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This paper addresses the challenges associated with defining and conceptualizing leadership amidst the plethora of theoretical constructs and definitions of leadership and proposes a model for developing transcendent servant-leaders. Based on a review of the literature, three categorical levels of leadership are outlined and discussed that describe the motives that drive leaders, their means of influence, and the outcomes they strive to achieve at each level. These levels include everyday leadership, effective organizational leadership, and transcendent servant leadership. Having delineated these leadership levels, a holistic model for leadership development and education that facilitates the transcendence of effective organizational leaders and ensures their sustaining power of influence is outlined and described.

This paper aims to study the extent of use of artificial intelligence (AI) in the modern organization; to comprehend the changing nature of future jobs in the context of application of AI; and to study the impact of AI on the economy of the country with special reference to the job market. Given the critical scenario of labor intensive Indian economy, the paper intends to show how AI shall affect rather coexist with human intelligence or labor.

The research on implementation of AI in different industries and its effect on job market are at a nascent stage. There is a dearth of literature. Hence, this study followed a qualitative approach to have a better understanding of the research questions as Bhattacherjee (2012) confirms that employing an interpretive paradigm (qualitative analysis as the analysis of data, e.g. data from interview transcripts) is the more productive way to study social order and that it is achieved through “subjective interpretation of participants involved, such as by interviewing different participants and reconciling differences among their responses using their own subjective perspectives”. Sample selection: The selection technique utilized is purposive sampling. The respondents in this research are the general managers and HRs from different companies. A total of 14 senior professionals from various sectors were approached for the interview out of which seven people gave their consent to take interview. Seven senior HR professionals, mainly general managers and HRs from various sectors viz. oil and gas sector, manufacturing, healthcare, construction, media, power and energy and retail were interviewed to understand how they are using AI in their respective fields. Inclusion Criteria: (1) Generally, the people covered under the research are from the decision-making level of their companies so they are in a position to give strategic perspective as well as day to day implication of implementation of AI. (2) Respondents have adequate knowledge of the respective industry to which they belong. (3) Respondents have reasonable industry of dealing with Human Resource Management and national economy as a whole assessment tool and its administration procedures. A narrative approach was adopted to have a better understanding of the research questions and comprehend their views regarding implementation of AI in their respective companies. A semi structured open ended interview was administered to steer the discussion around the research questions. The respondents were interviewed over the phone and each respondent shared their stories. Analysis of data: The narrations were then transcribed by online transcriber website otter.ai.com. The common keywords as prescribed by the website are as: AI, strategy, learning and implementation. The extracts of the discussions are noted in the next segment of the paper. As and when required this research also used secondary data from the journals, literature available in the websites to understand the implementation of AI globally.

A country where the government itself admits 90% of its workforce belongs to informal sector and conspicuously exits a multi-faceted stark digital divide (Huberman, 2001; DiMaggio et al., 2001; Guillen, 2006; Servon, 2002) wherein gap of digital divide is significant between the rural and urban India (Dasgupta et al., 2002; Nath, 2001; Singh, 2007; Mahajan, 2003; Dutta, 2003) talking of educating, applying and implementing AI seems to be “ a distant dream” but an “ambiguous ambition ”

Prior to implementation of AI that India has to ensure, the basic hygiene factors of informal sector labor force like social security, 2008, low wages and lack of legal protection, unpaid overtime and occupational health problems, poor bargaining power, working without leave under coercion, child care issues and health ailments(for which mere legislation or statutarization is just a formality executed than taking real action) to take the majority of Indian workforce to attain the motivational factor to acquire the knowledge and skill of AI and to implement it.

The AI and its adoption are still at their embryonic stage in Indian companies. With the adoption of such sophisticated technology, in one side, the organizations are dreaming of efficiency, higher productivity and better organizational performance whereas on the other side requirement of changing skill sets and decreasing manpower, creating fear among the mass, which results in hard resistance against the implementation process of AI. On the other hand, lack of expertise and high cost of adoption is also hindering AI to implement in the organizations. The adoption and implementation stage of AI vary from organization to organizations, as well as functions to functions. While the marketing departments of several organizations are using advanced level of AI, there, the HR departments are using AI at the very initial stage. But it is evident from the above discussions that adoption of AI in business functions is inevitable and only it is a matter of time. With the COVID-19 pandemic this has become the utmost necessity for many organizations, particularly who works across the globe. HR partners of the businesses are also adopting AI at a fast pace to do away with the mundane works and deliver efficient services to the stakeholders. It is understood from the discourse that the prerequisite for a successful implementation of AI across the industries throughout the country, needs a concerted effort from industries, academia and government.

The answer lies in Keynesian economics. The central tenet of which is government intervention rather investment to stabilize and progress the economy by way of spreading Internet connectivity, basic literacy and computer literacy, then only truly AI can be effective in a greater scale.

A study on application of artificial intelligence in the pandemic era from a wider perspective, this work is an empirical investigation into the benefits and limitations of artificial intelligence for human potential and labour -intensive pandemic ridden Indian economy.

