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The Indian stock market can be tricky when there's trouble in the world, like wars or big conflicts. It's like trying to read a secret message. We want to figure out what makes investors nervous or happy, because their feelings often affect how they buy and sell stocks. We're building a tool to make prediction that uses both numbers and people's opinions.

Hybrid approach leverages Twitter sentiment, market data, volatility index (VIX) and momentum indicators like moving average convergence divergence (MACD) and relative strength index (RSI) to deliver accurate market insights for informed investment decisions during uncertainty.

Our study reveals that geopolitical tensions' impact on stock markets is fleeting and confined to the short term. Capitalizing on this insight, we built a ground-breaking predictive model with an impressive 98.47% accuracy in forecasting stock market values during such events.

To the best of the authors' knowledge, this model's originality lies in its focus on short-term impact, novel data fusion and high accuracy. Focus on short-term impact: Our model uniquely identifies and quantifies the fleeting effects of geopolitical tensions on market behavior, a previously under-researched area. Novel data fusion: Combining sentiment analysis with established market indicators like VIX and momentum offers a comprehensive and dynamic approach to predicting market movements during volatile periods. Advanced predictive accuracy: Achieving the prediction accuracy (98.47%) sets this model apart from existing solutions, making it a valuable tool for informed decision-making.

Unacceptable behaviour in retailing – negative customer deviance (NCD) is rising, damaging retailers financially. Current research investigates forms of NCD by addressing its impact on employees but overlooks its effects on bystander-customers and their retail channel preferences. As channel switching within retailing is increasing unprecedentedly, this research investigates its correspondence with NCD encounters.

This research uses structural equation modelling, based on data collection administered through a web-based survey of 1,008 customers of at least 16 years of age, to analyse the research model.

The findings reveal unexplored forms of NCD perceived by bystander-customers in retailing and their consequences, linking it to bystander-customers' ill-being, dissatisfaction with the shopping experience, a decrease in store commitment and an increase in their retail channel-switching intentions. Additionally, the research uncovers moderating variables.

This research tests NCD dimensions and effects on bystander-customers, which indicate the need for retailers to address shopping values, attitudes and commitment through corrective, proactive and long-term strategic actions.

As one of the first studies to investigate the impact of NCD on bystander-customers' intentions to switch from store-based to online shopping, strategies for retailers are developed to help diminish and control NCD-induced threats to bystander-customers.

Gen Z, the largest and fastest-growing consumer generation, is transforming the hospitality industry as both customers and employees. By critically synthesizing empirical literature, this study aims to explore how this generation’s distinct behaviors are reshaping customer expectations and workforce trends within the sector.

A critical synthesis of empirical studies was used to examine current research on Gen Z as customers and employees in the hospitality industry.

Gen Z exhibits distinct preferences and expectations in their dual roles as customers and employees, prompting substantial shifts in hospitality industry standards and practices. They rely heavily on digital channels and peer recommendations when making travel decisions and expect highly personalized, tech-enabled experiences. This young cohort of travelers values unique, authentic and sustainable offerings. As employees, Gen Z prioritizes flexible work arrangements, career growth and workplaces aligned with sustainability, diversity and social responsibility. Hospitality providers must adapt their customer experience, marketing and HR strategies to meet these evolving demands.

To engage Gen Z customers and employees in the hospitality industry effectively, businesses must prioritize personalized experiences, leverage technology and adopt sustainable practices aligned with Gen Z’s social and environmental values. Moreover, offering adaptable work environments with remote opportunities and investing in professional development enhances appeal for Gen Z employees. Understanding Gen Z’s values and behaviors can help businesses improve customer satisfaction, attract top talent and remain competitive in a rapidly evolving market.

This study represents a preliminary endeavor to provide a critical assessment of Gen Z in the hospitality and tourism sector, offering novel insights into their travel behaviors, preferences and work values. It explores their expectations, attitudes toward work and career choices, offering guidance on how businesses can meet the evolving demands of this key demographic.

This study combines the TAM and UGT frameworks to investigate how Vietnamese students' views of ChatGPT and intrinsic needs affect their intentions to use it for education (via variables including perceived ease of use, perceived usefulness, novelty, information seeking and academic content creation). We will employ TAM theory (Davis, 1989) and UGT theory to elucidate university students' motivations for utilising ChatGPT in Vietnam. Simultaneously, we aim to address the limitation stemming from data uniformity. Our research will make a substantial contribution to the understanding of researchers regarding the use of ChatGPT and its varied consequences as it grows and develops.

