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This study aimed to find out the web content accessed by university students and to compare the level of interaction with real-life friends and online friends.

In this study, the quantitative research design used, and the researcher collected data through the survey method. The population comprises all undergraduate students at the University of the Punjab, Lahore. The sample of 320 students, age ranges from 18 to 22 years from eight selected departments, collected through a simple random sampling technique and after extraction 284 questionnaires evaluated by using Statistical Package for Social Sciences (SPSS).

The findings of the study showed that students preferred activities on the Internet is to access social networking sites. Additionally, the mobile phone is the most commonly used device among university students to access the Internet. Furthermore, students mostly used Facebook to keep in touch with their old friends and talk on different topics more easily with their online friends as compared to real-life friends. The study also shows that the results of both the hypothesis are significant; therefore, no difference exists regarding time spent on the Internet in real-life friendship patterns and online friendship patterns.

The research was used to find out the difference between the online friendship and real-life friendship patterns of the two groups who use the Internet for less time and who spend more time on the Internet among the university students.

The study examines how the technical features and associated social practices of an anonymous, text-based online forum intended for young people make it a unique platform for acquiring and sharing health information among peers.

The features and content of a young people's section of a popular Finnish discussion forum were examined with a focus on health-related threads. Observational notes and thread content were analysed with a focus on the forum's affordances for health information practices.

The findings indicate that the forum's affordances including anonymity, persistence, searchability, cohesion and tolerance enabled the pooling of peer experiences, opinions and experience-based advice on health, rather than sharing factual information or embracing reciprocal discussion. As such, instead of competing for a cognitive authority position with medical authorities or offering emotional support like tight online support communities, the anonymous forum served as a platform for young people to gain information on others' experiences and opinions on sensitive, mundane and disnormative health issues and for reflecting their own lived experiences to those of others.

The study is original in its approach to examining the affordances of an online platform for health information practices. It helps in understanding young people's ways of using different resources to meet their diverse health information needs and the value of gaining access to experiential health information.

The authors investigate the contributions of social capital (SC) dimensions (bridging, bonding and linking) in crowdfunding campaigns by comparing the dynamics of agri-food businesses with those of two other sectors – cultural and technological.

The authors develop linear regressions on a proprietary data set of 5,290 projects launched on the Italian platform “Produzionidalbasso.com”, from 2014 to 2020.

The authors’ findings suggest that combining the three social capital dimensions (bridging, bonding and linking) has a more substantial overall effect on the number of backers involved in agri-food projects than in cultural and technological projects. Agri-food entrepreneurs effectively mobilize all resources embedded in the SC dimensions and therefore create the conditions to develop new ties that financially support the project.

Agri-food entrepreneurs may benefit from those results improving their funding strategies. Therefore, agri-food entrepreneurs can explore and exploit the instruments available on the CFD platform – video and rewards associated with the campaign – gaining more benefit from the backers involved compared with other project categories.

The study proposes a broader perspective regarding SC that encompasses the proponent, the company and the campaign with three different types of ties: bonding, bridging and linking. These SC dimensions can differently shape diverse sectors and this eclectic configuration can differentiate the effects of SC in crowdfunding campaigns. This study pinpoints how crowdfunding determinants change, based on project categories.

This paper aims to examine a two-way interaction between social influencers’ number of followers (micro vs meso) and argument quality (weak vs strong) on consumers’ self-reported and brain responses to advertising posts on Instagram. Further, drawing upon source credibility theory and contemporary theories of persuasion, the Instagram users’ perceptions of the influencer’s credibility are predicted to mediate the hypothesized effects.

Through an online (N = 192) and a lab study (N = 112), the authors examined Instagram users’ responses to an advertising post from Instagram influencers in terms of perceived source credibility and electronic word-of-mouth intention, using validated multi-item scales from existing literatures and electroencephalogram (EEG) measures. The hypotheses were tested with a 2 (type of influencer: micro vs meso) × 2 (argument quality: weak vs strong) between-subject design using mediated moderated linear regression analysis.

The results highlight that meso-influencers are perceived as a credible source of information only when their product-related post provides strong argument quality. Moreover, this process involves an increase in users’ cognitive work (measured with EEG), with possible implications on marketing communication strategies and online message design.

The limitations of the work can serve as ideas for future research. First, this study did not account for the influencer’s relevance and resonance. Second, the authors studied consumer responses to online communication produced by Instagram influencers within a single product category. Another important product type distinction that requires further attention is between hedonic and utilitarian products. Finally, the two studies only used positive review content. Further research should study how consumers evaluate the source credibility of a micro- vs meso-influencer when they are exposed to negative reviews containing weak vs strong arguments.

