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Racism occurs in many ways and varies across countries, evolving and adapting to sociocultural history, as well as contemporary economic, political and technological changes. This chapter discusses the multilevel dimensions of racism and its diverse manifestations across multiracial societies. It examines how different aspects of racism are mediated interpersonally, and embedded in institutions, social structures and processes, that produce and sustain racial inequities in power, resources and lived experiences. Furthermore, this chapter explores the direct and indirect ways racism is expressed in online and offline platforms and details its impacts on various groups based on their intersecting social and cultural identities. Targets of racism are those who primarily bear the adverse effects. However, racism also affects its perpetrators in many ways, including by limiting their social relations and attachments, and by imposing social and economic costs. This chapter thus analyses the many aspects of racism both from targets and perpetrators' perspectives.

This paper examines the influence of different types of political connections and political uncertainty on earnings credibility in Pakistan. Based on discernible differences, connected firms are grouped into civil connected and military connected firms.

The authors provide evidence concerning the earnings credibility incentives of groups of political connected firms and report that their incentives are significantly different. The findings remain robust to alternate methods of earnings credibility.

The findings evidence that civil (military) connected firms report less (more) credible earnings than the control group. High political uncertainty reduces the credibility of earnings. Results for the interaction of political connections and political uncertainty variables are not significant.

The paper investigates just one aspect of Pakistan's political economy, i.e. credibility of earnings; thus, it requires to be cautious on part of readers and policymakers. To reach a clearer conclusion, earnings credibility should be ex amined in the larger context, i.e. in conjunction with rent extractions, etc. A possible extension of the paper can be to investigate the channels of rent extractions used by the two types of connected firms.

The paper has contribution for policymakers as well as users of general purpose financial reports. The findings indicate that the users of general purpose financial reports should be more careful in the use of financial information during political uncertain periods and also of politically connected firms. Furthermore, policymakers should keep the larger context at the forefront while attempting to strengthen the enforcemnet regime.

This paper adds to extant political connections literature by identifying two types of politically connected firms and report that both groups have divergent financial reporting incentives. Furthermore, political uncertainty reduces the credibility of earnings.

India has the biggest number of active users on social media platforms, particularly Twitter. The purpose of this paper is to examine public sentiment on COVID-19 vaccines and COVID Appropriate Behaviour (CAB) by text mining (topic modeling) and network analysis supported by thematic modeling.

A sample dataset of 115,000 tweets from the Twitter platform was used to examine the perception of the COVID-19 vaccination and CAB from January 2021 to August 2021. The research applied a machine-learning algorithm and network analysis to extract hidden and latent patterns in unstructured data to identify the most prevalent themes. The COVID-19 Vaccine Hesitancy Amplification Model was formulated, which included five key topics based on sample big data from social media.

The identified themes are Social Media Adaptivity, Lack of Knowledge Providing Mechanism, Perception of Vaccine Safety Measures, Health Care Infrastructure Capabilities and Fear of Coronavirus (Coronaphobia). The study implication assists communication strategists and stakeholders design effective communication strategies using digital platforms. The study reveals CAB themes as with Mask Wearing Issues and Employment Issues as relevant themes discussed on digital channels.

The themes extracted in the present study provide a roadmap for policy-makers and communication experts to utilize social media platforms for communicating and understanding the perception of preventive measures of vaccination and CAB. As evidenced by the increased engagement on social media platforms during the COVID-19-induced lockdown, digital platforms are indeed valuable from the communication perspective to be proactive in the event of a similar situation. Moreover, significant themes, including social media adaptivity, absence of knowledge-providing mechanism and perception of safety measures of the vaccine, are the critical parameters leading to an amplified effect on vaccine hesitancy.

The COVID-19 Vaccine Hesitancy Amplification Themes (CVHAT) equips stakeholders and government strategists with a preconfigured paradigm to tackle dedicated communication campaigns and assess digital community behavior during health emergencies COVID-19.

The increased acceptance of vaccines and the following of CAB decrease the advocacy of mutation of the virus and promote the healthy being of the people. As CAB has been mentioned as a preventive strategy against the COVID-19 pandemic, the research preposition promotes communication intervention which helps to mitigate future such pandemics. As developing, economies require effective communication strategies for vaccine acceptance and CAB, this study contributes to filling the gap using a digital environment.

Chan et al. (2020) recommended using social media platforms for public knowledge dissemination. The study observed that the value of a communication strategy is increased when communication happens using highly trusted and accessible channels such as Twitter and Facebook. With the preceding context, the present study is a novel approach to contribute toward digital communication strategies related to vaccination and CAB.

While current scholarship on innovation typically examines its antecedents, the purpose of this paper is to provide a more complete account by advocating for social impacts as a critical component of the sociological study of innovation.

This study adopts a conceptual approach to illustrate the ways in which innovation may generate unequitable outcomes. The authors illustrate the purpose of the paper by discussing strategically selected examples that are intended to reflect prominent themes and topics in the relevant literature.

