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The present study distinguishes itself by pioneering an innovative framework that integrates key elements of prospect theory and the fundamental principles of electronic word of mouth (EWOM) to forecast Bitcoin/USD price fluctuations using Twitter sentiment analysis.

We utilized Twitter data as our primary data source. We meticulously collected a dataset consisting of over 3 million tweets spanning a nine-year period, from 2013 to 2022, covering a total of 3,215 days with an average daily tweet count of 1,000. The tweets were identified by utilizing the “bitcoin” and/or “btc” keywords through the snscrape python library. Diverging from conventional approaches, we introduce four distinct variables, encompassing normalized positive and negative sentiment scores as well as sentiment variance. These refinements markedly enhance sentiment analysis within the sphere of financial risk management.

Our findings highlight the substantial impact of negative sentiments in driving Bitcoin price declines, in contrast to the role of positive sentiments in facilitating price upswings. These results underscore the critical importance of continuous, real-time monitoring of negative sentiment shifts within the cryptocurrency market.

Our study holds substantial significance for both risk managers and investors, providing a crucial tool for well-informed decision-making in the cryptocurrency market. The implications drawn from our study hold notable relevance for financial risk management.

We present an innovative framework combining prospect theory and core principles of EWOM to predict Bitcoin price fluctuations through analysis of Twitter sentiment. Unlike conventional methods, we incorporate distinct positive and negative sentiment scores instead of relying solely on a single compound score. Notably, our pioneering sentiment analysis framework dissects sentiment into separate positive and negative components, advancing our comprehension of market sentiment dynamics. Furthermore, it equips financial institutions and investors with a more detailed and actionable insight into the risks associated not only with Bitcoin but also with other assets influenced by sentiment-driven market dynamics.

An efficient e-waste management system is developed, aided by deep learning techniques. Here, a smart bin system using Internet of things (IoT) sensors is generated. The sensors detect the level of waste in the dustbin. The data collected by the IoT sensor is stored in the blockchain. Here, an adaptive deep Markov random field (ADMRF) method is implemented to determine the weight of the wastes. The performance of the ADMRF is boosted by optimizing its parameters with the help of the improved corona virus herd immunity optimization algorithm (ICVHIOA). Here, the main objective of the developed ADMRF-based waste weight prediction is to minimize the root mean square error (RMSE) and mean absolute error (MAE) rate at the time of testing. If the weight of the bins is more than 80%, then an alert message will be sent to the waste collector directly. Optimal route selection is carried out using the developed ICVHIOA for efficient collection of wastes from the smart bin. Here, the main objectives of the optimal route selection are to reduce the distance and time to minimize the operational cost and the environmental impacts. The collected waste is then considered for recycling. The performance of the implemented IoT and blockchain-based smart dustbin is evaluated by comparing it with other existing smart dustbins for e-waste management.

The developed e-waste management system is used to collect the waste and to avoid certain diseases caused by the dumped waste. Disposal and recycling of the e-waste is necessary to decrease pollution and to manufacture new products from the waste.

The RMSE of the implemented framework was 33.65% better than convolutional neural network (CNN), 27.12% increased than recurrent neural network (RNN), 22.27% advanced than Resnet and 9.99% superior to long short-term memory (LSTM).

The proposed E-waste management system has given an enhanced performance rate in weight prediction and also in optimal route selection when compared with other conventional methods.

This article adds to the existing literature by identifying persistent sociocultural norms that influence organizational culture as facilitators of gendered microaggressions experienced by women in the workplace.

Data were obtained from 25 women employees in the Indian banking and finance sector following an unstructured interview. Grounded theory was utilized to establish that organizational culture, which in turn is reinforced by gender microaggressions, contributes to its prevalence.

Gender microaggressions manifest in the form of Alienation, Opportunity Denial, Invisible Restrictions and Sexual Innuendos. The relationship between organizational culture and gender microaggressions is cyclical, reinforcing and strengthening each other.

This is the first study on gender microaggressions to be conducted in the banking and finance sector.

Three-dimensional (3D) printing is popular for many applications including the production of photocatalysts. This paper aims to focus on developing of 3D-printed photocatalyst-nano composite lattice structure. Digital light processing (DLP) 3D printing of photocatalyst composites was performed using photosensitive resin mixed with 0.5% Wt. of TiO₂ powder and varying amounts (0.025% Wt. to 0.2% Wt.) of graphene nanoplatelet powder. The photocatalytic efficiency of DLP 3D-printed photocatalyst TiO₂ composite was investigated, and the effects of nano graphite powder incorporation on the photocatalytic activity, thermal and mechanical properties were investigated.

