Application of bootstrap re-sampling method in statistical measurement of sustainability

Sustainability is of essential interest for many organizations and is defined as the ability to maintain existing resources at a certain rate or level when encountered with barriers. Factors affecting sustainability are categorized as enablers (capacities) and barriers (challenges) that have positive and negative effects on sustainability, respectively. To evaluate the status of sustainability, organizations need a measurement method to account for all the aspects of the sustainability classified into social, economic, and environmental tiers. Previously many researchers have provided indexes and measure specific to the studied field, which is not applicable to other areas. Furthermore, the proposed methods fail to cover all the aspects of sustainability. This study investigates a statistical method to measure the sustainability and the application of the bootstrap re-sampling method in order to overcome the problem with normality assumption when the sample size is not large enough and thus develop a more realistic stochastic model. The Bootstrap re-sampling method enables the unbiased estimation of population parameters such as mean and standard deviation. The proposed method is evaluated by comparing its results with those found in the literature.     

Enhancing environmental information transparency through corporate social responsibility reporting regulation

This research aims to contribute to the scientific debate about the lack of interlinkages between mandatory non-financial reporting and sustainable business models. For our purposes, a counter-accounting analysis was conducted on the non-financial reports of a sample of 145 Italian firms interested by the Directive 2014/95/EU effects. Specifically, the study adopts an empirical approach to evaluate environmental information transparency, which represents one of the main critical issues concerning the non-financial declarations prepared by European Italian Public Interest Entities (PIEs) to comply with Directive 2014/95/EU. The results highlight that corporate governance and report characteristics affect environmental transparency. Furthermore, the results confirm the overall attitude to avoid the disclosure of unfavourable or unavailable environmental information through impression management strategies. Finally, the analysis underlines the opportunities for policymakers to rethink mandatory non-financial reporting to sustain the ecological transition of European PIEs.     

Preventing motor vehicle crash injuries and deaths: science vs. folklore lessons from history

Abstract

Not long after the beginnings of motorization in the early 1900s, deaths and injuries from motor vehicle crashes became a problem in a number of high-income-countries (HIC)s, especially the United States. With the biggest problem the US led early efforts to address this issue, and for six decades these efforts were based on folklore (ie a body of widely held but false or unsubstantiated beliefs). They were not evaluated, but clearly were unsuccessful as crash deaths and injuries continued to rise. It was not until the 1970s that a broader range of countermeasures began to be adopted and was scientifically evaluated, and as a result, crash deaths and injuries declined. This history has important lessons today for many low-and-middle-income countries that have growing numbers of motor vehicle crash deaths and injuries, many of which are pedestrians and motorcyclists. This is because there continue to be advocates for many of the failed approaches (especially educational) that dominated the early efforts in HICs.     

Determinants of spectator no-show behaviour: first empirical evidence from the German Bundesliga

The analysis of stadium attendance demand has a long tradition in the economic literature. However, despite its evident merits, this previous research has been critiqued at several levels, in particular for relying on a suboptimal demand proxy, i.e. published attendance data. In this short note, we address these shortcomings by exploring a highly unique data set containing official information on spectators’ decisions of whether or not to physically attend 704 German football Bundesliga games played between August 2014 and January 2017.     

采用一维物理光学法的天线罩瞄准误差补偿

针对雷达天线罩瞄准误差的补偿问题，提出了一种适用于各向同性的天线罩瞄准误差修正方法。构建了基于一维物理光学法的天线罩瞄准误差的数学模型，推导了雷达导引头测量目标角度和角速度的误差修正公式。试验结果表明，该方法有效降低了天线罩瞄准误差对目标角速度性能的影响。     

Twenty-five years of business systems research and lessons for international business studies

