Emotional stimuli (e.g. words, images) are often remembered better than neutral stimuli. However, little is known about how memory is affected by an environmentally induced emotional state (without any overtly emotional occurrences) – the focus of this study. Participants were randomly assigned to discovery (n = 305) and replication (n = 306) subsamples and viewed a desktop virtual environment before rating their emotions and completing objective (i.e. item, temporal-order, duration) and subjective (e.g. vividness, sensory detail, coherence) memory measures. In both (...) samples, a Partial Least Squares Correlation analysis showed that an emotional state characterised by high negative emotion (i.e. threat, fear, anxiety) and arousal was reliably associated with better memory in both objective (i.e. item) and subjective (i.e. vividness and sensory detail) domains. No reliable associations were observed for any temporal memory measures (objective or subjective). Thus, an environmentally induced state of negative emotion corresponds with enhanced memory for indices of episodic memory pertaining to “what” happened, but not necessarily “when” it happened. (shrink)

This study examines the roles of environmental strategy and accounting in corporate carbon performance, as measured by the Greenhouse Gas (GHG) Protocol. A novel interaction model is developed based on legitimacy theory and natural-resource dependence theory to capture the interaction between environmental strategy and accounting. An international sample of 3322 firms from 73 countries is used in the analysis, based on a panel data design for 17 years (2005–2022). The empirical findings reveal an overall reactive role of these environmental initiatives (...) in relation to carbon performance. The marginal effect analysis shows that environmental accounting favourably moderates the effect of environmental strategic functions on carbon performance, indicating that the former facilitates the translation of the latter into practice. Similarly, environmental strategic initiatives improve the impact of environmental accounting information on carbon performance. The main contribution of this study stems from methodologically demonstrating how the synergy between environmental strategic initiatives and environmental information mechanisms can translate into improved carbon performance. This finding has multiple societal, practical and research implications. The interaction effect evidence can be viewed as consistent with recent trends of integrated approaches to thinking and reporting, where interrelated phenomena are integrated into operational and reporting contexts to improve efficiency. This can be of interest to policymakers, investors, corporate managers and providers of assurance services related to carbon performance. (shrink)

This study provides novel evidence of the impact of corporate social responsibility (CSR) on investment sensitivity to cash flows. We posit that CSR affects investment–cash flow sensitivity (ICFS) through information asymmetry and agency costs, commonly viewed as the two channels through which investment responds to the availability of internal cash flows. We find that CSR performance leads to a decrease in ICFS. We further find that ICFS decreases (increases) when CSR strengths (concerns) increase. Finally, we find that the effect of (...) CSR on ICFS is driven by the areas Community, Diversity, and Human Rights. In sum, the findings of this study stress the relevance of CSR—in particular, of CSR activities that extend beyond compliance behavior and reflect what is desired by society—in reducing market frictions and improving firms’ access to financial capital. (shrink)

The novel coronavirus disease is regarded as one of the most imminent disease outbreaks which threaten public health on various levels worldwide. Because of the unpredictable outbreak nature and the virus’s pandemic intensity, people are experiencing depression, anxiety, and other strain reactions. The response to prevent and control the new coronavirus pneumonia has reached a crucial point. Therefore, it is essential—for safety and prevention purposes—to promptly predict and forecast the virus outbreak in the course of this troublesome time to have (...) control over its mortality. Recently, deep learning models are playing essential roles in handling time-series data in different applications. This paper presents a comparative study of two deep learning methods to forecast the confirmed cases and death cases of COVID-19. Long short-term memory and gated recurrent unit have been applied on time-series data in three countries: Egypt, Saudi Arabia, and Kuwait, from 1/5/2020 to 6/12/2020. The results show that LSTM has achieved the best performance in confirmed cases in the three countries, and GRU has achieved the best performance in death cases in Egypt and Kuwait. (shrink)

