This study endorses the use of data envelopment analysis, which uses benefit-of-the-doubt weighting to evaluate the social, economic and overall performance of social enterprises. This methodology is especially useful for creating composite indicators based on multiple outputs expressed in different measurement units, and allows for enterprise-specific weighting of the different objectives. Applying this methodology on a unique longitudinal dataset of Flemish sheltered workshops suggests that social enterprises may face different types of mission drift. Further, our results show (...) that top-performing social enterprises are more economically and socially efficient than low performers. These top performers also have a stronger economic orientation, which sheds new light on the balance between social and economic orientations in social enterprises. (shrink)

In the era of the global village, crowd sourcing as a new model of service outsourcing is increasingly being valued by all walks of life. This study uses the data envelopment analysis method to explain the crowd sourcing competitiveness of service outsourcing base cities by using input-output efficiency. The crowd sourcing competitiveness among crowd sourcing base cities is organized and analyzed by collating and analyzing the data of 21 service outsourcing base cities in China from 2016 (...) to 2019. The results show that there is no significant difference in the competitiveness of 21 service outsourcing, the overall trend is that the competitiveness of crowd sourcing is not strong, the match between input and output is not high. Comparatively speaking, Beijing, Shanghai, Nanjing, Hangzhou, Suzhou and Wuxi are more competitive in crowd sourcing. Combining with the reality of China's economic development, taking the road of crowd sourcing with Chinese characteristics is a good choice for the development of China's crowd sourcing industry. (shrink)

We employ data envelopment analysis on a series of experiments performed in Fermilab, one of the major high-energy physics laboratories in the world, in order to test their efficiency (as measured by publication and citation rates) in terms of variations of team size, number of teams per experiment, and completion time. We present the results and analyze them, focusing in particular on inherent connections between quantitative team composition and diversity, and discuss them in relation to other factors (...) contributing to scientific production in a wider sense. Our results concur with the results of other studies across the sciences showing that smaller research teams are more productive, and with the conjecture on curvilinear dependence of team size and efficiency. (shrink)

This article presents a study of corporate-stakeholder relationships using an empirical technique called Data Envelopment Analysis (DEA) to assess company "best practices" with respect to five primary stakeholders at an industry level of analysis. Five key stakeholder domains are considered: community relations, employee relations, environment, customer (product category), and stockholders (financial performance). These data reflect the relationships between companies and these five primary stakeholders; these relationships are considered to be important elements of corporate social performance. (...) About 15% of companies, on average, are found to be operating at the multidimensional "best practices frontier" that DEA establishes. Differences in treatment of stakeholders within industries and between industries are observed. (shrink)

With the rapid and unbalanced development of industry, a large amount of cultivated land is converted into industrial land with lower efficiency. The existing research is extensively concerned with industrial land use and industrial development in isolation, but little attention has been paid to the relationship between them. To help address this gap, the paper creates a new efficiency measure method for industrial land use combining Subvector Data Envelope Analysis with spatial analysis approach. The proposed model has (...) been verified by using the industrial land use data of 30 Chinese provinces from 2001 to 2013. The spatial autocorrelation relationship between industrial development and industrial land use efficiency is explored. Furthermore, this paper examines the effects of industrial development on industrial land use efficiency by spatial panel data model. The results indicate that the industrial land use efficiency and the industrial development level in the provinces of eastern region are higher than those of the western region. The spatial distribution of industrial land use efficiency shows remarkable positive spatial autocorrelation. However, the level of industrial development has obvious negative spatial autocorrelation since 2009. The improvement of industrial development has a significant positive impact on the industrial land use efficiency. (shrink)

One of the mathematical programming techniques is data envelopment analysis, which is used for evaluating the efficiency of a set of similar decision-making units. Fixed resource allocation and target setting with the help of DEA is a subject that has gained much attention from researchers. A new model was proposed by determining a common set of weights. All DMUs were involved with the aim of achieving higher efficiency in every DMU after the procedure. The minimum resources and (...) targets allocated to each DMU were commensurate to the efficiency of that DMU and the share of DMU in the input resources and the output productions. To examine the proposed method, other methods in the DEA literature were examined as well, and then, the efficiency of the method was demonstrated through a numerical example. (shrink)

