Traditional Paradigm Research Articles

The Economics of Capital Allocation in Firms: Evidence from Internal Capital Markets

We analyze a unique chief financial officer (CFO) survey data set to examine capital allocation in firms. Top management is aware of agency and information problems at the divisional level and organizes the budgeting process to counteract managerial opportunism, employing systems of interconnected measures, including layers of approval, divisional budgets, reporting requirements, and compensation schemes. When making funding decisions, top management relies heavily on top-level nonfinancial information, such as the assessment of divisional managers’ abilities. However, substantial parts of the capital budget do not require top management approval as firms trade off the benefits and costs of decentralization, thereby deviating from the traditional paradigm of decentralized project initiation but centralized project approval. Even firms with active internal capital markets tilt capital allocation toward relatively even distributions, reflecting the use of capital allocation as a credible communication device. We also find that within-firm agency problems may result in capital rationing, that is, divisions’ restricted access to internal capital. CFOs also believe that integrating multiple businesses into an internal capital market results in tangible financial benefits, predominantly lower costs of capital and higher debt capacities. Thus, our findings also support coinsurance arguments suggesting that internal capital markets may improve access to external financing. This paper was accepted by Victoria Ivashina, finance. Funding: This work was supported by the BBBank Karlsruhe, Wissenschaftsförderung der Sparkassen-Finanzgruppe, and Karlsruher Institut für Technologie (Karlsruhe House of Young Scientists). Publishing fees were supported by the “Funding Programme Open Access Publishing” of the University of Hohenheim. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2021.02755 .

Research on the sentiment recognition and application of allusive words based on text semantic enhancement.

In the era of digital intelligence empowerment, the data-driven approach to the mining and organization of humanistic knowledge has ushered in new development opportunities. However, current research on allusions, an important type of humanities data, mainly focuses on the adoption of a traditional paradigm of humanities research. Conversely, little attention is paid to the application of auto-computing techniques to allusive resources. In light of this research gap, this work proposes a model of allusive word sentiment recognition and application based on text semantic enhancement. First, explanatory texts of 36,080 allusive words are introduced for text semantic enhancement. Subsequently, the performances of different deep learning-based approaches are compared, including three baselines and two optimized models. The best model, ERNIE-RCNN, which exhibits a 6.35% improvement in accuracy, is chosen for the sentiment prediction of allusive words based on text semantic enhancement. Next, according to the binary relationships between allusive words and their source text, explanatory text, and sentiments, the overall and time-based distribution regularities of allusive word sentiments are explored. In addition, the sentiments of the source text are inferred according to the allusive word sentiments. Finally, the LDA model is utilized for the topic extraction of allusive words, and the sentiments and topics are fused to construct an allusive word-sentiment theme relationship database, which provides two modes for the semantic association and organization of allusive resources. The empirical results show that the proposed model can achieve the discovery and association of allusion-related humanities knowledge.

Water Drops

This article examines how individuals of diverse cultural backgrounds in Norway participate in anti-racist activism via social media. It investigates the nature of digital activism compared to traditional paradigms, highlighting the varied forms of engagement enabled by digital technology. Drawing on nine months of ethnographic fieldwork among individuals in the arts and cultural sector, it reveals how seemingly minor actions on social media can spark organized activism, unveiling the political activism inherent in daily life and social media practices. The article argues that individuals not identifying as political activists still contribute to political change through everyday social media activities, suggesting that contemporary activism can exist without activists. Introducing the metaphor of ‘water drops’ the article conceptualizes everyday politics as small contributions that may collectively shape meaningful change. Small acts can be merely drops in a vast ocean without major significance. However, if sustained over time, efforts across disparate online spaces can coalesce to challenge and subvert dominant social narratives regarding difference, racism, discrimination, and exclusion. Thus, contemporary activism can thrive with ordinary people who contribute to collective social transformation through digital and mundane interactions.

