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The purpose of this paper is to explore how the cultural images of an urban quarter have been formulated by analyzing the Wing Lee Street (WLS) case in Hong Kong. This study aims to fill the gap in knowledge, which is predominantly associated with the effects of cultural policies on the production of attractive urban images, but has overlooked the social and ideological constructions placed on such imagery by the people viewing them.

In accordance with the study’s purpose, these images have been taken to have been formulated, thanks to the participation of different social forces that act based on their own respective interests.

This research has identified four social parties involved in the WLS project: the Urban Renewal Authority, which is a self-financed public corporation; local residents; nonprofit cultural organizations concerned with cultural continuity; and community interests, and artists and the media.

This study reveals the collisions, constraints and influences that result from these social forces’ interactions with one another, and how these have shaped the cultural image of WLS. Finally, this research presents the five dimensions of the cultural image of WLS.

Based on the social exchange theory, the paper aims to explore the effects of work–life support (WLS) practices on subjective well-being through work engagement and job satisfaction.

Data of 332 bank employees were collected in three waves and analyzed using AMOS and PROCESS macro.

The study revealed that WLS practices influenced employees' subjective well-being both directly and indirectly. The study's results further supported the serial mediation of the indirect effect through work engagement and job satisfaction.

Organizational WLS practices are supposed to play an effective role in helping employees increase subjective well-being. Organizations should attach importance to implementing WLS practices to ensure that employees are engaged and satisfied. Furthermore, organizations should undertake and communicate favorable WLS practices to stimulate employees' work and non-work well-being.

The study is the first that examines the impact of WLS practices on employees' subjective well-being. Furthermore, the study offers novel insights regarding the dual mediation effect of work engagement and job satisfaction in the relationship between WLS practices and subjective well-being.

The passive source localization (PSL) problem using angles of arrival (AOA), time differences of arrival (TDOA) or gain ratios of arrival (GROA) is generally nonlinear and nontrival. In this research, the purpose of this paper is to design an accurate hybrid source localization approach to solve the PSL problem. The inspiration is drawn from the fact that the bearings, TDOAs and GROAs are complementary in terms of their geometry properties.

The maximum-likelihood (ML) method is reexamined by using hybrid measurements. Being assisted by the bearings, a new hybrid weighted least-squares (WLS) method is then proposed by jointly utilizing the bearing, TDOA and GROA measurements.

Theoretical performance analysis illustrates that the mean-square error of the ML or WLS method can attain the Cramér-Rao lower bound for Gaussian noise over small error region. However, the WLS method has much lower computational complexity than the ML algorithm. Compared with the AOA-only, TDOA-only, AOA-TDOA, TDOA-GROA methods, the localization accuracy can be greatly improved by combining the AOAs, TDOAs and GROAs, especially for some specific geometries.

A novel bearing-assisted TDOA-GROA method is proposed for source localization, and a new hybrid WLS estimator is presented inspired from the fact that the bearings, TDOAs and GROAs are complementary in terms of their geometry properties.

The purpose of this paper is to consider the concept of Fuzzy Radial Basis Function Neural Networks with Information Granulation (IG‐FRBFNN) and their optimization realized by means of the Multiobjective Particle Swarm Optimization (MOPSO).

In fuzzy modeling, complexity, interpretability (or simplicity) as well as accuracy of the obtained model are essential design criteria. Since the performance of the IG‐RBFNN model is directly affected by some parameters, such as the fuzzification coefficient used in the FCM, the number of rules and the orders of the polynomials in the consequent parts of the rules, the authors carry out both structural as well as parametric optimization of the network. A multi‐objective Particle Swarm Optimization using Crowding Distance (MOPSO‐CD) as well as O/WLS learning‐based optimization are exploited to carry out the structural and parametric optimization of the model, respectively, while the optimization is of multiobjective character as it is aimed at the simultaneous minimization of complexity and maximization of accuracy.

The performance of the proposed model is illustrated with the aid of three examples. The proposed optimization method leads to an accurate and highly interpretable fuzzy model.

