Hasil untuk "Real estate business"

Benjamin Kwakye, Alexander Sasu, Stephen Ameyaw et al.

Previous studies have concluded that models that account for nonlinear relationships outperform their linear counterparts. However, while this is evident in advanced economies, the same cannot be inferred in Sub-Saharan Africa. This paper seeks to show how house prices are responsive to the nonlinear shocks of selected macroeconomic indicators, while controlling for the effects of interest rate and population in the Kenyan housing market. We employed the Nonlinear Autoregressive Distributed Lag (NARDL) model on a quarterly dataset from 2004Q1 to 2021Q4. In the long run, we showed that house prices respond to some nonlinear shocks of macroeconomic indicators, particularly shocks of the exchange rate and the shock of the market index, but not inflationary rate. Moreover, we established a significant negative effect of interest rate and population on house prices. In the short run, we also noted that a decrease in the exchange rate influences house prices negatively. Interest rate, including its lag terms, also impacts house prices negatively. These findings call for prudent macro-prudential policies, more importantly: (a) management of exchange rate and interest rate; (b) give property investment insight and (c) offer effective policy direction in the development and sustenance of the Kenyan property market.

Sandra Barragán, Adrián Pérez-Bote, Carlos Sáez et al.

We provide a description of pilot and production experiences to streamline some business functions in the official statistical production process using statistical learning models. Our approach is quality-oriented searching for an improvement on accuracy, cost-efficiency, timeliness, granularity, response burden reduction, and frequency. Pilot experiences have been conducted with data from real surveys in Statistics Spain (INE).

Hongyang Yang, Likun Lin, Yang She et al.

Enterprise Resource Planning (ERP) systems serve as the digital backbone of modern financial institutions, yet they continue to rely on static, rule-based workflows that limit adaptability, scalability, and intelligence. As business operations grow more complex and data-rich, conventional ERP platforms struggle to integrate structured and unstructured data in real time and to accommodate dynamic, cross-functional workflows. In this paper, we present the first AI-native, agent-based framework for ERP systems, introducing a novel architecture of Generative Business Process AI Agents (GBPAs) that bring autonomy, reasoning, and dynamic optimization to enterprise workflows. The proposed system integrates generative AI with business process modeling and multi-agent orchestration, enabling end-to-end automation of complex tasks such as budget planning, financial reporting, and wire transfer processing. Unlike traditional workflow engines, GBPAs interpret user intent, synthesize workflows in real time, and coordinate specialized sub-agents for modular task execution. We validate the framework through case studies in bank wire transfers and employee reimbursements, two representative financial workflows with distinct complexity and data modalities. Results show that GBPAs achieve up to 40% reduction in processing time, 94% drop in error rate, and improved regulatory compliance by enabling parallelism, risk control insertion, and semantic reasoning. These findings highlight the potential of GBPAs to bridge the gap between generative AI capabilities and enterprise-grade automation, laying the groundwork for the next generation of intelligent ERP systems.

Liyang Zhao, Olurotimi Seton, Himadeep Reddy Reddivari et al.

The sales process involves sales functions converting leads or opportunities to customers and selling more products to existing customers. The optimization of the sales process thus is key to success of any B2B business. In this work, we introduce a principled approach to sales optimization and business AI, namely the Causal Predictive Optimization and Generation, which includes three layers: 1) prediction layer with causal ML 2) optimization layer with constraint optimization and contextual bandit 3) serving layer with Generative AI and feedback-loop for system enhancement. We detail the implementation and deployment of the system in LinkedIn, showcasing significant wins over legacy systems and sharing learning and insight broadly applicable to this field.