The results suggest that marketers should carefully consider Instagram influencers based on the trade-offs between credibility and reach. Specifically, micro-influencers are perceived as more credible sources of information than meso-influencers, which means that they have greater potential to affect Instagram users’ behavior. Moreover, the results suggest that meso-influencers should leverage argument quality to enhance their credibility and draw greater positive outcomes for the products and brands they endorse.

To the best of the authors’ knowledge, this study is the first to investigate how the interaction between the type of social media influencer and the argument quality affects consumers’ self-reported and brain responses to advertising posts on Instagram. Moreover, using neuroscience, this study aims to shed light on the neurophysiological processes that drive consumer responses to product-related communication posted by different influencer types.

Advances in Big Data, artificial Intelligence and data-driven innovation bring enormous benefits for the overall society and for different sectors. By contrast, their misuse can lead to data workflows bypassing the intent of privacy and data protection law, as well as of ethical mandates. It may be referred to as the ‘creep factor’ of Big Data, and needs to be tackled right away, especially considering that we are moving towards the ‘datafication’ of society, where devices to capture, collect, store and process data are becoming ever-cheaper and faster, whilst the computational power is continuously increasing. If using Big Data in truly anonymisable ways, within an ethically sound and societally focussed framework, is capable of acting as an enabler of sustainable development, using Big Data outside such a framework poses a number of threats, potential hurdles and multiple ethical challenges. Some examples are the impact on privacy caused by new surveillance tools and data gathering techniques, including also group privacy, high-tech profiling, automated decision making and discriminatory practices. In our society, everything can be given a score and critical life changing opportunities are increasingly determined by such scoring systems, often obtained through secret predictive algorithms applied to data to determine who has value. It is therefore essential to guarantee the fairness and accurateness of such scoring systems and that the decisions relying upon them are realised in a legal and ethical manner, avoiding the risk of stigmatisation capable of affecting individuals’ opportunities. Likewise, it is necessary to prevent the so-called ‘social cooling’. This represents the long-term negative side effects of the data-driven innovation, in particular of such scoring systems and of the reputation economy. It is reflected in terms, for instance, of self-censorship, risk-aversion and lack of exercise of free speech generated by increasingly intrusive Big Data practices lacking an ethical foundation. Another key ethics dimension pertains to human-data interaction in Internet of Things (IoT) environments, which is increasing the volume of data collected, the speed of the process and the variety of data sources. It is urgent to further investigate aspects like the ‘ownership’ of data and other hurdles, especially considering that the regulatory landscape is developing at a much slower pace than IoT and the evolution of Big Data technologies. These are only some examples of the issues and consequences that Big Data raise, which require adequate measures in response to the ‘data trust deficit’, moving not towards the prohibition of the collection of data but rather towards the identification and prohibition of their misuse and unfair behaviours and treatments, once government and companies have such data. At the same time, the debate should further investigate ‘data altruism’, deepening how the increasing amounts of data in our society can be concretely used for public good and the best implementation modalities.

The purpose of the study is to examine the use of alternative information in bank lending to small and medium enterprises (SMEs). Understanding alternative information and its use in bank lending to SMEs is important because it has become a growing part of the future of SME finance. The results and findings of my study not only enrich the finance literature but, more importantly, also address the use of Fintech in the risk management of SME lending, a new and complex problem that is specific to both the information technology and finance field.

To answer the research question, the author used a case study approach that relies upon qualitative data and analysis. By iterating between the existing literature, theoretical pieces and empirical findings, the author explain and interpret in detail how the use of alternative information impacts loan outcomes and develop insights to guide future research.

The case is outlined in two time periods including the prepartnership period and the postpartnership period. It highlights the establishment of a partnership between LoanBank and FintechInc (pseudonym), aimed at SME-focused Fintech lending. The findings underscore how the partnership has enabled a mutually beneficial situation where LoanBank and FintechInc leverage each other’s strengths to provide efficient and effective lending services. The adoption of alternative information in the risk management Fintech (RMF) platform of FintechInc has transformed LoanBank’s lending processes, showcasing how technological innovations can enhance SME lending practices.

The study’s originality mainly lies in the three detailed insights regarding alternative information’s impact on SME lending: information, platform properties and financial inclusion. The information part demonstrates that RMF platforms expand the information used for lending decisions, shifting from traditional hard and soft data to incorporating various alternative information sources. The platform properties part suggests that location, openness and technology also play a pivotal role in shaping lending outcomes. Finally, the financial inclusion part proposes that the use of alternative information has the potential to improve financial inclusion and offer better credit terms to previously underserved borrowers.