The analysis suggests that while innovation yields many positive benefits, pervasive narratives about its virtues can be overstated when, in fact, innovation may generate adverse effects for particular social groups by reproducing or exacerbating inequality. The authors provide a more complete account of innovation by naming social impacts as a critical component of its sociological study and discussing examples that illustrate how innovation can produce disadvantageous effects by race, gender and social class. The authors move forward the discussion of social impacts by elaborating conditions in which innovation is likely to reproduce the status quo as well as ameliorate negative impacts.

While many studies have explained the conditions that foster innovation, this study pushes the boundaries of the study of innovation – a timely topic for practitioners and scholars in the fields of not only sociology, but management, education and public policy. Accordingly, we move forward the discussion of the social impacts of innovation by identifying the ways in which innovation is likely to reproduce structural inequalities.

The purpose of this study is to examine the relationship between cultural intelligence (CQ) and cross-cultural adjustment (CCA) using meta-analytic methods. The paper serves a dual purpose as it critically examines the CQ-CCA literature and provides summary effects using meta-analysis to determine how CQ and its facets affect CCA and its three dimensions.

A meta-analysis of 77 studies involving 18,399 participants was conducted to obtain the summary effects. The studies reporting the relationship of CQ and/or its facets with CCA or any of its dimensions were included in the analysis.

Results revealed that CQ (overall) and all individual CQs were positively and significantly related to CCA and its three subdimensions. Although CQ (overall) had a strong effect on CCA and moderate to strong effects on all the subdimensions of CCA, the strongest effect size was measured for the relationship of motivational CQ with CCA. Not only this, when individual CQs' relationships were assessed with the individual adjustment dimensions, the motivational aspect of CQ happened to be the most influencing factor, having a close to strong effect on interaction adjustment.

Since the study combines the results from numerous empirical research conducted over time, it avoids the limitations that an individual study has, which is carried out at a single point in time and on a limited sample.

This study adds to the academic research by critically reviewing the CQ-CCA literature. It also works as a guiding map for future research in the area. The study highlights the summary effects for each association between CQ and CCA and their dimensions, elucidating the mixed findings reported in previous research.

The present research aimed to identify the motivations, needs, wants, preferences and limitations of corporate professionals with regard to business social analytics.

Online interviews were conducted with 26 professionals the majority of whom work at the management level at 20 reputable corporations in Turkey. Both qualitative and quantitative data was collected during these interviews, which lasted an average of one hour.

The findings shed light on the motivations of corporate professionals for monitoring social media and other digital media, their perceived capability and limitations in doing so, the media that they monitor and wanted to monitor if possible, their criteria and processes for working with service providers in the field of business social analytics, their needs which are not fully met by service providers, their suggestions on service improvement and their reflections on how internal and external customer data can be analyzed with an integrated approach.

This research is an attempt to bridge the gap between the priorities of engineers who generate artificial intelligence for the purposes of social listening and analytics and the end users, e.g. corporate communication professionals. Only by doing so, this field, which is getting more and more important as people spend more time online, will reach its full potential and benefit corporations by providing fruitful insight upon which strategic steps can be taken.

This article aims to develop a new theory that can better explain and predict how and when humans interact with commercial robots. To this end, utility maximization theory (UMT) along with four principles and propositions that may guide how human-to-commercial robot interactions are developed.

This article conceptualizes UMT by drawing from social exchange, conservation of resources, and technology-driven theories.

This article proposes UMT, which consists of four guiding principles and propositions. First, it is proposed that the human must invest sufficient resources to initiate a human-to-commercial robot interaction. Second, the human forms an expectation of utility gain maximization once a human-to-commercial robot interaction is initiated. Third, the human severs a human-to-commercial robot interaction if the human is unable to witness maximum utility gain upon the interaction. Finally, once the human severs a human-to-commercial robot interaction, the human seeks to reinvest sufficient resources in another human-to-commercial robot interaction with the same expectation of utility maximization.

This article is one of the few studies that offers a theoretical foundation for understanding the interactions between humans and commercial robots. Additionally, this article provides several managerial implications for managing effective human-to-commercial robot interactions.

Despite multiple structural changes since its 2011 inception, many English Women's Super League (WSL) clubs have recorded losses and carried debt, leading to concerns about the financial health of the league. This study is the first to analyse the financial health of any professional women's sports league in the world. The authors examine WSL club finances between 2011 and 2019, theoretically situate the findings within joint production, and make policy recommendations.

In total, 73 annual accounts of 14 WSL clubs between 2011 and 2019 were scrutinised.

Since 2011, club revenue has increased 590% but is outstripped by club debt increase (1,351%). The authors find poor financial health throughout the league, which may damage both its and the clubs' future growth. Findings also indicate an emergent group of dominant clubs on and off the pitch, which may threaten long-term sporting integrity and disrupt the joint production of the WSL product.

Women's football exists at an important crossroad, and its next moves need careful consideration in relation to its governance structures and league design.

The authors provide a road map for necessary action (e.g. revenue distribution, licensing criteria, rewards) to protect the financial health of the WSL's clubs and promote sporting competition to assist the sport to capitalise further on positive gains in recent years.