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The farm sector is crucial for rural poverty alleviation, alongside the non-farm sector, which contributes to mitigating risks associated with crop failures. This paper investigates the effects of public policies on productive employment within both the farm and non-farm sectors in sub-Saharan Africa.

A meta-analysis is conducted exclusively on the results of the Partnership for Economic Policy (PEP)-funded studies under the Policy Analysis on Growth and Employment (PAGE II) initiative. Selected studies focused on the impact of public policies on productive employment in rural farm and non-farm sectors, encompassing a total of nine sub-Saharan Africa countries in: Benin, Burkina Faso, Cote d'Ivoire, Democratic Republic of Congo, Ghana, Lesotho, Nigeria, Senegal and South Africa.

The results indicate that public investments in rural areas and public policies that facilitate access to productive resources are likely to enhance productive employment. The overall effect size is positive and significant, ranging from 2% to 10% increases in productive employment. Sources of variation include the sector of activity and the policy instrument. In addition, the policy effects are gender-sensitive and seem more consistent in the non-farm sector.

Although the selected working papers addressed several aspects of productive employment, other aspects warrant further investigation. Policies involving restrictions or regulations have received little attention in the impact analysis. Researches to fill this gap would be important. Another suggestion for further research is the analysis of the relative importance of non-farm employment in rural areas in developing countries. It is always assumed that rural households depend heavily on agriculture for their subsistence.

The contribution of the paper lies in the comparative analysis of numerous public policies implemented in nine distinct countries. By consolidating data from fourteen 14 different experiences into a single study, the paper offers valuable insights on factors that determine policy effectiveness and contribute to understanding what worked for whom and why.

The purpose of this paper is to develop optimal estimation procedures for the stress-strength reliability (SSR) parameter R = P(X > Y) of an inverse Pareto distribution (IPD).

We estimate the SSR parameter R = P(X > Y) of the IPD under the minimum risk and bounded risk point estimation problems, where X and Y are strength and stress variables, respectively. The total loss function considered is a combination of estimation error (squared error) and cost, utilizing which we minimize the associated risk in order to estimate the reliability parameter. As no fixed-sample technique can be used to solve the proposed point estimation problems, we propose some “cost and time efficient” adaptive sampling techniques (two-stage and purely sequential sampling methods) to tackle them.

We state important results based on the proposed sampling methodologies. These include estimations of the expected sample size, standard deviation (SD) and mean square error (MSE) of the terminal estimator of reliability parameters. The theoretical values of reliability parameters and the associated sample size and risk functions are well supported by exhaustive simulation analyses. The applicability of our suggested methodology is further corroborated by a real dataset based on insurance claims.

This study will be useful for scenarios where various logistical concerns are involved in the reliability analysis. The methodologies proposed in this study can reduce the number of sampling operations substantially and save time and cost to a great extent.

The study investigates the influence of perceived security (PS) on behavioral intention (BI) via the trust attitude process and explores the moderating effects of gender. PS in mobile wallets enhances user trust (TR), attitude (ATT) and intention (INT). Using a multiple and serial mediation model, both TR and ATT were found to mediate the relationship between PS and BI.

Drawing on the stimulus-organism-response (S-O-R) theory, the proposed conceptual model comprises PS, TR, ATT and BI. An online survey was conducted with a cross-sectional sample of 744 mobile wallet users in India. Partial least squares structural equation modeling (PLS-SEM) was used to analyze the hypothesized relationships and test the mediation effects.

Results show that the stimulus, PS, has a positive and significant influence on TR and ATT, which eventually has a positive influence on BI. The research model explains 64.4 percent of the variance in BI. Further, both TR and ATT independently and parallelly mediate the relationship PS and BI. Lastly, gender is found to moderate the relationship between TR and BI and ATT and BI.

The research showed the importance of PS, TR and ATT towards mobile wallet adoption INTs. Further, the findings support the idea that developing TR and ATT is essential for shaping INTs. This suggests that mobile wallet service providers should invest in methods that not just enhance user TR but also reinforce a positive ATT towards the platform. To demonstrate TR, mobile wallet providers must ensure the confidentiality and privacy of user data, keep customer interests in mind and fulfill commitments. Lastly, for strengthening customer TR, excellent customer support is extremely important.

While prior researchers have majorly used technology acceptance model (TAM) and unified theory of acceptance and use of technology (UTAUT) models to explain adoption INTs, this study examines the relationship between PS, TR, ATT and BI through the lens of the SOR framework.

The purpose of this study is to investigate the entropy generation in different nanofluids flow over a vertically moving rotating disk. Unlike the classical Karman flow, water-based nanofluids have various suspended nanoparticles, namely, Cu, Ag, Al₂O₃ and TiO₂, and the disk is also moving vertically with time-dependent velocity.

The Keller box technique numerically solves the governing equations after reduction by suitable similarity transformations. The shear stress and heat transport features, along with flow and temperature fields, are numerically computed for different concentrations of the nanoparticles.

This study is done comparatively in between different nanofluids and for the cases of vertical movement of the disk. It is found that heat transfer characteristics rely not only on considered nanofluid but also on disk movement. Moreover, the upward movement of the disk diminishes the heat-transfer characteristics of the fluid for considered nanoparticles. In addition, for the same group of nanoparticles, an entropy generation study is also performed, and an increasing trend is found for all nanoparticles, with alumina nanoparticles dominating the others.