Sergey Yurievich Sedakov

В статье рассматриваются концептуальные представления об имущественном праве, в частности, о недвижимости, которые высказывались видными цивилистами различных эпох, а также получили свое отражение в законодательстве России конца ХIХ – начала ХХI в. Несмотря на временное забвение гражданско-правовой системой вещного права, в статье констатируется отход российской правовой теории и законодательства от общепринятых классических представлений о множественности объектов недвижимости. Закономерным продолжением развития концептуальных представлений о вещном праве является современный Гражданский кодекс Российской Федерации. Высказывается мнение о дальнейшем магистральном развитии законо­дательства в части недвижимости и вещного права в целом. Один из путей — это реализация Концепции развития законо­дательства о вещном праве, которая была разработана виднейшими российскими цивилистами. Концепция развивается и претерпевает изменения, но тем не менее поэтапно внедряется в гражданско-правовую систему. Концепция предполагает расширение круга ограниченных вещных прав, в частности, реализацию принципа единства судьбы земельного участка и находящихся на нем строений. В правовой и правоприменительной среде множественность объектов недвижимости породила проблему незарегистрированных строений (самовольных построек). Последнее изменение статьи 222 Гражданского кодекса РФ о самовольных постройках имело место в 2018 г. (редакция Федерального закона от 03.08.2018 № 339-ФЗ) и в настоящее время получило обширную судебную практику. Судебные дела рассматривались как Верховным судом Российской Федерации, так и Конституционным судом. Рассмотрение судами спорных вопросов в связи с самовольными постройками неизменно требует назначения судебной строительно-­технической экспертизы. Судебная строительно-техническая экспертиза, как правило, является одним из основополагающих доказательств при вынесении судом решения по делу, однако имеют место случаи, когда судебный акт принимается вопреки либо независимо от экспертного заключения. Рассмотрены конкретные судебные споры, разрешение которых состоялось независимо от выводов назначенных судебно-технических экспертиз, окончательное решение по которым принималось Верховным судом РФ.

Pilarczyk Aleksandra, Kondak Anna, Grzelka Kornelia et al.

It has long been established that people attach value to window views. However, the challenge in real estate market analyses is to capture what landscape features an attractive view contains and thus how they affect the worth (individual valuation) of the real estate. Real estate research predominantly uses questionnaires to analyze the perception of the landscape. This research assesses the possibilities of using eye-tracking as an objective tool for the assessment of the visual perception of the landscape. The research aim was achieved by comparing the results of subjective surveys with a qualitative analysis of the records of gaze patterns of participants observing on-screen photos of window views. All analyses concerned the urban landscape. Surveys show that natural areas are the most attractive for potential residential buyers, while the most undesirable are industrial window views. Participants of the eye-tracking study focused their attention on details such as distinctive buildings, construction machinery, road signs and traffic lights, advertisements, graffiti, murals, street lamps and electrical boxes. These undesirable details can obscure the entirety of even the most aesthetically pleasing landscape. Thus, the results of this study are expected to inform those involved in urban design to minimize the impact of such obstructions.

Sanchaniya Rashmi Jaymin, Černeckienė Jurgita, Gudumasu Naga Shilpa et al.

This study examines the adaptive reuse of properties for the development of social housing, focusing on the benefits, challenges, and best practices associated with this approach. Through a comprehensive literature review and analysis of case studies, the research investigates how adaptive reuse can address housing shortages while promoting sustainable urban development. The study identifies key economic, environmental, and social benefits of adaptive reuse in social housing, including cost savings, reduced environmental impact, and community revitalisation. It also explores the technical, financial, regulatory, and social challenges often arising in such projects. The research presents a detailed analysis of successful adaptive reuse case studies, highlighting effective strategies to overcome common obstacles. Based on these findings, the study proposes a set of best practices for planning, designing, and implementing adaptive reuse projects in social housing. The paper concludes with policy recommendations and suggestions for future research, highlighting the potential of adaptive reuse to contribute significantly to sustainable and inclusive urban housing solutions.