Application and Impact of the “Third Place” Concept — Starbucks as an Example

This essay explores the concept of the “Third Place” as epitomized by Starbucks, analyzing its significance in fostering community and enhancing the customer experience. By positioning itself as a communal hub, Starbucks transcends traditional retail paradigms, offering a space where social interactions flourish. The study found that Starbucks, through its successful global localization strategy, has effectively created a “third space” in different cultural contexts, enhancing customers’ sense of belonging and loyalty. Despite the impact of cultural differences on the brand experience, Starbucks’ space design and branding have become an important medium for customers to demonstrate their identity and interact socially. As the coffee shop market becomes increasingly crowded, Starbucks will need to continue to innovate and differentiate itself to meet customers’ evolving needs. In the future, Starbucks will need to continue to adapt to cultural differences and innovate to meet the challenges of the marketplace to maintain its global competitiveness.

Comparable yet distinct: a systematic review of social and small and medium-sized enterprises growth trajectories

Purpose This study aims to expand the concept of business growth by incorporating sustainability demands, particularly in the context of the Anthropocene era. It explores the growth trajectories of social enterprises (SEs) and small and medium-sized enterprises (SMEs), examining how SEs integrate social and environmental objectives into their growth process. Through a systematic literature review (SLR), this study compares these approaches with traditional SME growth paradigms, highlighting the need for a holistic understanding of business growth that addresses contemporary socioenvironmental challenges. Design/methodology/approach A qualitative SLR was conducted, using a structured search algorithm to identify and evaluate research on growth and scaling in SMEs and SEs. The search of the Web of Science database with specific growth-related keywords yielded 5,362 articles, which were narrowed to 194 after filtering by journal relevance. Content analysis, guided by an inductively developed codebook, examined growth definitions, operationalizations, and methodologies. This paper focused on key growth dimensions (economic, social and environmental) and identified whether growth was addressed as an outcome or process, along with its enablers and barriers. Findings While there are areas of intersection between the literatures, the findings reveal that traditional SME growth frameworks do not entirely align with SEs growth conception and management. Furthermore, SE’s growth barriers and facilitators, as well as growth trajectories more broadly, emerge as distinct from those of traditional SMEs. The results distill insights from SE growth paths that can be valuable for traditional SME managers, particularly in terms of managing stakeholders and the institutional environment. Social entrepreneurs commonly use strategies for reshaping business norms, influencing consumer culture and raising social issues awareness, leveraging the values of stakeholders to secure essential support. Originality/value As SMEs confront escalating pressure to align with the sustainable development agenda, the findings underscore the critical significance of drawing insights from the burgeoning SE growth literature. This suggests that traditional SME growth literature stands to gain invaluable insights from recent SE research, fostering a more nuanced comprehension of sustainability-centric SME growth trajectories.

Social Learning in Neural Agent-Based Models

Abstract Agent-based models (ABMs) are widely used to study how individual interactions shape collective behaviors. Critics argue that ABMs are often too simplistic to capture real-world complexities. We address this by integrating artificial neural networks into ABMs, focusing on enhancing the Hegselmann–Krause (HK) model. By using multilayer perceptrons as agents, we create more realistic ABMs that better reflect actual agents. This approach yields multiple models, as core elements of the HK model can be defined in various ways. We conduct two computational studies to compare these models with each other and with traditional individual-learning paradigms.

The Labyrinth: using new music experience in the performance of historical music

The education of a classical violinist – or mine at least, and I see scant evidence that anything else holds today – begins based on a mainstream Romantic ideal consisting of works, geniuses, and concepts of musical authenticity. This is quite useful as a tool to cajole the young violinist into learning the essentials of tone production and playing styles but is at odds with a questioning attitude towards normative traditions that might allow the musician greater interpretive freedom after gaining that technique. While the historically informed performance (HIP) movement was an early, important manifestation of this sort of questioning attitude, the experimental/avantgarde tradition, which has run parallel to these others from the early twentieth century, has not often been applied to the interpretation of historical music. The experimental tradition does not assume conventional tone production or historical authenticity: instead, it is asking the musician to interpret the symbols on the page according to their own artistically informed predilections and contexts to produce new performances emanating from the artwork, thereby transferring more responsibility for the performance from the composer to the musician. To what extent might the experience of the performer be allowed to contribute to the performance of a historical work? As part of a three-year artistic research project in Stockholm, I have been looking into ways of using interpretive techniques gleaned from the study of new music and applying these to historical works. This article describes some existing research that questions the traditional interpretive paradigm, along with the ontology of a musical work and its interpretation, and concludes with a case study, “The Labyrinth,” showing one way that these sorts of attitudes can be put into practice for a genre of music to which they seldom, if ever, have been applied.

