Sustainable development is a priority for the future of our society. Sustainable development is of particular importance to the Architecture, Engineering, and Construction (AEC) industry, both for new buildings and for the renovation of existing buildings. Great potential for sustainable development lies in the renovation of existing office buildings. This paper introduces a new framework for identifying the best set of renovation strategies for existing office buildings. The framework applies selected green building rating system criteria and cost-effective sustainable renovation solutions based on cost-benefit analysis (CBA), and thus provides a novelty in decision-making support for the sustainable renovation of office buildings at an early-stage. The framework covers all necessary steps and activities including data collection, determination of the required level of renovation, selection of the green building rating system, identification of impact categories and criteria, and final evaluation and decision-making using CBA. The framework can be used in conjunction with different systems and according to different regional characteristics. The applicability of the addressing procedure is shown through a case study of a comprehensive renovation of an office building in the city of Maribor. Full article

The purpose of innovation is to consume fewer natural resources in order to create sustainable performance; therefore, innovation can ease the pressure of the ecological load and promote the sustainable development of the economy. Taking the 269 enterprises listed on the main board of the electronic information industry from 2010 to 2019 as samples, using the threshold panel data model, the nonlinear relationship between the knowledge-based network structure hole and the short-term and long-term innovation performance of the enterprises were studied, and the threshold effect of R&D investment intensity was discussed. When the R&D investment intensity is from 1.96% to 15.96%, the knowledge-based network structure hole has a significant positive impact on short-term innovation performance. When the R&D investment intensity is from 5.72% to 10.64%, the knowledge-based network structure hole has a significant positive effect on long-term innovation performance. Lower R&D investment intensity can make the knowledge-based network structure hole promote the increase of short term innovation performance, but to make the knowledge-based network structure hole have a positive impact on long term innovation performance, the R&D investment intensity should be increased by more than 5.72%. When R&D investment intensity is not higher than 15.96%, the knowledge-based network structure hole has a significant positive impact on short term innovation performance, but to make the knowledge-based network structure hole maintain the positive effect on long term innovation performance, R&D investment intensity should not exceed 10.64%. Therefore, enterprises should be guided to optimize the knowledge-based network structure according to the R&D investment intensity in order to improve the short term and long-term innovation performance of an enterprise. These research results can help enterprises to save resources and promote the sustainable development of the economy. Full article

High-penetration grid-connected photovoltaic (PV) systems can lead to reverse power flow, which can cause adverse effects, such as voltage over-limits and increased power loss, and affect the safety, reliability and economic operations of the distribution network. Reasonable energy storage optimization allocation and operation can effectively mitigate these disadvantages. In this paper, the optimal location, capacity and charge/discharge strategy of the energy storage system were simultaneously performed based on two objective functions that include voltage deviations and active power loss. The membership function and weighting method were used to combine the two objectives into a single objective. An energy storage optimization model for a distribution network considering PV and load power temporal changes was thus established, and the improved particle swarm optimization algorithm was utilized to solve the problem. Taking the Institute of Electrical and Electronic Engineers (IEEE)-33 bus system as an example, the optimal allocation and operation of the energy storage system was realized for the access of high penetration single-point and multi-point PV systems in the distribution network. The results of the power flow optimization in different scenarios were compared. The results show that using the proposed approach can improve the voltage quality, reduce the power loss, and reduce and smooth the transmission power of the upper-level grid. Full article

This paper proposes a multi-class classification model for technology evaluation (TE) using patent documents. TE is defined as converting technology quality to its present value; it supports efficient research and development using intellectual property rights–research & development (IP–R&D) and decision-making by companies. Through IP–R&D, companies create their patent portfolios and develop technology management strategies. They protect core patents and use those patents to cooperate with other companies. In modern society, as conversion technology has been rapidly developed, previous TE methods became difficult to apply to technology. This is because they relied on expert-based qualitative methods. Qualitative results are difficult to use to guarantee objectivity. Many previous studies have proposed models for evaluating technology based on patent data to address these limitations. However, those models can lose contextual information during the preprocessing of bibliographic information and require a lexical analyzer suitable for processing terminology in patents. This study uses a lexical analyzer produced using a deep learning structure to overcome this limitation. Furthermore, the proposed method uses quantitative information and bibliographic information of patents as explanatory variables and classifies the technology into multiple classes. The multi-class classification is conducted by sequentially evaluating the value of a technology. This method returns multiple classes in order, enabling class comparison. Moreover, it is model-agnostic, enabling diverse algorithms to be used. We conducted experiments using actual patent data to examine the practical applicability of the proposed methodology. Based on the experiment results, the proposed method was able to classify actual patents into an ordered multi-class. In addition, it was possible to guarantee the objectivity of the results. This is because our model used the information in the patent specification. Furthermore, the model using both quantitative and bibliographic information exhibited higher classification performance than the model using only quantitative information. Therefore, the proposed model can contribute to the sustainable growth of companies by classifying the value of technology into more detailed categories. Full article

