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Purpose – The goal of this chapter was to empirically describe the patterns and dimensions of community interaction of typically underserved families of children with autism and other developmental disabilities within a family quality of life (FQoL) context.

Methodology – We utilized the theoretical framework of FQoL to examine the community interactions of 149 families who voluntarily participated in this study. The Family Quality of Life Survey (FQoLS-2006) was used to collect data from the primary caregivers of the children with the disability, 92% of which were mothers. We conducted an in-depth examination of the six dimensions (importance, opportunities, initiative, attainment, stability, and satisfaction) of community interaction.

Findings – Most families viewed community interaction as very important to their FQoL and the majority (62%) were satisfied with their community interaction, although just over a third reported high attainment, and only 48% reported having adequate opportunities for community interaction. Families of children with autism reported lower attainment of community interaction when compared to families of children with other developmental disabilities (t=2.63, df=147, p=0.01). Some race-related and child-related differences were also observed in the initiative taken to pursue community interaction and discrimination experienced by families.

Limitations – Results must be interpreted with caution, as the participants in this study were all volunteers and the majority were mothers, and therefore may not be representative of all families of children with disabilities. Despite the limitations, findings from this study are a first step in understanding the multidimensional nature of community interaction of low-income, minority families.

The purpose of this study is to provide further evidence on the importance of international diversification, and to determine the optimal allocation of assets in a portfolio comprising domestic (Australian) and international assets. The study focuses on stock index futures contracts in five countries ‐ Australia, USA, UK, Hong Kong and Japan. Daily data for the five selected contracts over the period from 1 January 1990 to 31 December 2000 is employed in the study. Consistent with previous studies, the results confirm the importance of international diversification and indicate that the portfolio risk is reduced considerably when more international assets are added sequentially to the portfolio. Empirical analysis also shows that the optimal asset allocation results in higher risk reduction and better returns when compared with an equally weighted portfolio.

The Chief Financial Officers Act and subsequent legislation require federal agencies to produce corporate-style financial statements. Arguments for financial statements drew on private sector analogies and suggested policy makers and managers would use the information to make better public policy and management decisions and improve accountability for financial management and program performance. Nearly all major government agencies have unqualified audit opinions and improvements in financial management are claimed. But benefits for policy making and management are not yet well understood. This paper examines the question by comparison with the private sector and by examining what agencies say about the uses and users of financial statement information. The emerging challenge in the evolution of federal financial reporting is to develop better government-specific analytical tools and other financial information for policy makers and managers.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

The purpose of this paper is to review the literature on Central Bank Digital Currencies (CBDCs) in light of the increasing demand for digital payments globally. It aims to assess the global research landscape, methodologies and data utilized in CBDC studies as their popularity grows.

The paper employs a systematic literature review (SLR) framework, utilizing the Scopus database to identify 323 studies related to Central Bank Digital Currency or CBDC. Through a thorough manual screening process, 169 studies were selected for inclusion. The research employs R, Biblioshiny and Excel for data evaluation, classifying the studies into three methodological categories: quantitative, qualitative and mixed approaches. This classification allows for a detailed assessment of the research techniques and data used in the literature on CBDCs.

The findings include a diverse range of research methodologies and data employed in CBDCs literature, highlighting the growing interest and depth of academic investigation into this area. By categorizing papers according to research technique, the study provides a comprehensive evaluation of the academic landscape regarding CBDC research. It offers valuable insights for researchers, policymakers and stakeholders, contributing to an enhanced understanding of the complexities and opportunities presented by the development and implementation of CBDCs.

This study’s originality lies in its rigorous and transparent methodology for data from CBDC studies, offering a solid framework for future research. By evaluating global research growth within an SLR framework and categorizing studies by research technique, it contributes uniquely to the academic discourse on digital currencies. The paper provides a critical resource for researchers, lawmakers and stakeholders, enriching the knowledge base on CBDCs and supporting informed decision-making in the context of digital financial innovation.

