Search Results (2,204)

The 2023 Global Sustainable Development Report identified sustainable cities and communities as a critical area for in-depth review, emphasizing the need for systematically examining theoretical knowledge and guidance on the direction of development This article reviews the relevant literature from the Web of Science core database over the past decade and introduces Professor Verganti’s theoretical perspective of “design-driven innovation” to summarize technological research, user needs/demand, and design, providing a new theoretical dimension for the research on sustainable communities. To this end, this study employs three econometric tools—VOSviewer, RStudio Bibliometric, and CiteSpace—to analyze status and trends visually. The findings reveal that the design level has garnered the most research results, with the USA as the primary contributor and China as the country with the most development potential. Moreover, the most prominent research topics within the three perspectives are microbial communities, sustainable development goals, and ecosystem services, with recent research highlights focusing on artificial intelligence, social innovation, and tourism. In conclusion, this article proposes a strategic framework for the future development of sustainable communities, encompassing consolidation of technical foundations, clarification of demand orientation, and updating design specifications and theories to provide diverse solutions. Full article

Driven by the rise of big data, enterprises urgently need to accurately utilize users’ real-time and accumulated information to realize present value and establish long-term advantages, then achieving the sustainable development. Previous works identified value co-created through big data as “big data cooperative assets”. However, while the mainstream research on this concept has primarily focused on analyzing its features, formation conditions, and influencing factors, particularly from the perspective of time-horizon value, an equally important area—the formation mechanism—has been neglected. To address this gap, this article constructs a classification framework of big data cooperative assets by combining time-horizon aspects with interaction dominators. It then examines the formation mechanisms of data link and data insight value through multi-case analysis. Overall, this research not only provides new perspectives for enriching the theoretical understanding of big data cooperative assets but also suggests useful practical guidelines for innovative interaction between enterprises and users in the age of data competition. In addition, improving the efficiency of realizing the value of big data cooperative assets helps the enterprise to better cope with external risks, such as market changes and policy adjustments, and maintain sound operations, further contributing to build a harmonious society and promote the construction of an ecological civilization. Full article

The increasing adoption of electric vehicles offers a way to combat the harmful impacts of climate change and to improve city living standards. Yet limited access to and lack of consistency among electric vehicle charging stations present obstacles for electric vehicle owners. This study advocates for an approach that positions the preferences of electric vehicle drivers first when choosing an electric vehicle charging station. By considering relevant factors to electric vehicle drivers and treating the problem as a grey system where certain information is known while other aspects are unknown, this research aims to empower users to make decisions aligned with their needs. The best–worst method is employed to assign preferences allowing electric vehicle users to make informed choices based on their priorities. The grey relational analysis method is utilized to rank electric vehicle charging stations based on user preferences. The best–worst method-grey relational analysis approach, as shown by examples, efficiently assists electric vehicle users in choosing the optimal electric vehicle charging station. This study acknowledges and incorporates the often-overlooked perspectives of electric vehicle drivers into a user-centric solution in existing research models. The gained insights carry significance for managing transportation and energy systems and designing user-friendly applications pertaining to electric vehicle charging station selection. Full article

The booming of the building industry has led to a sharp increase in energy consumption. The advancement of zero-energy buildings (ZEBs) is of great significance in mitigating climate change, improving energy efficiency, and thus realizing sustainable development of buildings. This paper reviews the recent progress of key technologies utilized in ZEBs, including energy-efficient measures (EEMs), renewable energy technologies (RETs), and building energy management system (BEMS), aiming to provide reference and support of the wider implementation of ZEBs. EEMs can reduce energy demand by optimizing the envelope design, phase change materials integration, efficient HVAC systems, and user behavior. The renewable energy sources discussed here are solar, biomass, wind, and geothermal energy, including distributed energy systems introduced to integrated various renewable resources and meet users’ demand. This study focuses on the application of building energy management in ZEBs, including energy use control, fault detection and diagnosis, and management optimization. The recent development of these three technologies mainly focuses on the combination with artificial intelligence (AI). In addition, this paper also emphasizes possible future research works about user behavior and zero-energy communities to improve the energy efficiency from a more complicated perspective. Full article