Twitter integrates with streaming data technologies and machine learning to add new value to healthcare. This paper presented a real-time system to predict breast cancer based on streaming patient’s health data from Twitter. The proposed system consists of two major components: developing an offline building model and an online prediction pipeline. For the first component, we made a correlation between the features to determine the correlation between features and reduce the number of features from the Breast Cancer Wisconsin Diagnostic dataset. (...) Two feature selection algorithms are recursive feature elimination and univariate feature selection algorithms which are applied to features after correlation to select the essential features. Four decision trees, logistic regression, support vector machine, and random forest classifier have been used on features after correlation and feature selection. Also, hyperparameter tuning and cross-validation have been applied with machine learning to optimize models and enhance accuracy. Apache Spark, Apache Kafka, and Twitter Streaming API are used to develop the second component. The best model with the highest accuracy obtained from the first component predicts breast cancer in real time from tweets’ streaming. The results showed that the best model is the random forest classifier which achieved the best accuracy. (shrink)

This paper seeks to discover whether companies that adopt a stakeholder approach, and thereby demonstrate a wider remit of corporate responsibility, provide inferior returns to those that embrace the shareholder value approach. To classify approaches, mission statements were analysed, the final sample comprising 32 shareholder oriented companies and 48 stakeholder oriented companies. To assess performance both accounting–based and market–based measures were used. A number of moderating variables were taken into account: systematic (beta) risk, gearing (long–term debt to total long–term finance), (...) tax ratios, and firm size. ANOVA and Kruskall–Wallis tests revealed that mission orientation did not affect performance, whether in terms of stock returns or excess returns. Neither were accounting returns on equity different overall, although shareholder oriented companies experienced wider variations in this measure. A number of multiple regressions were also performed. However, the mission dummy was not found to be a significant variable. (shrink)

This paper seeks to discover whether companies that adopt a stakeholder approach, and thereby demonstrate a wider remit of corporate responsibility, provide inferior returns to those that embrace the shareholder value approach. To classify approaches, mission statements were analysed, the final sample comprising 32 shareholder oriented companies and 48 stakeholder oriented companies. To assess performance both accounting–based and market–based measures were used. A number of moderating variables were taken into account: systematic (beta) risk, gearing (long–term debt to total long–term finance), (...) tax ratios, and firm size. ANOVA and Kruskall–Wallis tests revealed that mission orientation did not affect performance, whether in terms of stock returns or excess returns. Neither were accounting returns on equity different overall, although shareholder oriented companies experienced wider variations in this measure. A number of multiple regressions were also performed. However, the mission dummy was not found to be a significant variable. (shrink)

Spam electronic mails (emails) refer to harmful and unwanted commercial emails sent to corporate bodies or individuals to cause harm. Even though such mails are often used for advertising services and products, they sometimes contain links to malware or phishing hosting websites through which private information can be stolen. This study shows how the adaptive intelligent learning approach, based on the visual anti-spam model for multi-natural language, can be used to detect abnormal situations effectively. The application of this approach is (...) for spam filtering. With adaptive intelligent learning, high performance is achieved alongside a low false detection rate. There are three main phases through which the approach functions intelligently to ascertain if an email is legitimate based on the knowledge that has been gathered previously during the course of training. The proposed approach includes two models to identify the phishing emails. The first model has proposed to identify the type of the language. New trainable model based on Naive Bayes classifier has also been proposed. The proposed model is trained on three types of languages (Arabic, English and Chinese) and the trained model has used to identify the language type and use the label for the next model. The second model has been built by using two classes (phishing and normal email for each language) as a training data. The second trained model (Naive Bayes classifier) has been applied to identify the phishing emails as a final decision for the proposed approach. The proposed strategy is implemented using the Java environments and JADE agent platform. The testing of the performance of the AIA learning model involved the use of a dataset that is made up of 2,000 emails, and the results proved the efficiency of the model in accurately detecting and filtering a wide range of spam emails. The results of our study suggest that the Naive Bayes classifier performed ideally when tested on a database that has the biggest estimate (having a general accuracy of 98.4%, false positive rate of 0.08%, and false negative rate of 2.90%). This indicates that our Naive Bayes classifier algorithm will work viably on the off chance, connected to a real-world database, which is more common but not the largest. (shrink)

