Hasil untuk "Real estate business"

G. Friede, T. Busch, A. Bassen

Nemcova Jana, Svoboda Patrik, Hampel David

This study investigates the impact of international accounting and valuation standards (IFRS 13, IVS 2020, IVS 2022, RICS 2022, IPSM 2023) on information asymmetry in the residential real estate markets of the UK, Germany, and Spain. Given the frequent use of subjective inputs in fair value measurements, this sector is particularly susceptible to higher levels of information asymmetry, making it an apt context for analysis. The research analyses changes in selected standards and includes control variables such as company size and market capitalization, using two indicators over the period 2019–2023. Revisions to IFRS 13, IVS 2022, RICS 2022, and IPSM 2023 significantly reduced valuation variability (as measured by the VCVT indicator), confirming their positive effect on market transparency. In contrast, the IVS 2020 update was associated with an increase in the bid–ask spread, suggesting a rise in perceived uncertainty. By jointly examining the bid–ask spread and VCVT, the study provides a comprehensive assessment of how accounting and valuation standards influence liquidity and information asymmetry in the residential property sector - a field that has received limited attention in prior literature. The findings are consistent with earlier research indicating that reduced disclosure requirements can enhance stock market liquidity. Practical implications include recommendations for stricter guidance on Level 3 fair value models and the adoption of best practices from EPRA and REIT frameworks to enhance transparency and credibility in capital markets.

Marta Castellini, Chiara D’Alpaos, Michele Moretto et al.

The establishment of Renewable Energy Communities (RECs) requires a proper legal and management framework encompassing (i) an adequate legal and regulatory arrangement, (ii) an effective collective energy production and self-consumption and (iii) a sustainable business plan. The best combination of legal, technical and economic factors is vital to ensure the maximisation of energy self-production and self-consumption and an adequate redistribution of social net benefits. The design and implementation of such a setting require considerable managerial effort and an initial investment. Financial support for feasibility studies and legal expenditures, as provided by several Italian regions, can serve as a catalyst for the widespread generation of RECs. Most regions have launched calls for funding with specific features, requirements and criteria addressed to public and/or private actors. As Italy is strongly regionalised in several public sectors, a wide range of differentiated regional approaches and procedures have been observed. Based on a comparative analysis of the RECs’ legal and regulatory regional provisions and the regional calls for funding the creation of RECs, this article presents (i) a clustering of Italian regions based on the enforcement of regional laws and structural funds, (ii) an analysis of the correlation between allocated funds, population, household income and energy expenditure, and installed power, (iii) an analysis of requirements, criteria and rewards detected in the different calls for funding and (iv) an assessment of different scoring systems to reveal how they affect public funds’ distribution. As a main result, our analysis reveals the heterogeneity and fragmentation of regional public action.

Larisa Igorevna Zaytseva

Статья посвящена потенциалу примирительных механизмов как неотъемлемого компонента реализации инвестиционно-строительных проектов с точки зрения внесудебного разрешения споров, с учетом их разнообразия и наличия публичного элемента. Подчеркивается основная цель медиативных подходов — снижение конфликтной составляющей как в экономической деятельности в целом, так и в строительной отрасли. Представлен концептуальный подход к оценке экономической эффективности внесудебного урегулирования споров, раскрывающий уровни внедрения указанных подходов (законодательное закрепление, консалтинговая деятельность, сфера образования, модификация контрактных конструкций) и структурирующий затраты на судебный процесс: судебные издержки, расходы на проведение строительной экспертизы, направленной на экономическую, техническую, финансовую, стоимостную оценку, расходы на услуги представителя (юридическую помощь) и косвенные расходы, которые в основном связаны с временными издержками. Кроме того, выделены существенные факторы, влияющие на оценку экономической эффективности: размер судебных издержек, длительность разбирательства, инфляционные процессы, освобождение от уплаты и возврат государственной пошлины, а также тип контрактной модели. В статье сделан важный вывод о том, что даже в случае выигрыша спора в суде без использования медиативных технологий на ранних стадиях (направление в комнаты примирения) судебное разбирательство не является эффективным способом урегулирования разногласий. Полученные выводы и результаты могут способствовать развитию конструктивного партнерства при реализации проектов и принятию превентивных мер для существенного снижения уровня конфликтности в инвестиционно-строительной сфере.

