Key Performance Indicators for Sustainable Campus Assessment: A Case of Andalas University

Sustainable campus has became an important issue amongst universities around the world. Universities can generate a significant impacts to environment due to the high usage of energy, extensive transportation, massive waste, high consumption of materials, and extensive development of buildings and facilities. Thus, there is a need to assess the sustainable campus performance. This paper proposes a set of key performance indicators (KPIs) for sustainable campus assessment consisting of six categories divided into a total of 35 indicators. Analytical Hierarchy Process (AHP) method is applied to determine the importance weight of the KPIs. The results indicated the most important category for the sustainable campus assessment is education with an importance weight of 0.2665, while energy and climate change is regarded as the least important category. It is hoped the proposed KPIs can assist the universities to achieve the higher performance in sustainable campus

The Success Factors in Measuring the Millennial Generation’s Energy-Saving Behavior Toward the Smart Campus

The millennial generation has a pivotal role in leading the industrial digital revolution. Energy-saving behavior and millennials’ awareness of energy consumption for educational context become crucial in performing a smart campus. This study tries to identify the success factors in measuring the millennial generation’s energy-saving Behavior toward the smart campus. The measurement model considers two significant constructs, including energy-saving attitudes with energy-saving education (organizational saving climate); energy-saving education and environment knowledge (personal saving climate); and energy-saving information publicity as sub-indicators, and construct energy-saving Behavior viz sub-indicators Behavior regarding energy and behavior control. In order to determine the preference level of each indicator and sub-indicator, the Fuzzy Analytical Hierarchy Process (Fuzzy-AHP) approach was executed by disseminating the questionnaire to 100 respondents from energy practitioners, students, and academicians in Indonesia. The calculation reveals that the energy-saving behavior construct has a higher priority value (0.94) than the energy-saving attitude (0.06). Meanwhile, energy-saving education and environment knowledge (personal saving climate) have been analyzed at the cutting-edge sub-indicator, followed by energy-saving information publicity and education (organizational saving climate). In addition, the sub-indicator for behaviors regarding energy becomes more demanding compared to behavioral control. As a novelty, the priority analysis of this Model aids the management of the campus and government in developing smart campus policies and governance. This Model can be used as a guideline for the management level to execute the smart campus practices. Thus, the effectiveness and optimization of smart campus transformation can be cultivated and accelerated. Besides, the potential coming of risks can be avoidable

A Review on Fuzzy - AHP technique in Environmental Impact Assessment of Construction Projects, India

There are several countries today using procedures for Environmental impact assessment (EIA) is based on a series of mathematical techniques which attempt to localize, describe and assess the positive and negative effects that any human activity has on our environment, generally causing it to deteriorate. The environmental impact assessment (EIA) of projects requires the evaluation of the effects of very diverse actions on a number of different environmental factors, the uncertainty and inaccuracy being inherent in the process of allocating values to environmental impacts carried out by a panel of experts, stakeholders and affected population. The application of the fuzzy Logic and AHP technique can be helpful in identification of the risk associated with construction or developing project and improves the study of EIA. Fuzzy is one of the characteristics of human thoughts for which fuzzy sets theory is an effective tool for fuzziness. A fuzzy logic knowledge-based approach can be used for the environmental impact assessment study of the different construction projects. The review article highlights the role of Fuzzy AHP logic method in EIA of different construction projects, fuzzy logic modeling - software for fuzzy EIA, fuzzy numbers and steps of fuzzy methods as well as reveals that how fuzziness can be determined by applying fuzzy logic method in construction projects

Developing a green city assessment system using cognitive maps and the Choquet integral

Equitable human well-being and environmental concerns in urban areas have, over the years, become increasingly challenging issues. This trend is related to both the complexity inherent in the multiple factors to be considered when evaluating eco-friendly cities (i.e., green cities) and the way this type of city’s sustainability depends on many evaluation criteria, which hampers all decision-making processes. Using a multiple criteria decision analysis (MCDA) approach, this study sought to develop a multiple-criteria model that facilitates the evaluation of green cities’ sustainability, based on cognitive mapping techniques and the Choquet integral (CI). Taking a constructivist and process-oriented stance, the research included identifying evaluation criteria and their respective interactions using a panel of experts with specialized knowledge in the subject under analysis. The resulting framework and its application were validated both by the panel members and a parliamentary representative of the Portuguese ecology party “Os Verdes” (The Greens), who confirmed that the evaluation system created distinguishes between cities according to how strongly they adhere to “green” principles. The advantages and limitations of the proposed framework are also discussed.info:eu-repo/semantics/acceptedVersio

Assessing and predicting the students’ systems thinking preference: multi-criteria decision making and machine learning

