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Artificial intelligence (AI) is a growing paradigm and has made considerable changes in many fields of study, including medical education. However, more investigations are needed to successfully adopt AI in medical education. The purpose of this study was identify the determinant factors in adopting AI-driven technology in medical education.

This was a descriptive-analytical study in which 163 faculty members from Tabriz University of Medical Sciences were randomly selected by nonprobability sampling technique method. The faculty members’ intention concerning the adoption of AI was assessed by the conceptual path model of task-technology fit (TTF).

According to the findings, “technology characteristics,” “task characteristics” and “TTF” showed direct and significant effects on AI adoption in medical education. Moreover, the results showed that the TTF was an appropriate model to explain faculty members’ intentions for adopting AI. The valid proposed model explained 37% of the variance in faulty members’ intentions to adopt AI.

By presenting a conceptual model, the authors were able to examine faculty members’ intentions and identify the key determining factors in adopting AI in education. The model can help the authorities and policymakers facilitate the adoption of AI in medical education. The findings contribute to the design and implementation of AI-driven technology in education.

The finding of this study should be considered when successful implementation of AI in education is in progress.

This paper aims to extend insights about the relationship between inter-organizational collaboration and approaches to control from the perspective of decision-makers. We investigate the relationship between approaches to control and intended forms of integration between actors responsible for solving the complex problem of integrated person-centered care for elderly with diverse and significant needs.

The empirical study is based on a content analysis of contractual agreements. We have analyzed a total of 118 collaboration agreements and associative documents between all Swedish regions and municipalities.

The study shows that intended integration is subject to remarkable variation in intended forms of inter-organizational collaboration in this Swedish case. The paper illustrates that decision-makers’ intentions with proposed collaboration in each given context are important for the chosen approach to control. Regardless of intended forms of integration, our study suggests that an imminent soft approach to control is expressed alongside limited signs of hard control. Various forms of intended integration can be managed by the two approaches simultaneously insofar as the agreements appear to have a two-sided purpose.

Our paper proposes an empirically driven taxonomy of intended forms of integration initiatives. The taxonomy provides resources for studies about how collaboration can be managed when it is stipulated by national legislation but local self-governance gives actors considerable freedom to decide on how to organize and manage services. By presenting the taxonomy and relating this to approaches of control, our iterative study builds on and adds to a recent stream of research arguing that the relationship between collaboration and approaches to control may by fuzzier and more complex than originally thought.

This paper aims to identify and report the differential effects of activity control and capability control on role stressors, which subsequently affect salespeople’s job satisfaction and sales performance.

Drawing on job demands-resources (JD-R) theory, the authors defined active control and customer demandingness as the job demands and capability control as the job resource, and designed their relationship with role stressors, which are indicated as role ambiguity, role conflict and role overload. The authors enrolled a sample of 223 industrial salespeople from pharmaceutical companies. After collecting the data, the authors used structural equation modeling using AMOS to test and estimate causal relationships along with a two-step approach to examine the interaction effect. The authors have also tested the simple slope of two-way interactions. All of the measured variables were identical to those used in previous studies.

The study findings indicate that behavior-based control can be counterproductive. Reducing activity control can decrease role stress, increase job satisfaction and improve job performance; increasing capability control, however, can reduce role stress and increase job satisfaction and performance. It is also important to acknowledge the external environment of the sales context in which behavior-based control is most effective: whereas high customer demandingness and capability control are related to reduced role stress, high customer demandingness and activity control are related to increased role stress.

Sales managers should recognize that different control management regimes reinforce or mitigate salespeople’s job stressors and outcomes under specific conditions (i.e. work environments marked by higher or lower customer demandingness).

Drawing on JD-R theory, the research shows that a behavior control (i.e. activity control and capability control) has differential, and even opposite, psychological consequences.

This study examines the social acceptance and potential for residential solar integration in Abu Dhabi to support sustainable urban innovation and prosperity. A survey of 216 Abu Dhabi residents analyzed four scenarios for incentivizing household solar panel adoption. Results demonstrate high interest and preference for governmental financial support mechanisms to spur solar integration. This research contributes an assessment framework and citizen engagement insights that could inform smart city development strategies focused on renewable energy transformation across the Gulf region. As urban centers like Abu Dhabi strive to enact their visions for economic diversification and environmental sustainability, understanding citizen perspectives on innovations like distributed solar will be critical to align technology advancement with societal needs and values. The methodology and findings of this Abu Dhabi case study provide a model to catalyze stakeholder buy-in for new energy solutions, with potential applications for other Gulf cities aiming to transition their energy systems and build integrative renewables infrastructure to power next-generation smart development. This solar integration acceptance research lays the groundwork for continued scholarly discourse and policymaker collaboration around smart cities in the Gulf that realize multidimensional progress for society, economy, and environment.

