Search Results (2,833)

This study investigates how family firms adjusted their tax strategies following Brazil’s 2023 alignment with the OECD transfer pricing guidelines, using nonfamily firms as a benchmark. The analysis adopts a blended socioemotional wealth (SEW) and implicit theory perspective, which explains family firms’ behavioral responses to institutional change by linking SEW intensity to owners’ cognitive orientations. The sample comprises 1239 firm-year observations from 177 nonfinancial companies listed on Brazil’s stock exchange between 2018 and 2024. Before the transfer pricing reform, family firms displayed a more aggressive approach to corporate income tax (CIT) minimization than their nonfamily counterparts. After the reform, only nonfamily firms, typically more internationalized, intensified their CIT minimization, indicating greater responsiveness to the new OECD-aligned rules. Family firms, by contrast, exhibited no significant change. Exploiting the new rules requires cross-border operations, which family firms tend to limit to preserve family control. With little such exposure, they were not positioned to benefit from the reform and their tax behavior remained unchanged. This inertia is consistent with an entity-oriented mindset, indirectly inferable from the firms’ muted tax response to the reform. The study contributes to family business and international taxation research by revealing that ownership structure conditions firms’ responses to regulatory change, extending the SEW–implicit theory framework to explain heterogeneous tax behavior, and offering policy insights that standardized enforcement may yield uneven outcomes across ownership types. Full article

Rural coastal communities are grappling with climate change impacts, including the increased frequency of extreme storm events. Achieving sustainability goals requires addressing environmental, social, and economic dimensions of these events. Social vulnerability indices provide a means of addressing social vulnerability to advance sustainability goals. While such indices offer a metric for assessing relative social vulnerability at a community scale, they often fail to capture more nuanced dimensions of vulnerability. Our exploratory qualitative case study employed two community-driven exercises to examine the impacts due to loss of power, heat, and access to emergency services stemming from a storm event. Participants representing public, conservation, social service, emergency management, and business sectors received a customized social vulnerability index prior to the community exercise, which examined social vulnerabilities associated with an extreme storm event. Participants completed pre- and post-exercise surveys. Transcripts and notes from discussions were analyzed qualitatively. The results provide a refined understanding of who is vulnerable to climate change impacts, the limitations of vulnerability indices in capturing these vulnerabilities, and the potential for community-centered approaches for developing customized vulnerability indices. Such approaches can inform more comprehensive preparation and recovery initiatives in response to increasing extreme storm events. Full article

Construction companies, petrochemical enterprises, and airports are examples of large-scale organizational–technical systems (OTSs) and are characterized by a distributed structure, numerous parallel technological and business processes, and substantial energy consumption. The control of such systems is implemented through hierarchical distributed systems that require the regular collection, synchronization, and analysis of large volumes of heterogeneous data. This paper proposes a methodology for performance analysis and energy consumption optimization in OTSs based on the combined use of hierarchical control, business process modeling in BPMN and DRAKON notations, and the use of snapshots—consistent global states of a distributed system captured at specified time instants. The specifics of snapshot generation algorithms are discussed, including copy-on-write, the Chandy–Lamport algorithm, cloud orchestration, and log-based point-in-time recovery. A snapshot acquisition optimization problem is formulated, which minimizes the deviation of the captured state from the actual state under constraints on frequency, synchronization delay, and cost. The feasibility of the approach is illustrated by a numerical example of energy redistribution between the levels of a hierarchical control system using distributed model predictive control (DMPC). The advantages of the method include obtaining an objective “as is” picture, the applicability of control-theoretic methods for distributed systems based on big data processing, the ability to localize faulty subsystems, and its utility in assessing a company’s condition for stakeholders. Full article

