Hasil untuk "Real estate business"

Danny Casprini , Alessandra Oppio , Mario Calderini

Analyzing the cultural value of industrial artefacts is particularly challenging due to lack of recognition as heritage assets and misconceptions related to previous uses and feeling of unwanted heritage. Former industrial sites are in many cases object of urban transformation and regeneration projects focusing on the re-purposing of the building while producing limited societal impact. Commoning – recalling the notions of the commons – offers a valuable way to counteract commodification of industrial heritage and to enable local participation for the preservation and valorization of industrial heritage. Commoning leverages on latent resources, local identities and mutuality to stimulate co-creation of re-use interventions capable of adding a cultural value to industrial artefacts, shifting the paradigm of conservation from artefacts to the value they represent for the participants in the process. In this light, the paper aims to explore how commoning can support the attribution of social and cultural values to former industrial sites. In our research, based on a case study, we explore how formal and informal collaboration and self-management arrangements can enhance the use value of former industrial artefacts contributing to the co-creation of social and cultural values, recognized by a community of interest. In doing so, we increase knowledge about how commoning can engage communities in collaborative heritage-making processes on industrial heritage. Furthermore, we provide new insights about the typology of values that different stakeholders place on industrial artefacts, shedding lights on participatory practices as tools to increase recognition of cultural values by communities.

Arash Yadegari Ghahderijani, Hande Naz Turgay, Dimka Karastoyanova

Context: Change mining enables organizations to understand the changes that occurred in their business processes. This allows them to enhance their business processes and adapt to dynamic environments. Therefore, change mining is becoming a topic of interest for researchers, scholars, and practitioners. Objective: Motivated by the goal of establishing the state of the art in this area, this paper aims to investigate the literature in change logging and mining in process-aware information systems, provide an overview of the methods that are used in the existing publications, and identify gaps in the research on the topic of logging and mining process changes. Method: A literature review is conducted with the objective to identify and define methods to mine, store, and record changes in business processes. From 1136 publications, we selected 6 papers related to changes in business process and extended the list to 9 papers by including the relevant articles referenced by the papers that we selected originally. Results: In answer of our research questions, we have identified two classes of change mining methods, two ways of recording the changes into change logs, five formats for change log representation, and four objectives to be learned from changes. Conclusion: The literature review provides a summary of existing change mining and logging methods in process-aware information systems and identifies a number of research gaps in the area.

Daniel Levy, Haipeng, Chen et al.

Studies of micro-level price datasets find more frequent small price increases than decreases, which can be explained by consumer inattention because time-constrained shoppers might ignore small price changes. Recent empirical studies of the link between shopping behavior and price attention over the business cycle find that consumers are more attentive to prices during economic downturns, and less attentive during economic booms. These two sets of findings have a testable implication. The asymmetry in small price changes should vary over the business cycle. It should diminish during recessions and strengthen during expansions. We test this prediction using a large US store-level dataset with more than 98 million weekly price observations for the years 1989-1997, which includes an 8-month recession period, as defined by the NBER. We compare price adjustments between periods of recession - high unemployment, and expansion - low unemployment. Focusing on small price changes, we find, consistent with our hypothesis, that there is a greater asymmetry in small price changes during periods of low unemployment compared to the periods of high unemployment, implying that firms price-setting behavior varies over the business cycle.

Jeroen Middelhuis, Zaharah Bukhsh, Ivo Adan et al.

Resource allocation plays a critical role in minimizing cycle time and improving the efficiency of business processes. Recently, Deep Reinforcement Learning (DRL) has emerged as a powerful technique to optimize resource allocation policies in business processes. In the DRL framework, an agent learns a policy through interaction with the environment, guided solely by reward signals that indicate the quality of its decisions. However, existing algorithms are not suitable for dynamic environments such as business processes. Furthermore, existing DRL-based methods rely on engineered reward functions that approximate the desired objective, but a misalignment between reward and objective can lead to undesired decisions or suboptimal policies. To address these issues, we propose a rollout-based DRL algorithm and a reward function to optimize the objective directly. Our algorithm iteratively improves the policy by evaluating execution trajectories following different actions. Our reward function directly decomposes the objective function of minimizing the cycle time, such that trial-and-error reward engineering becomes unnecessary. We evaluated our method in six scenarios, for which the optimal policy can be computed, and on a set of increasingly complex, realistically sized process models. The results show that our algorithm can learn the optimal policy for the scenarios and outperform or match the best heuristics on the realistically sized business processes.