Azariy Abramovich Lapidus, Liubov Andreevna Adamtsevich

Современные проекты комплексного развития территорий характеризуются технологической, организационной и ин- формационной сложностью. Технологические вызовы включают интеграцию разнородных систем и обеспечение устойчивости объектов, организационных — полную координацию участников проекта иинформационных — обработку значительных объемов данных в условиях необходимости оперативного принятия решений. В этойсвязи особую актуальность имеет вопрособеспечения сквозного управления жизненным циклом объектов и согласованности решений для эффективного использования ресурсов. Целью исследования является анализ цифровых технологий для оптимизации управления жизненным циклом жилых зданий и объектов инфраструктуры в проектах комплексного развития территорий. В рамках представленного исследования проведен анализ публикаций по ключевым словам, определенным авторами в контексте рассматриваемой темы. Базой формирования выборок по ключевым словам стала международная база Scopus. Проведенный анализ демонстрирует, что внедрение циф­ровых двойников, IoT, BigData, BIM и машинного обучения позволяет достичь значительной оптимизации при управлении жизненным циклом объектов жилой и инженерной инфраструктуры в проектах комплексного развития территорий. Цифровая трансформация принципиально меняет подход к управлению жизненным циклом, переводя его от реактивного к прогнозному и адаптивному, что обеспечивает устойчивость, надежность и безопасность объектов, экономию ресурсов и повышение качества городской среды.

Aghimien Douglas, Aghimien Emmanuel, Aigbavboa Clinton et al.

This study explores the concept of digital partnering among construction organisations, focusing on the essential factors that contribute to successful partnerships and their impact on achieving digital transformation. To gather quantitative data, a survey was conducted with construction professionals engaged in projects throughout South Africa. The data analysis employed a comprehensive six-step methodology, including mean item scoring, Kruskal- Wallis H-Test, exploratory factor analysis (EFA), and multiple linear regression (MLR). The findings from the EFA indicated that the effectiveness of digital partnering hinges on three critical elements: a supportive partnering environment, trust and mutual understanding, and management support. The MLR analysis further validated these factors as crucial for attaining digitally transformed construction organisations. Given the competitive and often adversarial nature of the construction industry in developing countries like South Africa, the study recommends that organisations pursue collaborative partnerships both within and outside the industry to facilitate digital transformation. This can be achieved by fostering an environment that nurtures trust, understanding, and strong management support for developing digital capabilities through collaboration. The study offers empirical insights into the key factors necessary for successful digital partnering, an area that has been largely overlooked in discussions surrounding construction digitalisation.

Roy Abitbol, Eyal Cohen, Muhammad Kanaan et al.

As artificial intelligence (AI) continues to rapidly advance, there is a growing demand to integrate AI capabilities into existing business applications. However, a significant gap exists between the rapid progress in AI and how slowly AI is being embedded into business environments. Deploying well-performing lab models into production settings, especially in on-premise environments, often entails specialized expertise and imposes a heavy burden of model management, creating significant barriers to implementing AI models in real-world applications. KModels leverages proven libraries and platforms (Kubeflow Pipelines, KServe) to streamline AI adoption by supporting both AI developers and consumers. It allows model developers to focus solely on model development and share models as transportable units (Templates), abstracting away complex production deployment concerns. KModels enables AI consumers to eliminate the need for a dedicated data scientist, as the templates encapsulate most data science considerations while providing business-oriented control. This paper presents the architecture of KModels and the key decisions that shape it. We outline KModels' main components as well as its interfaces. Furthermore, we explain how KModels is highly suited for on-premise deployment but can also be used in cloud environments. The efficacy of KModels is demonstrated through the successful deployment of three AI models within an existing Work Order Management system. These models operate in a client's data center and are trained on local data, without data scientist intervention. One model improved the accuracy of Failure Code specification for work orders from 46% to 83%, showcasing the substantial benefit of accessible and localized AI solutions.

Laura Minkova, Jessica López Espejel, Taki Eddine Toufik Djaidja et al.

As businesses increasingly rely on automation to streamline operations, the limitations of Robotic Process Automation (RPA) have become apparent, particularly its dependence on expert knowledge and inability to handle complex decision-making tasks. Recent advancements in Artificial Intelligence (AI), particularly Generative AI (GenAI) and Large Language Models (LLMs), have paved the way for Intelligent Automation (IA), which integrates cognitive capabilities to overcome the shortcomings of RPA. This paper introduces Text2Workflow, a novel method that automatically generates workflows from natural language user requests. Unlike traditional automation approaches, Text2Workflow offers a generalized solution for automating any business process, translating user inputs into a sequence of executable steps represented in JavaScript Object Notation (JSON) format. Leveraging the decision-making and instruction-following capabilities of LLMs, this method provides a scalable, adaptable framework that enables users to visualize and execute workflows with minimal manual intervention. This research outlines the Text2Workflow methodology and its broader implications for automating complex business processes.

