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COVID-19 has had various effects on women’s labour supply worldwide. This study investigates how women’s labour market outcomes in the MENA region have been affected by the stringency of governments’ COVID-19 responses and school closures. We examine whether women, particularly those with children at young age, reduced their labour supply to take care of their families during the pandemic.

To investigate whether having a family results in an extra penalty to women’s labour market outcomes, we compare single women to married women and mothers. Using the ERF COVID-19 MENA Monitor Household Surveys, we analyse the key conditions underlying women’s labour market outcomes: (1) wage earnings and labour market status including remaining formally employed, informally, unpaid or self-employed, unemployed or out of the labour force and (2) becoming permanently terminated, being suspended, seeing a reduction in the hours worked or wages, or seeing a delay in one’s wage payments because of COVID-19. Ordered probit and multinomial logit are employed in the case of categorical outcomes, and linear models for wage earnings.

Women, regardless of whether they have children or not, appear to join the labour market out of necessity to help their families in the times of crisis. Child-caring women who are economically inactive are also more likely to enter the labour market. There is little difference between the negative experiences of women with children and child-free women in regard to their monthly pay reduction or delay, or contract termination, but women with children were more likely to experience reduction in hours worked throughout the pandemic.

These findings may not have causal interpretation facilitating accurate inference. This is because of potential omitted variables such as endogenous motivation of women in different circumstances, latent changes in the division of domestic work between care-giving and other household members, or selective sample attrition.

Our analysis explores the multiple channels in which the pandemic has affected the labour outcomes of MENA-region women. Our findings highlight the challenges that hamper the labour market participation of women, and suggest that public policy should strive to balance the share of unpaid care work between men and women and increase men’s involvement, through measures that support child-bearing age women’s engagement in the private sector during crises, invest in childcare services and support decent job creation for all.

The e-commerce boom presents new challenges for last-mile delivery (LMD), which may be mitigated by new delivery technologies. This paper evaluates the impact of mobile parcel lockers (MPL) on costs and CO₂ equivalent (CO₂e) emissions in existing LMD networks, which include home delivery and shipments to stationary parcel lockers.

To describe customers’ preferences, we design a multinomial logit model based on recipients’ travel distance to pick-up locations and availability at home. Based on route cost estimation, we define the operating costs for MPLs. We devise a mathematical model with binary decision variables to optimize the location of MPLs.

Our study demonstrates that integrating MPLs leads to additional cost savings of 8.7% and extra CO₂e emissions savings of up to 5.4%. Our analysis of several regional clusters suggests that MPLs yield benefits in highly populous cities but may result in additional emissions in more rural areas where recipients drive longer distances to pick-ups.

This paper designs a suitable operating model for MPLs and demonstrates environmental and economic savings. Moreover, it adds recipients’ availability at home to receive parcels improving the accuracy of stochastic demand. In addition, MPLs are evaluated in the context of several regional clusters ranging from large cities to rural areas. Thus, we provide managerial guidance to logistics service providers how and where to deploy MPLs.

This study aims to investigate whether the extent of corporate disclosure, proxied by COVID-19-related disclosure, affects the dividend policy of listed firms.

The study uses a multinomial logistic regression model to examine the relation between corporate disclosure and the dividend policy of the 100 largest market-cap firms in Vietnam in 2021. The COVID-19 pandemic, with its unique impact on business operations, serves as the backdrop for this analysis.

The findings indicate that firms with more extensive COVID-19-related disclosure are more inclined to distribute dividends in the form of stocks or cash instead of omitting them.

This research contributes to the understanding of how corporate disclosure practices influence a firm’s financial decisions, particularly in the context of the COVID-19 pandemic. The findings hold implications for corporate financial decision-making during times of macroeconomic shock.

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.

This study aims to explore the smallholder farmers’ perceptions of climate change and its adaptation options (changing crop variety; improved crop and livestock; soil and water conservation [SWC]; and irrigation practices) and drought indices in the Dire Dawa Administration Zone, Eastern Ethiopia.

A cross-sectional household survey was used. A structured interview schedule for respondent households for key informants and focus group discussions were used. This study used both descriptive statistics and an econometric model. The model was used to compute the determinants of climate adaptation options in the study area. Drought characterization was carried out by DrinC software.

