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China's population aging is gradually deepening and needs to be actively addressed. The purpose of this paper is to construct a novel model for analyzing the population aging.

To analyze the aging status of a region, this study has considered three major indicators: total population, aged population and the proportion of the aged population. Additionally, the authors have developed a novel grey population prediction model that incorporates the fractional-order accumulation operator and Gompertz model (GM). By combining these techniques, the authors' model provides a comprehensive and accurate prediction of population aging trends in Jiangsu Province. This research methodology has the potential to contribute to the development of effective policy solutions to address the challenges posed by the population aging.

The fractional-order discrete grey GM is suitable for predicting the aging population and has good performance. The population aging of Jiangsu Province will continue to deepen in the next few years.

The proposed model can be used to predict and analyze aging differences in Jiangsu Province. Based on the prediction and analysis results, identified some corresponding countermeasures are suggested to address the challenges of Jiangsu's future aging problem.

The fractional-order discrete grey GM is firstly proposed in this paper and this model is a novel grey population prediction model with good performance.

Forecasting population movement trends is crucial for implementing effective policies to regulate labor force growth and understand demographic changes. Combining migration theory expertise and neural network technology can bring a fresh perspective to international migration forecasting research.

This study proposes a conditional generative adversarial neural network model incorporating the migration knowledge – conditional generative adversarial network (MK-CGAN). By using the migration knowledge to design the parameters, MK-CGAN can effectively address the limited data problem, thereby enhancing the accuracy of migration forecasts.

The model was tested by forecasting migration flows between different countries and had good generalizability and validity. The results are robust as the proposed solutions can achieve lesser mean absolute error, mean squared error, root mean square error, mean absolute percentage error and R² values, reaching 0.9855 compared to long short-term memory (LSTM), gated recurrent unit, generative adversarial network (GAN) and the traditional gravity model.

This study is significant because it demonstrates a highly effective technique for predicting international migration using conditional GANs. By incorporating migration knowledge into our models, we can achieve prediction accuracy, gaining valuable insights into the differences between various model characteristics. We used SHapley Additive exPlanations to enhance our understanding of these differences and provide clear and concise explanations for our model predictions. The results demonstrated the theoretical significance and practical value of the MK-CGAN model in predicting international migration.

As an important carrier of sustainable economy and social development, population is the foundation of the whole society. Scientific predictions of future population growth will bring great reference to macro-economic and social planning. For China, as a country of the biggest population, the research on its population policy is worthwhile.

Previous literatures on population growth prediction are generally based on time-series analysis. However, the new two-child policy in China provides us an opportunity to predict the population growth from the perspective of the welfare efficiency, since each family is able to determine whether to have the second child on account of the family’s utility. The welfare efficiency is calculated through the database of newborn babies, disposable income per capita, living resource per capita, and health expenditure pre capital. These are the main factors by which each family decides whether to bear additional babies. In this chapter, we perform the micro-economic analysis on a new policy and propose a Data Envelopment Analysis (DEA) method to predict the population growth. Under the condition of policy adjustment, we successfully predict the population growth with this method. We also propose some suggestions concerning the implementation of the new policy.

The purpose of this paper is to predict the population of Anhui province. The authors analyze the trend of the main demographic indicators.

On the basis of the main methods of statistics, this paper studies the tendency of the population of Anhui province. It mainly analyzes the sex structure and the age structure of the current population. Based on the GM(1,1) model, this paper forecasts the total population, the population sex structure, and the population age structure of Anhui province in the next ten years.

The results show that the total population was controlled well, but there have been many problems of the population structure, such as the aging population, high sex ratio, heavy social dependency burden, and the declining labor force.

This paper forecasts the main indexes of the population of Anhui province and provides policy recommendations for the government and the relevant departments.

This paper utilizes data analysis method and the grey forecasting model to study the tendency of the population problems in Anhui province.