The problem of determining an optimal benchmark to inefficient decision-making units is an important issue in the field of performance analysis. Previous methods for determining the projection points of inefficient DMUs have only focused on one objective and other features have been ignored. This paper attempts to determine the best projection point for each DMU when the inputs and outputs data are in stochastic form and presents an alternative definition for the best projection by considering three main aspects: (...) technical efficient, minimal cost, and maximal revenue as much as possible. Considering the important role of the electricity industry in the economic growth of each country, a practical example has been implemented on 16 regional electricity companies in Iran in 9 consecutive periods. The efficiency score along with the projection points of the three technical models ), cost, and stochastic revenue are compared with the projection point obtained from the model presented in this article, which simultaneously meets these three objectives, showing the improvement of companies’ performance. (shrink)

This paper uses two techniques to build a socially responsible portfolio of U.S. equities and examines prospective performance using publicly available data. The first technique eliminates stocks from consideration using categorical exclusions with a restrictive Environment, Social and Governance screen. The paper shows that stocks surviving the screen have a significantly higher average projected Value Line alpha and are more likely to have a Morningstar 5-star rating. Using categorical exclusions, however, introduces a sector bias in that the ESG screen (...) is more likely to restrict stocks from the manufacturing sector than the service sector. The second technique does not introduce a sector bias because it uses a best-in-class optimization approach in place of screening. The paper introduces a linear programming model called Data Envelopment Analysis to the application of SRI portfolio development to find the best financially and socially performing companies within each industry sector. When compared to a categorical exclusions portfolio, a DEA portfolio is rated significantly higher by Morningstar and Value Line. Depending on the specific needs of a socially responsible investor, the DEA technique could be a better tool in developing a financially and socially balanced equity portfolio. (shrink)

Business Ethics, the Environment & Responsibility, Volume 31, Issue 2, Page 398-418, April 2022.

Industry sustainability plays a vital role in shaping the environment for cultural and creative business development. However, considering the influence of the external environment and random factors on the technical efficiency of cultural and creative industries with the inherent defects of the traditional data envelopment analysis model; this manuscript analyzed the operating efficiency of 56 cultural and creative enterprises using the three-stage DEA model from 2012 to 2018. An analysis of the results shows that differences in (...) efficiency exist between stage one and stage three DEA. Furthermore, the environmental elements and statistical noise measured by the stochastic frontier analysis in stage two reveal positive and negative influences on the creative cultural enterprises at different stages. As a result, the overall efficiency of the listed cultural and creative industries was revealed to be low in China. Finally, this study suggested effective countermeasures and recommendations for better-operating efficiency systems for cultural and creative enterprises. (shrink)

In terms of scenic marketing, big data research also plays an important role in the precise marketing of scenic spots. This paper has focused on the big data related to scenic spots as the research object, explores the relationship between various subdivision big data and the number of tourists in scenic spots, and investigates the difference and influence of the consumption behavior of the secondary consumption items in the scenic area, to find the potential of the scenic (...) area’s business growth and to promote the continuous and stable growth of the scenic area’s sales and tourism economy. Using the relevant theories and analysis methods, such as consumer behavior, big data, and tourism consumer behavior, the content mainly focuses on the establishment of the analysis model of the number of tourists in the scenic spot, the data collection, the estimation of the model parameters, the various types of big data, the calculation of the contribution rate of the data to the number of tourists in the scenic spot, and the difference analysis of the secondary consumption items of different types of tourists in the scenic spot. Results show that a multi-objective analysis model is established based on the relevant econometric theories, and an optimization plan is proposed after the multicollinearity diagnosis of the model; to establish a data envelopment analysis model of the difference and influence of different types of tourists’ consumption behavior in scenic spots and study the consumption behavior characteristics of different types of tourists when they purchase secondary consumption items in scenic spots; the econometric model is used to analyze the big data, adjust the linear relationship of some variables, then adopt the method of gradually adding variables combined with the consumer theory, and finally determine the number of daily tourists as the explained variable, the number of internet protocol, Baidu index, and the virtual value of the weekend, dummy variables for variables, bounce rate, and air pollution as explanatory variables. (shrink)

The sudden outbreak of coronavirus disease 2019 has caused a huge impact on the Chinese residents' health and economic level. In the pandemic background, the country and its institutions have introduced pandemic-related insurance to stabilize the national situation. At this stage, insurance has played an increasingly important role in social life. With the popularization of insurance, the idea of buying insurance to avoid risk has gradually become popular among people. Among them, the New Rural Cooperative Medical System has been farmers' (...) common choice. The NRCMS, a mutual aid system created by farmers spontaneously in the country, plays a great role in guaranteeing farmers access to basic health services, alleviating poverty caused by disease and returning to poverty due to disease, and promoting poverty alleviation and rural revitalization. Given this backdrop, we study the efficiency of the NRCMS that can effectively promote poverty alleviation and rural revitalization and ensure the people's happy life. Implementing the Data Envelopment Analysis, we find that technological progress is one of the main factors influencing the efficiency of the NRCMS. Therefore, it is important to improve the technology for providing the efficiency of the NRCMS and promoting the happiness of the society. (shrink)

