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This study aims to investigate the relationship between Kosovo remittances, migration and labor force participation and seeks to uncover how migration and remittances, often considered separately, interact to shape labor market outcomes across gender, age and education groups.

To analyze the relationship between remittances, migration and labor force participation, this study leverages multivariate probit (mvprobit) to rectify the endogeneity issue intrinsic from remittances and migration. Utilizing this robust methodological approach allows us to circumvent the limitations traditionally associated with biprobit analysis. The research is grounded in empirical evidence from the Millennium Century Corporation survey in Kosovo.

The findings indicate that remittances and migration are pivotal determinants in shaping the contours of labor force participation, particularly influencing disparities across gender, age and educational attainment. Further, this study unearthed intriguing evidence suggesting the disincentivizing effect of remittances on labor force participation, alongside the potentially disruptive influence of prospective migration plans.

The novelty of this work lies not only in the context-specific insights it provides into the socio-economic fabric of Kosovo—an area that has hitherto received limited scholarly attention—but also in its methodological innovation. The simultaneous application of mvprobit technique provides a nuanced approach to tackle the inherent endogeneity issue, thereby pushing the methodological frontiers of the field.

This study is motivated in part by the fact that the unfolding 2022 bear market, which has reached the −25% drawdown, has not been preceded by the inverted 10Y-3 m spread or an inverted near-term forward spread.

The authors develop a three-factor probit model to predict/explain the deep stock market drawdowns, which the authors define as the drawdowns in excess of 20%.

The study results show that (1) the rising credit risk predicts a deep drawdown about a year in advance and (2) the monetary policy easing precedes an imminent drawdown below the 20% threshold.

This study three-factor probit model shows adaptability beyond the typical recessionary bear market and predicts/explains the liquidity-based selloffs, like the 2022 and possibly the 1987 deep drawdowns.

This article aims to investigate the role of socioeconomic factors and individual time preferences in the demand for fast-food in Russia. An individual discount rate shows the ability of a person to postpone utility from consumption to future periods.

An individual discount rate is measured through a hypothetical money experiment. The database is the special survey of the Levada analytical center conducted in 2017. Multivariate probit model enables the authors to consider the possible endogeneity of individual discount rate and reveal the relationship between socioeconomic factors and frequent fast-food consumption.

Results show that a higher individual discount rate is related to frequent consumption of fast-food. At the same time, there are factors that provoke both a higher individual discount rate and the refusal of frequent consumption of fast-food. Findings advise the prioritization of measures highlighting the short-term benefits of healthy eating and the short-term costs of avoiding it.

To the authors' knowledge, this article is the first one which presents comprehensive investigation of microeconomic factors of fast-food consumption in Russia including individual time preferences of consumers.

Attaining the Sustainable Development Goal 2 (SDG2) of zero hunger continues to be a challenge in most parts of Sub-Saharan Africa. However, financial inclusion is seen as a potential pathway for reducing food insecurity among poor households. Mobile money is a financial inclusion instrument that is easily accessible to poor households and has the potential to increase the level of financial inclusion. This paper contributes to the literature by examining the determinants of mobile money adoption, its effects on household food security and the choice of coping strategies in Burundi, a post-conflict and fragile country.

Using survey data that involved 860 households in Burundi, we adopted the Household Hunger Scale (HHS) developed under the Food and Nutrition Technical Assistance Project to measure household food security. We further employ the endogenous switching regression treatment effects model for ordered outcomes and the multivariate probit model to achieve our aims.

The results of our study reveal that the adoption of mobile money is influenced by factors such as gender, marital status, age, formal education, membership in a social network, area of residence and access to a tarred road network. Additionally, the food security status of a household was determined by marital status, formal education, social network membership, access to tarred roads, off-farm income, access to credit and land tenure security. We confirm that mobile money adoption has a significantly positive effect on the food security status of households with heterogeneity in gender and area of residence. We also find that mobile money adoption reduces the likelihood of households adopting consumption-related coping strategies.

