Search results

This paper aims to investigate how best to classify money laundering through online video games (i.e. virtual laundering). Currently, there is no taxonomy available for scholars and practitioners to refer to when discussing money laundering through online video games. Without a well-defined taxonomy it becomes difficult to reason through, formulate and implement effective regulatory measures, policies and security controls. As such, efforts to prevent and reduce virtual laundering incidence rates are hampered.

This paper proposes three mutually exclusive virtual laundering categorizations. However, instead of fixating on the processes undergirding individual instances of virtual laundering, it is argued that focusing on the initial locale of the illicit proceeds provides the appropriate framing within which to classify instances of virtual laundering. Thus, the act of classification becomes an ontological endeavour, rather than an attempt at elucidating an inherently varied process (as is common of the placement, layering and integration model).

A taxonomy is proposed that details three core virtual laundering processes. It is demonstrated how different virtual laundering categories have varied levels of associated risk, and thus, demand unique interventions.

To the best of the authors’ knowledge, this is the first taxonomy available in the knowledge base that systematically classifies instances of virtual laundering. The taxonomy is available for scholars and practitioners to use and apply when discussing how to regulate and formulate legislation, policies and appropriate security controls.

This paper aims to propose the mechanism of cross-network effect embedded, which can help cross-border e-commerce (CBEC) platforms strengthen cooperative relationships with sellers more equitably and effectively by using the network structural characteristics of the platforms themselves.

A two-stage evolutionary game model has been used to confirm the influence factors. The mathematical derivation of evolutionary game analysis is combined with the simulation method to examine the role of cross-network effect in cooperation. The evolutionary game model based on the cross-network effect is proposed to achieve better adaptability to the study of cooperation strategy from the two-sided market perspective.

The evolutionary game model captures the interactions of cross-network effect and the influence factors from a dynamic perspective. The cross-network effect has a certain substitution on the revenue-sharing rate of SMEs. CBEC platforms can enhance the connection between consumers and the website by improving the level of construction, which is a good way to attract sellers more cost-effectively and efficiently.

This study provides a new method for the validation of the cross-network effect, especially when data collection is difficult. But this method is only a numerical simulation. So the conclusions still need to be further tested empirically. Besides, researchers are advised to explore the relationship between the added user scale and the cross-network effect in some specificCBEC platforms.

This study provides a new method for the validation of the cross-network effect, especially when data collection is difficult. But this method is only a numerical simulation. So the conclusions still need to be further tested empirically. Besides, researchers are advised to explore the relationship between the added user scale and the cross-network effect in some specific CBEC platforms.

Investigations that study cooperation strategy from the cross-network effect perspective in CBEC are limited. The research figured out which influence factors are affected by the cross-network effect in cooperation. A two-stage evolutionary game model was proposed to explain the interaction of the factors. The evolutionary game analysis with a simulation method was combined to highlight the role of cross-network effect on cooperation strategy to give a deeper investigation into the sustainable cooperation ofCBEC.

The purpose of this paper is to give an overview of artificial intelligence (AI) and other AI-enabled technologies and to describe how COVID-19 affects various industries such as health care, manufacturing, retail, food services, education, media and entertainment, banking and insurance, travel and tourism. Furthermore, the authors discuss the tactics in which information technology is used to implement business strategies to transform businesses and to incentivise the implementation of these technologies in current or future emergency situations.

The review provides the rapidly growing literature on the use of smart technology during the current COVID-19 pandemic.

The 127 empirical articles the authors have identified suggest that 39 forms of smart technologies have been used, ranging from artificial intelligence to computer vision technology. Eight different industries have been identified that are using these technologies, primarily food services and manufacturing. Further, the authors list 40 generalised types of activities that are involved including providing health services, data analysis and communication. To prevent the spread of illness, robots with artificial intelligence are being used to examine patients and give drugs to them. The online execution of teaching practices and simulators have replaced the classroom mode of teaching due to the epidemic. The AI-based Blue-dot algorithm aids in the detection of early warning indications. The AI model detects a patient in respiratory distress based on face detection, face recognition, facial action unit detection, expression recognition, posture, extremity movement analysis, visitation frequency detection, sound pressure detection and light level detection. The above and various other applications are listed throughout the paper.

