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In recent years the movement of refugees has led to increasing negative media and political discourse about migration in the United Kingdom, particularly as the number of refugees crossing the English Channel has increased. Despite this hostility, little is known about how the UK public perceive the journeys made by refugees or the refugees themselves.

In this study the authors used a story completion method to analyse perceptions and understandings of refugees. Participants were given the opening of a story about refugees crossing the English Channel and were asked to complete the remainder of the story. In total, 84 participants completed stories that ranged in length from two to 423 words. The stories were analysed using reflexive thematic analysis.

Each of the completed stories was analysed using reflexive thematic analysis and three themes were generated: Conflicting emotions: Uncertainty and the relief of reaching safety after a traumatic journey; The spectre of illegality: Borders and the uncertainty of what happens next; and Welcome or unwelcome?: Cultural values of welcome and hospitality.

The authors argue that this original use of the story completion method highlights how participants draw on cultural narratives of hospitality and welcome and that their stories are constructed using emotional categories that are in contrast to the more binary constructions of refugees that are present in media and government discourse about refugees and the English Channel crossings.

The consumption of news from social media is the new trend, still news channels are the authentic source to transmit relevant news to audiences. Social media has gradually left an impact on the audience but the news channels have upgraded and providing various news services online on social media websites. The present study aims to study the type of news videos uploaded by the top five Hindi TV news channels on their YouTube channels with an aim to see which type of videos spark interest for YouTube viewers.

By applying the techniques of content analysis, sentiment analysis and text mining the study aims to measure the average sentiments, top words and the trend of selected popular terms in the comments on uploaded news videos by the top five Hindi news channels over a period of one year.

Results of the study indicate that the news channels are uploading more news videos about crime and investigation, politics, health and protests while uploading fewer news videos covering travel, science and technology, and religion. While the viewers of the participating news channels are more interested in giving their thoughts or opinions in the form of comments on news videos concerning crime, politics, protests and health or that these videos inspire conversation on YouTube.

The findings might be of interest to content managers of news channels to understand the interest of their audience.

The study's distinctiveness resides in the approach utilised to collect data and analyse the results in order to better understand the online behaviour of news channel audiences.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-01-2022-0007

This study explores the impacts of Covid-19 on the performance of firms operating in different industries, and further discovers suspected impacting channels through which Covid-19 is significantly associated with firm performance.

A dataset of 402 listed firms from 2017Q1 to 2021Q4 is proceeded with high dimensional fixed effect (firm-quarter fixed effects) models and difference-in-difference models supported by propensity score matching. A thorough robustness testing procedure with a falsification test with a hypothetical event is applied.

The study asserts that the pandemic has remarkably hurt the businesses in industries that are more vulnerable to the coronavirus and governmental response policies. Adding to the confirmation of sales and expense channels, new channels – competition and short-term receivables –through which the negative impact of the pandemic is passed on firms is also examined.

First, this study is to be the first comprehensively investigate and affirm the varying impact of Covid-19 on the business performance of listed firms from different industries in Vietnam, providing additional insight into this research field in Vietnam and emerging economies. Second, the authors examine possible channels paving the way for the impact of Covid-19 on firms' performance and especially explore new channels associated with competition and short receivables. Third, the findings help to form the recommendations for Vietnamese firms, and the study could be replicated for other emerging countries under other similar infectious diseases-driven crises.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2023-0072

Drawing on dynamic capability theory, this study investigates how online–offline channel integration (OOCI) affects a firm's supply chain resilience and how such an effect is moderated by market turbulence and regulatory uncertainty.

A sample of 273 Chinese firms that conduct online and offline business and hierarchical regression analysis were used to examine the research model.

