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The study of sustainability within universities is recognized as essential for debates and research; in the long term, the “sustainable university” concepts can contribute to sustainability from a larger perspective. This study aims to propose a conceptual model for evaluating the students’ sustainability considering their interactions with the university and the environment. The proposed model is titled Sunshine model. It is applied to students of the La Salle University, Peru.

The model combines academic performance, happiness and the ecological footprint to quantify university students’ sustainability. A structured questionnaire survey was elaborated and applied to get the raw data that feeds the three methods. The students’ average grades evaluate academic performance. Happiness is quantified by the happiness index method, and the ecological footprint is measured by the demand for food, paper, electricity, transport and built-up areas. Results are evaluated under both approaches, overall group performance and clusters.

The proposed model avoids misleading interpretations of a single indicator or discussions on sustainability that lack a conceptual model, bringing robustness in assessing students’ sustainability in universities. To have a low ecological footprint, the student needs to need up to 1 planet for their lifestyle, be considered happy with at least 0.8 (of 1) for happiness index, and have good academic performance with at least a grade of 7 (of 10) in their course. Regarding the case study, La Salle students show a high academic grade degree of 7, a high level for happiness index of 0.8 and low performance for ecological footprint by demanding 1.8 Earth planets, resulting in an “environmentally distracted” overall classification for students with 2019 data. From a cluster approach, 81% of evaluated students (n = 603) have low performance for ecological footprint, whereas 31% have low performance for indicators of recreational activities of happiness. Changing lifestyles and making more recreational activities available play crucial roles in achieving higher sustainability for the La Salle students.

The happiness assessment questionnaire can be subject to criticism, as it was created as a specific method for this type of audience based on existing questionnaires in the literature. Although it can be seen as an important approach for diagnoses, the proposed model does not consider the cause–effect aspect. The decision-maker must consider the sociocultural aspects before implementing plan actions.

University managers can better understand why university students have high or low sustainability performance and provide more effective actions toward higher levels of students’ sustainability.

The proposed model, Sunshine model, overcomes the single-criteria existing tools that access the sustainability of universities. Rather than focusing on university infrastructure, the proposed model focuses on the students and their relationship with the university.

The study examines the presence of the pollution haven or pollution halo hypothesis in Brazil, Russia, India, China and South Africa (BRICS) and Next-11 economies. Hence, it empirically tests the direct impact of foreign direct investment (FDI) on the ecological footprint. Further, it explores the moderating role of green innovation on the nexus between FDI and ecological footprint.

The study uses the Driscoll–Kraay (DK) standard error panel regression technique to examine the long-run elasticities amongst the variables for the group of emerging countries, BRICS and Next-11, during the period of 1992 to 2018. Further, statistical robustness is demonstrated using the fully modified ordinary least squares technique.

The empirical finding shows that FDI degrades environmental quality by raising the ecological footprint. Thus, it proves that FDI is a source of pollution haven in BRICS and Next-11 countries. However, green innovation negatively moderates the relationship between FDI and ecological footprint. That means the joint impact of green innovation, and FDI proves the presence of the pollution halo hypothesis. Further, renewable energy consumption is reducing the ecological footprint, but economic growth and industrialisation are worsening the environmental quality.

This study offers policy implications for governments and policymakers to promote environmental sustainability by improving green innovation and allowing FDI that encourages clean and advanced technology.

No prior studies examine the moderating role of green innovation on the relationship between FDI and ecological footprint in the context of emerging countries.

The research is geared towards studying the impact of “GDP per capita (GDP)”, “energy consumption (EC)”, “human capital (HC)” and “trade openness (TO)” on India's ecological footprint (EF) from 1997–1998 to 2019–2020.

The autoregressive distributed lag model (ARDL) bound test was used to look at the short-run and long-term coefficients and the cointegration of the variables.

The results depicted a long-run connection between the variables. The long-run results found a favourable relationship between GDP, EC and EF, indicating that economic growth through heavy reliance on fossil fuels contributes to environmental unsustainability. An inverse relationship between HC, TO and EF was also observed, indicating that education fosters pro-environmental behaviour and leads to adopting cleaner technology that contributes to environmental sustainability.

The research substantiates India's pressing requirement for sustainable development, ensuring a harmonious balance between economic performance and environmental preservation. A carefully designed policy needs to be formulated to mitigate emissions stemming from growth in India. Policymakers are urged to implement measures that promote ecologically friendly tools, utilities and transportation to curb long-term environmental degradation.

The study is novel, incorporating an exhaustive review using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). This study further examines how India's EF is affected by its HC; the preceding literature has yet to discuss much about the connection between HC and the environment. Finally, the study employed advanced econometric techniques, namely the cointegration technique and ARDL model, to find the relationship between EF, GDP, HC, EC and TO.

