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The paper explores how social networks influence Cameroonian consumers' buying behavior. Then, the authors examine customers' advertising perceptions and psychological dispositions to explain their purchase intention and behavioral consumption.

The research framework is developed based on Nelson's theory of advertising by studying advertising perceptions, consumer psychological dispositions associated with social network characteristics and behavioral consumption. Using partial least squares structural equation modeling (PLS-SEM), the validation takes support from 231 responses collected with an online questionnaire from Cameroun.

The study reveals three critical results: (1) consumers' perceptions of advertising significantly influence their psychological disposition, (2) consumers' psychological dispositions and the social network significantly influence their intention to purchase and (3) consumers' intention to purchase significantly impacts their behavioral consumption.

The proposed and validated model contributes to understanding the influence of social network communication on customers' buying behavior on social s-Commerce platforms of developing country enterprises.

The interview documents early days in the field of disaster risk reduction.

The transcript and video were developed in the context of a United Nations Office for Disaster Risk Reduction (UNDRR) project on the History of DRR.

The transcript presents important developments during the 1980s with valuable lessons about risk reduction.

It takes the readers on a history of the journey of DRR over three decades.

Prediction is a critical task in targeted online advertising, where predictions better than random guessing can translate to real economic return. This study aims to use machine learning (ML) methods to identify individuals who respond well to certain linguistic styles/persuasion techniques based on Aristotle’s means of persuasion, rhetorical devices, cognitive theories and Cialdini’s principles, given their psychometric profile.

A total of 1,022 individuals took part in the survey; participants were asked to fill out the ten item personality measure questionnaire to capture personality traits and the dysfunctional attitude scale (DAS) to measure dysfunctional beliefs and cognitive vulnerabilities. ML classification models using participant profiling information as input were developed to predict the extent to which an individual was influenced by statements that contained different linguistic styles/persuasion techniques. Several ML algorithms were used including support vector machine, LightGBM and Auto-Sklearn to predict the effect of each technique given each individual’s profile (personality, belief system and demographic data).

The findings highlight the importance of incorporating emotion-based variables as model input in predicting the influence of textual statements with embedded persuasion techniques. Across all investigated models, the influence effect could be predicted with an accuracy ranging 53%–70%, indicating the importance of testing multiple ML algorithms in the development of a persuasive communication (PC) system. The classification ability of models was highest when predicting the response to statements using rhetorical devices and flattery persuasion techniques. Contrastingly, techniques such as authority or social proof were less predictable. Adding DAS scale features improved model performance, suggesting they may be important in modelling persuasion.

In this study, the survey was limited to English-speaking countries and largely Western society values. More work is needed to ascertain the efficacy of models for other populations, cultures and languages. Most PC efforts are targeted at groups such as users, clients, shoppers and voters with this study in the communication context of education – further research is required to explore the capability of predictive ML models in other contexts. Finally, long self-reported psychological questionnaires may not be suitable for real-world deployment and could be subject to bias, thus a simpler method needs to be devised to gather user profile data such as using a subset of the most predictive features.

The findings of this study indicate that leveraging richer profiling data in conjunction with ML approaches may assist in the development of enhanced persuasive systems. There are many applications such as online apps, digital advertising, recommendation systems, chatbots and e-commerce platforms which can benefit from integrating persuasion communication systems that tailor messaging to the individual – potentially translating into higher economic returns.

This study integrates sets of features that have heretofore not been used together in developing ML-based predictive models of PC. DAS scale data, which relate to dysfunctional beliefs and cognitive vulnerabilities, were assessed for their importance in identifying effective persuasion techniques. Additionally, the work compares a range of persuasion techniques that thus far have only been studied separately. This study also demonstrates the application of various ML methods in predicting the influence of linguistic styles/persuasion techniques within textual statements and show that a robust methodology comparing a range of ML algorithms is important in the discovery of a performant model.

Educational institutions are investing heavily in the internationalization of their campuses to attract global talent. Yet, highly skilled immigrants face persistent labor market challenges. We investigate how immigrant academics experience and mitigate their double precarity (migrant and academic) as they seek employment in higher education in Canada.

We take a phenomenological approach and draw on reflective interviews with nine immigrant academics, encouraging participants to elaborate on symbols and metaphors to describe their experiences.

We found that immigrant academics constitute a unique highly skilled precariat: a group of professionals with strong professional identities and attachments who face the dilemma of securing highly precarious employment (temporary, part-time and insecure) in a new academic environment or forgoing their professional attachment to seek stable employment in an alternate occupational sector. Long-term, stable and commensurate employment in Canadian higher education is out of reach due to credentialism. Those who stay the course risk deepening their precarity through multiple temporary engagements. Purposeful deskilling toward more stable employment that is disconnected from their previous educational and career accomplishments is a costly alternative in a situation of limited information and high uncertainty.

