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This chapter of the book seeks to use famous mathematical functions (statistical distribution functions) in evaluating and analyzing supply chain network data related to supply chain management (SCM) elements in organizations. In other words, the main purpose of this chapter is to find the best-fitted statistical distribution functions for SCM data. Explaining how to best fit the statistical distribution function along with the explanation of all possible aspects of a function for selected components of SCM from this chapter will make a significant attraction for production and services experts who will lead their organization to the path of competitive excellence. The main core of the chapter is the reliability values related to the reliability function calculated by the relevant chart and extracting other information based on other aspects of statistical distribution functions such as probability density, cumulative distribution, and failure function. This chapter of the book will turn readers into professional users of statistical distribution functions in mathematics for analyzing supply chain element data.

Supply chain management (SCM)-embedded valuable resources, such as capital, raw-materials, products, partners, customers and finished inventories, where the evaluation of environmental texture and flexibilities are needed to perceive sustainability. The present study aims to identify and evaluate the directory of green and agile (G-A) attributes based on decision support framework (DSF) for identifying dominating measures in SCM.

DSF is developed by exploiting generalized interval valued trapezoidal fuzzy numbers (GIVTFNs). Two technical approaches, i.e. degree of similarity approach (DSA) and distance approach (DA) under the extent boundaries of GIVTFNs, are implicated for data analytics and for recognizing constructive G-A measures based on comparative study for robust decision. A fuzzy-based performance indicator, i.e. fuzzy performance important index (FPII), is presented to enumerate the weak and strong G-A characteristics to manage knowledge risks in allied business environment.

The modeling is illustrated from the insights of decision-makers for augmenting business value based on cognitive identification of measures, where the best performance score is identified by the “sustainable packaging” under the traits of green supply chain management (GSCM). “The use of Web-based applications” under the traits of agile supply chain management (ASCM) and “Outsourcing flexibility” under traits of ASCM is found as the second and third most significant performance characteristics for business sustainability. Additionally, the “Reutilization (recycling) and reprocessing” under GSCM in manufacturing and “Responsiveness and speed toward customers needs” under ASCM are found difficult in attainment.

The G-A evaluation will assist in attaining performance excellence in day-to-day operations and overall functioning. The outcomes will help executives to plan strategic objectives and attaining success.

To reinforce the capabilities of SCM, wide extent of G-A dimensions are presented, concept of FPII is reported to manage knowledge risks based on identification of strong attributes and two technical approaches, i.e. DSA and DA under GIVTFNs are presented for attaining robust decision and directing managerial decision-making process.

This study aims to explore the relationship between the degree of state-owned enterprises’ (SOEs) mixed reform and the environmental response of enterprises, against the background of actively promoting the reform of mixed ownership in China.

The study is conducted on a sample of A-share listed manufacturing companies in Shanghai and Shenzhen of China, investigated for the period 2015 to 2020. The baseline regression results are robust to a series of robustness and endogeneity tests. To deal with the issue of endogeneity, the technique of instrumental variable method has been applied.

The study confirms the U-shaped effect of the depth and restriction of mixed ownership on SOEs’ environmentally responsive behaviour in the manufacturing industry, especially for lower environmental regulation and higher level of risk-taking firms. The findings indicate that the government, shareholders and other stakeholders of enterprises should not simply consider that the mixed reform is directly promoting or reducing the environmental response behaviour of enterprises.

SOEs should improve their shareholding structures to undermine performance enhancement at the expense of the environment and increase environmentally beneficial behaviours. Regulators and governments should improve the institutional mechanism of environmental regulation and make efforts to promote corporate awareness of the environment.

Although the adoption and implementation of environmentally friendly policies are costly, improved environmental response and other social responsibilities are helpful to corporate long-term growth and reputation and obtain more capital market attention. Therefore, firms would benefit from improving their environmental response to protect nature, as well as to enjoy the economic and social benefits of a better environmental response.

To the best of the authors’ knowledge, there is a lack of studies focussing on the environmental behaviour of SOEs of mixed reform. As the mixed reform in China has come to a climax phase in recent several years, SOEs of mixed reform is an ideal environment for research. The study focusses on manufacturing firms as these firms are more susceptible to contribute to environmental pollution, exploitation of natural resources and labour concerns.