Hełdak Maria, Cyganek Iga, Kulczyk-Dynowska Alina et al.

The study addresses the problem of assessing the investment attractiveness of commercial real estate measured based on the location and land use planning of the real estate offered for sale. The database includes offers published on the following websites: www.olx.pl and www.otodom.pl, in the period from the beginning of June to the end of December 2022. The subject matter of the analyses undertaken in the presented study is focused on land properties which can generate income, including commercial, speculative and capital properties. In the study, the exits from national roads which provide access to expressways and motorways were analyzed, as well as the designation of commercial real estate specified in spatial planning acts, in relation to the property’s offer price [USD]. The study used Ward’s taxonomic method which determines the distance between clusters. The least favorable areas are Type 3 and Type 4 counties, whereas the most favorable location and the best land use planning was observed in the counties classified as Type 1. The offer price amount does not always confirm the assumption that the higher the offer price, the better the conditions for investment.

Matthias Stierle, Karsten Kraume, Martin Matzner

Data-driven analysis of business processes has a long tradition in research. However, recently the term of process mining is mostly used when referring to data-driven process analysis. As a consequence, awareness for the many facets of process analysis is decreasing. In particular, while an increasing focus is put onto technical aspects of the analysis, human and organisational concerns remain under the radar. Following the socio-technical perspective of information systems research, we propose a new perspective onto data-driven process analysis that combines the process of analysis with the organisation and its stakeholders. This paper conceptualises the term process analytics and its various dimensions by following both an inductive and deductive approach. The results are discussed by contrasting them to a real-life case study from a large company implementing data-driven process analysis and automation.

Lorenzo Porcelli

Instant payment infrastructures have stringent performance requirements, processing millions of transactions daily with zero-downtime expectations. Traditional monitoring approaches fail to bridge the gap between technical infrastructure metrics and business process visibility. We introduce a novel feature engineering approach based on processing times computed between consecutive ISO 20022 message exchanges, creating a compact representation of system state. By applying anomaly detection to these features, we enable early failure detection and localization, allowing incident classification. Experimental evaluation on the TARGET Instant Payment Settlement (TIPS) system, using both real-world incidents and controlled simulations, demonstrates the approach's effectiveness in detecting diverse anomaly patterns and provides inherently interpretable explanations that enable operators to understand the business impact. By mapping features to distinct processing phases, the resulting framework differentiates between internal and external payment system issues, significantly reduces investigation time, and bridges observability gaps in distributed systems where transaction state is fragmented across multiple entities.

Jeho Choi

Large Language Models (LLMs) have shown promise in enabling natural language interfaces for structured data querying through text-to-SQL generation. However, their application in real-world Business Intelligence (BI) contexts remains limited due to semantic hallucinations, structural errors, and a lack of domain-specific evaluation frameworks. In this study, we propose a Fact-Consistency Evaluation Framework for assessing the semantic accuracy of LLM-generated SQL outputs using Exaone 3.5--an instruction-tuned, bilingual LLM optimized for enterprise tasks. We construct a domain-specific benchmark comprising 219 natural language business questions across five SQL complexity levels, derived from actual sales data in LG Electronics' internal BigQuery environment. Each question is paired with a gold-standard SQL query and a validated ground-truth answer. We evaluate model performance using answer accuracy, execution success rate, semantic error rate, and non-response rate. Experimental results show that while Exaone 3.5 performs well on simple aggregation tasks (93% accuracy in L1), it exhibits substantial degradation in arithmetic reasoning (4% accuracy in H1) and grouped ranking tasks (31% in H4), with semantic errors and non-responses concentrated in complex cases. Qualitative error analysis further identifies common failure types such as misapplied arithmetic logic, incomplete filtering, and incorrect grouping operations. Our findings highlight the current limitations of LLMs in business-critical environments and underscore the need for fact-consistency validation layers and hybrid reasoning approaches. This work contributes a reproducible benchmark and evaluation methodology for advancing reliable natural language interfaces to structured enterprise data systems.

