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This paper aims to explore the role of digital inclusive finance (DIF) in influencing household tourism consumption, whether this influence differs between households with different characteristics and determining the intermediate mechanisms that influence the relationship.

The conceptual framework of this study was designed on the basis of the research on DIF in residential consumption practices. The China Household Finance Survey (CHFS) and the Peking University DIF Index were used in the study, which included four years of unbalanced panel data from 25 provinces in China. A fixed effects model was used to validate the conceptual framework and hypothesis testing.

Both hypothesis paths proposed in this study were supported. Results of this study show that DIF has a significant contribution to household tourism consumption and shows a positive impact in terms of both breadth of coverage and depth of use, and that Internet usage is an important mediating mechanism for DIF to promote household tourism consumption. Thus, the use of DIF as a tool can have a positive impact on tourism consumption.

Results of this study will help researchers and tourism businesses understand the relationship and mechanisms at play between DIF and household tourism consumption and leverage financial tools to drive tourism revival. However, the lack of third-country data for comparative analysis may render the conclusions inapplicable to every economy.

This study is the first to examine the relationship between DIF and household tourism consumption, using an “individual + time + region” fixed effects model to conduct specific empirical tests.

The purpose of the present study is to explore the factors that influence the residential location choice of households in the Indian context.

Two sub-urban towns of Kolkata, i.e. Biddhanagar Municipal Corporation and Rajarhat Newtown, are taken as case studies. In total, 34 variables are considered related to the household's socioeconomic background (10), dwelling (3), travel (2) and level of importance of neighborhood characteristics (19). A revealed preference household survey is conducted, which resulted in the collection of 390 samples. Firstly, 19 level of importance variables are deduced to 3 latent factors using exploratory and confirmatory factor analysis. After that, a utility function is estimated using a multinomial logit regression to identify significant factors.

The results indicate the significance of car ownership, work travel time, work mode, monthly income, proximity to work, proximity to family/relative/friends, proximity to quality schools, quality of physical infrastructure such as water availability, power availability and housing typology among others in the residential location choice of households.

Kolkata, a major metropolitan area in eastern India, has been experiencing space constraints to cater to the housing demand of the ever-increasing population. Although satellite towns are being developed, the infrastructure landscape in such towns is uneven, resulting in more housing demand in one area than another. The study furnishes significant findings to develop more informed policies to attract households in low-demand areas and manage high-demand areas to achieve sustainable planning.

Considering the importance of geographical context, it is the first study on residential location choice, providing a perspective of household behavior from eastern India. It also shows the importance of physical infrastructure attributes in residential location choice for developing countries, which is seldom employed in the current practice. Moreover, previous studies (although few) done in India consider the objective value of location characteristics. The present study focuses on subjective value or the level of importance perceived by respondents.

This paper examines the factors influencing the adoption of Quality 4.0 technologies by quality professionals. The study evaluates perceived usefulness, perceived ease of use, attitude towards use, and intention to use new technologies.

The research involves a literature review, identification of latent variables derived from the Technology Acceptance Model (TAM), and a survey conducted among 200 quality professionals in the high-tech sector using computer-assisted web interviews.

The study elucidates the attitudes and intentions of high-tech industry employees towards adopting Quality 4.0 technologies. The primary conclusion drawn is that the predominant factor shaping the attitude of quality professionals towards new technologies is their confidence in their ability to effectively engage with these technologies rather than solely the perceived usefulness of such technologies to themselves or their organization.

This study is subject to certain limitations. Firstly, it focuses on five variables identified in the TAM model, potentially overlooking other pertinent factors that could provide a more comprehensive understanding. Secondly, the analysis of Quality 4.0 technologies is presented in a generalized manner, possibly resulting in nuanced differences if each specific technology were examined individually.

This article fills a gap in the literature by identifying the factors influencing quality professionals' adoption of Quality 4.0 technologies and delineating the relationships between these factors.

This paper examines the post-COVID-19 travel intentions to Kenya among Hong Kong outbound travelers using the theory of planned behavior (TPB) over three different time horizons of 1, 5, and 10 years.

An extension was made by including two new constructs of perceived destination image and travel constraints. A cross-sectional sample of Hongkongers was surveyed. Data were collected using a self-administrated bilingual (English and Chinese) online survey. Exploratory factor analysis, linear regression and mediation analysis were conducted to test the research model.

