Search results

This study aims to evaluate the performance of LLMs with various prompt engineering strategies in the context of health fact-checking.

Inspired by Dual Process Theory, we introduce two kinds of prompts: Conclusion-first (System 1) and Explanation-first (System 2), and their respective retrieval-augmented variations. We evaluate the performance of these prompts across accuracy, argument elements, common errors and cost-effectiveness. Our study, conducted on two public health fact-checking datasets, categorized 10,212 claims as knowledge, anecdotes and news. To further analyze the reasoning process of LLM, we delve into the argument elements of health fact-checking generated by different prompts, revealing their tendencies in using evidence and contextual qualifiers. We conducted content analysis to identify and compare the common errors across various prompts.

Results indicate that the Conclusion-first prompt performs well in knowledge (89.70%,66.09%), anecdote (79.49%,79.99%) and news (85.61%,85.95%) claims even without retrieval augmentation, proving to be cost-effective. In contrast, the Explanation-first prompt often classifies claims as unknown. However, it significantly boosts accuracy for news claims (87.53%,88.60%) and anecdote claims (87.28%,90.62%) with retrieval augmentation. The Explanation-first prompt is more focused on context specificity and user intent understanding during health fact-checking, showing high potential with retrieval augmentation. Additionally, retrieval-augmented LLMs concentrate more on evidence and context, highlighting the importance of the relevance and safety of retrieved content.

This study offers insights into how a balanced integration could enhance the overall performance of LLMs in critical applications, paving the way for future research on optimizing LLMs for complex cognitive tasks.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-02-2024-0111

This study aims to examine the status of personality dysfunction and its sociodemographic and psychological correlates among university students in Jordan.

This study used a cross-sectional, descriptive-correlational design. It was conducted in Jordan targeting 440 university students using a structured format of online survey during the period January to February 2024. Academic anxiety, loneliness, personality dysfunctions and self-esteem were the used measures in this study.

Students had moderate levels of global personality dysfunction, low to moderate levels of perception of self-esteem toward themselves, moderate to high levels of academic stress and moderate levels of loneliness. The analysis showed a significant and positive association between academic year and personality dysfunction (p = 0.004). On the contrary, no significant relationship was detected between GPA and personality dysfunction (p = 0.073). Using regression analysis, the model that included all the variables was significant (F _6,439 = 8.67, p < 0.001). In this model, the analysis showed that loneliness in the relationship with family (B = 2.08, p < 0.001) and loneliness due to friendship (B = 1.20, p = 0.035) are significant risk factors for developing personality dysfunctions.

One limitation of this study is related to the sample and the setting. The use of an online survey and convenience sampling techniques resulted in underrepresentation of the entire types of universities.

The research provides empirical insights into the association between personality dysfunction among university students and feelings of loneliness, which vary depending on students academic level. Additionally, academic anxiety and self-esteem were found to be associated with or predictive of personality dysfunctions among students.

The current research enhances our understanding of the factors contributing to personality dysfunctions among university students. Connectedness to family and strong robust binding to friends served as protective against personality dysfunctions.

This study emphasizes the role of social relationships and psychosocial well-being in enhancing the mental well-being of university students.

The Fourth Industrial Revolution is a prominent area of interest in the field of manufacturing that is bringing about revolutionary changes. In this study, the authors sought to determine whether professionals in academia or industry could have predicted the composition of advanced technologies associated with Industry 4.0 before Germany's Industrie 4.0 policy announcement. The purpose of this paper is to use the process for identifying technologies that can be included in industrial policy to improve national competitiveness in manufacturing.

Relevant documented research from 2000 to 2012 was identified and captured using a systematic literature review. The significant technological advancements during this period were analyzed to determine how technological innovations may have affected predictions about the future of manufacturing. The identified predictions were analyzed using an open-source natural language processing code that clustered relevant topics in the predictions that indicated common themes. The results were then compared to the ideas within “Industry 5.0”.

The results of this study showed that an aggregate analysis of manufacturing predictions would have preemptively revealed the Fourth Industrial Revolution and could have been used to inform industrial policy that could accelerate technology adoption. Also, contrary to popular belief, the popular Industry 5.0 is a sematic exemplification of a concept already embedded within the origins of the Fourth Industrial Revolution.

By examining the provenance of the Fourth Industrial Revolution, lessons are learned that bring light to Industry 4.0 and the measures that can be taken to enable the advancements that it brings. The results of this study show that is would be wise for government policymakers to enact programs that monitor the manufacturing predictions coming out of academia and to analyze them aggregately using natural language processing as a means to identify the next evolutions and revolutions and to mobilize policymakers to enhance outcomes of enacting policy.

Despite high hopes for the realization of Industry 4.0, there has been little discussion about the technological innovations and events that occurred to enable it. To the best of the authors’ knowledge, this is the first study that has determined that an aggregate analysis of manufacturing predictions would have preemptively revealed the Fourth Industrial Revolution. The success of the methodology used in this study has theoretical implications in support of natural language processing (NLP) being used to inform national policy.

