Modelling the Demand for Long-term Care to Optimise Local Level Planning

Long-term care (LTC) includes the range of health, social and voluntary support services provided to those with chronic illness, physical or mental disability. LTC has been widely studied in the literature, in particular due to concerns surrounding how future demographic shifts may impact the LTC system’s ability to cater to increasing amounts of patients not withstanding what the future cost impact might be. With that said, few studies have attempted to model demand at the local level for the purposes of informing local service delivery and organisation. Many developing countries with mature and developed systems of LTC in place are under pressure to reduce health care spend, whilst delivering greater value for money. We suggest that the lack of local studies in LTC stems from the lack of a strong case for the benefits of demand modelling at the local level in combination with low quantity and incomplete social care data. We propose a mathematical model to show how savings may be generated under different models of commitment with third party providers. Secondly, we propose a hybrid-fuzzy demand model to generate estimates of demand in the short to medium term that can be used to inform contract design based on local area needs – such an approach we argue is more suited to problems in which historic activity is incomplete or limited. Our results show that commitment models can be of great use to local health care planners with respect to lowering their care costs, at the same time our formulation had wider generic applicability to procurement type problems where commitment size in addition to the timing of commitments needs to be determined

Interpretive structural model of key performance indicators for sustainable manufacturing evaluation in automotive companies

This paper aims to analyze the interrelationships among the key performance indicators of sustainable manufacturing evaluation in automotive companies. The initial key performance indicators have been identified and derived from literature and were then validated by industry survey. Interpretive structural modeling (ISM) methodology is applied to develop a hierarchical structure of the key performance indicators in three levels. Of nine indicators, there are five unstable indicators which have both high driver and dependence power, thus requiring further attention. It is believed that the model can provide a better insight for automotive managers in assessing their sustainable manufacturing performance

A fuzzy front end model for concurrent specification in new product development

This research reports on the development of a new model for an early design stage in new product development (NPD) programmes called the Fuzzy Front End (FFE). The new FFE model aims at overcoming two kinds of limitations identified in previous FFE models. The first limitation concerns current trends in FFE model improvement including the need for a data-driven model, and to address agile development, incremental and radical NPDs, balanced explicitness and responsiveness characteristics, and balanced procedural and performative structures. The second limitation concerns deficiencies in the performance structure and operating mechanism regarding contextual performance and concurrent collaboration. This means that performances in the FFE do not systematically link with each other, either in a single functional domain or multidimensionally across diverse functional domains, but instead exist independently. A pragmatic-prescriptive model has been functionally embodied by analysing real-world FFE scenarios using inductive reasoning. The model is data-driven with a performative structure wherein parameters can interlock for contextual performance and concurrent collaboration throughout the entire FFE process. With this interlocking structure, once an initial parameter is produced, all remaining parameters considered from both perspectives can be obtained successively. This model allows performers to explicitly understand the purpose and roles of parameters and their relationships from both perspectives when processing parameters. The model thus leads to more agile FFE execution by reducing the iterative work needed to correct defective parameters which have not been handled with contextual performance and concurrent collaboration in mind but instead exist independently. A theoretical-descriptive model, produced by validating the developed pragmatic-prescriptive model, using deductive reasoning, consists of mathematical formulas, providing the underlying concept of an overall FFE as well as that of its parts. Consequently, the pragmatic-prescriptive model can serve as functional performance guidance, while the theoretical-descriptive model can serve as conceptual performance guidance when employing the pragmatic-prescriptive model.Open Acces

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

Application of Optimization in Production, Logistics, Inventory, Supply Chain Management and Block Chain

The evolution of industrial development since the 18th century is now experiencing the fourth industrial revolution. The effect of the development has propagated into almost every sector of the industry. From inventory to the circular economy, the effectiveness of technology has been fruitful for industry. The recent trends in research, with new ideas and methodologies, are included in this book. Several new ideas and business strategies are developed in the area of the supply chain management, logistics, optimization, and forecasting for the improvement of the economy of the society and the environment. The proposed technologies and ideas are either novel or help modify several other new ideas. Different real life problems with different dimensions are discussed in the book so that readers may connect with the recent issues in society and industry. The collection of the articles provides a glimpse into the new research trends in technology, business, and the environment

The development of an Interval Grey Regression Model for Limited Time Series Forecasting

[[abstract]]The grey model GM(1, 1) is a popular forecasting method in management and engineering applications. In order to obtain more validity and reliable forecasting values, fuzzy grey regression model is proposed by hybridizing fuzzy set into grey model GM(1, 1) for solving crisp-input and fuzzy-input limited time series. In the present study, we continue to investigate and derive the interval grey regression model with a minimum regression interval by necessity analysis in which the predicted interval is possibly to be belonged to the collected interval data with certain membership degree. In the illustrative example we did not have as much information as the research institutes of Display search, iSuppli, and PIPA, but we succeeded at forecasting LCD TV demand by using the interval grey regression model with limited and interval-input data.[[incitationindex]]SCI[[incitationindex]]EI[[booktype]]紙