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The figure of the female revenger has haunted the western imagination as far back as some of the earliest extant texts, most starkly in Euripides' tragedies Hecuba and Medea (c. 430–420 bc). She has tended to take on one of three forms: the scorned woman, the vengeful mother or the victim of physical violence, almost always sexual violence.

This chapter presents an interdisciplinary and transhistorical understanding of the troubling figure of the violent female revenger in her shifting incarnations. The investigation traces conceptual strands through a variety of cultural texts, focusing on specific instances that are both situated historically and simultaneously analysed for the ways in which they reflect recurring priorities and cultural anxieties through the centuries.

After considering key ideas such as revenge and justice and gender and revenge, the chapter looks more closely at the so-called rape-revenge genre, moving from the earliest examples such as I Spit on Your Grave (1978) to more recent films which are considered for the ways they intersect with the global feminist protest movement #MeToo, and other key cultural moments such as the Harvey Weinstein case and the very public trial of the USA Gymnastics national team doctor Larry Nassar: Revenge (2017), The Nightingale (2018) and Promising Young Woman (2020). The chapter draws direct lines of connection between imaginative works, cultural types and stereotypes, and lived reality in order to come to a fuller understanding of the female revenger.

The metaverse is a virtual world where users can communicate with each other in a computer-generated environment. The use of metaverse technology has the potential to revolutionize the way businesses operate, interact with customers, and collaborate with employees. However, several obstacles must be addressed and overcome to ensure the successful implementation of metaverse technology. This study aims to examine the implementation of metaverse technology in the management of an organization's supply chain, with a focus on predicting potential barriers to provide suitable strategies.

Covariance-based structural equation modeling (CB-SEM) was used to test the model. In addition, artificial neural network modeling (ANN) was also performed.

The CB-SEM results revealed that a firm's technological limitations are among the most significant barriers to implementing metaverse technology in the supply chain management (SCM). The ANN results further highlighted that the firm's technological limitations are the most crucial input factors, followed by a lack of governance and standardization, integration challenges, poor diffusion through the network, traditional organizational culture, lack of stakeholder commitment, lack of collaboration and low perception of value by customers.

Because metaverse technology has the potential to provide organizations with a competitive advantage, increase productivity, improve customer experience and stimulate creativity, it is crucial to discuss and develop solutions to implementation challenges in the business world. Companies can position themselves for success in this fascinating and quickly changing technological landscape by conquering these challenges.

This study provides insights to metaverse technology developers and supply chain practitioners for successful implementation in SCM, as well as theoretical contributions for supply chain managers aiming to implement such environments.

In this study, a new neural differential grey model is proposed for the purpose of accurately excavating the evolution of real systems.

For this, the proposed model introduces a new image equation that is solved by the Runge-Kutta fourth order method, which makes it possible to optimize the sequence prediction function. The novel model can then capture the characteristics of the input data and completely excavate the system's evolution law through a learning procedure.

The new model has a broader applicability range as a result of this technique, as opposed to grey models, which have fixed structures and are sometimes over specified by too strong assumptions. For experimental purposes, the neural differential grey model is implemented on two real samples, namely: production of crude and consumption of Cameroonian petroleum products. For validation of the new model, results are compared with those obtained by competing models. It appears that the precisions of the new neural differential grey model for prediction of petroleum products consumption and production of Cameroonian crude are respectively 16 and 25% higher than competing models, both for simulation and validation samples.

This article also takes an in-depth look at the mechanics of the new model, thereby shedding light on the intrinsic differences between the new model and grey competing models.

This study aims to compare graduate student perspectives of online versus face-to-face (FTF) education during the pandemic at two different universities. One university, the “International University”, was physically located in Korea but served an international base of students, and the other was a Jesuit, Catholic University in the USA.

An online Qualtrics survey was used to gather student perceptions on a five-point Likert scale on individual and program factors. Chi-square analysis using the contingency coefficient as the nominal value was performed to uncover significant differences.

Significant differences between the two groups existed on motivation, discipline, self-directed, independence, cost investment, preference, happiness, difficulty, student-to-student interaction and student-to-instructor interaction. This research has implications for instructors and administrators in identifying shortcomings and highlighting the uniqueness of different practices around the world.

Previous studies on student perceptions have been performed. However, this study is original in the fact that it directly compares two different graduate student populations perspectives of online versus FTF during the pandemic.

The purpose of this paper is to examine the 2015 Union Cycliste Internationale (UCI) Road World Cycling Championship in Richmond, Virginia.

An array of eclectic methods included in situ witness observations of several of the races, 21 semi-structured random interviews and multiple discussions with elements of UCI, the city of Richmond’s planners, residents and business owners during and after the championship in fall 2015.

