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The purpose of this paper is to explore the factors that influence migrant workers' household registration transfer willingness at both individual and urban levels and to provide empirical evidence on adjusting the household registration system to accommodate economic development and migrant workers' imbalances.

This paper adopts a hierarchical nonlinear model and examines individual and urban influencing factors of migrant workers' household registration transfer willingness, based on the data from China Migrants Dynamic Survey (CMDS) and the Urban Statistical Yearbooks.

This paper shows that: (1) multi-factors, such as age, education, marital status, household demographics, industry and migrant workers' contract coverage, have significant effects on migrant workers' household registration transfer willingness; (2) The urban public service equalization indicators, such as regional economic, educational resources, medical care and ecological quality, have significant effects on migrant workers' willingness to transfer household registration; (3) The heterogeneity of migrant workers' willingness to transfer household registration is significant in central, eastern and western China.

The authors provide a fresh perspective on population migration research in China and other countries worldwide based on the pull–push migration theory, which incorporates both individual and macro (urban) factors, enabling a comprehensive examination of the factors influencing household registration transfer willingness. This hierarchical ideology and approach (hierarchical nonlinear model) could be extended to investigate the influencing factors of various other human intentions and behaviors.

Micro approaches (individual perspective) have dominated existing studies examining the factors influencing migrant workers' household registration transfer willingness. The authors combine individual and urban perspectives and adopt a more comprehensive hierarchical nonlinear model to extend the empirical evidence and provide theoretical explanations for the above issues.

Focusing on micro-level indicators, we investigate financial inclusion levels in rural China, examining its determinants and impact on household welfare. We construct a financial inclusion index of four essential financial services: savings, digital payments, credit and insurance. We identify factors influencing financial inclusion among Chinese rural households and assess the effects of financial inclusion on household welfare.

With the entropy method, we use data from the 2019 China Household Finance Survey to assess financial inclusion levels in rural China. Determinants and their impact on welfare are analyzed through probit and ordinary least squares models, respectively. Propensity scoring matching is applied to address potential endogeneity.

We reveal that rural households exhibit limited usage of formal financial services, with notable regional disparities. The eastern region enjoys the highest financial inclusion and the central region lags behind. Household characteristics such as family size, education level of the household head, income, employment status and financial literacy significantly influence financial inclusion. Financial inclusion positively impacts household welfare as indicated by household consumption expenditure. The use of different types of financial services is crucial with varying but significant effects on household welfare.

This study offers valuable insights into China’s rural financial inclusion progress, highlighting potential barriers and guiding government actions.

While the monetary returns to education are well documented in the economics literature, the studies on non-monetary returns to education are scarce. The purpose of this study is to provide new insights into the non-market outcomes by exploring how education influences the food consumption choices of households and how these effects vary across different socio-economic groups using household-level calorie consumption data from Sri Lanka.

This study uses two waves of Household Income and Expenditure Surveys – 2006/2007 and 2016. The methods adopted in analysing the data were descriptive statistics and the OLS regression model.

The empirical results show that educated poor households pay less per calorie compared to non-educated poor households, highlighting the role of education in improving the ability to make better food choices and manage household budgets more economically.

This study informs policy-makers of the importance of education for formulating food and nutritional policies, which aim to raise the standard of living of resource-poor and vulnerable households in Sri Lanka as well as other developing countries with similar socio-economic conditions.

To the best of the authors' knowledge, this study is the first to explore the impact of education on the calorie consumption behaviour of people in the Sri Lankan context using nationwide household surveys.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2022-0007

Agriculture in Ethiopia relies heavily on traditional farm power sources and is designated by the lowest farm machinery access, in contrast to other Sub-Sahara African (SSA) countries. The purpose of this research is to analyze the heterogeneity of mechanization service transactions and factors determining farmers' cooperation in mechanization clusters and willingness to accept land consolidation.

The authors conducted a cross-sectional survey of producer households in major crop production areas in the Oromia, SNNPR, Amhara and Tigray regions. The sampling design involved three stages: districts were selected using a stratified sampling approach accompanied by simple random samples of kebele units and producer households in the second and final stages, respectively.

This study’s results show that mechanization service costs, service relationships, clustering and land consolidation exhibit significant heterogeneity across the study areas. Cluster farming was found to be advantageous against diseconomies, rationalized by upgrading the mechanization scale. The probit model parameterization of the probability distributions reveals that household, land, crop, mechanization service, remoteness and location-related factors determine participation in mechanization clusters and willingness to accept land consolidation.

Fostering cooperation by focusing on constraints and demand of users is suggested to reduce transaction costs and expand hired mechanization services to unaddressed areas. The findings are relevant to most SSA countries where mechanization development is hampered by land fragmentation.

Limited information is available on agricultural mechanization development for smallholder farmers, particularly in Ethiopia, and this study adds empirical evidence about the synergy between cluster farming and mechanization, horizontal coordination and alternative supply models.

This study profiles and segments potential tourists on the basis of their various attitudes toward artificial intelligence (AI) services. Furthermore, this study distinguishes descriptors among the different clusters, such as preference for using diverse AI services, overall image of AI services, willingness to use AI services (WUAI), willingness to pay more for AI services (WPAI) in tourism and hospitality, and characteristics of respondents.

An online survey was conducted in South Korea. Data on 758 potential tourists were used for K-means cluster analysis.

This study identified three distinct tourist segments with differentiated attitudes toward AI services: the group aspiring to use or fantasizing about AI services (Cluster 1), the group being knowledgeable and supportive of AI services (Cluster 2), and the group having low interest about AI services (Cluster 3).

Members of Cluster 2 were the most marketable as this segment exhibited the greatest knowledge of and support for AI services, while Cluster 1 would be an ideal segment to launch and test novel AI services.

