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The purpose of this study is to understand the investment decision-making of real estate investors in housing, highlighting the interplay between rational and irrational factors. In this study, investment satisfaction was a mediator, while reinvestment intention was the dependent variable.

A quantitative, cross-sectional and descriptive research design was used, gathering data from a sample of 550 residential real estate investors using a multi-stage stratified sampling technique. The partial least squares structural equation modelling disjoint two-stage approach was used for data analysis. This methodological approach allowed for an in-depth examination of the relationship between rational factors such as location, profitability, financial viability, environmental considerations and legal aspects alongside irrational factors including various biases like overconfidence, availability, anchoring, representative and information cascade.

This study strongly supports the adaptive market hypothesis, showing that residential real estate investor behaviour is dynamic, combining rational and irrational elements influenced by evolutionary psychology. This challenges traditional views of investment decision-making. It also establishes that behavioural biases, key to adapting to market changes, are crucial in shaping residential property market efficiency. Essentially, the study uncovers an evolving real estate investment landscape driven by evolutionary behavioural patterns.

This research redefines rationality in behavioural finance by illustrating psychological biases as adaptive tools within the residential property market, urging a holistic integration of these insights into real estate investment theories.

The study reshapes property valuation models by blending economic and psychological perspectives, enhancing investor understanding and market efficiency. These interdisciplinary insights offer a blueprint for improved regulatory policies, investor education and targeted real estate marketing, fundamentally transforming the sector’s dynamics.

Unlike previous studies, the research uniquely integrates human cognitive behaviour theories from psychology and business studies, specifically in the context of residential property investment. This interdisciplinary approach offers a more nuanced understanding of investor behaviour.

This paper aims to provide a comprehensive analysis of the transformative impact of Artificial Intelligence (AI) and Large Language Models (LLMs), such as GPT-4, on the real estate industry. It explores how these technologies are reshaping various aspects of the sector, from market analysis and valuation to customer interactions and evaluates the balance between technological efficiency and the preservation of human elements in business.

The study is based on an analysis of the strengths and weaknesses of AI as a technology in applications for real estate. It uses this framework to assess the potential of this technology in different use cases. This is supplemented by an emerging literature on the topic, practical insights and industry expert opinions to provide a balanced perspective on the subject.

The paper reveals that AI and LLMs offer significant benefits in real estate, including enhanced data-driven decision-making, predictive analytics and operational efficiency. However, it also uncovers critical challenges, such as potential biases in AI algorithms and the risk of depersonalising customer interactions.

The paper advocates for a balanced approach to adopting AI, emphasising the importance of understanding its strengths and limitations while ensuring ethical usage in the diverse and complex landscape of real estate.

This work stands out for its balanced examination of both the advantages and limitations of AI in real estate. It introduces the novel concept of the “jagged technological frontier” in real estate, providing a unique framework for understanding the interplay between AI and human expertise in the industry.

The paper aims to provide a comprehensive analysis of artificial intelligence’s (AI) transformative impact on the real estate industry. By examining various AI applications, from property recommendations to compliance automation, this study highlights potential benefits such as increased accuracy and efficiency. At the same time, this study critically discusses potential drawbacks, like privacy concerns and job displacement. The paper's goal is to offer valuable insights to industry professionals and policy makers, aiding strategic decision-making as AI continues to reshape the landscape of the real estate sector.

This paper employs an extensive literature review, combined with a qualitative analysis of case studies. Various AI applications in the real estate industry are examined, including machine learning for property recommendations and valuation, VR/AR property tours, AI automation for contract and regulatory compliance, and chatbots for customer service. The study also delves into the optimisation potential of AI in building management, lead generation, and risk assessment, whilst critically discussing potential challenges such as data privacy, algorithmic bias, and job displacement. The outcomes aim to inform strategic decisions for industry professionals and policy makers.

The study finds that AI has significant potential to revolutionise the real estate industry through enhanced accuracy in property valuation, efficient automation and immersive AR/VR experiences. AI-driven chatbots and optimisation in building management also hold promise. However, this study also uncovers potential challenges, including data privacy issues, algorithmic biases, and possible job displacement due to increased automation. The insights gleaned from this study underscore the importance of strategic decision-making in harnessing the benefits of AI while mitigating potential drawbacks in the real estate sector.

The paper's practical implications extend to industry professionals, policy makers, and technology developers. Professionals gain insights into how AI can enhance efficiency and accuracy in the real estate sector, guiding strategic decision-making. For policy makers, understanding potential challenges like data privacy and job displacement informs regulatory measures. Technology developers can also benefit from understanding the sector-specific applications and concerns raised. Additionally, highlighting the need for addressing algorithmic bias and privacy concerns in AI systems may foster better design practices. Therefore, the paper's findings could significantly shape the future trajectory of AI integration in real estate.

The paper provides original value by offering a comprehensive analysis of the transformative impact of AI in the real estate industry. Its multi-faceted examination of AI applications, coupled with a critical discussion on potential challenges, provides a balanced perspective. The paper's focus on informing strategic decisions for professionals and policy makers makes it a valuable resource. Moreover, by considering both benefits and drawbacks, this study contributes to the discourse on AI's broader societal implications. In the context of rapid technological change, such comprehensive studies are rare, adding to the paper's originality.

Robotic process automation (RPA) has recently emerged as a technology focusing on the automation of repetitive, frequent, voluminous and rule-based tasks. Despite a few practical examples that document successful RPA deployments in organizations, evidence of its economic benefits has been mostly anecdotal. The purpose of this paper is to present a step-by-step method to RPA investment appraisal and a business case demonstrating how the steps can be applied to practice.

