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The response of the receiver to a voiced patient safety concern is frequently cited as a barrier to health professionals speaking up. The authors describe a novel Receiver Mindset Framework (RMF) to help health professionals understand the importance of their response when spoken up to.

The framework draws on the broader receiver-focussed literature and integrates innovative findings from a series of empirical studies. These studies examined different receiver behaviour within vignettes, retrospective descriptions of real interactions and behaviour in a simulated interaction.

The authors' findings indicated that speaking up is an intergroup interaction where social identities, context and speaker stance intersect, directly influencing both perceptions of and responses to the message. The authors' studies demonstrated that when spoken up to, health professionals poorly manage their emotions and ineffectively clarify the speaker's concerns. Currently, targeted training for receivers is overwhelmingly absent from speaking-up programmes. The receiver mindset framework provides an evidence-based, healthcare specific, receiver-focussed framework to inform programmes.

Grounded in communication accommodation theory (CAT), the resulting framework shifts speaking up training from being only speaker skill focussed, to training that recognises speaking up as a mutual negotiation between the healthcare speaker and receiver. This framework provides healthcare professionals with a novel approach to use in response to speaking up that enhances their ability to listen, understand and engage in point-of-care negotiations to ensure the physical and psychological safety of patients and staff.

This chapter presents a spiritual or wisdom-based approach to development, its rationale, conceptualization, methods and examples of applications. The politics of being proposes that societies explicitly make the fulfillment (‘being’) of all its members – humans and non-humans – their main goal, which should guide the development and implementation of public policies. It stands in opposition to the current development paradigm focused on economic growth or ‘having’, and rooted in a set of modern western values – individualism, materialism, reductionism, anthropocentrism, etc. By nourishing our relational nature, the politics of being can address the root causes of the meta crisis the world is facing, reconciling human flourishing with sustainability and supporting the cultural evolution that is needed. It proposes a dialogue between wisdom and science, the two main areas of knowledge, to guide its design and implementation. It conceptualizes ‘being’ as the actualization of our truest ‘being’ and our highest ‘being’. This means that societies should provide the right conditions for their human members to express themselves and fulfil their healthy aspirations, as well as to develop human virtues and qualities. Wisdom traditions and spiritual teachings offer relevant insights into the nature of human fulfilment and the process of spiritual evolution that can be applied to societies. They emphasize the cultivation of spiritual values and qualities such as love, peace, happiness, life, mindfulness, mystery and the understanding of interconnectedness. In recent decades, these qualities have become areas of scientific research and been at the core of social change and development initiatives. Together they can serve as the foundations of the politics of being and allow to identify actionable public policy agendas in many sectors mainly based on existing examples.

The study aims to explore ‘motivational climate', which designs the recurring patterns associated with employees' attitudes, behaviour, and feelings. If organizations successfully adopt a motivational climate, such climate influences the performance and behavior of employees to a great extent. Responsible leadership plays a constructive role in injecting a motivational climate in an organization to ensure information flow. In a motivational climate, top management or leaders reward their employees for individual progress, improvement and mastery. Knowledge sharing is supported in a mastery climate because such a climate can reduce the motive of knowledge hiding and instead further help in stimulating creativity.

Study was to scrutinize a moderated-mediation model, a quantitative hypothetic deductive approach to verify the hypotheses of the study. The data were gathered from employees and supervisors of advertising agencies and marketing departments in metropolitan cities of Punjab, Pakistan. Such firms and departments are considered because they offer a great opportunity to relevant variables and their relations. These organizations and departments are the most creativity-seeking domains and involve frequent interactions (for instance, regular meetings) between leaders with their employees and among peers. Data were primarily gathered from managerial employees performing their duties in the areas mentioned above.

Current study reveals that RL has a positive and significant relation with employee creative behaviour. Increasing RL characteristics can ultimately boost employee performance in the creativity domain. Being a responsible leader becomes mandatory for leaders to foster employee creativity to maintain the sustainability of an organization. It is confirmed from the results that responsible leadership articulates the mind thinking of employees, which creates an open environment of information while persuading creative and similar behaviour.

The current research investigates how responsible leadership can efficiently leverage the stakeholder approach in influencing employees through a knowledge-based pathway to boost their creative behaviour. The current study tends to uncover the mediating effect of the basic construct of knowledge management, which is knowledge sharing. Knowledge sharing enables employees to exchange their information while creating mutual understanding, which helps in the smooth flow of knowledge within the organization; this flow enriches employees to think openly in a creative and appreciative environment.

The choice of crops to produce at a location depends to a large degree on the climate. As the climate changes and food demand evolves, farmers may need to produce a different mix of crops. This study assesses how much cropland may be subject to such upheavals at the global scale, and then focuses on China as a case study to examine how spatial heterogeneity informs different contexts for adaptation within a country.

A global agricultural economic model is linked to a cropland allocation algorithm to generate maps of cropland distribution under historical and future conditions. The mix of crops at each location is examined to determine whether it is likely to experience a major shift.

Two-thirds of rainfed cropland and half of irrigated cropland are likely to experience substantial upheaval of some kind.

