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This paper focuses on social innovation dynamics in extreme contexts where institutional volatility is deeply rooted and enduring. In other words, the authors focus their discussion on the challenges that social innovators are facing in their endeavor of solving wicked social problems within an extreme institutional environment. This research is guided by the following question: How does an extreme institutional environment influence social innovation processes?

This qualitative research builds on the unique case of the Palestinian non-governmental organization (NGO) sector, a rarely studied context in organizational studies. The authors combine archival sources with 24 semi-structured interviews with Palestinian NGOs.

The authors theorize three barriers that hinder social innovation in such contexts: institutional trap, effectiveness trap and sustainability trap. The authors also theorize five mechanisms through which these barriers influence each other dynamically: mingling, surviving, undermining, binding and reinforcing. Taken together, these barriers and mechanisms shed light on social innovation processes taking place within extreme institutional environments.

The main limitation of this study is the methodological design, based on an extreme single case-study which, on a bunch of features, is quite unique in the world. The authors argue that the results are all the same transferable to other relatively similar contexts.

By theorizing the institutional barriers to social innovation in an extreme institutional context, the research thus sheds light on how social innovation could be sustained and stimulated in Palestine and other contexts that face similar institutional challenges.

From an engaged scholarship perspective, studying Palestine cannot be more relevant than today considering the turmoil in which Palestinians are. The research thus provides a deeper understanding of organizational and institutional dynamics with crucial social repercussions.

The social innovation literature has overemphasized success stories to the detriment of the struggles that hinder social innovations in extreme institutional environments. By focusing on the barriers that social innovators experience in these contexts, the authors provide novel empirical insight. Furthermore, this study enriches the understanding of the institutional dynamics of social innovations by proposing a process model that elucidates how an extreme institutional context can influence social innovations.

Weather forecasting is the trending topic around the world as it is the way to predict the threats posed by extreme rainfall conditions that lead to damage the human life and properties. These issues can be managed only when the occurrence of the worse weather is predicted in advance, and sufficient warnings can be executed in time. Thus, keeping in mind the importance of the rainfall prediction system, the purpose of this paper is to propose an effective rainfall prediction model using the nonlinear auto-regressive with external input (NARX) model.

The paper proposes a rainfall prediction model using the time-series prediction that is enabled using the NARX model. The time-series prediction ensures the effective prediction of the rainfall in a particular area or the locality based on the rainfall data in the previous term or month or year. The proposed NARX model serves as an adaptive prediction model, for which the rainfall data of the previous period is the input, and the optimal computation is based on the proposed algorithm. The adaptive prediction using the proposed algorithm is exhibited in the NARX, and the proposed algorithm is developed based on the Grey Wolf Optimization and the Levenberg–Marqueret (LM) algorithm. The proposed algorithm inherits the advantages of both the algorithms with better computational time and accuracy.

The analysis using two databases enables the better understanding of the proposed rainfall detection methods and proves the effectiveness of the proposed prediction method. The effectiveness of the proposed method is enhanced and the accuracy is found to be better compared with the other existing methods and the mean square error and percentage root mean square difference of the proposed method are found to be around 0.0093 and 0.207.

The rainfall prediction is enabled adaptively using the proposed Grey Wolf Levenberg–Marquardt (GWLM)-based NARX, wherein an algorithm, named GWLM, is proposed by the integration of Grey Wolf Optimizer and LM algorithm.

This study aims to analyse what drives and limits the Dutch population during COVID-19 in their intention to travel for leisure once travel restrictions have been lifted, to gain an insight in the psychological travel barriers following a period of crisis.

The research process involved an online self-administrated method created with one of the leading research and web-based survey tools called Qualtrics. The questionnaire was filled by 402 respondents.

The findings indicate that the impact of COVID-19 on cutting down travel plans, certain personal values and structural constraints have a positive relationship with the leisure travel intention to various destinations. Moreover, risk perceptions and intrapersonal constraints have a positive relationship with domestic leisure travel intentions. However, these factors have a negative connection with the leisure travel intention to some international destinations. Further, decreased perceptions of risks have a negative relationship with the domestic leisure travel intentions.

Using questionnaires in the form of online, self-administrated surveys made it impossible to get an insight in and have control over who responded to the questionnaire. Gaining an insight into the factors impacting the leisure travel intentions following a period of crisis will make it possible for the tourism industry to respond adequately to future crises and will make it easier for destination marketers and managers to attract new tourists during the recovery process.

To the best of the author’s knowledge, no analysis has been so far published with a focus on the impact of COVID-19 on the Dutch population and their intention to travel. It is crucial for gaining an insight into leisure travel intention and the factors impacting this intention following a period of crisis since travel intention is an under-researched topic of academic tourism literature. This study closes the existing gap in literature.