Flexible paths to innovation: mitigating commuting’s impact on creative deviance

PurposeThis study aims to investigate how long commutes negatively affect employees’ creative deviance at work, exploring the mediating role that impaired work–life balance plays in linking commute to restricted creative deviance, as well as examining whether access to flexible work arrangements can alleviate commuting’s detrimental indirect effects.Design/methodology/approachThis study employed a three-wave survey methodology conducted over monthly intervals with 246 participants in China’s Pearl River Delta region. Rigorous screening ensured a demographically diverse sample.FindingsCommuting time negatively affects creative deviance, both directly and indirectly through work–life balance. Flexible work arrangements mitigate the adverse effects of long commutes on work–life balance, subsequently weakening the indirect effect of commuting time on creative deviance through work–life balance.Practical implicationsA holistic approach is suggested for organizations aiming to foster a supportive and ethical work environment, which involves a combination of organizational policies, leadership practices and individual actions to promote both creativity and employee welfare.Originality/valueThis research breaks new ground by identifying commuting time as a key factor influencing creative deviance in the workplace, mediated by work–life balance. It integrates transportation research with organizational behavior, applying an ethics of care perspective to challenge traditional paradigms. The study’s interdisciplinary approach, bridging multiple fields, provides a novel, holistic view of how non-work factors impact workplace innovation.

A METHODOLOGICAL APPROACH WITH VBL (VIDEO BASED LEARNING) ANALYZING THE REPRESENTATIONS OF THE ROCK FIGURES OF THE ALCOBAÇA VALLEY: BUÍQUE - PE

The Catimbau Valley, located in the municipality of Buíque- PE, which is located at the meeting point of the mesoregions of the Southern Agreste and the Sertão region of Pernambuco, has a predominant biome of the Caatinga, this biome being endemic to the Brazilian Northeast; with a favorable relief and of great interest in field experiences, carved into the Borborema Plateau, with the presence of Massifs and high hills in the landscape, with the variation of 650 to 1000 meters. With all the phytophysiognomy encompassing its natural attributes, which makes this entire environment even more interesting for studying the place, is given through the cave paintings found on the rocks there, with emphasis on the Archaeological Site of the Alcobaça Valley, with records on the bedrock, as well as records on fallen blocks, marked in different times and peoples. Historical marks left by the groups that passed through there are observed. Included in the imagery framework in the category Agreste Tradition (Martin 2000), which is categorized by the singularities of the images made, as well as the techniques for marking the relief. The rock art made by the primary peoples of the Catimbau region contributes to the teaching of Geography, thus allowing an understanding of the geographic space and its dimensions. During the didactic excursion, Geography students were able to analyze the changes in the way of life of the original population, as well as the main physical/natural transformations of the Catimbau Valley. Given the current scenario of basic education in geography teaching, the methods used contribute to traditional teaching, in the way in which teachers reproduce their knowledge and information, without any concern for the construction of knowledge of their respective students, thus the work in question proposes the breaking of the traditional paradigm. The objective of the research is to address how rock art can collaborate in the teaching of Geography and assist in the representation of geographic space for the understanding of spatial dynamics occurring in the territory, seeking to attribute photographs to the teaching of Geography, and to break with the traditional teaching method in basic education. The methodology used is based on “Video Based Learning”, through the recording of the trail of the Alcobaça Archaeological Site by students, to be used in the production of teaching material, being a video that tells the route of the trail, showing the wall with the respective rock art, and the realization of the didactic activity entitled "Geography written in the Reliefs", in which the students will draw the rock art that caught their attention the most and what meaning was attributed to the figure. As a result of the research, we will have the elaboration of the expository video (in editing), and the practical activity carried out in the classroom with the students, which brings different memories and meanings.It is concluded that addressing the use of representations of rock figures in the teaching of Geography helps students to analyze the territory in an innovative way. Therefore, it is clear that didactic excursions are valid and of such importance for future professionals to be able to develop didactic methods that can be applied inside and outside the classroom.

