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This study aims to identify the main challenges to achieving humanitarian logistics in the context of United Nations peace missions in sub-Saharan Africa and to present suggestions for overcoming the logistical gaps encountered.

The methodological approach of the work focuses on the comparative case study of the United Nations Mission in South Sudan, the United Nations Multidimensional Integrated Stabilisation Mission in the Central African Republic and The United Nations Organisation Stabilisation Mission in the Democratic Republic of Congo from 2014 to 2021. The approach combined a systematic literature review with the authors’ empirical experience as participant observers in each mission, combining theory and practice.

As a result, six common challenges were identified for carrying out humanitarian logistics in the three peace missions. Each challenge revealed a logistical gap for which an appropriate solution was suggested based on the best practices found in the case study of each mission.

This paper presents limitations when addressing the logistical analysis based on only three countries under the UN mission as a case study, as well as conceiving that certain flaws in the system, in the observed period, are already in the process of correction with the adoption of the 2016–2021 strategy by the UN Global Logistic Cluster. The authors suggest that further studies can be carried out by expanding the number of cases or using countries where other bodies (AU, NATO or EU) work.

To the best of the authors’ knowledge, this study is the first comparative case study of humanitarian logistics on the three principal missions of the UN conducted by academics and practitioners.

This paper examines whether the successful bid rate of the OnBid public auction, published by Korea Asset Management Corporation, can identify and forecast the Korea business-cycle expansion and contraction regimes characterized by the OECD reference turning points. We use logistic regression and support vector machine in performing the OECD regime classification and predicting three-month-ahead regime. We find that the OnBid auction rate conveys important information for detecting the coincident and future regimes because this information might be closely related to deleveraging regarding default on debt obligations. This finding suggests that corporate managers and investors could use the auction information to gauge the regime position in their decision-making. This research has an academic significance that reveals the relationship between the auction market and the business-cycle regimes.

This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?

A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.

The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.

The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.

The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?

In a world characterised by increasing environmental and social awareness, the number of corporate social responsibility and sustainability initiatives has significantly grown. Among these, the United Nations Global Compact (UNGC) is one of the most important, involving more than 12,000 companies. The purpose of this study is to investigate the UNGC’s worldwide diffusion, both at country and industry level, to understand the reasons leading to the highlighted dissemination patterns, and to propose various future projections.

The study pursues its objectives by applying the logistic curve model to data provided by the United Nations. The analysis is complemented by adopting instability and concentration indexes.

Results suggest that, while human rights and environmental safeguard in some areas and industries will remain a controversial issue, UNGC adoption will continue growing and giving the participants the required legitimacy to compete in worldwide markets.

To the best of the authors’ knowledge, this is the first paper that analyses the UNGC’s worldwide diffusion and proposes a prediction model for its future dissemination. The findings are of considerable importance in extending the knowledge of the initiative and in understanding the potential values of its adoption.

The recent promotion of prefabricated housing (PH) in China has resulted in a prosperous period for its implementation. However, transaction costs (TCs) cause low economic efficiency to stakeholders and hinder the further promotion of PH. No relevant study has yet been made to investigate the TCs and their causes in the PH field. This paper identifies critical TCs and explores the influencing factors from the developers' perspective.

Semi-structured interviews and a questionnaire survey were used to collect data about TCs and influencing factors. The most influential factors are identified with their impacts on particular TCs, yielded from correlation analysis and logistic regression.

From the developers' perspective in China's PH market, this study identified that the most concerning sources of TCs are: hidden costs arising from disputes, extra workloads from design changes, learning costs, intensive communication and coordination in assembly and unexpected information costs in decision-making. The use of an ordered logistic regression approach indicates that the four most influential factors are: qualification of the general contractor, mandatory local policies, owner type and competitiveness of the developer.

