The major goal of decisions made by a business organization is to enhance business performance. These days, owners, managers and other stakeholders are seeking for opportunities of modelling and automating decisions by analysing the most recent data with the help of artificial intelligence (AI). This study outlines a simple theoretical model framework using internal and external information on current and potential clients and performing calculations followed by immediate updating of contracting probabilities after each sales attempt. This can help increase sales efficiency, revenues, and profits in an easily programmable way and serve as a basis for focusing on the most promising deals customising personal offers of best-selling products for each potential client. The search for new customers is supported by the continuous and systematic collection and analysis of external and internal statistical data, organising them into a unified database, and using a decision support model based on it. As an illustration, the paper presents a fictitious model setup and simulations for an insurance company considering different regions, age groups and genders of clients when analysing probabilities of contracting, average sales and profits per contract. The elements of the model, however, can be generalised or adjusted to any sector. Results show that dynamic targeting strategies based on model calculations and most current information outperform static or non-targeted actions. The process from data to decision-making to improve business performance and the decision itself can be easily algorithmised. The feedback of the results into the model carries the potential for automated self-learning and self-correction. The proposed framework can serve as a basis for a self-sustaining artificial business intelligence system.
This study explores the feminization of poverty and the dynamics of the care economy in rural areas, focusing on the municipality of Génova, Quindío, Colombia. The novelty of this study lies in its analysis of the compounded effects of the COVID-19 pandemic on women’s economic participation and care responsibilities in a rural context, offering insights relevant to Latin America. This study addresses the critical problem of how increased caregiving responsibilities and labor informality during the pandemic have disproportionately impacted economically active women, exacerbating gender inequalities. The objective is to analyze the relationship between the care economy and feminization of poverty, providing policy recommendations for post-pandemic recovery in rural settings. The methodology consisted of a two-stage approach. In the first stage, a probabilistic stratified sampling design was applied using data from the Colombian National Population and Housing Census and the Génova, Quindío, and Colombia Municipal Panel. In the second stage, fieldwork was conducted with a sample of 347 women using the RedCap application for data collection. The results indicate a significant increase in unpaid domestic and caregiving work during the pandemic, particularly for the elderly, disabled, and children. Additionally, labor informality increased, further limiting economic opportunities for women. The key conclusion is that public policies aimed at reducing gender disparities in rural labor markets must prioritize caregiving support and formal employment opportunities for women. These findings suggest that addressing the care economy is crucial for closing gender gaps and fostering equitable economic recovery in rural Latin American areas.
The need for global energy conservation has become more urgent because of the negative effects of excessive energy use, such as higher fuel consumption, greater environmental pollution, and depletion of the ozone layer. There has been a significant increase in the demand for central and high-capacity household air conditioning systems in Muscat in recent years. The need for this is influenced by factors such as arid climate, increasing temperatures, air pollution, and population increase. As a result, there has been a significant increase in electricity use, putting a strain on power resources. To tackle this difficulty, the incorporation of solar collectors as supplementary thermal compressors in air conditioning systems offers a chance to utilise renewable energy sources. The objective of this hybrid technique is to enhance the effectiveness of cooling systems, hence minimising the need for electricity and lowering the release of environmental pollutants.
The COVID-19 pandemic has shifted education from traditional in-person classes to remote, online-dependent learning, often resulting in reduced learning effectiveness and satisfaction due to limited face-to-face interaction. To address these challenges, interactive teaching strategies, such as the flipped classroom approach, have gained attention. The flipped classroom model emphasizes individual preparation outside class and collaborative learning during class time, relying heavily on in-person interactions. To adapt this method to remote learning, the Remote Flipped Classroom (RFC) integrates the flipped classroom approach with online learning, allowing flexibility while maintaining interactive opportunities. RFC has incorporated short films as teaching tools, leveraging their ability to contextualize knowledge and cater to the preferences of visually-driven younger learners. However, research on the effectiveness of RFC with films remains limited, particularly in fields like nursing education, where practical engagement is crucial. This article shares the practical experience of applying RFC with films in a nursing education context. Positive feedback was observed, though many students still expressed a preference for in-person classes. These insights suggest that strategies like RFC with films could be valuable in maintaining engagement and learning efficiency in remote classrooms.
The study examines the economic and social impacts of a Southeast Asian multinational company operating in the northwestern region of Hungary, with a particular focus on the local labor market and community responses. The research aims to explore the company’s location choice motivations, its integration process into the local economy, and its cooperation with the local government and communities. The research provides a comprehensive picture of the company’s impacts by employing qualitative and quantitative methodologies—including management interviews and household surveys. The findings indicate that the company has significantly increased employment, enhanced infrastructure, and promoted cultural diversity. However, challenges related to cultural integration persist. The study offers valuable guidance for policymakers and businesses on leveraging the economic benefits of foreign investments and fostering cultural cooperation. Future research could delve deeper into the long-term socio-economic impacts.
This study aims to explore the factors influencing people’s intention to use home fitness mobile apps in the post-pandemic era. By incorporating the perspective of playfulness into the decomposed theory of planned behavior, it seeks to construct a behavioral model for the public's use of AR sports games for home exercise. The research focuses on Active Arcade users residing in Taiwan, employing the snowball sampling method to conduct an online questionnaire survey. A total of 340 valid questionnaires were collected and analyzed using linear structural equations. The study reveals three main findings: first, the behavioral model for Active Arcade users constructed based on the decomposed theory of planned behavior demonstrates a good fit; second, users’ attitudes, subjective norms, and perceived behavioral control have a positive and significant impact on behavioral intention; third, perceived usefulness, perceived ease of use, and perceived playfulness all positively and significantly influence attitudes, with perceived playfulness having the highest impact coefficient; fourth, perceived benefits of exercise are the most crucial factor affecting subjective norms; and fifth, convenience technologies are the key factor influencing perceived behavioral control. This study provides valuable insights for theory and management practice, offering guidance on the use of home fitness apps in the post-pandemic era while addressing research limitations and suggesting future directions.
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