The results revealed households adapted to selected adaptation options. The model results confirmed that education level, farm size, tropical livestock units (TLUs) and access to agricultural extension services have positive and significant impacts on changing crop variety by 0.0014%, 0.045%, 0.032% and 0.035%, respectively. The likelihood of farmers’ decisions to use adaptation strategies (family size, TLU, agricultural extension service and distance from the market) has positive and significant impacts on SWC. The reconnaissance drought index (RDI6) of ONDJFM and AMJJAS showed extreme and severe drought index values of −2.88 and −1.96, respectively.

This study used a locally adopted climate change adaptation intervention for smallholder farmers, revealing the importance of drought characterization indices both seasonally and annually.

The purpose of this study is to examine the buyers’ preferences influencing the purchase of privately developed affordable housing in Kolkata and to determine whether unsold houses result from misalignment with these preferences.

The literature review and user-opinion survey identified 119 independent variables that indicate buyers’ preferences. A questionnaire survey of 383 households in affordable housing units from 32 housing complexes in Kolkata recorded buyers’ preferences and satisfaction against the independent variables grouped under five levels of characteristics. The product weights of variables derived from the rank sum method and percentage satisfaction give the Utility Score. Multivariate regression and univariate linear regressions were conducted to determine the significance of each Level of characteristics and each variable, identifying the significant variables that would affect the sale of affordable houses.

The multivariate regression analysis has indicated that 68.56% of the variation in the percentage of unsold houses was explained by the five utility scores, which affirms that misalignment with buyers’ preferences significantly affects the sale of privately developed affordable houses. Furthermore, building and neighbourhood-level utility show the highest significance as predictors, while city-level and miscellaneous utility have moderate significance, but housing complex-level utility lacks statistical significance.

This study addresses a research gap in privately developed affordable housing in Kolkata, enhancing understanding of buyer preferences in this segment.

Indian railways (IR) is one of the largest railway networks in the world. As a part of its strategic development initiative, demand forecasting can be one of the indispensable activities, as it may provide basic inputs for planning and control of various activities such as coach production, planning new trains, coach augmentation and quota redistribution. The purpose of this study is to suggest an approach to demand forecasting for IR management.

A case study is carried out, wherein several models i.e. automated autoregressive integrated moving average (auto-ARIMA), trigonometric regressors (TBATS), Holt–Winters additive model, Holt–Winters multiplicative model, simple exponential smoothing and simple moving average methods have been tested. As per requirements of IR management, the adopted research methodology is predominantly discursive, and the passenger reservation patterns over a five-year period covering a most representative train service for the past five years have been employed. The relative error matrix and the Akaike information criterion have been used to compare the performance of various models. The Diebold–Mariano test was conducted to examine the accuracy of models.

The coach production strategy has been proposed on the most suitable auto-ARIMA model. Around 6,000 railway coaches per year have been produced in the past 3 years by IR. As per the coach production plan for the year 2023–2024, a tentative 6551 coaches of various types have been planned for production. The insights gained from this paper may facilitate need-based coach manufacturing and optimum utilization of the inventory.

This study contributes to the literature on rail ticket demand forecasting and adds value to the process of rolling stock management. The proposed model can be a comprehensive decision-making tool to plan for new train services and assess the rolling stock production requirement on any railway system. The analysis may help in making demand predictions for the busy season, and the management can make important decisions about the pricing of services.

There has been a lot of research on how to set marketing budgets, but the overlooked aspect was how allocating funds influences business performance in a multi-goal context. This study aims to examine the relationship between business performance, the process of allocating funds to multiple goals and the interaction among the goals.

Ratio data were generated through “a constant sum scale” from a sample of 362 managers from the B2C sector, besides data on after-tax revenue for two years. The data file was created. Then, a factor analysis was performed on the data. Furthermore, an econometric model with interaction terms was fitted to the data.

The results show that allocating funds to multiple marketing goals – demand generation, customer experience, brand image, marketing competency and purchase intention – influences business performance. Furthermore, a goal’s impact on business performance is higher when coupled with other goals than in isolation.