This study presents a systematic review of the literature on business localness, a concept which, despite increasing interest, remains theoretically fragmented. This fragmentation limits a comprehensive understanding of how firms are embedded in local economies and how localness can be systematically measured. Using the PRISMA methodology, 54 articles were analyzed from an initial set of 500 publications in the Scopus database. Combining bibliometric clustering and qualitative synthesis, the study identifies seven major research clusters and organizes them into broader research streams. The findings suggest that localness is primarily examined in terms of its relational, spatial and economic dimensions. Mechanisms such as knowledge diffusion, trust and access to resources are emphasized, as are outcomes relating to innovation, business performance, sustainability and regional development. However, the economic dimension remains fragmented and is rarely conceptualized as a distinct and measurable component of business localness. Combining findings from previously fragmented research streams, this study develops an integrative framework for business localness that incorporates spatial, relational, and economic dimensions of embeddedness and links them to the mechanisms and outcomes through which firms contribute to local economies. The study is limited by its reliance on English-language journal articles indexed in Scopus and by the conceptual nature of the proposed framework, which requires further empirical validation across different contexts and industries. By explicitly introducing economic embeddedness as a distinct analytical dimension, the framework extends existing embeddedness theory and provides a foundation for future empirical research on how firms contribute to local economic development and sustainability. Full article

With the rapid growth of electric vehicles (EVs) and renewable energy generation, Vehicle-to-Grid (V2G) technology has emerged as a promising approach for transforming EVs from passive charging loads into flexible distributed energy storage resources. By enabling bidirectional power exchange between EV batteries and the power grid, V2G can support renewable energy accommodation, peak shaving, demand response, ancillary services, and local grid balancing. This review provides a systematic synthesis of recent advances in V2G systems for renewable energy integration, with particular emphasis on coordinated scheduling, economic mechanisms, battery degradation, and user engagement. First, the technical foundations of V2G are introduced, including Vehicle-to-Everything operating modes, bidirectional charging architecture, aggregation mechanisms, grid-support services, and renewable accommodation pathways. Second, major scheduling strategies are reviewed, including price-based, load-based, renewable-forecast-driven, centralized, distributed, and hybrid approaches. Third, the economic feasibility of V2G is examined from the perspectives of revenue streams, pricing mechanisms, business models, battery aging costs, and compensation schemes. In addition, user participation barriers, such as range anxiety, battery lifetime concerns, loss of control, uncertain financial returns, and data privacy, are discussed. Key challenges related to communication standards, interoperability, cybersecurity, market access, policy design, and pilot-scale validation are also summarized. Finally, future development directions are identified, including AI-based scheduling, aggregator platforms, fleet-scale V2G, degradation-aware optimization, carbon-aware electricity markets, and user-centered participation mechanisms. This review highlights that large-scale V2G deployment requires the integrated coordination of technical scheduling, economic incentives, battery health protection, and user acceptance in renewable-rich power systems. Full article

With the increasing importance of green design in the business landscape, designers are compelled to shift towards eco-design practices. However, existing methodologies face challenges related to resource requirements, abstract concepts, and industry specificity. To address these challenges and stimulate innovation, this study proposes a green design methodology that integrates TRIZ concepts and is anchored in TRIZ evolutionary trends. The methodology includes function and attribute analysis, the introduction of green features, the identification of TRIZ trends through a two-stage process, and the use of a developed system to improve calculation efficiency. Detailed design solutions are generated by combining green features, TRIZ trends, and inventive principles. A case study validates the methodology, showcasing its value in promoting sustainable development. By leveraging the evolutionary potential of products and incorporating TRIZ, the methodology offers a promising approach to address sustainability challenges and drive innovation. This research serves as a starting point for a practical and efficient design methodology that utilizes TRIZ concepts and a computer-aided application tool. Future steps involve stress-testing the methodology and exploring its application in different domains. Full article

