Search Results (1,328)

Purpose: This study examines how large multinational corporations translate sustained macroenvironmental volatility into deliberate strategic reconfiguration processes, and how adaptive mechanisms differ across business models and sectors under shared environmental pressures. Design/Methodology: The study employs a qualitative comparative multiple-case design with abductive logic and a longitudinal perspective covering 2019–2024. Apple, Amazon, and McDonald’s were selected through theoretical sampling for their sector heterogeneity, their shared global regulatory and operational exposure, and their contrasting adaptive architectures—vertical integration, platform diversification, and franchising, respectively—rather than a uniform majority-international-revenue criterion. A corpus of 78 primary and secondary documents was analysed through open coding, axial coding, thematic aggregation, cross-case comparison, and pattern matching. Findings: All three firms converge around digitalisation, regulatory compliance, and sustainability as environmental legitimacy requirements rather than differentiating strategic choices. Divergence emerges in execution mechanisms: Apple deploys anticipatory vertical integration; Amazon converts operational complexity into structural barriers; McDonald’s exploits franchise flexibility for local adaptation while preserving brand coherence. The analysis yields an original Adaptive Reconfiguration Cycle (ARC Framework) comprising five iterative stages, evidenced for each firm across the full cycle rather than only its dominant stage. Theoretical Contribution: The study develops an integrated macroenvironment–capability reconfiguration framework that bridges PESTEL analysis, dynamic capabilities theory, and contingency theory, addressing an under-explored integration gap in each tradition. Three theory-building propositions, generated inductively from the three comparative cases and not presented as empirically established relationships, are advanced together with their moderating conditions. Practical Implications: Firms must institutionalise environmental sensing as a permanent strategic function, treat compliance capabilities as competitive assets, and build adaptive capacity as a standing organisational competency. Originality/Value: This study is among the few comparative analyses to integrate PESTEL trigger structures with dynamic capabilities reconfiguration logic across heterogeneous sectors using longitudinal evidence. The ARC Framework is offered as an analytically transferable, theory-generating model with explicit boundary conditions and testable propositions, rather than as a broadly generalisable one. Full article

Artificial Intelligence (AI) has emerged as a transformative force in the global economy, yet its contribution to environmentally sustainable productivity growth remains insufficiently understood. Using 33,017 firm-year observations from 4079 Chinese A-share listed firms during 2015–2024, this study examines the relationship between AI adoption and corporate green total factor productivity (GTFP). We construct a text-based proxy for AI adoption by applying a machine learning-generated dictionary to the management discussion and analysis (MD&A) sections of annual reports. We construct the GTFP proxy using the slacks-based measure, the Malmquist–Luenberger (SBM-ML) index, which incorporates undesirable outputs. The results show a significant positive relationship between AI adoption and GTFP. This relationship remains robust across a series of robustness checks, including alternative specifications, PSM-matched sample analysis, instrumental variable estimation, and exogenous shock design. Further analysis identifies R&D intensity as an important transmission channel. The relationship is stronger among firms facing tighter financing constraints, non-polluting industries, and non-state-owned enterprises. The positive association between AI adoption and firm value further indicates that its economic relevance may extend beyond environmental efficiency in the long term. These findings highlight the potential of AI-enabled innovation to advance green productivity and sustainable corporate development in emerging economies. Full article

Background/Objectives: The TEG^® 6s is a hemostasis analyzer system used to assess viscoelastic properties of whole blood. Although it provides rapid and comprehensive insights, interpreting thromboelastography tracings requires robust clinical training and is not standardized. Our aim was to develop and evaluate a prototype of MetaTEG—an AI-driven support tool for interpreting TEG^® 6s tracings, with a focus on the Global Hemostasis-Heparin Neutralization cartridge. Methods: TEG^® 6s tracings, obtained from Haemonetics Corporation’s internal case library, were used to train a custom AI agent developed with Microsoft Copilot Studio. Five different clinical cases were used for testing. The AI agent incorporated knowledge graph augmentation and prompt engineering to integrate published literature and assess coagulation states based on R-time, maximum amplitude, and other key parameters. The evaluation of the AI virtualization outcomes included semiquantitative scoring by an internal TEG expert panel who assessed the AI’s diagnostic accuracy, tracing interpretation, and therapeutic recommendations. UI/UX prototypes were designed in Figma to demonstrate potential integration into clinical workflows. Results: Using this proof-of-concept dataset and qualitative expert scoring, MetaTEG accurately described and interpreted TEG^® 6s tracings and suggested potential treatment options. Reviewers consistently rated the AI-generated outputs as both clinically useful and accurate. Conclusions: The MetaTEG prototype represents the first application of generative AI for TEG^® 6s interpretation, showcasing the potential of AI-powered, human-in-the-loop decision support in hemostasis diagnostics. Full article