This study was conducted at a private university in Vietnam with an estimated population of 15,000 students. One of Vietnam’s top private information technology institutions requires its students to use a variety of information and communication technologies (ICTs) on a regular basis to facilitate and enjoy their academic pursuits (Ngo, 2024; Nguyen). Students who are familiar with ChatGPT and have access to it for educational purposes are the ones that were chosen. This research is a quantitative study that utilises primary data through a survey method. Participants answered a questionnaire online through the Google Form platform sharing via social media platforms from October to December 2023. The questionnaire was divided into two sections: the first contained screening questions and demographic information and the second had five-point Likert-scale questions that measured the study’s components. Two screening questions are used to separate out the intended responders. (i.e. “I have heard the name ChatGPT” and “I know about ChatGPT”) were set to find whether the participants had any knowledge of ChatGPT. If participants were unaware of ChatGPT, their responses were not included in the study. A total of 283 responses were received. The participant’s demographic information is shown in Table 1. It is believed that a sample size of more than 200 provides adequate statistical power for data analysis in structural equation modelling. It is evident that the 283-sample size in this study is adequate to evaluate the research hypothesis and the fitting model. 42.9% of the 283 research samples were made up of men, while 57.1% were women. Business administration accounted for 40.1% of survey respondents, followed by information technology (25.2%) and English language (14.5%). The average ChatGPT usage time of respondents was 56 min in a single use. The study sample’s average age is 20–72 years old.

The present study contributes to the existing AI chatbot literature in the educational industry in several ways. First, this study addresses a gap in the literature by investigating the factors that influence students’ ITU ChatGPT for educational purposes in Vietnam. Using the extended model, we investigated factors influencing students’ intentions to use ChatGPT. It integrates three motive factors of the UGT (ACT, IS and N) with the core factors of TAM (PeoU and PU). The integrated framework’s findings indicate that in a Vietnamese educational setting, ChatGPT is a novel technology that should be considered in conjunction with PU and PEoU.

First, only Vietnamese students make up the research sample. To increase the relevance of the findings, it is advised that future research look at the study model in various geographic regions. Second, the present investigation’s constraints arise from the lack of clarity about the Chat GPT version utilised by the respondents, specifically whether it was the free or premium edition. Furthermore, the limited duration of the survey presents an obstacle to gathering thorough data. Due to their reliance on the particular features and functionalities of the Chat GPT version used, these restrictions may have an effect on the researcher’s objectivity. Furthermore, the limited survey time may curtail the coverage of the collected answers, particularly considering that our survey predominantly focuses on business administration students, thus limiting the diversity and richness of the gathered data. We recommend that future studies should conduct comparative research between different versions of GPT Chat, including free and paid variants that can provide valuable insights into potential differences in performance and results. Such analysis can provide a deeper understanding of the strengths and limitations of different GPT Chat versions. Third, because the study focused on behavioural intention, actual usage and post-usage behaviour may not be covered by the findings. To gain a deeper understanding of users' actual behaviour, we suggest doing research on their usage and post-usage behaviours.

The findings will assist service providers and legislators in determining critical variables and influencing students' incentives to use ChatGPT in educational settings that use constructivist teaching methods. As a result, the information will assist service providers in creating AI chatbots that are more user-friendly, visually appealing, efficient, safe and convenient for education. Governments, in conjunction with service providers, have the potential to significantly accelerate the adoption of AI-based chatbots by highlighting their ethical and sustainable use. The findings demonstrate that students' ITU towards ChatGPT is substantially impacted by PU and PEoU. It is recommended that service providers emphasize the advantages and ease of use of AI chatbots in order to draw new clients. Additionally, in order to promote ChatGPT or related technologies, marketers should concentrate on raising the technology’s perceived novelty value. This is because people are open to new technologies as long as they believe they are interesting and innovative.

ChatGPT is an advanced AI-powered chatbot that has the potential to advance and revolutionize the learning and teaching process. This study attempted to look at the elements that lead students to want to use ChatGPT from an academic standpoint by combining the UGT and TAM. For practitioners, academics and educators, the findings provide a solid knowledge of and encouragement for the sustainable use of such AI tools. Despite having important practical consequences, the study contains a number of limitations that indicate possible research gaps that should be filled by further investigation.

The study aimed to test the validity and reliability of the Polish version of the identity leadership inventory (ILI) proposed by Steffens, Haslam, Reicher et al. (2014) and to confirm the relationship between identity leadership and various job-related outcomes (i.e., trust in leaders, job satisfaction, work engagement and turnover intentions) among employees from Poland-based organizations. Identity leadership appears to be a universal construct (van Dick, Ciampa, & Liang, 2018) but no one has studied it in Poland so far.

The sample consisted of 1078 employees collected in two independent subsamples from different organizations located in Northern and Central Poland. We evaluated the ILI’s factorial structure using confirmatory factor analysis.