The purpose of this paper is to demonstrate how network theory and methods can provide insights into the forces shaping architectural learning agendas and knowledge construction in architectural schools.

The methodology involves conceptualising learning as a constructivist process and the agenda as an interconnected network of actors, concepts and relations. Network analysis techniques, including centrality and brokerage metrics, are used to identify roles and knowledge flows using the data locally collected from Turkish universities as well as from the OpenSyllabus open-source database.

The analysis reveals the enduring influence of early modernists, signalling imbalanced canon formation in the architectural learning system. However, marginal voices highlight struggles in integrating unconventional perspectives. Limited integration of local figures indicates a consolidation of Eurocentric epistemes. Identifying these hidden forces is vital for reimagining learning agendas and socio-culturally engaged forms of learning. Pioneering figures demonstrate potential for synthesis when situated as brokers, not bifurcated schools.

The outcomes are limited by the geographical and temporal boundaries of the data and the analysis method employed. Despite limitations, the diagnostic network framework reveals architectural learning as an open, contested ecosystem demanding pluralistic pedagogies concerning not only the global but the local, both canonical and marginal. Further research covering more data could enrich the understanding of qualitative complexities.

The network perspective prompts critical reflexivity about power, ideology and exclusion in knowledge construction. Strategic inclusion and diversification of voices provide pathways to bridge divides and ground learning locally.

This research offers a methodology model to examine forces and influences shaping architectural education by elucidating hidden and remote roles and knowledge gaps in learning agendas. Extending the techniques more widely can enable strategic interventions toward inclusive, impactful learning across disciplines, time and geographies.

The purpose of this paper is to introduce a three-echelon multimodal transportation problem applied to a humanitarian logistic case study that occurred in Mexico.

This study develops a methodology combining a transshipment problem and an adaptation of the multidepot heterogeneous fleet vehicle routing problem to construct a mathematical model that incorporates the use of land-based vehicles and drones. The model was applied to the case study of the Earthquake on September 19, 2017, in Mexico, using the Gurobi optimization solver.

The results ratified the relevance of the study, showing an inverse relationship between transportation costs and delivery time; on the flip side, the model performed in a shorter CPU time with medium and small instances than with large instances.

While the size of the instances limits the use of the model for big-scale problems, this approach manages to provide a good representation of a transportation network during a natural disaster using drones in the last-mile deliveries.

The present study contributes to a model that combines a vehicle routing problem with transshipment, multiple depots and a heterogeneous fleet including land-based vehicles and drones. There are multiple models present in the literature for these types of problems that incorporate the use of these transportation modes; however, to the best of the authors’ knowledge, there are still no proposals similar to this study.

Sustainable Development Goal 14 of the United Nations aims to ‘conserve and sustainably use the oceans, seas and marine resources for sustainable development’. To achieve this goal, we must rebuild the marine life-support systems that provide society with the many advantages of a healthy ocean. Therefore, countries worldwide have been using Marine Protected Areas (MPAs) to restore, create, or protect habitats and ecosystems. Palau was one of the first countries to use MPAs as a tool to develop biodiversity within its exclusive economic zone. On 22 October 2015, Palau placed approximately 80% of its maritime territory in a network of locally monitored MPAs, which has now shown a population increase in stationary and migratory fish species. This movement towards a MPA was intentional and because of increased pressure from tourism and the increasing incursion of foreign fishing vessels in Palauan territorial waters. Since countries worldwide are using and looking towards MPAs, secondary protection projects are becoming more and more popular. This chapter highlights the practical implementations and results in Palau, how to theoretically apply this within the Greater North Sea in combination with Windmill Farms, and how the Marine Strategy Framework Directive stimulates these practices.

Intellectual capital (IC) is an increasingly important strategic asset for sustainable value creation in organisations. This paper aims to provide a conceptual perspective on the university’s role as a catalyst for IC creation and development within the dynamic landscape of organisations, exploring the nexus to capture its essence.

Adopting a conceptual framework development approach, key concepts were cohesively and coherently synthesised from various theoretical underpinnings, namely, the multiple capitals approach to maximising corporate value creation, the evolved triple bottom line approach to corporate sustainability, the triple helix innovation model and its subsequent extensions, the upper echelons theory and the social licence construct linked to stakeholder, legitimacy and institutional theories.