The purpose of this paper is to explore whether official inquiries are an effective method for holding the medical profession to account for failings in the quality and safety of care.

Through a review of the theoretical literature on professions and documentary analysis of key public inquiry documents and reports in the UK National Health Service (NHS) the authors examine how the misconduct of doctors can be understood using the metaphor of professional wrongdoing as a product of bad apples, bad barrels or bad cellars.

The wrongdoing literature tends to present an uncritical assumption of increasing sophistication in analysis, as the focus moves from bad apples (individuals) to bad barrels (organisations) and more latterly to bad cellars (the wider system). This evolution in thinking about wrongdoing is also visible in public inquiries, as analysis and recommendations increasingly tend to emphasise cultural and systematic issues. Yet, while organisational and systemic factors are undoubtedly important, there is a need to keep in sight the role of individuals, for two key reasons. First, there is growing evidence that a small number of doctors may be disproportionately responsible for large numbers of complaints and concerns. Second, there is a risk that the role of individual professionals in drawing attention to wrongdoing is being neglected.

To the best of the authors’ knowledge this is the first theoretical and empirical study specifically exploring the role of NHS inquiries in holding the medical profession to account for failings in professional practice.

The purpose of this paper is to investigate US noncombatant evacuation operations (NEO) in South Korea and devise planning and management procedures that improve the efficiency of those missions.

It formulates a time-staged network model of the South Korean noncombatant evacuation system as a mixed integer linear program to determine an optimal flow configuration that minimizes the time required to complete an evacuation. This solution considers the capacity and resource constraints of multiple transportation modes and effectively allocates the limited assets across a time-staged network to create a feasible evacuation plan. That solution is post-processed and a vehicle routing procedure then produces a high resolution schedule for each individual asset throughout the entire duration of the NEO.

This work makes a clear improvement in the decision-making and resource allocation methodology currently used in a NEO on the Korea peninsula. It immediately provides previously unidentifiable information regarding the scope and requirements of a particular evacuation scenario and then produces an executable schedule for assets to facilitate mission accomplishment.

The significance of this work is not relegated only to evacuation operations on the Korean peninsula; there are numerous other NEO and natural disaster related scenarios that can benefit from this approach.

This research assesses the Know, See, Plan, portions of the Know, See, Plan, Do (KSPD) model for curriculum design in leadership education. There were 3 graduate student groups, each taught using 1 of 3 different curriculum designs (KSPD and 2 control groups). Based on apre- test, post-test design, students’ performance was measured to assess their knowledge, and application skills of the course material. Results indicated MBA students taught based on a KSPD curriculum (Group 1) performed significantly better than students in the two control groups on 3 post-test dependent measures designed to capture the effectiveness of the Know, See, Plan curriculum design model, (basic leadership information (K1), recognition of leadership concepts in practice (S1), and developing a plan of action (P1)). Group 1 also performed significantly better on all 3 post-test measures than they performed on the 3 pre-test measures. The non-MBA control group (Group 2) improved significantly from pre-test to post test on P1 but not on S1 or K1. The MBA control group (Group 3) had no significant changes in performance from pre-test to post-test on any of the three dependent measures. These findings are discussed in terms of their support for the KSPD model and in regard to limitations of this study.

Despite increasingly persuasive women-focused marketing of gambling products, there has only been limited investigation around women sports betting. Men remain the focus of much of the conversation about sports betting as they have generally been found to be the most active sports bettors and the most at risk of experiencing harms associated with their behaviour. This chapter aims to fill this gap by exploring the characteristics of young women sports bettors in the United Kingdom and the relationship between sports betting and the experience of gambling harms. To do this, we created two models of analysis. Our analysis is based on data from the first wave (2019) of the Emerging Adults Gambling Survey (EAGS) dataset (n = 3,549). The EAGS is a non-probability longitudinal survey that includes individuals between the ages of 16 and 24 who were residents in Britain at the time of data collection. Firstly, we examined the associations between women sports bettors and several factors identified as important predictors of sports betting. Secondly, we sought to understand the relationship between women's sports betting and the harms associated with this activity. From these models, we found that women's sports betting was most reliably predicted according to fandom and peer influence. We also found that women sports bettors were more at risk of experiencing harms associated with difficulties with family and friends than women gamblers using other products.

The paper traces the development of employee ownership in the UK since the 1980s. It proposes that employee ownership is a function of macro-level contexts and micro-level decisions, with the latter framed and guided by the former. The macro context comprises the regulatory framework and the provision of incentives to adopt employee ownership. The paper shows how the evolution of these has led to a steep increase in employee ownership in the last eight years.

The paper draws on several sources of empirical data to chart the development of employee ownership in the UK since the 1980s and to identify the current features of employee ownership. Two firm-level surveys conducted in 2015 and 2020/21 are supplemented by qualitative case study data collected in the early 1990s. An annual census of all employee-owned firms facilitates a comprehensive overview of the current state of UK employee ownership.

It is found that there has been a steep increase in the number of UK employee-owned firms since 2014 after several decades of uneven growth. This is attributed to the introduction of new incentives and to refinements of the regulatory framework. Over the period, there has been a shift from hybrid employee ownership, combining direct and indirect forms, to indirect ownership associated with the employee ownership trust model.