The results suggest that the effect of OOCI on supply chain resilience differs in terms of its dimensions (i.e. information integration, transaction integration and service integration). While information integration and service integration were positively associated with supply chain resilience, transaction integration had a non-significant relationship with supply chain resilience. Moreover, market turbulence negatively moderated the effect of transaction integration and positively moderated the effect of service integration. Regulatory uncertainty positively moderated the effect of transaction integration and negatively moderated the effect of service integration. Implications and suggestions for future research are discussed.

This study examines the effect of OOCI on supply chain resilience. It further explores the influence of market turbulence and regulatory uncertainty on the relationship between OOCI and supply chain resilience.

The purpose of this study is to document and analyze the success story of YouTube as a social network site in a competitive market, offering important academic and managerial implications.

Historical methods were used for investigation. This study applies the Resource-Advantage theory to identify key events in the history of YouTube from archival documents and evaluates and synthesizes the evidence to recount the channel’s evolution.

YouTube faced challenges from competitors across various industries since its launch. It has used its global user base and technological skills to develop innovative market offerings for users, contributors and marketers. YouTube built long-term relationships with stakeholders, continuously adapted to external changes and initiated internal alignments to compete in multiple industries. Over time, despite several changes in the competitive landscape, YouTube has grown into a successful media firm, competing across traditional broadcasting, gaming, live TV streaming and SNS industries. It is an exciting tale in the history of social networking.

This study significantly contributes to the marketing history of social network sites and platform-specific scholarship by applying the Resource-Advantage theory to document the evolution of YouTube.

Guided by the Comprehensive Model of Information Seeking (CMIS), this article identifies significant predictors that impact individuals seeking COVID-19 information. People with different political ideologies read contradictory information about the COVID-19 pandemic. However, how political ideology may affect COVID-19 information seeking remains unclear. This study explores the major information channels for individuals with different political ideologies to seek COVID-19 information. It further examines how political ideologies influence CMIS's effectiveness in predicting online health information-seeking.

This study collected 394 completed survey responses from adults living in the United States after the 2020 lockdown. ANOVA analyses revealed the differences in salience, beliefs, information carrier characteristics, utilities and information-seeking actions between Liberals and Conservatives. Regression analyses discovered variables that predict Liberals' and Conservatives' online health information seeking.

Results suggest that the internet is the top channel for COVID-19 information seeking. Compared to Conservatives, Liberals report more COVID-19 information-seeking actions. Liberals also express stronger salience, perceive higher trustworthiness of online COVID-19 information, are more likely to think of seeking online COVID-19 information as useful and helpful and report more substantial efficacy to mitigate the risk. Most CMIS variables predict Liberals' information seeking; however, only salience significantly predicts Conservatives' information seeking.

This article indicates that CMIS should include political ideology to refine its prediction of information seeking. These findings offer practical implications for designing health messages, enhancing information distribution and reducing the public's uncertainty.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-08-2022-0436.

This paper aims to study the synergistic lubrication effects of Sn–Ag–Cu and MXene–Ti₃C₂ to improve the tribological properties of M50 bearing steel with microporous channels.

M50 matrix self-lubricating composites (MMSC) were designed and prepared by filling Sn–Ag–Cu and MXene–Ti₃C₂ in the microporous channels of M50 bearing steel. The tribology performance testing of as-prepared samples was executed with a multifunction tribometer. The optimum hole size and lubricant content, as well as self-lubricating mechanism of MMSC, were studied.

The tribological properties of MMSC are strongly dependent on the synergistic lubrication effect of MXene–Ti₃C₂ and Sn–Ag–Cu. When the hole size of microchannel is 1 mm and the content of MXene–Ti₃C₂ in mixed lubricant is 4 wt.%, MMSC shows the lowest friction coefficient and wear rate. The Sn–Ag–Cu and MXene–Ti₃C₂ are extruded from the microporous channels and spread to the friction interface, and a relatively complete lubricating film is formed at the friction interface. Meanwhile, the synergistic lubrication of Sn–Ag–Cu and MXene–Ti₃C₂ can improve the stability of the lubricating film, thus the excellent tribological property of MMSC is obtained.