A comprehensive conceptual framework was developed that outlines universities’ role in catalysing four corporate IC forms crucial to sustainable organisational value creation: human capital, governance capital, social/relational capital and structural/organisational capital. The framework interprets this role of universities as dynamic IC reservoirs serving regional ecosystems for sustainable development. It highlights the synergistic sustainable value creation between universities and organisations in host communities and broader society, with university governance acting as a key driver.

This paper offers a theoretically grounded interpretation of universities’ pivotal role in catalysing essential forms of IC to support contemporary organisations’ sustainable value-creation processes. The proposed framework has the potential to ignite conversations on the crucial connection between universities and corporate IC development relevant to sustainable organisations, inspiring future empirical research, reflection and discussion.

Despite extensive academic research related to digital technologies (DT), their integration into architecture, engineering and construction (AEC) projects lags in practice. This paper aims to discover DT deployment patterns and emerging trends in real-life AEC projects.

A case study methodology was adopted, including individual case analyses and comparative multiple-case analyses.

The results revealed the temporal distribution of DT in practical AEC projects, specific DT products/software, major project types integrated with digital solutions, DT application areas and project stages and associated project performance. Three distinct patterns in DT adoption have been observed, reflecting the evolution of DT applications, the progression from single to multiple DT integration and alignment with emerging industry requirements. The DT adoption behavior in the studied cases has been examined using the technology-organization-environment-human (TOE + H) framework. Further, eight emerging trend streams for future DT adoption were identified, with “leveraging the diverse features of certain mature DT” being a shared recognition of all studied companies.

This research offers actionable insights for AEC companies, facilitating the development of customized DT implementation roadmaps aligned with organizational needs. Policymakers, industry associations and DT suppliers may leverage these findings for informed decision-making, collaborative educational initiatives and product/service customization.

This research provides empirical evidence of applicable products/software, application areas and project performance. The examination of the TOE + H framework offers a holistic understanding of the collective influences on DT adoption. The identification of emerging trends addresses the evolving demands of the AEC industry in the digital era.

Building on associative priming, anthropomorphism and biophilia theories, this study aims to explain that a natural–organic (that shows a natural object) and an anthropomorphised natural–organic logo (that shows an anthropomorphised natural object) both act as primes and imbue specific product value perceptions, which subsequently influence willingness to pay a premium price when products have not been used by or are unfamiliar to consumers.

Two between-subjects experiments were conducted with different products (one with real, but unfamiliar to consumers brand and another with a fictitious brand). Structural equation modelling was used to test the hypotheses.

Experimental studies showed that natural–organic logos evoked stronger utilitarian (functional and economic) value perceptions, which triggered greater willingness to pay a premium price compared to anthropomorphised natural–organic logos. The effect of hedonic (emotional and novelty) values on willingness to pay a premium price was stronger when an anthropomorphised natural–organic logo was used.

This research offers novel theoretical contributions highlighting the importance of careful logo design to imbue desired value perceptions when products have not been consumed or trialled.

Anthropomorphised natural–organic and natural–organic logos can provide different benefits to brand managers and can be used strategically to form desired value perceptions before products are consumed. Brands that wish to enhance premium pricing via hedonic values should consider using an anthropomorphised natural–organic logo. Natural–organic logos may be more suitable for brands that want to emphasise superior utilitarian values.

To the best of the authors’ knowledge, this research provides the first empirical assessment of the differential effects of the two forms of natural–organic logos on value perceptions and willingness to pay premium price.

This paper aims to explore the dynamic relationship between ESG scores and REITS returns. The overarching goal is to provide a better understanding of how ESG considerations impact financial performance across different temporal contexts.

Using a sample of 175 European Equity REITs, this analysis combines numerical ESG scores with the Fama-French model, employing both random and fixed effects methods. It integrates individual REIT data and the HESGL (High ESG Scores Minus Low ESG Scores) factors to assess their impact on REIT returns.

The findings highlight divergent patterns between the numerical ESG score and the HESGL factor concerning REIT returns. While the numerical ESG score displays a negative impact in later periods, the HESGL factor demonstrates a positive effect during prosperous times but loses significance during crises.

This research contributes original insights by emphasizing the importance of temporal segmentation in understanding the nuanced and evolving nature of the relationship between ESG scores and REITs’ returns. The study provides a comprehensive analysis and highlights divergent outcomes that are essential for a better interpretation of ESG impacts on real estate investments.