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This paper aims to consider the potential implications of the layering of regulation in relation to hydraulic fracturing (fracking) at the borders between the nations of the UK.

This paper uses a qualitative research method grounded in particular in legal geography to examine the existing approaches to regulating hydraulic fracturing and identify the places and their features that are constructed as a result of their intersection at the borders of the nations comprising the UK.

The current regulatory framework concerning hydraulic fracturing risks restricts the places in which the practice can occur in such a manner as to potentially cause greater environmental harm should the process be used. The regulations governing the process are not aligned in relation to the surface and subsurface aspects of the process to enable their management, once operational, as a singularly constructed place of extraction. Strong regulation at the surface can have the effect of influencing placement of the site only in relation to the place at which the resource sought reaches the surface, whilst having little to no impact on the environmental harms, which will result at the subsurface or relative to other potential surface site positions, and potentially even increasing them.

This paper is limited by uncertainty as to the future use of hydraulic fracturing to extract oil and gas within the UK. The issues raised within it would also be applicable to other extractive industries where a surface site might be placed within a radius of the subsurface point of extraction, rather than having to be located at a fixed point relative to that in the subsurface. This paper therefore raises concerns that might be explored more generally in relation to the regulation of the place of resource extraction, particularly at legal borders between jurisdictions, and the impact of regulation, which does not account for the misalignment of regulation of spaces above and below the surface that form a single place at which extraction occurs.

This paper considers the potential impacts of misaligned positions held by nations in the UK in relation to environmentally harmful practices undertaken by extractive industries, which are highlighted by an analysis of the extant regulatory framework for hydraulic fracturing.

Whilst the potential for cross internal border extraction of gas within the UK via hydraulic fracturing and the regulatory consequences of this has been highlighted in academic literature, this paper examines the implications of regulation for the least environmentally harmful placement of the process.

This study aims to examine the influence of social media usage (SMU) on minimalist consumption and how the fear of missing out (FoMO) underlies this effect.

Four preregistered correlational/experimental studies (n = 1,763) are used. A pilot study (n = 436) examines the correlations between SMU, FoMO and minimalism. Studies 1 (n = 409), 2 (n = 415) and 3 (n = 503) further investigate the influence of SMU on minimalist consumption intentions, including mindful purchase, forgoing free products and decluttering, and test for evidence of mediation via FoMO by measuring or manipulating FoMO.

The results show that a high SMU makes consumers susceptible to FoMO, leading to impulsive purchases and careless product acquisition. However, when campaigners promote minimalism as a social media movement, they can activate FoMO, persuading consumers to practice decluttering.

Future research might examine how subjective age affects FoMO and minimalist consumption tendencies. Could campaigners use young social cues to make older consumers more susceptible to FoMO appeals? Could old social cues cause younger consumers to perceive greater social responsibility and to embrace minimalist consumption?

Minimalist lifestyles can promote sustainable consumption. This research provides insights into how SMU is a double-edged sword – it can cause FoMO users to disdain minimalism. However, it can promote minimalism if a minimalist campaign is strategically positioned as a social media movement using a FoMO-laden appeal.

Extant consumer behavior research on minimalism has just begun to investigate the antecedents of minimalist consumption. FoMO is conceptually related to minimalism, but the relationship between FoMO and minimalist consumption has not yet been empirically tested. This research fills these gaps by examining SMU and the associated FoMO as antecedents of minimalist consumption. Empirical evidence for the impact of SMU on various minimalist consumption behaviors and the mediating role of FoMO is provided.

This paper aims to examine whether information technology (IT) managers’ virtual listening, as rated by their high-tech employees, affected turnover behaviour beyond a new constellation of variables, some of which have never been researched as antecedents of turnover behaviour, particularly during a pandemic or crisis. Namely, the main aim, among others, is to answer the research question: does IT employees’ perception of the quality of their supervisors’ virtual listening in the pandemic and crisis era, when employees and managers work remotely, will negatively affect turnover behaviour? If yes, in which constellation of antecedents the virtual listening effecting on turnover behaviour?

