Ezgi Akar

Although cryptocurrencies and blockchain technology can be considered new advances, they have started to be recognized widely, and this has been discussed and investigated in lots of research studies. In parallel, the primary purpose of this study is to investigate the development and evolution of cryptocurrencies and blockchain technology over the past years in the academic world. To this end, 334 scholarly journal articles are examined to: (1) conduct a comprehensive literature review in the field of cryptocurrencies and blockchain; (2) identify the possible trends and changes in this field over the ten years; (3) compare the publishing productivity of journals; and (4) guide future research in this field. The results highlight that the researchers mainly concentrate on legal and ethical issues of them; their benefits, challenges, and risks; their conceptualization, evolution, and future; the economic dimension of them; and financial and accounting related issues of them.

Online communities are one of the powerful digital sources for businesses to analyze online users’ behavioral data. In this sense, it is important for practitioners to know how to motivate community members, to keep them amused and regularly engaged in the community. But, practitioners should be aware that different user types exist in online communities, and they should understand these members’ diverse needs to manage these communities successfully and to give a better service to their members. Concordantly, this study focuses on the problem of the existence of different user types in online communities and development of different strategies for their motivation, involvement, and communication. Unlike previous studies, this study considers theories across managerial and social domains, conducts social network analysis, and considers users’ contribution patterns in an online community to identify particular user types in an online community. The study also presents motivational strategies for practitioners to keep each type of users frequently amused in online communities.

Recently, it has been evident that the analysis of user data and content in online environments allows practitioners to understand how to motivate online community members and keep them frequently involved in the community, and so to manage these communities successfully. In this sense, practitioners should comprehend community members’ usage intentions to give a better service and to motivate them. However, different user types engage in such communities, so understanding their diverse needs is also essential for practitioners. In parallel, this article addresses the problem of the different user types existing in online communities, and each of them requires different strategies to be motivated and involved in the community. Thus, unlike previous studies, this study firstly identifies user roles in an online community based on the structural role theory, social network analysis, and community members’ contribution behavior. After that, it investigates members’ usage intentions based on the technology acceptance model and examines the moderating effect of identified user roles on their usage intentions. The study also guides practitioners to develop motivational strategies to keep each type of member continually satisfied.

There is a dynamic and interconnected international setting shaped by the power of the Internet and social media. To gain more consumers, understand their behaviours and needs, and maintain closest relationships with them, businesses should understand how consumers behave in social media and how they vary in their purchase intentions. In the scope of the study, we integrate the social network theory and the theory of planned behaviour to analyse online consumers’ purchase intentions and to investigate their structural positions by analysing their friendships in social networks. We target Twitter users to conduct analysis due to Twitter's popularity in use, market penetration, and opportunity to work with open-source data. This study contributes to a better theoretical understanding of online consumers’ purchase intentions by integrating multiple theoretical perspectives. It expands the literature by considering both online consumers’ friendship network in Twitter and their individual online purchasing intentions. The study also guides e-marketers to design proper strategies for potential and current consumers and target the right sets of people in the social networks.

Millions of people share photos, texts, videos, and other types of contents on various social networking sites in their daily lives. It indicates that there is an enormous amount of data generated by those people on the Internet and this data generation continues to grow fast. Businesses collect any data such as consumer preferences, purchases, or trends on the Internet to keep their strategies up-to-date, to take strategic precautions, and to satisfy their consumers. In this sense, this study aims to analyze trending topic data gathered from Twitter that is one of the most popular and publicly available social media data sources. In Twitter, more than 500 million tweets are shared per day, and some of them become trending ones. These trending topics have the power to keep people aware and entertained. This capability also provides e-marketers with a useful tool to get in front of a big and potential audience. In parallel, this study investigates 100 trending topics involving 301.492 tweets and 92.745 unique users, and it clusters these topics considering user-related factors. Thus, this research shows a way for e-marketers how to make a trending topic and to reach new audiences through social networking platforms.

Cloud computing is an upcoming technology and emerging concept in the field of information technologies. Companies have begun to invest in cloud computing with the expectation that it will improve their business performances, operations, and processes. However, many companies are not so much aware of the cloud computing, so they can hesitate to adopt this new technology. The aims of the study are analyzing factors affecting the adoption of cloud computing and applying structural equation modeling technique to analyze the important dimensions of the adoption. Concordantly, previous studies are examined and expert interviews are arranged. Based on both our literature review and expert interviews, a model is proposed to measure the adoption of cloud computing. It is obvious that there are scarce researches about cloud computing adoption in the literature. Thus, the originality of the paper lies on that it proposes a research model for cloud computing adoption and it investigates various dimensions of cloud computing adoption in detail.

Cloud computing is a new and upcoming technology. It is also a new business model for companies. Cloud computing enables companies to buy their technological need what if it is needed and they only pay for the amount that they used. There are many factors that affect the adoption of cloud computing. This study examines previous studies related to cloud computing adoption and presents a new model and new factors according to both literature and interviews with cloud computing experts and cloud service providers. Study model also includes potential relationships between these factors.