Westphalian System of International Relations: Formation Dynamics and Disintegration Factors

This article explores the formation and evolution of the system of international relations, asserting that the principles established by the Peace of Westphalia in 1648, which marked the conclusion of the Thirty Years’ War, fundamentally transformed inter-state relations and laid the groundwork for the entire framework of international relations. The author conducts a comprehensive analysis of the core principles of the Westphalian system, identifying criteria and universal indicators of traditional state-centric international relations within this model. The study emphasizes the significance of examining the transformative processes within international relations, tracing subsequent variations from a state-centric to an institutionally-political framework. Each reconfiguration of the Westphalian system is described with attention to its temporal and spatial characteristics. The driving forces behind the genesis and functioning of all models of traditional inter-state relations are delineated. Furthermore, the research investigates the primary causes behind the disintegration of the Westphalian system, highlighting critical international political conditions that facilitate restructuring and the emergence of new systems. The author concludes that the system of international relations is transitioning into a qualitatively distinct phase, diverging from the traditional state-centric paradigm.

Current Trends in ICT Security: A Comprehensive Overview of Machine Learning and Soft Computing Applications

In an era marked by pervasive digitization, information and communication technology (ICT) security stands as a cornerstone of our digital infrastructure. The rapid evolution of cyber threats necessitates equally agile defence mechanisms. This research paper provides a comprehensive overview of the contemporary landscape of ICT security with a specific focus on the emergent trends in machine learning (ML) and soft computing (SC) applications. The paper commences by outlining the escalating challenges posed by cyber adversaries, underlining the inadequacy of traditional security paradigms in contending with the intricacies of modern-day attacks. This backdrop emphasizes the need for innovative, adaptable, and intelligent approaches to bolster ICT security.

Creating Collaborative Spaces for Community College Faculty and Staff to Discuss Pedagogy

ABSTRACT Research from undergraduate and K-12 environments suggests that providing meaningful support for Community College students requires faculty and staff to engage in ongoing self-reflection, peer support, and a commitment to research-based pedagogical shifts. Currently, California Community College (CCC) faculty and staff get very few of these opportunities. This study aims to address this issue through an intervention designed to provide opportunities for CCC faculty and staff to be part of a flexible, coherent professional learning community. The intervention is part of an NSF-funded research and development project at a community college in central California designated as a Hispanic Serving Institution (HSI), with the goal of providing faculty and staff with tools and processes to support students toward higher retention and success in STEM by facilitating “micro-internships.” Micro-internships are designed to reduce inequalities inherent in the traditional internship paradigm by providing access to professional and research skills for students who do not have the opportunities and/or confidence to participate in a more traditional full-length internship. Conversations with participants showed how they embraced the design principles that were negotiated as a project team, and how one or more of the study interventions had played a powerful role in supporting their learning and development toward certain pedagogical shifts. Our results highlight the power of providing spaces such as summer workshops and ongoing “community of practice” meetings for collaboration, professional learning, and peer-to-peer mentorship.

Digital Transformation in Manufacturing Enterprises: Unveiling the Path to Innovation and Efficiency

Abstract: With the development and advancement of technology, the manufacturing industry has undergone a major transformation in recent years. The emergence of digital transformation has become a defining force in the global manufacturing landscape, reshaping traditional paradigms and driving companies toward greater efficiency and innovation. This study delves into the far-reaching impact of digitalization on manufacturing companies, combining a comprehensive analysis of several Chinese companies. By seamlessly integrating advanced digital technologies such as the Internet of Things, big data analytics and artificial intelligence into traditional manufacturing processes, companies are opening up new realms of productivity and competitiveness. However, the road to digital integration is challenging, and companies need to deal with technical challenges and organizational resistance. This study illuminates the path for manufacturing companies to thrive in digitalization through empirical insights and strategic recommendations. By fostering a culture of innovation, optimizing productivity and expanding market reach, digital transformation becomes a key underpinning for sustainable growth in manufacturing.