Muhammad Arslan, Saba Munawar, Christophe Cruz

Businesses heavily rely on data sourced from various channels like news articles, financial reports, and consumer reviews to drive their operations, enabling informed decision-making and identifying opportunities. However, traditional manual methods for data extraction are often time-consuming and resource-intensive, prompting the adoption of digital transformation initiatives to enhance efficiency. Yet, concerns persist regarding the sustainability of such initiatives and their alignment with the United Nations (UN)'s Sustainable Development Goals (SDGs). This research aims to explore the integration of Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) as a sustainable solution for Information Extraction (IE) and processing. The research methodology involves reviewing existing solutions for business decision-making, noting that many systems require training new machine learning models, which are resource-intensive and have significant environmental impacts. Instead, we propose a sustainable business solution using pre-existing LLMs that can work with diverse datasets. We link domain-specific datasets to tailor LLMs to company needs and employ a Multi-Agent architecture to divide tasks such as information retrieval, enrichment, and classification among specialized agents. This approach optimizes the extraction process and improves overall efficiency. Through the utilization of these technologies, businesses can optimize resource utilization, improve decision-making processes, and contribute to sustainable development goals, thereby fostering environmental responsibility within the corporate sector.

Reil S. Romero, Dona Mae M. Alcantara, Edjelei R. Rodilla et al.

Small-scale landlords in the private rented sector make a critical contribution to the supply of affordable residential accommodation to prospective tenants. However, they face several constraints, resulting in the shortage supply of affordable residential dwellings aggravated by the growing demand in the rental market. This phenomenological qualitative study explores the limiting constraints to residential real estate investment expansion of small-scale landlords operating in the Downtown area of Davao City. Face-to-face interviews were conducted with five small-scale landlords and the qualitative data was analyzed using the Delphi technique. Six main themes emerged: (a) being business-minded with the opportunities; (b) making dwelling units available; (c) allocating income to expenditures; (d) investment decisions and financial challenges; (e) other regulatory and marketing limitations; and (f) long-term investment. The findings revealed that the most prevalent type of landlords in the area is subsistence landlords. Furthermore, the most important factor is financial constraints, whereas the least important factor is building regulations. This study is useful to alleviate the perceived constraints of small-scale landlords toward investment expansion and, therefore, produce more residential properties that will significantly contribute to the supply of affordable rental accommodation.

Janáčková Hana, Přečková Lenka

The aim of the article is to demonstrate the risk of underinsurance in selected production halls used for business activities in the Czech Republic by means of a case study. The case study determines the insured value in the new price category for three selected production halls. New price is a specific term for property insurance in the Czech Republic and means the replacement value of the property. The cost method of valuation is used to calculate the new price. The insured value is determined by an insurance broker, and two brokerage companies were approached for this purpose. The replacement cost is determined by the independent property appraiser using the valuation decree applicable from 1 January 2024. The case study compares the calculated new prices, assesses their level in terms of the risk of underinsurance and then makes a suggestion of problem areas that should be addressed in the Czech Republic, as they put the policyholder at risk. The results of the case study show an asymmetry of information between the policyholder and insurer. This is due to unavailable or unclear, yet very important information for the policyholder. In order to reduce information asymmetry and the occurrence of underinsurance, it seems important that all insurers follow an explicit procedure leading to the determination of the insured value, which would be known to the policyholder prior to the conclusion of the insurance contract. It seems appropriate to use the current valuation decree, which has been updated annually in the Czech Republic for 35 years, for the procedure of determining the insured value.