Data envelopment analysis is a popular mathematical tool for analyzing the relative efficiency of homogenous decision-making units. However, the existing DEA models cannot tackle the newly confronted applications with imprecise and negative data as well as undesirable outputs simultaneously. Thus, we introduce undesirable outputs into modified slack-based measure model and propose an interval-modified slack-based measure model, which extends the application of interval DEA in fields that concern with less undesirable outputs. The novelties of the model are (...) that it considers the undesirable outputs while dealing with imprecise and negative data, and it is slack-based. Furthermore, the model with undesirable outputs is proven translation-invariant and unit-invariant. Moreover, a numerical example is provided to illustrate the changes of the lower and upper bounds of the efficiency score after considering the undesirable outputs. The empirical results show that, without considering undesirable outputs, most of the lower bounds of the efficiency scores will be overestimated when the DMUs are weakly efficient and inefficient. The upper bound will also change after considering undesirable outputs when the DMU is inefficient. Finally, an improved degree of preference approach is introduced to rank the DMUs. (shrink)

As more objections have been raised against grant peer-review for being costly and time-consuming, the legitimate question arises whether machine learning algorithms could help assess the epistemic efficiency of the proposed projects. As a case study, we investigated whether project efficiency in high energy physics can be algorithmically predicted based on the data from the proposal. To analyze the potential of algorithmic prediction in HEP, we conducted a study on data about the structure and outcomes of HEP experiments (...) with the goal of predicting their efficiency. In the first step, we assessed the project efficiency using Data Envelopment Analysis of 67 experiments conducted in the HEP laboratory Fermilab. In the second step, we employed predictive algorithms to detect which team structures maximize the epistemic performance of an expert group. For this purpose, we used the efficiency scores obtained by DEA and applied predictive algorithms – lasso and ridge linear regression, neural network, and gradient boosted trees – on them. The results of the predictive analyses show moderately high accuracy, indicating that they can be beneficial as one of the steps in grant review. Still, their applicability in practice should be approached with caution. Some of the limitations of the algorithmic approach are the unreliability of citation patterns, unobservable variables that influence scientific success, and the potential predictability of the model. (shrink)

Os Objetivos de Desenvolvimento Sustentável (ODS) abrangem diversas questões socioambientais e são aplicáveis a todos os países. O ODS 15, Vida Terrestre, visa proteger os ecossistemas terrestres, conservar a biodiversidade e reduzir a perda de biodiversidade, e o estado do Paraná é um dos estados com uma das maiores proporções de área de remanescentes florestais do Brasil e conta com uma política de preservação ambiental. Em vista disso, o estudo tem como objetivo analisar a eficiência dos municípios paranaenses no atendimento (...) ao Objetivo do Desenvolvimento Sustentável 15 - Proteger a vida terrestre. Para isso, foi utilizada a abordagem da Análise Envoltória de Dados (DEA – Data Envelopment Analysis), tendo como input o Imposto sobre Circulação de Mercadorias e Serviços Ecológico (ICMS Ecológico) e como output o percentual de áreas florestais dos municípios. Os resultados apontaram que os municípios Campo do Tenente, Céu Azul, Guaratuba, Imbituva, Ipiranga, Mirador, Morretes e Teixeira Soares foram eficientes, tendo como característica principal, a presença de parques ecológicos. Por outro lado, foi observado que as regiões mais industrializadas e urbanas concentraram mais municípios com ineficiência forte. Além disso, os municípios Piraquara, Pinhais, Campo Magro e Quatro Barras apresentaram os maiores excessos no recebimento de recursos do ICMS Ecológico. Enquanto os municípios de Pinhais, Curitiba, São Jorge do Patrocínio, Altônia, São Pedro do Paraná e Quatiguá apresentaram as maiores necessidades relativas de aumentar as áreas remanescentes florestais. (shrink)