The Kunming–Montreal Global Biodiversity Framework (hereafter “KMGBF”) sets 23 action targets for 2030, and its implementation has now entered a critical phase. Despite the Framework’s emphasis on a whole-of-society approach, little is known about how transnational biodiversity initiatives relate to its targets. Using qualitative content analysis and social network analysis, we identify linkages between 35 transnational biodiversity initiatives and the 23 KMGBF targets and compare these patterns with target mappings reported in National Biodiversity Strategies and Action Plans (hereafter “NBSAPs”) from 167 Parties. We find that initiatives primarily address targets concerning capacity-building and knowledge management, whereas NBSAPs exhibit broad coverage across all targets. Within the target–target network, spatial planning functions as an important bridging target connecting otherwise separate subsets of biodiversity issues, despite having only moderate overall connectivity. Four action targets—including corporate disclosure and harmful subsidy reform—remain entirely unaddressed by the initiatives in our sample. These targets turn primarily on regulatory and policy interventions, suggesting a stronger role for states in their implementation. These findings suggest that states and transnational initiatives relate to the Framework’s targets in distinct but potentially complementary ways. Full article

In recent times, with increasing awareness of sustainable development, environmental, social, and corporate governance (ESG) performance has emerged as an important factor in achieving sustainable development. In the current literature, the determinants of ESG performance are mostly considered at the macro level, while the impact of firm-specific factors remains limited. To fill the gap in the literature, this study uses panel data from 2014 to 2023, focusing on 89 global firms, and applies the GMM approach to examine the impact of firm-specific factors on firms’ ESG performance. The findings reveal that ESG performance demonstrates strong continuity. Furthermore, the effects of financial indicators on ESG performance differ. While return on assets and capital expenditures negatively impact environmental performance, return on equity positively affects liquidity, firm size, and market capitalization for some ESG dimensions. Conversely, the total debt to total equity has a negative impact on social performance. The findings of this study regarding the impact of financial indicators on ESG performance have important implications for firms. This paper contributes to the ESG literature by providing empirical evidence that highlights the dynamic impact of firm-specific factors on ESG performance. Full article

Amid the global push for sustainability, Environmental, Social, and Governance (ESG) criteria have become core benchmarks for corporate value. Simultaneously, government WeChat accounts have reshaped China’s regional information ecosystems. This paper systematically examines the impact of the launch of government WeChat accounts (LGWA) on agricultural enterprises’ ESG performance. Drawing on information asymmetry theory, we treat municipal-level LGWA as a quasi-natural experiment, employing an optimized double machine learning (DML) model. The study utilizes unbalanced panel data from 326 listed agricultural enterprises (2009–2024) and over five million WeChat messages. Results indicate LGWA significantly enhances ESG performance by alleviating government-enterprise, enterprise-public, and bank-enterprise information asymmetry. Executive political connections negatively moderate this effect. This enhancement is more pronounced for highly active accounts posting during work hours, particularly benefiting less-digitalized enterprises. This study provides a novel perspective on the micro-level governance effects of digital government, guiding sustainable policy formulation and encouraging corporate digital adoption. Full article

To address the limitations of the original Honey Badger Algorithm (HBA), including premature convergence, limited search directionality, and insufficient local escape capability in high-dimensional complex optimization problems, this paper proposes an improved Honey Badger Algorithm based on a traffic-driven strategy, namely the Traffic-driven Covariance Honey Badger Algorithm (TCHBA). The proposed algorithm introduces three synergistic evolutionary mechanisms. First, Elite Covariance Rotation Guidance learns correlated search directions from the current elite subset and injects a truncated covariance-based step into the HBA update. Second, Urban Traffic-Inspired Search uses population density and an iteration-dependent signal to regulate attraction and diversion. Third, Stagnation-Aware Lens Opposition Mutation is activated after unsuccessful updates and combines lens opposition with a heavy-tailed Cauchy perturbation to restore search mobility. Extensive experiments are conducted on the CEC2017 (100-dimensional) and CEC2022 (10- and 20-dimensional) benchmark suites. The results demonstrate that TCHBA significantly outperforms nine state-of-the-art optimization algorithms, including VPPSO, EGWO, GJO, RIME, ALA, HBO, MO, PWO, and the original HBA, in terms of solution accuracy, convergence speed, and statistical robustness. Furthermore, TCHBA is applied to the problem of Taiwanese enterprise bankruptcy prediction, a representative financial risk classification task. By optimizing the key parameters of the K-nearest neighbors (KNN) classifier, a TCHBA-KNN prediction model is constructed. Experimental results on real-world datasets show that the proposed model achieves superior performance in terms of accuracy, Matthews correlation coefficient (MCC), recall, and F1-score, thereby validating the effectiveness and practical potential of the proposed algorithm for real-world engineering and financial decision-making problems. Full article

