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This paper aims to describe the phenomenon of multiple simultaneous un/natural disasters (MSDs). This study also aims to describe the importance and contribution of philosophy in describing MSDs warning and alarming systems.

The paper summarizes topics in the philosophy of MSDs that were covered in detail in previous research in order to continue with the topic of the philosophy of MSDs alarming and warning. A practical solution to conceptual paradoxes is researched by means of conceptual-morphological analysis.

The paper proposes a conceptual idea for MSDs alarming system which is its main topic; namely, it offers a conceptual solution to a series of practical-conceptual paradoxes that occur before, during and after MSDs.

This is only a conceptual research, and it does not deal with particular technological solutions.

The proposed solution of this research could be implemented in various warning and alarm systems.

The proposed concept of a universal alarm system for MSDs was not previously proposed.

This paper aims to provide a general overview of the international Tsunami warning system mandated by the United Nations, particularly on cataloging past studies and a strategic focus in the Indian Ocean, particularly on the Bay of Bengal region.

Present research assimilates the secondary non-classified data on the Tsunami warning system installed in the Indian Ocean. Qualitative review and exploratory research methodology have been followed to provide a holistic profile of the Tsunami rarly warning system (TEWS) and its role in coastal resilience.

The study finds the need for strategic focus to expand and interlink regional early warning cooperation mechanisms and partnerships to enhance capacities through cooperation and international assistance and mobilize resources necessary to maintain the TEWS in the Indian Ocean region. The enhanced capacity of the TEWS certainly improves the resilience of Indian Ocean coastal communities and infrastructures.

The study is original research and useful for policy planning and regional cooperation on data interlinkages for effective TEWS in the Indian Ocean region.

The purpose of the study is to evaluate the severity of public events in real time from the perspective of social media and to construct the early warning mechanism of public events.

This study constructed the severity assessment system of public events from the dimensions of the netizens' role, the Internet media's role, the spread of public events and the attitudes and feelings of netizens. The method of analyzing the influence tendency of the public event severity indicators was proposed. A total of 1,107,308 microblogging entries regarding four public events were investigated. The severity of public events was divided into four levels.

It is found that serious public events have higher indicator values than medium level events on the microblogging platform. A quantitative severity classification standard for public events was established and the early warning mechanism of public events was built.

Microblogging and other social media platforms provide rich clues for the real-time study and judgment of public events. This study only investigated the Weibo platform as the data source. Other social media platforms can also be considered in future.

Different from the ex-post evaluation method of judging the severity of public events based on their physical loss, this study constructed a quantitative method to dynamically determine the severity of public events according to the clues reflected by social media. The results can help the emergency management departments judge the severity of public events objectively and reduce the subjective negligence and misjudgment.

The purpose of this pilot study was to evaluate an online mental health literacy training program for college female mentors.

Undergraduate female participants (n = 10) completed in asynchronous mental health literacy training. Participants completed the Heads Up Checkup (HCU) and mental health literacy scale (MHLS). Participant usage data were collected for the training course and analyzed using means and standard deviations. Qualitative data were analyzed by axial coding and thematic categorization.

The mean MHLS score, based on mean (M) and standard deviation (SD), was high for the participants (M = 145.69, SD = 8.41). Six qualitative themes from the training effectiveness feedback were used: (1) help-seeking, (2) stress management, (3) tailored guidance to resources, (4) understanding warning signs, (5) body image awareness and (6) engaging with mentees.

There are a few limitations to this study including the small sample size, unrestricted time frame for completion of the asynchronous training and the need for long-term follow-up of the intervention effects.

This pilot study provides initial support for the mental health literacy training program when implemented with undergraduate females.

Given inadequate mental health literacy in college females regarding such topics, continually training undergraduates about these warning signs is necessary. Future research could consider implementing this program with all gender identities, various age groups and in both synchronous and asynchronous modalities. This program could also be replicated using a pre- and post-test design to evaluate direct impact of the training on outcome variables.

All the participants discussed how the training prepared them in aiding mentees in help-seeking and identifying appropriate mental health resources. Participants also indicated how the training enabled personal and others-oriented stress management, which supports a mental health literacy training program that reduced stress in medical students.

This paper aims to develop a crisis readiness framework for road traffic crisis response for law enforcement agencies in the United Arab Emirates (UAE).

A Delphi method was used that combined questionnaire-based survey and the analytical hierarchy process to collect quantitative and qualitative data from an expert panel of crisis readiness professionals on how they prioritise and weigh the different strategic criteria, sub-criteria and performance indicators in the context of law enforcement agencies’ traffic response.

