Abstract-The initial criteria for evaluating a researcher's output is the number of papers published. Furthermore, for the measurement of author's research quality, the number of citations is significant. Typically, citations are directly linked with the visibility of a research paper. Many researches had shown that the visibility of a research paper can be improved further by using the search engine optimization techniques. In addition, some research already proved that the visibility of an article could improve the citation results. In this article, we analysed the impact of search engine optimization techniques that can improve the visibility of a research paper. Furthermore, this paper also proposing some strategies that can help and making the research publication visible to a large number of users.

The involvement application and use of crisis and emergency management and communication are increasing rapidly. This study conducts a systematic literature review to identify the development of theoretical models in the area of social media crisis communication and management. The study aims to review and analyse the relationship of social media-based crisis communication in the context of crisis informatics and its taxonomy and the related crisis communication theoretical models to derive the challenges and limitations. A total of 207 articles were selected for the evaluation based on quality, relevancy, and contribution. The findings revealed that the situational crisis communication theory (SCCT) is the most dominant theory, followed by social-mediated crisis communication (SMCC) and integrated crisis mapping (ICM) models. The study identified theories such as the STREMII model, social media crisis management matrix/framework (SMSMF), and an interactive crisis communication model (ICCM) as emerging models. Moreover, the result of the finding shows that stakeholder interaction is an understudied field, while information reliability and processing for decision-making purposes, the wider application of social media sites, privacy issues, and how social media interaction can improve community resilience or build stakeholders relationships remain suitable topics for future research.

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Smart education and the sustainable development of smart campuses have drawn significant research attention. This is enabled by intelligent devices that are widely attracting massive applicability in personal and big business contexts and can increase efficiency and convenience. This paper aims to present a solution to address the lack of a proper adoption model for smart campus initiatives. The evaluation and synthesis of the literature were conducted by following the systematic literature review (SLR) procedure. The study’s findings revealed the taxonomy and IoT technologies leading to the wide adoption of IoT-based smart campuses. The technology adoption models and their corresponding variables help the authors identify and classify a suitable adoption framework for smart campuses. The limitations and challenges of adoption theories as they pertain to smart campuses are discussed. Finally, the study adapts perceived scalability, perceived replicability, perceived reliability, perceived privacy and security, perceived trust, the cost of deployment, usefulness, enjoyment, and technicality as adoption factors of sustainable smart campuses. This study offers practical and theoretical implications regarding the adoption and propagation of emerging smart campuses.

The advancement of technology is making university campuses smarter every single day. Despite the benefits of these advanced technologies, the literature concerning the adoption of smart campuses is significantly lacking increased knowledge to provide effective smart campus solutions. This study aims to prioritize the adoption factors of an IoT-based smart campus. The study applied an analytical hierarchical process (AHP) on 25 factors drawn from the literature. The factors were classified into technology specific factors (TSF), organizational specific factors (OSF), environmental specific factors (ESF), and end-user specific factors (USF). Based on the results obtained, the most significant contributing factors were government support, privacy concerns, social influence, facilitating conditions, and service collaboration, whereas the least significant contributing factors were enjoyment, availability, reliability, mobility, and compatibility. Moreover, based on the global ranking computation, 12 factors from the OSF, ESF, and USF categories appeared to be more significant than TSF. The findings of this study could help university administrators, manufacturers, and policy-makers to understand the critical factors of smart campuses in order to improve the adoption and utilization of these solutions effectively.