The results confirm that the 15-item Polish version of the ILI has a four-dimensional structure with factors representing prototypicality, advancement, entrepreneurship and impresarioship. It showed satisfactory reliability. The identity leadership inventory-short form (four items) also showed a good fit with the data. As expected, the relationships between identity leadership and important work-related outcomes (general level of job satisfaction, work engagement, trust toward the leader and turnover intentions) were also significant.

Despite the cultural specifics of Polish organizations, the research results were generally very similar to those in other countries, confirming the universality of the ILI as shown in the Global Identity Leadership Development project (GILD, see van Dick, Ciampa, & Liang, 2018; van Dick et al., 2021).

We aimed to determine how remote management support (MS) practices and staff diversity influenced employee performance (EP) within the digital workplace (DW) during the COVID-19 pandemic. The article highlights the challenges managers face in achieving EP in the DW compared to traditional work environments.

We developed a theoretical model (MS→DW→EP) and tested it based on the computer-assisted web interview (CAWI) conducted in mid-2022. Factors of primary, secondary and organizational diversity moderated the relationship between the variables. We purposely selected a sample of 1,000 respondents with remote working experience.

The results show that the DW partially mediates the relationship between MS and EP. The greater the uncertainty in managing people, the more flexibility, trust and job satisfaction required in the DW to achieve EP. Organizational diversity influenced the model more (i.e. teamwork vs individual work) than the primary and secondary diversity (i.e. gender and education).

Although the sample size was large, we cannot consider it statistically representative.

Zoomers and Millennials reflect full mediation in the model that supports EP.

Broader work autonomy, smaller organizations and teams as well as hybrid work arrangements, reduce the necessity for in-person meetings with superiors.

Supervisors had to reduce control over the DW while expanding organizational citizenship behavior (OCB) to enhance job satisfaction and thus ensure the expected EP during the pandemic. We may consider allowing an employee to postpone work as a new managerial activity within MS.

Although legislation and regulations form an important foundation for recordkeeping and for accountability, questions of transparency and openness must be addressed in a wider context. Oliver and Foscarini have argued for the importance of recognising differing cultures and the ways in which they value records and recordkeeping. In addition to reporting mechanisms and relationships, accountability must encompass a culture and a mindset which is transparent, responsive and focused on self-improvement. This paper aims to apply a dual interpretation of accountability in the context of Irish public sector recordkeeping to identify shortcomings and suggest potential remedies with a view to improving the accountability of Irish recordkeeping itself, and the extent to which it contributes to wider accountability in society.

This paper assesses accountability in Irish public sector recordkeeping using a model suggested by Mark Bovens, which views accountability as both a mechanism and a virtue. The model emphasises that both interpretations are necessary but that mechanisms (laws, regulations and checklists) on their own cannot be sufficient to satisfy accountability requirements. As noted by Onora O’Neill, the aim of accountability should not be checklists or artificial metrics, but the nurturing of behaviours and cultures which make public institutions more deserving of our trust. Reference will be made to Irish legislation, to records management policies in government departments, to relevant annual reports and to current practice with regard to appraisal and other recordkeeping functions to measure Irish public sector recordkeeping against Bovens' model.

This paper suggests that Irish public sector recordkeeping has a range of shortcomings under both the narrow (mechanism) and broad (virtue) interpretations of accountability. Lack of reporting requirements and oversight mechanisms in existing legislation allows for major gaps in public sector recordkeeping, facilitating a lack of accountability in the citizen–state relationship. Meanwhile, an absence of records management policies and an overall lack of appreciation of the value of records leads to opaque practices and a lack of transparency. The recordkeeping profession itself adopts processes and practices, which are not aligned with the concept of accountability as a virtue, and which do not reflect a commitment to transparency and meeting the legitimate interests of stakeholders. This paper suggests changes in relevant legislation but also suggests that these must be accompanied by a more open and responsive working culture within the recordkeeping profession.

By applying Bovens’ dual concept of accountability, this paper provides a new and more comprehensive assessment of public sector recordkeeping in Ireland, which can equally be applied in other contexts. It identifies ways in which revised legislation can contribute to greater accountability, but emphasises that regulations must be accompanied by a culture of transparency and responsiveness, and that recordkeepers have a crucial role to play in terms of their own commitment to transparency and professional accountability.

Recognizing the importance of Robo-advisors in digital financial services, this paper aims to analyse the users’ perception and acceptability of artificial intelligence (AI) in digital investment solutions using an extended “Technology Acceptance Model” (TAM).

The model is tested using 454 online valid responses received from Indian Fintech users via direct path analysis, mediation and moderation.