The findings of this paper resulted in the identification, ranking and validation of ten key dimensions of crisis readiness clustered into three distinct sets of priority rankings: response planning, resources, training and coordination; information management and communication and risk and hazard assessment; and early warning, legal and institutional frameworks, recovery initiation and property protection. The results additionally established the relative priority of sub-criteria for each criterion and validated a broad set of key performance indicators (KPIs) for the top six ranked criteria.

The findings are based on a single case study focused on a specific area of operation within crisis response and one group of organisations of the UAE police sector. This potentially places a constraint on the wider generalisation of the findings to different operational areas and agencies, as they may have different priorities or organisational conditions that have implications for the framework application and the relative importance of certain criteria and sub-criteria.

This paper provides strategic guidance in the form of a prioritised list of criteria, sub-criteria and KPIs that can direct efforts to optimise different dimensions of crisis readiness at a strategic and operational level.

This paper makes an original contribution in identifying the key criteria and performance indicators of crisis readiness for road traffic situations. The findings contribute a comprehensive strategic readiness framework that supports planning and decision-making for the development of organisational capacities that can enhance response times of police to road traffic crises. This framework ranks dimensions of crisis readiness and key sub-criteria in order of priority and validates the key components of crisis readiness that can support practitioners to structure, standardise and benchmark key processes and elements of crisis response.

While there has been a growing call for insights on algorithms given their impact on what people encounter on social media, it remains unknown how enhanced algorithmic knowledge serves as a countermeasure to problematic information flow. To fill this gap, this study aims to investigate how algorithmic knowledge predicts people's attitudes and behaviors regarding misinformation through the lens of the third-person effect.

Four national surveys in the USA (N = 1,415), the UK (N = 1,435), South Korea (N = 1,798) and Mexico (N = 784) were conducted between April and September 2021. The survey questionnaire measured algorithmic knowledge, perceived influence of misinformation on self and others, intention to take corrective actions, support for government regulation and content moderation. Collected data were analyzed using multigroup SEM.

Results indicate that algorithmic knowledge was associated with presumed influence of misinformation on self and others to different degrees. Presumed media influence on self was a strong predictor of intention to take actions to correct misinformation, while presumed media influence on others was a strong predictor of support for government-led platform regulation and platform-led content moderation. There were nuanced but noteworthy differences in the link between presumed media influence and behavioral responses across the four countries studied.

These findings are relevant for grasping the role of algorithmic knowledge in countering rampant misinformation on social media, as well as for expanding US-centered extant literature by elucidating the distinctive views regarding social media algorithms and misinformation in four countries.

This study aims to explore the switching behaviour of short video (SV) users and its influencing factors and promote the sustainable development of SV platforms (SVPs) and the marketing strategy formulation of library and information institutions.

Using the qualitative research method of semi-structured interviews and grounded theory, this study conducts an exploratory study on the user switching phenomenon of an SVP. The authors encoded the interview text at three levels, extracted the factors influencing user switching behaviour on an SVP and constructed the corresponding theoretical model.

This study identifies the following major internal and external factors influencing user switching behaviour of SVP: platform quality, social environment, individual characteristics and use needs. It also elaborates on the impact of these internal and external factors on user switching behaviour.

This study explored the factors influencing SV user switching behaviour and constructed corresponding theoretical models, enriching research in information technology and social media switching. In practice, this study helped the existing SVPs and library and information institutions establish a corresponding early warning mechanism to prevent the loss of existing users and attract new users.

Expanding on the real-world financial market framework and considering the current market turmoil, with cryptocurrencies (where contracts for difference (CFDs) are extremely common) (Hasso et al., 2019) displaying unprecedented volatility, the authors aim to test in an online laboratory setting whether displaying a risk warning message is truly effective in reducing the level of risk taken and whether the placement of this method makes a difference.

To explore the impact of risk disclosure framing on risk-taking behavior, the authors conducted an online pair-wise lottery choice experiment. In addition to manipulating risk awareness through the presence or absence of risk warning messages of varying intensity, the authors also considered dynamic inconsistency, cognitive ability and questionnaire-based financial risk tolerance (FRT) scores. The authors aimed to identify potential relationships between these variables and experimentally elicited risk aversion. The authors' study offers valuable insights into the complex nature of risky decision-making and sheds light on the importance of considering dynamic inconsistency in addition to risk awareness and aversion.

The authors' results provide statistical evidence for the efficacy of informative and very salient messages in mitigating risky decision, hinting at several policy implications. The authors also provide some statistical evidence in support of the relationship between cognitive abilities and risk preferences. The authors detect that individual with low cognitive abilities scores display great risk aversion.