Калоян Иванов

В сектора на недвижимите имоти се наблюдава развитието на нов модел за финансиране на проекти в дигиталния свят, под формата на платформи за т. нар. „колективно финансиране“. Тези платформи свързват лица и компании, търсещи финансиране, с лица, които търсят диверсифицирани възможности за инвестиране на своите средства, дори когато техният размер е малък. Този пазар се развива и набира популярност, особено след финансовата криза от 2008 г. и Covid-19 кризата от 2020 г., като заедно с това привлича множество инвеститори, които целят да допринесат и да се възползват от развитието на новите технологии. Такава например е блокчейн технологията, която намира все по-често и все по-широко приложение в платформите за колективно финансиране. В тази разработка са разгледани метода и моделите, чрез които платформите оперират, в това число и блокчейн технологията. Основно се използват модели, чрез които собствеността в недвижими имоти се разпределя на дялове, гарантирайки на своите инвеститори доход от дивиденти. Друг вид модел е предоставянето на заеми, които кредитополучателите да изплащат на кредиторите, чрез изградените интернет платформи. Разработката представя основна характеристика и разглежда възможностите пред сектора, който представлява бързо развиваща се алтернатива на традиционните финансови институции, като чрез конкуренция с тях, ги предизвиква да се адаптират към новата дигитална реалност.

Fabiana Fournier, Lior Limonad, Inna Skarbovsky

Large Language Models (LLMs) are increasingly used for boosting organizational efficiency and automating tasks. While not originally designed for complex cognitive processes, recent efforts have further extended to employ LLMs in activities such as reasoning, planning, and decision-making. In business processes, such abilities could be invaluable for leveraging on the massive corpora LLMs have been trained on for gaining deep understanding of such processes. In this work, we plant the seeds for the development of a benchmark to assess the ability of LLMs to reason about causal and process perspectives of business operations. We refer to this view as Causally-augmented Business Processes (BP^C). The core of the benchmark comprises a set of BP^C related situations, a set of questions about these situations, and a set of deductive rules employed to systematically resolve the ground truth answers to these questions. Also with the power of LLMs, the seed is then instantiated into a larger-scale set of domain-specific situations and questions. Reasoning on BP^C is of crucial importance for process interventions and process improvement. Our benchmark, accessible at https://huggingface.co/datasets/ibm/BPC, can be used in one of two possible modalities: testing the performance of any target LLM and training an LLM to advance its capability to reason about BP^C.

Benedetto Manganelli, Francesco Paolo Del Giudice

The article addresses real estate appraisals in Italy involving lands already subject to Local Government uses then legitimized or soils burdened by Emphyteusis (Land Lease). Local Government uses are collective property rights on rural land. Considering these conditions, it is possible for the land to be legitimized by the occupant, who thus obtains the right to alienate the land with the burden of the rent. Emphyteusis (Land Lease), on the other hand, is a right of enjoyment on another’s land with the obligation to improve it and pay a periodic rent. These two types of agrarian relationships may appear similar but confusing them can lead to inequalities when updating the rent or quantifying the capital of enfranchisement. Therefore, a historical-legal investigation becomes essential to reconstruct the existence of the right and its particular genesis, in order to identify the true owner of the land between the grantor and the grantee. The work also provides operational suggestions, in the two cases examined, for estimating the rent and capital of enfranchisement that are in line with the prescriptions imposed by case law and represent a fair balance between the various interests of the parties involved.

Radomir Yurievich Simionov, Andrey Andreevich Kirpichenkov

Сохранение окружающей природной среды во многом зависит от повышения экологической ответственности строительных организаций. Статистические данные показывают, что последние годы характеризуются ростом объемов работ по виду экономической деятельности «Строительство», что требует организационных, правовых, экономических, технологических и технических мер, реализуемых на государственном, отраслевом уровнях и в системе управления строительными организациями, направленных на рациональное природопользование. Эти меры относятся не только к стадии строительства объектов, но и периоду эксплуатации объектов недвижимости, что обусловлено значительной ресурсоемкостью объектов недвижимости как в процессе строительства, так и эксплуатации в течение всего жизненного цикла. Исследование проблемы приводит к выводу, что формировать механизм экологического менеджмента следует с учетом специфики строительной деятельности, обеспечивая безопасность на стадии при проектировании объектов, организации строительной площадки, освоении территории застройки, внедрении процессных инноваций в строительстве. В управлении ресурсосбережением кроме инвестиционной стоимости объекта необходимо управлять затратами на эксплуатацию объекта, которые составляют 75 % затрат владения объектом. Принципы экологической эффективности должны находить отражение в показателях оценки инвестиционных проектов. Ответственное с позиций экологии инвестирование может стать одним из трендов реализации национальных проектов, поскольку цели национальных проектов соответствуют концепции устойчивого развития и сбалансированности экономических, социальных и экологических факторов. Выявлены барьеры препятствий ESG-инвестированию в отечественной экономике, в частности недооценка влияния названных факторов на долгосрочные финансовые показатели самих организаций. Для организации системы экологического менеджмента в строительных организациях необходимо формирование системы показателей (индикаторов устойчивости), наличие которой позволит моделировать экологический профиль организации. Экологический профиль позволяет установить баланс внешних запросов и реальных возможностей самой организации. Это требует не только наличия сбалансированной системы экологических показателей организации, но и эталонных значений показателей, обеспечивающих организации повышение конкурентоспособности на рынке подрядных работ.