Higher institutions in Nigeria have witnessed an increase in the number of student enrolments; Northern Nigerian universities are not excluded. As the number of students increases, so do their needs in terms of facilities such as lecture halls, libraries, laboratories, accommodation, studios, furniture and other auxiliary facilities services (among others things). The purpose of this study is to explore the structural characteristics of building features’ performance and to statistically group them into building components (dependent) and physical and non-physical building features (independent) constructs, relating to influence of facilities’ performance in student satisfaction in Northern Nigerian universities.

Questionnaires used were designed to collect data on both academic facilities, based on student experience and satisfaction with respect to physical and non-physical facilities. The school building assessment method questionnaire by Sanoff (2001) was adapted. Hence, the validity and reliability of measures was examined via academicians and data analysis with statistical package of social science (SPSS) version 22. In general, the values of alpha coefficients were above 0.80.

The result of exploratory factor analysis revealed that all factors loaded more than 0.61. In conclusion, the results indicated acceptable factor loadings and effective grouping of the features according to the conceptualised framework for the building component. A hypothetical model of building components was then proposed, suggesting the effects of physical and non-physical building features on building components.

This research has been applied to a Northern Nigerian university. The research should be expanded to other institutions offering higher education.

Based on a conceptual framework, the study gives practical insights concerning the performance of building component as a key success factor for higher education institutions’ (HEIs) facilities.

Therefore, the need to develop and improve instruments that will reflects facilities performance for students satisfaction in Nigerian universities became paramount. Thus there is lack of an integrating framework for facilities performance as well as students satisfaction and experience in the context of Nigerian HEIs, especially in the region of northern Nigeria.

This chapter highlights the perspectives, examples, and applications on the current trend in teaching and learning counseling ethics education in a more effective way. The trend utilizes inquiry-based learning concept and educational activities to foster counselor education training programs fast-forward in meeting the social demands and global challenges. The discussion is based on the theme emerged from an interpretive case study research conducted by the authors, in addition to the insightful literature authored by the profound educators and counseling researchers, globally. Teaching and learning counseling ethics education is an integrative effort and is more than just content acquisition from textbooks. In addition, the inquiry-based teaching and learning approach can be a tool in finding solutions for authentic problems through in-depth investigations while learning counseling ethics education. This chapter hopefully will improve counselor educators’ ability, strengthen counselor education training programs’ capability, and expand counseling students ethical competency; for creating innovations and adaptations in teaching and learning counseling ethics education, utilizing inquiry-based learning toward enhanced professional ethical practice in counseling realm.

This study aims to identify the effect of demographic factors on the relationship between academic contribution and university–industry knowledge exchange in Sri Lanka.

This study is of quantitative and explanatory type , which applied the deductive research method, and is conducted with minimum interference of researcher taking individual academics as the unit of analysis. The study collected data from 178 academics randomly through a structured questionnaire designed to analyze through statistical package for the social sciences and analysis of a moment structure statistical software. A structural equation model is applied to collected data to explore the moderating impact of the demographic factor on the university–industry knowledge exchange.

Overall involvement of academic staff in joint research, contract research, human resource mobility and the training with industry were was low in Sri Lanka. However, all four independent variables significantly associated with the knowledge exchange process from which only joint research and training had a statistically significant effect on university–industry knowledge exchange . Concerning demographic factors, only the quality of academic research significantly moderated the relationship between academic contribution and university–industry knowledge exchange process in Sri Lanka.

This study considered only the university side of the university–industry knowledge exchange process.

This paper implies that gender, age and area of specialization did not have significant power to moderate the relationship between academic contribution and university–industry knowledge exchange process.

There is a lack of research literature discussing the moderating effect of demographic factors on the university–industry knowledge exchange process. In Sri Lanka, money and commercial benefits that received through industry partnerships had not been valued by academics. The majority considered the connection with industry and exchange knowledge as a responsibility that they should perform in return to free education received from grade one to graduation.

This study proposes a framework for Earthwork Ontology (EW-Onto) to support and enhance data exchange in the project and the efficient decision-making in the planning and execution phases.

The development of EW-Onto started from defining the concepts and building taxonomies for earthwork operations and equipment following the METHONTOLOGY approach. In addition, several rules have been extracted from safety codes and implemented as SWRL rules. The ontology has been implemented using Protégé. The consistency of EW-Onto has been checked and it has been evaluated using a survey.

The assessment of EW-Onto by experts indicates an adequate level of consensus with the framework, as an initial step for explicit knowledge exchanges within the earthwork domain.

The use of an ontology within the earthwork domain can help: (1) link and identify the relationships between concepts, define earthwork semantics, and classify knowledge in a hierarchical way accepted by experts and end-users; (2) facilitate the management of earthwork operations and simplify information exchange and interoperability between currently fragmented systems; and (3) increase the stakeholders' knowledge of earthwork operations through the provision of the information, which is structured in the context of robust knowledge.