Michał Dominik Stasiak, Żaneta Staszak

The oil market is one of the most important markets for the global economy. Often, oil prices influence the financial results of whole countries and sectors. Therefore, the modeling and prediction of crude oil prices are of high importance. Most up-to-date publications have used daily closing rates in crude oil price modeling, not considering the variability in prices during the day. The application of this kind of price representation leads to a loss of information about the range of price changes during the day, which influences the accuracy of the models and makes them useless in short-term course predictions. In this paper, we introduce the concept of a new state model in a binary-temporal representation, which uses trend analysis, which is one of the main methods used in the prediction of the direction of future changes in the course trajectory. The model described in this paper stands as the first tool that allows for predicting course changes in a given range. The presented work also summarizes the research results of modeling crude oil prices from the last six years, which prove the effectiveness of the mentioned modeling method.

Panos Vassiliadis, Patrick Marcel, Faten El Outa et al.

We introduce a conceptual model for highlights to support data analysis and storytelling in the domain of Business Intelligence, via the automated extraction, representation, and exploitation of highlights revealing key facts that are hidden in the data with which a data analyst works. The model builds on the concepts of Holistic and Elementary Highlights, along with their context, constituents and interrelationships, whose synergy can identify internal properties, patterns and key facts in a dataset being analyzed.

Leandro Fiorini Aurichi, Lucas Real

In infinite graph theory, the notion of ends, first introduced by Freudenthal and Jung for locally finite graphs, plays an important role when generalizing statements from finite graphs to infinite ones. Nash-Willian's Tree-Packing Theorem and MacLane's Planarity Criteria are examples of results that allow a topological approach, in which ends might be considered as endpoints of rays. In fact, there are extensive works in the literature showing that classical theorems of (vertex-)connectivity for finite graphs can be discussed regarding ends, in a more general context. However, aiming to generalize results of edge-connectivity, this paper recalls the definition of edge-ends in infinite graphs due to Hahn, Laviolette and Širáň. In terms of that object, we state an edge version of Menger's Theorem (following a previous work of Polat) and generalize the Lovász-Cherkassky Theorem for infinite graphs with edge-ends (inspired by a paper of Jacobs, Joó, Knappe, Kurkofka and Melcher).

Alexandre Duarte, Francisco Fernandes, João M. Pereira et al.

Depth maps produced by consumer-grade sensors suffer from inaccurate measurements and missing data from either system or scene-specific sources. Data-driven denoising algorithms can mitigate such problems. However, they require vast amounts of ground truth depth data. Recent research has tackled this limitation using self-supervised learning techniques, but it requires multiple RGB-D sensors. Moreover, most existing approaches focus on denoising single isolated depth maps or specific subjects of interest, highlighting a need for methods to effectively denoise depth maps in real-time dynamic environments. This paper extends state-of-the-art approaches for depth-denoising commodity depth devices, proposing SelfReDepth, a self-supervised deep learning technique for depth restoration, via denoising and hole-filling by inpainting full-depth maps captured with RGB-D sensors. The algorithm targets depth data in video streams, utilizing multiple sequential depth frames coupled with color data to achieve high-quality depth videos with temporal coherence. Finally, SelfReDepth is designed to be compatible with various RGB-D sensors and usable in real-time scenarios as a pre-processing step before applying other depth-dependent algorithms. Our results demonstrate our approach's real-time performance on real-world datasets. They show that it outperforms state-of-the-art denoising and restoration performance at over 30fps on Commercial Depth Cameras, with potential benefits for augmented and mixed-reality applications.