Zayed F. Zeadat

Seventy percent of the population in Jordan is young and urban. A plethora of research demonstrated that collaborative urban policymaking would positively impact youth’s physiological and physical welfare as well as the quality of urban planning. Nevertheless, youth participation in Jordan’s urban planning is fragile, limited, and sporadic. Youth marginalization from urban policymaking would deter sustainable urban development. Therefore, this article examines the most convenient strategy to promote the inclusion of young Jordanians in the planning practice to be fully-fledged members of society. The fuzzy Delphi method (FDM) was employed to mathematically analyze the level of importance of each suggested strategy based on the opinions of eight experts with long experience in promoting youth participation in Jordan’s public policy. Research results reveal that adopting cutting-edge communication technology is the most suitable strategy to genuinely recognize youth input, opinions, and experience in urban policymaking.

E. А. Nigay, A. A. Naumchenko

Digital transformation today is an objective reality and a vital need for organizations in all fields of activity. It can be the result of forced circumstances of external conditions (pandemic), as well as an intentional decision of the strategic development set by the company’s management. In both cases, the digital business transformation process provides a multiple increase in the speed, quality, and efficiency of business processes. For real estate, these trends are no exception.The object of research in the article is management business modeling of the activities of real estate organizations. The subject of research is the process of digital transformation of the business model of real estate organization.The purpose of the article is to substantiate the digital business model of real estate organization based on the ecosystem approach in the BANI world.The article justifies the conceptual process of transforming the business models of real estate organizations, based on the evolutionary transition from SPOD to VUCA and the BANI concept of entrepreneurial reality. Each of the presented “worlds” is characterized by differences in management metrics and a different level of technology presence in the activities of organizations. The forced immersion of business in the entrepreneurial BANI world accelerated the processes of digital transformation. The dynamic development and ubiquitous presence of digital technologies requires appropriate adaptation of business models and management approaches. For the conditions of the BANI world, the most relevant is the ecosystem approach, combining complex approaches and platform solutions.

Roger Knecktys, Henrik Bette, Rüdiger Kiesel et al.

Technology trends as digitalization and Industry 4.0 initiate a growing demand for new business models. Most of this models requires a fundamental shift of operational and financial risks between seller and buyer. A key question is therefore how to include additional risk pricing and hedging. In this paper we propose a new approach for a risk theory of innovative performance based business models as "Pay-for-Performance" or "Product as a Service". A new model and calculation method for determination the risk premium is presented. It contains beside financial price fluctuations also operational failure behaviour of products. We apply the model for a typical industrial application and simulate the pricing dependency for different cost distributions.

Lena Ji, Mattie Ji

We study real double covers of $\mathbb P^1\times\mathbb P^2$ branched over a $(2,2)$-divisor, which have the structure of a conic bundle threefold with smooth quartic discriminant curve via the second projection. In each isotopy class of smooth plane quartics, we construct examples where the total space of the conic bundle is rational. For five of the six isotopy classes we construct $\mathbb C$-rational examples that have obstructions to rationality over $\mathbb R$, and for the sixth class, we show that the models we consider are all rational. Moreover, for three of the five classes with irrational members, we give characterizations of rationality using the topology of the real locus and the intermediate Jacobian torsor obstruction of Hassett--Tschinkel and Benoist--Wittenberg. The double cover models we consider were introduced and previously studied by S. Frei, S. Sankar, B. Viray, I. Vogt, and the first author.