With the rapid growth of information technology and sports, analyzing sports information has become an increasingly challenging issue. Sports big data come from the Internet and show a rapid growth trend. Sports big data contain rich information such as athletes, coaches, athletics, and swimming. Nowadays, various sports data can be easily accessed, and amazing data analysis technologies have been developed, which enable us to further explore the value behind these data. In this paper, we (...) first introduce the background of sports big data. Secondly, we review sports big data management such as sports big data acquisition, sports big data labeling, and improvement of existing data. Thirdly, we show sports data analysis methods, including statistical analysis, sports social network analysis, and sports big data analysis service platform. Furthermore, we describe the sports big data applications such as evaluation and prediction. Finally, we investigate representative research issues in sports big data areas, including predicting the athletes’ performance in the knowledge graph, finding a rising star of sports, unified sports big data platform, open sports big data, and privacy protections. This paper should help the researchers obtaining a broader understanding of sports big data and provide some potential research directions. (shrink)

Doctoral graduates in philosophy are an excellent source of information about the discipline: they are at the cutting edge of research trends, have an inside view of researchfocused departments, and their employment prospects provide early insights on the future health of the discipline. We report on the results of a survey sent to recent PhD graduates and current students, as well as data gathering efforts by Academic Placement Data and Analysis that have taken place over the past (...) ten years. In this report we especially focus on demographic representation, program ratings, academic job placement, and non-academic careers. (shrink)

Academic Placement Data and Analysis (APDA) has released its complete 2017 Final Report, an 81-page document that collects data on PhD-granting philosophy programs (including ratings by former students, placement rates, and diversity) and the discipline as a whole (including hiring networks, placement maps, cluster analyses of programs, job descriptions, non-academic hiring). The report was created by Carolyn Dicey Jennings, Patrice Cobb, Pablo Contreras Kallens, and Angelo Kyrilov, all of University of California, Merced. (from Daily Nous).

As Social Economy financial institutions, credit unions have traditionally been considered less efficient than traditional banking entities. However, like banks and savings banks, they have to be as efficient and competitive as possible to survive in today’s business environment, especially at times of crisis. To date, there have been very few studies on their efficiency and practically none for the crisis period. Moreover, almost all the existing studies assess only financial efficiency, without considering their social function. This study examines the (...) levels of both financial and social efficiency in Spanish credit unions as well as their main determinants during the recent crisis. We apply the two-stage double bootstrap data envelopment analysis methodology based on panel data corresponding to all the credit unions active in Spain between 2008 and 2013. The empirical results indicate that financial and social efficiency achieved an acceptable level, although on average the former was slightly greater than the latter. We also find that both age and merger and acquisition activity were positively influential on the financial efficiency of credit unions but had a significant negative effect on their social efficiency. Moreover, the regional location of such entities and the financial crisis were also crucial determinants of both types of efficiency. Our findings are therefore useful for all the stakeholders of credit unions to know if these entities have been efficient according to a double bottom line accounting in the crisis period and hence to maintain successful social management that is compatible with satisfactory financial efficiency. (shrink)

Prior research suggests that participating in corporate social responsibility (CSR) activities can lead to higher future productivity. However, the empirical evidence is still scarce. The purpose of this study is to examine the relationship between CSR and future firm productivity in the U.S. chemical industry. Specifically, this study examines the relationship between CSR in year t and firm productivity in year (t + 1), (t + 2), and (t + 3). We use Data Envelopment Analysis, a non-parametric (...) method, to measure firm productivity. Results from the regression analysis support a significantly positive relationship between CSR and future firm productivity, suggesting that CSR can lead to higher productivity in the chemical industry. The findings add to the validity of the proposition in prior research. (shrink)

As Social Economy financial institutions, credit unions have traditionally been considered less efficient than traditional banking entities. However, like banks and savings banks, they have to be as efficient and competitive as possible to survive in today’s business environment, especially at times of crisis. To date, there have been very few studies on their efficiency and practically none for the crisis period. Moreover, almost all the existing studies assess only financial efficiency, without considering their social function. This study examines the (...) levels of both financial and social efficiency in Spanish credit unions as well as their main determinants during the recent crisis. We apply the two-stage double bootstrap data envelopment analysis methodology based on panel data corresponding to all the credit unions active in Spain between 2008 and 2013. The empirical results indicate that financial and social efficiency achieved an acceptable level, although on average the former was slightly greater than the latter. We also find that both age and merger and acquisition activity were positively influential on the financial efficiency of credit unions but had a significant negative effect on their social efficiency. Moreover, the regional location of such entities and the financial crisis were also crucial determinants of both types of efficiency. Our findings are therefore useful for all the stakeholders of credit unions to know if these entities have been efficient according to a double bottom line accounting in the crisis period and hence to maintain successful social management that is compatible with satisfactory financial efficiency. (shrink)