Despite the growing importance of intercultural marketing in global consumer markets, limited research has examined how intercultural marketing factors interact and contribute to corporate competitiveness within internationally recognised consumer brands. Therefore, this case study investigates these relationships using the example of a globally recognised consumer brand. Drawing on Hofstede’s Cultural Dimensions Theory and intercultural marketing literature, this study investigates the relationships between event marketing, consumer behaviour and sales factors using the case of Red Bull in the global energy drink industry. Data obtained from 50 respondents were analysed using affinity diagrams, relationship diagrams, linear regression and the Analytic Hierarchy Process (AHP). The results confirmed positive relationships between event marketing and consumer behaviour (r = 0.401) and between consumer behaviour and sales factors (r = 0.400). The study contributes to international marketing literature by proposing an integrated framework linking intercultural marketing activities with corporate competitiveness and identifying the most influential marketing sub-criteria. The study further focuses on the identification and comparison of sub-criteria using the Analytic Hierarchy Process (AHP) method. Full article

The global energy transition is increasingly shaped by industrial competition, supply chain restructuring, and fragmented regulation. Morocco seeks to turn its renewable energy potential into green industrial capacity, while China has become an important partner in renewable-energy infrastructure, battery materials, storage, and hydrogen. This study examines whether China–Morocco energy cooperation is moving from individual projects toward green industrialization, and what conditions shape its sustainability outcomes. Using a qualitative case study approach, it analyzes policy documents, legal texts, corporate announcements, project records, and international organization reports from 2016 to June 2026. The project database covers twelve projects: four operational, three under construction, three signed, one awarded, and one announced. The findings show an emerging, partial, and uneven shift in project composition that points toward a potential project-to-industry transition, though industrial upgrading remains largely prospective. Chinese investment may support Morocco’s renewable deployment, manufacturing localization, and participation in low-carbon value chains, but these gains depend on domestic supplier linkages, workforce skills, technological absorption, environmental governance, and institutional coordination. European Union (EU) due-diligence rules and United States (U.S.) clean energy policies also create regulatory exposure and compliance pressures that may shape project ownership, sourcing, production standards, and export-market access. The study argues that foreign green capital alone does not constitute green industrialization. Sustainable progress depends on Morocco’s ability to anchor individual projects in local capabilities while adapting to a fragmented geoeconomic environment. Full article

This study addresses organizational adaptation under conditions of prolonged market instability within capital-intensive real estate sectors. It investigates the multidimensional alignment between crisis-era decisions and reported post-crisis organizational actions among 144 active housing developers in Istanbul. A two-stage analytical method was employed: nonlinear canonical correlation analysis (OVERALS) evaluated the global association between the two action sets, while co-occurrence network analysis and bridge centrality identified the structural positioning of individual practices. The findings indicate a non-random pattern of association that is broadly consistent with evolutionary resilience perspectives, without implying direct causal relationships or testing temporal performance shifts. Knowledge-oriented and relational practices—specifically corporate social responsibility, R&D and new market activity, and consultant reports—exhibited the highest cross-set connectivity with reported post-crisis adjustments. Defensive actions displayed more heterogeneous cross-set positions: project suspension was non-bridging under the baseline threshold, whereas budget control retained a comparatively prominent position in the bridge-strength ranking. This pattern suggests that defensive actions were not uniformly peripheral within the observed network. Overall, this study offers an exploratory framework for understanding how crisis-era action configurations correspond to reported organizational practices in highly volatile urban property markets. Full article

Against the combined backdrop of intensifying global climate governance, China’s carbon-peaking and carbon-neutrality goals, and the rapid deployment of artificial intelligence (AI) for low-carbon development, this study examines how AI adoption affects the carbon emission intensity of energy firms. Using panel data for listed Chinese energy firms from 2010 to 2023 and fixed-effect models, we find that AI adoption significantly reduces carbon emission intensity; this result remains robust to alternative variable measures, lagged specifications, and other sensitivity tests. Executive digital background strengthens this effect, while the low-carbon city pilot policy provides a complementary institutional incentive that generates additional emission reductions when combined with AI. Mechanism tests indicate that AI lowers carbon emission intensity by increasing capacity utilization, improving supply-chain efficiency, and raising production efficiency. The effect is stronger in eastern and central China, state-owned enterprises, conventional energy firms than in western China, non-state-owned enterprises, and new-energy firms. These findings provide firm-level evidence on how AI facilitates the low-carbon transition of the energy sector and offers actionable implications for policy design and corporate strategy. Full article