Artificial Intelligence as a driver of Fintech: Interesting Applications

This paper explores the transformative impact of artificial intelligence (AI) on financial technology (Fintech). With the rapid evolution of digital technologies, AI has become an important driver in reshaping financial services; where its effect is manifesting as increased net revenues of Fintech organizations. This short article examines various applications of AI in Fintech, including extraordinary payment systems, super-fast lending mechanisms and an example of a near real time insurance settlement system. This paper uses examples from industry to highlight how AI-driven innovations are not only enhancing efficiency and customer experience but also introducing new challenges, issues and considerations. The integration of AI in Fintech is altering traditional financial paradigms, prompting a discussion on the future of financial services, as well as organizational decision making, in an AI-dominated landscape.

Maximizing profitability in integrated energy markets: A novel framework for multi-faceted energy trading

The emergence of Integrated Energy Systems (IESs) has shifted energy management from traditional electricity paradigms to a more diverse approach involving electricity, thermal energy, and natural gas. This study introduces a framework for an Integrated Energy Network (IEN) that enables simultaneous trading across these interconnected markets. The objective is to maximize the profitability of integrated energy companies by optimizing energy trading strategies. The proposed business strategy incorporates integrated load response, addressing constraints within electric distribution systems, heating networks, and natural gas pipelines. A three-stage process is used: information sharing in the unified energy market, energy conversion in hubs, and flexible load planning in the retail market. Flexible loads are categorized as displaceable, reducible, or transformable. A Conditional Value-at-Risk (CVaR) mean-variance model addresses market price volatility. Simulations on a test system validate the model, demonstrating its effectiveness in improving profitability and operational efficiency for integrated energy companies.

Analysis of Effectiveness of Collaborative Pedagogy Practices

This study analyzes the effectiveness of collaborative teaching and learning strategies to enhance student's educational experience and learning results. Collaborative pedagogy converts the traditional teacher-centered paradigm into a more participatory, student-centered approach, promoting active participation via group work, debates, and collective problem-solving. This study examines existing literature, case studies, and empirical evidence to evaluate the impact of collaborative approaches on student accomplishment, motivation, and the development of fundamental abilities such as critical thinking, communication, and cooperation. The study found that collaborative teaching and learning approaches are essential for strengthening comprehension, increasing information retention, and cultivating superior social skills. The benefits of peer learning, active engagement, and instructor facilitation are highlighted in cultivating a dynamic classroom atmosphere. The study underscores other problems linked to implementing collaborative pedagogy, including resource constraints, dominant teacher-centered cultural norms, and substantial class sizes, especially in poor countries such as Nepal. The acceptance of collaborative pedagogy in Nepal is increasing owing to continuing educational reforms and curricular modifications; nonetheless, many obstacles hinder its extensive implementation. The document emphasizes the need for augmented teacher training, greater infrastructural support, and customized teaching methodologies to use the benefits of collaborative learning properly. The results demonstrate that, when properly implemented, collaborative teaching-learning methodology may substantially improve educational quality and prepare students to confront real-world difficulties.

Graph neural networks for multi-view learning: a taxonomic review

With the explosive growth of user-generated content, multi-view learning has become a rapidly growing direction in pattern recognition and data analysis areas. Due to the significant application value of multi-view learning, there has been a continuous emergence of research based on machine learning methods and traditional deep learning paradigms. The core challenge in multi-view learning lies in harnessing both consistent and complementary information to forge a unified, comprehensive representation. However, many multi-view learning tasks are based on graph-structured data, making existing methods unable to effectively mine the information contained in the input multiple data sources. Recently, graph neural networks (GNN) techniques have been widely utilized to deal with non-Euclidean data, such as graphs or manifolds. Thus, it is essential to combine the advantages of the powerful learning capability of GNN models and multi-view data. In this paper, we aim to provide a comprehensive survey of recent research works on GNN-based multi-view learning. In detail, we first provide a taxonomy of GNN-based multi-view learning methods according to the input form of models: multi-relation, multi-attribute and mixed. Then, we introduce the applications of multi-view learning, including recommendation systems, computer vision and so on. Moreover, several public datasets and open-source codes are introduced for implementation. Finally, we analyze the challenges of applying GNN models on various multi-view learning tasks and state new future directions in this field.