This study proposes an optimization method based on Rough Set Theory (RST) and Particle Swarm Optimization–Support Vector Regression (PSO-SVR), aimed at enhancing the emotional dimension of outdoor micro-space (OMS) design, thereby improving users’ outdoor activity duration preferences and emotional experiences. OMS, as a key element in modern urban design, significantly enhances residents’ quality of life and promotes public health. Accurately understanding and predicting users’ emotional needs is the core challenge in optimizing OMS. In this study, the Kansei Engineering (KE) framework is applied, using fuzzy clustering to reduce the dimensionality of emotional descriptors, while RST is employed for attribute reduction to select five key design features that influence users’ emotions. Subsequently, the PSO-SVR model is applied to establish the nonlinear mapping relationship between these design features and users’ emotions, predicting the optimal configuration of OMS design. The results indicate that the optimized OMS design significantly enhances users’ intention to stay in the space, as reflected by higher ratings for emotional descriptors and increased preferences for longer outdoor activity duration, all exceeding the median score of the scale. Additionally, comparative analysis shows that the PSO-SVR model outperforms traditional methods (e.g., BPNN, RF, and SVR) in terms of accuracy and generalization for predictions. These findings demonstrate that the proposed method effectively improves the emotional performance of OMS design and offers a solid optimization framework along with practical guidance for future urban public space design. The innovative contribution of this study lies in the proposed data-driven optimization method that integrates machine learning and KE. This method not only offers a new theoretical perspective for OMS design but also establishes a scientific framework to accurately incorporate users’ emotional needs into the design process. The method contributes new knowledge to the field of urban design, promotes public health and well-being, and provides a solid foundation for future applications in different urban environments. Full article

The impact of digital empowerment on green innovation is increasingly evident, enabling various subjects to improve the integration of innovation elements and enhance innovation efficacy across a broader temporal and spatial scope. A comprehensive examination of the mechanisms that underlie this process is required. This paper constructs the ‘elements-subjects-environments’ research framework of digital innovation ecosystems, collecting data from 30 provinces in China from 2017 to 2021 and using green total factor productivity (GTFP) to evaluate the level of green regional development. In this study, the dynamic qualitative comparative analysis (QCA) method is employed to analyze the intricate causal mechanisms and configurations of green regional development that are driven by digital innovation ecosystems from both temporal and spatial perspectives. The results show that: (1) green regional development requires the interaction of multiple elements, subjects, and the environment, and a single condition does not constitute a necessary condition; (2) there are four pathways with different configurations for high-level green development: data elements-driven enterprise application innovation, data elements-driven enterprise-user co-creation, data elements-driven multi-collaborative innovation, and digital environment-driven university basic innovation; (3) the temporal and spatial dimensions of China’s green regional development pathways are heterogeneous: the significance of data elements in fostering green regional development is increasing; the multi-collaborative innovation configuration is facilitating the green development of the eastern and central regions, whereas the western and northeastern regions are progressing at a relatively slow pace. This study provides theoretical and practical insights to promote the integration of digital innovation and green development. Full article

Urban transit systems are crucial for modern cities, providing sustainable and efficient transportation solutions for residents’ daily commutes. Extensive research has been conducted on optimizing the design of transit systems. Among these studies, designing transit line trajectories and setting operating frequencies are critical components at the strategic planning level, and they are typically implemented in an urban integrated transportation network. However, its computational complexity grows exponentially with the expansion of urban integrated transportation networks, resulting in challenges to global optimization in large-scale cities. To address this problem, this study investigates the layout planning of a basic public transit network (BPTN) to simplify the urban integrated transportation network by filtering out road segments and intersections that are unattractive for both users and operators. A non-linear integer programming model is proposed to maximize the utility of the BPTN, which is defined as a weighted sum of expected travel times (from a user perspective) and transportation efficiency (from an operator perspective). An expected transit flow distribution (ETFD) analysis method is developed, combining different assignment approaches to evaluate the expected travel time and transportation efficiency of the BPTN under various types of transit systems. Moreover, we propose an objective–subjective integrated weighting approach to determine reasonable weight coefficients for travel time and transportation efficiency. The problem is solved by a heuristic solution framework with a topological graph simplification (TGS) process that further simplifies the BPTN into a small-scale graph. Numerical experiments demonstrate the efficacy of the proposed model and algorithm in achieving desirable BPTN layouts for different types of transit systems under variable demand structures. The scale of the BPTN is significantly reduced while maintaining a well-balanced trade-off between expected travel time and transportation efficiency. Full article

