Estimation and prediction for a Burr type-III distribution with progressive censoring

We consider estimation of unknown parameters and reliability characteristics of a Burr type-III distribution under progressive censoring. Predictive estimates for censored observations and the associated prediction intervals are also obtained. We derive maximum-likelihood estimators of unknown quantities using the EM algorithm and then also obtain the observed Fisher information matrix. We provide various Bayes estimators for unknown parameters under the squared error loss function. Highest posterior density and asymptotic intervals are also constructed. We evaluate performance of proposed methods using simulations. Finally, an illustrative example is presented in support of the methods discussed.     

On progressively censored inverted exponentiated Rayleigh distribution

In this paper, we discuss a progressively censored inverted exponentiated Rayleigh distribution. Estimation of unknown parameters is considered under progressive censoring using maximum likelihood and Bayesian approaches. Bayes estimators of unknown parameters are derived with respect to different symmetric and asymmetric loss functions using gamma prior distributions. An importance sampling procedure is taken into consideration for deriving these estimates. Further highest posterior density intervals for unknown parameters are constructed and for comparison purposes bootstrap intervals are also obtained. Prediction of future observations is studied in one- and two-sample situations from classical and Bayesian viewpoint. We further establish optimum censoring schemes using Bayesian approach. Finally, we conduct a simulation study to compare the performance of proposed methods and analyse two real data sets for illustration purposes.     

An integrated lean and green approach for improving sustainability performance: a case study of a packaging manufacturing SME in the U.K.

Abstract

Competitive landscape, informed consumers and stringent regulations have forced many manufacturing small- and medium-sized enterprises (SMEs) to focus on operational efficiency along with sustainability issues in recent years. While many manufacturing organisations have been taking lean initiatives for the past few years for operational excellence, an impulsive rush to adopt lean without a strategic deployment vision has led to scattered implementation of lean tools and projects without desired success. Many researchers and practitioners prescribe value stream mapping as a foundation for lean transformation initiatives; however, little empirical work is available on the symbiosis of lean and green paradigms to reap maximum benefits. This research, through a systematic methodology and a novel tool called Green Integrated Value Stream Mapping (GIVSM), integrates both paradigms in a case study on a U.K. packaging-manufacturing SME. Applying the GIVSM demonstrates that simultaneous deployment of lean and green paradigms have synergistic effect for improving both operational efficiency and environmental performance. In addition, continuous improvement framework with sustainable procurement is proposed to overcome the lean-green misalignments. This study also provides a guiding reference for practitioners to undertake similar improvement projects and identifies opportunities to expand this academic research on integrated lean-green approach into other industry sectors.     

Estimating standard error of intra-class correlation coefficients up to three level unbalanced nested clinical trials

ABSTRACT

Very often researchers plan a balanced design for cluster randomization clinical trials in conducting medical research, but unavoidable circumstances lead to unbalanced data. By adopting three or more levels of nested designs, they usually ignore the higher level of nesting and consider only two levels, this situation leads to underestimation of variance at higher levels. While calculating the sample size for three-level nested designs, in order to achieve desired power, intra-class correlation coefficients (ICCs) at individual level as well as higher levels need to be considered and must be provided along with respective standard errors. In the present paper, the standard errors of analysis of variance (ANOVA) estimates of ICCs for three-level unbalanced nested design are derived. To conquer the strong appeal of distributional assumptions, balanced design, equality of variances between clusters and large sample, general expressions for standard errors of ICCs which can be deployed in unbalanced cluster randomization trials are postulated. The expressions are evaluated on real data as well as highly unbalanced simulated data.     

Alzheimer's in the Workplace: A Challenge for Social Work

It is estimated that 5.3 million Americans have Alzheimer's disease or a related disorder (ADRD) with approximately 500,000 of these persons younger than 65. Moreover, the number of people affected by the disease will increase 350% by the middle of this century. Although research exists on organizational policies with regard to caregivers, very little is known about how organizations deal with employees themselves who show symptoms of ADRD. This article reports on a pilot study of employers' responses to dementia as it impacts both caregiving employees and employees who themselves show signs of cognitive impairment.     

Knowledge management based collaboration moderator services to support SMEs in virtual organizations

Abstract

Collaboration Moderator Services (CMS) are discussed as a Knowledge management service for SMEs operating in a virtual organization (VO). In this research, a CMS supports the pre-creation stage of a VO by quickly identifying potential business opportunities and collaborative partners. Text mining techniques are used to analyze calls for tender documents based on the competencies and areas of interest stored in the shared information about companies in a collaboration pool. A case study of UK-based SMEs demonstrates the application of text mining as a knowledge discovery tool, supporting SMEs at the pre-creation stage of a VO. Results show that text mining can be used to (1) identify possible business opportunities for SMEs in the collaborative network (2) Indicate potential collaborations between pairs of SMEs using link analysis and (3) Raise awareness of business opportunities and possible SME partners for multi-enterprise collaborations using a dimensional matrix.     

Knowledge management for food supply chain synergies – a maturity level analysis of SME companies

Abstract

Despite the considerable number of papers addressing knowledge management (KM) aspects in supply chains, many research issues in the area are still neglected. One of the main research gaps in this field concerns the maturity level of KM practices adoption by small and medium enterprises (SMEs). This paper addresses this research gap by developing a framework to support the analysis of the maturity level of KM adoption in an SME context. The framework is applied in a multiple case study developed to investigate the extent to which SMEs operating in the food sector are deploying KM practices to support more sustainable initiatives. By relating KM maturity levels, perspectives and processes to sustainable practices concerning food waste and by-product synergies, the paper makes an original contribution to advance theory and practice in the area. The paper also points out potential barriers that companies face to implement sustainability-related KM practices.     

Motivation to volunteer among senior center participants

Senior centers in the United States play a vital role in the aging continuum of care as the focal points of a community-based system of services targeting independent older adults to promote their social integration and civically engagement. Although several studies have evaluated the diversity of senior center programs, demographic characteristics of participants, and benefits of participation, very few have explored motivations to volunteer among participants. Many senior centers rely on a cadre of participants who volunteer there to assist with programs and meal services. However, a systematic examination of volunteering interests and the rationale for volunteering among senior center participants has been missing from the literature. This mixed-methods study, conducted at a large suburban senior center, explores the interests and motivations of volunteerism among the participants. The study found that there was limited interest in volunteering among senior center participants. Those who were motivated to volunteer wanted to do so in order to stay connected with their community. There was strong interest in volunteering for single events or projects rather than a long-term commitment. Implications for senior centers are discussed.     

Big-data analytics framework for incorporating smallholders in sustainable palm oil production

Abstract

This paper aims to address the constraints faced in incorporating smallholders in sustainable palm oil production. There exists literature that acknowledges the need for incorporating smallholders in the production of sustainable palm oil but none has proposed a solution beyond ‘Roundtable on Sustainable Palm Oil’ (RSPO) certification. In the current business scenario, several organizations are struggling to procure RSPO certified palm oil even after committing huge resources. RSPO, though a good first step, has a major process and capacity constraints resulting in long processing times, delays, and lack of traceability for the customers. This paper proposes a Big Data Analytics framework enabled by cutting-edge technologies to incorporate smallholders in the RSPO certification process. The data used was collected through farm visits, stakeholder meetings, key stakeholder interviews, and, secondary sources. The proposed framework not only addresses the limitation of the current certification process but also converts it from being punitive to preventive. The outcomes of this research will be extremely useful for all the stakeholders in the palm oil supply chain.