The purpose of this study is to examine the influence of stakeholder integration and project complexity on information technology (IT) projects in Kenya. The following research question guided our inquiry: what is the influence of project complexity and stakeholder integration on the performance of IT projects in Kenya?

To advance the current understanding of the effect of stakeholder integration and project complexity on IT projects, multiple regressions were used to predict how project complexity and stakeholder integration influence project performance. Both government-funded and privately funded IT projects from a developing country were examined.

The study found that any project’s complexity and stakeholder integration levels offer a distinctive contribution to its success. Theoretically, the study contributes to linkages between stakeholder integration and project complexity concerning IT project performance. Through the adoption of actionable research and theoretical elaboration, we have shown that the successful execution of IT projects is driven by the successful integration of stakeholders and monitoring the level of complexity at each phase of the project.

The findings of this study add to the burgeoning literature on the performance of IT projects and come with several managerial implications as well. It brings to the fore the concept of stakeholder integration as an essential element of project success. The findings suggest that the inclusion of stakeholder integration into corporate decisions, strategies and policies can be an asset to the production of sustainable competitive advantages needed during the implementation of IT projects in government entities and organisations. As shown in this study, all the above require a collaborative platform allowing for data sharing among diverse stakeholders to ameliorate distrust or lack of information.

The manufacturing industry in Pakistan, like any other industry, promotes sustainability in its supply chain operations. Yet, the scenario is different in the chemical manufacturing sector, which lags in the development and implementation of sustainable development practices and policies to safeguard its long-term viability. Embracing sustainable practices not only fulfills manufacturing needs but also stands out from other companies. Hence, the purpose of this study is to explore the eco-friendly business practices that impact corporate innovation. Organizational size is considered a moderator in the relationship between green practices and corporate innovation.

The quantitative study was conducted to collect the data through convenience sampling techniques. In total, 138 responses were analyzed through the partial least squares method.

The findings reveal that the implementation of green practices increases corporate innovation. Thus, the impact varies based on different organizational sizes. The crux of the organizational strategy relies on the implementation of eco-friendly practices and holding the right size to survive.

The proposed study provides new grounds for the natural resource-based perspective theory and stakeholder theory. Chemical manufacturers can tailor their strategies that accommodate varying resources and capabilities, facilitating more effective implementation of green practices across different companies within the sector.

The paper provides new ground for the natural resource-based perspective theory. More specifically, this study was expected to help chemical manufacturers choose environmentally friendly practices that would help them meet corporate sustainability performance goals through innovation.

This study aims to explore the relationship between loneliness and addiction to smartphones, specifically examining whether gender and place of residence have a moderating effect on this association.

This study conducted a comprehensive investigation to assess the correlation between loneliness and smartphone addiction, focusing on the potential moderating roles of gender and place of residence.

It was found that loneliness significantly contributes to the development of smartphone addiction across various demographics, irrespective of gender and place of residence. The initial hypothesis that gender and place of residence would moderate the relationship between loneliness and smartphone addiction was not supported.

This study advances our understanding of the mechanisms through which loneliness can lead to smartphone addiction, highlighting its role in potentially exacerbating mental health issues like anxiety and depression. The findings underscore the universal impact of loneliness on smartphone addiction, contributing to the broader discourse on mental health and technology use.

This study aims to investigate the regulatory challenges of emerging disruptive Information and Communication Technologies (ICT) in Brazil and the strategies regulators use to address them.

It is an empirical qualitative research on Brazil’s three administrative levels, focusing on the legislative houses’ specialised Science and Technology Committees. It combines archival analysis of public meeting records with elite interviews of parliamentarians and technocrats who participated in Public Hearings in 2019, which results in this paper analysed through the Theory of Communicative Action with a critical stance.

The research reveals that regulatory challenges gain new dimensions by involving discussions about emerging ICT. Factors such as time constraints, rapid technological evolution and widespread adoption compound these challenges, straining the preference for the incremental pace of regulation and the traditional model of specialised regulatory agencies. The research captures some regulators’ values, underlying concerns and perceived necessities for surmounting these challenges. It also outlines the preferred process for ICT regulation, revealing parliamentary assistants and executive intermediate-level specialists as gateways for interest groups’ action.

The study's findings highlight the crucial role of specific actors as gateways to the covert action of interest groups, particularly Big Tech firms. This contribution is significant as it empowers civil society and academia to monitor and mitigate the risk of regulatory capture, thereby promoting a more transparent and equitable regulatory environment.

This research is original in directly engaging with the key figures (lawmakers, legislative assistants and specialised bureaucrats) involved in the critical and timely issue of regulating emerging disruptive technologies.