Against the backdrop of global sustainability transitions and the growing importance of ESG investing, firms face increasing trade-offs between short-term financial objectives and long-term ESG commitments. While previous studies have mainly examined how ESG performance affects financial outcomes, less attention has been paid to whether financial performance influences subsequent ESG strategies and how the national culture shapes this relationship. Drawing on the resource-based view and Hofstede’s cultural dimensions theory, this study employs cross-country firm-level panel data and logistic regression models to examine whether prior-year financial performance target achievement promotes subsequent ESG improvement. The results show that firms achieving their financial targets are significantly more likely to improve ESG performance in the following year, suggesting that financial success provides the resources needed to support ESG investment. Moreover, the effect varies across national cultural contexts, highlighting the moderating role of cultural heterogeneity. By examining the reverse pathway from financial performance to ESG, this study extends the conventional ESG–financial performance literature and provides new evidence of the dynamic interaction between financial objectives and ESG strategies. These findings also contribute to understanding how national culture influences corporate sustainability decisions and strategic resource allocation. Full article

The news media in Gulf countries are among the most important institutions shaping the public’s understanding of climate action. This study aims to explore the longitudinal developments, thematic framing, and sentiment tones of Omani English-language newspapers’ sustainability discourse during the period 2015–2025. The study applied a multi-stage computational method to analyze a deduplicated corpus of 709 news articles from two English-language dailies of Oman: Times of Oman and Oman Daily Observer for a time period from 2015 to 2025. Latent Dirichlet Allocation (LDA) topic modeling was used to group topics into five types of macro frames. Results show that the focus of the Omani media is very localized, and the dominant frames are “Corporate ESG, Business & Green Investment” and “Clean Energy Policy, Research & Institutional Governance”. Furthermore, a sentiment analysis of headlines using VADER showed clearly defined sentiment polarity; domestic economic transition headlines were characterized by high positive polarity, while global climate crisis headlines had a higher negative polarity. The study concludes that the press in Oman is in a strategic process of “nationalizing” the climate change issue, moving from the conventional disaster discourse to making sustainability a local opportunity for economic diversification, technological modernization, and national resilience. Full article

With climate risk and sustainable development dominating global policy agendas, a key question for regulators and researchers alike is whether and under what conditions fintech development is associated with improved corporate ESG performance. Using A-share listed firms in China from 2011 to 2024, this paper builds a city-level fintech index from Baidu News advanced search records and links it to firm-level ESG and financial data. Our baseline estimates confirm that fintech development significantly improves corporate ESG performance. This core finding remains robust across lagged regressors, an ordered logit specification, additional industry fixed effects, the exclusion of the 2020 to 2022 pandemic window, and a spherical-distance-to-Hangzhou instrumental variable. Mechanism tests reveal two complementary channels: fintech eases financing frictions and stimulates green innovation. Further analyses are conducted to explore boundary conditions. Both management shareholding and spatial competition exert direct positive effects on ESG performance, yet their interactions with fintech are significantly negative, pointing to a substitution rather than complementary relationship. Heterogeneity analysis shows that the effect is more pronounced among state-owned enterprises, large firms, non-high-tech and labor-intensive industries, growth-stage firms, and firms in the eastern region. Our results offer differentiated policy implications for strengthening digital infrastructure, refining financing arrangements for growth-stage and SMEs, and calibrating region- and life-cycle-sensitive regulatory frameworks. Full article

The study addresses the design and development of a unified corporate information system for multimodal transport and logistics companies engaged in maritime and railway transportation. Analysis of the existing literature revealed the absence of a coherent methodological framework for the design of corporate information systems tailored to the specific operational characteristics of multimodal transport and logistics enterprises. To bridge this gap, a design methodology for corporate information system databases is proposed, intended for subsequent deployment in companies operating multimodal supply chains. The development of the unified corporate information system was guided by the principle of “total costs,” which requires that the decision-maker—when selecting transport modes, methods of transportation, carriers, routing, and auxiliary intermediaries (insurer, stevedore, bank, and customs broker)—address the problem as an integrated whole rather than optimizing individual components in isolation. The study encompasses information modeling of the business processes of multimodal transport and logistics companies, construction of an optimal model of the transport process for maritime and railway transportation using integrated computer automated manufacturing definition (IDEF) and structured analysis and design technique (SADT) modeling, and the design of a multilevel unified database structure for the coordination of different transport modes. A decision-making and support system has been developed for managing the operational activities of a multimodal transport and logistics company engaged in maritime and railway transportation. The proposed unified corporate information system enables the replacement of task resolution by local optimization criteria applied separately to each transport mode—such as freight cost and delivery time—with a single global optimization criterion for the multimodal supply chain. Full article