Search Results (839)

Building archetypes are essential for advancing architectural theory and energy modeling, providing a foundation for scalable assessments of building performance and sustainability worldwide. In Saudi Arabia, educational buildings, especially those in public universities, are predominantly constructed using standardized and repetitive design templates, such as courtyard and prototype models, which have significant implications for energy efficiency, indoor environmental quality, and sustainability outcomes. Despite their prevalence, there is a notable lack of systematic research on the classification and distribution of these archetypes within the Saudi context, particularly regarding their impact on energy consumption and sustainable campus planning. This study addresses this gap by systematically collecting and analyzing data from 29 public universities across Saudi Arabia, employing GIS mapping to document building characteristics including age, region, urban context, masterplan typology, and architectural design. A cumulative weighting factor was applied to quantify the representativeness of archetypes, while chi-square tests and effect size metrics assessed the statistical concentration and significance of observed patterns. The results reveal a pronounced dominance of a small number of archetypes, especially standardized courtyard and identical design models, across the national stock, with the top 10% of archetype ranks accounting for the majority of buildings. This high degree of standardization enables efficient modeling, benchmarking, and targeted energy interventions, while also highlighting the need for greater contextual adaptation in future campus planning. While this study does not directly simulate building energy performance, it establishes a national-scale typological foundation that can support future simulation, benchmarking, and policy design. The developed GIS-based framework primarily serves managerial and planning objectives, offering a standardized reference for facility management, retrofitting prioritization, and strategic energy-efficiency planning in Saudi public universities. Full article

The integration of artificial intelligence (AI) and information technology (IT) is transforming business operations while increasing energy demand. A scalable and nonintrusive method for assessing the adoption of energy-conscious IT governance without direct measurements of energy use is lacking. To address this gap, a machine learning framework is developed and validated that infers the presence of energy-conscious IT governance from five indicators of digital maturity and AI adoption. Enterprise survey data were used to train five classification algorithms—support vector machine, logistic regression, decision tree, neural network, and k-nearest neighbors—to identify organizations implementing energy-efficient IT/AI management. All models achieved strong predictive performance, with SVM achieving 90% test accuracy and an F1 score of 89.8%. The findings demonstrate that an enterprise’s technological profile can serve as a reliable proxy for assessing sustainable IT/AI practices, enabling rapid assessment, benchmarking, and targeted support for green digital transformation. This approach offers significant implications for policy design, ESG reporting, and managerial decision-making in energy-conscious governance, supporting the alignment of digital innovation with environmental objectives. Full article

This study examined the impact of supply chain collaboration (SCC) on supply chain innovation (SCI) and sustainability performance in the context of manufacturing firms in Jordan. The study also investigated the mediating role of SCI in the relationship between different types of SCC and sustainability performance. SCC was represented by three types namely, customer collaboration, supplier collaboration, and internal collaboration. Data were collected using a structured questionnaire that was distributed to employees from numerous management levels in firms located in Jordan as a developing country. A total of 314 valid responses were obtained between December 2024 and March 2025. The data were analyzed using partial least squares structural equation modeling with using the SmartPLS software package. The results of the study revealed that customer, supplier, and internal collaboration significantly enhanced SCI. These three forms of SCC also improved sustainability performance. SCI was found to directly influence sustainability performance, confirming its role as a driver of sustainable outcomes. Moreover, SCI mediated the relationship between internal collaboration and sustainability performance. However, no mediating effects were found between customer or supplier collaboration and sustainability performance. The findings contribute to the resource-based view and dynamic capabilities theory by highlighting collaboration and innovation as critical pathways for achieving sustainable performance. The study offers managerial insights for manufacturing firms in Jordan, emphasizing the importance of strengthening collaboration with customers and suppliers, while also fostering internal innovation to embed sustainability into organizational practices. Full article

Drawing on prior research, this study analyzes panel data from listed companies (2013–2023) to examine how chairpersons’ local social connections affect corporate green innovation. Specifically, it explores how such networks provide access to resources and policy advantages through social capital, thereby shaping firms’ green innovation. The findings reveal that local chairpersons negatively affect firms’ green innovation. Firms led by local chairpersons undertake significantly fewer green innovation initiatives than those with non-local leaders. Moreover, ESG performance and a strong legal environment can mitigate the negative impact of local chairpersons on green innovation. In contrast, stable executive teams may alleviate the adverse effect of local chairpersons on corporate green innovation by curbing myopic managerial behavior and reinforcing a long-term strategic orientation. Full article