A “state-driven” approach suggests that colonists use census categories to rule. However, a “society-driven” approach suggests that this state-driven perspective confers too much power upon states. A third approach views census-taking and official categorization as a product of state–society interaction that depends upon: (a) the population's lay categories, (b) information intellectuals' ability to take up and transform these lay categories, and (c) the balance of power between social and state actors. We evaluate the above positions by analyzing official records, key texts, travelogues, and statistical memoirs from three key periods in India: Indus Valley civilization through classical Gupta rule (ca. 3300 BCE–700 CE), the “medieval” period (ca. 700–1700 CE), and East India Company (EIC) rule (1757–1857 CE), using historical narrative. We show that information gathering early in the first period was society driven; however, over time, a strong interactive pattern emerged. Scribes (information intellectuals) increased their social status and power (thus, shifting the balance of power) by drawing on caste categories (lay categories) and incorporating them into official information gathering. This intensification of interactive information gathering allowed the Mughals, the EIC, and finally British direct rule officials to collect large quantities of information. Our evidence thus suggests that the intensification of state–society interactions over time laid the groundwork for the success of the direct rule British censuses. It also suggests that any transformative effect of these censuses lay in this interactive pattern, not in the strength of the British colonial state.

Most scientific research has focused on understanding Ponzi schemes from the point of view of the schemes and their operators, based on qualitative analysis. This paper aims to analyze Ponzi schemes from the perspective of their investors, emphasizing behavioral aspects, which have been little explored in the scientific literature, especially in quantitative research. In this way, the authors sought to understand the effects of heuristics and cognitive biases in understanding investor behavior.

A logistic regression was carried out with Brazilian investors, some of them participants in Ponzi schemes, who answered a structured questionnaire by means of a survey.

The authors found that social pressures, overconfidence and deliberate ignorance lead to credulity, generating little risk analysis and the desire to make a lot of money quickly.

Helping investors improve their levels of information through financial education and self-knowledge about their behavior. Contribute to the competent authorities in the search for improvements in the information displayed to investors.

Understanding the mechanisms used when making a financial decision from the point of view of investors in general, but especially those exposed to Ponzi schemes, has the mission of enlightening them about the importance of financial education and the weight of psychological factors so that they can reduce the effects of heuristics and analysis biases when faced with a financial decision.

The basis of this work will be the inclusion of psychological variables and financial education, adapting existing models in an attempt to demonstrate the effects they may or may not have on mental accounting in the specific case of investors

Hazing, a practice where existing group members subject newcomers to humiliation, embarrassment or abuse, is often perceived as either violent or harmless fun. Regardless of its nature, all forms of hazing carry a significant risk of harm. The dual-factor model of mental health provides a framework for understanding this harm. This model posits that mental health and mental illness, while related, are not identical. In other words, individuals need more than just the absence of mental illness to thrive; they also require positive mental health. This chapter seeks to apply the dual-factor model to the context of hazing. It will first introduce the model of mental health, followed by an exploration of how violent hazing can potentially lead to mental illness. It will also examine how hazing, even when perceived as harmless fun, can result in languishing mental health. This chapter will conclude with recommendations and strategies to foster safe and caring organisational environments. The goal is to create spaces where all members can participate and flourish without the fear of harm, thereby promoting both individual and collective well-being.

The emergence of smart cities, metropolises that integrate physical infrastructure, digital technology, and data analytics, and that focus on urban sustainability, have profoundly changed urban development. In the modern digital era, robust infrastructure has become an indispensable catalyst for urban advancement. Kuwait is dedicated to the integration of diverse renewable energy technologies in the development of smart cities that enhance energy security, promote innovation, and contribute to global climate change mitigation efforts. Focusing on smart cities within Gulf Cooperation Council (GCC) countries, a review is presented of how successfully they have effectively combined technology, infrastructure, and sustainability to serve as models for new global and regional developments. Insights into what makes a city smart are provided in different settings.

This chapter explains the phenomenon of artificial intelligence (AI) powered by big data in technology and its contribution in knowledge-based marketing in B2B and its impact on rational decision-making in B2B marketing that affects business performance. This chapter is literature review prepared by compiling and reviewing previous literature, studies, articles, books and other sources related to the contribution of big data-enabled AI to B2B marketing. According to the information analysed, the findings show that big data supported by AI plays a significant role in creating user knowledge, external knowledge and customer knowledge, all of which are factors that significantly influence the ability of business-to-business marketers to make rational decisions that affect the performance of their companies. This chapter explains to them the phenomena of AI powered by big data and its effect on B2B marketing rational decision that will enhance company performance and its contribution on knowledge-based marketing in B2B. This chapter contributes to understanding main functions and interactions of AI system powered by big data and how such a system helps in B2B marketing by generating knowledge about customers, users and markets.