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The case study draws on structured interviews with Rob Chase, Founder and CEO of NewGen Surgical, as well as secondary data sources to analyze the effectiveness of these solutions in mitigating the risks and enhancing the company’s competitive advantage.

This case study examines how NewGen Surgical, a small- to medium-sized medical equipment manufacturer based in the USA, navigates a supply chain crisis caused by post-pandemic (COVID-19) supply and demand distress, trade restrictions, and the US–China trade war in 2022. It outlines the journey of CEO and Founder, Robert Chase, as he started, grew and is maintaining the company and its various challenges. The case study reviews the risks and vulnerabilities of the company, which heavily relies on Chinese suppliers for most of its operations. To address the supply chain challenges, the case study explores alternative solutions such as insourcing, reshoring, diversifying the supplier base, changing safety stock and implementing new technologies. The case can be designed to teach business courses such as global business, supply chain and entrepreneurship.

This case study is intended for undergraduate and graduate students in courses such as global business, supply chain and entrepreneurship. In addition, this case study may be incorporated with modules on learning organizations, knowledge management and entrepreneurship to aid students in comprehending the principles of global sourcing, offshoring and supply chain management.

This historical example of the creation of the arms industry in the Connecticut River Valley in the 1800s provides new insights into the value of government venture capital (GVC) and government demand in creating a new industry. Since current theoretical explanations of the best uses of governmental venture capital are still under development, there is considerable need for further theory development to explain and predict the creation of an industry and especially those industries where failures in private capital supply necessitates governmental involvement in new firm creation. The purpose of this paper is to provide an in depth historical review of how the arms industry evolved spurred by GVC and government created demand.

This study uses abductive inference as the best way to build and test emerging theories and advancing theoretical explanations of the best uses of GVC and governmental demand to achieve socially required outcomes.

By observing this specific historical example in detail, the authors add to the understanding of value creation caused by governmental venture capital funding of existing theory. A major contribution of this paper is to advance theory based on detailed observation.

The relatively limited research literature and theory development on governmental venture capital funding and the critical success factors in startups are enriched by this abductive investigation of the creation of the historically important arms industry and its spillover into creating the specialized machine industry.

There is a dearth of knowledge regarding how user dependency offers valuable resources to develop the intellectual capital of social streaming apps (SSAs) companies. This study aims to integrate major conceptual components of the UandD model, identify contextualized goal-oriented SSA dependency and empirically evaluate their interrelated user-dependency relationships in the SSA context.

A mixed-methods approach was utilized in this study. First, user gratifications were elicited through a qualitative approach, considering the exploratory stage of the SSA phenomenon. Second, statistical methods were applied to investigate and extract the sub-dimensions of SSA dependency. At last, a research model was developed grounded on the UandD model and empirically validated using the quantitative approach.

The results validated the gratification-dependency-attitude-behavior relationships hypothesized by the UandD framework in SSA. The role of user-SSA dependency in enhancing intellectual capital in the social media industry has been highlighted in this study.

This research not only provides an opportunity for the UandD model to realize its theoretical potential as envisioned by scholars but also contributes to the scholarship on social streaming apps and media dependency theory by conceptualizing goal-oriented dependency in SSAs.

The research results will guide digital media practitioners to a more nuanced understanding of the relationships between their users and modern digital media apps and thus empower the practitioners to better manage their intellectual capital based on the facilitation of their users’ dependency.

This work is one of the pioneers in contextualizing the UandD model in the SSA field, refining and measuring the SSA dependency and its distinct subdimensions and employing mixed-methods to offer a comprehensive understanding of how user dependency boosts intellectual capital in the SSA industry.

This study responded to calls to investigate the behavioural and social antecedents that produce a highly positive response to AI bias in a constrained region, which is characterised by a high share of people with minimal buying power, growing but untapped market opportunities and a high number of related businesses operating in an unregulated market.

Drawing on empirical data from 225 human resource managers from Ghana, data were sourced from senior human resource managers across industries such as banking, insurance, media, telecommunication, oil and gas and manufacturing. Data were analysed using a fussy set qualitative comparative analysis (fsQCA).

The results indicated that managers who regarded their response to AI bias as a personal moral duty felt a strong sense of guilt towards the unintended consequences of AI logic and reasoning. Therefore, managers who perceived the processes that guide AI algorithms' reasoning as discriminating showed a high propensity to address this prejudicial outcome.