The study’s findings show that trust, perceived usefulness and perceived risk all significantly impact users’ attitudes towards Robo-advisors. In contrast, ease of use and social influence did not impact users’ attitudes statistically. Furthermore, the results indicate that their attitudes and ease of use influence users’ intentions to adopt Robo-advisors. Moreover, the moderation effect of gender partly supports the overall model. Specifically, in the path between attitudes and their antecedents, gender plays a role in influencing the relationships among these variables. This aligns with preliminary research in the field, providing additional insight into how gender may moderate the factors influencing users’ attitudes and intentions regarding Robo-advisory services.

This research study also reveals that trust, perceived risk, ease of use and demographic factors influence the adoption of Robo-advisory services. It is functional, but its sample selection is not probabilistic and overly emphasizes gender. Future research should use probabilistic sampling, other demographic factors and experience and situational factors. Also, it is necessary to examine how convenient and satisfying it is to communicate with service providers. Filling these gaps will improve the knowledge of consumer behaviour in the context of Fintech adoption and develop the current research.

This study posits that perceived usefulness, trust, perceived risk and ease of use remain core determinants of adopting Robo-advisory services. So, to improve the level of trust of users, it is necessary to develop security measures, data clarity and quality and customer support. Enhancing ease of use by incorporating better interface gestures is always beneficial for increasing the number of users and their level of satisfaction. As identified in previous studies, practical solutions will be achieved by pursuing the increased use of technology while leveraging AI for personal services and minimizing perceived risks, which will strengthen more advanced security measures as well as sufficiently clear communication.

The paper aims to extend the TAM by incorporating measures of trust and social influence to identify the factors that drive the adoption of Robo-advisors. In doing so, the paper may contribute to developing a more comprehensive understanding of the factors that shape consumers’ attitudes and intentions towards these technologies. Moreover, the paper appears to examine the moderating effect of gender on attitude and its predictors, which could provide insights into how gender characteristics may impact the adoption of Robo-advisors.

This study aims to analyze the attitude of consumers toward the recycling process, especially toward the manner of its promotion through social media platforms.

Using social media analysis, the authors analyzed the posts on the RetuRO page on Facebook. The results showed us that the first posts started in January, the recycling program and the guarantee return systems implementation have been active in the stores since November 30. Thus, the posts from each month were analyzed, observing that at the beginning of the program, the posting frequency was higher (8–10 posts/month), whereas in 2024, the frequency registered a slight decrease.

This paper reflects two facets of consumer attitudes: if at the beginning of the recycling program, the feeling expressed was one of delight and satisfaction because customers had the opportunity to get rid of plastic or glass packaging, respectively aluminum cans, thus contributing to protecting the environment, with the development of the program, their opinions changed. The problems generated by the difficulty of recycling, and the technically deficient aspects of the devices led to a paradigm shift and the manifestation of a negative component of consumer attitudes.

To the best of the authors’ knowledge, this study is the first carried out in Romania that analyses the influence of the RetuRO platform in the recycling process carried out in our country using social media analysis.

This paper seeks to evaluate the factors that contribute to congestion at port entrances, propose a comprehensive approach to managing port gates that addresses the factors causing traffic jams and assess the outcomes of resolving the issue through an optimal model for incoming container truck traffic.

The study employed a one-way ANOVA and a one-way MANOVA to examine the impact of congestion-causing factors on the waiting time of trucks in each lane at the entrance gate. The purpose of this was to comprehend the intricate issue and demonstrate the outcomes of the resolution. We used the identified factors that were causing congestion to develop a management strategy for the port gate. As part of this strategy, we implemented a policy where traffic flows in the opposite direction in certain lanes. The Simulation of Urban Mobility program introduced the microscopic traffic simulation model as a discrete event simulation.

The examination of variables influencing the congestion at the port entrance revealed that there were four factors contributing to the congestion: (1) the quantity of lanes; (2) the level of bookings; (3) the factors related to the traffic signal cycle and (4) the assignment of lane types. The one-way MANOVA analysis of the three factors yielded significant evidence for a single pair of interactions. (1) The factors to consider are the quantity of lanes, the level of booking and the assignment of lane types. If the entrance to the rear alley consists of two lanes with a width of 1.85 at the 50% capacity level, and if the critical value of the uneven queue coefficient is reached, it can result in a maximum reduction of the average waiting time by 15.02%.

This study is unique because it examines the surrounding environment and operational behavior of the port to identify how individual and group congestion factors interact. It uses various statistical tools to determine the allocation of the number of port entrances with a reversible lane policy and appointment level. Additionally, it analyzes the detailed results using microscopic traffic simulation modeling. The established foundational model can assist operators in simulating the queue length and mean waiting time of trucks for this specific waiting line in other ports with comparable entrance characteristics.