The promotion of mobile money should, therefore, be included in Burundi’s national food security policies.

This study contributes to the literature by providing empirical evidence on the effect of mobile money adoption on household food security and the choice of coping strategies in a post-conflict context.

Multiple chronic conditions (MCCs) have attracted significant public policy and clinical attention. Whether MCCs determine other important outcomes, or are themselves the outcomes of health-producing activities or interventions, metrics based thereon have potential to be useful indicators of the health of populations and of differences between and among the health of subpopulations. While the attention MCCs are attracting in various policy circles is impressive, MCCs' potential roles as indicators of population health and of how health determinants influence population–health outcomes have received less attention. The purpose of this chapter is to direct attention towards questions that involve considerations of chronic condition (CC) patterns as health outcomes; specifically, this paper hopes to advance the consideration of patterns of MCCs as indicators of individual and population health. Using data from the United States (US) Behavioural Risk Factor Surveillance System (BRFSS), the chapter explores whether both the ‘intensity’ (i.e. the number or count) of CCs as well as their ‘composition’ (i.e. the patterns of particular CCs) might be jointly of interest when considering the prevalence of MCCs in populations and how the nature of MCCs may vary across subpopulations of interest. It is seen that information about intensity tells an incomplete story about MCC health outcomes.

 Social assistance programs have been implemented in Madagascar to assist the most vulnerable and neediest poor in achieving a minimum standard of living during critical times. In the Grand South and Southeast Madagascar, where climate change, price fluctuations and sociopolitical instability threaten the population’s livelihood, the effectiveness of such aid-based programs is uncertain because of possible mistargeting. This study aims to assess the accuracy of the targeting methodology of four different types of social protection programs in Southern Madagascar.

The authors draw evidence from a national representative data set and use multiple techniques that integrate targeting performance and regression-based analyses.

Results show that cash transfers constitute the only program that effectively reaches the poorest 20% living in drought- and cyclone-affected regions. However, mistargeting is likely to occur in food, seed transfers, and the HIMO public works programs. Social inclusion information related to proximity to urban zones, religious affiliation, and number of long-lasting insecticide-treated nets are significantly associated to all program participation. Nevertheless, a serious under-coverage of the eligible poor is noted for Southern Madagascar.

This study is among the first to evaluate the targeting effectiveness of social programs in Madagascar. It introduces a novel approach to evaluating the poverty rate by utilizing a composite-based wealth score. The authors enhance the classic targeting assessment methodology by incorporating geospatial covariates, categorical, geographical and social network information into an econometric model. The study provides a comprehensive view of the main profile of beneficiaries reached by four social assistance programs in Southern Madagascar.

The aim of this study is to provide an empirical investigation of the agricultural cluster’s economic, social and environmental values. By doing so, the authors aim to offer policymakers and decision-makers a strategic approach that promotes competitiveness and economic development through shared value.

The authors used AMOS software and applied structural equation modeling to achieve the study’s objectives. The study used this approach with path analysis through the Analysis of Moment Structures software.

The empirical results indicate that creating shared value (CSV) can enhance the agricultural sector’s competitiveness through clustering. Rather than enhancing competitiveness directly, CSV plays a crucial role in improving the relationship between clustering and competitiveness. The authors also examined Porter’s diamond of competitiveness and evaluated factors for creating a shared value strategy, such as factor conditions, demand conditions, related and supporting industries, strategy, structure, rivalry and the role of government.

This study focuses solely on the agricultural cluster in Qalqilya governorate and cannot be applied to other regions without additional research.

Ensuring that stakeholders in the agricultural sector are kept informed about the activities of the cluster and the benefits of their participation is crucial. Empirical findings and conclusions have demonstrated that a shared value strategy can enhance the competitiveness of this sector. To achieve this, institutions involved in developing the agricultural cluster must increase their efficiency and capacity. Consulting experts in this field and drawing on experiences from other countries can aid in achieving this goal. Additionally, enhancing farmers’ productivity should be a priority, and the Ministry of Agriculture can provide training and workshops to improve their skills and expertise.