Logistic regression analysis was conducted to test the hypotheses via SPSS 26 and PROCESS (Model 6). The variance inflation factor was calculated to test multicollinearity. Interaction was tested using the Hayes and Preacher PROCESS macro model. The researchers also used the J-N technique test (Johnson–Neyman via process). The supplemental analysis used also PROCESS MACRO (IBM Corp., Armonk, NY, USA, 2023) Model 4 and Bootstrap test.

The findings show that perceptions of supervisors’ virtual listening quality as rated by their employees moderated the relationship between organisational deviance as a type of organisational misbehaviour (OMB) and turnover behaviour and had the strongest effect on turnover behaviour beyond other key predictors (organisational deviance as a type of misbehaviour, turnover intention, job satisfaction, embeddedness and alternatives in the labour market). Alternatives to current work moderated the association between the perception of managers’ virtual listening behaviour as rated by their employees and turnover behaviour. Specifically, when alternatives in the labour market were high or medium, the perceived quality of managers’ virtual listening reduced turnover behaviour. Finally, the perception of the IT employees supervisors’ virtual listening moderated the relationship between organisational deviance and turnover intention among high-tech employees.

Evaluating supervisor listening in the high-tech firm may have value in terms of its relationship to outcomes such as retaining employees, turnover intention and especially turnover behaviour. The effect on turnover behaviour and of that new constellation of antecedents on turnover behaviour when people work remotely was not researched yet and important for the post COVID-19 era. Additionally, in contrast to most studies of turnover, this study also focus on the positive aspects of turnover and especially turnover behaviour to organisations in general and especially to high-tech firm and not just the negative aspect as was researched until now. Another contribution is the finding that when employees perceived their managers’ virtual listening quality as high, the effect of deviance as a type of OMB on turnover behaviour was positive. Namely, the listening as a moderator and turnover assisted in making the organisation cleaner from inappropriate behaviour. Additionally, when alternatives in the labour market are high or medium, perceived quality of virtual listening of managers as rated by their employees can reduce turnover behaviour. This virtual listening–turnover relationship and the moderator of alternatives to current work had not previously been found in the turnover literature and this is also significant a contribution to the turnover and withdrawal literature.

The purpose of the study is to propose a normative approach for market segmentation, profile and monitoring using computing and information technology to analyze User-Generated Content (UGC).

The specific steps include performing a structural analysis of the UGC and extracting the base variables and values from it, generating a consumer characteristics matrix for segmenting process, and finally describing the segments' preferences, regional and dynamic characteristics. The authors verify the feasibility of the method with publicly available data. The external validity of the method is also tested through questionnaires and product regional sales data.

The authors apply the proposed methodology to analyze 53,526 UGCs in the New Energy Vehicle (NEV) market and classify consumers into four segments: Brand-Value Suitors (32%), Rational Consumers (21%), High-Quality Fanciers (26%) and Utility-driven Consumers (21%). The authors describe four segments' preferences, dynamic changes over the past six years and regional characteristics among China's top five sales cities. Then, the authors verify the external validity of the methodology through a questionnaire survey and actual NEV sales in China.

The proposed method enables companies to utilize computing and information technology to understand the market structure and grasp the dynamic trends of market segments, which assists them in developing R&D and marketing plans.

This study contributes to the research on UGC-based universal market segmentation methods. In addition, the proposed UGC structural analysis algorithm implements a more fine-grained data analysis.

This paper aims to design, develop and validate an instrument to measure employer branding by considering existing employee perceptions.

In this systematic research, the predominant factors of employer branding are identified through Pareto analysis; using structured questionnaire information and data collected from 423 employees. The number of items and dimensions was reduced by conducting exploratory factor analysis (EFA) and validated extracted dimensions using confirmatory factor analysis (CFA) using statistical software (SPSS-21). The designed scale was verified by applying relevant statistical techniques, including a multicollinearity test, construct validity, content validity, divergent validity, convergent validity and reliability test. Structural equation modeling (SEM) was performed using AMOS, to explore the interrelationship between the dimensions of the scale.

