Search Results (67)

Complementary currencies are increasingly recognized worldwide as a valuable tool for supporting the development of local and regional communities. This paper explores the role of functional complementary currencies in fostering regional socio-economic advantages and the potential benefits they offer to local communities. The research employs a critical review of existing literature and a comparative analysis to highlight differences in the use of complementary currencies across various contexts. The study identifies key areas where complementary currencies provide support and includes an analysis of user perceptions within a multilateral barter system, focusing on both the benefits and concerns associated with complementary currency use. These currencies are closely aligned with the principles of sustainable development, with their impacts categorized into three primary pillars: social, economic, and environmental. The successful introduction of complementary currencies requires social acceptance and cooperation from local communities. To deliver long-term sustainable benefits, complementary currencies must be implemented in an economically and socially sustainable manner. Full article

The incorporation of human-like social concepts into the Internet of Things (IoT) has given rise to the paradigm of Social IoT (SIoT). In these networks, objects autonomously form social relationships to enhance network scalability in information and service discovery, focusing on their own benefits. However, social likeness or dislikeness among nodes can result in selfish behavior, adversely affecting network performance. Existing node stimulation mechanisms primarily focus on ad hoc and IoT networks, emphasizing topological structures and traffic patterns, while overlooking the social and behavioral factors crucial to the SIoT. This work proposes a novel node stimulation scheme for the SIoT that incorporates both social and behavioral characteristics and network topology. The mechanism employs a virtual currency-based game to incentivize cooperation by considering parameters such as proximity, energy levels, buffer size, correlated relays, and data quality. Additionally, social factors—including social preference, node importance, interaction history, and the probability of vital data transfer—are integrated into the decision-making process. Simulation results demonstrate that the proposed mechanism outperforms existing approaches in terms of energy efficiency, throughput, packet delivery ratio, and end-to-end delay, making it a robust solution for improving cooperation and performance in SIoT networks. Full article

This study examines the impact of gender as a social factor on the lexical variation of the Jordanian currency, dinar, among students at the University of Jordan. Utilizing a mixed-method approach, the study aims to determine whether the role of gender is statistically significant in the choices among different lexical variants of the terms. For quantitative results, the chi-square test of independence, conducted after distributing a questionnaire to 510 participants, revealed that gender significantly influences lexical choices. Furthermore, data obtained from fifty audio-recorded interviews revealed that the majority of participants agreed with the findings from the quantitative analysis. Applying Gender Performativity Theory to analyze these choices socially and the meanings conveyed by their usage reveals that lexical preferences in Jordan are deeply connected with societal expectations regarding gender roles. Full article

This study proposes that MNCs might withdraw from the CSR concept to gain tangible benefits, like improved corporate financial performance (CFP), and intangible benefits, such as reputational capital (RC). This represents a paradigm shift from the philanthropic end of the spectrum to the strategic win–win side, where all investments are expected to yield a return. Being tacit, quests for reputational returns are discussed in terms of corporate social performance (CSP) with its currency being RC (an intangible asset). However, this requires a deep understanding of the CSP concept and ‘good management’. This study argues that CSR will change trajectory based on three facets. First, we argue for the replacement of CSR by CSP, where ESG becomes ‘business as usual’. Second, regulatory categories (voluntary or legislated) will merge. Third, ethics endorsing ‘good management’ will alter executive mindsets, making CSP deeply embedded in corporate behavior. Organizational behavior towards CSP must, therefore, be sincere yet not embedded overwhelmingly. We extend previous discussions regarding the relationship between CSP and CFP, who present robust evidence that (1) absent CSR embedment has no/neutral CSP and CFP effect; (2) inadequate CSR yields negative CSP and CFP; and (3) productive CSR positively affects CSP and CFP. Consequently, this study argues that (4) strategic CSR (SCSR) maximizes positive CSP and that (5) excessive CSR is detrimental, yielding negative effects on both CSP and CFP. This study, therefore, conjectures the existence of a ‘sweet spot’, where SCSR optimizes CSP and CFP outcomes. The contributions address ESG engagement as a ‘sweet spot’ concept and provide a model enabling SCSR discussion, CSP evaluations, and an implementation framework for its achievement. The framework gives executives a toolbox to influence their stakeholders toward improved CFP. Therefore, our perspective supports CSP embedment, enabling firms to address business growth and sustainability requirements. Full article