The paper provides an original history of employee ownership in the UK using rich and unique data, along with the most comprehensive picture of current employee ownership to date.

New Space activities offer benefits for human progress and life beyond the Earth. However, there is a risk that the New Space Economy may develop according to an anthropocentric mindset favouring human progress and survival at the expense of all other species and the environment. This mindset raises concerns over the social and environmental impacts of space activities and the accountability of space actors. This research article explores the accountability of space actors by presenting a pluralistic accountability framework to understand, inspire and change accountability in the New Space Economy. This study also identifies future research opportunities.

This paper is a reflective and normative essay. The arguments are developed using contemporary multidisciplinary academic literature, publicly available evidence and examples. Further, the authors use Dillard and Vinnari's accountability framework to examine a pluralistic accountability system for space businesses.

The New Space Economy requires public and private entities to embrace hybrid and pluralistic accountability for their social and environmental impacts. A new way of seeing the relationship between human life, the Earth and celestial space is needed. Accounting language is used to mirror and mobilise broader forms of responsibility in those involved in space.

This paper responds to the AAAJ's special issue call for examining how accountability can be ensured in the New Space Age. The space activities businesses conduct, and the anthropocentric view inspiring their race toward space is concerning. Hence, the authors advocate the need for rethinking accountability between humans and nature. The paper contributes to fostering the debate on social and environmental accounting and the accountability of space actors in the New Space Economy. To this end, the authors use a pluralistic accountability framework to help understand how the New Space Economy can face the risks emanating from its anthropocentric mindset.

Research reveals that the built environment graduates are not matching the needs of the 21st century construction industry. Evidence shows that the built environment academics (BEA) struggle to reskill and upskill to meet the industry's demand. Studies about Nigeria's BEA's perceived barriers in meeting the 21st-century industry demands are scarce. Thus, the paper investigated the perceived barriers and measures to improve BEA in Nigeria's 21st-century world of teaching. The outcome intends to enhance teaching practices and increase employability in the built environment disciplines.

Data were sourced from elite virtual interviews across Nigeria. The participants were well informed about Nigeria's built environment education and the possible barriers hindering 21st-century teaching from improving employable graduates in the built environment professionals (BEP). The researchers adopted a thematic analysis for the collected data and supplemented the data with secondary sources.

The study shows that BEA needs to improve BEA's teaching mechanism. Improving BEA will enable the built environment graduates to meet the minimum standards expected by the 21st-century industry. Findings categorised the perceived 22 barriers facing BEA into internal stakeholders-related barriers, external stakeholders-related barriers, and common barriers. Also, findings proffered practicable measures to improve BEA in the workplace via improved industry collaboration and technological advancement.

The research is restricted to the perceived barriers and measures to improve BEA in 21st-century teaching in Nigeria via a qualitative research design. Future research should validate the results and test the paper's proposed framework.

The paper confirms that the BEA requires stakeholder collaboration and technological advancement measures to improve teaching in the 21st century, leading to enhanced employability graduates. The paper would stir major stakeholders, especially BEA, and advance the quality of employable graduates in the Nigerian built environment professions.

The thematic network and proposed framework could be employed to stimulate Nigeria's BEA for better service delivery. This intends to create an enabling environment that will enhance stakeholders' collaboration and technological advancement for the BEA to produce better employable graduates in the 21st century.

Social media platforms are highly visible platforms, so politicians try to maximize their benefits from their use, especially during election campaigns. On the other side, people express their views and sentiments toward politicians and political issues on social media, thus enabling them to observe their online political behavior. Therefore, this study aims to investigate user reactions on social media during the 2016 US presidential campaign to decide which candidate invoked stronger emotions on social media.

For testing the proposed hypotheses regarding emotional reactions to social media content during the 2016 presidential campaign, regression analysis was used to analyze a data set that consists of Trump’s 996 posts and Clinton’s 1,253 posts on Facebook. The proposed regression models are based on viral (likes, shares, comments) and emotional Facebook reactions (Angry, Haha, Sad, Surprise, Wow) as well as Russell’s valence, arousal, dominance (VAD) circumplex model for valence, arousal and dominance.

The results of regression analysis indicate how Facebook users felt about both presidential candidates. For Clinton’s page, both positive and negative content are equally liked, while Trump’s followers prefer funny and positive emotions. For both candidates, positive and negative content influences the number of comments. Trump’s followers mostly share positive content and the content that makes them angry, while Clinton’s followers share any content that does not make them angry. Based on VAD analysis, less dominant content, with high arousal and more positive emotions, is more liked on Trump’s page, where valence is a significant predictor for commenting and sharing. More positive content is more liked on Clinton’s page, where both positive and negative emotions with low arousal are correlated to commenting and sharing of posts.

Building on an empirical data set from Facebook, this study shows how differently the presidential candidates communicated on social media during the 2016 election campaign. According to the findings, Trump used a hard campaign strategy, while Clinton used a soft strategy.