BackgroundCare.data was a programme of work led by NHS England for the extraction of patient-identifiable and coded information from general practitioner records for secondary uses. This study analyses the forms which enabled patients to opt out.MethodsTheoretical sampling and summative content analysis were used to collect and analyse dissent forms used by patients to opt out from care.data. Domains included basic information about the programme, types of objections and personal details required for identification purposes.ResultsOne hundred opt-out forms were (...) analysed. Fifty-four forms mentioned that this programme was run by NHS England. 81 forms provided two types of objections to data-sharing, and 15 provided only one objection. Only 26 forms mentioned that direct care would not be affected and 32 that patients maintain their right to opt back anytime. All but one of the opt-out forms we reviewed requested the name of the person wishing to opt out. 94 required a date of birth and 33 an NHS number. 82 required an address, 42 a telephone number and 7 an email address.ConclusionsNumbers of patients opting out should be treated with caution, because the variability of information provided and the varied options for dissent may have caused confusion among patients. To ensure that dissent is in accordance with individual preferences and moral values, we recommend that well-designed information material and standardised opt-out forms be developed for such data-sharing initiatives. (shrink)

Business orientation toward sustainable development goals and the circular economy are relevant research topics today in business theory and practice. The waste recycling sector is a key industry in the circular economy framework for promoting clean production and environmental sustainability. This study analyzes business performance in the recycling sector, focusing on efficiency indicators. The associations between firm efficiency and risk variables were also evaluated. The study goes through several methodological stages, including a Data Envelopment Analysis (DEA) multistage (...) method and multivariate modeling: tobit regression, bootstrap models, and generalized method of moments (GMM). The main results indicate that the average efficiency of waste recycling firms is at a medium level. Large-sized firms achieve higher levels of efficiency than medium-sized and small firms, supporting the economies of scale hypothesis. The evidence also suggests that risk variables (rating score and Zscore) and capital structure are key determinants of firm efficiency in the waste recycling industry. (shrink)

Academic Placement Data and Analysis (APDA), a project funded by the American Philosophical Association (APA) and headed by Carolyn Dicey Jennings (UC Merced), aims “to make information on academic job placement useful to prospective graduate students in philosophy.” The project has just been updated to include new data, which Professor Jennings describes in a post at New APPS. She also announces a new interactive data tool with which one can sift through and sort information. (from Daily (...) Nous). (shrink)

This Differential Emotions Scale (DES) is an objective pencil-and-paper instrument designed to measure the subjective-experience components of the fundamental emotions, based on the assumption that mood states involved a characteristic pattern. Following Boyle (Boyle, G.J. Reliability and validity of Izard's Differential Emotions Scale, Personality, 56, pp. 747-750, 1984), the present paper reports a repeated-measure multiple discriminant function analysis for individual items across raters. At least, two-thirds of the DES items are sensitive indicators of the different mood states, however, the (...) construct validity of the subscales is not clear. In particular, the profiles for the South African participants indicated that there is need for improving the construct validity and retest reliability of DES in order to be useful in applied psychological contexts in non-Western nations. (shrink)

Motivated by the disproportionately high incidence of fraudulent financial reporting in the IT sector where technological capability is a major source of competitive advantage, this study investigates the possible relationship between technological capability and fraud probability in the IT sector. Technological capability is measured by a firm’s technical efficiency relative to peers in transforming cumulative R&D resources into innovative output, which is a source of competitive advantage, according to the resource-based view of the firm. Technical efficiency is estimated via (...) class='Hi'>data envelopment analysis. A sample of fraud firms taken from Accounting and Auditing Enforcement Releases is matched with control samples of non-fraud firms. Consistent with the RBV, technological capability is found to have a negative and economically significant effect on fraud probability. Moreover, fraud probability is insignificantly associated with the scale efficiency of innovative activities, as investment in R&D resources per se is not a source of sustainable competitive advantage. (shrink)