A MOPSO‐CD as well as O/WLS learning‐based optimization are exploited, respectively, to carry out the structural and parametric optimization of the model. As a result, the proposed methodology is interesting for designing an accurate and highly interpretable fuzzy model.

The purpose of this study is to explore the factors that influence the reporting of adverse events related to elder abuse and neglect in nursing homes from nursing home leaders' perspectives. Good leadership requires in-depth knowledge of the care and service provided and the ability to identify and address problems that can arise in clinical practice.

A qualitative explorative design with data triangulation was used. The sample consisted of 43 participants from two levels of nursing home leadership, representing six municipalities and 21 nursing homes in Norway. Focus group interviews were undertaken with 28 ward leaders and individual interviews with 15 nursing home directors. The constant comparative method was used for the analyses.

Both ward leaders and nursing home directors described formal and informal ways of obtaining information related to elder abuse and neglect. There were differences between their perceptions of the feasibility of obtaining formal reports about abuse in the nursing home. Three main categories of influencing factors emerged: (1) organisation structural factors, (2) cultural factors and (3) abuse severity factors. A main finding is that in its present form, the Norwegian adverse event reporting system is not designed to detect abuse and neglect.

This paper provides an in-depth understanding of patient safety and factors related to reporting elder abuse in nursing homes in Norway.

The knowledge- and Internet-based economy demands a reexamination of the accounting treatment for intangibles and a thorough understanding of the empirical evidence on this topic.

The study reviews the literature on research and development (R&D), a specific internally developed intangible asset, using meta-analysis techniques that allow to highlight the areas of consensus and disagreement in quantitative empirical results. The literature the authors review addresses four main research questions on (1) the determinants of the decision to capitalize R&D, (2) stock market-based outcomes of capitalizing R&D, (3) firm-based outcomes related to expensing R&D and (4) stock market-based outcomes of expensing R&D.

The authors find higher value relevance of capitalized compared with expensed R&D. There is, however, little robust evidence on the determinants of the capitalization decision and the characteristics of capitalizers.

The authors conclude by highlighting future research that can allow accounting academics to contribute to standard setting.

The purpose of this paper is to investigate convergence or divergence trends at global scale.

The paper questions the methodology and findings of the conventional convergence literature using linear OLS models. It introduces polynomial (quadratic) weighted least square (WLS) regression analysis to explore whether a number of economic performance indicators follow a non‐linear pattern of change.

The results indicate the formation of two groups in the world: a convergence one, including countries with low to medium‐high development levels, and a divergence one including countries with medium‐high to very high development levels.

Data availability after 1990 (for the composite indicators).

The findings shed light on important issues, such as the decrease of economic disparities between countries, the prospects for global economic convergence, and the development of a more equal world. Apart from obvious policy implication such findings are also of theoretical significance, providing a basis to check (indirectly) the validity of alternative growth theories.

This is the first paper (to the authors' knowledge) that explores world convergence/divergence employing quadratic WLS regression analysis with a number of economic indicators. WLS regressions enable the removal of the impact of country size on results, whereas non‐linear modelling allows the possibility of multiple equilibria and different development trajectories to be taken into account. Finally, the employment of various economic‐performance indicators (simple and composite) works as a cross‐check of validity for the results provided.

Determining alarm levels of river floods is considered an effective non-structural measure to prevent and mitigate the damages of flood and inundation. This study aims to propose a holistic approach, a comprehensive review of the factors affecting flooding and flood risk, based on which the water level (WL) is proposed for the flood alarm levels. The corresponding proposed WL to the necessary flood alarm levels is based on observed data, as well as simulated data from statistical methods and hydrological and hydraulic models.

In this paper, the proposed criteria to delineate WLs corresponding to flood alarm levels include flood magnitude; flood derivation and flood duration; flood risks and damage; correlation with neighboring stations; flood characteristics and local characteristics; and other criteria (flood prevention strategy and flood experience).

