A new S2 control chart using repetitive sampling

A new S² control chart is presented for monitoring the process variance by utilizing a repetitive sampling scheme. The double control limits called inner and outer control limits are proposed, whose coefficients are determined by considering the average run length (ARL) and the average sample number when the process is in control. The proposed control chart is compared with the existing Shewhart S² control chart in terms of the ARLs. The result shows that the proposed control chart is more efficient than the existing control chart in detecting the process shift.     

Consequences of Domestic Violence against Women: Some Reflections from Rural Bangladesh

The aim of this study was to explore the consequences of domestic violence against rural Bangladeshi women. Drawing on in‐depth qualitative phenomenological interviews with 39 female victims of domestic violence from 8 rural settings of the Netrokona and Mymensingh districts, it was found that domestic violence not only causes serious consequences to the overall health and wellbeing of victims, it also causes negative impacts to their children and family members. For victims, consequences were physical, sexual, reproductive, psychological, and economic. For the children of the victims, consequences were mostly behavioral and psychological, while for family members of the victims, consequences were mainly economic and psychological. This study has significant academic implications because it could trace the consequences of domestic violence in a three dimensional manner. Based on empirical findings, this study proposes policy recommendations, such as campaigning against domestic violence and the proper implementation of laws related to domestic violence.     

The impact of globalization on social work in the UK

Since the late 1980s social work in the UK has undergone a period of unremitting change affecting its organizational structure, value-base, and service users. There has been a regrettable narrowness of scope in the social work literature on such changes, as analysis has been limited to policy and service delivery issues, which treat such changes as if they were simply new technical responses to the problems of reorganizing social services. We argue that such analyses do not engage sufficiently with the complex dynamics driving these changes and that there is a need to contextualize change in social work against the wider political and economic context. The transformative nature of the contemporary period is posited with reference to the impact of global macro-level forces and the ways that these interact with national and political variables on micro-level forms of social work practice. This paper reviews selective literature on globalization and draws linkages with changes in social services at the agency and practitioner level in the UK.     

A Study of the Relationship Between Innovation and Performance Among NPOs in Pakistan

Abstract

Innovation has become a core driver for the success and survival of organizations regardless of their size and nature. A plethora of literature has discussed the importance of innovation in profit-based organizations, while nonprofit organizations (NPOs) have generally been ignored in research. This study examines the influence of the sub-dimensions of innovation on the performance of NPOs. Data were collected through structured questionnaires using a sample size of 309 NPOs operating in the emerging market Pakistan. The hypotheses were tested through structural equation modeling (SEM) in AMOS.21. The results indicate that process innovation and organization innovation have significant positive influence on the performance of NPOs, while product innovation and marketing innovation have insignificant influence on the performance of NPOs. NPOs are advised to give enough attention to process and organization innovation in order to boost their performance. Future researchers are encouraged to test the model in other environmental settings. Implications for practice were discussed.     

Characterization of probability distributions through higher order gap

Weibull, Burr, Pareto and power function distributions have been characterized through the conditional moments of order statistics with higher gap and some of its important deductions are discussed.     

A Flexible Hierarchical Bayesian Modeling Technique for Risk Analysis of Major Accidents

Safety analysis of rare events with potentially catastrophic consequences is challenged by data scarcity and uncertainty. Traditional causation‐based approaches, such as fault tree and event tree (used to model rare event), suffer from a number of weaknesses. These include the static structure of the event causation, lack of event occurrence data, and need for reliable prior information. In this study, a new hierarchical Bayesian modeling based technique is proposed to overcome these drawbacks. The proposed technique can be used as a flexible technique for risk analysis of major accidents. It enables both forward and backward analysis in quantitative reasoning and the treatment of interdependence among the model parameters. Source‐to‐source variability in data sources is also taken into account through a robust probabilistic safety analysis. The applicability of the proposed technique has been demonstrated through a case study in marine and offshore industry.     

Theoretical Beacons: Maturana's Theory in Clinical Practice

This paper introduces several theoretical constructs drawn from the work of Humberto Maturana that can be applied to a diverse range of clinical contexts, including supervision. These constructs are: love as a fundamental need of human beings; pathways of explanation: (Objectivity), Objectivity; Emotioning; Structural Coupling; Plasticity; Domains of Operational Coherences. These constructs assist in choosing a point of entry for specific clinical situations and form a foundation on which one's preferred model of practice can be built.     

Domino Effect Analysis Using Bayesian Networks

A new methodology is introduced based on Bayesian network both to model domino effect propagation patterns and to estimate the domino effect probability at different levels. The flexible structure and the unique modeling techniques offered by Bayesian network make it possible to analyze domino effects through a probabilistic framework, considering synergistic effects, noisy probabilities, and common cause failures. Further, the uncertainties and the complex interactions among the domino effect components are captured using Bayesian network. The probabilities of events are updated in the light of new information, and the most probable path of the domino effect is determined on the basis of the new data gathered. This study shows how probability updating helps to update the domino effect model either qualitatively or quantitatively. The methodology is applied to a hypothetical example and also to an earlier‐studied case study. These examples accentuate the effectiveness of Bayesian network in modeling domino effects in processing facility.