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This paper aims to give a brief review on behavioral economics and behavioral finance and discusses some of the previous research on agents' utility functions, applicable risk measures, diversification strategies and portfolio optimization.

The authors also cover related disciplines such as trading rules, contagion and various econometric aspects.

While scholars could first develop theoretical models in behavioral economics and behavioral finance, they subsequently may develop corresponding statistical and econometric models, this finally includes simulation studies to examine whether the estimators or statistics have good power and size. This all helps us to better understand financial and economic decision-making from a descriptive standpoint.

The research paper is original.

This paper aims to investigate how a prospective buyer’s optimal home-size purchase can be determined by means of a stochastic-dominance (SD) analysis of the historical data of Hong Kong.

By means of SD analysis, the paper uses monthly property yields in Hong Kong over a 15-year period to illustrate how buyers of different risk preference may optimize their home-size purchase.

Regardless of whether the buyer eschews risk, embraces risk or is indifferent to it, in any adjacent pairing of five well-defined housing classes, the smaller class provides the optimal purchase. In addition, risk-averters focusing on total yield would prefer to invest in the smallest and second-smallest classes than in the largest class.

As the smaller class provides the optimal purchase, the smallest class affords the buyer the optimal purchase over all classes in this important housing market – at least where rental yields are of primary concern.

The findings suggest that in the Hong Kong housing market, long-term investors may be better off purchasing smaller homes. For other type of investors, it depends on their risk preference.

There is a very small body of empirical literature on housing investment, especially if the focus is on the optimal home-size purchase.

Due to the structural layout, mining process, and working environment, curved chains such as horizontal and vertical bends inevitably exist in the armoured face conveyor (AFC). With the increasing power, conveying capacity, and distance of the AFC, the dynamic influence of these curved chains should be highly emphasized. This paper establishes a dynamic model of the AFC by multi-body system theory and finite segment method, in which the curved chains can be fully considered.

The scraper chains are firstly grouped into the straight, horizontal bend, vertical convex and concave bend sections. Each bend section running in a circle is simplified as an ideal arc. Through solving its differential equilibrium equation and using Newton's second law, its running resistance is derived. Then the grouped chains are discretized into finite control elements according to the Kelvin model, and the governing equation of each control element is established. The dynamic model of the AFC is obtained by assembling these equations, and the corresponding simulation model is developed by using MATLAB/Simulink.

Case studies with real scenarios are provided, and simulations are carried out. The results show that the running resistance contributed by the curved chains is larger than the traditional empirical value.

The work in this paper helps the dynamic performance design of AFC, with a deep understanding of the curved chains.

The frequency‐of‐circulation distributions from each of the sixteen libraries participating in the initial period of operation of the Public Lending Right are discussed. Differences between the libraries are highlighted and for each the adequacy of various refinements of the simplest model are considered.

Some scholars argue that corruption hinders economies and investment because it generates extra costs, while others suggest that it can act as a stimulus. Their mixed empirical findings have prompted the analysis of whether investors' attitude towards corruption changes depending on its degree of prevalence.

The authors examined 4,518 public–private partnerships (PPPs) located in 46 developing countries for the period 1997–2017. The data were collected from the World Bank PPP database. The authors investigated the relationship between the amount of investment in PPP projects and the level of corruption using regression with multilevel mixed effects.

Corruption and the amount of investment in PPP projects are inversely related at the low and high end of the spectrum of corruption, but the relationship is positive towards the middle. Further analysis revealed that this was spurred by high investment PPP projects in less developed countries.

The findings allow the authors to reconcile the opposing positions in the literature through a “sand–grease–sand the wheels” effect between the volume of investment and corruption, which can be configured as a reverse S-shape consisting of three stages.

The purpose of this paper is to study the seismic performance of the energy-saving block and invisible multi-ribbed frame composite walls (EBIMFCW), changing the shear-span ratio as the test parameter, the low-cycle reciprocating loading tests of six 1/2 scale wall models were carried out.

The test design method and analysis are used for the seismic performance of the EBIMFCW.

With the increase of shear-span ratio: the walls tend to occur bending failure even more, the initial stiffness of the wall decreases, the overall ductility of the wall is improved and the walls tend to occur bending failure.

The previous studies do not involve the seismic performance of EBIMFCW under different shear-span ratios. Therefore, the paper studies the hysteresis behavior, ductility, stiffness degradation and energy dissipation performance of EBIMFCW under different shear-span ratios.

To analyze the impact of temporary retail price discount on a consumer goods product category using semiparametric regression and considering different promotional price discount characteristics as well as brand characteristics.

A semiparametric regression model using Support Vector Machines, which aim to evaluate retailers' decisions about temporary price discounts, has been developed. The model is derived from the analysis of historical sales data, which provide precise evaluation of previous temporary price discounts periods. The model is also consistent with ample empirical evidence showing that historical retail sales data can be used to evaluate the impact of past promotions.

Provides an estimation of the shape of the deal effect curve, indicating which temporary price discounts are more effective to increase sales and showing the existence of different threshold and saturation levels. Confirms that promotional price discounts accelerate sales especially during week ends. Evidences that promoting high‐priced (high‐quality) brands has a stronger impact on sales of low‐priced (low‐quality) brands than the reverse and that cross‐price effects are stronger on the sales of brands with similar prices. Suggests the convenience of the use of the proposed semiparametric methodology to the study of the promotional effects considered.

It is not possible to generalize the modelled shapes of the deal effect curves. There is no information available on feature advertising nor displays. It is important to determine the generalizability of these results to the study of additional promotional effects. It would also be interesting to assume that the retailer's deal policy is exogenous.

Provides a relevant tool to assess the set of price promotional periods by the grocery retailer. With a more precise and accurate knowledge about the performance of past temporary price cuts, retailers can implement more effective promotional periods.

This study aims to research the prediction performance of the bifurcation approach with different base models in different kinds of turbulent flows with rotation and curvature.

The k−ω and Shear-Stress Transport (SST) k−ω models are modified by using the complete eddy viscosity coefficient expression, and the latter is modified by using two sets of model coefficients. The two bifurcation models were tested in three cases: rotating channel flow with system rotation, Taylor–Couette flow with wall rotation and curvature effect and swirling flow through an abrupt axisymmetric expansion with inlet swirling flow.

In these flows, the bifurcation approach can significantly improve the prediction performance of the base model in the fluctuation velocity. The deviation of the BSkO model is slightly superior to the BkO model by about 2% in the Taylor–Couette flow. The prediction effect of the root-mean-square (RMS) velocity of the BSkO model increases by about 4–5% as the number of grids increases about 2.37 times, and the best is the Large Eddy Simulation (LES) grid used. Finally, compared with the SST k−ω model, the average iteration time of the SST with curvature correction (SST-CC), bifurcation k−ω (BkO) and bifurcation SST k−ω (BSkO) models increased by 27.7%, 86.9% and 62.3%, respectively.

This study is helpful to understand further the application of the bifurcation method in the turbulence model.