The findings of the study should assist managers in increasing revenue while spending less on marketing and shifting funds from less efficient goals and pairs of goals to highly efficient ones.

By extending the relevant theory on the relationship between the process of marketing fund allocation, multiple goals and business performance, this study contributes to the literature on marketing.

The purpose of this paper is to examine the prevalence of labour force participation and the factors affecting labour supply among older persons in Ghana. Both the extensive and intensive margins of older persons’ labour supply were analysed.

The paper uses nationally representative samples of household and individual data in 2016–2017 – Ghana Living Standard Survey (GLSS 7) data – for the analysis. Heckman’s sample selection model is used to analyse both the extensive and intensive margins of older persons’ labour supply.

The study found that older persons in Ghana who are pensioners, widowed, have high levels of education, poor health status and live in urban areas are less likely to participate actively in the labour market. On the other hand, being head of a household, married and owning certain assets increase the likelihood of an older person to work. Furthermore, pensions, household headship and post-secondary education have negative effects on the labour supply as having them make older persons work fewer hours per week compared to their counterparts.

This research is the first study to examine the prevalence of old age employment and factors that affect labour market decisions of older persons in Ghana. It also adds to the limited literature on pension and retirement decisions in developing countries.

The advent of the postpandemic era has brought renewed attention to the development of business tourism. However, the existing research on business tourism is fragmented, and there are gaps in the current understanding of the subject. This study aims to identify the intellectual structures, current hotspots and research directions in the business tourism field from 1994 to 2023.

A bibliometric visual analysis using VOSviewer was conducted to assimilate the available knowledge from 136 business tourism-related articles collected in the WoS Core Collection database between 1994 and 2023.

The results indicate that the number of business tourism-related research fluctuates, but the overall trend is gradually increasing. It synthesizes four main research themes, which are tourist behavior, destination marketing, information technology and work-family interferences of business travelers.

To the best of the authors’ knowledge, this study is among the first to systematically review business tourism publications over the past 29 years. It assists scholars in gaining a more comprehensive understanding of business tourism research and informs future research directions.

后疫情时代的到来使得商务旅游的发展再次受到关注。然而, 目前的商务旅游研究是零散的, 我们对与这一主题的理解存在空白。本研究旨在确定1994至2023年商务旅游相关领域的知识结构、当前热点和研究方向。

本研究使用VOSviewer进行了文献计量学可视化分析, 以吸收从Web of Science（WOS）核心合集数据库中收集的136 篇1994年至2023年间的商务旅游相关文章中的可用知识。

结果表明, 与商务旅游相关的研究数量呈现出波动但总体逐渐增加的趋势。其中包括四个主要的研究主题, 分别是游客行为、目的地营销、信息技术和商务旅行者的工作与家庭。

本研究系统回顾了过去29年间与商务旅游相关的出版物。从而有助于学者们对商务旅游研究有更全面地了解, 并获得未来的研究方向。

El advenimiento de la era postpandemia ha renovado la atención prestada al desarrollo del turismo de negocios. Sin embargo, la investigación existente sobre el turismo de negocios está fragmentada y existen lagunas en la comprensión actual del tema. El presente estudio tiene como objetivo identificar las estructuras intelectuales, los focos actuales y las direcciones de investigación en el ámbito del turismo de negocios desde 1994 hasta 2023.

Se realizó un análisis visual bibliométrico utilizando VOSviewer para asimilar el conocimiento disponible en 136 artículos relacionados con el turismo de negocios recogidos en la base de datos WoS Core Collection entre 1994 y 2023.

Los resultados indican que el número de investigaciones relacionadas con el turismo de negocios fluctúa, pero la tendencia general es a aumentar gradualmente. Se sintetizan cuatro temas principales de investigación: el comportamiento del turista, el marketing de destinos, la tecnología de la información y las interferencias trabajo-familia de los viajeros de negocios.

Este estudio es uno de los primeros que revisa sistemáticamente las publicaciones sobre turismo de negocios de los últimos 29 años. Ayuda a los investigadores a obtener una comprensión más completa de la investigación sobre el turismo de negocios y sugiere futuras líneas de investigación.