This analysis helps establish a global context for the local changes that producers might face under future climate and socioeconomic changes. The scale of the challenge means that the agricultural sector needs to prepare for these widespread and diverse upheavals.

This paper aims to map the antecedents and precursory contexts regarding the four principles of management. Moreover, a description of its codification and coalescence as a unified teaching framework is provided, critically reviewing key theoretical underpinnings of management principles in academic research and management textbooks.

A historiographic approach reviewed seminal works for theory origins of the four principles of management, by analyzing 260 management textbooks from 1935 to 2013 to document their adoption in management education. This study used critical hermeneutics (Prasad, 2002) to explore the framework’s progression by providing the context of cultural, political and economic influences.

This research study tracked and mapped the creation of the four principles of management, as it became the commonly accepted teaching framework in management education. Today, every predominant management principles textbook uses the four principles of management – plan, lead, organize and control – as the basis for teaching students.

There is limited research on the application of the four principles of management in contemporary management, despite its ubiquity in management education. The study’s historical account of its formation provides insights into its adoption and utilization in modern education context. The study’s primary limitation stems from the generalization of the representative sample of textbooks used in the study (1917–2013). However, data saturation was achieved for the scale of textbooks and writings which was reviewed.

Through a critical analysis into the formation of the four principles of management, this research not only provides a historical account of its construction but, as importantly, the influencing factors that led to its development. This research fills a gap in critical literature, as a post mortem exegesis has never been conducted on the four principles of management in the afteryears of its amalgamation.

The negative influence of gamification on online communities has received little attention in the available literature. The study examines the adverse effects of gamification during engaging in online communities.

Gap-spotting methods were used to develop the research questions, followed by model development using the social exchange and social-network theories. Data were collected from 429 samples. The study applied partial least squares structural equation modeling to test the research hypotheses followed by ANN application.

The study identified five factors related to gamification that have a significant adverse effect on the mental and emotional well-being of the users. Furthermore, the results of PLS-SEM were then compared through an artificial neural network (ANN) analytic process, revealing consistency for the model. This research presents a theoretical contribution by providing critical insights into online gamers' mental and emotional health. It implies that gamification can even bring mental and emotional disturbance. The resulting situation might lead to undesirable social consequences.

The result highlights the managerial and social relevance from the perspective of a developing country. As respondents are becoming more engrossed in online gaming, managers and decision-makers need to take preventive measures to overcome the dark side of online gaming.

The present study shows that the dark side of gamification has some adverse effects on human mental and emotional health. The study's findings can be used to improve gamification strategies while engaging online communities.

Web users rely heavily on online content make decisions without assessing the veracity of the content. The online content comprising text, image, video or audio may be tampered with to influence public opinion. Since the consumers of online information (misinformation) tend to trust the content when the image(s) supplement the text, image manipulation software is increasingly being used to forge the images. To address the crucial problem of image manipulation, this study focusses on developing a deep-learning-based image forgery detection framework.

The proposed deep-learning-based framework aims to detect images forged using copy-move and splicing techniques. The image transformation technique aids the identification of relevant features for the network to train effectively. After that, the pre-trained customized convolutional neural network is used to train on the public benchmark datasets, and the performance is evaluated on the test dataset using various parameters.

The comparative analysis of image transformation techniques and experiments conducted on benchmark datasets from a variety of socio-cultural domains establishes the effectiveness and viability of the proposed framework. These findings affirm the potential applicability of proposed framework in real-time image forgery detection.

This study bears implications for several important aspects of research on image forgery detection. First this research adds to recent discussion on feature extraction and learning for image forgery detection. While prior research on image forgery detection, hand-crafted the features, the proposed solution contributes to stream of literature that automatically learns the features and classify the images. Second, this research contributes to ongoing effort in curtailing the spread of misinformation using images. The extant literature on spread of misinformation has prominently focussed on textual data shared over social media platforms. The study addresses the call for greater emphasis on the development of robust image transformation techniques.

This study carries important practical implications for various domains such as forensic sciences, media and journalism where image data is increasingly being used to make inferences. The integration of image forgery detection tools can be helpful in determining the credibility of the article or post before it is shared over the Internet. The content shared over the Internet by the users has become an important component of news reporting. The framework proposed in this paper can be further extended and trained on more annotated real-world data so as to function as a tool for fact-checkers.

In the current scenario wherein most of the image forgery detection studies attempt to assess whether the image is real or forged in an offline mode, it is crucial to identify any trending or potential forged image as early as possible. By learning from historical data, the proposed framework can aid in early prediction of forged images to detect the newly emerging forged images even before they occur. In summary, the proposed framework has a potential to mitigate physical spreading and psychological impact of forged images on social media.

This study focusses on copy-move and splicing techniques while integrating transfer learning concepts to classify forged images with high accuracy. The synergistic use of hitherto little explored image transformation techniques and customized convolutional neural network helps design a robust image forgery detection framework. Experiments and findings establish that the proposed framework accurately classifies forged images, thus mitigating the negative socio-cultural spread of misinformation.