Methods involve 3D computer-aided design modeling, printing parameters and comprehensive characterization techniques such as structural equation modeling, X-ray diffraction, thermogravimetric analysis, Fourier-transform infrared (FTIR) and mechanical testing.

Results highlight successful dispersion and characteristics of TiO₂ and graphene nanoplatelet (GNP) powders, intricate designs of 3D-printed lattice structures, and the influence of GNPs on thermal behavior and mechanical properties.

The study suggests applicability in wastewater treatment and environmental remediation, showcasing the adaptability of 3 D printing in designing effective photocatalysts. Future research should focus on practical applications and the long-term durability of these 3D-printed composites.

This study utilizes Bourdieu’s concepts of field, capital and habitus to investigate the networking strategies of Asian and Black knowledge workers in the London Insurance Market. It also examines the factors contributing to the success or failure of these strategies. The trading activities of the London Insurance Market are underpinned by interdependent relations among its participants. It provides an appropriate context for examining the networking strategies adopted by Asian and Black workers to accelerate their careers.

This research employed a qualitative methodology, gathering data from 24 participants through semi-structured interviews. Participants were selected using purposive, convenience, and snowball sampling methods. Thematic analysis was used to analyze data and develop aggregated concepts from the identified themes and subthemes.

The London Insurance Market accords great importance to networking. Interpersonal connections significantly influenced career progression, often overshadowing educational attainments. Asian and Black workers faced systemic nepotism and limited access to influential networks in this field. Participants strategically used their interactions to overcome these challenges and advance their careers. Many believed that their careers had a better chance of progressing through informal networks than through formal channels such as Human Resources. Some participants declined to engage in the commonly accepted networking practices, choosing alternative ways to further their careers.

Findings underscore the need for implementing specific organizational policies to address systemic biases and nepotism, particularly in front-office recruitment. Such policies could include prioritizing merit-based hiring practices and developing targeted initiatives to reduce the underrepresentation of minority ethnic workers in front-office positions. By adopting these measures, organizations can create more equitable career advancement opportunities and leverage the full potential of their diverse workforce.

This study contributes to the existing literature on minority ethnic workers' careers, networking theory and workplace diversity. It provides insights into the networking strategies of Asian and Black workers within the London Insurance Market, revealing that these strategies are dependent on contextual factors. The study also highlights the pervasive practice of nepotism deeply ingrained in the habitus of the London Insurance Market and which acts as a barrier for gaining access to influential networks.

This paper aims to explore the influence of corrosion-deformation interactions (CDI) on the corrosion behavior and mechanisms of 316LN under applied tensile stresses.

Corrosion of metals would be aggravated by CDI under applied stress. Notably, the presence of nitrogen in 316LN austenitic stainless steel (SS) would enhance the corrosion resistance compared to the nitrogen-absent 316L SS. To clarify the CDI behaviors, electrochemical corrosion experiments were performed on 316LN specimens under different applied stress levels. Complementary analyses, including three-dimensional morphological examinations by KH-7700 digital microscope and scanning electron microscopy coupled with energy dispersive spectroscopy, were conducted to investigate the macroscopic and microscopic corrosion morphology and to characterize the composition of corrosion products within pits. Furthermore, ion chromatography was used to analyze the solution composition variations after immersion corrosion tests of 316LN in a 6 wt.% FeCl₃ solution compared to original FeCl₃ solution. Electrochemical experiment results revealed the linear decrease in free corrosion potential with increasing applied stress. Electrochemical impedance spectroscopy results indicated that high tensile stress level damaged the integrity of passivation film, as evidenced by the remarkable reduction in electrochemical impedance. Ion chromatography analyses proved the concentrations increase of NO₃⁻ and NH₄⁺ ion concentrations in the corrosion media after corrosion tests.

The enhanced corrosion resistance of 316LN SS is attributable to the presence of nitrogen.

The scope of this study is confined to the influence of tensile stress on the electrochemical corrosion of 316LN at ambient temperatures; it does not encompass the potential effects of elevated temperatures or compressive stress.

The resistance to stress electrochemical corrosion in SS may be enhanced through nitrogen alloying.

This paper presents a systematic investigation into the stress electrochemical corrosion of 316LN, marking the inaugural study of its impact on corrosion behaviors and underlying mechanisms.

Different age groups display different shopping patterns in terms of how and where consumers buy products. During times of crisis, such behavioural differences become even more striking yet remain under-researched with respect to elderly consumers. This paper investigates the impact of age on retail-related behavioural changes and behavioural stability of elderly shoppers (in comparison to younger consumers) during a crisis.