Improvements in quality of life, new technologies and population growth have significantly increased energy consumption in Brazil and around the world. The Paris Agreement aims to limit global warming and promote sustainable development, making green hydrogen a fundamental option for industrial decarbonization. Green hydrogen, produced through the electrolysis of water using renewable energy, is gaining traction as a solution to reducing carbon emissions, with the global hydrogen market expected to grow substantially. This study applies the ${\rho }_{DCCA}$ method to evaluate the cross-correlation between the green hydrogen market and various financial assets, including the URTH ETF, Bitcoin, oil futures, and commodities, revealing some strong positive correlations. It highlights the interconnection of the green hydrogen market with developed financial markets and digital currencies. The cross-correlation between the green hydrogen market and the index representing global financial markets presented a value close to 0.7 for small and large time scales, indicating a strong cross-correlation. The green hydrogen market and Bitcoin also presented a cross-correlation value of 0.4. This study provides valuable information for investors and policymakers, especially those concerned with achieving sustainability goals and environmental-social governance compliance and seeking green assets to protect and diversify various traditional investments. Full article

Cost overruns represent a continuous challenge within the construction industry, frequently affecting the success of projects. This study explores the factors influencing cost during the construction phase in Saudi Arabia, utilizing data from a survey of 1076 engineers working in the Saudi construction industry. The results identify a number of cost-related factors, including inadequate project management, poor cost estimation, and design errors. Interestingly, some factors, such as currency exchange rate fluctuations and social and cultural influences, were found to have a limited impact on construction costs. Furthermore, the study highlights the role of experience and education level in shaping engineers’ perceptions of these cost factors. The study employs statistical analysis, including Pearson’s chi-squared test, to demonstrate associations between demographics, project characteristics, and cost-influencing factors. The findings suggest the need for refined project management practices, enhanced technical training, and the implementation of digital technologies such as Construction 4.0 to mitigate cost-related risks. This research provides significant insights for construction professionals and policymakers seeking to enhance cost management within the Saudi construction sector, thereby contributing to the ongoing development initiatives aligned with Saudi Arabia’s Vision 2030. Full article

Monetary markets serve as established resource allocation mechanisms, typically achieving efficient solutions with limited information. However, they are susceptible to market failures, particularly under the presence of public goods, externalities, or inequality of economic power. Moreover, in many resource-allocating contexts, money faces social, ethical, and legal constraints. Consequently, artificial currencies and non-monetary markets are increasingly explored, with Karma emerging as a notable concept. Karma, a non-tradeable, resource-inherent currency for prosumer resources, operates on the principles of contribution and consumption of specific resources. It embodies fairness, near incentive compatibility, Pareto-efficiency, robustness to population heterogeneity, and can incentivize a reduction in resource scarcity. The literature on Karma is scattered across disciplines, varies in scope, and lacks conceptual clarity and coherence. Thus, this study undertakes a comprehensive review of the Karma mechanism, systematically comparing its resource allocation applications and elucidating overlooked mechanism design elements. Through a systematic mapping study, this review situates Karma within its literature context, offers a structured design parameter framework, and develops a road map for future research directions. Full article

Partaking in the editorial process of an academic journal is both a challenging and rewarding experience. It takes a village of dedicated individuals with a vested interest in the dissemination and sharing of high-quality research outputs. As members of the editorial team of an open access data journal, we reflect on the emergence of data-driven open research, a new journal genre (data paper), and a new journal type (data journal) in the Arts, Humanities, and Social Sciences (AHSS). Access to data—the currency of empirical research—is valuable to the research community, crucial to scientific integrity, and leads to cumulative advancements in knowledge. It therefore requires significant investment and appropriate venues for dissemination. We illustrate the necessity of raising awareness about data-driven open research and best practices in data-driven publishing. We discuss how it involves building a community of authors and readers, establishing a company of editors, reviewers, and support staff, and passing on the practice, which has been challenging the status quo in research and publishing. Potential future directions are considered, including data peer review and reward, recognition, and funding structures for data sharing. Full article