This paper has uncovered five findings: First, the material investment was considerably smaller than that of other events (common good criterion CGC i – good governance); second, pre-planning was critical to successfully hosting the event; third, this event included not only two entities as one would expect at first glance, but many (common good criterion CGC ii – good management); fourth, a filière approach to community service and the exploitation of clustered thematic activities was of critical importance to successfully hosting the 2015 UCI Road World Cycling Championship; and fifth, this event enabled the opportunity to market other city and regional assets (common good criterion CGC iii – good outcomes).

Cities hoping to bid for events ought to consider hosting unique events such as road championships. Those cities will benefit from careful event pre-planning, responsible event hosting and post-event legacies in the form of socio-economic and mindscape memories.

Bidding and pre-event planning is increasingly seen as an opportunity to locate, create and develop support for common good urban projects, which will remain valuable after the event is over or which will need to be built in spite of the bid’s result.

This study fills an unresearched gap on the impact of events on a city’s future non-motorized sustainable transportation priorities.

This study aims to examine foreign direct investment (FDI) factors and develops a rational framework for FDI inflow in Western European countries such as France, Germany, the Netherlands, Switzerland, Belgium and Austria.

Data for this study were collected from the World development indicators (WDI) database from 1995 to 2018. Factors such as economic growth, pollution, trade, domestic capital investment, gross value-added and the financial stability of the country that influence FDI decisions were selected through empirical literature. A framework was developed using interpretable machine learning (IML), decision trees and three-stage least squares simultaneous equation methods for FDI inflow in Western Europe.

The findings of this study show that there is a difference between the most important and trusted factors for FDI inflow. Additionally, this study shows that machine learning (ML) models can perform better than conventional linear regression models.

This research has several limitations. Ideally, classification accuracies should be higher, and the current scope of this research is limited to examining the performance of FDI determinants within Western Europe.

Through this framework, the national government can understand how investors make their capital allocation decisions in their country. The framework developed in this study can help policymakers better understand the rationality of FDI inflows.

An IML framework has not been developed in prior studies to analyze FDI inflows. Additionally, the author demonstrates the applicability of the IML framework for estimating FDI inflows in Western Europe.

The growth in social content such as video facilitates consumer exposure to social information at e-tail settings. Research has recommended enhancing the e-store socialness. Focusing on focal consumer outcomes (flow and purchase intentions), the current research delineates a boundary condition, proposing that e-tail socialness improves outcomes when the consumer interdependent self, rather than the independent self, is activated.

The experimental approach is employed to test the research thesis. Two experiments (N1 = 303 Females 42.4%; N2 = 387 Females 51.4%) that used different manipulation for socialness and sample frames (USA and Canadian) are performed. Analysis of variance was applied.

The results generally support the research thesis, suggesting that e-tail socialness enhances consumer flow and purchase intentions when the interdependent self is activated. The effect, however, is marginal for segments with high brand preference.

As more information increase overload and reduce decision quality, e-tail practitioners should focus on providing social information predominately for consumers whose interdependent self is activated. This recommendation is particularly relevant for segments with low brand preference.

So far, studies recommend enhancing the e-store socialness, or increasing the social volume, to achieve better outcomes. Such research stream is giving rise to the “social is better in e-tail” conventional wisdom. The current work contributes by delineating a boundary condition based on consumer self-construal. This work suggests that the use of online socialness is fruitful predominantly for interdependent consumers.

Social commerce (SC) is a new genre in electronic commerce (e-commerce) that has great potential. This study proposes a new research framework to address deficiencies in existing social commerce research frameworks (e.g. the information model).

In the era of Industrial Revolution 4.0 technologies and new social commerce (s-commerce) models, the authors believe that there is an immediate need for a new research framework. The authors analysed the progress of the s-commerce paradigm between 2003 and 2023 by applying longitudinal science mapping. The authors then developed a research framework based on the themes in the strategic diagrams and evolution map.

From 2003 to 2010, studies on s-commerce mainly focused on social networking sites, virtual communities, social shopping and analytic approaches. From 2011 to 2015, it shifted to s-commerce, consumer behaviour, Web 2.0, artificial intelligence, social technologies, online shopping, user studies, data gathering methods, applications, service-based social commerce constructs, e-commerce and cognitive factors. Social commerce remained the primary research paradigm from 2017 to 2023.

The SC framework may be analogous to popular research frameworks such as technology-organisation-environment (T-O-E) and stimulus-organism-response (S-O-R). Based on this SC framework, researchers may gain a better understanding by determining the factors of the social, commercial, technological and behavioural dimensions.

The authors redefined s-commerce and developed an SC framework. Practical guidelines for the SC framework and an exemplary research model are presented. Overall, this study offers a new research agenda for the extant understanding of s-commerce, with the SC framework as the next frontier of the theoretical advancements and applications of s-commerce.