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Various method have been used by organisations in the construction industry to improve quality, employing mainly two major techniques: management techniques such as quality control, quality assurance, total quality management; and statistical techniques such as cost of quality, customer satisfaction and the six sigma principle. The purpose of this paper is to show that it is possible to employ the six sigma principle in the field of construction management provided that sufficient information on a particular population is obtained.

Statistical properties of the hyperbolic distribution are given and quality factors such as population in range, number of defects, yield percentage and defects per million opportunities are estimated. Graphical illustrations of the hyperbolic and Gaussian distributions are also given. From that, detailed comparisons of these two distributions are numerically obtained. The impacts of these quality factors are briefly discussed to give a rough guidance to organisations in the construction industry on how to lower cost and to improve project quality by prevention. A case study on a construction project is given in which it is shown that the hyperbolic distribution is better suited to the cost data than the Gaussian distribution. Cost and quality data of all projects in the company are collected over a period of eight years. Each project may consist of a number of phases, typically spanning about three months. Each phase can be considered as a member of the project population. Quality factors of this population are estimated using the six sigma principle.

The paper finds that by using a suitable distribution, it is possible to improve quality factors such as population in range, yield percentage and number of defects per million opportunities.

This paper is of value in assessing the suitability of the hyperbolic and Gaussian distributions in modelling the population and showing that hyperbolic distribution can be more effectively used to model the cost data than the Gaussian distribution.

The purpose of this study is to investigate the relationship between local population, natural and cultural resources on tourist quality an ecotourism product in Seagrass Trikora Conservation Area, Bintan Regency and Riau Island.

The research model portrayed in this case consists of three variables (tourists, local population and resources); these variables try to describe how ecotourism in Riau Island can be developed. This study is based on a survey conducted in June 2015 of 200 Indonesian citizens and residents. List contains 900 potential participants that were filtered from numerous public sources and from the researchers’ professional and social contacts. The interviewers were contacted to alert them to participate in the survey. A total of 200 completed responses were received within 10 weeks of survey, and 200 responses were successfully collected. These responses are analyzed and presented in this research.

This study found that higher quality of the local population, natural resources and cultural resources would have an impact on improving ecotourism quality. On the other hand, higher ecotourism quality would be able to improve the performance of ecotourism. The implications of this research contributed to the development of ecotourism in the Riau Island: improving the quality of the surrounding population, i.e. in the improvement of non-formal education of the population capable of supporting ecotourism; improvement of material and non-material quality of the ecotourism area; and maintenance of the natural resources of the ecotourism area.

This research tried to sort natural and cultural resources into two different things: natural resources were measured by specific activities, biodiversity protection, ecology maintenance and travel involvement in natural landscape and cultural resources were measured by ensuring cultural integrity, ensuring the social coherence of communities and maintaining cultural possibilities. Thus, the originality of this research lied in the use of two separate variables of natural resources and cultural resources in the performance of ecotourism. Separation of variables of ecotourism quality and performance of ecotourism became the second originality in this study. This study aimed to examine the effects of quality of local population (X1), natural resources (X2) and cultural resources (X3) on ecotourism quality (Y1), and its impact on Performance of Ecotourism (Y2), comprehensively.

This paper aims to identify variables that determine the differing levels of environmental quality on Java and other islands in Indonesia.

Using a quantitative approach, secondary data were sourced from the Central Statistics Agency and the Ministry of Environment and Forestry. The data were obtained through the collection of documentation from 33 provinces in Indonesia. The analytical approach used was discriminant analysis. The research variables are Trade Openness, Foreign Direct Investment (FDI), industry, HDI and population growth.

The variables that distinguish between the levels of environmental quality in Indonesian provinces on the island of Java and on other islands are Industry, HDI, FDI and population growth. The openness variable is not a differentiating variable for environmental quality. The most powerful variable as a differentiator of environmental quality on Java Island and on other islands is the Industry variable.

This study has not classified the quality of the environment based on the Ministry of Environment and Forestry's categories, namely, the very good, good, quite good, poor, very poor and dangerous. For this reason, further research is needed using multiple discriminant analysis (MDA).

Industry is the variable that most strongly distinguishes between levels of environmental quality on Java and other island, while the industrial sector is the largest contributor to gross regional domestic product (GDRP). Government policy to develop green technology is mandatory so that there is no trade-off between industry and environmental quality.