Matyáš Skalický, Štěpán Šimsa, Michal Uřičář et al.

Information extraction from semi-structured documents is crucial for frictionless business-to-business (B2B) communication. While machine learning problems related to Document Information Extraction (IE) have been studied for decades, many common problem definitions and benchmarks do not reflect domain-specific aspects and practical needs for automating B2B document communication. We review the landscape of Document IE problems, datasets and benchmarks. We highlight the practical aspects missing in the common definitions and define the Key Information Localization and Extraction (KILE) and Line Item Recognition (LIR) problems. There is a lack of relevant datasets and benchmarks for Document IE on semi-structured business documents as their content is typically legally protected or sensitive. We discuss potential sources of available documents including synthetic data.

Metallinos Pavlos

The object of the research focuses on the use and application of the management reserves and contingencies of the hierarchical structure of the Earned Value Management System framework. The study explores logical failures of the method, which do not seem to have been recorded in the international literature. These failures do not seem to have been perceived, although they relate to variables that they identify and must ensure the accuracy of the results of the method, in the way this method is executed in application of EVMS standard/EIA 748. The derived failure of these variables leads to incorrect qualitative and quantitative calculation of Earned Value Method (EVM) calculations. Spoiled results in terms of the accuracy of their algebraic prices lead to erroneous and possibly more costly decisions by the actors in the production process; especially when it comes to borderline situations. Because of these failures, both the on-schedule handover time and the size of the expected rate of profit (IRR) on the part of the entrepreneur do not seem to be accurately predicted or measured at the end of the production process/handover. The cause is structural. It derives from the logic and the correlation of the individual components of Budget Element hierarchy. The study focuses on the logical contradictions and conceptual failures of the method. The author aims to highlight these specific failures with the purpose of achieving more effectively the uncertainty management and determining more accurately the risk algebraic value. Henceforth, the user is provided with an improved ability to manage the resources of the construction. This is ensured by the scientifically more accurately documented measurement of the production time and the construction cost of the technical project.

A. Jafari, M. R. Delavar, A. Stein

Estimating real estate prices helps to adapt informed policies to regulate the real estate market and assist sellers and buyers to have a fair business. This study aims to estimate the price of residential properties in District 5 of Tehran, Capital of Iran, and model its associated uncertainty. The study implements the Stacking technique to model uncertainties by integrating the outputs of basic models. Basic models must have a good performance for their combinations to have acceptable results. This study employs four statistical and machine learning models as basic models: Random Forest (RF), Ordinary Least Squares (OLS), Weighted K-Nearest Neighbour (WKNN), and Support Vector Regression (SVR) to estimate the price of residential properties. The results show that the integrated output is more accurate for the quadruple combination mode than for any of the binary and triple combinations of the basic models. Comparing the Stacking technique with the Voting technique, it is shown that the Mean Absolute Percentage Error (MAPE) reduces from 10.18% to 9.81%. Hence we conclude that our method performs better than the Voting technique.

P. A. Gloor, S. Woerner, D. Schoder et al.

We explore what benefits network position in online business social networks like LinkedIn might confer to an aspiring entrepreneur. We compare two network attributes, size and embeddedness, and two actor attributes, location and diversity, between virtual and real-world networks. The promise of social networks like LinkedIn is that network friends enable easier access to critical resources such as legal and financial services, customers, and business partners. Our setting consists of one million public member profiles of the German business networking site XING (a German version of LinkedIn) from which we extracted the network structure of 15,000 start-up entrepreneurs from 12 large German universities. We find no positive effect of virtual network size and embeddedness, and small positive effects of location and diversity.

Mohammad Amin Edrisi

Establishing a new business may involve Knowledge acquisition in various areas, from personal to business and marketing sources. This task is challenging as it requires examining various data islands to uncover hidden patterns and unknown correlations such as purchasing behavior, consumer buying signals, and demographic and socioeconomic attributes of different locations. This paper introduces a novel framework for extracting and identifying important features from banking and non-banking data sources to address this challenge. We present an attention-based supervised feature selection approach to select important and relevant features which contribute most to the customer's query regarding establishing a new business. We report on the experiment conducted on an openly available dataset created from Kaggle and the UCI machine learning repositories.