Search results

The purpose of this paper is to explore the potential benefits and challenges of using large language models (LLMs) like ChatGPT to edit Wikipedia.

The first portion of this paper provides background about Wikipedia and LLMs, explicating briefly how each works. The paper's second section then explores both the ways that LLMs can be used to make Wikipedia a stronger site and the challenges that these technologies pose to Wikipedia editors. The paper's final section explores the implications for information professionals.

This paper argues that LLMs can be used to proofread Wikipedia articles, outline potential articles and generate usable Wikitext. The pitfalls include the technology's potential to generate text that is plagiarized or violates copyright, its tendency to produce “original research” and its tendency to generate incorrect or biased information.

While there has been limited discussion among Wikipedia editors about the use of LLMs when editing the site, hardly any scholarship has been given to how these models can impact Wikipedia's development and quality. This paper thus aims to fill this gap in knowledge by examining both the potential benefits and pitfalls of using LLMs on Wikipedia.

This study explored the information practices of cosplayers, as well as the social norms, social types and information infrastructure of an online cosplay Facebook group, the Rey Cosplay Community (RCC).

To better understand individual behavior, the authors made use of ethnographic methods and semi-structured interviews. Observation of the RCC was combined with information gleaned from select participant interviews.

The results suggest that the RCC can be conceived of as an information community where fans obtain and share information about cosplay costume making. Sufficient and well-organized information and positive community culture greatly help community members make their costumes.

This works serves as a bridge between fan studies and information science research in its exploration of online communities, shared information practices and creating non-toxic virtual environments. It also lends support to the idea that positivity, respect for community rules and a tight-knit connection between members play essential roles in building a non-toxic fan and information community.

The purpose of this paper is to develop an EU sociotechnical systems (STSs) map to represent a harmonised concept of operations (CONOPS) as a future development platform for technologies used in multi-services emergency responses to chemical, biological, radiological and nuclear (CBRN) incidents.

AcciMaps were developed to locate where technologies are currently used, and opportunities for new technologies. The AcciMaps were iteratively co-designed with end users (fire, ambulance, police and military) across three EU countries (the UK, Finland and Greece). Data were collected using document analysis and interviews with senior ranking (Gold or Silver Command level) representatives of the participating end users.

Despite differences in terminology and between service sectors, consensus was achieved for the command structures (Gold, Silver and Bronze), and Hot Zone responders (specialist blue light responders and blue light responders (BLR)). A control room was included as the communication spine. BLR activities were limited by their scope of practice and available equipment, for example, breathing apparatus. The harmonised EU AcciMap offers a high-level STSs map of CBRN response. Critical segments have been identified which offer opportunities for technology developments that can add value in terms of response capabilities (e.g. tag and trace).

A large scale major CBRN incident may need cross-border and cross-professional engagement where efficient interoperability is vital. This research is the first EU consensus of a STS map for CONOPS. It supports future research for technology development, e.g., detection and decontamination equipment design and use, communication, diagnosis and response technologies.

When performing system-level developmental testing, time and expenses generally warrant a small sample size for failure data. Upon failure discovery, redesigns and/or corrective actions can be implemented to improve system reliability. Current methods for estimating discrete (one-shot) reliability growth, namely the Crow (AMSAA) growth model, stipulate that parameter estimates have a great level of uncertainty when dealing with small sample sizes. The purpose of this paper is to present an application of a modified GM(1,1) model for handling system-level testing constrained by small sample sizes.

The paper presents a methodology for incorporating failure data into a modified GM(1,1) model for systems with failures following a poly-Weibull distribution. Notional failure data are generated for complex systems and characterization of reliability growth parameters is performed via both the traditional AMSAA model and the GM(1,1) model for purposes of comparing and assessing performance.

The modified GM(1,1) model requires less complex computational effort and provides a more accurate prediction of reliability growth model parameters for small sample sizes and multiple failure modes when compared to the AMSAA model. It is especially superior to the AMSAA model in later stages of testing.

This research identifies cost-effective methods for developing more accurate reliability growth parameter estimates than those currently used.

Analyses of work based learning (such as that offered by Brennan and Little) have typically ignored the issue of ownership of knowledge. Here the authors consider this issue as it relates to accreditation in the UK higher education sector, arguing that the points raised have relevance for the international community. The main argument is that employing organisations are the main beneficiaries of accreditation, and as such universities need to make a much clearer case for work based learning to safeguard learners – and society – from exploitation and the universities from becoming vessels for narrowly defined performance statements, unworthy of higher education.

The article attempts to determine whether academic research in the area of finance has a direct link to the practitioners in the field.

This paper used a survey of over 50 finance practitioners to ask their opinion on the relevance of academic finance journals to their respective jobs.

The results suggest that most business practitioners are more interested in proprietary research than in generally distributed academic research, the academic peer‐review process seems to reduce the interest of practitioners in academic research due to the time lag between the findings of research and their publication, and the statistical significance of academic research results does not interest practitioners as much as the immediate relevance of the research findings to their respective jobs.

A review of the literature suggests this might be one of the first papers to actually test the hypothesis that academic finance research has a direct transference to the finance industry.