The global transition toward net-zero emissions has led to the restructuring of labor markets and an intensification of the demand for sustainability-competent business graduates. However, higher-education curricula lack an operationalized, job-competency-based framework, and this gap in knowledge is especially acute in emerging industrial economies that are facing pressures due to the ongoing decarbonization of the global supply chain. In this context, this study addresses two interrelated gaps in the relevant research: the lack of a structured system of criteria to assess competency in sustainability that is specifically geared toward business education, and the insufficient attention that has been paid to causal interdependencies among such criteria in previously developed frameworks. The authors apply a two-stage, hybrid multiple-criteria decision-making design based on the KSAO framework, which classifies professional competency into knowledge (K), skills (S), abilities (A), and other characteristics (O). A modified Delphi method that involved 12 academic and industry experts serving as surrogate assessors of competency requirements for business and management students was first used to consolidate 142 literature-derived items into 26 initial criteria, which were then refined into 12 core competencies in sustainability, identified through cross-domain expert consensus. Following this, fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) was applied to analyze the structure of causal influence among the retained criteria. The results identified interdisciplinary work as the primary driving competency and integrated problem-solving as the central hub with the highest prominence, with the two factors forming a bidirectional feedback dynamic that anchored the competency system. The retention of four “other” criteria (O-dimension)—ethical values, normative orientation, empathy, and adaptive resilience—confirmed that competency concerning sustainability in business education extends beyond technical knowledge into deeper dispositional attributes. These findings provide business schools in Taiwan with a structurally grounded logic of sequencing for their curricula, as well as a reference framework for curriculum design that is aligned with the Association to Advance Collegiate Schools of Business (AACSB) Societal Impact standards. While the findings are grounded in Taiwan’s specific ESG regulatory and industrial context, only the methodological approach is offered as a reference for comparable settings; the substantive findings require cross-national verification. Full article

The unprecedented rate of technological advances, accelerated industry disruptions and social and environmental sustainability crises require very different business organizations from the traditional paradigm. The main research question for this paper is: What change (paradigm shift) is needed for South African business organizations to be future-fit? The paper introduces an integrated, transdisciplinary paradigmatic model of an emerging, progressive future business organization in South Africa, as mostly influenced by Western futurists, and proposes an understanding of the paradigm shift required in our socially constructed reality for such organizations to emerge. A multi-method methodology, based on complexity theory and a transdisciplinary approach, was developed and applied. The researcher’s conceptualization of a ‘paradigm’, focusing on language-based representations, is explicated as a theoretical foundation. Textual analyses, including corpus linguistics, of practitioner-focused literature were used to elicit concept maps (or domain models) of the shared, societal-level mental models of a South African business organization for two periods: (1) the Traditional Business Organization, and (2) a Progressive Future Business Organization. The outcomes were compared using a novel qualitative method, resulting in a proposed set of societal-level ontological shifts needed for a progressive organizational future. The study shows a paradigm shift to complexity and social responsibility, and the need for transdisciplinarity to reflect complex, integrated organizational realities. Full article

With the advent of the Fourth Industrial Revolution, the adoption of digital transformation technologies has accelerated across industries. Digital transformation has become a critical task for businesses, with success depending on strategic responses to rapidly changing environments, where establishing a technology development roadmap is pivotal. This study proposes a framework for a technology roadmap aimed at promoting effective digital transformation and applies it to the Korean water industry. Key technological management areas requiring digital transformation were identified, followed by an evaluation of development trends, preferences, technology levels, and potential through expert surveys. Data were quantitatively analyzed using Euclidean distance and frequency analysis. Results indicate that the most urgent areas for digital transformation in the Korean water industry are natural environment management and prediction, water supply and customer service, water intake and resource facilities, and water purification. Essential technologies to be prioritized in each area were also derived. Unlike previous studies that only compared technological priorities, this research contributes by providing a multi-layered analysis that considers preferences, levels, and potential, constructing a more robust roadmap. Full article