The findings from 216 Hongkongers reveal that different combinations of the four constructs, namely, perceived behavioral control, attitude, subjective norms, and destination image, share a positive effect on individuals' travel intention to Kenya over the three different time horizons. Travel constraints act as a significant negative mediator on the four constructs in predicting travel intention to Kenya among Hongkongers.

The results provide useful insight to Kenya's destination marketing organization (DMO) and Hong Kong outbound travel agencies to integrate prominent elements into marketing strategies to arouse travel intention and expand their business prospects, which will also accelerate tourism recovery in the post-pandemic era.

By integrating two extended variables into the TPB model, this study makes a contribution by overcoming the deficiency of the original theory.

In metropolitan areas experiencing rapid urbanization and housing production, the size of housing units emerges as a crucial factor to consider in housing policy formulation. This study aims to focus on Turkey, a developing country undergoing rapid urbanization and a construction boom in recent years, to examine households’ housing size preferences. Through a detailed analysis, this research delves into the causal relationships between income, education and housing size preferences.

This study uses the Family Structure Survey in Turkey 2016 data set collected nationwide by the Turkish Statistical Institute (TurkStat). To address potential endogeneity issues related to income and education levels in households’ choice of house size, an extended regression model is used. In addition, survey weights are applied to the statistical model to generalize the results of the study.

The study demonstrates that household income correlates with an increase in house size, while household education is associated with a decrease in house size. Variables such as household age, composition and vehicle ownership are found to impact the choice of house size. Particularly, one-person and couple-only households tend to prefer smaller dwellings compared to others. Lastly, the results reveal that the influence of household composition on dwelling size varies according to household age.

This study presents a comprehensive analysis of the determinants influencing households’ housing size preferences within the framework of a developing country context, focusing on Turkey. It specifically offers insights into the causal impact of education and income levels on housing size preferences, as well as the intricate interplay between household characteristics in shaping these preferences.

This study aims to assess the household food insecurity in Malaysia during the initial phase of the movement control order (MCO) to provide insights into the prevalence and predictors of food insecurity in this context.

The research used an online cross-sectional survey between March 28 and April 28, 2020. The study collected data from the Radimer/Cornell Hunger Scale and a food insecurity instrument. Analytical tools included chi-square and logistic regression models.

Of the 411 participating households, 54.3% were food-secure, while 45.7% experienced varying food insecurity. Among these, 29.9% reported mild hunger-associated food insecurity, 8.5% experienced individual food insecurity and 7.3% reported child hunger. The study identified predictors for food insecurity, including household income, as those with total income of < RM 2,300 had 13 times greater odds (odds ratio [OR] 13.8; confidence interval [CI] 5.9–32.1; p < 0.001) than those with income of RM 5,600, marital status as divorced (OR 4.4; 95% CI 1.0–19.9; p-value = 0.05) or married (OR 1.04; 95% CI 0.52–2.1) compared to those who are single. Self-employed respondents had three times greater odds of living in a household experiencing food insecurity (OR 3.58; 95% CI 1.6–7.7; p-value = 0.001) than those in the private sector (OR 1.48; 95% CI 0.85–2.61) or experiencing job loss (OR 1.39; 95% CI 0.62–3.1) compared with those who reported being in full-time government employment.

This study acknowledged limitations, such as not considering various dimensions of food insecurity, such as coping strategies, nutritional support, diet quality and well-being, due to the complexity of the issue.

The study underscores the importance of targeted support for vulnerable groups and fostering collaborative efforts to address household food insecurity during crises like the MCOs.

The research offers insights into how to address household food insecurity and its impact on society.

It identifies predictors, quantifies increased odds and emphasizes the necessity of targeted policies and collaborative approaches for fostering resilient recovery and promoting well-being in vulnerable populations.

The present study aims to examine the households’ attitudes and intentions to adopt an indoor air purifier against the smog crisis in India by using a comprehensive theoretical framework based on the combination of the Protective Action Decision Model (PADM) and the Theory of Planned Behavior (TPB). The United Nations Sustainable Development Goals (SDGs) 2030 also emphasized ensuring a healthy and safe life, especially by achieving SDG-3, SDG-11 and SDG-13.

Using purposive sampling, the data were collected through a survey questionnaire distributed to 382 households, and study hypotheses were assessed by using partial least squares structural equation modeling employing SmartPLS.

