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The purpose of this paper is to validate an instrument, based on previous research, for measuring procedurally just and unjust police behavior during interactions with citizens.

Data were gathered from September 2015 to January 2016 using systematic social observations in two local police forces in Belgium. A total of 284 full police-citizen interactions were observed. The authors describe and explain how the procedurally (un)just police behavior is measured and discuss existing research on the subject. The authors also test the validity of the instrument and stress the importance of making a distinction between procedurally just and unjust behavior, which has often been overlooked in previous research.

The measurement instrument passed the validity test, except for the procedurally just neutrality sub-index. The findings also confirm that both procedurally just and procedurally unjust police behavior can occur in the same interaction. Moreover, except for the trustworthy sub-indexes, the authors found a stronger negative correlation of procedurally unjust behavior with the citizen’s behavior compared to the strength of the positive correlations of the procedural justice indexes.

The findings confirm a usable measurement instrument for research about procedural justice using systematic social observations. Important improvements were made to instruments that have been utilized in previous research. One of the most important recommendations for future research is to make a distinction between procedurally just and unjust police behavior.

This study is the first in which all four elements of police procedurally just behavior as well as their four procedurally unjust variants were measured using systematic social observations.

The purpose of this paper is to empirically examine the performance of socially responsible stocks portfolio vis-à-vis portfolios of general companies in the Indian stock market.

The study has used absolute rate of return as well as various risk adjusted measures like Sharpe ratio, Treynor ratio, Jensen’s α, Information ratio, Fama’s decomposition measure and dummy regression model to evaluate the performance of various portfolios.

Socially responsible stocks portfolios are found to have lower relative risk despite having higher systematic risk. Further the authors find that during crisis and post-crisis period, socially responsible stocks portfolio generated significantly higher return as compared to other portfolios in the Indian stock market. Environmental, social and governance (ESG) Index and GREENEX Index provided positive net selectivity returns in all the three sub periods, especially during crisis period. GREENEX and ESG outperformed NIFTY and SENSEX even on net selectivity basis. This indicates that the compromise made with respect to diversification by investing in socially responsible stocks portfolios was well rewarded in terms of higher returns in Indian context.

The findings lend support to the case of socially responsible investing (SRI) in India and are relevant for companies, regulators, policy makers and investors at large. Mutual funds and other investment funds should launch schemes which invest in socially responsible stocks so as to provide the benefits of SRI even to small investors in India.

The study contributes to the related literature by analysing the performance of socially responsible stocks portfolios in Indian stock market which is one of the emerging markets.

The purpose of this paper is, to study macroeconomic risk factors driving the expected stock returns of listed private equity (LPE). The authors use LPE indices divided into different styles and regions from January 2004 to December 2016 and a set of country stock indices to estimate the macroeconomic risk profiles and corresponding risk premiums. Using a seemingly unrelated regressions (SUR) model to estimate factor sensitivities, the authors document that LPE indices exhibit stock market βs that are greater than 1. A one-factor asset pricing model using world stock market returns as the only possible risk factor is rejected on the basis of generalized method of moments (GMM) orthogonality conditions. In contrast, using the change in a currency basket, the G-7 industrial production, the G-7 term spread, the G-7 inflation rate and a recently proposed indicator of economic policy uncertainty as additional risk factors, this multifactor model is able to price a cross-section of expected LPE returns. The risk-return profile of LPE differs from country equity indices. Consequently, LPE should be treated as a separate asset class.

Following Ferson and Harvey (1994), the authors use an unconditional asset pricing model to capture the structure of returns across LPE. The authors use 11 LPE indices divided into different styles and regions from January 2004 to December 2016, and a set of country stock indices as spanning assets to estimate the macroeconomic risk profiles and corresponding risk premiums.

Using a seemingly unrelated regressions (SUR) model to estimate factor sensitivities, the authors document that LPE indices exhibit stock market ßs that are greater than 1. The authors estimate a one-factor asset pricing model using world stock market returns as the only possible risk factor by GMM. This model is rejected on the basis of the GMM orthogonality conditions. By contrast, a multifactor model built on the change in a currency basket, the G-7 industrial production, the G-7 term spread, the G-7 inflation rate and a recently proposed indicator of global economic policy uncertainty as additional risk factors is able to price a cross-section of expected LPE returns.