Sanchaniya Rashmi Jaymin, Singh Harmeet, Kundziņa Antra et al.

The success of the construction sector is dependent on its diverse workforce and its role in driving growth. India’s economy is significantly tied to construction, especially residential and commercial projects. Effective project management relies on technical, knowledge-based, and soft skills. Realistic management techniques and stakeholder relationships are vital for success. The transition from construction to operations occurs during the handover phase. Developing project management competence is crucial in the midst of failures and delays. This study aims to improve Indian construction through a model developed through an online survey of civil engineering, architecture, and project management professionals. Factor analysis identifies key success factors grouped into project management competency, environmental factors, financial viability, operational efficiency, and structural safety. Recommendations involve the adoption of technology such as BIM, skill enhancement, and sustainability promotion, which can address sectoral challenges and support Indian construction growth. Further research is suggested for industries and global construction contexts. Insights are relevant for Indian construction professionals.

Francesco Tajani, Francesco Sica, Carola Clemente et al.

European directives on sustainable finance identify binding guidelines in investment planning for the decarbonization of the real estate sector. The Sustainable Finance Disclosure Regulation regularizes the methods of economic evaluation of projects by identifying the pillars Environmental (E), Social (S) and Governance (G) as thematic reference stylistic features. The ESG triptych constitutes inspiration in the scientific literature in the field for the proposal and testing of valuation algorithms aimed at the optimal structuring of investment portfolios. The paper proposes an ESG-based economic-financial analysis model for energy retrofit programs referring to the existing real estate sector. The model assumes the configuration of a multi-objective system built by borrowing algebraic formalisms of Operations Research, especially those of optimization algorithms. These algorithms make it possible to construct logical-functional relationships such as to represent the anatomy of the proposed evaluation model in terms of objective function and constraints, for example on the European decarbonization pathway target, or even on the available budget. The implementation of the proposed model, applied to a case study, returns a time priority list of assets to be energy efficient, balancing for each the investment costs, payback period and post-retrofit CO2 production.

Irina Lvovna Vladimirova, Yulia Yurevna Kosareva, Galina Yurevna Kallaur et al.

Представлен анализ подходов девелоперов к приобретению земельных участков для реализации проектов, исследована распространенная в современных условиях форма, когда девелопер приобретает 100 % долей юридического лица, имеющего права аренды на земельный участок, предназначенный под застройку. Отмечена многофакторность задачи оценки эффективности инвестиций на основе финансового моделирования с учетом особенностей рассматриваемого варианта вхождения в проект по критерию доходности инвестиций. Построен порядок принятия решений в процессе анализа, состоящий из восьми этапов и включающий расчеты экономических, технических, градостроительных, социальных и других параметров проекта. По предложенному алгоритму выполнены расчеты на примере реального девелоперского проекта с использованием современной нормативной и аналитической информации, которые подтверждают возможность и целесообразность вхождения в проект через покупку долей юридического лица. Практическое значение имеют сформулированные требования к построению финансовой модели проекта с учетом рассматриваемой формы приобретения земельного участка, в том числе: определение объема инвестиций в проект с учетом проектного финансирования, формирование показателя доходности проекта на основе сопоставления потоков дивидендов от проекта и стоимости приобретения долей юридического лица, а также налогообложение как для самого проекта, так и для девелопера при получении дивидендов.

