CORPORATE SOCIAL RESPONSIBILITY AUTHENTICITY AND FIRM PERFORMANCE IN AN EMERGING MARKET

This study uses quantitative methods to investigate the importance of corporate social responsibility authenticity (CSRA) on the performance of small and medium-sized enterprises (SMEs). It investigates the interceding roles of organizational identification (OID) and corporate reputation (CRE) between CSRA and firm performance (FPE). The data, which were questionnaire responses from 548 customers, employees, and shareholders of SMEs, were analyzed using SmartPLS version 3.3.2. Significant positive correlations were found between the authenticity of corporate social responsibility (CSR) and three key factors: firm performance, organizational identification, and corporate reputation. This study contributes to existing knowledge by exploring the mediating roles of OID and CRE in the relationship between CSRA and FPE. To better understand how CSR affects OID, CRE, and eventually FPE, this study integrates the perceptions of internal and external stakeholders on the degree to which CSR is seen as authentic. This study particularly adds to the body of CSR literature in the context of increasing skepticism of stakeholders about CSR authenticity. Grounded in stakeholder behaviors, social identity, and social exchange theories, this study extends these theories by operationalizing a novel empirical framework in a new setting. Furthermore, the implications of this study extend to society’s current concerns about “greenwashing” or “corporate hypocrisy.

The relationship between trading volume, stock index returns and volatility: Empirical evidence in Nordic countries.

In this paper, several methods such as VAR and EGARCH are employed to examine the relationship between trading volume, stock index returns and volatility in Nordic countries for the period 1999 to 2009. Our results confirm a positive relationship between trading volume and absolute stock returns. More specifically, there are bidirectional causality in Demark and Finland while Sweden and Norway are found to have unidirectional causality from returns to trading volume. This paper also points out that while trading volume may contain some information which is helpful in explaining volatility it cannot remove the persistence of volatility

COCO-Counterfactuals: Automatically Constructed Counterfactual Examples for Image-Text Pairs

Counterfactual examples have proven to be valuable in the field of natural language processing (NLP) for both evaluating and improving the robustness of language models to spurious correlations in datasets. Despite their demonstrated utility for NLP, multimodal counterfactual examples have been relatively unexplored due to the difficulty of creating paired image-text data with minimal counterfactual changes. To address this challenge, we introduce a scalable framework for automatic generation of counterfactual examples using text-to-image diffusion models. We use our framework to create COCO-Counterfactuals, a multimodal counterfactual dataset of paired image and text captions based on the MS-COCO dataset. We validate the quality of COCO-Counterfactuals through human evaluations and show that existing multimodal models are challenged by our counterfactual image-text pairs. Additionally, we demonstrate the usefulness of COCO-Counterfactuals for improving out-of-domain generalization of multimodal vision-language models via training data augmentation.Comment: Accepted to NeurIPS 2023 Datasets and Benchmarks Trac

Semi-Structured Chain-of-Thought: Integrating Multiple Sources of Knowledge for Improved Language Model Reasoning

An important open question pertaining to the use of large language models for knowledge-intensive tasks is how to effectively integrate knowledge from three sources: the model's parametric memory, external structured knowledge, and external unstructured knowledge. Most existing prompting methods either rely solely on one or two of these sources, or require repeatedly invoking large language models to generate similar or identical content. In this work, we overcome these limitations by introducing a novel semi-structured prompting approach that seamlessly integrates the model's parametric memory with unstructured knowledge from text documents and structured knowledge from knowledge graphs. Experimental results on open-domain multi-hop question answering datasets demonstrate that our prompting method significantly surpasses existing techniques, even exceeding those which require fine-tuning

Counterfactual analysis among Covid-19: fiscal and monetary policy for green economic recovery

This study examines fiscal-monetary policy links in America across a time period that includes the recent global economic crisis and the COVID-19 emergency. Hypotheses deviate that regulatory administrations are permanent and calculate fiscal policy yearly percentage rate and budgetary regulations which are likely to change between two governments. Additionally, study uses the VAR technique to evaluate the effects of financial initiatives similar to those undertaken in the aftermath of the Covid-19 outbreak. Results discovered that fiscal policy is more successful than monetary policy, and that lavishing on public debt helps increase short-run economic performance. People argue that concerns about a rapid rise in prices as a result of fiscal stimulus are unfounded because the US economy was not close to full employment or full use of funds prior to the global epidemic, and the dissemination processes that could contribute to accelerating rising prices are not always in place. As a result, with the withdrawal of monetary stimulus, the favourable effects on actual GDP and real private expenditure are gone. Long-term mortgage rates have risen, money invested has decreased, and prices have risen, raising concerns about the banking system’s inflationary tendency

Removal of Pollutants by Atmospheric Non Thermal Plasmas

Results on the application of non thermal plasmas in two environmentally important fields: oxidative removal of VOC and NOx in excess of oxygen were presented. The synergetic application of a plasma-catalytic treatment of NOx in excess of oxygen is also described.Comment: 6 pages; Published in Catalysis for Environment: Depollution, Renewable Energy and Clean Fuels, Zakopane : Pologne (2008

Smart Shopping Assistant: A Multimedia and Social Media Augmented System with Mobile Devices to Enhance Customers’ Experience and Interaction

Multimedia, social media content, and interaction are common means to attract customers in shopping. However these features are not always fully available for customers when they go shopping in physical shopping centers. The authors propose Smart Shopping Assistant, a multimedia and social media augmented system on mobile devices to enhance users’ experience and interaction in shopping. Smart Shopping turns a regular mobile device into a special prism so that a customer can enjoy multimedia, get useful social media related to a product, give feedbacks or make actions on a product during shopping. The system is specified as a flexible framework to take advantages of different visual descriptors and web information extraction modules. Experimental results show that Smart Shopping can process and provide augmented data in a realtime-manner. Smart Shopping can be used to attract more customers and to build an online social community of customers to share their interests in shopping