The implementation of the rural revitalization strategy can effectively inherit the excellent traditional Chinese culture and facilitate the comprehensive development of the cultural industry. At present, China is promoting the transformation and upgrading of its industrial structure. The criterion for measuring the “cultural soft power” of a country or region is the competitiveness of its cultural industry. The cultural industry has grown rapidly in recent years, and the overall economic benefits of the industry have also improved, effectively alleviating the employment (...) pressure across the country. However, there are still many problems. How to accurately measure the level of competitiveness of the regional cultural industry and enhance its competitiveness is the first problem in the development of the cultural industry. It finds out the main factors that affect the competitiveness of the cultural industry in the context of rural revitalization strategy using the relevant theories of cultural industry and industrial competitiveness. Besides, the evaluation index system of cultural industry competitiveness is constructed from the perspective of the system. The projection pursuit model and data envelopment analysis model are established based on the genetic algorithm. The model is used to carry out empirical research on the competitiveness level of cultural industry in a region, and conclusions are drawn. The average projected value of the base competitiveness in the region exceeds 0.8. The average projected value of dominant competitiveness exceeds 0.7. The average projected value of potential competitiveness exceeds 1.1. This research proposes corresponding suggestions for the problems in the current growth of the cultural industry in this region through the competitiveness of this region and the level of other areas. This study can also provide some help for the in-depth study of the Chinese cultural industry. (shrink)

Poverty alleviation through tourism is an important way for China to achieve targeted poverty alleviation and win the battle of poverty alleviation. As a region with deep poverty and great difficulty in poverty alleviation, whether tourism development has injected key impetus into ethnic minority areas needs to be tested by both qualitative analysis and quantitative measurement. This paper takes eight ethnic provinces in China as an example to conduct an empirical study. Based on the Data Envelopment (...) class='Hi'>Analysis -BCC model and Malmquist index, it evaluates the tourism investment and tourism poverty alleviation efficiency of the ethnic regions in the two stages of tourism poverty alleviation, and analyzes them by classification. The results of the study show: The pure technical efficiency in the first stage is relatively high, but the total factor productivity of each region is declining; The pure technical efficiency in the second stage is also relatively high, but the scale efficiency is low, and the change rate of total factor productivity of the provinces in China has increased significantly; The “double high” type includes Guangxi, Inner Mongolia, and Guizhou, and the “double low” type includes Qinghai, Yunnan, Tibet, Xinjiang, and Ningxia. The results of the study generally show that tourism poverty alleviation has brought about the improvement of the living standards of residents and the development of local economy, but the efficiency of tourism poverty alleviation needs to be improved. On this basis, the article puts forward corresponding improvement measures, in order to further help the ethnic minority areas get rid of poverty in a comprehensive way by promoting the efficient and sustainable development of tourism. (shrink)

We question the falsifiability of Tsuda's theory and emphasise the need for physiologically based, quantitative models of large scale cortical function that can be validated through experimental data. We outline such a model emphasising its verification through experimental data and possible avenues for testing Tsuda's predictions about nonlinearities in neural behaviour.

The first research report of the APDA project. Findings include that "gender is a significant predictor of type of placement (i.e. permanent versus temporary). The intercept tells us that the odds for male participants to have a permanent academic placement within the first two years after graduation are statistically significant at .37, p < 0.001 when year of graduation is held constant. The odds for female participants to have a permanent academic placement are 1.85, p < 0.001 when graduation year (...) is held constant. In terms of differences, the odds of having a permanent (versus temporary) academic placement are 85% greater for females as compared to males.". (shrink)

This study is based on the situation of Taiwan listed companies as derivative financial products from 2015 to 2017, analyzing the relationship between the hedging of derivative financial products and characteristics of enterprises and the factors that affect the hedging decision-making of companies. It is found that even after the announcement of Taiwan’s No. 34 and No. 36 bulletins, there are still some problems that are needed to improve in the disclosure of derivative financial product investment information by Taiwan’s listed (...) companies, at least in the disclosure of the reasons for this conduct which is still insufficient. In this study, two-stage regression analysis method is applied to empirical analysis, and it is found that hedging activities are related to corporate characteristics, such as expected financial crisis costs, corporate size, equity issues, growth investment opportunities, and information asymmetry. In the investment of derivative financial products, enterprises should evaluate their own financial characteristics as a reference for the risk avoidance decision. At the same time, it is necessary to investigate different natures of hedging tools used in appropriate risk categories, so as to fully achieve the hedging effect and maximize the hedging benefits. This study also found that companies with higher growth investment opportunities, larger size, and higher financial crisis costs will tend to use derivative financial products for hedging. As for the impact of other industries, it is found that the electronic and electrical machinery industries are more active than other industries in hedging behaviors of undertaking derivative financial products’ transaction. (shrink)

Several key areas in modeling the cardiovascular and respiratory control systems are reviewed and examples are given which reflect the research state of the art in these areas. Attention is given to the interrelated issues of data collection, experimental design, and model application including model development and analysis. Examples are given of current clinical problems which can be examined via modeling, and important issues related to model adaptation to the clinical setting.