As awareness of consequences has to go hand in hand with an ascription of responsibility; organisational heads have to build the capacity of their HR managers to recognise the importance of taking personal responsibility for artificial intelligence algorithm bias because, by failing to nurture the appropriate attitude to reinforce personal norm among managers, no immediate action will be taken.

By integrating the social identity theory, norm activation theory and justice theory, the study improves our understanding of how a collective organisational identity, perception of justice and personal values reinforce a positive reactive response towards AI bias outcomes.

This study aims to expand understanding of the diversity of virtual influencer forms by investigating their nonhuman-like, animal and graphic or cartoon variations.

A three-year multisite longitudinal netnography studied 174 virtual influencers and spanned ten social media platforms. Typological categories were constructed from the data set, focusing on 14 influencers located across quadrants. In-depth findings were then developed for eight illustrative cases.

Findings deepen the knowledge of the virtual influencer sphere by highlighting diversity in human-like, nonhuman-like, imaginative and realistic forms. The authors postulate four types of virtual influencers: hyper-human, antihuman, pan-human and alter-human. These forms are linked to specific personalities and communication styles, addressing various consumer needs. Imaginatively represented virtual influencers may prompt audiences to reevaluate beliefs, values and behaviors. These findings challenge prior work’s focus on attractive, hyperreal and human-like virtual influencers, encouraging consideration of divergent types engaged in novel meaning-shaping activities and targeting different segments.

This research paves the way for consumer and marketing researchers and practitioners to broaden their representations of virtual influencers beyond the human-like, beyond the commercial and into new worlds of fantasy, imagination and posthuman possibility.

Different types of virtual influencers speak to diverse audiences and convey marketing messages in subtly different ways. Some forms of virtual influencers fit into roles like defiant voices, oppositional characters, activists, educators, entertainers and change leaders. As the universe of virtual influencers diversifies, this research opens new avenues of marketing for brands.

This study pioneers comprehensive qualitative research across the universe of virtual influencers and their communities, exploring links to popular culture. It offers connections between virtual influencer forms and communication strategies for marketers.

As more firms adopted AI-related services in recent years, AI service failures have increased. However, the potential costs of AI implementation are not well understood, especially the effect of AI service failure events. This study examines the influences of AI service failure events, including their industry, size, timing, and type, on firm value.

This study will conduct an event study of 120 AI service failure events in listed companies to evaluate the costs of such events.

First, AI service failure events have a negative impact on the firm value. Second, small firms experience more share price declines due to AI service failure events than large firms. Third, AI service failure events in more recent years have a more intensively negative impact than those in more distant years. Finally, we identify different types of AI service failure and find that there are order effects on firm value across the service failure event types: accuracy > safety > privacy > fairness.

First, this study is the initial effort to empirically examine market reactions to AI service failure events using the event study method. Second, this study comprehensively considers the effect of contextual influencing factors, including industry type, firm size and event year. Third, this study improves the understanding of AI service failure by proposing a novel classification and disclosing the detailed impacts of different event types, which provides valuable guidance for managers and developers.

Social media platforms have matured into significant arenas for moral conflict and often intense confrontation between brands and their consumers. This research aims to scrutinize the strategic development of a fresh brand entity deliberately detached from its morally compromised corporate parent, intended to reshape public perceptions and elude regulatory scrutiny.

Promoted as a center for transformative dialogue and innovation, Mission Winnow by Philip Morris is a novel example of a brand creating an entirely separate brand entity to provide sponsorship, and to associate itself with new brand values. This study employs a multisited netnography through which the posts and conversations on Mission Winnow’s platform and website hub are captured and interpreted, as well as the branded content and the free flows of consumers’ conversations generated around the brand on social media.

Findings reveal a broad interchange of moral controversy, acceptance and opposition discourses on social media. When consumers’ acceptance narratives gain traction, consumers extend their support toward the new brand entity, employing strategies that echo moral rationalization and decoupling. When resistance narratives dominate, consumers consciously draw connections between the decoupled brand and the parent brand’s immoral behavior.

This study expands upon prior research into brand activism and consumers’ moral reasoning toward controversial brands, linking the notion of brand decoupling to brand activism discourse and introducing key underexplored aspects like the power of imagery, linguistic creativity and nostalgia. Moreover, it presents significant implications for a more nuanced understanding of the important interrelationship of brand decoupling and recoupling on social media.