Purpose/Background: Small and medium-sized enterprises (SMEs) that deploy Enterprise Resource Planning (ERP) systems face a persistent paradox: although ERP centralises organisational data, frontline users frequently lack the technical expertise to navigate complex menu structures, preventing efficient information retrieval for decision-making. This study presents a preliminary Research and Development (R&D) effort to design, build, and qualitatively evaluate a prototype intelligent question-answering system that connects to Odoo ERP through application programming interfaces (APIs) via Retrieval-Augmented Generation (RAG), enabling natural-language access to real SME business data. Methods: A single-organisation R&D case study was conducted at an SME in Khon Kaen Province, Thailand. The development cycle comprised problem analysis and requirement specification, system architecture design, prototype construction, integration and deployment, iterative testing and refinement, and multidimensional evaluation. The prototype was implemented with Chainlit (conversational interface), FastAPI (orchestration and tool-calling layer), and Odoo XML-RPC/JSON-RPC APIs (structured data retrieval). A fixed set of 20 test questions spanning four complexity levels (easy, moderate, complex, out-of-scope) was evaluated by three automated tools (OpenAI Evals, DeepEval, Ragas), by real-task verification against live ERP data, by five domain experts using 5-point Likert-scale questionnaires, and by three end users from the case-study organisation, who additionally completed the System Usability Scale (SUS). Given the very small expert and user samples, all human evaluation results are reported descriptively as preliminary, exploratory indicators rather than as statistically generalisable measures. Results: Automated evaluation achieved indicative pass rates of 95.00% (OpenAI Evals, 19/20), 90.00% (Ragas, 18/20), and 85.00% (DeepEval, 17/20). Descriptive expert feedback (n = 5) yielded an overall mean of 3.82 (high level), and descriptive end-user feedback (n = 3) yielded an overall satisfaction mean of 4.33 (highest level). The SUS score was 66.67/100, sitting at the boundary between ‘OK’ and ‘Good’ and revealing a divergence between high stated satisfaction and lower confidence in independent system use (item 9, raw mean = 2.33) and a stronger perceived need for expert assistance (item 4, raw mean = 2.67). These results are interpreted as preliminary diagnostic signals for further development rather than as confirmatory evidence. Conclusions: This preliminary R&D study suggests that a RAG-based ERP chatbot can meaningfully simplify ERP data access for SME users, while exposing persistent gaps in multi-step reasoning, user confidence, and data privacy boundaries that must be addressed in subsequent development cycles. The SUS pattern, in particular, suggests a ‘novelty effect’ in which users are enthusiastic about the natural-language interface yet remain anxious about correctness and stability during real tasks. Originality/Value: This work contributes a transparent, replicable preliminary R&D blueprint that combines (i) live API-mediated RAG over structured ERP data, (ii) a complementary multi-tool automated evaluation set (OpenAI Evals + DeepEval + Ragas), (iii) descriptive expert and end-user feedback, and (iv) SUS-based usability assessment, all documented for a single Thai SME using Odoo 18. The study explicitly positions itself as an early step toward larger, multi-site, and on-premise deployments of trustworthy ERP-integrated conversational agents. Full article

This paper proposes a regional distributed energy operation framework that integrates Power-to-X (P2X)-based sector coupling with Distributionally Robust Optimization (DRO) for distribution network operation environments in special zones established under South Korea’s Special Act on the Promotion of Distributed Energy. The conventional South Korean electricity market has primarily operated under a centralized Cost-Based Pool (CBP) structure, where the participation of small-scale renewable energy providers has been limited due to requirements for centralized dispatch generators. To address these structural limitations, the South Korean government introduced the distributed energy special zone policy and has promoted a Peer-to-Peer (P2P)-based electricity trading mechanism that enables direct electricity transactions between renewable energy providers and consumers within regional distribution networks. As a result of these policy initiatives, investment in small-scale renewable energy projects within designated special zones is expected to increase significantly; however, the limited local demand capacity of regional distribution networks simultaneously imposes clear constraints on the accommodation of renewable energy. Therefore, this study applies P2X-based sector coupling technologies to improve the capability to accommodate renewable energy within special zones while simultaneously establishing new energy business models. In addition, DRO is incorporated into the proposed framework to demonstrate the system’s economic feasibility and operational robustness under high uncertainty in electricity prices. Full article

Reusing cast-in-place (CIP) concrete elements could enhance the sustainability of the construction industry by enabling circularity, preserving embodied value, and reducing primary resource consumption, construction and demolition waste, and emissions from new concrete production. However, the implementation of such reuse is hindered by project-specific geometries, monolithic connections, and complex coordination requirements. Existing process representations address individual aspects of reuse, but an integrated process framework for coordinating assessment, dismantling, logistics, and reuse across multiple actors and projects is still lacking. To address this gap, this study develops a concept for a process-driven digital ecosystem supporting the circular reuse of CIP concrete elements within the Collaborative Research Centre 1683. Literature-based process representations are analysed, translated into Business Process Model and Notation (BPMN), and synthesised into domain-specific process models. The resulting models formalise the reuse chain, clarify actor responsibilities and information flows, and support the identification of technical, temporal, and spatial dependencies. Building on this formalisation, a conceptual digital ecosystem is derived that links information on reusable elements with process logic and reuse-related decision-making. The concept centres on a construction kit (CK) as a standardisation layer and an element data store (EDS) as the information basis for traceability, coordination, and matching. The results provide a structured foundation for digitally supported sustainability-oriented circular construction and for future ontology integration, process simulation, and decision-support applications. Full article

