating websites have continued to increase in popularity. This growth justifies the need to better understand how these volitional and paid websites have been so successful. By addressing the call for research in emergent information systems （IS） contexts, this study proposes a theoretical framework for investigation in a purely volitional website context. A framework based on the DeLone and McLean＇s IS success model is developed. Implications for practice and research are discussed.

IDT-TAM Integrated Model for IT Adoption

Two classical theories, the technology acceptance model （TAM） and the innovation diffusion theory （IDT）, were integrated into a model for analyzing individual information technology （IT） adoption behavior. In this IDT-TAM framework, the perceived characteristics of innovation are categorized as subjective evaluation, objective conditions, and interaction factors. The cognitive mechanisms that drive user IT acceptance are analyzed based on the patterns through which these characteristics influence individual user IT adoption behavior. The model was tested using an empirical survey regarding the adoption and use of e-mail in China. Results from a structural equation model analysis illustrate that the model provides meaningful insights for understanding, explaining, and predicting the IT adoption behavior of Chinese users.

Broadband usage for rural communities in the North Island of Aotearoa New Zealand

New Zealand government’s Rural Broadband Initiative(RBI)aims to invest 400 million New Zealand dollar to provide 99%of New Zealanders with access to 50 Mbps peak broadband speed,with the remaining 1%at 10 Mbps by 2025.By 2017,stage 1 of the RBI has been completed,and research is needed to find out the level of usage,proficiency,and productivity achieved by then.Therefore,a survey was carried out to learn whether the rural residents and their communities are making good use of the new fast broadband connection.The survey collected data from 217 rural residents from North Island,and the results indicate that about half of the interview respondents are satisfied with the new broadband speed and the reliability which is offered by RBI stage 1.However,there is about 28%of the respondents disagreed with them.The majority of the Internet uses for rural residents are information searching,reading news,online entertainment,and online banking.Besides that,only a small proportion of respondents know how to utilize the Internet in their work/business and benefit/profit from it,e.g.,using cloud technology capabilities and online marketing campaigns,etc.by then.Therefore,we argue that information and communications technologies(ICT)adoption is not only the availability of the infrastructure but also the beneficial outcomes of Internet availability.In other words,Internet skills in-depth training and education need to catch up with the infrastructure deployment,which is useful to fuel the digital productivity and inclusion for booming rural economies.The survey data-driven findings presented in this paper could serve as a reference to inform government policymakers and those who wish to create,invest,and take actions to speed up the economic and social growth of rural communities in Aotearoa New Zealand through the Internet while shifting from the Internet speed and traffic volume-driven to a more effective Internet connectivity and value-added driven rural economy.