In this chapter, the author proceeds to explore the second ‘C’ in the 3C Model of Taoism: conversation, with an emphasis on ecological sustainability. The discussion delves into the connections between Taoism and deep ecology, eco-effectiveness and eco-efficiency, and the Diderot effect and sustainable consumption. Taoism underscores the value of maintaining balance with nature and regards the natural world as a wellspring of wisdom and inspiration. Taoism and deep ecology share many philosophical similarities. Both perspectives highlight the importance of cherishing all living beings, coexisting peacefully with nature, and acknowledging that humans are a small component of a larger ecosystem. Taoism strongly accentuates the interconnectivity of all things and the critical need for balance between nature and human life. Along with promoting harmony and respect for the environment, deep ecology also advocates for social and political reform to protect the ecosystem. These two approaches emphasize the need to understand our position in the world and how our actions affect the environment and all living organisms. The wisdom of Taoism perceives sustainability as encompassing the entire ecosystem, an intricate network of life with its abundant and diverse range of species. This view aligns with the principles of deep ecology, which sees the ecosystem as a living entity in which humanity is merely one component.

This study examines how carbon tools, including carbon accounting and management tools, can be created, used, modified and linked with other traditional management controls to materialise and effectuate organisations’ response strategies to multiple interacting logics in carbon management and the role of sustainability managers in these processes.

This study utilises the construct of accounting toolmaking, which refers to practices of adopting, adjusting and reconfiguring accounting tools to unfold how carbon tools are used as means to materialise responses to multiple interacting carbon management logics. It embraces a field study approach, whereby 38 sustainability managers and staff from 30 organisations in New Zealand were interviewed.

This study finds that carbon toolmaking is an important means to materialise and effectuate organisations’ response strategies to multiple interacting carbon management logics. Four response strategies are identified: separation, selective coupling, combination and hybridisation. Adopting activity involves considering the additionality, detailing, localising and cascading of carbon measures and targets and their linkage to the broader carbon management programme. In adjusting carbon tools, organisations adapt the frequency and orientation of carbon reporting, intensity of carbon monitoring and breadth of carbon information sharing. Through focusing on either procedural sequencing, assimilating, equating or integrating, toolmaking reconfigures the relationship between carbon tools and traditional management control systems. Together, these three toolmaking activities can be configured differently to construct carbon tools that are fit for purpose for each response strategy. These activities also enact certain roles on sustainability managers in the process of representing, communicating and/or transferring carbon information knowledge, which also facilitate different response strategies.

The study demonstrates the various carbon toolmaking practices that allow organisations to handle the multiple interacting logics in carbon management. The findings provide suggestions for organisations on how to adopt, adjust and reconfigure carbon tools to better embed the ecological logic in organisations’ strategies and operations.

The authors identify how carbon toolmaking materialises and effectuates organisations’ responses to multiple interacting logics in carbon management.

This study aims to perform a scoping review of the recent studies on critical resources required for the doctoral program by mapping the resources at various levels of Bronfenbrenner's ecological systems and their underlying theories. The study proposes a holistic model of supportive resources in the doctoral education.

The current scoping review is supported by Arksey and O'Malley's five-stage methodological guidance The authors reported sixty-eight articles that were published between 2010 and 2023 and complied with the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews (PRISMA-ScR) checklist.

The study identified two categories of resources that promote doctoral student well-being: personal resources such as research self-efficacy and intrinsic motivation of the doctoral student. Second, the contextual resources provided by supervisors, department, family, peers, institution and Government policy impact the well-being of doctoral students. The study relied on the self-determination and conservation of resources theory to determine doctoral students' stress-free, high-quality research journey.

The study findings can help higher education institutions, supervisors, peers and academicians plan and implement the finest resources to improve the well-being of doctoral students. The institutions can develop a wide range of strategies, tailored supportive programs, and interventions that can help in improving students' mental and emotional health, based on the developed multifaceted resource framework. Doctoral students can also use the review's findings to help them deal with program obstacles by encouraging themselves internally and participating in mentoring programs.

This review article proposes a comprehensive conceptual framework by considering Bronfenbrenner's ecological systems on multilevel resources that help to understand the inter-relationship between resources required in the doctoral student's program.

While providing users with important innovation resources, an enterprise's open innovation community also encounters numerous challenges. The purpose of this study is to develop and implement a set of evaluation systems that can identify the ecological characteristics of open innovation communities. The ultimate goal is to provide guidance for the construction and establishment of these communities.

