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This paper aims to discuss the practical dilemmas of institutional change to tackle the climate crisis in a UK university, identifying key assumptions and issues that block meaningful change. The research was part of an initiative to define a theory of change (ToC) to meet the university’s institutional climate commitments.

The findings are based on interviews with members of an inter-disciplinary ToC working group, a staff–student climate coalition and student representatives at the university. Interviewees were purposively selected to gain insights into assumptions about the nature of the university and its role in tackling the climate crisis, which must be addressed for the university to effectively implement its climate plan.

This paper identified tensions between the university’s role as a public and commercial institution, a lack of clarity over decision-making processes and the difficulties in balancing (and being transparent about) actions with commitments to tackle the climate crisis. A democratic and flexible approach to change is essential to mitigate these issues, providing an opportunity to reflect on the diversity of the university community and openly debate goals and commitments.

In setting out the initial steps of a ToC in a UK university, this paper offers practical insights for higher education institutions looking to change practices. By highlighting assumptions at a particular institution, this paper also contributes a level of granularity to a growing field of research on efforts in higher education institutions to tackle the climate crisis.

This study aims to develop an experimentally validated three-dimensional numerical model for predicting different flow patterns produced with a gas dynamic virtual nozzle (GDVN).

The physical model is posed in the mixture formulation and copes with the unsteady, incompressible, isothermal, Newtonian, low turbulent two-phase flow. The computational fluid dynamics numerical solution is based on the half-space finite volume discretisation. The geo-reconstruct volume-of-fluid scheme tracks the interphase boundary between the gas and the liquid. To ensure numerical stability in the transition regime and adequately account for turbulent behaviour, the k-ω shear stress transport turbulence model is used. The model is validated by comparison with the experimental measurements on a vertical, downward-positioned GDVN configuration. Three different combinations of air and water volumetric flow rates have been solved numerically in the range of Reynolds numbers for airflow 1,009–2,596 and water 61–133, respectively, at Weber numbers 1.2–6.2.

The half-space symmetry allows the numerical reconstruction of the dripping, jetting and indication of the whipping mode. The kinetic energy transfer from the gas to the liquid is analysed, and locations with locally increased gas kinetic energy are observed. The calculated jet shapes reasonably well match the experimentally obtained high-speed camera videos.

The model is used for the virtual studies of new GDVN nozzle designs and optimisation of their operation.

To the best of the authors’ knowledge, the developed model numerically reconstructs all three GDVN flow regimes for the first time.

The history of online trading began in the 1960s with the emergence of electronic communication networks, which allowed the electronic execution of trades outside traditional exchanges. The internet revolution led to the development of online brokerage platforms such as E*Trade and Schwab, enabling non-institutional investors to participate in the digital trading revolution. These platforms have evolved to serve the retail investor market, eventually adapting to mobile-first and commission-free models, significantly lowering the barriers to entry for financial markets. Platforms like Robinhood and other fintech firms have rapidly gained market share by offering services and products previously unavailable, such as commission-free trades, mobile trading, and novel products such as fractional shares and cryptocurrency investing. This chapter provides an overview of the history of online trading. It also introduces several new developments in fintech and the online trading industry and discusses various controversies and future implications of new technologies.

Intentions are central to entrepreneurial thinking and thus entrepreneurial action yet we have not explored the different pathways of how intent evolves. How does an easily assessed measure of cognitive style influence how entrepreneurs develop their intentions?

We examine how cognitive style interacts with entrepreneurial intentions testing the model separately with subjects scoring as Intuitives or Analytics on cognitive style, plus nationality and gender as covariates with entrepreneurial intensity as a prospective moderator, using 528 university students from Norway, Russia and Finland.

Cognitive style does moderate the intentions model. For intuitives, country influenced social norms and entrepreneurial intensity proved a moderator. For analytics, neither perceived desirability, country, nor entrepreneurial intensity were significant.

We will replicate these findings in different samples, especially non-WEIRD settings. It will also be useful to test alternate measures of cognitive style and other likely moderators.

We offer diagnostics for educators and ecosystem actors given that our findings suggest intriguing differences in the entrepreneurial mindset.

Understanding multiple pathways exist to entrepreneurial intent and thus action helps policymakers and entrepreneurial champions better able to help nurture entrepreneurs and thus entrepreneurship in their communities.

Cognitive style has dramatic effects on the specification of the formal intentions model arguing for multiple pathways to entrepreneurial intent. For example, two entrepreneurs might arrive at the same intention but through very different processes because they differ in cognitive style.

This study aims to propose and test an appraisal theory-based framework that depicts the impact of negatively valenced brand personality dimensions on brand hate development and the resultant outcomes of non-purchase intention and anti-brand actions. The study also delineates the moderation effect of Big Five consumer personality traits on brand personality-brand hate relationship.

An international sample of 370 brand haters was collected and analysed with partial least square-based structural equation modelling.

Both negatively valenced brand personality dimensions of responsibility and activity are significant predictors of brand hate in consumers, and this brand hate leads to outcomes of anti-brand actions and non-purchase intention of consumers. Moderation analysis delineates that the consumer personality trait of neuroticism significantly moderates the relationship between both brand personality dimensions and brand hate. The study also established the importance of national culture in defining consumers’ behavioural intentions.