The theory of competitiveness of cities is based on Porter’s Diamond Theory. There is a relation between housing and urban competitiveness. The adequacy of land supply and allocation of land for new housing development is integral. This paper aims to estimate the required number of housing units to secure housing needs in Tehran for the next four years in 1400 H.Sh (2021 A.D.). The research methodology is carried out using qualitative and quantitative approaches based on the given data. First, the population of Tehran in 1400 H.Sh was predicted using nonlinear quadratic polynomial, Gompertz and logistic models. Then, a Logistic model is proposed to estimate the number of housing units in Tehran. The calculations of residential units related to the population obtained from the Gompertz model equivalent to 663141 is suggested as a criterion for local authority to future decision making and planning for urban development.

The present research is an applied research in terms of the purpose a descriptive research in terms of the nature and methodology and a descriptive-analytical research in terms of attitude and approach toward the research problem (Hafeznia, 2013, 58, 63 and 71). To provide the required information for the analytical stage, a documentary method, related to the use of internal and external books and papers, has been applied. First, the population of Tehran in 1400 H.Sh is estimated using three nonlinear models of quadratic polynomials, Gompertz and logistic. Then, among them, the options that were more consistent with the estimation of the new comprehensive plan of Tehran (1386 H.Sh), which is the most important plan of this city, were chosen. After that, by using the logistic model, which is an appropriate expression of saturable phenomena and a suitable method of estimating the number of residential units in a city and based on the past trend, the future of housing is predicted, and the number of required residential units is determined.

Any city for competitiveness must seek the search and development of a set of unique strategies and practices that will shape its status from other cities. No single action for all cities is feasible. In fact, the most important challenge is to propose a unique value proposition and to formulate a strategy that distinguishes that city from the rest. Among the measures taken around the world is attention to infrastructure. From the point of view of competitiveness, different types of investment in infrastructure are important for different types of cities and in different stages of development of a city. Large cities need targeted investments in housing issues to overcome the segments associated with the poorer neighborhoods. Without investment in desirable housing, there will be holes in competitive advantage. In this paper, the number of residential units in Tehran was projected for 2021. The city’s population was originally estimated for 2021. In addition to the models used to predict and estimate necessary, it is necessary to consider the area, land use map, future development lines and […] city. To this end, the city can continue to meet the needs of residents’ diversification and the city’s needs. We cannot accept any predictions about the population and, consequently, the number of residential units. Providing predictions can provide the most predictive, or more prudent, and different scenarios that can emerge, which will lead to flexibility in the presentation of plans and programs. Among the models that were used to predict the population, the result obtained from second-order polynomial and Gompartz models was found to be appropriate for the estimation of the new comprehensive design of Tehran (2007). But the prediction of the population of the logistic model was beyond the prediction of the new comprehensive plan of Tehran (2007) and thus was not considered appropriate. The number of residential units required according to the predicted population of the second order polynomial models, Gompartz and the population considered in the new comprehensive plan of Tehran (2007). After the finalization of the proposed population, using the logistic model, the number of residential units needed in Tehran was projected for 2021. Since these three estimates are somewhat close to each other, it is suggested that Gompertz model calculations, equivalent to 663,141 residential units, are proposed, and according to that, local authorities are planning to supply land to achieve economic competitiveness (urban). As it is shown in the conceptual model of the paper in Figure 1, after determining the need for housing, it is necessary to ask whether the adequacy of the supply and allocation of land, as well as the importance of maintaining it for the development of housing by local authorities, is clear. Also, is there any suitable planning for that? Despite the severe shortage of ready-made land for the city of Tehran, a large volume of land is a large area owned by natural and legal persons, and, in particular, state-owned enterprises of semipublic and public institutions, which have been abandoned in cities for years without use and in the form of barren. According to municipal management laws, municipalities can receive land, taxes and fees that are included in the annual budget of the Tehran Municipality. According to the figure obtained from this study, which states that 663,141 residential units are needed for Tehran in 2021, large landowners in Tehran need to supply their land to the market. According to the Population and Housing Census in Tehran in 2011, there are 245,769 inhabited vacancies in Tehran; hence there are two scenarios for the provision of residential units in the city of Tehran in 2021, assuming that these units in the housing market require 417,372 units Another residence will be for Tehran, otherwise 663141 residential units will be needed for Tehran in 2021. Other possibl

