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The 2019 Global Assessment Report on Disaster Risk Reduction (GAR) cites earthquakes as the most damaging natural hazard globally, causing billions of dollars of damage and killing thousands of people. Earthquakes have the potential to drastically impact physical, social and economic landscapes; to reduce this risk, earthquake early warning (EEW) systems have been developed. However, these technical EEW systems do not operate in a vacuum; the inequities in social systems, along with the needs of diverse populations, must be considered when developing these systems and their associated communication campaigns.

This article reviews aspects of social vulnerability as they relate to ShakeAlert, the EEW system for the USA. The authors identified two theories (relationship management theory and mute group theory) to inform self-reflective questions for agencies managing campaigns for EEW systems, which can assist in the development of more inclusive communication practices. Finally, the authors suggest this work contributes to important conversations about diversity, equity and inclusion (DEI) issues within early warning systems and earthquake preparedness campaigns in general.

To increase inclusivity, Macnamara (2012) argues that self-reflective questioning while analyzing perspective, philosophy and approaches for a campaign can help. Specific to EEW campaigns, developers may find self-reflective questions a useful approach to increase inclusion. These questions are guided by two theories and are explored in the paper.

Several research limitations exist. First, this work explores two theories to develop a combined theoretical model for self-reflective questions. Further research is required to determine if this approach and the combination of these two theories have adequately informed the development of the reflective questions.

The authors could find little peer-reviewed work examining DEI for EEW systems, and ShakeAlert in particular. While articles on early warning systems exist that explore aspects of this, EEW and ShakeAlert, with its very limited time frames for warnings, creates unique challenges.

This paper aims to investigate seven prominent translations of the Qur'anic verb-noun collocations into English (Pickthall, 1930; AL-Hilali and Khan, 1977; Ali, 1934; Arberry, 1955; Shakir, 1999; Sarwar, 1981; Saheeh International, 1997) to unfold their renditions of the style and meaning of such Qur'anic verb-noun collocation into English.

The study follows a corpus-based research in a sense that the study is conducted on seven translations of the Noble Qur'an that have been taken form The Qur'anic Arabic Corpus, using linguistic and exegetical analyses. Based on Reiss’ model of text analysis (2000), the author analyses the intralinguistic and extralinguistic features of the Qur'anic verb-noun collocations.

Findings reveal that linguistic and exegetical analyses are perquisites for adequate rendition, which prevent deviation in meaning and translation loss. It is also found that Qur'anic collocations use unique literary techniques and devices, which hinder their natural and adequate renditions into English.

The novelty of this study lies in studying the architectural design of the Qur'anic verb-noun collocations in terms of the unique selection of words and style. Such unique architectural design of such collocations creates monumental hindrances in their rendition into other languages, which have not been given due attention in translation studies.

The performance of financial markets is significantly influenced by the political environment during general elections. This study investigates the effect of general elections on stock market performance in selected African markets.

Prior studies have been inconsistent in determining whether electioneering events negatively or positively influence stock market performance. The study utilized panel data set with annual observations from 1990 to 2020. The generalized method of moments (GMM) is employed to investigate the effect of electioneering and change in government on key stock market performance indicators, including stock market capitalization, stock market turnover ratio and the value of stock traded.

The study finds that electioneering activities generally have a positive impact on the performance of the stock market, whereas a change in government has a negative impact. As a result, the study recommends that stakeholders of the stock market remain vigilant and actively monitor electioneering events to devise and implement effective policies aimed at mitigating political risks during general elections. By adopting these measures, investor confidence can be significantly enhanced, fostering a more robust and secure investment environment.

The study investigates a neglected section of the literature by highlighting not only the effect of elections on stock market indicators but also possible change in government during elections.

In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.

Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.

The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.

The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.

This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.

This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.

Despite to useful relevance to better understand how group-level identity develops, few studies have explored the identity theory in the esports field and, in particular, considering the impact of a fan's role identity. The current study aims to explore esports fan role-identity vis-à-vis the relationship with the sponsor and the sponsee so as to understand the effects on their behavioral intentions.

Using a sample of 356 esports fans who attended the 2021 FPF eFootball Open Challenge, a Confirmatory Factor Analysis (CFA) analyzed the psychometric properties of the constructs and a subsequent Structural Equation Modeling (SEM) examined the effects of fan identity on two types of behavioral intentions and sponsor–sponsee relationship.

Results indicate that fans who highly identify with esports have the highest attachment to the event and tend toward having a positive word-of-mouth intention. Esports fans who have a higher brand identification reported a positive attitude toward the event's sponsor brand and tend to purchase its products. Moreover, the study findings also provide evidence of the bidirectional interaction between the way in which fans attach with the esports event and its sponsor brand, leading to greater reciprocity in their identity formation.

This study helps to understand how the fan identity process can enhance its fate and develop mutually, building role overlapping identity in the esports sponsor–sponsee relationship. Complementarily, it supports of how the marketeers and managers must analyze the importance of being a fan to the individual in order to understand how its self-identity can shape the future behavior.