Resilience is the ability to restore performance after sustaining serious damage by a usually unexpected threat. This paper analyzes resilience of process plants as there are oil and gas refining, chemical manufacturing, power-producing plants, and many more. Over the years, plant safety has shifted from retrospective to proactive measures. Safety is important from many points of view, such as protection of workforce and nearby population, but certainly too from an economical and sustainability aspect. Pro-action requires predictive insight of what in the process can go wrong because of internal or external disruptive disturbance. Over the years, to that end, much effort was spent developing risk assessment methods and management. However, risk assessment has proven to be fallible because of various uncertainties and not the least by overlooked or unknown threats. To protect against those upsetting threats, measures can be taken up to a certain limit. These start in designing error-tolerant equipment able to be receptive to early warning signals during operations, responding to those with ‘plasticity’ of mind (that is, an organization and its leadership especially able to think ‘outside-the box’ for coping with unexpected situations), and finally, to deploy effective emergency response and able to recover from damage quickly. The paper presents a summary/review of nearly a decade of research work at the Mary Kay O’Connor Process Safety Center at the Texas A&M University to develop the concept and the techniques to realize a resilient plant, so far with a focus on chemical plant. It is, however, still a ‘work-in-progress’; potential is large. Besides the conceptual details, cases are presented that show how human and technical factors, combined in a socio-technical system, can lead to a broader plant safety insight enabling more effective risk control and increased resilience. These cases have up to now only considered warning signals and possible management action, while still limited to internal threats. Hence, aspects of equipment design and recovery should be further considered, also in the light of the dynamics of present-day business environment. Full article

Building information modeling (BIM) and life cycle assessment (LCA) are two methods that can be helpful when designing buildings with lower environmental impacts. One of the most significant examples of environmental impact assessments in construction is green building certification. Certified buildings have improved performance and greater asset value. In this study, four certification systems were investigated for their potential interconnections with BIM and LCA. The main tasks were (1) to review a BIM-based workflow, (2) assess its usage as an input for the LCA within green certifications, and (3) provide suggestions for developing building models. Building models can be helpful during the design process, but the best results are expected when the specifically described steps are followed. These suggestions aim at improving building models in terms of their usage for green building certifications and particularly for LCA. All the investigated results were clarified and adjusted using a model of a recently finished building in Zug. As reference tools, One Click LCA and a manual process were selected. The outcomes were aligned with those of other studies and confirmed the necessity of good data and management quality for building projects. Full article

This paper proposes a framework for assessing the financial sustainability of a wine producing company. The probabilistic approach is used to model the expected changes in the financial situation of an enterprise based on the historical trends. The case of an enterprise in Ukraine is considered as an illustration. The Markov chain is adopted for the forecasting exercise. Using the Markov chain framework allows one to predict the probability of financial security change for several periods ahead. The forecast relies on the transition probabilities obtained by exploiting the historical data. The proposed framework is implemented by construction of the financial security level transition matrices for three scenarios (optimistic, baseline and pessimistic). The case study of a Ukrainian wine producing company is considered. The possibilities for applying the proposed method in establishing anti-crisis financial strategy are discussed. The research shows how forecasting the financial security level of a company can serve in anti-crisis financial potential buildup. Full article