This study is able to identify the differentiating variables of environmental quality in two different groups, on Java and on the other islands of the Indonesian archipelago.

At the beginning of the 21st century, multiple and diverse social entities, including the public (consumers), private and nonprofit healthcare institutions, government (public health) and other industry sectors, began to recognize the limitations of the current fragmented healthcare system paradigm. Primary stakeholders, including employers, insurance companies, and healthcare professional organizations, also voiced dissatisfaction with unacceptable health outcomes and rising costs. Grand challenges and wicked problems threatened the viability of the health sector. American health systems responded with innovations and advances in healthcare delivery frameworks that encouraged shifts from intra- and inter-sector arrangements to multi-sector, lasting relationships that emphasized patient centrality along with long-term commitments to sustainability and accountability. This pathway, leading to a population health approach, also generated the need for transformative business models. The coproduction of health framework, with its emphasis on cross-sector alignments, nontraditional partner relationships, sustainable missions, and accountability capable of yielding return on investments, has emerged as a unique strategy for facing disruptive threats and challenges from nonhealth sector corporations. This chapter presents a coproduction of health framework, goals and criteria, examples of boundary spanning network alliance models, and operational (integrator, convener, aggregator) strategies. A comparison of important organizational science theories, including institutional theory, network/network analysis theory, and resource dependency theory, provides suggestions for future research directions necessary to validate the utility of the coproduction of health framework as a precursor for paradigm change.

Much has been written about quality in patient care and clinical support services, but very little about the quality of purchasing. This paper gives an overview of quality issues in purchasing, and offers guidelines and practical steps for purchasers to improve service quality – both their own and their providers’. It defines quality in purchasing and considers how purchasers can influence markets and work with providers to improve health services quality. The paper gives practical guidance for improving quality, which recognises the limited resources and skills which purchasers have for the task. It addresses some issues raised by purchaser/managers: How does a purchasing organisation measure and improve quality? Is there a better way of specifying and monitoring quality than the “shopping‐list of standards” approach – what should be asked of providers? How can information about clinical quality, outcome and costs, be obtained in a form in which reliable comparisons can be made? Is quality accreditation or registration a good predictor of future quality?

During the early 1970s, faced with the serious demographic situation, China began to fully implement the policy of family planning in urban and rural regions. Nowadays, the problems of pension and medical care for aged parents confronted by the first generation of the one‐child family have begun to gradually appear. Meanwhile, China's population and the family planning are also faced with some problems that are difficult to solve, including unbalanced fertility rate of urban and rural population, the gender imbalance, the difficulty of the risk diversification in a one‐child family, as well as the profound contradiction between the stability of the family planning policy and the drive of administrative measures. Therefore, it is necessary to establish the integrated‐scheduled life security system of the one‐child family in urban and rural areas, in order to overcome the problems and to promote the transformation of the family planning policy. The purpose of this paper is to discuss the life security system for China's one‐child families.

The life security system for the one‐child family proposed by this paper consists of three issues: the basic security based on the level of social security, the additional security of the policy insurance and the supplementary security of the commercial insurance. The paper begins with the history of the family planning policy in the first section and then go through some relevant articles regarding complementary measures such as maternity insurance, rural endowment insurance that only focused on one aspect of issues associated with the family planning. In section three, four typical problems are listed for the purpose of following discussion of corresponding solutions which are full of deficiency in section four. In part five, the integrated planning of the life security system for Chinese one‐child family is elaborated with risk and fund management. In the last part, we conclude that the family planning policy maintains stable, whereas measures to be taken are adjusted along with changeable new problems.

The policy insurance plays an increasingly important role in dealing with the life security of older people in one‐child families. It may be better to promote the kind of insurance.

The paper comprehensively discusses the life security system for Chinese families in compliance with the family planning policy.

The aims of this study is to put on the agenda discussions concerning the approach of sustainable goals and indicators, in terms of how they relate to each other and how to list their importance within a network of contemporary city management. From the millennium objectives experience, UN has launched the continuity of the development program, through the sustainable development goals (SDG), which have the purpose of giving support to local and regional governments for the 2030 agenda in local sphere. In the city context, sustainable development has also been approached in regulations, like ISO 37120: 2017 “Sustainable development of communities: Indicators for city services and quality of life”. These instruments have in common the concern of offering parameters of public services to citizens and promoting in a uniform manner both social and economic growth of the urban environment.