Since 1992, the national business systems (NBS) approach has been increasingly used to analyse not only firm characteristics, structures and strategies within NBS, but also the nature of international business and its interactions with both national and transnational institutions. In reviewing 25 years of NBS literature, we heed calls in IB journals urging researchers to use NBS notions and findings in IB research. Our systematic review of 96 articles analyses the patterns and contributions of NBS literature, revealing four thematic junctures: (1) comparative business systems, (2) firm internationalisation and the management/organisation inside MNCs, (3) the role of internationalisation in the development of organisational capabilities and innovation and (4) the emergence of transnational communities in and across firms and societies. Themes are described in terms of (a) the research questions (RQ) they focus on, (b) how NBS approach investigates the RQ and what are the major findings, (c) how IB frames and approaches the same RQ, (d) how does the NBS approach extend the perspectives of IB and (e) what are the problems faced by NBS in terms of developing further insights into the RQ. Our review contributes to the recent endeavour of IB research to institutionalism, encouraging a productive dialogue between IB and NBS research.     

乘积型指数滤波器及其在多目标时延估计中的应用

指数滤波器是一类新构造出来的输出信噪比和目标时延分辨力随指数变化的滤波器，该滤波器在损失一定输出信噪比的前提下可以有效提高目标时延分辨力，从而提高目标时延估计精度,但仅采用单个指数滤波器仍存在输出信噪比和目标时延分辨力均达不到实际需求的情况。在乘积型高阶模糊函数乘积运算的启发下，在指数滤波器的基础上提出了一种新的乘积型指数滤波器，并分析了该乘积型指数滤波器的输出信噪比及目标时延分辨力等性能。仿真实验表明，所提的乘积型指数滤波器在低信噪比情况下可以更有效提高多目标时延估计精度，且算法简单易于实现，适用于背景复杂的多目标参数估计任务。     

Measuring customer experience in service: A systematic review

The aim of this systematic review is to identify how customer experience in the service sector has been measured in relevant publications in the marketing field. A sample of 33 papers was collected from two electronic databases—the Web of Science (Thomson Reuters) and Scopus (Elsevier)—covering a large number of publications. After analyzing the articles and reviewing the customer experience literature, the following are our main contributions: (i) clarification of the concepts that appear in the literature review of customer experience in the service sector; (ii) classification of the variables, scales, and constructs related to customer experience in service; (iii) demonstration of the service experience as the preponderant construct that is used to measure customer experience in service; and (iv) proposal of a new dimension—the concept of ‘pre-experience’—to measure customer experience in service. These contributions can provide a more solid basis for measuring customer experience in service.     

Can welfare be measured with a preference-satisfaction index?

Welfare in economics is generally conceived of in terms of the satisfaction of preferences, but a general, comparable index measure of welfare is generally not taken to be possible. In recent years, in response to the usage of measures of subjective well-being as indices of welfare in economics, a number of economists have started to develop measures of welfare based on preference-satisfaction. In order to evaluate the success of such measures, I formulate criteria of policy-relevance and theoretical success in the context of preference-satisfaction measures of welfare. I present a detailed case study of the methodological choices put forward in a prominent generalized proposal for measuring welfare through preferences recently published in the American Economic Review. I contrast this with an alternative welfare measure which also uses preferences to weight aspects of welfare: the ICECAP-A measure. I assess the methodology of both approaches in detail and argue that the two goals of a preference measure of welfare can only be satisfied at the expense of making a measure prohibitively costly.     

Transport infrastructure equities in mixed-asset portfolios: estimating risk with a Garch-Copula CVaR model

Transport infrastructure is an important subsector within infrastructure, but knowledge of its equities in terms of risk-return characteristics and contribution to portfolio performance is still limited. This study assesses the subsector individually and in a multi-asset, index-based portfolio. In doing so, we apply a t-Copula-based Conditional Value-at-Risk model to simulate risk and returns. Our findings reveal that the subsector has a relatively low dependency on other equities, performs like other alternative asset classes such as general real estate, and does not grant significant risk diversification benefits for mainstream institutional investors such as pension funds. Investors aiming for higher target returns may however assign substantial weights to transport infrastructure, supporting our conjecture that it does not share the same asset class characteristics as general infrastructure. By contrasting Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) scores for both the mean-variance framework and the t-Copula simulation, we further document the limitations of traditional VaR approaches. Hence, this study’s results support the use of risk assessment tools that incorporate non-normal distributions to represent multivariate dependence structures.