Research is largely delimited to the area of COVID-19-related studies. Also, bias of selective assessment may be present. In Indian context, advanced technology is yet to be harnessed to its full extent. Also, educational system is yet to be upgraded to add these technologies potential benefits on wider basis.

First, leveraging of insights across various industry sectors to battle the global threat, and smart technology is one of the key takeaways in this field. Second, an integrated framework is recommended for policy making in this area. Lastly, the authors recommend that an internet-based repository should be developed, keeping all the ideas, databases, best practices, dashboard and real-time statistical data.

As the COVID-19 is a relatively recent phenomenon, such a comprehensive review does not exist in the extant literature to the best of the authors’ knowledge. The review is rapidly emerging literature on smart technology use during the current COVID-19 pandemic.

In most economies, there are rules from the market regulators or government to sell at an equal wholesale price (EWP). But when one upstream channel is facing a negative demand disruption and another positive, EWP can create extra pressure on the disadvantageous supply chain partner, which faces negative disruption. The purpose of this study is to analyse the impact of EWP and the scope of the discriminatory wholesale price (DWP) during disruptions.

For the study, the authors used a dual-channel supply chain consisting of a manufacturer, online retailer (OR) and traditional brick-and-mortar (BM) retailer. Stackelberg game is used to model the interaction between the upstream and downstream channel partners, and the horizontal Nash game to analyse the interaction within downstream channel partners. For modelling asymmetric disruption, the authors took instances from the lock-down and post-lock-down periods of the COVID-19 pandemic, where consumers flow from BM retailer to OR store.

By analysing the disruption period, the authors found that this asymmetric disruption is detrimental to the BM channel, favourable to OR and has no impact on the manufacturer. But with DWP, the authors found that the profit of the BM channel and manufacturer can be increased during disruption. Though the profit of the OR decreased, it was found to be higher than in the pre-disruption period. Under DWP, the consumer surplus increased during disruption, making it favourable for the customers also. Thus, DWP can aid in creating a win-win strategy for all the supply chain partners during asymmetric disruption. Later as an extension to the study, the authors analysed the impact of the consumer transfer factor and found that it plays a crucial role in the optimal decisions of the channel partner during DWP.

Very scant literature analyses the intersection of DWP and disruptions. To the best of the authors’ knowledge, this study, for the first time uses DWP as a tool to help the disadvantageous supply chain partner during asymmetric disruptions. The study findings will assist the government, market regulators and manufacturers in revamping the wholesale pricing policies and strategies to help the disadvantageous supply chain partner during asymmetric disruption.

To extend research into sport consumer behaviors related to online sports betting, this study is designed to identify and examine the relationship between online sports betting motivations and online sports betting intentions. By applying a push-pull framework from online sport consumption and gambling studies, nine motivations to engage in online sports betting were identified. These motivations were hypothesized to motivate online sports betting intentions.

A quota sampling technique based on the sports bettor demographics available in the American Gaming Association (AGA, 2019) and the Pew Research Center (2022) obtained a total of 550 completed surveys that met the inclusion and exclusion criteria. For data analyses, confirmatory factor analysis (CFA) and structural equation modeling (SEM) were used to examine the measurement model and the hypothesized model, respectively.

The results revealed that four motivations (i.e. monetary gain, excitement, convenience and negative technology-readiness) were related to online sports betting intention, while five motivations (i.e. sport fandom, positive technology-readiness, impulsivity, socialization and promotion) were not.

The results provide foundational theoretical knowledge of what motivates sports fans to participate in online sports betting. Furthermore, the findings assist practitioners in their allocation of resources by enhancing their understanding of online sports betting motivations.