This research is a novel work on a vertically moving rotating surface for the water-conveying nanoparticle fluid flow with entropy generation analysis. The results were found to be in good agreement in the case of pure fluid.

This study aims to analyze the long-run dynamic relationship between financial inclusion and economic growth for developing nations.

This study develops a comprehensive financial inclusion index based on the UNDP methodology for 53 developing nations. The authors use second-generation unit root tests, cointegration techniques and an advanced dynamic common correlated effects estimator model called cross-sectional augmented autoregressive distributed lags (CS-ARDL) to examine long-run dynamics among variables.

The tests confirm the presence of slope-heterogeneity and cross-sectional dependency. The second-generation panel unit root tests show the chosen variables are stationary at first difference. The bootstrap Westerlund cointegration result shows the variables are cointegrated in the long run. The CS-ARDL estimates conclude that financial inclusion positively enhances gross domestic product per capita in selected developing countries. The robustness check through augmented mean group estimation validates the findings.

The study makes three important contributions: first, it constructs a comprehensive financial inclusion index using 10 variables for a panel of 53 developing nations; second, the potential cross-section dependence and slope heterogeneity of panel data have been accounted for by applying the second-generation unit root tests; third, the study uses the dynamic common correlated effects estimator model (CS-ARDL) to examine long-run dynamics among variables.

The research aims to develop an assessment framework that evaluates critical success factors (CSFs) for the Quality 4.0 (Q 4.0) transition among Indian firms.

The authors use the fuzzy-Delphi method to validate the results of a systematic literature review (SLR) that explores critical aspects. Further, the fuzzy decision-making trial and laboratory (DEMATEL) method determines the cause-and-effect link. The findings indicate that developing a Q 4.0 framework is essential for the long-term success of manufacturing companies. Utilizing the power of digital technology, data analytics and automation, manufacturing companies can benefit from the Q 4.0 framework. Product quality, operational effectiveness and overall business performance may all be enhanced by implementing the Q 4.0 transition framework.

The study highlights significant awareness of Q 4.0 in the Indian manufacturing sector that is acquired through various means such as training, experience, learning and research. However, most manufacturing industries in India still follow older quality paradigms. On the other hand, Indian manufacturing industries seem well-equipped to adopt Q 4.0, given practitioners' firm grasp of its concepts and anticipated benefits, including improved customer satisfaction, product refinement, continuous process enhancement, waste reduction and informed decision-making. Adoption hurdles involve challenges including reliable electricity access, high-speed Internet, infrastructure, a skilled workforce and financial support. The study also introduces a transition framework facilitating the shift from conventional methods to Q 4.0, aligned with the principles of the Fourth Industrial Revolution (IR).

This research exclusively examines the manufacturing sector, neglecting other fields such as medical, service, mining and construction. Additionally, there needs to be more emphasis on the Q 4.0 implementation frameworks within the scope of the study.

This may be the inaugural framework for transitioning to Q 4.0 in India's manufacturing sectors and, conceivably, other developing nations.

This paper examines India's socio-economic attributes and different financial dimensions of financial inclusion (FI).

The paper uses a principal component analysis (PCA) to build indexes related to financial dimensions. It applies the logistics regression model and the Fairlie decomposition method to determine India's socio-economic and financial characteristics of FI.

Based on the logistic regression, socio-economic factors like age, gender, marital status, level of education and religion have an impact on FI. The use of financial institutions has positively contributed to the probability of FI, while the low proximity of financial service providers retards the process of FI. Fairlie decomposition concludes regional disparity and gender disparity in FI; however, the rural–urban gap in FI is not captured by the variables included in the study. The main reasons for the discrepancy are lack of education, financial literacy, the proximity of financial service providers and lack of financial institutions.

This paper makes two important contributions: first, it presents a micro-level analysis of FI across the socio-demographic strata of India, and second, it demonstrates the regional, rural–urban and gender disparity in FI in India.

The purpose of this paper is to implement a closed loop regulated bidirectional DC to DC converter for an application in the electric power system of more electric aircraft. To provide a consistent power supply to all of the electronic loads in an aircraft at the desired voltage level, good efficiency and desired transient and steady-state response, a smart and affordable DC to DC converter architecture in closed loop mode is being designed and implemented.

The aircraft electric power system (EPS) uses a bidirectional half-bridge DC to DC converter to facilitate the electric power flow from the primary power source – an AC generator installed on the aircraft engine’s shaft – to the load as well as from the secondary power source – a lithium ion battery – to the load. Rechargeable lithium ion batteries are used because they allow the primary power source to continue recharging them whenever the aircraft engine is running smoothly and because, in the event that the aircraft engine becomes overloaded during takeoff or turbulence, the charged secondary power source can step in and supply the load.

A novel nonsingular terminal sliding mode voltage controller based on exponential reaching law is used to keep the load voltage constant under any of the aforementioned circumstances, and its performance is contrasted with a tuned PI controller on the basis of their respective transient and steady-state responses. The former gives a faster and better transient and steady-state response as compared to the latter.

This research gives a novel control scheme for incorporating an auxiliary power source, i.e. rechargeable battery, in more electric aircraft EPS. The battery is so implemented that it can get regeneratively charged when primary power supply is capable of handling an additional load, i.e. the battery. The charging and discharging of the battery is carried out in closed loop mode to ensure constant battery terminal voltage, constant battery current and constant load voltage as per the requirement. A novel sliding mode controller is used to improve transient and steady-state response of the system.