The paper proposed a synthesis approach to determine flood warning levels in Vietnam. The retrieved levels are the basics to revise the Decision 632/2010 of the Vietnam Government on determining water alarm levels for flood prevention. The study proposes a new flood alarm system including revised flood levels at 115 existing stations and new flood levels at 30 additional stations. The proposed flood warning level can help manage the flooding problem in major river systems that supports flood protection and prevention services in Vietnam.

The paper proposed a novel synthesis approach to flood prevention in Vietnam.

In the finance literature, fitting a cross-sectional regression with (estimated) abnormal returns as the dependent variable and firm-specific variables (e.g. financial ratios) as independent variables has become de rigueur for a publishable event study. In the absence of skewness and/or kurtosis the explanatory variable, the regression design does not exhibit leverage – an issue that has been addressed in the econometrics literature on the finite sample properties of heteroskedastic-consistent (HC) standard errors, but not in the finance literature on event studies. The paper aims to discuss this issue.

In this paper, simulations are designed to evaluate the potential bias in the standard error of the regression coefficient when the regression design includes “points of high leverage” (Chesher and Jewitt, 1987) and heteroskedasticity. The empirical distributions of test statistics are tabulated from ordinary least squares, weighted least squares, and HC standard errors.

None of the test statistics examined in these simulations are uniformly robust with regard to conditional heteroskedasticity when the regression includes “points of high leverage.” In some cases the bias can be quite large: an empirical rejection rate as high as 25 percent for a 5 percent nominal significance level. Further, the bias in OLS HC standard errors may be attenuated but not fully corrected with a “wild bootstrap.”

If the researcher suspects an event-induced increase in return variances, tests for conditional heteroskedasticity should be conducted and the regressor matrix should be evaluated for observations that exhibit a high degree of leverage.

This paper is a modest step toward filling a gap on the finite sample properties of HC standard errors in the event methodology literature.

The purpose of this paper is to examine the factors affecting the academic outcome of real estate students in a specialized Federal University in Nigeria. Furthermore, this paper investigates the phenomenon of publication bias in the extant literature as such evidence poses severe threats to the validity of empirical findings on factors affecting the degree outcome of undergraduate students.

The standard statistical approach adopted was to examine whether the reported coefficient estimates from ten empirical studies (105 observations) are independent of their standard errors by employing both ordinary least squares (OLS) and weighted least squares (WLS). In this paper, this approach enabled evidence of publication bias in the cited literature to be refuted. In addition, data were also collected on the academic measure and demographic information of 449 students who graduated between 2005 and 2011. For the purpose of analysis, the study utilized a stepwise logistic regression technique to examine the factors impacting on the degree outcome of real estate students.

The results of the OLS and WLS regression indicate that there is no significant evidence of any empirical effect of publication bias in the extant literature. The results of the logistic regression also revealed that grade point average, gender differences, prior knowledge of real estate discipline and potential difference in year of enrollment impact on students’ academic performance in terms of their ability to graduate at first attempt. In addition, factors such as age, marital status, high school grade and geopolitical/ethnic background of undergraduate real estate students do not influence their opportunities to graduate at first attempt from the university.

This paper focuses only on one specialized university of technology offering a bachelor’s program in real estate in Nigeria, so as to remove any extraneous factor(s) that could be present in the other institutional settings where students have completed such program. Extending similar study to tertiary institutions in Nigeria that share similar geographical characteristics and institutional settings can produce far-reaching generalization.

This paper contributes to the scanty literature on factors affecting the academic performance of students in an undergraduate real estate program in Nigeria. A scientific element of novelty in this paper is the evidence of the absence of the underlying effect of publication bias in the extant literature on students’ academic outcome in tertiary institutions. Findings from this study serve as the basis for university officers to monitor significant transitions in real estate students’ academic progress, so as to identify those who are unlikely to graduate at first attempt early at the entrant level. Generally, the outcome of this research could provide faculty and admission officers in tertiary institutions with complementary information in arriving at an informed decision in a non-discriminatory admission process.