Search results

Generative AI and more specifically ChatGPT has brought a revolution in the lives  of people by providing them with required knowledge that it has learnt from an exponentially large knowledge base. In this viewpoint, we are initiating the debate and offer the first step towards Generative AI based knowledge management systems in organizations.

This study is a viewpoint and develops a conceptual foundation using existing literature on how ChatGPT can enhance the KM capability based on Nonaka’s SECI model. It further supports the concept by collecting data from a public sector univesity in Hong Kong to strenghten our argument of ChatGPT mediated knowledge management system.

We posit that all four processes, that is Socialization, Externalization, Combination and Internalization can significantly improve when integrated with ChatGPT. ChatGPT users are, in general, satisfied with the use of ChatGPT being capable of facilitating knowledge generation and flow in organizations.

The study provides a conceptual foundation to further the knowledge on how ChatGPT can be integrated within organizations to enhance the knowledge management capability of organizations. Further, it develops an understanding on how managers and executives can use ChatGPT for effective knowledge management through improving the four processes of Nonaka’s SECI model.

This is one of the earliest studies on the linkage of knowledge management with ChatGPT and lays a foundation for ChatGPT mediated knowledge management system in organizations.

Conversations around diversity, race and science fiction and fantasy films/television have sparked in response to recent casting decisions made in the upcoming live-action The Little Mermaid, The Lord of the Rings: The Rings of Power and Star Wars' Obi-Wan Kenobi (Deggans, 2022; Romano, 2022). Backlash against casting of actors of Color in these genres highlights racial projects where a cultural memory of whiteness comes up against multicultural change. The authors of this paper feel that there is great potential in using current-day racial issues around fantasy films/television to explore these racial projects with students in social studies classes (Omi and Winant, 2014).

Using a qualitative textual analysis (Peräkylä, 2005), the authors examined online news media outlets addressing the casting of actors of Color in the aforementioned media pieces. After reviewing over twenty articles, the authors determined two major themes that would serve as the findings.

In this paper, themes of nostalgia for an imagined ‘way things were’ and future-based fears of how things will become emerged from the analysis, revealing a need for engaging students in the history of sci-fi and fantasy media, and the existing, diverse histories of storytelling featuring multiple races.

The authors argue that examining racial projects found in contemporary sci-fi and fantasy casting are chances for students to understand complex racial histories and how they blend into current-day cultural landscapes, and are opportunities to practice analysis of real-life racial histories and richly-imagined fantasy worlds, noticing how and why the two often collide when it comes to race.

Properly planned road illumination systems are collectively a public wealth and the commissioning of such systems may require extensive planning, simulation and testing. The purpose of this simulative work is to offer a simple approach to facilitate luminance-based road lighting calculations that can be easier to comprehend and apply to practical designing problems when compared to complex multi-objective algorithms and other convoluted simulative techniques.

Road illumination systems were photometrically simulated with a created model in a validated software platform for specified system design configurations involving high-pressure sodium (HPS) and light-emitting diode (LED) luminaires. Multiple regression analyses were conducted with the simulatively obtained data set to propound a linear model of estimating average luminance, overall uniformity of luminance and energy efficiency of lighting installations, and the simulatively obtained data set was used to explore luminaire power–road surface average luminance characteristics for common geometric design configurations involving HPS and LED luminaires, and four categories of road surfaces.

The six linear equations of the propounded linear model were found to be well-fitted with their corresponding observation sets. Moreover, it was found that the luminaire power–road surface average luminance characteristics were well-fitted with linear trendlines and the increment in road surface average luminance level per watt increment of luminaire power was marginally higher for LEDs.

This neoteric approach of estimating road surface luminance parameters and energy efficiency of lighting installations, and the compendia of luminaire power–road surface average luminance characteristics offer new insights that can prove to be very useful for practical purposes.

This study aims to investigate the effects of the number of miss stitches and tuck stitches in the knit structure on the technological parameters and physical and mechanical properties of knitted fabrics.

The number of miss stitches and tuck stitches was increased from 3.6% to 8.3%, and the influence of this increase on knitwear properties was analyzed.

It was found that an increase from 3.6% to 8.3% leads to a decrease in the stretchability of knitwear in width from 330% to 290% and in length from 112% to 95%. With an increase from 5% to 6.3%, the surface density of knitwear decreases by 11.6 g. And with an increase from 6.3% to 8.3%, the surface density of knitwear decreases by 11.8 g. It was also found that the presence of miss stitches and tuck stitches in the knit structure reduces the material consumption, and the presence of miss stitches increases the shape stability of the knitted fabric.

It was concluded that the number of miss stitches and tuck stitches has the strongest influence on surface density, followed by volume density.

This study proposes a novel method utilising a speech-word pair bipartite network to examine the correlation structure between members of parliament (MPs) in the context of the UK- China relationship.

We construct MP-word pair bipartite networks based on the co-occurrence relationship between MPs and words in their speech content. These networks are then mapped into monopartite MPs correlation networks. Additionally, the study calculates correlation network indicators and identifies MP communities and factions to determine the characteristics of MPs and their interrelation in the UK-China relationship. This includes insights into the distribution of key MPs, their correlation structure and the evolution and development trends of MP factions.

Analysis of the parliamentary speeches on China-related affairs in the British Parliament from 2011 to 2020 reveals that the distribution and interrelationship of MPs engaged in UK-China affairs are centralised and discrete, with a few core MPs playing an integral role in the UK-China relationship. Among them, MPs such as Lord Ahmad of Wimbledon, David Cameron, Lord Hunt of Chesterton and Lord Howell of Guildford formed factions with significant differences; however, the continuity of their evolution exhibits unstableness. The core MP factions, such as those led by Lord Ahmad of Wimbledon and David Cameron, have achieved a level of maturity and exert significant influence.

The research has several limitations that warrant acknowledgement. First, we mapped the MP-word pair bipartite network into the MP correlation network for analysis without directly analysing the structure of MPs based on the bipartite network. In future studies, we aim to explore various types of analysis based on the proposed bipartite networks to provide more comprehensive and accurate references for studying UK-China relations. In addition, we seek to incorporate semantic-level analyses, such as sentiment analysis of MPs, into the MP-word -pair bipartite networks for in-depth analysis. Second, the interpretations of MP structures in the UK-China relationship in this study are limited. Consequently, expertise in UK-China relations should be incorporated to enhance the study and provide more practical recommendations.

Firstly, the findings can contribute to an objective understanding of the characteristics and connotations of UK-China relations, thereby informing adjustments of focus accordingly. The identification of the main factions in the UK-China relationship emphasises the imperative for governments to pay greater attention to these MPs’ speeches and social relationships. Secondly, examining the evolution and development of MP factions aids in identifying a country’s diplomatic focus during different periods. This can assist governments in responding promptly to relevant issues and contribute to the formulation of effective foreign policies.

First, this study expands the research methodology of parliamentary debates analysis in previous studies. To the best of our knowledge, we are the first to study the UK-China relationship through the MP-word-pair bipartite network. This outcome inspires future researchers to apply various knowledge networks in the LIS field to elucidate deeper characteristics and connotations of UK-China relations. Second, this study provides a novel perspective for UK-China relationship analysis, which deepens the research object from keywords to MPs. This finding may offer important implications for researchers to further study the role of MPs in the UK-China relationship.

This study proposes a novel scheme for analysing the correlation structure between MPs based on bipartite networks. This approach offers insights into the development and evolving dynamics of MPs.