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Today, many industries are implementing creative approaches in response to increasing environmental awareness. It is of great importance to answer the question of whether the military sector, one of the most important sectors, can support renewable energy (RE) adaptation. This study aims to examine how military spending affects the supply of RE in 27 Organization for Economic Cooperation and Development (OECD) nations as well as the regulatory function of factors such as innovation, international trade and oil prices between 1990 and 2021.

The study examines the effects of military spending, income, green innovation, international trade, oil prices and the human development index on the supply of RE using various econometric approaches, which are the cointegration test, moments quantile regression and robustness test.

The findings demonstrate that all factors, excluding military spending, quite likely affect the expansion of the renewable supply. Military spending negatively influences the RE supply; specifically, a 1% increase in military spending results in a 0.88 reduction in the renewable supply. In addition, whereas income elasticity, trade and human development index in OECD nations are higher in the last quantiles of the regression than in the first quantiles, the influence of military spending and innovation on renewable supply is about the same in all quantiles.

OECD nations must consider the practical implications, which are essential to assess and update the military spending of OECD countries from a green energy perspective to transition to clean energy. Based on the study’s overall findings, the OECD countries should incorporate the advantages of innovation, economic growth and international trade into their clean energy transition strategies to lessen the impact of military spending on renewables.

The study aims to fill a gap in the literature regarding the role of military expenditures in the RE development of an OECD country. In addition, the results of the methodological analysis can be used to guide policymakers on how military spending should be in the field of RE.

This study aims to examine the effect of foreign direct investment (FDI) inflows on tax revenue in 34 developed and developing countries from 2006 to 2020.

Feasible generalised least squares (FGLS), a dynamic panel of a two-step system generalised method of moments (GMM) system and a pool mean group (PMG) panel autoregressive distributed lag (ARDL) approach were used to compare the developed and developing countries. Basic estimators were used as pre-estimators and diagnostic tests were used to increase robustness.

The FGLS, a two-step system of GMM, PMG–ARDL estimator’s results showed that there was a significant negative long and positive short-term in most countries relationship between FDI inflows and tax revenue in developed countries. This study concluded that attracting investments can improve the quality of institutions despite high tax rates, leading to low tax revenue. Meanwhile, there was a significant positive long and negative short-term relationship between FDI inflows and tax revenue in the developing countries. The developing countries sought to attract FDI that could be used to create job opportunities and transfer technology to simultaneously develop infrastructure and impose a tax policy that would achieve high tax revenue.

The present study sheds light on the effect of FDI on tax revenue and compares developed and developing countries through the design and implementation of policies to create jobs, transfer technology and attain economic growth in order to assure foreign investors that they would gain continuous high profits from their investments.

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.