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This paper aims to examine the impact of Digital Financial Inclusion (DFI) on three key economic aspects: banking crises, economic expansion and economic downturns across 93 countries from 2004 to 2017.

Bayesian Logit regression models provide important insights into how DFI influences these economic factors.

The findings show that DFI has a modest positive effect on banking crises (coefficients: 0.002–0.027), but rapid growth could increase crisis risks if not regulated. DFI positively impacts economic expansion (coefficients: 0.003–0.012), supporting growth at reasonable levels. For economic downturns, DFI has a negative effect, potentially reducing recession risks, though the impact is small. Regionally, DFI helps mitigate banking crises and downturns in Africa, Latin America and Asia, but in Europe, it slightly increases risks, suggesting potential instability if not properly managed.

The study provides original insights into the nuanced effects of DFI on banking crises, economic expansion and economic downturns across different regions, offering valuable policy recommendations based on these findings.

This article aims to study the nonlinear effect of financial inclusion on tax revenue of 21 low financial development countries (LFDCs) and 22 high financial development countries (HFDCs) from 2004 to 2020.

The study calculates the world average financial development index (FD̅) for all countries using data from the IMF. The average FD of HFDCs is higher than (FD̅). On the other hand, the average FD of LFDCs is lower than (FD̅). Data of 21 LFDCs and 22 HFDCs cover the period 2004–2020. With the small sample problem, we applied the Bayesian method to examine the nonlinear effect of financial inclusion on the tax revenue of the two groups of countries.

Using the Bayesian method, the results show that financial inclusion negatively impacts tax revenue with an absolute probability of 100% in LFDCs and a lower probability of 92.45% in HFDCs. Additionally, the financial inclusion threshold at LFDCs is 18.90. Below this threshold, financial inclusion promotes tax revenue with a 100% probability. On the contrary, when financial inclusion exceeds the threshold, it will have a negative effect on tax revenue. Similarly, the financial inclusion threshold at HFDCs is 20.14, with a probability of 92.45%.

To the best of the authors’ knowledge, this is the first paper to examine the nonlinear impact of financial inclusion on tax revenue in high and low financial development countries.

The purpose of this study is to use vector error-correction modeling together with directed acyclic graphs (DAG) for analyzing dynamic relations among monthly retail property price indices of 10 major cities in China from 2005–2021.

This paper apply both the PC and Linear Non-Gaussian Acyclic Model (LiNGAM) algorithms for inference of the DAG, with the former leading to the causal pattern and the latter leading to the causal path. This paper carry out innovation accounting analysis based on the causal path according to the LiNGAM algorithm.

Their results show sophisticated dynamics among processes of price adjustments following shocks. The results do not reveal clear evidence that supports dominance of the price series of the top-tier cities.

These results suggest that it could be beneficial to design policies at granular levels regarding regional retail property prices in China.

Profitability is crucial for a company’s sustainability. This study aims to examine the influence of profitability and specific variables on the value of real estate companies in Indonesia.

The study uses a sample of 42 real estate companies listed on the Indonesia Stock Exchange from 2017 to 2023. A static panel regression approach was adopted, with the best model being the fixed effect model, verified through a robustness test.

The results indicate that the fixed effect model is the most effective in explaining firm value. Profitability, proxied by return on assets (ROAs), does not significantly impact firm value. This finding is confirmed by robustness tests using another profitability measure, return on equity (ROE). Additionally, company size negatively and significantly impacts firm value, while activity ratio and leverage have a positive and significant effect. Liquidity and company growth do not significantly affect firm value.

The research is limited to Indonesian real estate firms, cautioning against broad generalization to other countries or industries. The study could not demonstrate the influence of profitability on the value of real estate companies. Instead, firm value is influenced by company size, activity ratio and leverage.

Real estate firms should increase their activity, optimize funding and consider company size to enhance firm value.

This study contributes to the Indonesian real estate sector by revealing that profitability does not enhance firm value. Indonesian real estate companies generally have low profitability and firm value.

This study aims to identify determinants of single-family residential property values and fill the gap by analyzing respondents’ willingness to pay/receive data alongside real transaction data. Ordinal logistic regression and ordinal least square regression were used.

Ordinal logistic regression effectively analyzes willingness-to-pay/receive data, accommodating the ordered nature of property value responses while incorporating multiple influencing factors. Ordinal least square regression quantifies the impact of continuous and categorical predictors on real transaction data.

Findings revealed strong associations between property values and several variables. Analysis of willingness-to-pay/accept data from 232 respondents showed significant impacts of factors such as the number of rooms, site area, construction material, property orientation, property age and proximity to bus stations and the central business district (p < 0.05). Similarly, ordinal least square regression analysis of transaction data confirmed the significance of most of these factors, except for property orientation, which indicates the difference of preference in the local market or reporting inconsistencies, demand further investigation. Variables such as views, proximity to wetlands, roads, green areas, religious institutions and schools were statistically insignificant across both data sets (p > 0.05).

It provides a robust basis for housing and urban development strategies. The stakeholders such as real estate developers, urban planners and policymakers are encouraged to incorporate these findings into housing policies, land value capture initiatives and urban planning frameworks to enhance residential property value and align with sustainable urban development goals.

This study contributes original insights into single-family residential property valuation by integrating willingness-to-pay and transaction data, substantiating the determinants of property value.