Considering the perception of existing employees, seven factors along with 24 items scale were designed and developed to measure the employer branding. The identified seven factors are; career development opportunities; compensation and benefits; corporate social responsibility; training and development; work environment; organizational culture; and work-life balance. The proposed model explains a total variance of 70.35% and the model fit indices are within the acceptable range, validity and statistical reliability are established for seven dimensions of employer branding.

Employer branding is studied from existing employee perspective by collecting responses from the employees of the IT sector only.

This validated scale is valuable for practitioners and academicians. The proposed dimensions in the scale may help practitioners explore the impact on the outcomes of organizations such as employee commitment, employee retention, employee satisfaction and total productivity. This novel instrument helps to measure employees' perception of their employers. Further, the authors identify the gaps and accordingly plan strategies to attract and retain the talented workforce.

The authors believe that this novel measuring instrument is comprehensive and the first of its kind. Employer branding has been modeled using SEM analysis by considering the perceptions of the present employees.

Blockchain is a disruptive technology that has matured to deliver robust, global, IT systems, yet adoption lags predictions. The authors explore barriers to adoption in the context of a global challenge with multiple stakeholders: integration of carbon markets. Going beyond the dominant economic-rationalistic paradigm of information system (IS) innovation adoption, the authors reduce pro-innovation bias and broaden inter-organizational scope by using technological frames theory to capture the cognitive framing of the challenges perceived within the world’s largest carbon emitter: China.

Semi-structured interviews with 15 key experts representing three communities in China’s carbon markets: IT experts in carbon markets; carbon market experts with conceptual knowledge of blockchain and carbon market experts with practical blockchain experience.

Perceived technical challenges were found to be the least significant in explaining adoption. Significant challenges in five areas: social, political legal and policy (PLP), data, organizational and managerial (OM) and economic, with PLP and OM given most weight. Mapping to frames developed to encompass these challenges: nature of technology, strategic use of technology and technology readiness resolved frame incongruence that, in the case explored, did not lead to rejection of blockchain, but a decision to defer investment, increase the scope of analysis and delay the adoption decision.

Increases scope and resolution of IS adoption research. Technological frames theory moves from predominant economic-rational models to a social cognitive perspective. Broadens understanding of blockchain adoption in a context combining the world’s most carbon emissions with ownership of most blockchain patents, detailing socio-technical challenges and delivering practical guidance for policymakers and practitioners.

Students pursuing different professional courses at the higher education level during 2021–2022 saw the first-time occurrence of a pandemic in the form of coronavirus disease 2019 (COVID-19), and their mental health was affected. Many works are available in the literature to assess mental health severity. However, it is necessary to identify the affected students early for effective treatment.

Predictive analytics, a part of machine learning (ML), helps with early identification based on mental health severity levels to aid clinical psychologists. As a case study, engineering and medical course students were comparatively analysed in this work as they have rich course content and a stricter evaluation process than other streams. The methodology includes an online survey that obtains demographic details, academic qualifications, family details, etc. and anxiety and depression questions using the Hospital Anxiety and Depression Scale (HADS). The responses acquired through social media networks are analysed using ML algorithms – support vector machines (SVMs) (robust handling of health information) and J48 decision tree (DT) (interpretability/comprehensibility). Also, random forest is used to identify the predictors for anxiety and depression.

The results show that the support vector classifier produces outperforming results with classification accuracy of 100%, 1.0 precision and 1.0 recall, followed by the J48 DT classifier with 96%. It was found that medical students are affected by anxiety and depression marginally more when compared with engineering students.

The entire work is dependent on the social media-displayed online questionnaire, and the participants were not met in person. This indicates that the response rate could not be evaluated appropriately. Due to the medical restrictions imposed by COVID-19, which remain in effect in 2022, this is the only method found to collect primary data from college students. Additionally, students self-selected themselves to participate in this survey, which raises the possibility of selection bias.

The responses acquired through social media networks are analysed using ML algorithms. This will be a big support for understanding the mental issues of the students due to COVID-19 and can taking appropriate actions to rectify them. This will improve the quality of the learning process in higher education in Oman.

Furthermore, this study aims to provide recommendations for mental health screening as a regular practice in educational institutions to identify undetected students.

