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The present study aims to propose a framework elucidating the attributes of mobile augmented reality (AR) shopping apps (i.e., spatial presence, perceived personalization and perceived intrusiveness) and how they translate to downstream consumer-related outcomes (i.e., immersion, psychological ownership and stickiness to the retailer).

By conducting a questionnaire-based survey, 308 responses were collected, and the data were submitted to partial least square structural equation modeling (PLS-SEM) and artificial neural network (ANN) analyses.

A few important findings were generated from the present study. First, attributes of mobile augmented reality shopping apps (i.e., spatial presence, perceived personalization and perceived intrusiveness) influence stickiness to the retailer through immersion and consumer empowerment in serial. Second, immersion positively influences psychological ownership. Third, the optimum stimulation level moderates the relationship between spatial presence and immersion. Lastly, a post-hoc exploratory finding yielded by the multigroup analysis uncovered the moderating effect of gender.

This study offers a novel contribution to the smart retail literature by investigating the role of mobile AR shopping apps in predicting consumers' stickiness to the retailer. A holistic framework elucidating the serial mediating effect of immersion and consumer empowerment, and the moderating roles of optimum stimulation level and gender were validated.

This study aims to examine the tail connectedness between the Chinese and Association of Southeast Asian Nations (ASEAN) stock markets. More specifically, the authors measure the return spillovers at three quantile levels: median (t = 0.5), lower extreme (t = 0.05) and upper extreme (t = 0.95). The connectedness at extreme upper and lower quantiles provides insightful information to investors regarding tail risk propagation, which ultimately suggests that investors adjust their portfolios according to the extreme bullish and bearish market conditions.

The authors employ the quantile connectedness approach of Ando et al. (2022) to examine the quantile transmission mechanism among the ASEAN and Chinese stock markets.

The results show significant evidence of a higher level of connectedness between Chinese and ASEAN stock markets at extreme upper and lower quantiles compared to the median quantiles, which suggests the use of a quantile-based connectedness approach instead of an average-measure-based one. Furthermore, the time-varying connectedness analysis shows that the total spillovers reach the highest peaks during the global financial crisis, the Chinese stock market crash and the COVID-19 pandemic at the upper, lower and median quantiles. Finally, the static and dynamic pairwise spillovers between the Chinese and ASEAN markets vary over quantiles as well.

This study is the first attempt to examine quantile vector autoregression (VAR)-based return spillovers between China and ASEAN stock markets during different market statuses. Besides, the COVID-19 has intensified the uncertainty in Asian countries, mainly China and ASEAN economies.

The purpose of this study is to explore the causal relationship between smart transportation technology innovation and green transportation efficiency.

A comprehensive framework is used in this paper to assess the level of green transportation efficiency in China based on the instrumental variable – generalized method of moments model, followed by an examination of the impact of innovation in smart transportation technology on green transportation efficiency. Additionally, their non-linear relationship is explored, as are their important moderating and mediating effects.

The findings indicate that, first, the efficiency of green transportation is significantly enhanced by innovation in smart transportation technology, which means that investing in such technologies contributes to improving green transportation efficiency. Second, in areas where green transportation efficiency is initially low, smart transportation technology innovation exerts a particularly potent influence in driving green transportation efficiency, which underscores the pivotal role of such innovation in bolstering efficiency when it is lacking. Third, the relationship between smart transportation technology innovation and green transportation efficiency is moderated by information and communication technology, and the influence of smart transportation technology innovation on green transportation efficiency is realized through an increase in energy efficiency and carbon emissions efficiency.

Advancing green transportation is essential in establishing a low-carbon trajectory within the transportation sector.

The present study investigates the effect of foreign direct investment (FDI) and governance quality on carbon emissions in the Economics Community of West African States (ECOWAS).

To achieve the objective of this research, panel data for dependent and explanatory variables over the period 2005–2016, collected in the World Development Indicators (WDI) database and World Governance Indicators (WGI), are analyzed using the generalized method of moments (GMM). Also, the panel-corrected standard errors (PCSE) method is applied to the four segments of the overall sample to analyze the stability of the results.