Biophilic designs and elements have been the focus of numerous studies due to their potential impact on key marketing outcomes including satisfaction, word-of-mouth, and revisit intentions. However, previous studies have mainly relied on simplified image-based experiments that focused only on the presence or absence of biophilic elements, overlooking the quality of these designs as hotel guests actually experience them. This study aimed to investigate the quality of actual biophilic elements in hotel service settings and their impact on guest well-being, perceived value, and patronage intentions while also exploring the moderating effects of guest delight. The study employed a self-administered questionnaire survey to collect data from a total of 428 guests who had already stayed at hotels with biophilic designs/elements in Egypt. Using SmartPLS 3.0, a PLS-SEM analysis was performed to test the study hypotheses and conceptual model. The findings revealed that the high quality of biophilic designs/elements in hotels significantly affected guest well-being and perceived value, which eventually supported revisit intentions and willingness to pay a premium. The results also affirmed the moderating effects of guest delight on the proposed model. This study addresses a notable knowledge gap and provides valuable managerial implications regarding hotel biophilic designs. Full article

As climate change poses growing sustainability challenges worldwide, companies face unprecedented pressure to innovate in environmentally sustainable ways. This study examines the impact of extreme climate risks on corporate green innovation through the State-Pressure-Response framework, using data from Chinese A-share listed companies between 2014 and 2024. Results demonstrate that extreme climate risks significantly promote corporate green innovation levels. Mechanistically, climate risks exacerbate companies’ financing constraints, yet under evolving green finance architectures, this financial pressure can drive them toward green innovation to improve their access to preferential green financing channels. Media attention amplifies this sustainability-oriented response by heightening reputational stakes, while managerial myopia weakens it by prioritizing immediate performance over long-term sustainable development. The effect is most pronounced among heavily polluting industries and state-owned enterprises, revealing differential pathways toward sustainable transformation. These findings offer valuable guidance for policymakers seeking to harness climate pressures for sustainable transformation through targeted green finance expansion, mandatory climate risk disclosure frameworks, and corporate governance reforms that align executive incentives with long-term environmental performance. Full article

The advent of artificial intelligence marks a decisive turning point in the evolution of Industry 5.0, redefining the paradigms of industrial performance. This holistic transformation affects not only technological aspects but also the entire industrial ecosystem. Industrial performance is amplified by AI through two major axes: operational excellence and strategic differentiation of solutions. These drivers of performance are structured around concrete strategic advantages, particularly in terms of technological leadership and operational resilience. However, this transformation raises significant challenges on both the human, technical, and financial levels. The managerial implications require a structured approach to the adoption of AI, supported by appropriate organizational development. Future prospects suggest an ever-deeper integration of AI within the industrial ecosystem, paving the way for new models of performance and innovation. In this paper, we strive to make a scientific contribution aimed at shedding light on the impact of artificial intelligence on Industry 5.0, highlighting its implications for the pillars of industrial transformation: operational efficiency and optimization of industrial processes, technological innovation, and competitiveness. We have opted for a theoretical analysis of research related to the integration of AI into industrial systems, in order to provide a synthetic and critical review of this phenomenon. Full article

Corporate carbon information disclosure (CID) is gradually transitioning from being voluntary to mandatory, consistent with the global consensus on addressing climate change and achieving sustainable development. CID reflects corporate environmental performance and is a crucial source for the market to comprehend corporate environmental risks and assess their long-term value. However, corporate operations are often influenced by managers’ behavioral preferences when formulating disclosure strategies, as managerial cognitive vision and values directly affect strategic decisions. This study used a sample of Chinese A-share-listed companies for 2010 to 2023 to investigate the relationship between managerial myopia and CID. The findings indicate that managerial myopia significantly inhibits CID by reducing executive environmental awareness and corporate green innovation capabilities. A heterogeneity analysis shows that managerial myopia has a stronger inhibitory effect on CID in companies with weak governance structures and those that are not technology-intensive, providing valuable references for environmental performance and CID practice in emerging countries. Full article