The purpose of this bibliometric and systematic literature review is to survey and evaluate key study’s in tacit knowledge (TK). Through analysing and synthesizing based on the antecedents, decisions, outcomes-theories, context and methods (ADO-TCM) framework, this paper highlights research gaps and avenues for future research. It is important to recognize the antecedents, results and theories in the available literature as it offers enough evidence for encouraging the significance of TK.

This research paper follows a bibliometric analysis and systematic approach in identifying, analyzing and synthesizing pertinent literature in TK. A total of 59 research studies were carefully and systematically reviewed with the help of NVivo12 and excel software to code and analyse.

With the help of bibliometric analysis and framework-based systematic review, this research paper offers a retrospective view of the TCM framework in the amalgamation with ADO framework, bibliometric analysis and important themes of TK research.

This paper is different from existing reviews as the authors have to combine bibliometric analysis and framework-based systematic review approach to provide a more robust encapsulation of TK research. To the best of the knowledge, the present research is one of the first systematic reviews based on a framework relating to TK.

The case is designed to be used with the digital business model framework developed by Peter Weill and Stephanie Woerner of Massachusetts Institute of Technology (MIT) (Weill and Woerner, 2015) and is referred to as the W & W framework. This approach provides a useful structure for thinking through the strategic options facing environments ripe for digital transformation.

Research for this case was conducted through face-to-face interviews with the protagonist, as well as through a review of their business planning documents and other data and documentation provided by the founder. Some of the market and industry data were obtained using secondary research and industry reports. Interviews were digitally recorded and transcribed to ensure accuracy.

The case follows the story of Kurt Waltenbaugh, a Minnesota entrepreneur who shared the dream of using data analytics to reduce costs within the US health-care system. In early 2014, Waltenbaugh and a physician colleague founded Carrot Health to bring together their personal experience and expertise in both consumer data analytics and health care. From the beginning, they focused on how to use data analytics to help identify high-risk/high-cost patients who had not yet sought medical treatment. They believed that they could use these insights to encourage early medical interventions and, as a result, lower the long-term cost of care.

Carrot’s initial success found them in a consultative role, working on behalf of insurance companies. Through this work, they honed their capabilities by helping their clients combine existing claims data with external consumer behavioral data to identify new potential customers. These initial consulting contracts gave Carrot the opportunity to develop its analytic tools, business model and, importantly, to earn some much-needed cash flow during the start-up phase. However, they also learned that, while insurance companies were willing to purchase data insights for one-off market expansion projects, it was much more difficult to motivate them to use data proactively to eliminate costs on an ongoing basis. Waltenbaugh believed that Carrot’s greatest potential lay in their ability to develop predictive models of health outcomes, and this case explores Carrot’s journey through strategic decisions and company transformation.

This case is intended for either an undergraduate or graduate course on entrepreneurial strategy. It provides an effective introduction to the unique structure and constraints which apply to an innovative start-up within the health-care industry. The case also serves as a platform to explore the critical criteria to be considered when developing a digital transformation strategy and exposing students to the digital business model developed by Weill and Woerner (2015) at MIT (referred to in this instructor’s manual as the W&W framework). The case was written to be used in an advanced strategy Master of Business Administration (MBA) class, an undergraduate specialty health-care course or as part of a health-care concentration in a regular MBA, Master of Health Care Administration (MHA) or Master of Public Health (MPH). It may be taught toward the end of a course on business strategy when students are building on generic strategy frameworks and adapting their strategic thinking to the characteristics of specific industries or sectors. However, the case can also be taught as part of a course on health-care innovation in which case it also serves well as an introduction to the health-care payments and insurance system in the USA. Finally, the case can be used in a specialized course on digital transformation strategy in which case it serves as an introduction to the MIT W&W framework.

The case is particularly well-suited to students who are familiar with traditional frameworks for business strategy and business models. The analysis builds on this knowledge and introduces students interested in learning about the opportunities and challenges of digital strategy. Equally, the case works well for students with clinical backgrounds, who are interested in how business strategy can influence changes within the health-care sphere. Finally, an important aspect of the case design was to develop students’ analytical confidence by encouraging them to “get their hands dirty” and to carry out some basic exploratory data analytics themselves. As such, the case requires students to combine and correlate data and to experience the potentially powerful combination of clinical and consumer data. Instructors should find that the insights from these activities give students unique insights into the potential for of data analytics to move health care from a reactive/treatment ethos to a proactive/intervention ethos. This experience can be particularly revealing for students with clinical backgrounds who may initially be resistant to the use of clinical data by commercial organizations.

This case examines the public controversy that erupted over the increasingly high price of EpiPens. Mylan Inc. (Mylan), a generic drug maker, bought the EpiPen product line from Merck in 2007. Since that time, the company both invested in marketing to raise awareness for the drug and dramatically increased the price, lifting it from $100 to $600 per two pack in the U.S. In 2016, simmering consumer anger about the high prices of pharmaceutical drugs finally reached a boiling point and a media firestorm ensued. The case challenges students to think about the role of fairness in pricing. How can Mylan justify the dramatic price increases? How can it justify the variation in prices across countries, as an EpiPen is priced at an equivalent of $85 in France? The case challenges students to think about how they would handle a public controversy. The EpiPen case is well suited for students in MBA, MBA for Executives, and executive education programs. For MBA students, it can be placed in first-year marketing, pricing, or marketing communications courses. For executives, it can serve as a vehicle to discuss both ethical issues of pricing and how to handle a public controversy.