Children are beginning to socialize as consumers earlier than ever, highlighting the importance of their saving behavior as an effective form of consumer protection. The paper explored the influence of parents, peers, attitudes, knowledge, past behavior, allowance and self-efficacy on saving intention.

With the aim to explore a range of determinants of adolescent saving and to specify the potential mechanisms through which different determinants operate, we adopted a multitheoretical approach based on theories of planned behavior, consumer and financial socialization, and self-efficacy. The paper investigates the formation of the saving intentions on a sample of 1,476 children 10–15 years old in Croatia.

The results indicate strong importance of parental influence and self-efficacy, implying that saving intention among tweens requires a supportive family structure as well as beliefs in the tweens themselves that they are able to save money and face difficulties.

This paper investigates the very nature of saving intention formation at a crucial developmental stage; it investigates the interplay of mechanisms through which determinants of savings operate at that developmental stage; and it explores the age-variance of the mechanism and the interplay of relevant variables, shedding light on the nature of the mechanism of development.

Press reports have indicated that firms frequently underprice restricted stock and employee stock options. I test for underpricing of stock and options.

I examined a sample of 5,333 private firm stock and option issuances between 1985 and 2017. I tested for underpricing using two approaches: assuming investors have no special market-timing ability and assuming instead they have perfect market-timing ability.

I find evidence of widespread stock and option underpricing by private firms before they go public reflecting large discounts that exceed reasonable compensation for lack of marketability. Unreported underpricing is more frequent in the last pre-IPO private equity transactions that offer the last opportunity to give such discounts before the stock is publicly traded, but the discounts are greater in the earlier pre-IPO transactions where unreported discounts are presumably tougher for the SEC to detect. Underpricing is still detected even when the actual DLOMs are tested against a benchmark that assumes investors have perfect market-timing ability.

Firms frequently underprice restricted stock and employee stock options. Firms tend to underprice stock options more frequently than restricted stock, but restricted stock tends to be priced at deeper discounts when recipients are assumed not to have any special market-timing ability.

Private firms issue restricted stock and options as incentive compensation. Lowballing the valuation transfers wealth from outside stockholders to employees/insiders. Wealth transfers take place through the issuance of equity claims to employees/insiders before firms go public. I found that more than a quarter of the DLOMs exceed the theoretical maximum by, on average, between 16% (median) and 20% (mean). This finding raises two questions worthy of investigation. First, to what extent do the frequency and magnitude of DLOMs above the theoretical maximum depend on whether a board of directors obtains an independent appraisal of a stock’s fair market value? Second, if DLOMs above the theoretical maximum are observed even when the stock is independently appraised, how do appraisers justify such large DLOMs?

The wealth transfers that take place through the issuance of equity claims to employees/insiders before firms go public benefit employees/insiders at the expense of outside shareholders.

My paper is the first to furnish evidence of widespread stock and option underpricing by private firms before they go public; demonstrate that the unreported underpricing is more frequent in the last pre-IPO private equity transactions that offer the last opportunity to give such discounts before the stock is publicly traded and show that the discounts are greater in the earlier pre-IPO transactions where unreported discounts are presumably tougher for the SEC to detect.

The rapid growth of 3D printing has transformed the cost-effective production of prototypes and functional items, primarily using extrusion technology with thermoplastics. This study aims to focus on optimizing mechanical properties, precisely highlighting the crucial role of mechanical compressive strength in ensuring the functionality and durability of 3D-printed components, especially in industrial and engineering applications.

Using the Box−Behnken experimental design, the research investigated the influence of layer thickness, wall perimeter and infill level on mechanical resistance through compression. Parameters such as maximum force, printing time and mass utilization are considered for assessing and enhancing mechanical properties.

The layer thickness was identified as the most influential parameter over the compression time, followed by the degree of infill. The number of surface layers significantly influences both maximum strength and total mass. Optimization strategies suggest reducing infill percentage while maintaining moderate to high values for surface layers and layer thickness, enabling the production of lightweight components with adequate mechanical strength and reduced printing time. Experimental validation confirms the effectiveness of these strategies, with generated regression equations serving as a valuable predictive tool for similar parameters.

This research offers valuable insights for industries using 3D printing in creating prototypes and functional parts. By identifying optimal parameters such as layer thickness, surface layers and infill levels, the study helps manufacturers achieve stronger, lighter and more cost-efficient components. For industrial and engineering applications, adopting the outlined optimization strategies can result in components with enhanced mechanical strength and durability, while also reducing material costs and printing times. Practitioners can use the developed regression equations as predictive tools to fine-tune their production processes and achieve desired mechanical properties more effectively.

This research contributes to the ongoing evolution of additive manufacturing, providing insights into optimizing structural rigidity through polylactic acid (PLA) selection, Box−Behnken design and overall process optimization. These findings advance the understanding of fused deposition modeling (FDM) technology and offer practical implications for more efficient and economical 3D printing processes in industrial and engineering applications.