Given data availability, the authors’ sample is strongly influenced by the financial crisis and its aftermath.

Information about the risk profile of LPE is important for asset allocation decisions. In particular, it may help to optimally react to contemporaneous changes in economy-wide risk factors.

To the best of authors’ knowledge, this is the first LPE study which investigates whether a set of macroeconomic factors is actually priced and, therefore, associated with a non-zero risk premium in the cross-section of returns.

The purpose of this paper is to present a more objective evaluation method for a mining area ecological environment. It proposes the weight of indices with respect to the total goal, and provides a new evaluation method which generalizes the weighted‐average method.

First, the authors describe the evaluation grades by fuzzy variables in credibility space, and the degree of an index belonging to a grade is transformed to be the credibility measure of a fuzzy event by the credibility inversion theorem. Second, a new algorithm which generalizes the weighted‐average method is proposed to realize the transformation from the credibility degree of the underlying indices to the credibility degree of the total target.

The method proposed in this paper can obtain the correct results illustrated with a numerical evaluation example. The comparison with two other methods shows that the proposed method has stronger classification ability.

The new method presented in this paper generalizes the weighted‐average method, and provides methods for other evaluation systems with a hierarchical structure.

The purpose of this paper is to construct a novel grey incidence evaluation model to investigate a scientific and effective evaluation system of regional road traffic safety.

To provide a method for the evaluation of regional road traffic safety, the grey incidence feature vector method is employed to construct the evaluation index system for regional road traffic safety and then the index weights are calculated with Shannon entropy method. In this paper, the grey incidence feature vector method and grey incidence analysis are utilised to construct evaluation index systems for regional road traffic safety and determine the index weights. Then a grey incidence-ideal point method is used to establish a novel evaluation model for regional road traffic safety. To thoroughly investigate the road traffic safety in one region, the data of 13 cities in Jiangsu province is gathered, using the grey clustering and grey incidence-ideal point method to obtain the ranking results of the 13 cities.

The results provide a basic analysis of the present situation and show the differences for these regions based on the proposed model, according to which several solutions are proposed, aiming to improve regional road traffic safety situation.

The method exposed in the paper can be used to deal with the problems of the evaluation of regional road traffic safety.

The paper succeeds in understanding the status quo and implementing effective road traffic safety management based on the proposed model.

The increasing need to access and elaborate dynamic and heterogeneous information sources distributed over the Internet calls for new models and paradigms for application design and development. The mobile agent paradigm promotes the design of applications where agents roam through Internet sites to locally access and elaborate information and resources, possibly co‐operating with each other. Focuses on mobile agent co‐ordination, and presents the TuCSoN co‐ordination model for Internet applications based on mobile information agents. TuCSoN exploits a notion of local tuple‐based interaction space, called a tuple centre. A tuple centre is a tuple space enhanced with the capability of programming its behaviour in response to communication events. This enables properties to be embedded into the interaction space, and a mobile agent to be designed independently of the peculiarities of the information sources. Several issues critical to Internet applications can then be charged on tuple centres transparently to agents. The effectiveness of the TuCSoN model is first shown by means of an application example in the area of Internet information retrieval, then discussed in the context of workflow management and electronic commerce.

This paper aims to build an improved grey panel clustering evaluation model and evaluate the comprehensive development potential of industrial economy, society and ecological environment in the Yangtze River Economic Belt of China. The purpose of this study is to provide some theoretical basis and tool support for management departments and relevant researchers engaged in industrial sustainable development.

This study uses the driving force pressure state impact response analysis framework to build a comprehensive evaluation index system. Based on the center point triangle whitening weight function, it classifies the panel grey clustering of improvement time and index weight.

The results show that there are great differences in the level of industrial ecological development in different regions of the Yangtze River Economic Belt, which further illustrates the scientificity and rationality of the evaluation method proposed in this paper.

Due to the industrial ecological development is in a constantly changing state, and the information is uncertain. Whitening weight function is introduced to represent the complete information of relevant data. The industrial ecological evaluation involves a comprehensive complex system, which belongs to the panel data analysis problem. The improved grey panel clustering evaluation model is applied to grade the industrial ecological development level of the Yangtze River Economic Belt. The results have important guiding significance for the balanced development of industrial ecology in the region.