The Business Model Canvas and value chain have significantly impacted how companies and entrepreneurs develop their business strategies. Both the Business Model Canvas and the value chain provide a simple, visual approach to effectively map out the key elements of a business. They have also been used as foundational models for ecosystem business models. Ecosystem business models are created by integrating the Business Model Canvas and the pie model, known as the Integrated Business Model. Another method for generating an ecosystem business model is integrating the value chain and the pie model, known as the service-dominated business model radar. Ecosystem business models with an organizational approach also provide a broad view of the roles of each organization, divided into five actors: governor, input provider, aggregator, enabler, and end user. In this research, the perspective of the ecosystem business model originates from an ecological analogy. The ecological concept consists of community ecology and ecosystem ecology. Community ecology relates to the types of actors that play roles in the ecosystem, while ecosystem ecology pertains to the value chain processes within the ecosystem. This research will discuss the advantages and limitations of the Business Model Canvas, the value chain, and organizations as foundational models for ecosystem business models, as well as opportunities to create new ecosystem business models based on the concepts of community ecology and ecosystem ecology. The new business model developed will be applied to electric vehicles in sustainable tourism areas. Full article

This paper examines Instagram’s increasing influence on the hotel industry, an area that remains under-researched from both consumer and hotel perspectives. Through a sequential explanatory design, combining a quantitative analysis of 1031 posts with qualitative interviews from hotel professionals, the research uncovers the types of content that resonate most with users and how hoteliers strategically leverage Instagram. The findings reveal which content formats, hotel attributes and post characteristics capture audience attention. Additionally, the study offers unique insights into Instagram’s distinct role compared to other social media platforms in the hotel industry. The study provides a novel definition of what makes a hotel “Instagrammable” from both consumer and industry viewpoints, offering valuable insights into how hotels can strategically harness Instagram to attract and engage their audience. Full article

Interaction is typically at the core of the value co-creation process through operant resource exchange in online collaborative innovation communities (OCICs). While some studies emphasize the facilitating effect of interaction on value co-creation, others have drawn opposite conclusions, such as more peer interaction leads to less idea generation. Thus, the purpose of this paper is to utilize the service ecosystem framework to clarify the overall relationship between interaction and value co-creation and to explore the moderating factors that may have contributed to the divergence and inconsistency of previous studies. We conducted a meta-analysis of 65 effect sizes obtained from 63 articles with a cumulative sample size of 25,185 between 2004 and 2023, using a random effects model. The results indicate that interaction has a significantly positive impact on user value co-creation within OCICs (r = 0.453, 95%CI [0.405, 0.499]), and the heterogeneity among studies was significant (Q = 1409.29, p < 0.001). The strength of this correlation was moderated by the types of interaction (human–computer or human–human interactions), the types of OCICs (business-sponsored or socially constructed online communities), and the number of involved OCICs (one or multiple online communities), but not by the cultural background. These findings support the service ecosystem perspective rather than resource scarcity theory by resolving the mixed findings regarding the relationship between interaction and user value co-creation. Furthermore, this study systematically examined the contingent factors separately across three levels, micro (types of actor interactions), meso (types and number of OCICs), and macro (cultural background), combining the whole and the part insights, and empirically integrating service ecosystems as the foundational paradigm and unit of analysis for value co-creation research for the first time. This research contributes to theoretical frameworks in service ecosystems and offers actionable insights for management practices in business and marketing. Full article

As critical infrastructure of age-friendly cities, senior centers are designed to be embedded in communities and facilitate service accessibility for older adults. However, their underutilization is widely documented, suggesting a need to reassess their effectiveness. Existing studies often analyze the issue focusing on socio-demographic factors, overlooking the spatial contexts in which senior centers are embedded and their impacts on older people’s access. This study aims to address the research gap by investigating the spatial embeddedness of senior centers using Space Syntax methods and examining its influence on older people’s access patterns. Using a geo-behavioral dataset collected in Nanjing, China, we find that about 70% of the senior centers in the research area are embedded in highly localized settings with limited connections to global street networks, which significantly restricts the access of older people from wider spatial contexts. This spatial segregation may force senior centers to incur higher costs to attract users, thereby reducing the effectiveness of community-based services. This study introduces a novel spatial perspective to evaluate community-based services, highlighting the critical influence of the spatial context on service accessibility. The findings provide valuable empirical insights for policymakers and planners striving to create age-friendly cities and communities. Full article

(1) Background: Telemedicine is a vital tool for enhancing healthcare accessibility and outcomes at reduced costs. This study aimed to assess the usability of the Maia Connected Care telemedicine platform for managing spasticity in patients receiving botulinum toxin type-A, focusing on the perspectives of Italian physiatrists with expertise in this treatment. (2) Methods: Conducted from March 2023 to June 2023, this multicenter survey involved 15 Italian physicians who used the platform for teleconsultations. Data collected included demographic details, responses to the Telemedicine Usability Questionnaire, and physician insights on patient satisfaction, treatment effectiveness, and implementation challenges in telehealth. (3) Results: The platform demonstrated high usability, with strong physician satisfaction due to its user-friendly interface and quality of interactions. A majority expressed willingness to continue telehealth for spasticity management, noting its effectiveness in improving patient satisfaction and outcomes. Challenges included replicating the depth of in-person consultations and addressing issues like reimbursement and telehealth standardization. (4) Conclusions: This study highlights telemedicine’s potential for spasticity management and clinician satisfaction, while underscoring the need for improvements in simulating in-person experiences and addressing systemic issues. The absence of patient perspectives represents a limitation, advocating for future research to optimize telemedicine practices and evaluate long-term clinical impacts. Full article