The emergence of digital technologies during the last two decades has placed strain on democracies globally. From disinformation to artificial intelligence (AI), policy-makers have struggled to address the authoritarian and anti-democratic tendencies that Big Tech companies have been pushing. A dominant response from European Union (EU) policy-makers has been to promote ‘literacy’: media literacy to address disinformation, and ‘AI literacy’ to foster constructive uses of AI. We ask: what does it mean for the EU to use media literacy and AI literacy as a response to disinformation and the risks of AI? More broadly, what kind of policy and model of democracy is being constructed when the EU suggests that the solution to disinformation and AI depends on citizens becoming more “literate”? We empirically examine the usage of ‘literacy’ in EU policy documents in the context of disinformation and AI, and argue that it shifts responsibility from platforms to individual citizens. In doing so, it moves attention away from a structural approach into the political economy of Big Tech companies, hence empowering them and their ‘surveillance capitalist’ business model. This article argues instead that literacy needs to be rethought beyond individual skills, as a way of making visible the structural and infrastructural power of privately owned digital systems shaping contemporary public spheres. Therefore, reclaiming democracy requires moving beyond individual adaptation, and instead towards addressing the underlying systemic structures of Big Tech power. Full article

Sensor-based Particle Ore Sorting (POS) has gained significant acceptance as a unit process in mineral processing in recent years, particularly in the diamond, copper, tin, and tungsten sectors. The increased uptake has led to a steady increase in testwork volume since 2010. Testwork is the basis for all technical and financial evaluation of a potential business case for POS. To support the growing volume of POS testwork, this contribution develops standardized test methodologies and sampling requirements for different project stages. Our aim is to bridge the understanding and terminology between the various technical disciplines involved. This allows all stakeholders to enter the complex realm of POS with full transparency. Tests can be conducted using three different feed types: endmember samples, lithotype samples, and composite samples. Four testwork methods are presented for POS project development and optimization: Single Particle Test (SPT), Bench Scale Test (BST), Cascade Test (CT), and Process Test (PT). From the possible combinations, this results in ten POS testwork methods. Each test type serves a different purpose with regard to process effectiveness contributions and relationships to the project lot, serving specific roles during project stages from scoping to feasibility. Specific project parameters are recommended to be defined up front for future POS projects to improve clarity and interpretation of test objectives, limitations, and results. Full article

Agile teams often struggle to translate business requirements into maintainable, high-quality software due to the persistent ambiguity in the roles and relationships of behavior-driven development (BDD), Acceptance Test-driven Development (ATDD), and Test-driven Development (TDD). These approaches are frequently misunderstood, inconsistently applied, and only loosely connected within a unified delivery lifecycle. This article introduces BLOW (Behavior-Driven Development in a Layered Organization of Work-Centers), a systematic approach that establishes BDD as the coordinating methodology between ATDD (business-focused) and TDD (technology-focused). BLOW structures scenario-driven development across layered domains of accountability with clearly defined roles and responsibilities, organizing delivery through nested work-centers that transform user stories into executable specifications and production code. This approach integrates two complementary collaboration practices: the Three Amigos for discovering and formulating business scenarios, and the proposed Technical Three Amigos for linking those scenarios to Technical Domain Contexts, identifying required Enablers, and deriving technical scenarios when additional architectural support is needed. The proposed operating model emphasizes observability through executable scenarios as first-class artifacts, introducing native, test-anchored metrics that support reasoning about progress, technical effort, and value delivery within scenario-driven development. An exploratory longitudinal case study, consisting of a single-sprint proof of concept followed by an 18-month production deployment, reports patterns in which technical enablement precedes business value delivery and reusable infrastructure supports sustained growth of business scenarios over time. The findings also indicate that changes in the applied operating model are associated with measurable shifts in scenario evolution and internal quality indicators. Overall, BLOW provides a governance-compatible, end-to-end approach for organizing scenario driven development and improving alignment between stakeholder intent and technical implementation in complex software systems. Full article