The authors surveyed 643 Austrian consumers to assess the impact of perceived threat on behavioural change and the moderating effect of age groups. Based on findings from this survey, they subsequently conducted 51 semi-structured interviews to understand the causes of behavioural change and behavioural stability during a crisis.

Elderly shoppers display more stable shopping behaviour during a crisis compared to younger consumers, which is influenced by perceived threat related to the crisis. Such findings indicate that elderly shoppers reinforce their learnt and embedded shopping patterns. The causes of change and stability in behaviour include environmental and inter-personal factors.

Through the lens of social cognitive theory, protection motivation theory and dual process theory, this research contributes to an improved understanding of changes in shopping behaviour of elderly consumers, its antecedents and consequences during a time of crisis. The authors reveal reasons that lead to behavioural stability, hence the absence of change, in terms of shopping during a crisis. They further outline implications for retailers that might wish to better respond to shopping behaviours of the elderly.

The purpose of the quantitative correlational research study was to determine the relationship, if any, between the predictor variable, cosmeceutical business service quality, and the outcome variable, cosmeceutical client satisfaction, in the southeast region of the United States of America. Cosmeceuticals were cosmetics and medications administered by estheticians.

Literature on business service quality and client satisfaction theories was synthesized after extensive review. Quantitative research data were collected and statistically analyzed on the following subscales of consumer satisfaction: general satisfaction, technical quality, interpersonal manner, communication, financial aspects, time spent with professionals and accessibility/convenience. The hypotheses addressed the research question (RQ) of whether cosmeceutical business service quality affects client satisfaction. The Cosmeceutical Client Satisfaction Questionnaire 18 (CCSQ-18), a web-based research instrument, had strong reliability with a Cronbach’s alpha of 0.84. The target population (N = 50) included randomly selected female cosmeceutical consumers in the southeast region of the United States of America. The researcher did not digress from the detailed research protocol, instrumentation, data collection or data analyses. Through the Likelihood Ratio (LR) chi-squared statistic (18) = 65.35 and its associated probability, Prob > chi-squared = 0.000, the researcher determined the predictor variable cohesively has a statistically significant effect on the outcome variable.

Research results concluded that a significant relationship exists between cosmeceutical business service quality and cosmeceutical client satisfaction in the southeast region of the United States of America.

The findings detailed in the results complimented the argument that, generally, business service quality is important to consider, because good business is based on client satisfaction.

The purpose of this study is to identify the level of quality of work life (QWL) of employees working in the Garment industries using a validated scale.

Survey methods were used for this study. A questionnaire was designed to collect the data and information, and it is validated through exploratory factor analysis, confirmatory factor analysis.

The majority of employees are not satisfied with the present status of QWL in garment units. Followings are the predominant components, which influence the QWL of employees compensation and rewards; job security; grievance handling; work environment; training and development; job nature; satisfaction in job; facilities and relation and cooperation.

The study was conducted in 133 garment industries where sample responses were obtained from 851 workers working in Indian Garment industries. In the competitive business environment, retaining a talented workforce is one of the big challenges to the organization. An unsatisfied employee is the first enemy of the organization, it is the prime task of the employers to keep the workforce at a satisfying level, otherwise, it will lead to employee turnover, performance and productivity. This paper helps to identify and quantify the components of the quality of work-life of employees if employers address these components job satisfaction level of employees will increase; therefore, our results will help the HR managers and policymakers to take appropriate decisions to enhance QWL.

The purpose of this paper is to study the relationship between subsidiary manager’s demographic characteristics and performance, while incorporating the subsidiary context. We draw upon upper echelon theories and International Business theories to understand this relationship.

Using a dataset based on listed Multinational subsidiaries in India we use linear regression to establish the relationship between subsidiary external performance (host market performance), subsidiary internal performance and subsidiary manager’s demographic characteristics.

With our data set we find a positive relationship between percentage of host country nationals (HCN) in the Top Management Team (TMT) and subsidiary host market performance and that subsidiary age moderates this relationship. We also find an inverted U-shaped relationship between parent country nationals (PCN) tenure and subsidiary performance.

One of the limitations is that our study views the strategy process through the Upper Echelons (UE) theory lens, as a clearly specified planning process that associates strategy with intentionality. The opportunity that emanates at lower levels can turn an intended strategy into something different than what was started.

The findings in this paper can be the basis for decision making on the constitution of leadership teams.

There is a dearth of empirical evidence and studies on TMTs in the subsidiary, particularly from the non-North American context. Using a unique data set of listed multinational subsidiaries in India, the paper explores the impact of TMT demographics such as tenure of the TMT and age of the subsidiary operations on the performance of the subsidiary.