This study extends the authors’ knowledge of AI scholarship by unpacking the existing market segments, which could be tapped to sustain AI penetration in the tourism industry. Hence, this study contributes to existing debates on AI scholarship, which is predominated by conceptual reflections and issues of AI services in the tourism and hospitality field.

This study examines the drivers of marketing channel participation amongst smallholder rice farmers in the northern region of Ghana.

Using a sample of 397 smallholder rice farmers drawn from a multistage sampling procedure, the study employed multivariate probit (MVP) model in the empirical estimations. In this context, the model assumes that a rice farmer should at least participate in one market channel.

The study reveals that the wholesaler market channel is the most commonly used channel among farmers, followed by the aggregator channel. However, the processor market channel is the least patronized one in the study area. The results also show statistically significant correlation coefficients in four out of the six possible combinations, implying that market channel participation among smallholder farmers is not mutually exclusive. Rice market channel participation is positively and significantly influenced by age, gender, household headship, access to credit, extension service, irrigation, improved seed and access to price information.

This study is limited in extending the analysis to include the impact of market channels on some outcome measures. This is due to data limitation.

The findings of this study add to the growing literature on smallholder market channel participation in Ghana.

Maize and rice constitute the two major staple crops in Ghana. The demand for maize and rice outstrips production levels in Ghana, creating deficits for farmers to capitalize on to increase yield. Farmers procure certified seeds from different supply outlets to improve crop yield. This study assessed the effectiveness of supply outlets of certified maize and rice seeds. This study also examined factors that influence smallholder farmers' decisions in sourcing seed from the identified supply outlets.

Multi-stage sampling was used to collect data from smallholder farmers. A total of 360 farmers were interviewed for the analysis. The multivariate probit model was used to estimate the main drivers of the supply outlets of certified seeds.

The findings revealed that farmers' decisions to use certified seeds from a particular supply outlet are contingent on household size, years of farming, extension contacts, distance to the nearest market, distance to the district capital, access to credit and farm size.

Sourcing certified seeds from National Seed Traders Association of Ghana, Research Institutions and Ministry of Food and Agriculture is more effective than input dealers, open market and family and friends.

This study is one of its kind that looked at how effective are the supply outlets of certified seed purchasing outlets.

This study aims to determine website quality, young adult socialization and dark triad personality as the factors influencing the real estate purchase decision. In addition, this study also measures the mediating effects of young adult socialization on real estate purchase buying behavior.

Related literature, quantifiable variables with a five-point Likert scale, hypothesis testing and mediators are used to study the model. A systematic questionnaire that was divided into four sections was used. A total of 336 valid responses were collected and analyzed through a structural equation model.

The results suggest that dark triad personality and young adult socialization considerably affect real estate purchase decisions. The development proves website quality does not significantly impact real estate purchase behavior.

This study is limited to a few young consumers’ responses. Future studies could be more widespread globally and should include more variables and offline methods of purchasing behavior.

As per the review of existing literature, this research is the first, to the best of the authors’ knowledge, to determine the factors affecting the real estate purchase decision with factors like website quality, dark triad personalities and young adult socialization involving it.

This study assesses the extent to which integrated extension services contribute to the adoption of climate-smart agriculture (CSA) innovations within the cotton value chain in Burkina Faso.

To address the research question, a probit multivariate econometric model with sample selection is utilized. The model is applied to a random sample of farmers (n = 510), and the endogeneity is addressed through a control function approach.

The study highlights the central role of value chains, particularly in the cotton sector, in overcoming resource scarcity through integrated extension services. Findings show that smallholder farmers who benefit from sound extension services are more willing to adopt and diversify CSA technologies. These include improved seeds, conservation techniques, adapted planting dates and mechanization. This study confirms the synergistic nature of these technologies and emphasizes that effective climate risk mitigation depends on the combined adoption of CSA technologies.

The use of cross-sectional data limits the analysis of long-term farmer behavior, and due to data limitations, the focus was primarily on the contributions of cotton companies and farmers to climate risk mitigation. Future research using panel data across the value chain could provide a more robust insights for policy decision-making.

The study contributes to the existing body of knowledge by emphasizing the crucial role of integrated extension services within the cotton value chain in developing countries. This highlights the critical benefits for farmers and emphasizes the need to diversify modern technologies to effectively combat climate change and its variability in agriculture.

Many town centres in England exhibit high retail property vacancies and require regeneration. Several alternatives for the replacement of town centre retail (TCR) have been suggested, one of which is healthcare. The healthcare sector in England is in distress, with the National Health Service (NHS) tackling extensive patient waiting lists, whilst operating from an ageing estate. This paper is an introductory study that uses seven carefully selected personalised surveys to raise academic awareness of the importance and potential of integrating healthcare into town centres and calls for large-scale research to establish the statistical validity of the reported observations.

This study is developed from an interpretative standpoint. Through semi-structured interviews with key stakeholders specific to retail-to-healthcare conversions, this study reports stakeholders' perspectives on opportunities and limitations for such conversions to give direction for large statistical research in the future.

All participants support the integration of healthcare into town centres and agreed that diagnostic services, mental health support and primary care services are appropriate for provision within town centres. The participants advocate large-scale change in town centres in England, with integrated healthcare co-located with complementary services to fit with wider regeneration plans. Participants prefer adaptation of existing buildings where technically feasible and emphasise the importance of obtaining the buy-in of other stakeholders whilst expressing concerns about the uncertainty of capital funding availability.

This is the first study to analyse the practice of retail-to-healthcare conversions in town centres. These are still rare in England and projects are complex. The market experience is limited, and thus, the literature is scarce. This study fills this void and provides a starting point for future quantitative research in this area and informs the new town-planning policies.