Comparing the mental health issues of two professional course students is the novelty of this work. This is needed because both studies require practical learning, long hours of work, etc.

This study explores citizen activism in the articulation of a politicised counter-account of Aboriginal rights. It aims to uncover the enabling factors for a successful challenge to established political norms and the obstacles to the fullest expression of a radical imagining.

Laclau and Mouffe's theory of hegemony and discourse is used to frame the movement's success in challenging the prevailing system of urbanised healthcare delivery. Empirical materials were collected through extensive ethnographic fieldwork.

The findings from this longitudinal study identify the factors that predominantly influence the transformational success of an Yaṉangu social movement, such as the institutionalisation of group identity, articulation of a discourse connected to Aboriginal rights to self-determination, demonstration of an alternative imaginary and creation of strong external alliances.

This study offers a rich empirical analysis of counter-accounting in action, drawing on Aboriginal governance traditions of non-confrontational discourse and collective accountability to conceptualise agonistic engagement. These findings contribute to the practical and theoretical construction of democratic accounting and successful citizen activism.

This study seeks to develop a clearer understanding of the motivational factors affecting Saudi female business undergraduates' choice of pursuing entrepreneurship.

The research adopts a quantitative approach to gain general understanding of the students' perceptions with regard to their motivations to pursue entrepreneurship. Data were collected through a structured questionnaire survey administered to 214 female business undergraduates at Prince Mohammad Bin Fahd University (PMU) in Al-Khobar, to investigate their perceptions of entrepreneurial motivations. Descriptive statistics and factor analysis were used to identify the motivational factors. Multiple regression analysis was used to reveal relationships between the motivation factors and entrepreneurial motivation of female business undergraduates.

The study revealed four generalised entrepreneurial motivations among Saudi female business undergraduates: personal motivational factors with an emphasis on freedom and social status; business motivational factors such as financial rewards and security; social motivational factors manifested in the influence of the community, roles and family; and environmental motivations which were mainly associated to education, the market knowledge and ability to access finance.

The study was restricted to female students at PMU University. Thus, generalisation of the results could be limited. The findings of the study could be useful to relevant authorities to enhance and boost entrepreneurship for female students and hence to contribute to the national Vision 2030.

This study is among those few studies located in the MENA region that explore Saudi female university students' attitude towards entrepreneurship. It adds to the authors' understanding on the four generalised factors by highlighting the importance of the family's role and entrepreneurship education in motivating Saudi female students towards entrepreneurship engagement. It also contributes to the understanding of these motivations that could be applied in other similar contexts.

This study aims to synthesize the existing literature with insights gained from interviews conducted with regulatory experts. The objective is to analyse the challenges associated with incorporating cryptocurrencies into regulatory frameworks and to explore constraints in the regulatory institutionalization of cryptocurrencies.

The study methodology consists of two steps. The first step is to identify regulatory constraints in the literature review and in the next step, interviews are conducted with officials of the State Bank of Pakistan (SBP). The study used a qualitative case study methodology, in which a single case (regulatory constraint) was selected as a unit of analysis.

The findings show that lack of traceability, legal status, lack of governmental control due to decentralization, difficulty enforcing laws, volatility, lack of skills with regulators and difficulty integrating cryptocurrencies into the current financial system are the main obstacles to the introduction of a regulatory framework. Thus, on a broader conceptual level, the findings can be grouped into opportunism, lack of strategic capability and fragmented global laws.

This study could inform global cryptocurrency regulation discussions, sharing a developing country’s views on balancing the government, central banks, the financial sector and public interests. This could guide countries to consider cryptocurrency adoption in similar situations. This could affect the cryptocurrency market, impacting demand, supply and investor trust in Pakistan.

The study has implications for policy making officials. The research aims to offer valuable insights to the SBP and other regulatory authorities, helping them identify potential risks and create an effective regulatory framework for cryptocurrencies.

The study has implications for society in knowing about the volatile nature of cryptos and anonymity of their issuers, which poses regulatory constraints. This then implies its harmfullness to its traders and the huge losses that may arise from their trading due to its volatile nature.

This study contributes to the literature on the constraints, responsibilities and consultation framework of cryptocurrency regulations.