To reduce the TCs, experiencing learning and ensuring the design scheme's complicity are recommended to save information searching and exchanging costs. The implications for the PH developers are for them to: (1) professionalize their own organization and (2) procure high-qualified general contractors. For the policymakers, this means they should improve the clarity of the mandatory local policies for PH step-by-step.

By applying the TCs economic theory, this study explores factors that influence TCs in the PH industry. It sheds light on the influencing mechanism behind the TCs in the context of prefabricated housing.

Malnutrition is one of the serious public health problems especially for children and pregnant women in developing countries such as Bangladesh. This study aims to identify the risk factors associated with child nutrition for both male and female children in Bangladesh.

This study was conducted among 23,099 mothers or caretakers of children under five years of age from a nationally representative survey named Bangladesh Multiple Indicator Cluster Survey, 2019. This study used chi-square test statistic for bivariate analysis and multinomial logistic regression was used to evaluate the adjusted effects of those covariates on child nutritional status.

The prevalence of severely malnourished, nourishment was higher for males than females (5.3% vs 5.1%, 77.4% vs 76.8%) while moderately malnourished were higher for females (18.1% vs 17.4%). The findings from the multinomial model insinuated that the mother’s education level, wealth index, region, early child development, mother’s functional difficulties, child disability, reading children's books and diarrhea had a highly significant effect on moderate and severe malnutrition for male children. For the female children model, factors such as mother’s education level, wealth index, fever, child disability, rural, diarrhea, early child development and reading less than three books were significant for moderate and severe malnutrition.

There is a solution to any kind of problem and malnutrition is not an exceptional health problem. So, to overcome this problem, policymakers should take effective measures to improve maternal education level, wealth status, child health.

The main goal of this paper is to identify the attributes of consumer experience in Michelin-starred restaurants and to estimate their effects on restaurant ratings.

A sample of 70,233 online reviews of 224 Spanish Michelin-starred restaurants were analysed with the latent Dirichlet allocation algorithm. A sentiment analysis and a logistic regression analysis were also employed to estimate the effect of attributes on restaurant ratings.

Customer attention, food quality, decor and ambience and value for money are frequently used to define restaurant experience. However, it is shown in this study that the experience in a Michelin-starred restaurant goes beyond the evaluation of those four attributes. Furthermore, the effect of the factors that were identified on customer satisfaction differed depending on the restaurant ratings.

The findings are linked to the context of Spanish Michelin-starred restaurants. It is also assumed in this study that online reviews are based on truthful opinions.

Restaurant managers should primarily focus on customer attention and food quality to achieve customer satisfaction. In addition, those restaurants with an error-free service and a highly appreciated wine list among diners are more likely to achieve the culinary excellence that deserves a 5-star rating on TripAdvisor.

The attributes of the restaurant experience are frequently identified in literature reviews. Research based on text-mining analyses of customer reviews to discover a posteriori the factors that define a restaurant experience is scarce, and particularly difficult to find in the context of Michelin-starred restaurants.

This study aims to develop a model based on the financial variables for better accuracy of financial distress prediction on the sample of private French, Spanish and Italian firms. Thus, firms in financial difficulties could timely request for troubled debt restructuring (TDR) to continue business.

This study used a sample of 312 distressed and 312 non-distressed firms. It includes 60 French, 21 Spanish and 231 Italian firms in both distressed and non-distressed groups. The data are extracted from the ORBIS database. First, the authors develop a new model by replacing a ratio in the original Z”-Score model specifically for financial distress prediction and estimate its coefficients based on linear discriminant analysis (LDA). Second, using the modified Z”-Score model, the authors develop a firm TDR probability index for distressed and non-distressed firms based on the logistic regression model.

The new model (modified Z”-Score), specifically for financial distress prediction, represents higher prediction accuracy. Moreover, the firm TDR probability index accurately depicts the probabilities trend for both groups of distressed and non-distressed firms.

The findings of this study are conclusive. However, the sample size is small. Therefore, further studies could extend the application of the prediction model developed in this study to all the EU countries.