The results revealed that mental health risk perception (MHRP) was the most influential determinant of households’ attitudes toward adopting air purifiers, followed by smog knowledge, physical health risk perception (PHRP), information seeking and product knowledge. Notably, results revealed that households’ attitude is a leading determinant of their adoption intention toward the air purifier compared to subjective norms (SN) and perceived behavioral control (PBC).

To the best of the authors’ knowledge, the present study is the first to provide new insights into an individual’s protective behavior response toward ecological hazards by examining the households’ adoption intention toward the air purifier against the smog crisis using PADM and TPB model inclusively. In addition, the present study analyzes the impact of both PHRP and MHRP on individuals’ protective behavior separately. Also, this study provides theoretical contributions and important practical implications for the government, manufacturers and air purifier sellers.

This study investigates the causal relationship and mechanisms between the development of digital finance and household carbon emissions. Its objective is to explore how digital finance can influence the carbon footprint at the household level, aiming to contribute to the broader understanding of financial innovations' environmental impacts.

The research combines macro and micro data, employing input-output analysis to utilize data from the China Household Finance Survey (CHFS) for the years 2013, 2015, 2017, and 2019, national input-output tables, and Energy Statistical Yearbooks. This approach calculated CO2 emissions at the household level, including the growth rate of household carbon emissions and per capita emissions. It further integrates the Peking University Digital Financial Inclusion Index of China (PKU-DFIIC) for 2012–2018 and corresponding urban economic data, resulting in panel data for 7,191 households across 151 cities over four years. A fixed effects model was employed to examine the impact of digital finance development on household carbon emissions.

The findings reveal that digital finance significantly lowers household carbon emissions. Further investigation shows that digital transformation, consumption structure upgrades, and improved household financial literacy enhance the restraining effect of digital finance on carbon emissions. Heterogeneity analysis indicates that this mitigating effect is more pronounced in households during the nurturing phase, those using convenient payment methods, small-scale, and urban households. Sub-index tests suggest that the broadening coverage and deepening usage of digital finance primarily drive its impact on reducing household carbon emissions.

The paper recommends that China should continue to strengthen the layout of digital infrastructure, leverage the advantages of digital finance, promote digital financial education, and facilitate household-level carbon emission management to support the achievement of China's dual carbon goals.

The originality of this paper lies in its detailed examination of the carbon reduction effects of digital finance at the micro (household) level. Unlike previous studies on carbon emissions that focused on absolute emissions, this research investigates the marginal impact of digital finance on relative increases in emissions. This method provides a robust assessment of the net effects of digital finance and offers a novel perspective for examining household carbon reduction measures. The study underscores the importance of considering heterogeneity when formulating targeted policies for households with different characteristics.

Solo travel is one of the fastest-growing tourism segments, especially among women. This study aims to identify which research topics of interest are more evident in solo female travelers (SFTs) and provide future researchers directions to explore some other research areas in SFTs.

Adopting the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, the searched keywords included “female travel*” OR “women travel*” AND solo, extracted from Web of Science, Scopus, Emerald and ProQuest databases conducted in English.

Out of the 163 initial records, 25 papers were included. The reviews revealed four research topics that are more evident in SFT studies, namely, push and pull factors, perceived risks and travel constraints, risk management and negotiation strategy and travel experience. More work is required on SFTs beyond the existing research streams.

The papers selected for this study were chosen based on the review’s selection criteria and might omit other SFT studies.

This paper contributes to uncovering the literature on SFTs to date.

Virtual wine experiences (VWEs) replaced in-person wine experiences during the Covid-19 pandemic and continue to be offered by some actors. This study aims to investigate the factors driving interest in VWEs and identify relevant traits of potential consumers to help assess VWEs long-term potential.

A representative sample of 399 Oregon and California wine consumers answered a structured online survey. The authors combine ordered logistic regression and qualitative techniques to analyze the data.

VWEs may effectively attract potential wine consumers and tourists. High interest in VWEs is associated with strong wine involvement and intentions to visit wine regions. Digitization, aversion to travel-related risk and convenience are other relevant drivers of VWE interest. The segmentation analysis revealed that consumers with a potentially higher interest in VWE have distinct traits.

Wineries and wine tourism destinations could leverage VWEs to attract wine tourists and consumers. The authors discuss specific characteristics of high-interest consumers.

Participants in VWEs interact with hosts and explore products in real time. This engagement has long-term marketing potential for attracting them as customers or visitors. The study provides strategic information for practitioners and academics on VWE interest drivers and potential demand, which is currently missing from the literature.