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Academic literature and news media on young people’s activism predominantly champions young people who align with liberal or progressive values, evident most recently in the youth-led climate strikes around the world. Research is often undertaken by scholars who see their work as advocacy for children and young people, countering deficit-based depictions of politically disengaged or ill-informed youth. Yet, this scholarship rarely includes young people whose forms of political activism align with conservative, right-wing, or even alt-right politics. Such ‘selective advocacy’ reinforces a limited picture of the who and what of young people’s political participation. In this chapter, I explore what it might mean for the field of youth studies to provide a more complex picture of young people’s activism and the necessary discomfort that emerges when the desire to advocate for young research participants conflicts with a researcher’s own political and moral concerns. Through a feminist post-structural frame, I examine media and public discourses surrounding instances of young people’s activism in conservative, right-wing, and alt-right spaces. I present the case of a conservative protest organised by a group of university students and targeting a drag queen hosted children’s story time at a library in Brisbane, Australia. This case highlights the importance of maintaining ‘epistemic uncertainty’ when it comes to the complexity of youth and activism. If we are to provide a fuller picture of youth activism, I argue that it is important not to overlook less ‘comfortable’ forms that do not neatly align with the progressive advocacy that dominates the field of youth studies.

This study examines the impact of social media investor sentiment on the stock market performance through qualitative and quantitative proxies.

The authors use a sample of daily stock performance related to S&P 500 Index for the period from December 18, 2017, to December 18, 2018. The social media investor sentiment was assessed through qualitative and quantitative proxies. For qualitative proxies, the study relies on three social media resources”: Twitter, Trump Twitter account and StockTwits. The authors proposed 3 methods to reflect investor sentiment. For quantitative proxies, the number of daily messages published from Trump Twitter account and StockTwits is considered as a signal of investor sentiment. For regression model, the study adopts the autoregressive distributed lagged to determine the relationships between the nonstationary series.

Empirical findings provide evidence that quantitative measures of investor sentiment have significant effects on S&P’500 performances. The authors find that Trump's tweets should be interpreted with caution. The results also show that the number of Trump's tweets on t−1 day have a positive effect on performance on day t.

Social media sentiment contains information for predicting stock returns and transaction activity. Since, the arrival of new information in capital markets triggers investor sentiment on social media.

This study investigates the investors’ sentiment through social media and explores quantitative and qualitative measures. The amount of information on social media reflects more the investor sentiment than content analysis measures.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-12-2022-0818

Drawing on a framework of conservation of resources theory, the purpose of this paper is to explore the relationship between self-perceived academic performance and individual entrepreneurial intention and consider the potential moderating role of (1) participation in serious leisure, (2) perceived stress and/or (3) gender.

A total of 405 UK-based undergraduates completed the questionnaire, with a representative gender split of 57% women and 43% men.

The positive relationship between self-perceived academic performance and individual entrepreneurial intention was moderated by serious leisure (stronger when participation in serious leisure increased) and by perceived stress (stronger when levels of perceived stress were lower). However, contrary to our expectations, gender had no statistically significant moderating role.

The practical contribution comes from informing policy for universities and national governments to increase individual entrepreneurial intention in undergraduates.

The theoretical contribution comes from advancing conservation of resources theory, specifically the interaction of personal resources, resource caravans and resource passageways.

This chapter offers an overview of the applications of artificial intelligence (AI) in the textile industry and in particular, the textile colouration and finishing industry. The advent of new technologies such as AI and the Internet of Things (IoT) has changed many businesses and one area AI is seeing growth in is the textile industry. It is estimated that the AI software market shall reach a new high of over US$60 billion by 2022, and the largest increase is projected to be in the area of machine learning (ML). This is the area of AI where machines process and analyse vast amount of data they collect to perform tasks and processes. In the textile manufacturing industry, AI is applied to various areas such as colour matching, colour recipe formulation, pattern recognition, garment manufacture, process optimisation, quality control and supply chain management for enhanced productivity, product quality and competitiveness, reduced environmental impact and overall improved customer experience. The importance and success of AI is set to grow as ML algorithms become more sophisticated and smarter, and computing power increases.

The purpose of this paper is to study the spillover effects of foreign direct investment (FDI) on skilled–unskilled wage inequality in the Indian manufacturing industries.

The authors show theoretically with a model of spillover that if foreign firms (receiving FDI) have a negative spillover effect on domestic firms (not receiving FDI), then the level of capital and skilled workers in the domestic firms falls down. Consequently, the authors conduct an empirical analysis by using system GMM estimation technique on the firm-level data of the Indian organised manufacturing sector.

The authors show that wage inequality worsens when there is negative spillover effects like competition spillover or skill spillover effect of FDI in India.

To the best of the authors’ knowledge, this is the first attempt to measure the various spillover effects of FDI on the wage inequality in the Indian manufacturing industries by using firm-level data.

The technical report released by the National Transportation Safety Board, along with the primary flight cockpit voice recorder data and archival interview data, were used as the basis for this case. Other available public data such as news reports were used to round out the synopsis of the case study.

United Express Flight 5925 was a scheduled commuter passenger flight operated by Great Lakes Airlines with a Beechcraft 1900 twin turboprop. It was a regularly scheduled flight from Chicago O'Hare International Airport to Quincy, Illinois, with an intermediate stop in Burlington, Iowa. Drawing from various first-hand accounts (cockpit voice recorder) and secondary evidence (news reports, archival interview data, and online sources) of the tragedy, the case provides a detailed account of the key events that took place leading up to the accident at Quincy regional airport. The case describes how the radio interactions, a jammed door and degradation of situational awareness all contributed to the accident. Through many of the quotes in the text and eyewitness accounts, readers gain an understanding of the impressions and perceptions of the pilots, including how they felt about many of the critical decisions in the last minutes of the flight and the situation at the airport.