The methodology relies on design science research (DSR). The step-by-step method is a design artefact that builds on the mapping of processes and modelling of the associated costs. Due to the longitudinal nature of capital investments, modelling uses discounted cashflow and present value methods. Empirical grounding characteristic to DSR is achieved by field testing the artefact.

The step-by-step method is comprised of a preparatory step, three modelling steps and a concluding step. The modelling consists of compounding the interest rate, discounting the investment costs and establishing measures for comparison. These steps were applied to seven business processes to be automated by the case company, Estate Blend. The decision to deploy RPA was found to be trivial, not only based on the initial case data, but also based on multiple sensitivity analyses that showed how resistant RPA investments are to changing circumstances.

By following the provided step-by-step method, executives and managers can quantify the costs and benefits of RPA. The developed method enables any organization to directly compare investment alternatives against each other and against the probable status quo where many tasks in organizations are still carried out manually with little to no automation.

The paper addresses a growing new domain in the field of business process management by capitalizing on DSR and modelling-based approaches to RPA investment appraisal.

This study aims to enrich our understanding of the characteristics of non-urban coworking spaces (CSs) that focus on corporate users, as well as the benefits that companies expect to gain from incorporating those CSs into their corporate real estate (CRE) portfolios.

This study leverages a series of in-depth interviews with owners and managers of CSs in non-urban locales that focus on serving corporate clients.

The research reveals various CS characteristics and forms within non-urban areas, focusing on corporate clients. It suggests that implementing a CS in corporate premises is perceived to enhance CRE use-value strategies with a focus on the employee's well-being, innovation and the attraction of talents. Moreover, exchange-value strategies with a focus on portfolio flexibility may benefit from the implementation of a CS. However, strategies related to life-cycle cost optimization or gains are not perceived to be supported. Social events for the surrounding neighborhood and the choice of location emerge as critical success factors for non-urban CSs. Besides infrastructure and connectivity, non-urban corporate-centric CSs built their location decisions rather on a personal connection to the location and place of residence of potential users than on lower rental prices.

This research pioneers in providing a comprehensive understanding of non-urban CSs, particularly in the context of their perceived implications for corporate real estate management. The nuanced perspectives it offers are invaluable for stakeholders looking to leverage CSs as part of their corporate strategies.

The purpose of this study was to investigate the relationship between job crafting and work engagement and the potential mediating effect of organizational happiness on this relationship.

A sample of 256 full-time employees from various industries such as automobiles, retail, real estate, petrochemicals, investment, industrial and education, working at top 50 Forbes Middle East companies in UAE, were surveyed to gather data on job crafting, organizational happiness and work engagement. The study used an empirical research design, with data collected through surveys.

The results of this study, obtained through a two-step structural equation modelling approach, indicate that job crafting has a positive and direct influence on both organizational happiness and work engagement. The findings also suggest that the relationship between job crafting and work engagement is partially mediated by organizational happiness.

The findings emphasize the need for human resources (HR) professionals to develop programmes and training workshops focused on cultivating these concepts, particularly as remote and blended working arrangements become more prevalent. In addition, the study highlights the global impact of employee disengagement on financial losses and stresses the importance of revising HR policies in the UAE to mitigate potential risks. Lastly, the study suggests that enhancing happiness and reducing disengagement can be achieved through training managers and employees in task structuring techniques, emphasizing the teachability of job crafting skills through interventions that align tasks with employees’ interests.

To the best of the author's knowledge, this is the first study to theoretically explore and empirically test a proposed model on the relationships between job crafting, organizational happiness and work engagement in the context of the UAE.

The rising concern for the accuracy of residential valuations in Nigeria has created the need for key stakeholders in the residential property markets in the study areas to know the level of accuracy of valuations in order to make rational residential property transactions, amongst other purposes.

A blend of descriptive and causal designs was adopted for the study. Data were collected via structured questionnaire administered to 179 estate surveying and valuation (ESV) firms in the study areas using census sampling technique. Analytical techniques such as median percentage error (PE), mean and relative importance index (RII) analysis were employed in the analysis of data collected for the study.

The study found that valuation accuracy is greater in the residential property market in Abuja than in Minna, with inappropriate valuation methodology as the most significant cause of valuation inaccuracy.

The practical implication of this study is that a reliable databank should be established for the property market to provide credible transaction data for valuers to conduct accurate valuations in these cities. Strict enforcement of national and international valuation standards by the regulatory authorities as well as retraining of valuers on appropriate application of valuation approaches and methods are the recommended corrective measures.

No study has comparatively examined the accuracy of valuations in two extremely different residential property markets in the country using actual valuation and transaction prices.

Informal housing stands out as a major challenge surrounding the massive reconstruction of Syrian cities, devastated by a bloody war and a terrible earthquake. The purpose of this article is to assess the adequacy of the Syrian Law to adequate provide a solution to this problem.

With the purpose of informing the question, this paper offers a legal-institutional analysis of the informal housing phenomenon and the corresponding regulatory responses in Syria. A literature review is conducted, and functional analysis of the legal texts and their effective implementation is provided.

First, informal housing in Syria has been fostered by the existence of an erratic regulation, particularly burdened by the incoherence of passing repressive provisions against informal housing while master plans were conspicuously absent or incomplete. Second, the regulatory policy seems to be leaning toward the urban renewal option, indicating a supply-oriented housing approach that may face serious challenges due to the scarcity of capital. In this context, regulation should not underestimate any policy tools at hand (renewal and upgrading; with the contribution of public, private and cooperative sectors).

Although there have been several studies on informal housing in Syria, none has taken a legal institutionalist approach. Furthermore, this study offers an up-to-date account of the problem, taking into account the problematic after the 2023 earthquake and the content of Law 2/2023.