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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.

In this study, a novel framework was proposed to assess the trust in e-government (e-Gov) services under an uncertain environment. The proposed framework was applied in Iranian municipality websites of e-Gov services to evaluate the readiness score of trust in e-Gov services.

A unique hybrid research methodology was proposed. In the first phase, a comprehensive set of indices were determined from an extensive literature review and finalized by employing the fuzzy Delphi method. In the second phase, interval-valued intuitionistic fuzzy set (IVIFS) -was utilized to model the problem's uncertainty with analytic called IVIFS- hierarchy process (AHP) to determine the importance of indices and indicators by assigning the weights. In the third phase, the fuzzy evaluation method (FEM) is followed for assessing the readiness score of indices in case studies.

The findings indicated that “Trust in government” is the most significant index affecting citizen's trust in e-Gov services while “Maintenance and support” has the least impact on user's intention to use e–Gov services.

The study contributes by introducing a unique research methodology that integrates three phases, including fuzzy Delphi, IVIFS AHP and fuzzy evaluation method. Moreover, the fuzzy sets theory helps to reach a more accurate result by modeling the inherent ambiguity of indicators and indices. Interval-valued intuitionistic fuzzy models the ambiguity of experts' judgments in an interval.

The study helps policy makers to monitor wider aspects of trust in e-Gov services as well as understanding their importance. The study enables policy makers to apply the framework to any potential case studies to evaluate the readiness score of indices and recognizing strengths and weakness of trust dimensions as well as recommending advice for improving the situation.

The study is one of the few to indicate significant indices of trust in e-Gov services in developing countries. The study shows the importance of indicators and indices by assigning a weight. Additionally, the framework can assess the readiness score of various case studies.

The purpose of this study is to investigate whether repeated alliances between two members of a patent pool boost enterprise innovation. Furthermore, this paper intends to determine whether the innovation performance becomes higher or lower based on the partnership characteristics.

In this empirical study, hierarchical regression is used to analyze the longitudinal data obtained from 12 patent pools managed by MPEG LA during a time period ranging from 2006 to 2018. The members of patent pools comprise research institutions, firms and universities. Research analyses are performed based on a sample of 68,400 member pairs who had established repeated alliances. The information regarding such pairs is gathered from public databases.

Repeated alliances positively correlate with enterprise innovation performance in patent pools; this performance is higher when the two enterprises have exploratory collaborations. Conversely, the performance is lower when the partners have a similar technology base and are engaged in a technological competition (competitive learning and patent litigation). Moreover, the performance is lower when one partner demonstrates higher network centrality and richer structural holes than the other partner.

Patent pools play an instrumental role in eliminating patent-licensing barriers, thereby allowing mutual acquisition of complementary technologies, and cooperatively strengthening technology development. From the perspective of theories of coopetition, knowledge management and social network, this study explores the impact of patent pools on enterprise innovation performance and ascertains the moderating roles of technology coopetition, technology similarity and network position, thereby expanding the scope of innovation effect in the context of patent pools.