Tehran is the largest city and the capital of Iran, and it is also the capital of the province Tehran. In the southern foothills of the Alborz Mountains within a longitude of 51 degrees and 2 minutes East to 51 degrees and 36 minutes East, with an approximate length of 50 kilometers and latitude 35 degrees and 34 minutes North to 35 degrees and 50 minutes North with an approximate width of 30 kilometers. The area of this city is 730 km². This is one of the largest cities in West Asia, the 25th the most populous city, and the 27th greatest city to the world. The administrative structure of Iran has been concentrated in this city. The city has been divided into 22 zones, 134 areas (including Rey and Tajrish), and 370 districts (Wikipedia). The problem of housing in the city of Tehran has always been one of the important issues that less has been planned for it. The result is housing shortage, high housing prices and so on, due to the excessive expansion of the city, its population increase and so on.

The Saudi 2030 Housing Program Vision aims to increase the population of Riyadh City, the capital of the Kingdom of Saudi Arabia, to between 15 and 20 million people. This paper aims to predict the demand for residential units in Riyadh City by 2030 in line with this vision.

This paper adopts a statistical modeling approach to estimate the residential demands for Riyadh City. Several population growth models, including the nonlinear quadratic polynomial spline regression model, the sigmoidal logistic power model and the exponential model, are tested and applied to Riyadh to estimate the expected population in 2030. The growth model closest to the Kingdom’s goal of reaching between 15 and 20 million people in 2030 is selected, and the paper predicts the required number of residential units for the population obtained from the selected model. Desktop database research is conducted to obtain the data required for the modeling and analytical stage.

The exponential model predicts a population of 16,476,470 in Riyadh City by 2030, and as a result, 2,636,235 household units are needed. This number of housing units required in Riyadh City exceeds the available residential units by almost 1,370,000, representing 108% of the available residential units in Riyadh in 2020.

This study provides valuable insights into the demand for residential units in Riyadh City by 2030 in line with the Saudi 2030 Housing Program Vision, filling the gap in prior research. The findings suggest that significant efforts are required to meet the housing demand in Riyadh City by 2030, and policymakers and stakeholders need to take appropriate measures to address this issue.

This paper aims to analyze general development trend of China’s population and to forecast China’s total population under the change of China’s family planning policy so as to measure shock disturbance effects on China’s population development.

China has been the most populous country for hundreds of years. And this state will be sustained in the forthcoming decade. Obviously, China is confronted with greater pressure on controlling total scale of population than any other country. Meanwhile, controlling population will be beneficial for not only China but also the whole world. This paper first analyzes general development trend of China’s population total amount, sex ratio and aging ratio. The mechanism for measurement of the impact effect of a policy shock disturbance is proposed. Linear regression model, exponential curve model and grey Verhulst model are adopted to test accuracy of simulation of China’s total population. Then considering the policy shock disturbance on population, discrete grey model, DGM (1, 1), and grey Verhulst model were adopted to measure how China’s one-child policy affected its total population between 1978 and 2015. And similarly, the grey Verhulst model and scenario analysis of economic developing level were further used to forecast the effect of adjustment from China’s one-child policy to two-child policy.

Results show that China has made an outstanding contribution toward controlling population; it was estimated that China prevented nearly 470 million births since the late 1970s to 2015. However, according to the forecast, with the adjustment of the one-child policy, the birth rate will be a little higher, China’s total population was estimated to reach 1,485.59 million in 2025. Although the scale of population will keep increasing, but it is tolerable for China and sex ratio and trend of aging will be relieved obviously.

