Search results

The trading expenses encountered domestically and across borders have a detrimental influence on global trade. Higher trade costs hamper trade and limit the benefits of trade liberalisation. The current research applies Novy's micro-founded trade cost measure (2013) to estimate global trade costs connected with Afghanistan, along with the factors that influence trade costs. Based on the investigation, trade in agriculture costs is significantly higher compared to the non-agricultural. As a consequence, focusing on agricultural trade facilitation would be advantageous.

Furthermore, enhancing and expediting trade facilities in trading areas are top priorities for government intervention to reduce trade costs. Focusing on free trade agreements and better shipment communication with trade partners increases transportation routes efficiently, cutting time and other expenses. The study proposes that the World Trade Organization's trade facilitation agreement be effectively implemented, administrative burdens at entry points minimised, non-tariff barriers (NTBs) be simplified and harmonised and soft infrastructures be established utilising current technologies.

Local governments use taxes on future increases in property values to pay for current economic development through tax incremental financing (TIF). TIF is a powerful tax tool used to spur improvements to a designated area. Proponents of TIF argue that it allows local governments to make investments without affecting previously established government and school district programs. Detractors argue that because the TIF designation denies existing overlapping districts (e.g., schools) the benefits of increases in property values, TIF can have a negative impact on a community. Empirical evidence on the economic and fiscal effects of TIF is mixed. This paper describes the potential costs and benefits associated with the use of TIF and then summarizes prior research on outcomes associated with this widely used property tax program.

Technology-enhanced learning (TEL), particularly in science, technology, engineering, arts, and math (STEAM), revolutionizes educational approaches by fostering active, transformative learning and expediting the learning process. TEL employs various tools like online courses, artificial intelligence (AI) technologies, virtual reality (VR), simulations, makerspaces, visual learning, and project-based learning, all contributing to accelerated learning in STEAM. A notable TEL innovation is the emergence of Large Language Models (LLMs) and AI chatbots, exemplified by the release of GPT-3 in December 2022. These tools utilize extensive parameters to generate natural language and perform tasks such as classification and prediction, thereby offering personalized and collaborative learning experiences essential for STEAM education. The generative pre-training transformer (GPT), a leading model in natural language processing (NLP), excels in generating human-like text and handling complex tasks like translation, summarization, and question answering. This chapter explores TEL environments that support transformative learning in STEAM, focusing on AI models. It reviews research on TEL’s impact on STEAM education, discussing the constructionism theory and emphasizing TEL’s role in creating engaging, student-centered learning experiences. However, challenges like technology access, instructor training, infrastructure, internet connectivity, and hardware resources are crucial. Additionally, the rise of AI brings ethical concerns regarding privacy, security, and potential biases in AI algorithms. Despite these hurdles, TEL’s potential to enhance STEAM learning experiences and accelerate the educational process is significant. By effectively implementing TEL strategies and leveraging LLMs and AI tools, educators can substantially improve learning outcomes in STEAM education.

Much research has explored high levels of son preference in India, finding that parents often report a desire for more sons than daughters. While scholars have noted that a nontrivial portion of respondents claim to have no sex preference, little is known about (1) the characteristics of this group and (2) how such parental preferences relate to child outcomes. We use data from a representative study of rural South Indian households (n = 7,891 adults) to address these gaps. Descriptive results show that a sizable portion of respondents – one in four – indicated that, at the start of their marriage, they had no preference for the number of daughters or sons they wanted. Further, multinomial regression results show that those who reported no sex preference at the time of marriage were more likely to be female, older, and less likely to be sterilized than those who reported equal or son preference, with additional distinctions across educational attainment and religion. Turning to child-level outcomes, we examined whether parents’ sex preferences related to adolescent mental health through ordinary least squares (OLS) regression models (n = 1,245 adolescents). Adolescents whose mothers stated no sex preference reported significantly fewer anxiety and depressive symptoms than their peers. Fathers’ sex preferences were not significantly related to adolescent mental health. These findings suggest that a lack of sex preference may hold meaningful and positive implications for adolescent mental health. Further, although son preference is a widespread phenomenon, singular attention on those with son preference may mask important nuances among Indian families.

This chapter clarifies the definition and reviews recent theories of consciousness, such as the dual systems framework, global workplace theory, and higher-order theory. Aspects of conscious experiences are useful in studying tourism decisionmaking, memory, emotions, tourism behaviour, and other topics related to tourism psychology. For instance, studies on conscious experiences of decisionmaking are useful to better understand destination choice and tourists' emotions elicitation, unconscious biases help to understand tourism attitude formation, while explicit and implicit cognition research provides insights to destination image attributes. Future studies may consider using objective and subjective methods of studying consciousness in the tourism context.

When making decisions about their future dream holidays, tourists often spend significant time thinking about future scenarios. This is an example of ‘mental time travel’, a process called prospection. The concept of prospection refers to human ability of ‘pre-experience’ the future and hence how that future ‘feels’, which is why it is sometimes called affective forecasting. There is a large volume of psychological research on prospection, but in applied fields, the use of various terms makes the current literature complex, disconnected and hard to navigate. This chapter provides an introduction to prospection as an underlying mechanism explaining some of the effects of experiential marketing. It discusses tourism prospection-related terms, errors of prospection and mental biases and ways to better manage tourist experiences.