This study has important practical implications. This study responds to the EU directive call by developing the financial distress prediction model to allow debtors to do timely debt restructuring and thus continue their businesses. Therefore, this study could be useful for practitioners and firm stakeholders, such as banks and other creditors, and investors.

This study significantly contributes to the literature in several ways. First, this study develops a model for predicting financial distress based on the argument that corporate bankruptcy and financial distress are distinct events. However, the original Z”-Score model is intended for failure prediction. Moreover, the recent literature suggests modifying and extending the prediction models. Second, the new model is tested using a sample of firms from three countries that share similarities in their TDR laws.

The paper aims to analyze the coverage of health insurance and its correlates in the north-eastern region of India.

The study accessed the raw data of the National Family Health Survey (NFHS-4) (2015–16), which was an extensive, multiround survey conducted in a representative sample of households throughout India, which included socioeconomic, demographic and information on coverage of health insurance of any member of the household. The multivariate analysis of logistic regression was adopted to find the correlates of health insurance for all the eight (8) north-eastern states of India.

The results observed that among the north-eastern states, the coverage of health insurance was highest in Arunachal Pradesh (59%) followed by Tripura (58%), Mizoram (47%) surpassing the all India level of 27%, whereas the lowest was in Manipur (4%) followed by Nagaland (6%) and Assam (10%). The multivariate analysis of logistic regression found that the socioeconomic and demographic factors, households with a bank account and below poverty line (BPL) cardholders played a significant role in the coverage of health insurance in the north-eastern states of India.

The study focuses only on the coverage and correlates of health insurance. Further evaluation studies on each scheme of the social health insurance are needed for proper assessment of the health insurance schemes in the region.

There has been evidence around the world (South Korea, Taiwan and Thailand) that health insurance could be a protective shield from the entrapment into poverty due to high health expenditure. The NFHS-4 put up the finding that in the north-eastern part of India, the coverage of health insurance had been low. This implied that the region could fall into poverty due to high medical expenses on health. Taking account of multiple health insurance providers, risk pooling and consolidation of health insurance providers have become the need of the hour.

The study is different from other studies of health insurance since it covered all the eight (8) north-eastern states of India, which are ethnically, culturally and historically distinct from the rest of India in general and within the region and states in particular and examines the impact of each of the independent variables with the dependent variables. The study has shown that the variation in health insurance coverage associated with socioeconomic and other household-level demographic attributes (although not very strong).

This paper aims to investigate infant sensory patterns and their associations with previous perinatal loss, maternal-foetal attachment and postnatal maternal sensory patterns.

In a prospective cohort study, women with and without perinatal loss (N = 57) were recruited from an Australian public hospital. Participants were surveyed during pregnancy (maternal-foetal attachment, loss) and again postnatally (maternal/infant sensory patterns). Chi-square tests and logistic regression analyses controlling for previous perinatal loss were conducted with infant sensory patterns as outcome variables.

“More than typical” infant low registration was associated with poorer quality of maternal-foetal attachment. “More than typical” infant sensory seeking was associated with previous perinatal loss and higher levels of maternal sensory seeking. “More than typical” infant sensory sensitivity was linked with previous perinatal loss, poorer quality of maternal-foetal attachment and higher maternal low registration. “More than typical” infant sensory avoidance was associated with poorer quality of maternal-foetal attachment and higher levels of maternal sensory sensitivity.

To support more typical infant sensory patterns, results point to the potential benefit of occupational therapists supporting pregnant women with previous perinatal loss; facilitating favourable maternal-foetal attachment; and educating new mothers on how their sensory patterns impact on interactions with their infant. Sensory modulation strategies that consider the sensory patterns of both mother and infant may be beneficial to promote engagement in co-occupations.

These findings are the first to suggest that previous perinatal loss, poorer quality of maternal-foetal attachment and higher levels of maternal postnatal sensory patterns represent risk factors for infant sensory patterns that are “more than typical.”