The approach constructed in the paper can be used to measure the effect of population change under the policy shock disturbance. It can be used for other policy effect measurement problems under shock events’ disturbance.

The paper succeeded in studying the mechanism for the measurement of the post-impact effect of a policy and the effect of changes in China’s population following the revision of the one-child policy. The mechanism is useful for solving system forecasting problems and can contribute toward improving the grey decision-making models.

We analyse the dynamics of social assistance benefit (SA) receipt among working-age adults in Britain between 1991 and 2005. The decline in the annual SA receipt rate was driven by a decline in the SA entry rate rather than by the SA exit rate (which also declined). We examine the determinants of these trends using a multivariate dynamic random effects probit model of SA receipt probabilities applied to British Household Panel Survey data. We show how the model may be used to derive year-by-year predictions of aggregate SA entry, exit and receipt rates. The analysis highlights the importance of the decline in the unemployment rate over the period and other changes in the socio-economic environment including two reforms to the income maintenance system in the 1990s and also illustrates the effects of self-selection (‘creaming’) on observed and unobserved characteristics.

This paper's objective is to provide improvement plans that take into account problems in the housing sector, as well as low fertility and demographic problems caused by aging, by suggesting long‐term policy directions considering all future possible changes in fertility and housing policies.

This research analyzes age specific fertility rates by socioeconomic index, composition of three scenarios about the total fertility rate, the forecast of the future population by the cohort component method, and the forecast of housing demand according to the Mankiw‐Weil (M‐W) model.

If the fertility rate increases through improvements in socioeconomic conditions, then we see that housing demand also increases. If the fertility rate level is higher than that of scenario 3, then a housing demand decrease comes later. However, even if the low fertility rate issue is addressed, the problem with the housing market due to the aging is expected to continue for the time being.

If the population decrease cohort is accumulated due to the continuously low fertility, then it will cause an increase in the reduction effect of housing demand. Considering housing spaces, the elderly require a relatively large amount of available space in Korea where the aged population is rapidly increasing. This increase in seniors could counterbalance the reduced demand for housing.

This is a long‐term‐oriented paper about housing demand and the changing trends in Korea, which is undergoing demographic changes due to low fertility and ongoing aging. We need to monitor fertility rates and the structure of population changes to achieve a stable housing market, and we should also recognize that these structural changes by age will have diverse ripple effects on housing demand.

Expanded awareness and application of recent PLS-SEM reporting practices were again called for by Hair (2022) in his PLS 2022 Keynote Address. This paper aims to analyze and extend the application of PLS-SEM in Industrial Management and Data Systems (IMDS) to focus on trends emerging in the more recent 2016–2022 period.

A review of PLS-SEM applications in information systems studies published in IMDS and MISQ for the period 2012–2022 identifies and comments on a total of 135 articles. Selected emerging advanced analytical PLS-SEM applications are also highlighted to expand awareness of their value in more rigorously evaluating model results.

There is a continually increasing maturity of the information systems field in applying PLS-SEM, particularly for IMDS authors. Model complexity and improved prediction assessment as well as other advanced analytical options are increasingly identified as reasons for applying PLS-SEM.

Findings demonstrate the continued use and acceptance of PLS-SEM as a useful alternative research methodology within IS. PLS-SEM is the preferred SEM method in many research settings, but particularly when the research objective is prediction to the population, mediation and mediated moderation, formative constructs are specified, constructs must be modeled as higher-order and for competing model comparisons.

This update on PLS-SEM applications and recent methodological developments will help authors to better understand and apply the method, as well as publish their work. Researchers are encouraged to engage in more complete analyses and include enhanced reporting procedures.

Applications of PLS-SEM for prediction, theory testing and confirmation are increasing. Information systems scholars should continue to exercise sound practice by reporting reasons for using PLS-SEM and recognizing its wider applicability for both exploratory and confirmatory research.