This study investigates the impact of risk warning messages on investment decisions in an online laboratory setting – a unique approach. However, the authors go beyond this and also examine the potential influence of dynamic inconsistency on decision-making, adding further value to the literature on this topic. To ensure a comprehensive understanding of the participants, the authors collect data on cognitive ability and FRT using questionnaires. This study provides a simple and cost-effective framework that can be easily replicated in future research – a valuable contribution to the field.

Plagiarism has been on the rise, mainly because of increased access to the internet and digital sources. To combat the threat of plagiarism, various universities have implemented countermeasures such as capacity building, anti-plagiarism policies and the purchase of anti-plagiarism software. In Kenya, there appears to be a lack of cohesion among universities in combating plagiarism, a situation that threatens teaching, learning and research if not addressed adequately. This paper aims to review and identify anti-plagiarism practices in Kenyan universities; it further proposed various best practices and policy actions that ought to be adopted to win the fight and the misperception of plagiarism.

This study adopted a mixed-method approach by surveying the librarians and interviewing the graduate school directors or deans to establish the strength and challenges in implementing plagiarism measures in the universities in Kenya. Before collecting data, the researcher checked the reliability of the tools by pretesting and readjusting the tools based on input from the participants.

This study established that most universities in Kenya appreciate the fact that plagiarism negatively affects the quality of teaching, learning and research. However, despite the fact that there is goodwill in the effort to combat plagiarism, there were no unified mechanisms, strategies and implementation policies in solving plagiarism issues among universities in Kenya. Different universities have adopted different strategies in terms of policy, software and capacity. Further, it was noted that the well-established/funded universities had clear stipulated mechanisms as opposed to the ill-funded universities with limited funding and budget.

This research provides an opportunity for universities to make an informed choice about the policies, required capacity and software to tackle plagiarism. The findings from the study will be used to improve the quality of academic writing and standardize procedures on plagiarism by proposing policy actions needed to maximize the benefits of the investments in this venture. This study recommends a collaborations approach among universities in the fight against plagiarism. Because the Kenya Library and Information Services Consortium already supports many university cooperation, they ought to take the initiative in formulating policy, choosing the appropriate software to use and developing the necessary ability in the battle against plagiarism.

To the best of the authors’ knowledge, this study is the first effort to evaluate the anti-plagiarism strategies being applied in different universities in Kenya. This study demonstrates the gaps and variations in university strategies in combating academic plagiarism. The findings can be applied to improve academic communication and indeed the quality of research output at other universities in Kenya and beyond.

This paper aims to study the role of self-concept in consumer relationships with anthropomorphised conversational artificially intelligent (AI) agents. First, the authors investigate how the self-congruence between consumer self-concept and AI and the integration of the conversational AI agent into consumer self-concept might influence such relationships. Second, the authors examine whether these links with self-concept have implications for mental well-being.

This study conducted in-depth interviews with 20 consumers who regularly use popular conversational AI agents for functional or emotional tasks. Based on a thematic analysis and an ideal-type analysis, this study derived a taxonomy of consumer–AI relationships, with self-congruence and self–AI integration as the two axes.

The findings unveil four different relationships that consumers forge with their conversational AI agents, which differ in self-congruence and self–AI integration. Both dimensions are prominent in replacement and committed relationships, where consumers rely on conversational AI agents for companionship and emotional tasks such as personal growth or as a means for overcoming past traumas. These two relationships carry well-being risks in terms of changing expectations that consumers seek to fulfil in human-to-human relationships. Conversely, in the functional relationship, the conversational AI agents are viewed as an important part of one’s professional performance; however, consumers maintain a low sense of self-congruence and distinguish themselves from the agent, also because of the fear of losing their sense of uniqueness and autonomy. Consumers in aspiring relationships rely on their agents for companionship to remedy social exclusion and loneliness, but feel this is prevented because of the agents’ technical limitations.

Although this study provides insights into the dynamics of consumer relationships with conversational AI agents, it comes with limitations. The sample of this study included users of conversational AI agents such as Siri, Google Assistant and Replika. However, future studies should also investigate other agents, such as ChatGPT. Moreover, the self-related processes studied here could be compared across public and private contexts. There is also a need to examine such complex relationships with longitudinal studies. Moreover, future research should explore how consumers’ self-concept could be negatively affected if the support provided by AI is withdrawn. Finally, this study reveals that in some cases, consumers are changing their expectations related to human-to-human relationships based on their interactions with conversational AI agents.

This study enables practitioners to identify specific anthropomorphic cues that can support the development of different types of consumer–AI relationships and to consider their consequences across a range of well-being aspects.

This research equips marketing scholars with a novel understanding of the role of self-concept in the relationships that consumers forge with popular conversational AI agents and the associated well-being implications.