Yazn Alshamaila

With the increasing popularity of mobile learning in educational settings, the use of social networking sites (SNSs) as a tool for remote learning has become increasingly prevalent. However, the negative aspects of mobile learning through SNSs have not been extensively explored by scholars. Therefore, in this paper, we aim to investigate the impact of social overload, information overload, life invasion, and privacy invasion on students’ technostress and exhaustion and the resulting reduced intention to use SNSs for mobile learning. We also aim to investigate the impact of social overload, information overload, life invasion, and privacy invasion on students’ technostress and exhaustion and the resulting reduced intention to use SNSs for mobile learning. Data were collected through an online survey from 648 voluntary participants in Jordanian universities. The SOR framework provided a theoretical foundation for understanding the impact of SNSs on mobile learning. Through this study, we found information overload and life invasion were significantly related to higher levels of technostress and exhaustion among students. This suggests that, when students feel overwhelmed by excessive information or when their personal lives are invaded by SNS use, they experience increased technostress and exhaustion. Moreover, the study revealed that technostress and exhaustion were positively associated with a reduced intention to use SNSs for mobile learning. This indicates students who experience higher levels of technostress and exhaustion are less likely to engage with SNSs as a platform for their mobile learning needs. In contrast, we did not find a significant relationship between social overload and technostress, suggesting the amount of social interaction on SNSs may not directly contribute to students’ technostress levels. Additionally, we observed no significant relationship between privacy invasion and exhaustion, indicating privacy concerns may not directly contribute to students’ feelings of exhaustion in the context of mobile learning through SNSs. Regarding practical implications, we thus suggest the importance of establishing norms and rules to protect students’ privacy and prevent overburdening them with excessive SNS use. The SOR framework provides a theoretical foundation for understanding the impact of SNSs on mobile learning, and future researchers could benefit from its application.

Software defect prediction is a promising approach aiming to improve software quality and testing efficiency by providing timely identification of defect-prone software modules before the actual testing process begins. These prediction results help software developers to effectively allocate their limited resources to the modules that are more prone to defects. In this paper, a hybrid heterogeneous ensemble approach is proposed for the purpose of software defect prediction. Heterogeneous ensembles consist of set of classifiers of different learning base methods in which each of them has its own strengths and weaknesses. The main idea of the proposed approach is to develop expert and robust heterogeneous classification models. Two versions of the proposed approach are developed and experimented. The first is based on simple classifiers, and the second is based on ensemble ones. For evaluation, 21 publicly available benchmark datasets are selected to conduct the experiments and benchmark the proposed approach. The evaluation results show the superiority of the ensemble version over other well-regarded basic and ensemble classifiers.

With the use of Web 2.0 technology, e-commerce is undergoing a radical change that enriches consumer involvement and enables a better understanding of economic value. This emerging phenomenon is known as social commerce. Social commerce (s-commerce) presents a new alternative for consumers to search for and find information about products they are seeking to buy. In spite of its universality, the adoption of this burgeoning technology is affected by several factors. This research project is an initial attempt to explore individuals’ intention of s-commerce usage through the data mining approach. The data was collected via a web-based questionnaire survey of 360 social network site (SNS) users in Jordan. Data mining techniques were then used to analyze the collected data in order to figure out what group of features is best for predicting s-commerce adoption among SNS users. The results showed that data characteristics related to gender, monthly income, civil status, number of connections, and prior online shopping experience are key factors in the classification process. The findings may assist researchers in investigating social commerce issues and aid practitioners in developing new s-commerce strategies.

Online interactions pave the way for new streams of collaborations and support among connected users of social networking sites, and this collaboration is leveraged for business purposes. The purpose of this paper is to contribute to a growing body of research on social commerce by studying individuals’ behavior from the consumer perspective of information technology innovations. By adopting “social support” and the technology acceptance model as a theoretical base, this study used a web-based questionnaire survey to collect data from 325 users of SNSs in Jordan. The data were then analyzed using Statistical Package for the Social Sciences regression. Jordan was selected because it is a country that has reported high SNS usage compared to other countries. The main factors that were identified as playing a significant role in individual adoption of social commerce were social commerce construct and perceived usefulness. This study did not find enough evidence that perceived ease of use and perceived information quality were a significant determinant of social commerce adoption. These findings have important implications and value for the academia, businesses managers, and social media specialists in terms of formulating better strategies for handling social commerce effects on businesses. For social media specialists, using the research model in this study can assist in increasing their understanding of why some individuals choose to adopt social commerce services. Additionally, business managers may need to improve their interaction with SNS users and develop a better understanding of how consumers use social commerce in the purchasing decision process. Based on our review of the existing scientific literature on social commerce, few empirical studies have been conducted to scientifically evaluate and explain the usage behavior of social commerce in Jordan. This paper contributes to the continuing research in social commerce adoption and diffusion in the individual context.

Purpose: The purpose of this paper is to contribute to a growing body of research on cloud computing, by studying the small to medium‐sized enterprise (SME) adoption process. If SMEs have access to scalable technologies they could potentially deliver products and services that in the past only large enterprises could deliver, flattening the competitive arena.Design/methodology/approach: By adopting the Technological, Organisational and Environmental (TOE) framework as a theoretical base, this qualitative exploratory study used semi‐structured interviews to collect data in 15 different SMEs and service providers in the north east of England. The north east of England was selected as it is a region that aspires to become home to innovative digital firms and most of the companies in the region are SMEs.Findings: The main factors that were identified as playing a significant role in SME adoption of cloud services were: relative advantage, uncertainty, geo‐restriction, compatibility, trialability, size, top management support, prior experience, innovativeness, industry, market scope, supplier efforts and external computing support. In contrast, this study did not find enough evidence that competitive pressure was a significant determinant of cloud computing adoption.Research limitations/implications: These findings have important implications and great value to the research community, managers and information and communication technologies (ICT) providers, in terms of formulating better strategies for cloud computing adoption. For service providers, using the research model in this study can assist in increasing their understanding of why some SMEs choose to adopt cloud computing services, while seemingly similar ones facing similar market conditions do not. Also, cloud computing providers may need to improve their interaction with SMEs which are involved in the cloud computing experience, in an effort to create a healthy environment for cloud computing adoption, and to remove any vagueness surrounding this type of technology.Originality/value: This study is an attempt to explore and develop an SME cloud computing adoption model that was theoretically grounded in the TOE framework. By adopting the TOE framework this study has shown that the three contexts of this framework (technological, organisational, and environmental) are connected to each other.