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In recent decades, advances in technology have led to the adaptation of business models to the connected era. This has resulted in the modification of the goals of both startup and cooperative models, leading to the emergence of a new hybrid business model combining the two and known as cooperative startups. The present study aims to investigate the evolution, functioning and characteristics of cooperative startups as a potential research area that may be of future relevance due to its potential growth. To this end, a bibliometric analysis using Web of Sciences academic database and VOSViewer software is conducted to identify specific characteristics, opportunities, and challenges that cooperative startups should understand in order to achieve business success. In this regard, a co-citation analysis, bibliographic coupling and keyword concurrency analysis are computed to understand the literature published in this research field to date. The findings of this analysis contribute to the creation of knowledge on cooperative startups identifying 19 future research questions linked to 5 research categories in cooperatives startups: strategy, members of the team, performance, finance and economy and innovation. The results provide insights on the challenges and characteristics of this new business model that is characterized by the management of investments and economy democracy while boosting innovation and handling competence. Finally, theoretical and practical implications are presented. [ABSTRACT FROM AUTHOR]

With the advancement of technology, different approaches to make teachers' tasks more interactive and improve teacher teaching methodologies are becoming more and more common. Additionally, students must feel motivated and positively interact with these new methodologies. To understand these new initiatives, this paper aims to identify the adoption model of a game-focused student response system. To do so, the theoretical framework of the hedonic-motivation system adoption model was applied to Kahoot! which turns the classroom into a game show. For this purpose, a survey was designed, supported by a questionnaire administered to 214 students, applying a non-probabilistic convenience sampling to the students who decided to be evaluated by this method, together with the classic paper tests and the electronic tests on an e-learning platform. The results showed that the application of the hedonic motivation system adoption model is adequate for the adoption of a game-based student response system tool, and all relationships were significant except those related to the Temporal Dissociation variable. The results of this research can help the education sector to have a better acceptance of these kinds of tools in the classroom, and a better understanding of their functionalities. In general, the results of the present study contributed to the literature by identifying the important role of a game-based student response system tool in education. [ABSTRACT FROM AUTHOR]

Copyright of ESIC Market. Economic & Business Journal is the property of ESIC Business & Marketing School and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transformations in Business & Economics is the property of Vilnius University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The development of the Internet and the implementation of traditional marketing strategies have given rise to the emergence of digital marketing strategies exploited both by SMEs and large companies. These companies combine data sciences with digital marketing strategies to sell products, generate brand awareness, or access new markets. The present study aims to understand the role and use of data science by SMEs in their online marketing performance. The research method used in this study is a systematic literature review. The data were analyzed using multiple correspondence analysis (MCA) in the programming language R. Based on the results, we identify a total of seven state-of-the-art uses of data science in digital marketing used by SMEs in their online marketing strategies that are graphically represented and analyzed. In addition, four future lines of research are proposed and discussed to understand the direction of the next steps that SMEs should take to successfully develop their digital strategies. Finally, the review concludes with a discussion of the theoretical and practical implications of our findings for further research on the influence and use of data sciences in SMEs' online marketing performance. [ABSTRACT FROM AUTHOR]

In an increasingly competitive global market, companies have steadily increased their production, logistics, and innovation capacities. However, the ability to develop competitive advantages afforded by technology is becoming increasingly important. In the paradigm where competition and the speed of technological development grow exponentially, companies must be able to obtain a competitive advantage through the adoption of technologies that would allow them to improve their products, services, strategies, or production processes, among others. To this end, the present study aims to identify the characteristics of the technology to enable competitive advantages. This is achieved through a systematic review of the literature and analyzing its results with a statistical analysis known as Multiple Corresponds Analysis (MCA) developed in the R language. Based on the results, we identify four independent clusters linked to the characteristics of the technology to enable competitive advantages. The first of these clusters is focused on specialization, integration, compatibility, cost and scalability variables; the second includes flexibility, applicability, demand and innovation; the third is related to sustainability, productivity, energy and resources; finally, the fourth one is composed by complexity, utility and connectivity. The implications of the study show how the characteristics of the technology can be applied to enable competitive advantages. The paper concludes with a discussion of the stateof-the-art in relation to the characteristics of technology to enable competitive advantage and formulation of 30 future research questions to be explored in further research. [ABSTRACT FROM AUTHOR]

The present study aimed to analyse the main risks related to security and privacy of social networks based information systems in Industry 4.0. The methodology we used is an innovative exploratory data-driven process divided into three steps. First, we performed sentiment analysis to divide the database composed of 67, 206 tweets into feelings. Second, we applied a topic-modelling algorithm to extract topics. Third, we applied textual analysis to collect insights. A total of 10 topics related to security and privacy issues were identified as results. The paper concludes with a discussion of the challenges and main concerns related to the identified topics. [ABSTRACT FROM AUTHOR]