A wealthy eccentric places two envelopes in front of you. She tells you that both envelopes contain money, and that one contains twice as much as the other, but she does not tell you which is which. You are allowed to choose one envelope, and to keep all the money you find inside.

Musical performance is a multimodal experience, for performers and listeners alike. This paper reports on a pilot study which constitutes the first step toward a comprehensive approach to the experience of music as performed. We aim at bridging the gap between qualitative and quantitative approaches, by combining methods for data collection. The purpose is to build a data corpus containing multimodal measures linked to high-level subjective observations. This will allow for a systematic inclusion of the knowledge of music (...) professionals in an analytic framework, which synthesizes methods across established research disciplines. We outline the methods we are currently developing for the creation of a multimodal data corpus dedicated to the analysis and exploration of instrumental music performance from the perspective of embodied music cognition. This will enable the study of the multiple facets of instrumental music performance in great detail, as well as lead to the development of music creation techniques that take advantage of the cross-modal relationships and higher-level qualities emerging from the analysis of this multi-layered, multimodal corpus. The results of the pilot project suggest that qualitative analysis through stimulated recall is an efficient method for generating higher-level understandings of musical performance. Furthermore, the results indicate several directions for further development, regarding observational movement analysis, and computational analysis of coarticulation, chunking, and movement qualities in musical performance. We argue that the development of methods for combining qualitative and quantitative data are required to fully understand expressive musical performance, especially in a broader scenario in which arts, humanities, and science are increasingly entangled. The future work in the project will therefore entail an increasingly multimodal analysis, aiming to become as holistic as is music in performance. (shrink)

Computational social science, as an emerging interdisciplinary discipline, is a field ushered in by long-term development of traditional social science. It is committed to supplying data thinking, resources, and analytics to study human social behavior and social operation laws to accurately grasp and judge the developing path of the discipline, which is of great significance to promote the innovation and development of social sciences. This study is to conduct a systematic quantitative analysis from a bibliometric perspective, aiming to (...) provide a reference for scholars to explore the paths and changing rules in the field. We use the relevant literature in Web of Science as the dataset. After eliminating journal calls and irrelevant literature, R language and SciMAT tools are used to visualize and analyze the number of articles, keyword clustering, keyword cooccurrence network, and theme evolution, so as to summarize and sort out the paths of computational social science research. The study found that the annual volume of publications has been gradually increasing and will probably remain active in the next few years with high productivity. Subject themes in different periods are diversified, and the evolutionary relationship is found complex as well. Besides, as a cross discipline, scientific knowledge from different fields cross collides and couples with each other in the big data environment, changing the traditional concept of computational social science and forming a new development path. Recently, the emergence of “big data+” has promoted the rise of new subject areas, making the development of new disciplines a reality. (shrink)

Banking firms are becoming increasingly aware that their clients’ management of environmental and social risks may in term threaten their own business as lenders and investors. In addition, stakeholders are requiring banks to improve their social performance. As a result, some banks are developing corporate social responsibility (CSR) policies and management systems to reduce potential risks and improve their performance. In the Spanish financial system, half of the banking firms are savings banks, most of which have always used some Corporate (...) Social Responsibility (CSR) criteria in their management. Private Banks have only recently started to integrate social aspects in their performance. However, no formal analysis has been carried out on the impact of CSR strategies. Various initiatives have been launched nationally and internationally to include the social dimension in management systems. The purpose of this research is to analyse the social performance of the main Spanish financial companies through public data such as social or sustainability reports and media sources. In order to do this, we need to determine which CSR criteria most greatly affect banking firms and to choose the most accurate quantitative and qualitative indicators to measure social performance. (shrink)

This article discusses the status of transcripts in Conversation Analysis. Repeatedly, the function and the epistemic state of transcripts have been the subject of discussions and reflections in Conversation Analysis. Drawing on a range of empirical examples taken from various authors, this article discusses the question of how present forms of visuality and multi-modality in the data material or the handling of artifacts can be captured in transcripts and how the problem of ‘representation’ of complex and interactive (...) situations can be solved. It turns out that the evolution of recording media along with the medium shift in Conversation Analysis has altered the status of transcripts, effecting a twofold ‘in-between-ness’: transcripts inhabit the conceptual space between orality and literacy on the one hand and between artwork and figure on the other hand. This oscillating hybrid nature proves to be the central property of transcripts in present-day Conversation Analysis. Transcripts are described as scientific ‘objects of knowledge’ and discussed with respect to their methodological and epistemic status. (shrink)