As environmental degradation intensifies, governments increasingly subsidize green manufacturing to promote sustainability. This study develops a game-theoretic model of two competing supply chains, comprising original equipment manufacturers (OEMs) and both traditional and green contract manufacturers (CMs), to investigate the impacts of subsidies on green manufacturing adoption. Specifically, we construct a four-stage dynamic game model to examine the interactions among OEMs, CMs, and the government. The main findings are as follows: First, the government subsidy affects OEMs’ adoption decisions only if the production cost of green manufacturing or competition intensity is sufficiently high or if the market sensitivity to green products is relatively low. Second, the optimal subsidy level depends jointly on the production cost of green manufacturing, competition intensity, and market greenness sensitivity: when the production cost of green manufacturing is low (high), the subsidy should rise (fall) with market greenness sensitivity but fall (rise) with competition intensity. Third, while intensified competition reduces OEMs’ profits and overall supply chain performance, its impact on CMs and consumers depends on the production cost of green manufacturing; in contrast, greater consumer sensitivity to green products yields an all–win outcome for all stakeholders. These results yield important managerial implications. For policymakers, when the production costs of green manufacturing are relatively low, green subsidies should be scaled back as market competition intensifies. For manufacturers, it is critical to carefully evaluate the production costs of green manufacturing and the level of government subsidies and to strategically pursue first-mover advantages in advancing sustainable operations, thereby fostering an all-win outcome for stakeholders. Full article

The agricultural sector is a cornerstone of Serbia’s economy, ensuring national food security and contributing significantly to GDP, but it also generates notable environmental pressures, particularly through air and water pollution. This paper investigates the impact of agricultural enterprises’ environmental pressures on their financial performance between 2011 and 2021. The sample comprises 52 of the 63 agricultural enterprises listed in the national PRTR register as major air polluters in Serbia. Using enterprise-level data, environmental performance is measured through air emissions relative to revenues, while profitability is captured by return on assets (ROA). Panel regression analysis is conducted with Dynamic Ordinary Least Squares (DOLS) and Fully Modified Ordinary Least Squares (FMOLS) estimators to assess the long-run relationship between eco-efficiency and financial outcomes. The results show that reductions in environmental pressure are associated with improved profitability, highlighting the trade-offs and synergies between ecological responsibility and economic performance. These findings underscore the importance of promoting eco-efficiency as both a managerial strategy and a public policy priority, offering evidence to support Serbia’s alignment with EU environmental and agricultural sustainability goals. Full article

In this paper we present an exact numerical model for the evaluation of a three-echelon supply chain with multiple retailers. Poisson demand, exponentially distributed transportation times and lost sales at the retailers are assumed. The system is modeled as a continuous time Markov chain, and the analysis is based on matrix analytic methods. We analyze the infinitesimal generator matrix of the process and develop an algorithm for its construction. Performance measures for the system are calculated algorithmically from the stationary probabilities vector. The algorithm is used for an extensive numerical investigation of the system so that conclusions of managerial importance may be drawn. Full article

Smart grid operators face escalating cyber threats and tight resource constraints, demanding the transparent, defensible prioritization of security controls. This paper asks how to select cybersecurity controls for smart grids while retaining picture fuzzy evidence throughout and supporting policy-sensitive “what-if” analyses. We propose a hybrid Picture Fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA) and Combinative Distance-based Assessment (CODAS) framework that carries picture fuzzy evidence end-to-end over a domain-specific cost/benefit criteria system and a relative-assessment matrix, complemented by multi-scenario sensitivity analysis. Applied to ten prominent solutions across twenty-nine sub-criteria in four dimensions, the model highlights Performance as the most influential main criterion; at the sub-criterion level, the decisive factors are updating against new threats, threat-detection capability, and policy-customization flexibility; and Zero Trust Architecture emerges as the best overall alternative, with rankings stable under varied weighting scenarios. A managerial takeaway is that foundation controls (e.g., OT-integrated monitoring and ICS-aware detection) consistently remain near the top, while purely deceptive or access-centric options rank lower in this context. The framework contributes an end-to-end picture fuzzy risk-assessment model for smart grid cybersecurity and suggests future work on larger expert panels, cross-utility datasets, and dynamic, periodically refreshed assessments. Full article