In socially aware networking, nodes typically behave selfishly due to resource constraints and social correlations, resulting in low network performance. To incentivize selfish nodes to actively participate in message forwarding, this paper proposes a resource-based dynamic pricing and forced forwarding incentive algorithm (DFIA). Firstly, the algorithm introduces virtual currency as a transaction medium and then designs a pricing function based on factors such as the node’s resource status, participation contribution, location relevance, and social connectivity. It ensures that the forwarding service is transacted at a reasonable price through bargaining rules. Secondly, a forced forwarding strategy is implemented to compel selfish nodes, which are unwilling to participate in other nodes’ message forwarding, to forward a certain number of non-local messages. Meanwhile, in order to prevent nodes from discarding messages and to ensure successful forwarding to the destination, specific rules are used to allocate contribution values to nodes that successfully participate in message forwarding. Lastly, to avoid false quotation behavior, blockchain technology is employed. Transaction information is packaged into blocks and added to the blockchain after consensus validation by other nodes in the network, ensuring the transparency and immutability of transaction data. Simulation results indicate that compared with the existing incentive algorithms, this algorithm not only enhances message delivery probability but also effectively reduces average latency. Full article

The shadow economy’s size and impact remain subjects of extensive research and debate, holding significant implications for economic policy and social welfare. In Lebanon, the ongoing crisis since 2019 has exacerbated severe economic challenges, with the national currency’s collapse, bank crisis, and foreign reserve deficits. The World Bank reports Lebanon’s financial deficit surpassed $72 billion, three times the GDP in 2021. Despite a drastic decline in GDP, imports have surged to near-pre-crisis levels, exacerbating economic woes and indicating a constant outflow of foreign currencies. Considering such contracting facts, this paper aims to investigate global factors influencing the shadow economy and discern their manifestations in Lebanon during financial crises. Our methodology involves a comprehensive literature review, alongside a case study approach specific to Lebanon. This dual-method strategy ensures a detailed understanding of the shadow economy’s impact and the development of actionable insights for policy and economic reform. Through this approach, we seek to contribute to a nuanced understanding of Lebanon’s economic landscape and provide valuable guidance for policy decisions aimed at reducing corruption, promoting transparency, and fostering a robust formal economy. The increase in the shadow economy raises the formal economy risk, as resources and activities diverted to informal channels hinder the growth and stability of the official economic sector. Although focusing on Lebanon, this analysis deepens the comprehension of the economic landscape and provides valuable guidance for policymakers, researchers, and stakeholders, aiming to address the root causes of informal economic activities and promote sustainable growth in developing countries in general. Full article

Nowadays, transactions carried out with digital currencies are increasing. Modern societies are asked to respond to growing challenges related to the management of digital currencies in their daily lives. However, due to the lack of digital skills of users, the management of digital currencies hides risks. To the best of our knowledge, the originality of the current research lies in the act of combining the concept of digital skills with the use of digital currencies. After all, the use of digital currencies is constantly increasing, which means that citizens should familiarize themselves with their use, an element that makes this study valuable for digital societies. Digital skills effectively contribute to the development of digital societies because they increase the employment of citizens, facilitate access to information, and contribute to the social inclusion of individuals through digital communication, while also increasing efficiency and productivity in the workplace. Also, the government and banking institutions can more effectively sensitize citizens to digital skills for more effective use of digital currencies. In this way, tax payments will be facilitated, the use of e-wallets will be safer, and e-governance will be greatly promoted, while the quality of banking services will be improved. The methodology of this study was based on the Digital Competence Framework for Modern Societies (DigComp) and was applied through a questionnaire completed by 443 respondents. The main objective was to evaluate their digital skills from the perspective of digital currency use. The analysis of the responses was carried out by using Structural Equation Modeling (SEM). The most important result from this research reveals that users of digital currencies are significantly capable of developing communication to solve everyday problems. At the same time, users of digital currencies mostly detect digital threats and effectively manage fake news without being affected by them. However, users of digital currencies consider that security issues are important, but only for transactions and not for their supporting functions. The study concludes with suggestions for improving the experience of digital currency users through individual actions, thus having a positive impact on the state and banking institutions. Full article