The purpose of this paper is to introduce a hybrid framework (suppliers, inputs, process, output and customers+define, measure, analyze, improve and control (SIPOC+DMAIC)) aimed at improving supply chain management (SCM) process dimensions in a supply chain (SC) network.

Based upon the critical review of literature, process dimensions (average outgoing quality limit (AOQL), average outgoing quality (AOQ), process Z, defect per million opportunity) critical to SCM performance were identified. A framework consisting of three phases, i.e., design, implementation and results has been conceptualized and a case from paint industry is investigated. Implementation framework makes use of SIPOC model and Six Sigma DMAIC methodology. The goals of the study were achieved by using Six Sigma tools such as brainstorming sessions; root cause analysis, histograms, statistical tools such as control charts and process capability analysis.

Authors made an attempt to propose a conceptual framework for improving process dimensions in a SC network. It is observed from the results that selection of appropriate strategies for improving process performance based upon experiences, and use of statistical tools by cross-functional teams with an effective coordination, guarantees success. Metrics such as AOQL shows the maximum worst possible defective or defect rate for the AOQ. Process Z helps to know about sigma capability of the process.

The framework so developed is tested in a single company manufacturing batches of paint. The study has important implications for the industry since it tries to integrate SCM process dimensions which would help in successful implementation of SCM practices in firm by following the DMAIC process. The framework enables the practitioners to investigate the process and demonstrate improvements using DMAIC which makes use of statistical tools.

Although process dimensions related to SCM are critical to organization competitiveness, research so far has tended to focus on supply chain operations and reference model, balanced scorecard, total quality management, activity-based costing, just in time, etc., but in literature hardly any description of the SIPOC-DMAIC model to improve SCM process performance is provided. The use of statistics in DMAIC provides better insight into the process performance, and process control.

The paper aims to incorporate the relationship of reverse logistics into the economic, environmental, and social sustainability, known as triple bottom line and developed a framework for reverse logistics performance evaluation.

The performance measures, based on triple bottom line approach, were selected, and fuzzy analytical hierarchy process and extent analysis approach was applied for estimating the weights, global weights of performance measures and hence, the reverse logistics performance index. Reverse logistics performance of three electronic companies were evaluated and compared for the demonstration of the methodology.

The results show that economic performance has highest performance index followed by environmental performance and social performance. “Recapturing value” and “return on investment” from economic, “minimum energy consumption” and “optimum use of raw material” from environmental and “community complaints” and “customer health and safety” from social perspective have higher performance indexes. Over all, “reduced packaging”, “use of recycled material” and “employee benefits” show very poor performance indexes.

The study will provide useful guidance to the academicians and practitioners for evaluating, improving and benchmarking the reverse logistics performance.

The analysis adds to the very few studies on triple bottom line aspects of reverse logistics and its performance evaluation. Also, fuzzy analytical hierarchy process and extent analysis is used first time being an efficient tool to tackle the fuzziness of the data involved in performance evaluation.

This study aims to examine the current state of literature on structural equation modeling (SEM) studies in “cloud computing” domain with respect to study domains of research studies, theories and frameworks they use and SEM models they design.

Systematic literature review (SLR) protocol is followed. In total, 96 cloud computing studies from 2009 to June 2018 that used SEM obtained from four databases are selected, and relevant data are extracted to answer the research questions.

A trend of increasing SEM usage over years in cloud studies is observed, where technology adoption studies are found to be more common than the use studies. Articles appear under four main domains, namely, business, personal use, education and health care. Technology acceptance model (TAM) is found to be the most commonly used theory. Adoption, intention to use and actual usage are the most common selections for dependent variables in SEM models, whereas security and privacy concerns, costs, ease of use, risks and usefulness are the most common selections for causal factors.

Previous cloud computing SLR studies did not focus on statistical analysis method used in primary studies. This review will display the current state of SEM studies in cloud domain for all future academics and practical professionals.