Modern warfare and modern battlefield are very demanding. The recent conflicts showed that the usage of the helicopters is very limited and only the best constructions are able to provide support for the operations. The purpose of this research is to show the possibilities of new design tool for main rotor aerostructural optimization. It is a next chapter of the research that is aimed at finding new solutions for rotorcraft constructions.

This work presents a method of preliminary structure optimization of the main rotor blade using parametric modeling. It is the next step in the main rotor optimization studies. It is the next step after preparing the parametric model for the external shape CFD analysis. As a basis for parametric blade structure calculations, the analytical model is provided in this paper. The equations of rigid blade loads and, as a consequence of the strength elements, stresses are shown. The parametric blade modeling is conducted using the Graphic Integrated Programming language. The parametric design method is shown to be used for various blade planform models and different section airfoils. The structure of a blade is generated automatically after the user enters the parameters. The code-inbuilt analysis systems provide a quick inertia examination of the generated geometry, which is the basis for further optimization. The program calculates the blade loads and verifies them with the given material conditions and proposed safety factors. In the analysis, composite materials for the strength elements were proposed.

The results of this research showed the application of parametrization into the main rotor blade design loop. It was presented that the main rotor blade structure can be enhanced using fluid-structure interaction (FSI) methods. The time saving with the implementation the process into design loop is shown.

This work can be practically used in the main rotor blade design process. It provides the possibilities to check various blade aerodynamic configuration in a structure strength aspect.

To the best of the authors’ knowledge, there were no published research that combines the main rotor FSI analysis. The method, which is presented in the work, provides a new approach to a rotorcraft design. The application of the parametrization and combining it with the FSI method gives a novel solution for helicopters construction enhancement.

The paper examines whether special purpose governments follow the pecking order model when raising capital, replacing firm equity in the original model with local intergovernmental revenues. Special purpose governments are a relatively underexamined component of state and local governments, and their capital structure choices have important implications for America’s aggregate fiscal health. This paper seeks to illuminate special purpose governments’ choices among available forms of capital.

To address our research inquiry regarding whether special-purpose governments adhere to the pecking order theory, we narrow our focus to a specific group of transit entities. Our investigation utilizes data sourced from two distinct repositories: the United States Census of Governments and the National Transit Database. To facilitate integration of these disparate datasets, we establish a correspondence between them using the Federal Information Processing Standard and the transit identification number. Initially, our analysis employs maximum likelihood estimation, comparing these estimates to those generated by a naïve model. Subsequently, we derive parameter estimates through the application of a bivariate probit model.

The paper supports the pecking order hypothesis where internal funds are consumed first, debt is consumed next and IGR is consumed last. The results are robust and are not influenced by simultaneity bias.

The paper uses transit special purpose governments as the special purpose government of interest. These transit special purpose governments have high fixed costs that may inform their capital structure decisions relative to non-transit special purpose governments. Additionally, transit special purpose governments often have a profit-maximizing objective that may not uniformly apply to other special purpose governments, such as school districts, who lack such an incentive.

Our research should grab the attention of state and local politicians, voters, policy experts and scholars. Special-purpose governments, a key part of our governmental system, are on the rise. Understanding them better can guide decision-making on how to allocate resources, set policies and plan strategically. This knowledge boosts financial reporting quality, transparency, accountability and public confidence. Journalists can leverage our findings to ensure accurate and thorough reporting, fostering accountability and trust. Additionally, debt markets and analysts can factor this information into their risk assessments.

The paper enhances our understanding of how special purpose governments interact with existing models of corporate finance when making capital structure decisions.

Fashion brands, including fast and luxury segments, receive harsh criticism for engaging in unethical practices such as poor working conditions and environmental damage. As a result, fashion supply chains are pressured by stakeholders to publicly disclose internal supply chain performance information and to show a high level of supply chain transparency. This paper compares supply chain transparency in fast and luxury fashion in Europe.

By applying the maturity curve of fashion supply chain transparency, developed by Muratore and Marques (2022), the websites of 20 fast and 20 luxury fashion brands were analysed and classified as Opaque, Translucent or Transparent.

Despite its reputation, fast fashion demonstrated higher levels of transparency than luxury fashion. Luxury fashion only performed better in terms of the accessibility of sustainability information. Luxury brands avoided disclosing key transparency information, suggesting that they may be operating in contradiction to that which is inferred on their websites.

The findings of the study shed light on the sustainability credentials of the fashion industry, which has the potential to influence the purchase intentions of consumers, particularly millennials and Generation Z. Implications for practice are developed to highlight how fashion can improve its supply chain transparency.