Sustainable tourism can be the motivation to manage resources to satisfy environmental, social and economic needs through cultural integrity, biological diversity, ecological processes, social and economic equity, and general enrichment. Based on a systematic literature review conducted on research papers published between 2015 and 2020, and on the case studies contained within them (19 papers), this analysis focuses on the innovation drivers and sustainability drivers identified within family businesses in tourism. This desk-based research has made it possible to highlight how variable sustainability is present, albeit in a limited fashion, within family businesses in tourism; at the same time, it also shows how innovative strategies contribute to sustainable development. From the analysis, the correlations between family businesses, family dynamics, sustainability practices, innovation drivers and case studies were analyzed. The results show the poor implementation of innovative strategies, and at the same time, the presence of other variables that guarantee the adoption of sustainable practices. Important research gaps are identified, and future research priorities are suggested. Furthermore, the article is based on a collection of non-exhaustive literary sources. The implications for both family businesses and sustainable development are discussed. Full article

Problem posing is rarely seen in Spanish classrooms, least of all in preschool education. The lack of research, coupled with a lack of guidance, has resulted in teachers simply not considering the approach as something that could enrich their work. This study examines a problem-posing lesson given by a preschool teacher to a class of four-year-olds. It focuses in particular on the organisational principles and the factors to be taken into consideration in applying the strategy. Through the application of a bottom-up analysis, seven characterisers are identified, four associated with task design and planning: Characteristics of the resources, type of problem, expression of problem formulation, and type of problem formulation; and three associated with lesson management: Stages in task execution, degree of liberty, and role of the pupils’ drawings of the problem. Full article

Physical education (PE) helps form lifelong learning and exercise habits; therefore, PE courses should be designed to enhance student motivation. Team-game tournaments (TGTs) enable learning in heterogeneous groups and involve positive interdependence, individual accountability, social skills, face-to-face interaction, group processing, and equal opportunities. Therefore, this quasi-experimental pre-test–post-test study investigated the effects of the TGT on learning motivation and motor skills. In this study, 108 students who enrolled in an advanced basketball course from two classes in a Taiwanese university were recruited as participants. Experimental teaching was implemented based on the class patterns, during which the students were divided into experimental and control groups. The control group, consisting of 56 students (46 male and 10 female), received conventional PE. In the TGT experimental group, constituting 52 students (40 male and 12 female), the TGT learning program was implemented. After a 12-week basketball teaching session, the TGT teaching strategy significantly improved student motivation but not motor skill acquisition. Competency level, however, did not significantly affect motivation but was significantly related to motor skill acquisition. Interaction effects between teaching strategy and competency level were non-significant. Despite TGTs enhancing learning motivation, PE teachers are still responsible for teaching rules, knowledge, and skills, engaging team members, and ensuring sufficient time for skill practice. Full article

This paper aims at contributing to the debate on the relationships between the European financial sector and sustainable development. Using a non-financial disclosure analysis of 262 European banks, the research sought, first, to investigate the “scope” of the contribution of European banks to the Sustainable Development Goals (SDGs) and, second, to explore the factors that seem to differentiate the SDGs approach among banks. The results show that country of origin, legal system, and adoption of an integrated report seem to differentiate banks in terms of contribution to the SDGs. The business model and stock exchange listing, conversely, do not seem to represent discriminatory factor in the contribution of banks toward the SDGs. The study can be useful for managers and decision makers to develop policies to support organizations in contributing to the SDGs. Full article

This paper presents findings relating to the territorial processes underlying the distribution and location of P2P accommodation in rural parts of Catalonia by establishing a system for classifying rural municipalities based on the volume and growth rate of the supply of this tourist accommodation, its share of the total supply of tourist accommodation, the pressure on the local population, and the function of this supply of accommodation in the regional tourism context. According to the findings, there are three distinct types of rural municipality: (a) Rural municipalities where the volume and growth of the supply of this accommodation are striking, these municipalities are located in the coastal hinterland and in high mountain areas, both of which enjoy high levels of tourism. This supply of accommodation plays a key role in the expansion of the areas of influence of well-established tourist destinations, (b) rural municipalities where this supply of accommodation presents an average volume and growth rate, located in inland areas of Catalonia and in high mountain regions with non-mass tourism development models specializing in rural tourism. This supply is helping boost tourism by expanding and diversifying the range of accommodation, and (c) rural municipalities where no tourist accommodation was available before the arrival of P2P accommodation. These are municipalities in inland areas with a strong agricultural presence, where P2P accommodation is paving the way for tourism. Full article