For a sample comprising 36,105 U.S. firm-year observations from 1985 to 2008, we find that firms located in more religious counties enjoy cheaper equity financing costs. This result is robust to a battery of sensitivity tests, including alternative assumptions and model specifications, additional controls for noise in analyst forecasts, and various approaches to addressing endogeneity. In another set of tests, we find that the equity pricing role that religion plays comes predominantly from Mainline Protestants. We also document that the effect (...) of religiosity on firms’ cost of equity capital is larger for firms (periods) lacking alternative monitoring (regulation) mechanisms as measured by lower institutional ownership (the pre-SOX era), implying that religion plays a corporate governance role. Finally, we find that the importance of religion to equity pricing is concentrated in firms that suffer lower visibility, which tend to be more sensitive to local social and economic factors. By examining the links between religiosity and valuation at the firm level, we provide strong, robust evidence supporting the perspective that religion facilitates economic development. (shrink)

We examine how corporate environmental responsibility affects the cost of equity capital for manufacturing firms in 30 countries. Using several approaches to estimate firms’ ex ante equity financing costs, we find in regressions that control for firm-level characteristics as well as industry, year, and country effects that the cost of equity capital is lower when firms have higher CER. This finding is robust to addressing endogeneity through instrumental variables, to using alternative specifications and proxies for the cost of equity capital, (...) and to accounting for noise in analyst forecasts. We conclude that investment in CER reduces firms’ equity financing costs worldwide. (shrink)

An improved variant of the Jaya optimization algorithm, called Jaya2, is proposed to enhance the performance of the original Jaya sacrificing its algorithmic design. The proposed approach arranges the solutions in a ring topology to reduce the likelihood of premature convergence. In addition, the population size reduction is used to automatically adjust the population size during the optimization process. Moreover, the translation dependency problem of the original Jaya is discussed, and an alternative solution update operation is proposed. To test Jaya2, (...) we compare it with nine different optimization methods on the CEC 2020 benchmark functions and the CEC 2011 real-world optimization problems. The results show that Jaya2 is highly competitive on the tested problems where it generally outperforms most approaches. Having an easy-to-implement approach with little parameter tuning is highly desirable since researchers from different disciplines with basic programming skills can use it to solve their optimization problems. (shrink)

Recent research suggests that collectivism breeds corruption in bank lending. This finding, together with the stickiness of culture, poses a direct challenge to economic growth in collectivist societies. In this paper, we address this grim outlook by examining the types of firms that are susceptible to the detrimental effect of collectivism on lending integrity and the formal institutions that can help alleviate such effect. We find that the adverse effect of collectivism on bank corruption is more severe in small and (...) medium-sized firms, privately owned firms, and non-exporting firms, while it is considerably weaker in countries with more effective private monitoring, a higher fraction of foreign-owned banks, a more competitive banking sector, better information sharing, and stronger legal and political institutions. Our findings are robust to using alternative measures of collectivism and alternative dependent variables. These results highlight how firm-level characteristics and formal institutions interact with collectivism in affecting firms’ access to bank credit. (shrink)

Prior research suggests that the media plays an important information intermediary role in capital markets. We investigate the role of the media in influencing firms’ engagement in corporate social responsibility activities. Using a large sample of 4396 unique firms from 42 countries over the period 2003–2012, we find strong evidence that firms engage in more CSR activities if located in countries where the media has more freedom. This relation is robust to using various proxies for media freedom, an alternative source (...) of CSR data, and to applying the instrumental variables approach to address endogeneity. In additional analyses, we find that the positive relation between media freedom and CSR engagement is stronger for better governed firms and for larger firms. Since the media have the ability to impact reputational capital, we conclude that media freedom affects firms’ incentives to engage in costly CSR activities. (shrink)

The disclosure of corporate environmental performance is an increasingly important element of a firm’s ethical behavior. We analyze how the legal origin of foreign institutional investors affects a firm’s voluntary greenhouse gas emissions disclosure. Using a large sample of firms from 36 countries, we show that foreign institutional ownership from civil law countries improves the scope and quality of a firm’s greenhouse gas emissions reporting. This relation is robust to addressing endogeneity and selection biases. The effect is more pronounced in (...) firms from non-climate-sensitized countries, for which the gap between firms’ environmental standards and investors’ environmental targets is potentially larger, and in less international firms. Firms with a higher level of voluntary greenhouse gas emissions disclosure also exhibit higher valuations. (shrink)

Festschrift volume to K. Ramakrishna Rao, Indian psychologist, philosopher and educationist; contributed articles.