This study provides a novel appraisal theory-based integrated framework to understand the relationship between cognition of brand personality, brand hate emotional state and behavioural actions of consumers. To the best of the authors’ knowledge, this study is the first to consider the impact of these personality dimensions on brand hate development while assessing the interaction effect of consumer and brand personality dimensions on brand hate development.

Quality 4.0 is essential to the Industry 4.0 framework, notably in the electronics sector. It evaluates product quality in real-time using automatic process controls, quality tools and procedures. The implementation of Quality 4.0 criteria in the electronics industry is the subject of this study’s investigation and analysis. In this study, nine Customer Requirements (CRs) and 18 Design Requirements (DRs) have been defined to adopt Quality 4.0, aiming to increase yield while reducing defects. This study has developed a Quality 4.0 framework for effective implementation, incorporating the People, Process and Technology categories.

Many CRs and DRs of Quality 4.0 exhibit interdependencies. The Analytic Network Process (ANP) considers interdependencies among the criteria at various levels. Quality Function Deployment (QFD) can capture the customer’s voice, which is particularly important in Quality 4.0. Therefore, in this research, we use an integrated ANP-QFD methodology for prioritizing DRs based on the customers' needs and preferences, ultimately leading to better product and service development.

According to the research findings, the most critical consumer criteria for Quality 4.0 in the electronics sector are automatic systems, connectivity, compliance and leadership. The Intelligent Internet of Things (IIOTs) has emerged as the most significant design requirement that enables effective control in production. It is observed that robotics process automation and a workforce aligned with Quality 4.0 also play crucial roles.

Existing literature does not include studies on identifying CRs and DRs for implementing Quality 4.0 in the electronics industry. To address this gap, we propose a framework to integrate real-time quality measures into the Industry 4.0 context, thereby facilitating the implementation of Quality 4.0 in the electronics industry. This study can provide valuable insights for industry practitioners to implement Quality 4.0 effectively in their organizations.

The present study examines the effect of supervisor incivility on service employee creativity and the mediating mechanism of negative affect state on the said relationship with the aid of Affective Events Theory (AET) and Social Power Theory. Additionally, the study explores the mitigating role of core self-evaluation in the dual stage of the moderated mediation model.

Survey data were collected from 420 frontline employees working in four-star and five-star hotels across India and PROCESS macro in SPSS 23.0 was employed to test the hypotheses proposed in the study.

The study findings observe that frontline employees experiencing supervisor incivility face a negative affect state and it further diminishes service employee creativity. Also, the indirect effect gets attenuated at dual stages when frontline employees are equipped with a high level of core self-evaluation.

The study findings provide various insights to the managers to understand the deleterious effect of supervisor incivility at work and to develop interventions to manage supervisor incivility and the negative affect state among frontline hotel employees.

The present study is the first and unique attempt to investigate the role of supervisor incivility experienced by frontline hotel employees in India with reference to their creativity towards customers and mediating mechanism of negative affect state. The study adds value to the literature by establishing the role of core self-evaluation in the moderated mediation model. Further, the study also provides a unique contribution to the management of frontline hospitality employees.

This study aims to introduce a vision-based model to generate droplets with auto-tuned parameters. The model can auto-adjust the inherent uncertainties and errors involved with the fabrication and operating parameters in microfluidic platform, attaining precise size and frequency of droplet generation.

The photolithography method is utilized to prepare the microfluidic devices used in this study, and various experiments are conducted at various flow-rate and viscosity ratios. Data for droplet shape is collected to train the artificial intelligence (AI) models.

Growth phase of droplets demonstrated a unique spring back effect in droplet size. The fully developed droplet sizes in the microchannel were modeled using least absolute shrinkage and selection operators (LASSO) regression model, Gaussian support vector machine (SVM), long short term memory (LSTM) and deep neural network models. Mean absolute percentage error (MAPE) of 0.05 and R² = 0.93 were obtained with a deep neural network model on untrained flow data. The shape parameters of the droplets are affected by several uncontrolled parameters. These parameters are instinctively captured in the model.

Experimental data set is generated for varying viscosity values and flow rates. The variation of flow rate of continuous phase is observed here instead of dispersed phase. An automated computation routine is developed to read the droplet shape parameters considering the transient growth phase of droplets. The droplet size data is used to build and compare various AI models for predicting droplet sizes. A predictive model is developed, which is ready for automated closed loop control of the droplet generation.

Based on affective event theory (AET), this study aims to unpack the association between team relationship conflict and employees’ subjective career success by examining the mediating role of negative emotions and the moderating role of emotional intelligence.

Using Mplus 8.1, the study analyzes multi-level, multi-wave data collected from 288 employees in 51 teams across Pakistan.

The results indicate that team relationship conflict is negatively associated with employees’ subjective career success, both in terms of career satisfaction and job satisfaction. While employees’ negative emotions partially mediate this negative relationship, emotional intelligence moderates the association between team relationship conflict and negative emotions, such that individuals with higher emotional intelligence experience less negative emotions.

This study advances career research by demonstrating how and when team relationship conflict is related to employees’ subjective career success. It also extends current understanding of the mediating and moderating mechanisms behind the association between team relationship conflict and employees’ subjective career success.