Most consumers in Taiwan have never eaten pure rice noodles (PRNs) and some may mistakenly treat corn starch-based rice noodles as PRNs. This study examines consumers’ willingness to pay (WTP) for PRNs using discrete choice (DC) experiments with a blind tasting test to understand consumers’ ability to identify PRNs with varying rice content on the basis of their appearance and taste. Collecting data from the Taipei metropolitan area, our DC experimental results of both pre- and post-experiment conditions show that Taiwanese consumers do prefer PRNs and their WTP for PRNs was strengthened. A latent class model highlights that attribute preferences tend to differ by group and thus rice content ratios should be properly labeled so that consumers can make a better choice according to their preferences. Our WTP estimates also imply that offering tasting trials to consumers is an effective marketing strategy to encourage potential purchases of PRNs for the rice noodle industry. Full article

Due to recent advancements in industrialization, climate change and overpopulation, air pollution has become an issue of global concern and air quality is being highlighted as a social issue. Public interest and concern over respiratory health are increasing in terms of a high reliability of a healthy life or the social sustainability of human beings. Air pollution can have various adverse or deleterious effects on human health. Respiratory diseases such as asthma, the subject of this study, are especially regarded as ‘directly affected’ by air pollution. Since such pollution is derived from the combined effects of atmospheric pollutants and meteorological environmental factors, and it is not easy to estimate its influence on feasible respiratory diseases in various atmospheric environments. Previous studies have used clinical and cohort data based on relatively a small number of samples to determine how atmospheric pollutants affect diseases such as asthma. This has significant limitations in that each sample of the collections is likely to produce inconsistent results and it is difficult to attempt the experiments and studies other than by those in the medical profession. This study mainly focuses on predicting the actual asthmatic occurrence while utilizing and analyzing the data on both the atmospheric and meteorological environment officially released by the government. We used one of the advanced analytic models, often referred to as the vector autoregressive model (VAR), which traditionally has an advantage in multivariate time-series analysis to verify that each variable has a significant causal effect on the asthmatic occurrence. Next, the VAR model was applied to a deep learning algorithm to find a prediction model optimized for the prediction of asthmatic occurrence. The average error rate of the hybrid deep neural network (DNN) model was numerically verified to be about 8.17%, indicating better performance than other time-series algorithms. The proposed model can help streamline the national health and medical insurance system and health budget management in South Korea much more effectively. It can also provide efficiency in the deployment and management of the supply and demand of medical personnel in hospitals. In addition, it can contribute to the promotion of national health, enabling advance alerts of the risk of outbreaks by the atmospheric environment for chronic asthma patients. Furthermore, the theoretical methodologies, experimental results and implications of this study will be able to contribute to our current issues of global change and development in that the meteorological and environmental data-driven, deep-learning prediction model proposed hereby would put forward a macroscopic directionality which leads to sustainable public health and sustainability science. Full article

The scope of the present paper is to promote social, cultural and environmental sustainability in cities by establishing a conceptual framework and the relationship amongst safety in urban public space (UPS), lighting and Information and Communication Technology (ICT)-based surveillance. This framework uses available technologies and tools, as these can be found in urban equipment such as lighting posts, to enhance security and safety in UPS, ensuring protection against attempted criminal activity. Through detailed literary research, publications on security and safety concerning crime and lighting can be divided into two periods, the first one pre-1994, and the second one from 2004–2008. Since then, a significant reduction in the number of publications dealing with lighting and crime is observed, while at the same time, the urban nightscape has been reshaped with the immersion of light-emitting diode (LED) technologies. Especially in the last decade, where most municipalities in the EU28 (European Union of all the member states from the accession of Croatia in 2013 to the withdrawal of the United Kingdom in 2020) are refurbishing their road lighting with LED technology and the consideration of smart networks and surveillance is under development, the use of lighting to deter possible attempted felonies in UPS is not addressed. To capitalize on the potential of lighting as a deterrent, this paper proposes a framework that uses existing technology, namely, dimmable LED light sources, presence sensors, security cameras, as well as emerging techniques such as artificial intelligence (AI)-enabled image recognition algorithms and big data analytics and presents a possible system that could be developed as a stand-alone product to alert possible dangerous situations, deter criminal activity and promote the perception of safety thus linking lighting and ICT-based surveillance towards safety and security in UPS. Full article