This study investigates the determinants of customers’ perception of business model innovation (BMI) and its impact on customer satisfaction (CS), customer loyalty (CL), and firm sustainability (FS) within Ecuadorian family economic groups (EFEGs). It also examines the moderating role of perceived BMI in the relationships between CS, CL, and FS. Data were collected through an online survey yielding 342 valid responses, using a structured instrument that included socio-demographic variables, perceived EFEG characteristics, and nine validated constructs. Reliability and validity were corroborated through exploratory and confirmatory factor analyses, while structural equation modeling (SEM) and multiple regression analyses were employed to test the proposed relationships. The results reveal that socially responsible consumption (SRC), technological/digital customer skills (TCS), value creation innovativeness (VCrI), value proposition innovativeness (VPI), and value capture innovativeness (VCI) significantly influence customers’ perception of BMI. In turn, BMI positively influences CS, CL, and FS, and moderates the relationships between CS and FS, and CL and FS, though it does not significantly moderate the CS–CL relationship. These findings are consistent with previous research on European family firms, emphasizing the relevance of innovation capabilities, entrepreneurial orientation, and socioemotional wealth in enhancing adaptability and performance in family-owned businesses. This study contributes novel empirical evidence on BMI in the context of an emerging economy dominated by family firms. It underscores BMI as a dynamic capability crucial for fostering customer engagement, improving competitiveness, and ensuring long-term sustainability. Managerial implications suggest that EFEG managers should prioritize digital integration, service innovation, and transparency to strengthen customer trust and loyalty. Future research should broaden the scope to include other Latin American contexts, integrate internal organizational perspectives, and explore intergenerational dynamics and digital transformation processes to deepen understanding of BMI in family business ecosystems. Full article

This study evaluates the economic dimension of sustainable supply chain efficiency among Korean automotive suppliers using an SCOR-aligned two-stage Network Range-Adjusted Measure (NRAM) Data Envelopment Analysis (DEA) model. The framework separates performance into Stage 1 (internal operations: Plan/Source/Make/Deliver) and Stage 2 (external outcomes: sales and profitability), enabling stage-specific assessment of operational versus market-facing efficiency. Firm-level financial data for about 1200 suppliers annually from 2021 to 2024, spanning five sectors, were analyzed with descriptive statistics, visualizations, and non-parametric tests. Results show that Stage 1 efficiency was consistently high and stable, while Stage 2 efficiency was lower, more variable, and declined in 2022 and 2024, revealing vulnerability to systemic market disruptions. Overall efficiency mirrored Stage 2, underscoring the fact that downstream financial outcomes drive total performance. Rather than introducing a new methodology, the contribution of this study lies in applying an established two-stage NRAM DEA within an SCOR-aligned framework to a large-scale longitudinal dataset. This application provides sectoral and temporal benchmarks on a national scale, offering evidence-based insights into how structural interdependence and systemic shocks influence supply chain efficiency. While the scope is limited to the economic pillar of sustainability, the findings contribute contextualized benchmarks that can inform managerial practice and future research integrating environmental and social performance dimensions. Full article

Corporate boards play a pivotal role in shaping firms’ environmental strategies, yet the influence of board demographics, particularly director age, on sustainability outcomes remains insufficiently understood. This study investigates how the age profile of board members affects corporate environmental performance, including greenhouse gas emissions. Analyzing a comprehensive panel of 1843US publicly listed firms (17,218 firm-year observations) from 1996 to 2018, primarily through panel regressions with firm and year fixed effects, we find consistent evidence that firms with older boards tend to exhibit poorer environmental performance and higher direct, indirect and value chain greenhouse gas emissions. We argue that this relationship is driven by age-related differences in risk tolerance, time horizons, and sensitivity to environmental concerns. Additionally, the study explores moderating factors such as poor governance oversight (board co-option), pressure for profitability from institutional ownership, CEO social and environmental consciousness (CEO gender), and managerial ability, revealing that these governance dynamics significantly influence the strength of the director age–environmental performance link. The results, robust to endogeneity concerns, underscore the importance of considering age diversity and board refreshment in corporate governance to foster more effective environmental stewardship. These insights offer valuable implications for board members, corporate leaders, and policymakers aiming to advance sustainable business practices, but also open up opportunities for further exploration in alternative institutional contexts. Full article