Study of rationalism in Urdu literature.

Constitutional and judicial law-making is increasingly beginning to find its reflection not only in the Anglo-Saxon, but also in the Romano-Germanic legal family. However, the prerequisites for the use of this legal instrument are different, which determines the relevance of conducting a comparative analysis regarding the provision of such a mechanism in the USA and Kazakhstan. The purpose of the research is to identify common and distinctive features in the process of implementation of constitutional and judicial law-making in countries belonging (...) to different legal systems. The article uses the methods of analysis, synthesis, comparison, deduction and generalization. As a result, the specificity of ensuring the mechanism of constitutional law-making in the USA was expressed, taking into account various forms of law-making activity. It has been established that the development of constitutional provisions in the United States takes place with the help of the constitutional doctrines of the Supreme Court of the United States, which provide for the introduction of amendments to constitutional provisions without a formal procedure. As a result of the study of the experience of Kazakhstan, it was established that special priority was given to the role of precedent, in particular, the decision of the Supreme Court of the Republic of Kazakhstan. This is explained by the integrative nature of the Romano-Germanic legal system, which allows effective development of national legislation as a whole and its provisions. The obtained results can be used during the professional training of judges in the Republic of Kazakhstan. (shrink)

K. Satchidananda Murty (1924-2011) was a vociferous writer and an iconoclast. This volume is a collection of his unpublished writings. It includes Murty's views on the Veda, its meaning, relevance, and study, and shows the significance of the Vedāntic vision to the modern world. Murty elucidates the basic tenets of Advaita Vedānta and expounds the Advaitic doctrine of the relationships between Brahman and God, Brahman and the individual self, as well as between God and the world. In his writings, Murty (...) contrasts empirical knowledge with transcendental wisdom and surveys the history of Indian science and scientific views in ancient times. The book also includes Murty's musings on the scholar Śankara's philosophy, authorship and religious life. An important contribution to Indian philosophy, the volume will be of great interest to scholars, teachers and students of Hindu philosophy, Vedāntic philosophy, Advaita Vedanta, comparative philosophy, religious studies, and South Asian studies. (shrink)

This chapter provides an introduction to higher-order metaphysics as well as to the contributions to this volume. We discuss five topics, corresponding to the five parts of this volume, and summarize the contributions to each part. First, we motivate the usefulness of higher-order quantification in metaphysics using a number of examples, and discuss the question of how such quantifiers should be interpreted. We provide a brief introduction to the most common forms of higher-order logics used in metaphysics, and indicate a (...) number of questions which can be raised in such systems using logical vocabulary alone. Using a further example, we return to applications of higher-order logics in metaphysics. We also mention key developments in the history of higher-order logic as it pertains to metaphysics. Finally, we mention certain arguments which have been raised against the use of higher-order logic, and some ways of responding to them. (shrink)

Using a large sample of 3,040 U.S. firms and 16,606 firm-year observations over the 1991–2010 period, we find strong evidence that firm internationalization is positively related to the firm’s corporate social responsibility rating. This finding persists when we use alternative estimation methods, samples, and proxies for internationalization and when we address endogeneity concerns. We also provide evidence that the positive relation between internationalization and CSR rating holds for a large sample of firms from 44 countries. Finally, we offer novel evidence (...) that firms with extensive foreign subsidiaries in countries with well-functioning political and legal institutions have better CSR ratings. Our findings shed light on the role of internationalization in influencing multinational firms’ CSR activities in the U.S. and around the world. (shrink)

This study provides evidence on the relationship between corporate social responsibility and firms’ credit ratings. We find that credit rating agencies tend to award relatively high ratings to firms with good social performance. This pattern is robust to controlling for key firm characteristics as well as endogeneity between CSR and credit ratings. We also find that CSR strengths and concerns influence credit ratings and that the individual components of CSR that relate to primary stakeholder management matter most in explaining firms’ (...) creditworthiness. Overall, our results suggest that CSR performance conveys important non-financial information that rating agencies are likely to use in their evaluation of firms’ creditworthiness, and that CSR investments—particularly those that extend beyond compliance behavior to reflect what is desired by society—can lead to lower financing costs resulting from higher credit ratings. (shrink)