Money laundering is an illicit activity that seeks to conceal the nature and origins of criminal proceeds, posing a substantial threat to the national economy, the political order, and social stability. To scientifically and reasonably predict money laundering risks, this paper focuses on the “layering” stage of the money laundering process in the field of supervised learning for money laundering fraud prediction. A money laundering and fraud prediction model based on deep learning, referred to as MDGC-LSTM, is proposed. The model combines the use of a dynamic graph convolutional network (MDGC) and a long short-term memory (LSTM) network to efficiently identify illegal money laundering activities within financial transactions. MDGC-LSTM constructs dynamic graph snapshots with symmetrical spatiotemporal structures based on transaction information, representing transaction nodes and currency flows as graph nodes and edges, respectively, and effectively captures the relationships between temporal and spatial structures, thus achieving the dynamic prediction of fraudulent transactions. The experimental results demonstrate that compared with traditional algorithms and other deep learning models, MDGC-LSTM achieves significant advantages in comprehensive spatiotemporal feature modeling. Specifically, based on the Elliptic dataset, MDGC-LSTM improves the Macro-F1 score by 0.25 compared to that of the anti-money laundering fraud prediction model currently considered optimal. Full article

This study employed a risk and resilience framework to investigate the influence of multidimensional factors, considering psychosocial and behavioral aspects, on online victimization among fifth-grade children (ages 10–11). Loneliness, online social currency disturbance, and digital citizenship were examined as predictors of online victimization. Data were collected from 196 students through a self-reported online survey conducted on electronic devices provided by the schools. The findings indicated that 78.6% of fifth-graders owned a smartphone, 70.9% had a gaming console, and the most common online activities were playing online gaming (73%), talking with friends (62.8%), and seeking entertainment (62.2%). Online victimization was prevalent, with 30.8% of children reporting they had been called bad names, 24.7% receiving rude comments, 15.9% expressing feelings of worry or threat due to online harassment, and 3.1% experiencing cyberbullying lasting for days. Furthermore, the results revealed a negative association between digital citizenship and online victimization, while loneliness and online social currency disturbance were positively associated with online victimization after accounting for children’s gender and time spent online. In conclusion, this study suggests that efforts to prevent and address online victimization should prioritize promoting digital citizenship and increasing awareness of the roles of loneliness and social currency disturbances in online social dynamics. Full article

Digital technologies and economies can strengthen participative processes and data- and knowledge-based sustainable urban development. It can also accelerate social integration and the efforts of urban dwellers towards more resilient urban environments. Gap: Most of the tools that strengthen participatory processes were not cocreated with stakeholders. Research shows that codesigned platforms driven by new technological advances and the development of collaborative sharing economy concepts can increase climate change awareness. Still, the rise of participatory innovation technologies does not focus on enabling social engagement in climate change mitigation. Therefore, this paper addresses a research question: can a codesigned community currency stimulate bottom-up initiatives for climate change mitigation, and what is needed for such tools to succeed with the implementation of climate-responsive policies? The aim was to introduce an approach allowing us to codesign an application to encourage pro-environmental behaviors. Hence, the approach of this research was to define the concept of such a tool as a part of a cocreation process with stakeholders in a multidisciplinary and cross-sectoral environment. Method: It uses design thinking enriched with case studies evaluation, workshops, UX design, low fidelity, SUS, and testbeds. Findings and value: The authors introduce the Greencoin concept and argue that the codesigned digital currency operating based on an educational application has the potential to strengthen social engagement in climate change mitigation. Beneficiaries and practical implementation: Such a tool can increase climate awareness by supporting social integration and bottom-up initiatives for climate change mitigation. It can therefore be used by local communities to strengthen their climate-responsive efforts. Full article

Since the advent of Bitcoin, the cryptocurrency landscape has seen the emergence of several virtual currencies that have quickly established their presence in the global market. The dynamics of this market, influenced by a multitude of factors that are difficult to predict, pose a challenge to fully comprehend its underlying insights. This paper proposes a methodology for suggesting when it is appropriate to buy or sell cryptocurrencies, in order to maximize profits. Starting from large sets of market and social media data, our methodology combines different statistical, text analytics, and deep learning techniques to support a recommendation trading algorithm. In particular, we exploit additional information such as correlation between social media posts and price fluctuations, causal connection among prices, and the sentiment of social media users regarding cryptocurrencies. Several experiments were carried out on historical data to assess the effectiveness of the trading algorithm, achieving an overall average gain of 194% without transaction fees and 117% when considering fees. In particular, among the different types of cryptocurrencies considered (i.e., high capitalization, solid projects, and meme coins), the trading algorithm has proven to be very effective in predicting the price trends of influential meme coins, yielding considerably higher profits compared to other cryptocurrency types. Full article