The results help in deep understanding of the synergistic lubrication effects of Sn–Ag–Cu and MXene–Ti₃C₂ on the tribological properties of M50 bearing steel. This work also provides a useful reference for the tribological design of mechanical components by combining surface texture with solid lubrication.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0381/

Considering the emergence of e-commerce platforms and their integration into marketing channels, this paper aims to investigate how artificial intelligence (AI) resources – both technological and human – possessed by e-commerce platforms can enhance their channel power by acquiring market-based assets (relational and intellectual).

Based on resource-based theory and resource orchestration theory, the authors developed a framework tested using survey data gathered from the sellers, which incorporated six key variables: the e-commerce platform’s AI technology resources and human resources, rational and intellectual market-based assets, intraplatform competition and channel power. The analyses are performed using the regression analysis technique.

The empirical findings indicate that both technological and human AI resources are crucial in building channel power. In addition, market-based assets serve as a mediator in this relationship, while intraplatform competition moderates the effect of intellectual market-based assets on channel power negatively.

This study contributes to the existing literature by exploring how e-commerce platforms’ AI resources affect their channel power. The results offer valuable guidance to managers and researchers on optimizing AI resources to improve channel power.

The purpose of this study is to explore the information-seeking behavior of Egyptian physicians serving in COVID-19 isolation hospitals.

A sample of 91 physicians serving in Egyptian isolation hospitals answered the study questionnaire.

Demographically, more than half of respondents were males. Over one-third of them are holding Doctor of Medicine (M.D), followed by one-third holding Master of Medicine (MMed). Respondents' age ranged from 30 to 60 years. Internal medicine is the most common specialty, accounting for nearly half of all physicians, followed by chest medicine and intensive care medicine. The information-seeking behavior of these three groups in their regular work is believed to be different, but since all of the participants are working in COVID-19 isolation hospitals, they should have the same information resources, Internet access and the same needs relevant to COVID-19 in order to make accurate clinical decisions. The physicians used traditional and electronic information sources to fulfill their information needs, the most important of which were to make a specific research, find an answer to a specific case, and deliver a medical lecture. Colleagues, coworkers, nurses and pharmacists were the most important channels pursued by Egyptian physicians to obtain information.

This study is the first study that focuses on investigating the information-seeking behavior of Egyptian physicians serving in isolation hospitals. Any findings resulted from this study may serve as a noteworthy reference that may be useful to the Egyptian health sector, experts, researchers, as well as policymakers in establishing strategic decisions for making the understating much better.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-08-2020-0350

This study aims to investigate the psychological mediating mechanisms through which omnichannel integration affects customer word-of-mouth (WOM) behaviors in omnichannel retailing.

Guided by prior omnichannel retailing studies, the authors identify taxonomy of customer WOM behaviors with three archetypes, namely, face-to-face WOM, online store WOM, and social media WOM. Then, the authors draw on social exchange theory (SET) to explain how omnichannel integration influences customer WOM behaviors through the mediating roles of perceived personal preference fit and perceived social relatedness. The authors empirically tested the model using structural equation modeling and multiple mediation analysis with a field survey of 335 omnichannel customers.

Perceived personal preference fit positively influences face-to-face WOM and social media WOM, whereas perceived social relatedness is positively associated with face-to-face WOM, online store WOM, and social media WOM. Furthermore, transactional integration and relational integration positively affect perceived personal preference fit, whereas relational integration has a positive effect on perceived social relatedness. Finally, perceived personal preference fit mediates the effects of transactional integration and relational integration on face-to-face WOM and social media WOM. Perceived social relatedness mediates the effects of relational integration on face-to-face WOM, online store WOM, and social media WOM.

The authors' study advances the omnichannel retailing literature by proposing a taxonomy of customer WOM behaviors in omnichannel retailing and identifying the mediating mechanisms through which omnichannel integration influences customer WOM behaviors.