The 21st century is marked by a technological revolution that features digital implementation and high interconnectivity between systems across different domains, such as transportation, agriculture, education, and health. Although these technological changes resulted in modern systems capable of easing individuals’ lives, these systems are increasingly complex, and that increased complexity is only expected to continue. The increased system complexity is due to the rapid exchange of information between subsystems, which creates high interconnectivity and interdependence between the subsystems and their elements. Workforce skill sets, as a result, must be modified appropriately to ensure the systems’ success. Systems Thinking is an approach that helps individuals better understand and effectively solve modern complex systems problems by encouraging holistic thinking. Systems thinking consists of two approaches holistic and reductionist views. This dissertation aims to study college engineering and non-engineering students’ preference for holistic thinking versus reductionist thinking, their ranking to the systems thinking dimensions, and whether this preference varies depending on demographics and general factors. Additionally, this study investigates the possibility of predicting the students’ preference for holistic thinking. The study uses the multi-criteria decision-making method, the Analytic Hierarchy Process and Fuzzy Analytic Hierarchy Process to determine the student’s preferences, and uses statistical analysis such as independent sample t-test and ANOVA to evaluate the factors. Also, the study uses machine learning classification models such as Logistic Regression, Support Vector Machine, Naïve Bayes, Decision Trees, voting classifiers, Bagging, and Random Forest to predict and evaluate the most predicting model. The results of the dissertation conclude that overall students prefer the reductionist approach and report the students’ preference towards dimensions of complexity, independence, uncertainty, systems worldview, and flexibility and the ranking difference based on some factors. Lastly, the results show that the students’ preference for holistic thinking can be predicted with a 77% accuracy using the Random Forest classifier

Ekologiczny łańcuch dostaw: narzędzia do oceny E-odpadów – globalna perspektywa

When a company's supply chain has achieved a desirable degree of eco-friendliness in all regards, from a sustainability perspective, its performance will be satisfactory. Since the closed-loop e-waste supply chain's operations are primarily focused on achieving sustainability objectives related to the manufacturing, distribution, reusing, and discarding electrical components, it is crucial to evaluate its success in this area. In order to monitor the performance of supply chains and enhance the processes, the supply chain operations reference model offers suggestions and benchmarking tools. In this study, a conceptual framework is illustrated to show how these standards could be used in the E-waste supply chain to link business processes, metrics, industry standards, and technology in order to enhance the relationship and coordination between the supply chain members and to increase sustainability throughout the supply chain. Insufficient attention so far has been paid to the SCOR model's sustainability criteria, according to an assessment of the literature. Consequently, in the wake of portraying the structure of Supply Chain Operation Reference model, we make sense of which credits should be included in Supply Chain Operation Reference so to reflect manageability and which cycles and practices are related with every standard or should be remembered for Supply Chain Operation Reference to lay out the connection between execution, cycles, and practices.Kiedy łańcuch dostaw firmy osiągnie pożądany stopień przyjazności dla środowiska pod każdym względem, z punktu widzenia zrównoważonego rozwoju, jego wyniki będą zadowalające. Ponieważ operacje łańcucha dostaw E-odpadów w obiegu zamkniętym koncentrują się przede wszystkim na osiąganiu celów zrównoważonego rozwoju związanych z produkcją, dystrybucją, ponownym użyciem i utylizacją komponentów elektrycznych, kluczowe znaczenie ma ocena jego sukcesu w tej dziedzinie. Aby monitorować wydajność łańcuchów dostaw i ulepszać procesy, model referencyjny operacji łańcucha dostaw oferuje sugestie i narzędzia do analizy porównawczej. W tym badaniu nakreślono ramy koncepcyjne, aby pokazać, w jaki sposób standardy te można wykorzystać w łańcuchu dostaw elektrośmieci w powiązaniu z procesami biznesowymi, wskaźnikami, standardami branżowymi i technologią w celu wzmocnienia relacji i koordynacji między członkami łańcucha dostaw i aby zwiększyć poziom zrównoważonego rozwoju w całym łańcuchu dostaw. Jak dotąd, co potwierdza dokonany przegląd literatury, kryteria zrównoważonego rozwoju modelu SCOR nie poświęcano wystarczającej uwagi. W związku z tym, po przedstawieniu struktury Modelu referencyjnego operacji łańcucha dostaw, rozumiemy, które kredyty powinny zostać uwzględnione w referencyjnej operacji łańcucha dostaw, aby odzwierciedlić łatwość zarządzania oraz które cykle i praktyki są związane z każdym standardem lub należy o nich pamiętać w odniesieniu do łańcucha dostaw, co umożliwia ukazanie związku pomiędzy wykonaniem, cyklami i praktykami

Toward better intelligent learning (iLearning) performance:what makes iLearning work for students in a university setting?

We explored the critical factors associated with iLearning that impact students’ learning performance and identified the factors with a notable influence to help managers in higher education institutions increase the effectiveness of iLearning for students. We initially synthesised 4 main dimensions (including 26 criteria): performance expectancy, lecturers’ influence, quality of service, and personal innovativeness. Subsequently, we conducted surveys in two stages. First, by studying a group of students with experience using iLearning at Taiwanese universities, we extracted 5 critical dimensions (including 18 criteria) through a factor analysis. Second, by studying a group of senior educators and practitioners in Taiwan, we prioritised the dimensions and criteria through the analytic hierarchy process (AHP). We found that performance expectancy is the top critical dimension, and the top five critical criteria pertain to enhancing the learning performance, increasing the learning participation, altering learning habits, ensuring access at all times, and enabling prompt use of learning resources. Moreover, we recommend several suggestions for the relevant managers to enhance the students’ iLearning performance