Petr Grigorievich Grabovyу, Nikolay Igorevich Korolev

В статье рассматриваются вопросы выявления, оценки и учета основных особенностей возведения объектов недвижимости и деятельности строительных предприятий. Выявлены основные тенденции и подходы, которые необходимо использовать и реализовывать в настоящее время при возведении многоэтажных объектов недвижимости на рынке жилья. В частности, дана оценка таким показателям, как совокупная площадь строящихся единиц, количество возводимых объектов, средняя площадь строящихся объектов недвижимости в г. Москве и другим. Методами исследования являются теоретический анализ и эмпирическое исследование, в частности анализ статистических данных, а также описание и группировка данных. Информационной базой для анализа данной проблемы стали литературные источники по вопросам деятельности строительных организаций, научные статьи, монографии, электронные ресурсы, источники правового характера. Методологической основой при выполнении статьи послужили такие научные методы, как описание, классификация. Для эффективной работы предприятий на рынке жилья необходимо создание комплекса законодательных, правовых и экономических нормативов, проведение различных мероприятий на организационно-технологических процессах, которые наиболее полно учитывают интересы каждого участника процесса и позволяют формировать эффективную систему их взаимоотношений на основе перехода к технологическим и организационным новшествам.

Olga Cherednichenko, Fahad Muhammad

The present-day business landscape necessitates novel methodologies that integrate intelligent technologies and tools capable of swiftly providing precise and dependable information for decision-making purposes. Contemporary society is characterized by vast amounts of accumulated data across various domains, which hold considerable potential for informing and guiding decision-making processes. However, these data are typically collected and stored by disparate and unrelated software systems, stored in diverse formats, and offer varying levels of accessibility and security. To address the challenges associated with processing such large volumes of data, organizations often rely on data analysts. Nonetheless, a significant hurdle in harnessing the benefits of accumulated data lies in the lack of direct communication between technical specialists, decision-makers, and business process analysts. To overcome this issue, the application of collaborative business intelligence (CBI) emerges as a viable solution. This research focuses on the applications of data mining and aims to model CBI processes within distributed virtual teams through the interaction of users and a CBI Virtual Assistant. The proposed virtual assistant for CBI endeavors to enhance data exploration accessibility for a wider range of users and streamline the time and effort required for data analysis. The key contributions of this study encompass: 1) a reference model representing collaborative BI, inspired by linguistic theory; 2) an approach that enables the transformation of user queries into executable commands, thereby facilitating their utilization within data exploration software; and 3) the primary workflow of a conversational agent designed for data analytics.

Sharma Manu

In this paper, we studied the influence of interest rates on a US-based real estate private equity index as well US Wilshire public equity REIT Index. The interest rates that are chosen as independent variables include Monthly LIBOR, Yearly LIBOR and the Federal Cost of Funds Index. The dependent variables include US-based real estate private equity index that includes quarterly returns of 1,035 real estate funds, including liquidated funds formed between 1986 and 2018. The other dependent variable is the US Wilshire REIT Index. The variance of returns of interest rates considerably influences the variance of returns of the US PERE Index, whereas variance of returns of interest rates doesn’t influence the variance of returns of the US Wilshire REIT Index. Also, the real estate index is positively correlated to interest rates and so rising interest rates influence the returns of US PERE Index in a positive manner. The study shows that private equity real estate investors should expect higher return as the cost of funds increase.

Elena Korol’, Аnastasia Zhuravleva

In recent years, there has been an active growth in low-rise housing construction in Russia. This trend is explained by the state policy, which is aimed at developing this sector in order to increase accessibility for the population and provide comfortable housing. In addition, the relevance of low-rise housing construction is evidenced by the need of the population in the natural environment, as well as the possibility of living in separate houses. Along with individual construction, the most popular is low-rise housing development in the form of organized residential settlements (“cottage village”) with a developed communal, transport and social infrastructure. The regulations define the requirements to ensure the efficient and rational use of fuel and energy resources. This confirms the need to increase energy savings also in the sector of low-rise housing construction. The article presents the classification of energy consumption by functional purpose in the construction of low-rise residential buildings, identifies the main groups of energy consumers “machines and mechanisms”, “temporary infrastructure of the construction site” for complex low-rise residential buildings and considers an algorithm for calculating the costs of fuel and energy resources for these groups. It is proposed to include forms of documents for calculation, accounting and control of fuel and energy resources in organizational and technological documentation. This approach will allow you to choose energy-efficient construction technologies at the design stage and keep track of energy consumption during the construction of buildings.