Firstly, from the perspective of information ecology, according to the connotation requirements of the four information elements of “people, information, technology and environment” in the information ecosystem, this paper determines the evaluation indicators of enterprise's open innovation community from the aspects of integrity and dynamics. Then, based on the improved analytic hierarchy process, the weight of each index is calculated, and a complete evaluation system of open innovation community is established. Finally, the fuzzy comprehensive evaluation method is used to conduct empirical research on Haier Open Partnership (HOPE) platform, analyze its ecological situation and existing problems and put forward the corresponding construction recommendations.

The application of HOPE platform shows that the evaluation index system built in this study has good applicability, and the whole research process and research method have certain reference value for future studies. At the same time, the study found that the HOPE platform has good ecological characteristics, but there are also some problems. This study can directly promote the construction of the platform.

This paper, for the first time, combines the information ecology theory with the open innovation community. The results demonstrate that the open innovation community is an information ecosystem, which can be evaluated ecologically. Furthermore, to ensure the calculation's scientific accuracy, the index weight is determined by constructing a judgment matrix based on expert questionnaires.

Research on knowledge creation within eSports learning is scarce. This study extends the understanding of competition-oriented collaborative learning in eSports by examining the relationship between the dynamics of knowledge creation modes and the continuum of the motivational profile, along with the moderating effects of mutualistic co-presence therein.

Participants were recruited from the community of massively multiplayer online gamers (MMOGs). Through a quantitative survey, their motivations (i.e. self-extrinsic, self-intrinsic, peer-extrinsic and peer-intrinsic motivations), knowledge creation involvements (i.e. internalization, externalization, combination and socialization) and perception of mutualistic benefit of self and peers were captured for hypothesis testing.

Significant and positive direct relationships were observed between four motivations and four knowledge creation modes. The mutualistic co-presence positively moderated the positive relationship between the self-extrinsic, peer-extrinsic and peer-intrinsic motivations and socialization. When mutualistic self-benefit were outweighed, peer-extrinsic motivated gamers became less likely to perform internalization, whereas self-extrinsic and peer-extrinsic motivated gamers were less likely to perform combination.

This study is among the first to rationalize the relationship between motivational profile and the dynamics of knowledge creation in eSports learning. The conceptualization of the new construct – mutualistic co-presence – using the ecological concept of symbiosis is uncommon in prior literature. The findings also demonstrate that the four modes of knowledge creation in eSports learning are continuous and interwoven; they can be initiated at any point and do not necessarily occur in a specific sequence.

This study aims to verify the influence of stakeholders on Disruptive Innovation Disclosure (DID) by using company size as a control variable. DID is measured using the DID index. The authors use panel data regression with the period 2011–2020. Observations were made on 198 companies throughout the year in companies around the world. This study proves that shareholders, customers, suppliers, and company size are dimensions that affect DID. This situation shows that these dimensions have the power to control DID. The average company in the world has provided information about disruptive innovation. The scope of this research is limited to countries that have a visualization network of disruptive innovation collaboration in as many as 15 countries. The value of this study is to portray DID in countries that have disruptive innovation collaborative visualization networks.

In traditional Bayesian belief networks (BBNs), a large amount of data are required to complete network parameters, which makes it impractical. In addition, no systematic method has been used to create the structure of the BBN. The aims of this study are to: (1) decrease the number of questions and time and effort required for completing the parameters of the BBN and (2) present a simple and apprehensible method for creating the BBN structure based on the expert knowledge.

In this study, by combining the decision-making trial and evaluation laboratory (DEMATEL), interpretive structural modeling (ISM) and BBN, a model is introduced that can form the project risk network and analyze the impact of risk factors on project cost quantitatively based on the expert knowledge. The ranked node method (RNM) is then used to complete the parametric part of the BBN using the same data obtained from the experts to analyze DEMATEL.

Compared to the traditional BBN, the proposed method will significantly reduce the time and effort required to elicit network parameters and makes it easy to create a BBN structure. The results obtained from the implementation of the model on a mass housing project showed that considering the identified risk factors, the cost overruns relating to material, equipment, workforce and overhead cost were 37.6, 39.5, 42 and 40.1%, respectively.

Compared to the traditional BBN, the proposed method will significantly reduce the time and effort required to elicit network parameters and makes it easy to create a BBN structure. The results obtained from the implementation of the model on a mass housing project showed that considering the identified risk factors, the cost overruns relating to material, equipment, workforce and overhead cost were 37.6, 39.5, 42 and 40.1%, respectively. The obtained results are based on a single case study project and may not be readily generalizable.

The presented framework makes the BBN more practical for quantitatively assessing the impact of risk on project costs. This helps to manage financial issues, which is one of the main reasons for project bankruptcy.