This study suggests that Palestinian policymakers should establish effective partnerships between the government and the agricultural sector’s firms in Qalqilya to reinforce the cluster’s competitiveness. This strategy can stimulate competitiveness and promote economic and social development in Palestine.

This paper examines the relationship between open innovation (measured by exploratory and exploitative linkages) and firm-level innovative activity in the offshore renewable energy (ORE) sector.

A unique, purpose-built survey that targeted firms operating in the ORE sector and its supply chain was used. The data provides novel insights into the research activities and networking capabilities of an industry in its infant stages of development. Regression models are used to estimate the relationship between firm-level external linkages and innovative activity.

Exploratory linkages are positively related to more innovative activity. This relationship is subject to diminishing returns, distinguishing the ORE sector from other sectors. Collaborating with suppliers and accessing scientific journals are conducive to research and development (R&D) activity and process innovation, whilst collaborating with customers is associated with the decision to introduce new products and processes.

This study provides evidence of a positive, but curvilinear, relationship between external knowledge linkages and innovative activity, adding novel insights into the relationship between open innovation (OI) strategies, research and innovation outcomes for firms predominantly in the introductory stages of the technological life cycle with limited commercialisation experience. The nuanced finding that specific linkages matter for certain research and innovation (R&I) outcomes adds deeper complexity to March’s (1991) framework, where tailoring certain exploratory or exploitative linkages to specific innovation activities is important.

Responding to calls for deeper analysis of the conceptual foundations of service infusion in manufacturing, this paper examines the underlying assumptions that: (i) manufacturing firms incorporating services follow a pathway, moving from pure-product to pure-service offerings, and (ii) profits increase linearly with this process. We propose that these assumptions are inconsistent with the premises of behavioural and learning theories.

Machine learning algorithms are applied to test whether a successive process, from a basic to a more advanced offering, creates optimal performance. The data were gathered through two surveys administered to USA manufacturing firms in 2021 and 2023. The first included a training sample comprising 225 firms, whilst the second encompassed a testing sample of 105 firms.

Analysis shows that following the base-intermediate-advanced services pathway is not the best predictor of optimal performance. Developing advanced services and then later adding less complex offerings supports better performance.

Manufacturing firms follow heterogeneous pathways in their service development journey. Non-servitised firms need to carefully consider their contextual conditions when selecting their initial service offering. Starting with a single service offering appears to be a superior strategy over providing multiple services.

The machine learning approach is novel to the field and captures the key conditions for manufacturers to successfully servitise. Insight is derived from the adoption and implementation year datasets for 17 types of services described in previous qualitative studies. The methods proposed can be extended to assess other process-based models in related management fields (e.g., sand cone).

The timeliness and quality of information provided to board members are crucial for them to effectively monitor and advise a firm. This study examines the influence of board composition and structure on (1) the board’s actions to mitigate the information asymmetry problem by implementing enterprise information systems (EIS) and (2) the board of directors’ awareness of information asymmetry, their perception of its causes and their efforts to address it.

Our research employs a mixed-methods approach. First, using data from 115 publicly listed Chinese companies, we empirically assess the likelihood of top-level EIS modules adoption at the firm level. Subsequently, through 23 semi-structured interviews, we aim to gain deeper insights into the behavioral motivations behind directors’ attempts to reduce information asymmetry.

The study reveals that boards with a higher number of independent directors or with a strategy committee – indicative of a greater concern regarding information asymmetry problems – are more inclined to adopt top-level EIS modules. Additionally, we identify three primary sources of information asymmetry that directors consider significant in prompting the adoption of top-level EIS modules to alleviate perceived information asymmetry.

This study contributes to both the corporate governance and information systems literature. The implementation and utilization of EIS at the board level have not been extensively explored previously. Moreover, while the issue of information asymmetry at the board level is recognized as a critical governance challenge, the ways in which directors perceive and address this issue remain largely unknown. Our research seeks to illuminate this relatively less-explored area.