Search results

The study based on the estimation of the stress–strength reliability parameter plays a vital role in showing system efficiency. In this paper, considering independent strength and stress random variables distributed as inverted exponentiated Rayleigh model, the author have developed estimation procedures for the stress–strength reliability parameter R = P(X>Y) under Type II hybrid censored samples.

The maximum likelihood and Bayesian estimates of R based on Type II hybrid censored samples are evaluated. Because there is no closed form for the Bayes estimate, the author use the Metropolis–Hastings algorithm to obtain approximate Bayes estimate of the reliability parameter. Furthermore, the author construct the asymptotic confidence interval, bootstrap confidence interval and highest posterior density (HPD) credible interval for R. The Monte Carlo simulation study has been conducted to compare the performance of various proposed point and interval estimators. Finally, the validity of the stress–strength reliability model is demonstrated via a practical case.

The performance of various point and interval estimators is compared via the simulation study. Among all proposed estimators, Bayes estimators using MHG algorithm show minimum MSE for all considered censoring schemes. Furthermore, the real data analysis indicates that the splashing diameter decreases with the increase of MPa under different hybrid censored samples.

The frequentist and Bayesian methods are developed to estimate the associated parameters of the reliability model under the hybrid censored inverted exponentiated Rayleigh distribution. The application of the proposed stress–strength reliability model will help the reliability engineers and also other scientists to estimate the system reliability.

Grounded on resource dependence theory, the authors explored how power and dependence affect sustainability adoption in an artisanal fishing supply chain (AFSC) in Mexico.

An in-depth longitudinal case study was conducted to identify relationships among fishers, a cooperative and intermediaries using a content analysis of data gathered from a combination of interviews, focus groups, observations, participatory workshops and secondary data.

As a result of the existing power imbalance among AFSC members, mediated forces (e.g. rewards for intermediary–fishers relationship) were the most prominent observed. In addition, a close and high dependence on resources affecting supply chain sustainability (SCS) adoption was identified. For example, within intermediary–cooperative relationships, a power imbalance caused mostly by financial resource dependence generated a negative impact on economic sustainability related to unfair prices and unfair trade. The results, thus, showed the detrimental influence of intermediaries among AFSC members on SCS adoption.

A greater understanding of power imbalance and dependence can help AFSC members to identify their weaknesses and develop actions to adopt sustainability.

Unlike previous research, the authors go beyond the often positive research focus of SCS studies and provide, through the resource dependence theory, a longitudinal view on how power imbalance negatively affects SCS adoption.

Livelihood preference for children is anchored in the aspiration of parents for a better life for them with due consideration of their capacities given available resources and opportunities from inside and outside the community. Given the data from an earlier survey I conducted, this chapter examines the fisheries management issues as contexts and the time factors that may have influenced the livelihood preference for children of parents, primarily fathers. Twenty-five percent of parents or 30 out of the 120 non-probability samples of municipal fishing families surveyed in South Negros in the Philippines preferred fishing for their children. For a comparative analysis, 30 parents were also randomly drawn from the remaining samples who preferred other livelihoods for their children away from fishing. As a male-dominated industry, evident in the fishing history of families, the tradition may have already declined among most parents as non-fishing livelihoods were perceived to offer family resilience to ecological and socioeconomic changes. The projected decrease in new families engaged in fishing would also mean a pressure reduction on municipal fisheries; thus, opportunities for non-fishing livelihoods must be accessible through full scholarships for college or technical-vocational education. Meanwhile, basic education sciences should infuse lessons in responsible or right fishing practices to expose children to sustainable fisheries at a young age if they pursue fishing livelihoods when they become adults.

This study conducts a meta-analysis to investigate the impact of board diversity, independence and size on carbon emission disclosure.

The results of 22 empirical investigations on the association between board qualities and carbon emission disclosure are synthesised using a meta-analysis approach. Inclusion and exclusion criteria are established, and search strategies are devised to locate relevant material. Data extraction entails gathering important information such as the names of the authors, variables and correlation coefficients. Fisher's z-transformation is used to compute and synthesise effect sizes and assumptions, sensitivity testing and subgroup analysis are performed to assess the robustness of the findings.

A substantial association was discovered between board characteristics and carbon emission disclosure. Board independence and gender diversity revealed small to medium-strength positive relationships, whilst board size had a medium-strength positive correlation. The study periods varied from 2011 to 2022, with 2018 having the most studies. However, highly heterogeneous groups were discovered; further subgroup analyses were then carried out to sort out this issue.

Several limitations were recognised due to the limited number of studies and heterogeneity, although subgroup analysis was used to reduce the influence of heterogeneity. To investigate alternate outcomes, more analysis of the heterogeneity level and potential modifications to the model assumptions may be required.

Companies should consider board size, independence and gender diversity when formulating long-term competitive strategies in the climate change movement. These characteristics can aid in bridging information gaps and garnering stakeholder support for carbon-reduction initiatives.

This meta-analysis addresses a gap in the literature by addressing prior studies' conflicting and inconsistent findings on the association between board characteristics and carbon emission disclosure. It employs a rigorous approach and synthesis strategy to provide a thorough and robust understanding of the crucial role of board characteristics in carbon emission disclosure.

A progressive hybrid censoring scheme (PHCS) becomes impractical for ensuring dependable outcomes when there is a low likelihood of encountering a small number of failures prior to the predetermined terminal time T. The generalized progressive hybrid censoring scheme (GPHCS) efficiently addresses to overcome the limitation of the PHCS.

In this article, estimation of model parameter, survival and hazard rate of the Unit-Lindley distribution (ULD), when sample comes from the GPHCS, have been taken into account. The maximum likelihood estimator has been derived using Newton–Raphson iterative procedures. Approximate confidence intervals of the model parameter and their arbitrary functions are established by the Fisher information matrix. Bayesian estimation procedures have been derived using Metropolis–Hastings algorithm under squared error loss function. Convergence of Markov chain Monte Carlo (MCMC) samples has been examined. Various optimality criteria have been considered. An extensive Monte Carlo simulation analysis has been shown to compare and validating of the proposed estimation techniques.

The Bayesian MCMC approach to estimate the model parameters and reliability characteristics of the generalized progressive hybrid censored data of ULD is recommended. The authors anticipate that health data analysts and reliability professionals will get benefit from the findings and approaches presented in this study.

The ULD has a broad range of practical utility, making it a problem to estimate the model parameters as well as reliability characteristics and the significance of the GPHCS also encourage the authors to consider the present estimation problem because it has not previously been discussed in the literature.