Sushil Bhunia, Amit Kulshrestha, Anupam Singh

In this article, we determine the non-real elements--the ones that are not conjugate to their inverses--in the group $G = G_2(q)$ when $char(F_q)\neq 2,3$. We use this to show that this group is chiral; that is, there is a word w such that $w(G)\neq w(G)^{-1}$. We also show that most classical finite simple groups are achiral

Leandro Fiorini Aurichi, Paulo Magalhães Júnior, Lucas Real

The notion of ends in an infinite graph $G$ might be modified if we consider them as equivalence classes of infinitely edge-connected rays, rather than equivalence classes of infinitely (vertex-)connected ones. This alternative definition yields to the edge-end space $Ω_E(G)$ of $G$, in which we can endow a natural (edge-)end topology. For every graph $G$, this paper proves that $Ω_E(G)$ is homeomorphic to $Ω(H)$ for some possibly another graph $H$, where $Ω(H)$ denotes its usual end space. However, we also show that the converse statement does not hold: there is a graph $H$ such that $Ω(H)$ is not homeomorphic to $Ω_E(G)$ for any other graph $G$. In other words, as a main result, we conclude that the class of topological spaces $Ω_E = \{Ω_E(G) : G \text{ graph}\}$ is strictly contained in $Ω= \{Ω(H) : H \text{ graph}\}$.

Maurizio d’Amato

The paper provides the methodological foundations of a property valuation method based on income approach called cyclical capitalization. The model is proposed for the valuation of income producing properties and was originally introduced by d’Amato (2001) and relies on the assumption of more than a single capitalization rate it integrates direct capitalization with the analysis of an entire market cycle. Such integration has been required in literature (Kazdin,1944; Pyhrr et al.,1990). The procedure has recently and indirectly been recalled by international valuation standards (IVS 2017; IVS 2020; IVS 2022; IVS 105 item 50.21 letter (e)), as it will be discussed in the paper. International Valuation Standards since 2017 required a different approach to the determination of terminal value (going out value, scrap value, exit value, terminal value, exit value) in Discounted Cash Flow Analysis. The models proposed in the paper are the basic ones systematized in the first contributions that took up and reorganized this line of research from its original systematic introduction (d’Amato, 2013; d’Amato, 2015; d’Amato, 2017a; d’Amato, 2017b). The initial applications were based on the office market in London. The first application to the Italian market will be made in this contribution referring to the office real estate market in Milan offered by the then REAG Study Office (currently Kroll). Evidence from the application shows that the proposed model is capable of reaching a prudent value judgments than the income-capitalization estimate normally used. Prudent opinion of value can help in determining the security value and the most likely market value under specific market conditions. Il lavoro introduce il lettore ai fondamenti metodologici di una procedura di valutazione basata sulla capitalizzazione del reddito denominata capitalizzazione ciclica. La procedura di valutazione introdotta precedentemente (d’Amato,2001) si basa sulla ipotesi di formulare la previsione di più di un solo saggio di capitalizzazione, in maniera da integrare il processo di capitalizzazione con l’analisi di un intero ciclo di mercato. Tale integrazione è stata richiesta da tempo (Kaz- din,1944; Pyhrr et al.,1990). La procedura è stata indirettamente richiamata dagli standard di valutazione internazionali (IVS 2017; IVS 2020; IVS 105 punto 50.21 lettera (e)), come si avrà modo di vedere. Il richiamo degli standard è esplicitamente riferito alla capitalizzazione del reddito per la stima del valore di uscita (going out value, scrap value, exit value, terminal value) che chiude la normale applicazione metodologica della attualizzazione del flusso di cassa scontato, altrimenti definita Discounted Cash Flow Analysis. I modelli proposti nel contributo sono quelli basilari, sistematizzati nei primi contributi che riprendono e riorganizzano questa linea di ricerca dalla sua originale sistematica introduzione (d’Amato, 2013; d’Amato, 2015; d’Amato, 2017a; d’Amato, 2017b). Le prime applicazioni sono state effettuate facendo riferimento al mercato londinese. La prima applicazione al mercato italiano sarà effettuata in questo contributo facendo riferimento ai dati del mercato immobiliare degli uffici a Milano offerti dall’allora Ufficio Studi REAG (attualmente Kroll). Le evidenze che derivano dalla applicazione mostrano che il modello proposto è in grado di formulare giudizi di valore maggiormente prudenti rispetto alla stima per capitalizzazione del reddito normalmente utilizzata. Valutazioni più prudenti possono essere di aiuto nella determinazione del valore cauzionale e del più probabile valore di mercato in specifiche condizioni di mercato.