The present study aims to compare these two sustainable development tools by means of a documentary analysis and to analyze the feasibility of the proposed indicators and their qualitative evaluation goals to improve citizens’ quality of life.

The results suggest that the main urban challenges are related to unplanned urban growth and poor-quality public services, which generate a lack of commitment to enforce laws and to achieve sustainable development goals.

The study establishes bases for guiding the discussion to support managers and investors decisions to promote paradigm changes in the citizens’ life and in the way cities are planned.

The Organization for Economic Cooperation and Development (OECD) countries are facing unprecedented challenges related to climate change and population aging. The purpose of the analysis is to explore the relationship between population aging and environmental degradation, accounting for human capital, using a sample of 19 OECD countries over the period 1980–2019.

On the empirical methodology, the analysis uses panel estimators with heterogenous coefficients and an error structure that takes into consideration cross-country heterogeneity and cross-sectional dependence for a panel of 19 OECD countries over the period 1980–2019. To examine the relationship between population aging and environmental degradation, the authors employ two alternative measures of environmental degradation that is energy consumption and CO2 emissions in metric tons per capita. Concerning the regressors, the authors account for two alternative aging indicators, namely the elderly population and the old-age dependency ratios to confirm robustness.

The analysis provides evidence that population aging and human capital development (IHC) lead to lower energy consumption in the OECD sample. Overall, the growing number of elderly people in the OECD seems to act as a mitigating factor for energy consumption. The authors view these results as conveying the message that the evolution of population aging along with channeling government expenditures towards human capital enhancement are important drivers of curbing energy consumption and ensuring environmental sustainability. The authors' research is of great significance for environmental policymakers by illuminating the favorable energy consumption patterns that population aging brings to advanced economies.

The main limitation of this study concerns data availability. Future research, and subject to greater data availability in the future, could dig deeper into understanding the dynamics of this complex nexus by incorporating additional control variables. Similarly, the authors focus on aggregate renewable energy consumption, and the authors do not explicitly model the sources of renewable energy (wind, hydropower, solar power, solid biofuels and other). Additional analysis of the breakdown of renewable energy sources would be insightful – subject to data availability – especially for meeting the recently agreed new target of 42.5% for European Union (EU) countries by 2030. A deep transformation of the European energy system is needed for the EU to meet the target. Finally, extending the model to include a range of non-OECD countries that are also experiencing demographic transformations is a promising avenue for future research.

To the best of the authors' knowledge, this study is the first to examine the effects of population aging and human capital on environmental degradation using a broad set of OECD countries and advanced spectrum estimation methods. Given cross-sectional dependencies and cross-country heterogeneity, the authors' empirical results underline the importance of cross-OECD policy spillovers and knowledge diffusions across the OECD countries. The new “energy culture” calls for concerted policy action even in an aging era.

The purpose of this study is to reduce the number of mutations and, consequently, reduce the cost of mutation test. The results of related studies indicate that about 40% of injected faults (mutants) in the source code are effect-less (equivalent). Equivalent mutants are one of the major costs of mutation testing and the identification of equivalent and effect-less mutants has been known as an undecidable problem.

In a program with n branch instructions (if instruction) there are 2n execution paths (test paths) that the data and codes into each of these paths can be considered as a target of mutation. Given the role and impact of data in a program, some of data and codes propagates the injected mutants more likely to the output of the program. In this study, firstly the error-propagation rate of the program data is quantified using static analysis of the program control-flow graph. Then, the most error-propagating test paths are identified by the proposed heuristic algorithm (Genetic Algorithm [GA]). Data and codes with higher error-propagation rate are only considered as the strategic locations for the mutation testing.

In order to evaluate the proposed method, an extensive series of mutation testing experiments have been conducted on a set of traditional benchmark programs using MuJava tool set. The results depict that the proposed method reduces the number of mutants about 24%. Also, in the corresponding experiments, the mutation score is increased about 5.6%. The success rate of the GA in finding the most error-propagating paths of the input programs is 99%. On average, only 7.46% of generated mutants by the proposed method are equivalent. Indeed, 92.54% of generated mutants are non-equivalent.

The main contribution of this study is as follows: Proposing a set of equations to measure the error-propagation rate of each data, basic-block and execution path of a program. Proposing a genetic algorithm to identify a most error-propagating path of program as locations of mutations. Developing an efficient mutation-testing framework that mutates only the strategic locations of a program identified by the proposed genetic algorithms. Reducing the time and cost of mutation testing by reducing the equivalent mutants.