This paper proposes a framework for Earthwork Ontology (EW-Onto) to support and enhance data exchange in the project and the efficient decision-making in the planning and execution phases. EW-Onto represents the semantic values of the entities and the relationships, which are identified and formalized based on the basic definitions available in the literature and outlined by experts.

The purpose of this paper is to contribute to emergent understandings in research into urban climate change-related disasters (such as extreme heat), which recognise that present-day actions or failures of cities to address climate risk are rooted in a historical context.

The paper analyses content of scientific journals produced by the not-for-profit Kyushu Environmental Evaluation Association in Fukuoka since the 1970s. The aim is to evaluate the shifting understanding and conception of a liveable urban environment within Fukuoka over time and assess how this narrative has informed capability to understand and manage extreme heat as an emergent disaster risk.

The strong technical competences enabling Fukuoka to undertake evidence-based management of risks from climate-related disasters today exist at least partially because of earlier environmental concerns within the city and an early emergence of techno-scientific competence within the city's research institutions working at the science–policy interface.

The findings suggest a need to avoid uncritically exporting “lessons” from apparent urban climate “success stories”, without full recognition of the historical context enabling production and utilisation of weather and climate knowledge in specific locations.

Through the ideas of and within Oceania that we outline, and within which we locate architecture and institutions for CIE regionally, we illustrate the identified turning points through analysis of dynamic and intersecting trajectories of the Oceania Comparative and International Education Society (OCIES), formerly the Australia and New Zealand Comparative and International Education Society (ANZCIES), and the Vaka Pasifiki, formerly the Rethinking Pacific Education Initiative for and by Pacific Peoples (RPEIPP) project. We offer initial responses to an over-arching theme in posing the question: how, and through what processes, have these groups influenced understandings of ‘regionalism’ for CIE within Oceania? This involves examining the conferences, financing, membership, the Society journal/publications and aspects of CIE education of the two bodies.

This paper aims to compare the impacts of adaptive daily and seasonal cooling setpoints on cooling energy consumption and overheating hours to determine which approach is more effective in a desert climate, develop a methodology that effectively integrates passive strategies with adaptive daily and seasonal cooling setpoint strategies and assess how future climate conditions will impact these strategies in the medium and long term.

(1) Integrate adaptive thermal comfort principles into mechanical cooling systems to find the optimized cooling setpoint. (2) Evaluating the optimized cooling setpoints using a mixed-mode operation: In this step, the natural ventilation is activated by opening 40% of the window area when the indoor temperature is higher than 23°C and the outdoor temperature. Both the adaptive seasonal and daily setpoint strategies are evaluated. (3) If overheating hours exceed acceptable limits gradually add mitigation measures (e.g. exterior shading, cool roofs and green roofs). (4) If necessary, further reduce the cooling setpoint until acceptable limits are met. (5) Generate extreme future climate scenarios and evaluate the optimized model. (6) Implement additional measures and setpoint adjustments to maintain acceptable overheating hours in future conditions.

Although the building complies with the Dubai Green Code and uses external shading, its cooling energy consumption was 92 kWh/m² in 2021 with a 24°C setpoint. Using the adaptive seasonal setpoint combined with a cool roof, night cooling and cross-ventilation reduces cooling energy consumption by 52, 48 and 35% in 2020, 2050 and 2090, respectively, with overheating hours not exceeding 40 h annually. Using an adaptive daily setpoint strategy with the same mitigation measures is similarly effective; it achieved a 57, 42 and 34% reduction in cooling energy consumption in 2020, 2050 and 2090, respectively, while eliminating overheating hours.

The originality and value of this study lie in optimizing cooling setpoints without the effect of overheating hours in desert climates. Using the adaptive seasonal setpoint combined with a cool roof, night cooling and cross-ventilation reduces cooling energy consumption by 52, 48 and 35% in 2020, 2050 and 2090, respectively, with overheating hours not exceeding 40 h annually. Using an adaptive daily setpoint strategy with the same mitigation measures is similarly effective; it achieved a 57, 42 and 34% reduction in cooling energy consumption in 2020, 2050 and 2090, respectively, while eliminating overheating hours.

• (1)

  A methodology is developed to find the optimal cooling setpoints

• (2)

  Adaptive thermal comfort concept is extended for integration with a cooling system

• (3)

  Validation simulation model is used using certain building information

• (4)

  Climate change effect is studied using current and future warmer typical years

• (5)

  Effective passive summer mitigation measures are studied

A methodology is developed to find the optimal cooling setpoints

Adaptive thermal comfort concept is extended for integration with a cooling system

Validation simulation model is used using certain building information

Climate change effect is studied using current and future warmer typical years

Effective passive summer mitigation measures are studied