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Customizing a mass appraisal model for residential property tax assessment: a hedonic regression approach in Bahir Dar city, Ethiopia

PurposeThe paper aims to estimate the house rental values for the purpose of customizing mass appraisals in Bahir Dar City, Ethiopia. It seeks to identify the critical factors affecting the rental values of residential properties and customize a mass appraisal model for such properties. The study focuses on identifying attributes that significantly affect house rental values.Design/methodology/approachThe paper adopted a survey research design, utilizing a survey questionnaire, expert group discussion and document analysis. The data were analyzed using thematic, descriptive and inferential statistical analysis, including correlation and hedonic regression analysis.FindingsAmong the variables included in the model, the number of rooms, availability of schools, land value grading, type of nearest road, housing typology, built-up area, plot area, walling material, traveling cost and fencing materials were the most significant factors for predicting the annual rental value of residential properties in the city.Research limitations/implicationsThe findings of this study will provide valuable insights to tax assessors, property owners and local government authorities, including municipalities, concerning the key determinants of the rental values of residential properties. Besides, these findings will serve as a useful tool for valuers and researchers in the field of property value modeling.Originality/valueThis study represents the first attempt to develop a framework for mass appraisal of residential properties using annual rental values in the Ethiopian context.

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Green human resource management and corporate social responsibility as drivers of organizational performance: mediating effects of employee engagement and corporate reputation in Vietnam

Purpose This study aims to investigate the relationship between green human resource management (GHRM), corporate social responsibility (CSR) and organizational performance (OP) of small- and medium-sized enterprises (SMEs) by examining corporate reputation (CR) and employee engagement (EE) as mediators in Vietnam. Design/methodology/approach This study used the quantitative method with 458 valid responses from mid- to senior-level managers and chief executive officers (CEOs) were obtained and used for data analysis. To analyze and explore the relationships between constructs and mediators, SmartPLS version 4.0 structural equation modeling was used to analyze the data of the SMEs of Vietnam in 2023. Findings The results showed strong and positive relationships between GHRM, CSR and OP in SMEs, with CR and EE serving as significant mediators. Originality/value This research provides new insights into how GHRM and CSR enhance OP by using an integrated model that examines how CR and EE mediate this relationship. It demonstrates that businesses implementing GHRM and CSR can promote sustainable development among stakeholders, leading to improved OP in Vietnam’s dynamic economic environment. The findings have practical implications for executives and managers, emphasizing the need to balance stakeholder, environmental and social interests to optimize GHRM and CSR initiatives and foster sustainable growth. This study’s insights could significantly influence SMEs in the Vietnamese economy.

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A.S. PUSHKIN AND MIKHAILOVSKOYE IN CRITICAL ARTICLES BY V.YA. KURBATOV

The article is the first registered attempt to comprehend the perception of A.S. Pushkin and the role of Mikhailovskoye in Pushkin’s inner spiritual life by V.Ya. Kurbatov (1939–2021), the well-known literary critic. The material for research is the critic’s articles and notes from the period of 1990–2010 collected in his book “Pushkin for Every Day” that make up his myth about the national poet. In this article the author demonstrates that it is the national idea that becomes the background for the interpretative angle of Kurbatov’s critical reflection in the epoch of self-identification. Being the unconditional value reference point for the critic, Pushkin is perceived by him as the benchmark for integrity and completeness as well as Mikhailovskoye is seen as the place where the comprehensiveness of the Russian life can be found yet at the same time being the reproach to the contemporaries for their duality and spiritual “emigration”. The specifics of V.Ys. Kurbatov’s position is conditioned by his triune religious, philosophic and literary approach to the phenomena of the Russian culture, on one hand, and by his subjective method together with his personal, individual view and his search for self-identity, on the other hand. In this article the author makes the conclusion that the articles and notes of V.Ya. Kurbatov about A.S. Pushkin written in line with the religious and philosophic interpretations of the national poet in XIX–XX centuries, reveal the deep and unique personality, ethical standpoint and aesthetic views of our famous contemporary.

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Investigating the Performance of Data-Driven Ensemble Machine Learning Models in Preliminary Designing Multi-Stage Friction Pendulum Bearings

Over the last few decades, the field of base isolation systems has demonstrated enormous advancements through the innovation of novel systems, and there has been an enhancement in the performance of structures equipped with isolation under conditions of moderate and severe seismic activity. One of the most important systems is the multi-stage friction pendulum, which offers a spectrum of effective pendulums across different regimes, thereby achieving enhanced capability for energy dissipation. The difficulty in designing these bearings at the preliminary stage comes from the fairly long process of trials and errors in selecting the properties of each sliding surface so that the required effective period, effective damping, and displacement capacities are achieved. This study investigates the performance of various data-driven ensemble machine learning models in directly designing multi-stage friction pendulum bearings. Within the context of the analysis, the most recent generation of friction pendulum that has been introduced to the literature, the quintuple friction pendulum, is used as the investigation employs a case to assess the dependability of the design strategy and the efficacy of a multi-output machine learning techniques. In general, the findings of this study have shown that machine learning models provide an accurate way to directly design quintuple friction pendulum isolators and attain the necessary properties of the isolators. The practicality of this research lies in highlighting how machine learning can be applied to considerably expedite the design and optimization of multi-stage friction pendulum bearings and in defining the most suitable machine learning technique to adopt in such tasks.

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