Background Since 2010 the People’s Republic of China has been engaged in an effort to reform its system of organ transplantation by developing a voluntary organ donation and allocation infrastructure. This has required a shift in the procurement of organs sourced from China’s prison and security apparatus to hospital-based voluntary donors declared dead by neurological and/or circulatory criteria. Chinese officials announced that from January 1, 2015, hospital-based donors would be the sole source of organs. This paper examines the availability, transparency, (...) integrity, and consistency of China’s official transplant data. Methods Forensic statistical methods were used to examine key deceased organ donation datasets from 2010 to 2018. Two central-level datasets — published by the China Organ Transplant Response System and the Red Cross Society of China — are tested for evidence of manipulation, including conformance to simple mathematical formulae, arbitrary internal ratios, the presence of anomalous data artefacts, and cross-consistency. Provincial-level data in five regions are tested for coherence, consistency, and plausibility, and individual hospital data in those provinces are examined for consistency with provincial-level data. Results COTRS data conforms almost precisely to a mathematical formula while Central Red Cross data mirrors it, albeit imperfectly. The analysis of both datasets suggests human-directed data manufacture and manipulation. Contradictory, implausible, or anomalous data artefacts were found in five provincial datasets, suggesting that these data may have been manipulated to enforce conformity with central quotas. A number of the distinctive features of China’s current organ procurement and allocation system are discussed, including apparent misclassification of nonvoluntary donors as voluntary. Conclusion A variety of evidence points to what the authors believe can only be plausibly explained by systematic falsification and manipulation of official organ transplant datasets in China. Some apparently nonvoluntary donors also appear to be misclassified as voluntary. This takes place alongside genuine voluntary organ transplant activity, which is often incentivized by large cash payments. These findings are relevant for international interactions with China’s organ transplantation system. (shrink)

The sceptical positions philosophers have adopted with respect to neuroimaging data are based on detailed evaluations of subtraction, which is one of many data analysis techniques used with neuroimaging data. These positions are undermined when the epistemic implications of the use of a diversity of data analysis techniques are taken into account. I argue that different data analysis techniques reveal different patterns in the data. Through the use of multiple data (...) analysis techniques, researchers can produce results that are locally robust. Thus, the epistemology of neuroimaging must take into consideration the details of the different data analysis techniques that are used to evaluate neuroimaging data, and the specific theoretical aims those techniques are deployed towards. _1_ Introduction _2_ Scepticism about Neuroimaging _3_ Data Analysis and Evidence _4_ Deconvolution and Pattern Classification Analysis _4.1_ Deconvolution analysis _4.2_ Region of interest selection _4.3_ Pattern classification analysis _5_ The Strength of Multiple Analyses _6_ Conclusion. (shrink)

Banking firms are becoming increasingly aware that their clients’ management of environmental and social risks may in term threaten their own business as lenders and investors. In addition, stakeholders are requiring banks to improve their social performance. As a result, some banks are developing corporate social responsibility (CSR) policies and management systems to reduce potential risks and improve their performance. In the Spanish financial system, half of the banking firms are savings banks, most of which have always used some Corporate (...) Social Responsibility (CSR) criteria in their management. Private Banks have only recently started to integrate social aspects in their performance. However, no formal analysis has been carried out on the impact of CSR strategies. Various initiatives have been launched nationally and internationally to include the social dimension in management systems. The purpose of this research is to analyse the social performance of the main Spanish financial companies through public data such as social or sustainability reports and media sources. In order to do this, we need to determine which CSR criteria most greatly affect banking firms and to choose the most accurate quantitative and qualitative indicators to measure social performance. (shrink)

Road accidents have increased rapidly in recent years for a variety of reasons. Analyzing and visualizing road accidents through heatmaps can help improve policies for their prevention by informing about areas with a high-risk of road accidents. The purpose of this research is to build a model for the analysis and visualization of road accidents through heatmaps. Information about road accidents is extracted from the news of the main online media portals through scripts in the Python language and Web (...) Scraping techniques. From the extraction of about 30,000 articles from news portals for one year, only 829 were selected in the end that provided information about road accidents. As a result, and contribution of this research, a corpus was built with the geographic coordinates of road accidents and on this data our model was applied for the analysis and visualization of high-risk areas of road accidents using heatmaps. The visualization of heatmaps was done through a Python script, where it was applied to the geographic coordinates of road accidents. (shrink)