Comparative analysis of English and American humor in literary discourse

The article studies humor as a type of comic in the literary discourse. The composition of the traditional comic variety paradigm is determined, including humor, irony, satire, and sarcasm. The leading techniques and linguistic/speech means of representing and enhancing the comic effect in the literary discourse are described. The essentials of their complex description are considered. The concept of humor is analyzed as a linguistic and sociocultural phenomenon in the literary discourse. Attention is focused on investigating the peculiarities of British and American humor. The authors trace the differences between English and American humor in domestic and foreign linguistic and literary sources. The peculiarities of the linguistic criterion itself are revealed, which is essential in linguists' identification and study of humor as a kind of comic. The leading classifications of verbal means, forms, and techniques of humorous wit in the literary discourse are highlighted. Humor among the English tends to manifest itself mainly in times of personal hardship and to be largely self-directed. The most crucial feature of American humor is slang, which is peculiar only to Americans.

Canvassing Taboo: African Sexuality as Post-Cultural Discourse in the Kenyan Disconnect 2 and Nafsi Films

Sexuality narratives in the Kenyan film industry play a crucial role in directly and indirectly shaping narrative interests, addressing stakeholder concerns, and delivering effective messaging. Locally, these narratives are closely monitored, regulated, and classified due to their sensitive nature, compounded by their evolving nature as newer sexuality concepts integrate with traditional paradigms. This study aims to explore the social conceptualization of African Sexuality as a Post-Cultural Discourse in the Kenyan films Disconnect 2 and Nafsi. Utilizing film analysis and key informant interviews with industry professionals, the research reveals that post-cultural sexuality narratives are presented as non-threatening sexual ideals and practices that can coexist harmoniously with traditional sexual paradigms. Recommendations include establishing a structured hierarchy for sexual narratives in film production to depict both traditional and post-cultural themes effectively. By incorporating consequences within the post-cultural discourse, audiences can better engage with and understand the complex sexual ideologies presented in these films.

Automatic Recommender System of Development Platforms for Smart Contract-Based Health Care Insurance Fraud Detection Solutions: Taxonomy and Performance Evaluation.

Health care insurance fraud is on the rise in many ways, such as falsifying information and hiding third-party liability. This can result in significant losses for the medical health insurance industry. Consequently, fraud detection is crucial. Currently, companies employ auditors who manually evaluate records and pinpoint fraud. However, an automated and effective method is needed to detect fraud with the continually increasing number of patients seeking health insurance. Blockchain is an emerging technology and is constantly evolving to meet business needs. With its characteristics of immutability, transparency, traceability, and smart contracts, it demonstrates its potential in the health care domain. In particular, self-executable smart contracts are essential to reduce the costs associated with traditional paradigms, which are mostly manual, while preserving privacy and building trust among health care stakeholders, including the patient and the health insurance networks. However, with the proliferation of blockchain development platform options, selecting the right one for health care insurance can be difficult. This study addressed this void and developed an automated decision map recommender system to select the most effective blockchain platform for insurance fraud detection. This study aims to develop smart contracts for detecting health care insurance fraud efficiently. Therefore, we provided a taxonomy of fraud scenarios and implemented their detection using a blockchain platform that was suitable for health care insurance fraud detection. To automatically and efficiently select the best platform, we proposed and implemented a decision map-based recommender system. For developing the decision-map, we proposed a taxonomy of 102 blockchain platforms. We developed smart contracts for 12 fraud scenarios that we identified in the literature. We used the top 2 blockchain platforms selected by our proposed decision-making map-based recommender system, which is tailored for health care insurance fraud. The map used our taxonomy of 102 blockchain platforms classified according to their application domains. The recommender system demonstrated that Hyperledger Fabric was the best blockchain platform for identifying health care insurance fraud. We validated our recommender system by comparing the performance of the top 2 platforms selected by our system. The blockchain platform taxonomy that we created revealed that 59 blockchain platforms are suitable for all application domains, 25 are suitable for financial services, and 18 are suitable for various application domains. We implemented fraud detection based on smart contracts. Our decision map recommender system, which was based on our proposed taxonomy of 102 platforms, automatically selected the top 2 platforms, which were Hyperledger Fabric and Neo, for the implementation of health care insurance fraud detection. Our performance evaluation of the 2 platforms indicated that Fabric surpassed Neo in all performance metrics, as depicted by our recommender system. We provided an implementation of fraud detection based on smart contracts.