Anton Pavlovich Khrabrov

Enhancing construction control possibilities with the implementation of information modelling technologies (BIM) is a method of ensuring the organizational and technological reliability of creating multifunctional real estate objects as a tool to increase the effectiveness of this type of commercial construction. Construction control is one of the effective methods of ensuring the organizational and technological reliability of the creation of capital construction facilities, the use of modern technologies can significantly increase their efficiency. To date, there are still a huge number of questions and difficulties that designers, builders, regulatory authorities and other participants in this area face every day. Large construction companies have already started testing and implementing new technologies. Every year, information modelling technologies in the Russian Federation are increasingly used at all stages of the life cycle of objects. BIM technologies are now quite common in design, a little less at the construction stage, and very slightly at the stage of operation of buildings and structures. There are Russian developers who create new software for the needs of modern realities, which helps to reduce the time for routine processes, save and verify information, and bring it to all recipients as quickly and without loss as possible1. This paper discusses some of the similar technologies that are already being used at the construction and construction control stage in a common data environment (CDE). This allows you to receive data at the right time, and in the right form, without spending a lot of time on all sorts of corrections, which become more costly the later they occur. At the design stage, if the designer does not receive special requirements from the customer, he has the right to perform the task assigned to him in any way convenient to him. If, at the initial stage of planning the construction of any new or reconstruction of an existing facility, the customer will form a package of requirements not only for the interim results of the entire investment and construction project, but also requirements for further work results (construction and operation)2, this will allow to clearly build a strategy for all processes at an early stage, select modern technologies that can reduce many costs, and especially financial and time costs.

Rita Yi Man Li, M. James C. Crabbe, M. James C. Crabbe et al.

Ian W. Gray, Jack Cable, Benjamin Brown et al.

Ransomware operations have evolved from relatively unsophisticated threat actors into highly coordinated cybercrime syndicates that regularly extort millions of dollars in a single attack. Despite dominating headlines and crippling businesses across the globe, there is relatively little in-depth research into the modern structure and economics of ransomware operations. In this paper, we leverage leaked chat messages to provide an in-depth empirical analysis of Conti, one of the largest ransomware groups. By analyzing these chat messages, we construct a picture of Conti's operations as a highly-profitable business, from profit structures to employee recruitment and roles. We present novel methodologies to trace ransom payments, identifying over $80 million in likely ransom payments to Conti and its predecessor -- over five times as much as in previous public datasets. As part of our work, we publish a dataset of 666 labeled Bitcoin addresses related to Conti and an additional 75 Bitcoin addresses of likely ransom payments. Future work can leverage this case study to more effectively trace -- and ultimately counteract -- ransomware activity.

Sören Nagel, Jobst Heitzig, Eckehard Schöll

In this letter we present a stochastic dynamic model which can explain economic cycles. We show that the macroscopic description yields a complex dynamical landscape consisting of multiple stable fixed points, each corresponding to a split of the population into a large low and a small high income group. The stochastic fluctuations induce switching between the resulting metastable states, and excitation oscillations just below a deterministic bifurcation. The shocks are caused by the decisions of a few agents who have a disproportionate influence over the macroscopic state of the economy due to the unequal distribution of wealth among the population. The fluctuations have a long-term effect on the growth of economic output and lead to business cycle oscillations exhibiting coherence resonance, where the correlation time is controlled by the population size which is inversely proportional to the noise intensity.

Sari Pekkala Kerr, W. Kerr, Ramana Nanda

During 1992-2007, house price growth is strongly correlated with local entrepreneurship. We show with Census Bureau data that most of this entry is related to construction and real estate; these entrants tend to be small and short-lived. Using a 1998 Texas reform that allowed home equity lending for the (cid:133)rst time in the state, we isolate that entrepreneurship through the collateral channel tends to be longer-lived and more balanced across sectors. The collateral channel is a tenth or less of the entry associated with house price increases, driven by a small share of homeowners who are constrained without price growth. those related to real estate. On the other hand, entrepreneurs entering due to unlocked collateral are longer-lived and more balanced across sectors. These results align with home equity loan data from the SBO. We conclude that unlocked home equity due to house price increases can be very important for a small share of constrained potential entrepreneurs, and result in meaningful businesses being started, but that this channel is a small share of the total entry linked to house price run-ups.