Due to the industrial ecological development is in a constantly changing state, and the information is uncertain. Whitening weight function is introduced to represent the complete information of relevant data. The industrial ecological evaluation involves a comprehensive complex system, which belongs to the panel data analysis problem. In order to improve the effectiveness of industrial ecological evaluation, the improved grey panel clustering evaluation model is applied to grade the industrial ecological development level of the Yangtze River Economic Belt. The results have important guiding significance for the balanced development of industrial ecology in the region.

the new model proposed in this paper complements and improves the grey clustering analysis theory of panel data, that is, aiming at the subjective limitation of using time degree to determine time weight in panel grey clustering, a comprehensive theoretical method for determining time weight is creatively proposed. Combining the DPSIR (Driving force-Pressure-State-Influence-Response) model model with ecological development, a comprehensive evaluation model is constructed to make the evaluation results more authentic and comprehensive.

The purpose of this paper is to present an overview of the concepts of corporate social responsibility (CSR) in banks and integrated reporting, a review of the literature on the subject and the author’s own research results. The author’s research was designed to identify information on CSR included in the management commentaries of selected banks operating in Poland and to evaluate the disclosures with regard to their quality, diversity and the ways they change over time.

The author formulates three hypotheses relating to the social and environmental disclosures and verifies them using a disclosure index approach based on the analysis of 84 management commentaries of 12 banks operating in Poland in 2005-2011.

Banks tend to include CSR disclosures in the management commentary. They present CSR information in a diverse manner, focusing mainly on community involvement. The quality of CSR disclosures in 2011 was higher as compared with 2005. None of the banks in the sample produced integrated reports.

The study concentrates on CSR disclosures only in management commentaries and relies on the review of information presented by a limited number of banks.

The study contributes to the scarce literature on social responsibility disclosures by financial institutions in Central and Eastern Europe; it also discusses a new integrated reporting model.

The purpose of this study is to examine the usage of non-financial information related to corporate social responsibility (CSR) issues from the perspective of sell-side analysts (SSAs) and buy-side analysts (BSAs) employed in Poland-based financial institutions.

The authors conducted a survey among financial analysts with the use of the computer-assisted telephone interview (CATI) method and an online questionnaire. The adopted methods included purposeful, quota sampling and snowball sampling.

Results indicate that financial analysts make use of CSR disclosures very rarely and attribute little importance to such information. Despite the limited use of CSR information and negative assessments of its quality, respondents are in favor of making a more frequent use of CSR disclosures. Finally, except for an analyst’s attitude toward the “comparability in time” information characteristic, results do not indicate any significant differences between SSAs’ and BSAs’ responses.

The limited number of questionnaires prevented the use of more sophisticated statistical methods and the formulation of conclusions that could apply to the entire population. In addition, although the adopted CATI method provides a number of advantages, it also has its limitations – interviews had limited time and the questions along with the answers had to take into account the respondents’ limited perception ability.

The results of this study suggest that CSR disclosures have limited usage for financial analysts, at least in the Polish context. Further, not only do respondents rarely make use of CSR disclosures but they also give low assessments to their quality. This implies that the concept of CSR remains relatively far from becoming a priority; hence, some measures and incentives may be necessary.

The paper adds to a relatively small number of studies that have dealt with the issue of non-financial information and its usefulness for SSAs and BSAs in Central and Eastern Europe.

The study aims to analyze the effects of the Covid-19 pandemic on house prices.

The authors start by discussing the possibility that house price indexes may not fully incorporate the effects of the pandemic as of yet. Against the background of the pandemic, the authors then analyze economic and behavioral effects affecting house prices. The authors also discuss how the linkages between tourism and house prices have been affected. The authors further present evidence of an emerging shift in preferences from urban locations to more peripheral ones.

The authors report variance in the evolution of house prices across countries at the onset of the pandemic, with locations depending heavily on tourism showing slower price appreciation while appreciation has firmed in other places. The authors argue that the resilience of house prices is not only because of the low-interest rate environment and government efforts to support firms and households, but also behavioral factors. In some locations, the price of condominiums has declined relative to the price of detached houses. This could indicate that wealthier households are seeking more space and larger units as a result of the crisis. There is also evidence of a downward pressure on rents, leading to increased price–rent ratios in the USA.

By considering both economic and behavioral factors, this paper provides for a better understanding of the resilience and realignment of house prices at the onset of the Covid-19 pandemic.