The findings of this study are: (1) FDI inflows have a negative effect on carbon emissions in ECOWAS and (2) The interaction between FDI inflows and governance quality have a negative effect on carbon emissions. These results show the decreasing of environmental damage by increasing institutional quality. However, the estimation results on the country subsamples show similar and non-similar aspects.

This study suggests that policymakers in the ECOWAS countries should strengthen their environmental policies while encouraging FDI flows to be environmentally friendly.

The subject has rarely been explored in West Africa, with gaps such as the lack of use of institutional variables. This study contributes to the literature by drawing on previous work to examine the role of good governance on FDI and the CO2 emission relationship in the ECOWAS, which have received little attention. However, this research differs from previous work by subdividing the overall sample into four groups to test the stability of the results.

This study empirically examines the moderating role of geopolitical risk on the tourism–economic growth nexus by applying a recent geopolitical risk indicator developed by Caldara and Iacoviello (2022) in a cross-country panel data growth model context for a sample of 24 countries.

A Dummy Variable Least Squares panel data model, nonparametric covariance matrix estimator and SYS-GMM estimation techniques are employed for the analysis. The authors capture the GPR moderating effect by disaggregating the cross-country sample according to low versus high country GPR score and through a GPR interaction coefficient. Several controls are included in the models such as gross fixed capital formation and—consistent with Barro (1990)—government consumption. Trade openness is used to account for the export-led growth effect. In line with neoclassical growth theory (e.g. Barro, 1991), the authors also include the real interest rate, to account for policy makers' commitment to macroeconomic stability, financial depth, as a proxy for financial development, population growth and the level of secondary school education. The authors also control for unobserved country-specific and time-invariant effects.

The research finds that the interaction term of geopolitical risk significantly contributes to the predictive ability of the regression and provides empirical evidence that confirms that only in low geopolitical risk countries international tourism positively and significantly contributes to economic growth. Important theoretical and policy implications flow from these findings.

The study not only contributes to advancing academic knowledge on the tourism–growth nexus, it also has impact beyond academia. Many countries have in the past pursued and many continue to pursue, tourism specialization and/or tourism-led growth strategies based on the theoretically well-established and empirically validated positive link between inbound tourism and economic growth. The findings alert policy makers in such countries to the significant moderating role that geopolitical risk plays in affecting the above-mentioned relationship and to the importance of prioritizing geopolitical stability as a policy precursor for the successful implementation of such strategies.

Financial inclusion is a critical component of financial development, which disseminates accessible financial services to benefit all parts of society and consequently promotes economic growth. The study explores the dynamic common correlated effects of financial inclusion on economic growth in Organization of Islamic Cooperation (OIC) countries.

The conventional econometric techniques overlook heterogeneity and cross-sectional dependence and provide false results. Hence, a unique methodology, ‘Dynamic Common Correlated Effects (DCCE)’, is used, which can efficiently tackle the above-mentioned issues.

The DCCE estimation indicates a positive and significant impact of financial inclusion on economic growth in overall and higher-income OIC economies. Moreover, in the lower-income OIC group, financial inclusion is inversely correlated with economic growth, which converts into a positive linkage by including an interaction term of financial inclusion and institutional quality.

Based on the research outcomes, it is recommended that policymakers and governments of OIC economies seek to increase financial inclusion to achieve sustainable, optimal and inclusive economic growth.

The DCCE technique in this study considers heterogeneity and cross-sectional dependence among countries and thus provides robust findings.

Climate change-related weather events significantly affect rice production. In this paper, we investigate the impact of and interrelationships between agriculture inputs, climate change factors and financial variables on rice production in India from 1970–2021.

This study is based on the time series analysis; the unit root test has been employed to unveil the integration order. Further, the study used various econometric techniques, including vector autoregression estimates (VAR), cointegration test, autoregressive distributed lag (ARDL) model and diagnostic test for ARDL, fully modified least squares (FMOLS), canonical cointegrating regression (CCR), impulse response functions (IRF) and the variance decomposition method (VDM) to validate the long- and short-term impacts of climate change on rice production in India of the scrutinized variables.