When the authors teach this case, the students are required to read it as pre-reading before class. Various readings and materials (see supplemental readings below and Exhibit 3) are made available to students before class, and the instructor can choose to use some of these materials to further explore areas of interest. This case is best explored over a 90-min session but could be expanded to take up one 3-h session. This case can be covered in an undergraduate senior capstone organizational behaviour seminar, any general organizational behaviour class (including introductory in nature), an undergraduate communication theory class or an MBA class that focuses on applied organizational behaviour concepts. It works particularly well in the MBA class, as students with work experience can make the links between the behaviours explored in the case and their everyday workplaces.

We seek to quantify the relationship between urbanization and economic growth in China using recent advances in econometric techniques.

This study adopts a smoothed instrumental variables quantile regression (SIVQR) estimator to obtain consistent estimates of the effects of urbanization on economic growth in China. Our approach accounts for the differential impacts of urbanization across the conditional distribution of economic growth while allowing for an identification strategy that addresses the endogeneity of urbanization. Our main findings reveal that ignoring urbanization endogeneity leads to inconsistent estimates of urbanization effects. Further, we find a positive relationship between urbanization and growth resembling an inverted U-shape. This supports the hypothesis that the beneficial effects of urbanization intensify at initial stages while diminishing beyond a certain threshold, due perhaps to weakening scale economies.

Our main results indicate that the individual productivity gains brought by urbanization outweigh the negative effects thereof that impede productivity, thus contributing to the economic growth in China. Further, we find that ignoring differential impacts of urbanization underestimates the beneficial effects of urbanization for provinces whose quality of governance is in the vicinity of the center of quality distribution. Ignoring the endogeneity of urbanization generates inconsistent estimates of the elasticity of economic growth with respect to urbanization. Finally, we estimate an inverted U-shape resembling relationship between urbanization and growth.

First, future studies would benefit from incorporating more data as provinces further east on the mainland become more urbanized and urbanization runs its course. Second, controlling the barriers to rural-urban mobility would contribute to the robustness of the estimated relationship between urbanization and growth once such data became available. Unveiling the impact of government-imposed barriers is key to designing optimal policies that help fuel economic growth in the country. Finally, future research could benefit from information on urbanization sources not considered here such as inter-provincial migration, as such data become publicly available.

Quantifying the beneficial effects of urbanization on economic growth can help guide the government in China to further fuel the growth through a set of relevant policy tools that promote urbanization.

Rural-urban migration in China lays the groundwork for economic advancement in recipient cities and economies, as it may induce scale economies. This can benefit both the economy at large and the migrants.

The SIVQR estimator accounts for potential heterogeneous effects of urbanization across the entire conditional distribution of growth while allowing for an identification strategy that addresses the endogeneity of urbanization. An additional distinguishing feature of the current study is our use of the most recent novel, provincial-level data obtained from the National Bureau of Statistics of China. Our focus on a single country allows sidestepping issues arising from the inconsistency of the definition of urban across different countries while accounting for intra-country urbanization drivers intrinsic to China, such as natural features and geographic characteristics. Therefore, our approach has the potential to sidestep the bias resulting from the differences in mechanisms behind urbanization-growth relationships across different countries.

This examine the impact of environmental, social and governance (ESG) performance on financial reporting quality (FRQ) before and during COVID-19 in the Egyptian market.

This study uses quarterly data from 2017 to 2021 to draw conclusions, with a sample consisting of 486 firm-year observations for 27 Egyptian companies listed on the Standard and Poor’s/Egyptian Stock Exchange ESG index. This study uses both firms’ ESG scores and the Beneish Model, an earnings detection model, as proxies for FRQ. COVID-19 effects on ESG performance and FRQ were examined by using Pearson’s correlation coefficient and two-stage least squares.

COVID-19 has a significant impact on the link between ESG and FRQ. This implies that corporations with high ESG performance are less likely to manipulate earnings (having a low M-score) and thus provide high FRQ during the COVID-19 pandemic. Moreover, there is a significant positive relationship between firm size, leverage and M-Score, indicating that large firms typically present a high FRQ.

The sample size and data availability are the main research limitations. Additionally, this study only considers the effects of firms’ ESG performance on FRQ during the COVID-19 pandemic. Thus, future research should consider other factors associated with investors’ corporate social responsibility (CSR).

This research has practical implications for market regulators seeking to establish a legislative framework and enhance guidance to mandate managers to provide ESG data and CSR reports appropriate for Egypt and other developing economies in times of crisis.

Promoting the adoption of ESG practices in business, particularly during crises, has the potential to effectively provide high-quality and reliable financial reporting required for investment.

This study aspires to address notable deficiencies in the pertinent literature concerning the relationship between ESG performance and FRQ during COVID-19. To the best of the authors’ knowledge, little is known about how ESG performance changes in response to pandemics in emerging markets. To address this gap, this study examines the effects of COVID-19 on the relationship between ESG performance and FRQ in Egyptian-listed firms from 2017 to 2021.

Social media has become an indispensable part of modern politics. Its rise in the political arena has coincided with the decline in trust toward mainstream media. Today, more than half of the population gets their political news and information through social media platforms like Twitter and Facebook. Social media offers a great marketing opportunity to politicians as they allow them to bypass traditional media and communicate directly with voters, engage citizens during campaign and noncampaign periods, and create a brand image. As social media's influence in politics grows, so has the research devoted to political marketing on social media. It is against this backdrop that this chapter is written, which provides readers with an overview of the academic domain and the current state of literature. The chapter highlights the various research areas that have been explored in the literature and the implications of social media for political marketing strategy, along with the domain's current limitations and possible avenues of further research.