The paper aims to estimate the house rental values for the purpose of customizing mass appraisals in Bahir Dar City, Ethiopia. It seeks to identify the critical factors affecting the rental values of residential properties and customize a mass appraisal model for such properties. The study focuses on identifying attributes that significantly affect house rental values.

The paper adopted a survey research design, utilizing a survey questionnaire, expert group discussion and document analysis. The data were analyzed using thematic, descriptive and inferential statistical analysis, including correlation and hedonic regression analysis.

Among the variables included in the model, the number of rooms, availability of schools, land value grading, type of nearest road, housing typology, built-up area, plot area, walling material, traveling cost and fencing materials were the most significant factors for predicting the annual rental value of residential properties in the city.

The findings of this study will provide valuable insights to tax assessors, property owners and local government authorities, including municipalities, concerning the key determinants of the rental values of residential properties. Besides, these findings will serve as a useful tool for valuers and researchers in the field of property value modeling.

This study represents the first attempt to develop a framework for mass appraisal of residential properties using annual rental values in the Ethiopian context.

This paper aims to propose a model for democratization of Islamic home financing to tackle the issue of sustainability of homeownership affordability.

A conceptual framework and fractional equity model (FEM) are developed to incorporate big data analytics, artificial intelligence and blockchain technology in an ecosystem for affordability and sustainability of homeownership via the proposed financing model. In addition, the FEM adopts the simulation approach to show its validity in terms of liquidity when compared with traditional home financing. In this regard, this paper is focused on developing and demonstrating the feasibility of a new financing model, rather than testing specific hypotheses or relationships. This is to propose the democratization model for Islamic Home Financing that will not benefit the prospective home buyers without compromising the profitability of the financial institutions.

The findings indicate that the proposed end-to-end solution within the financing ecosystem can lead to more efficient matching market between the buyers and sellers of houses, reduced transaction costs, greater transparency and enhanced efficiency which in the end could lead to lower costs of owning homes and sustained financial resilience among house owners. The findings indicate that the FEM model is able to increase homeownership with more elements of liquidity, marketability and sustainability for homebuyers.

This research highlights the potential of big data and blockchain technology in democratizing Islamic home financing and evidence that the transfer of ownership is possible through tokenization. However, this will require a mature financing environment to adapt the technology for practical application.

The model proposes a solution to propagate shared prosperity among stakeholders such as the house buyers/owners, sellers, investors as well the government agencies. The proposed FEM model provides alternative home financing that is more marketable, flexible and sustainable for households/buyers and financiers.

It is hoped that with the proposed financing ecosystem to promote affordability and sustainability of homeownership via big data analytics, artificial intelligence and blockchain technology can lead to greater financial resilience for homeowners which can then be translated to enhanced well-being, increased productivity and can further promote economic growth.

This research is a concept paper based on academic research and industry collaboration with a technology provider.

Decision-makers often struggle to combine advice with their own intuition. This study examines how advice-giver traits and decision-makers’ intuition influence advice uptake. We present a novel typology based on decision-makers’ trust in advice-givers and their perceived expertise.

This qualitative study uses a sample of publicly available interview data with 51 elite performers. Using inductive and content analysis, we explore the mediation between decision-makers’ intuitive competence (ability to effectively deploy intuition in interface with advice) and their autonomy (self-endorsement from past performance).

We identify four sources of advice: mentor advice, specialist advice, confidant advice and commentator advice. Drawing on instances of different sources of advice along varying degrees of trust and expertise, we propose a framework for interaction between intuitional competence and advice characteristics.

We offer a novel way of contextualising nuanced forms of advice and provide a structured typology of sources, characterised by trust and expertise. This typology and our findings help reconcile contradictions in decision-making research. Finally, we offer practical guidance for the uptake of advice.

Management consulting aims to enhance organizational effectiveness through manager development and empowerment. There is evidence that management consultants perceive themselves as leaders, but little research has been conducted on their power bases. The purpose of this study is to examine management consultants’ power bases to gain insight into their leadership and their perceptions regarding managers’ development.

Using qualitative methods, 40 consultants were interviewed, and a semi-structured interview outline was applied to identify their power bases and determine how their power base influences their leadership and managers’ development. Thematic content analysis was applied to analyze the data.

The findings indicate that management consultants have either a prominent referent or expert power base and that these two informal power bases affect consultant leadership differently: referent power leads to solving the managers’ problems, while expert power enhances managers’ self-efficacy and ability to solve their problems by themselves.

The study sheds light on an under-explored subject and contributes to both theory and practice; it extends and refines the connection between power dynamics and managers’ development as well as leadership theory and offers practical implications for the relationship between management consultants and managers.

This paper aims to examine the influence of overconfident or conservative CEOs on the performance feedback of R&D investment, as well as the combined impact of CEO overconfidence and demographic characteristics on the relationship between performance feedback of R&D investments.

Grounded in the upper echelon theory, listed companies in China are selected as samples, and the Heckman two-stage model is used to examine all the models.

This paper reveals that overconfident CEOs tend to make suboptimal investment decisions. These decisions are influenced by cognitive biases that have a negative impact on the performance of R&D investments. However, the negatively moderating effects of CEO overconfidence can be mitigated if they have overseas experience or academic background, or they are younger.

These mechanisms highlight the various ways in which CEO psychological factors and demographic characteristics can complement each other.