This paper explores how financial technology (FinTech) organisations address poverty-related challenges when providing digital financial services. Employing the conceptual foundation of the liability of poorness (i.e. literacy gaps, a scarcity mindset, intense non-business pressures and a lack of financial slack), this paper explores the innovative strategies that FinTechs use to address these liabilities and promote entrepreneurship.

The paper uses detailed case data collected from three FinTech organisations operating in one South Asian country.

FinTech organisations' innovative strategies reflect a combination of “high touch” (human) vs “low touch” (digital) solutions. All the organisations simplified internal systems or procedures to accommodate customers. The degree to which the three organisations adopted each of the identified strategies shows an emerging typology of FinTechs; that is, innovators with high digital interactions, a mix of digital-human interactions and high human interactions.

The paper develops a typology which categorises FinTech innovative strategies. The typology highlights strategies pro-poor FinTechs use and explains the types of entrepreneurial support innovative organisations provide for their customers. Both the typology and the innovative strategies contribute to enhanced financial inclusion and entrepreneurial promotion amongst the poor.

The originality of the paper comes from its focus on FinTechs' innovative pro-poor strategies. Existing studies typically address the technology-side of innovations. In contrast, this paper combines innovative strategies with the liability of poorness to identify issues associated with financial inclusion.

In August, 2015, Serena Williams, one of the most successful female athletes of all time, was body shamed in a New York Times article. The incident highlights the issue of unequal treatment of male and female athletes – while a muscular frame enhances masculinity for male athletes, a muscular physique invites body shaming for female athletes. In this study, symbolic interactionist theories regarding the generalized other are called into question. While George Mead's theorizing exhibits a nonproblematic role taking of the generalized other in a cooperative manner, this study reports the presence of paradoxical generalized others, and consequently, the incongruent role taking of a latent generalized other by individuals. This study investigates if the issue of body image exists among college female athletes, if college female athletes experience the dilemma of choosing between outstanding performance with a muscular frame or maintaining traditional female appearance. To provide answers to the question, female athletes in a midwest university were invited to fill out a survey. The survey results confirm the existence of a paradox between performance and appearance among some college female athletes.

The purpose of this study was to compare four different consumer pathway models based on identity theory, attitude/loyalty theory, lifestyle theory and hierarchy of effects theory, each with associated instruments measuring connection to the team.

The authors did a two-study analysis, first collecting data from people aware of an NFL team (N = 218) and then an MLS team (N = 209) to determine which connection item performed better.

The authors found that the Consumer Pathway for Sport Fandom based on the hierarchy of effects theory and its associated interest measurement item performed better than the other three frameworks and items. The Interest item shared the most variance with games attended, games intending to attend, games watched via media and games intending to watch via media.

The Consumer Pathway for Sport Fandom represents the entire consumer spectrum from non-aware consumers all the way up to die-hard sports fans. This pathway will allow sport marketers to track their consumers from initial awareness of the product or service all the way through the brand relationship to ultimate loyalty.

The purpose of this research is to explore how one unsanctioned community sport organization (CSO), AM Hockey, sought to acquire legitimacy in a highly institutionalized minor hockey marketplace at various points in its organizational life cycle.

This study was guided by instrumental case study methodology. Twenty (20) AM Hockey stakeholders from a variety of roles (e.g. executives, program directors and coaches) were interviewed. Document analysis was also utilized to supplement the interviewees. Internal and public documents reflective of the CSO's creation and growth were obtained.

Findings revealed that the CSO had to navigate distinct phases of evolution including the Building, Growth, Competition and Stabilization phases. Although the four life cycle phases identified in this study share similarities with the phases identified by Lester et al. (2003), findings indicated that institutional work mechanisms must be understood in their context as they can vary over the life cycle of an organization. Therefore, start-up sports organizations must approach the pursuit of legitimacy as a continual process rather than something acquired and defended through maintenance work.

Developing legitimacy remains a central challenge for CSOs that seek to deliver alternative sport programming, yet it continues to be understudied. Ultimately, the long-term viability of an unsanctioned CSO in a federated sports system relies, in part, on its ability to continually determine the actions needed to achieve legitimacy within its environment.