Introduction: Diabetes mellitus (DM) has a millennia-long history, with early references dating back to ancient Egypt and India. However, it was not until the 20th century that the connection between diabetes and insulin was fully understood. The sequencing of insulin in the 1950s initiated the convergence of biotechnology and diabetes management, leading to the development of recombinant human insulin in 1982. This marked the start of peptide-based therapies in DM. Recombinant peptides for DM treatment: Numerous recombinant peptides have been developed since, starting with modified insulin molecules, with the aim of bettering DM management through fine-tuning the glycemic response to insulin. Peptide-based therapies in DM have expanded substantially beyond insulin to include agonists of Glucagon-like peptide-1 receptor and Glucose-dependent insulinotropic polypeptide receptor, glucagon receptor antagonists, and even peptides exerting multiple receptor agonist effects, for better metabolic control. Insulin pumps, continuous glucose monitoring, and automated insulin delivery systems: The development of modern delivery systems combined with real-time glucose monitoring has significantly advanced diabetes care. Insulin pumps evolved from early large devices to modern sensor-augmented pumps with automated shutoff features and hybrid closed-loop systems, requiring minimal user input. The second-generation systems have demonstrated superior outcomes, proving highly effective in diabetes management. Islet cell transplantation, organoids, and biological pancreas augmentation represent innovative approaches to diabetes management. Islet cell transplantation aims to restore insulin production by transplanting donor beta cells, though challenges persist regarding graft survival and the need for immunosuppression. Organoids are a promising platform for generating insulin-producing cells, although far from clinical use. Biological pancreas augmentation relies on therapies that promote beta-cell (re)generation, reduce stress, and induce immune tolerance. Further biotechnology-driven perspectives in DM will include metabolic control via biotechnology-enabled tools such as custom-designed insulin hybrid molecules, machine-learning algorithms to control peptide release, and engineering cells for optimal peptide production and secretion. Full article

In the context of the coronavirus pandemic and the armed conflict between Russia and Ukraine, energy security is essential to economic challenges nowadays. The basis for the proper operating of the energy sector is to ensure a stable supply of energy to end users and to secure finances of energy companies, so that they can operate sustainably in times of uncertainty. In our studies, we have addressed this issue with the main objective of assessing the state of energy security from the perspective of the stability of the financial situation of energy sector companies in the context of the global energy crisis and a sustainable energy future. Financial indicators and a canonical variable analysis were used to examine the financial situation of companies in the energy sector and to describe links between selected groups of energy companies. Such companies operating during political and economic instability did not record worse financial results than in the year 2018. It was found that in case-studied firms, total debt decreased and moreover, liquidity and return on assets improved. Companies have focused on securing their financial health and ensuring the stability of their energy supplies and the issue of the environmental impact of energy production has unfortunately become a secondary concern. Nevertheless, in the event of further crises, it is reasonable to assume that a focus on maintaining liquidity and generating profits for energy companies will be more important to companies than environmental challenges and the fight against climate change. Full article

A concept of a high throughput, user-friendly, versatile bending magnet beamline at the fourth-generation synchrotron radiation facility SKIF, currently being constructed in Koltsovo (a science town near Novosibirsk, Russia), is proposed. The beamline is designed to implement the conventional and most demanded synchrotron techniques: XAS (X-ray absorption spectroscopy); XRD (X-ray diffraction), both powder and single-crystal, including the in situ mode; and XRF (X-ray fluorescence analysis). The beamline is conceived to be as simple as possible, but it is multifunctional, being a base beamline for the education and training of students, future synchrotron users, and beamline scientists. A number of potential beamline optical layouts are modeled in the XRT (XRayTracer) program package. The resulting beam characteristics at the sample position are discussed. A monochromator model is proposed. Surface distortions and their influence on the rocking curve of the Si111 crystal due to incoming heat loads are realistically modeled. The optimum design of the station is defined. The range of crystalline objects that are possible to be studied at the proposed station is emphasized, and future perspectives are outlined. Full article