We bring into the conversation discussions of migrant precarity and academic precarity and draw on immigrant academics’ unique experiences and strategies to understand how this double precarization shapes their professional identities, mobility and work integration in Canadian higher education.

Digital tourism has drawn the attention of researchers around the globe. This study aims to assess the digital tourism experience for tourist site revisit from an emerging market perspective.

Anchored on the social cognitive theory, the study employed a quantitative method, using the convenience sampling to select 328 participants who responded to tourism and technology sharing items through an online questionnaire. The study's hypotheses were tested utilizing structural equation modelling.

The results suggest a significant influence of technology-based service innovativeness on service value, tourist site revisits and experience sharing through technology. Further, the findings also revealed the significant influence of service value on tourist site revisit and experience-sharing through technology.

This study was conducted with only clients or tourists, and this limits generalization of the study's findings.

The study offers the understanding of how tourist site operators and all stakeholders have to deploy new ways of technology-based service innovation to get maximum return on their investment in the hospitality industry.

The outcome of this research advanced the linkage between technology and tourism in context, which is important to policymakers and practitioners in the sector.

The authors revisit the notion of co-production, highlight more critical and re-politicized forms of co-production and introduce three principles for its operationalization. The paper’s viewpoint aims to find entry points for enabling more equitable disaster research and actions via co-production.

The authors draw insights from the authors’ reflections as climate and disaster researchers and literature on knowledge politics in the context of disaster and climate change, especially within critical disaster studies and feminist political ecology.

Disaster studies can better contribute to disaster risk reduction via political co-production and situating local and Indigenous knowledge at the center through three principles, i.e. ensuring knowledge plurality, surfacing norms and assumptions in knowledge production and driving actions that tackle existing knowledge (and broader sociopolitical) structures.

The authors draw out three principles to enable the political function of co-production based on firsthand experiences of working with local and Indigenous peoples and insights from a diverse set of co-production, feminist political ecology and critical disaster studies literature. Future research can observe how it can utilize these principles in its respective contexts.

This study aims at investigating the evolution of disaster management by identifying the different phases it has gone through over time, and laying a ground for the next generation of disaster studies that focus on value-creating and value-adding activities.

An extensive review of the existing literature was made to develop an understanding of the evolution of disaster management. This study does not aim at assessing the tools or techniques used; rather it aims at identifying the major developments that took place over time.

Disaster management is a dynamic process. It has encountered/experienced different evolutionary phases that indicate that it has been developing over time. It continues to evolve until today as long as disasters occur. The nature and complexity of disasters are also changing. Most importantly, what seemed to be a practical approach for managing disasters yesterday might not fit for the use of today or tomorrow.

Understanding the evolution of disaster management mirrors the evolution of mankind and the ways people survived major incidents. As life itself evolves, disasters will continue to evolve which subsequently triggers the need for broader management insight to cope with.

This study traces the evolution of disaster management and the development of research and practice in this field over time. The existing literature rarely addresses the uniqueness of individual disasters and the need to treat them differently even the recurrent ones. To the best of the author’s knowledge, there is no single study that attempted to capture the evolution of disaster management during the 20th century until today. This study aims to achieve this goal.

Equality is a basic human right. However, LGBTQ individuals often have their human rights violated because of their gender identity or sexual orientation. They also experience discrimination because of homophobic and transphobic attitudes. They frequently deal with derisive attitudes at school, are discriminated against in the workplace and struggle to access health services. This paper aims to determine the discriminatory attitudes of nurses in their social and professional lives toward LGBTQ individuals.

This study involved 503 nurses and used a questionnaire to examine their views regarding members of the LGBTQ community. The questionnaire consisted of 24 questions. Ten experts from the fields of social psychology, sociology, and nursing provided the necessary inputs, which were subsequently incorporated into the questionnaire.

The nurses were found to have a negative attitude toward LGBTQ individuals; they felt that they should not be allowed to live in comfort in Turkey and that they disrupted the social order and compromised public morality. It was observed that married (in general), male (in particular), and have fewer nursing education nurses are much more likely to have a discriminatory attitude toward LGBTQ people, and they were more discriminatory in their society rather than in their professional lives.

According to the principles of justice and equality, which are a prominent part of the nursing code of ethics – “With the awareness that all people have equal rights, the nurse serves regardless of race, language, religion, age, gender, belief, social and economic status and political opinion” – nurses should not have a discriminatory attitude. This study reveals the inequality and the ethical problems that riddle Turkey’s health sector.