The study's findings revealed that the rice area, precipitation and maximum temperature have a significant and positive impact on rice production in the short run. In the long run, rice area (ß = 1.162), pesticide consumption (ß = 0.089) and domestic credit to private sector (ß = 0.068) have a positive and significant impact on rice production. The results show that minimum temperature and direct institutional credit for agriculture have a significant but negative impact on rice production in the short run. Minimum temperature, pesticide consumption, domestic credit to the private sector and direct institutional credit for agriculture have a negative and significant impact on rice production in the long run.

The present study makes valuable and original contributions to the literature by examining the short- and long-term impacts of climate change on rice production in India over 1970–2021. To the best of the authors’ knowledge, The majority of the studies examined the impact of climate change on rice production with the consideration of only “mean temperature” as one of the climatic variables, while in the present study, the authors have considered both minimum as well as maximum temperature. Furthermore, the authors also considered the financial variables in the model.

This study aims to develop a database of existing academic information in house purchase decision (HPD) using systematic literature review (SLR), to facilitate worldwide advancement of research under HPD domain.

This research examined papers from two reputable databases – Scopus and Google Scholar – from 1992 to 2022 using a scoping review technique (Arksey and O’Malley, 2005) and a theme analysis method. Out of 374, 181 articles fit the inclusion parameters and were evaluated using the theme analysis approach.

Data from 181 articles was evaluated thematically to create a thematic map of HPD research. Five main themes and their sub-themes were identified: consumer behaviour, housing attributes, factors influencing purchasing decisions, investment analysis and demographics, which proved essential in understanding HPD and customer preferences for house purchase.

Data from 181 articles were evaluated thematically to create a thematic map of HPD research. This SLR intends to provide useful new insights on consumer concerns about home purchases in the rapidly developing residential real estate market and the issues that marketers, housing sector stakeholders, real estate industry and existing and future researchers should prioritize.

This research is unique such that it is the only 30-year-long SLR on the subject matter of HPD. This paper makes a significant contribution to residential real estate domain signifying the present state of research in HPD.

This paper aims to measure and unveil the relationship between customer satisfaction and efficiency levels in the most relevant Brazilian airports.

The authors utilize a two-stage network DEA (data envelopment analysis) and AHP (analytic hierarchy process) model as the cornerstones of the study. The first stage of the network productive structure focuses on examining the infrastructure efficiency of the selected airports, while the second stage assesses their business efficiency.

Although the results indicate that infrastructure and business efficiency levels are heterogeneous and widely dispersed across airports, controlling the regression results with different contextual variables suggests that the impact of efficiency levels on customer satisfaction is mediated by a set of socio-economic and demographic (endogenous) and regulatory (exogenous) variables. Furthermore, encouraging investment in airports is necessary to achieve higher infrastructural efficiency and scale efficiency, thereby improving customer satisfaction.

There is a scarcity of studies examining the relationships among customer satisfaction, privatization and airport efficiency, particularly in developing countries like Brazil.

The paper aims to investigate the relationship between institutions and economic growth in developing countries, considering the role of financial inclusion, education spending and military spending.

The study employs dynamic panel analysis, specifically two-step system generalized method of moments (GMM), on a sample of 61 developing countries over the period 2009–2020.

The results confirm that weak institutional quality, weak financial inclusion and increased military spending are barriers to economic growth, conversely, increased spending on education and gross capital formation contribute to economic growth in developing countries. Regarding the specific institutional factor, we find that corruption, ineffective government, voice and accountability and weak rule of law contribute negatively to growth.

The study calls for strengthening institutions so that the financial system supports economic growth and suggests increasing spending on education to improve access to and the quality of human capital, which is an important determinant of economic growth.

The study contributes to scarce literature by empirically analyzing the relationship between institutions and economic growth by considering the role of financial inclusion, public spending on education and military spending, factors that have been ignored in previous studies. In addition, the study identifies the institutional dimension that contributes to reduced economic growth in developing countries.