The sustainability of the creative industry through creative-based tourism in the Laweyan Tourism Village requires the support of a sustainable and inclusive development model for local communities. This research aims to present the design of a tourist village development model that applies the eco-cultural city concept as a Surakarta City Perspective through creative-based tourism towards creative industries. This research uses a qualitative approach with a descriptive exploratory method. Data collection techniques use interviews with key informants. Empirical observation using cultural mapping as identification of physical mapping of spatial layout, build ings and environment, as well as cultural landscapes for tangible and intangible cultural assets of the community in the local landscape in the Laweyan tourist village. Content analysis is applied as a research data analysis method. The research results provide an overview of the design of the creative-based tourism village development model towards a sustainable creative industry including aspects attraction, accessibility, amenities, and ancillary, and green tourism. Model design requires commitment and participation from the government and private sector in collaborating with sustainable tourist village development forums.

Artificial Intelligence (AI) has become a pivotal force in transforming the retail industry, particularly in the online shopping environment. This study investigates the impact of various AI applications—such as personalized recommendations, chatbots, predictive analytics, and social media engagement—on consumer buying behaviors. Employing a quantitative research design, data was collected from 760 respondents through a structured online survey. The snowball sampling technique facilitated the recruitment of participants, focusing on diverse demographics and their interactions with AI technologies in online retail. The findings reveal that AI-driven personalization significantly enhances consumer purchase intentions and satisfaction. Multiple regression analysis shows that AI personalization (β = 0.35, p < 0.001) has the most substantial impact on purchase intention, followed by chatbot effectiveness (β = 0.25, p < 0.001), predictive analytics (β = 0.20, p < 0.001), and social media engagement (β = 0.15, p < 0.01). Similarly, AI personalization (β = 0.30, p < 0.001), predictive analytics (β = 0.25, p < 0.001), and chatbot effectiveness (β = 0.20, p < 0.001) significantly influence consumer satisfaction. The hierarchical regression analysis underscores the importance of ethical considerations, showing that ethical and transparent use of AI increases consumer trust and engagement. Model 1 explains 45% of the variance in consumer behavior (R² = 0.45, F = 154.75, p < 0.001), while Model 2, incorporating ethical concerns, explains an additional 10% (R² = 0.55, F = 98.25, p < 0.001). This study highlights the necessity for retailers to leverage AI technologies ethically and effectively to gain a competitive edge, improve customer satisfaction, and drive long-term success. Future research should explore the long-term impacts of AI on consumer behavior and the integration of emerging technologies such as augmented reality and the Internet of Things (IoT) in retail.

The scientific objective of this study is to demonstrate how a hybrid photovoltaic-grid-generator microsystem responds under transient regime to varying loads and grid disconnection/reconnection. The object of the research was realized by acquiring the electrical magnitudes from the three PV systems (25 kW, 40 kW, and 60 kW) connected to the grid and the consumer (on-grid), during the technological process where the load fluctuated uncontrollably. Similar recordings were also made for the transient regime caused by the grid disconnection, diesel generator activation (450 kVA), its synchronization with PV systems, power supply to receivers, and grid voltage restoration after diesel generator shutdown. Analysis of the data focused on power supply continuity, voltage stability, and frequency variations. Findings indicated that on-grid photovoltaic systems had a 7.9% maximum voltage deviation from the standard value (230 V) and a frequency variation within ±1%. In the transient period caused by the grid disconnection and reconnection, a brief period with supply interruption was noted. This study contributes to the understanding of hybrid system behavior during transient regimes.

Cities play a key role in achieving the climate-neutral supply of heating and cooling. This paper compares the policy frameworks as well as practical implementation of smart heating and cooling in six cities: Munich, Dresden and Bad Nauheim in Germany; and Jinan, Chengdu and Haiyan in China, to explore strategies to enhance policy support, financial mechanisms, and consumer engagement, ultimately aiming to facilitate the transition to climate-neutral heating and cooling systems. The study is divided into three parts: (i) an examination of smart heating and cooling policy frameworks in Germany and China over the past few years; (ii) an analysis of heating and cooling strategies in the six case study cities within the context of smart energy systems; and (iii) an exploration of the practical solutions adopted by these cities as part of their smart energy transition initiatives. The findings reveal differences between the two countries in the strategies and regulations adopted by municipal governments as well as variations within each country. The policy frameworks and priorities set by city governments can greatly influence the development and implementation of smart heating and cooling systems. The study found that all six cities are actively engaged in pioneering innovative heating and cooling projects which utilise diverse energy sources such as geothermal, biomass, solar, waste heat and nuclear energy. Even the smaller cities were seen to be making considerable progress in the adoption of smart solutions.

This study investigates the impact of artificial intelligence (AI) integration on preventing employee burnout through a human-centered, multimodal approach. Given the increasing prevalence of AI in workplace settings, this research seeks to understand how various dimensions of AI integration—such as the intensity of integration, employee training, personalization of AI tools, and the frequency of AI feedback—affect employee burnout. A quantitative approach was employed, involving a survey of 320 participants from high-stress sectors such as healthcare and IT. The findings reveal that the benefits of AI in reducing burnout are substantial yet highly dependent on the implementation strategy. Effective AI integration that includes comprehensive training, high personalization, and regular, constructive feedback correlates with lower levels of burnout. These results suggest that the mere introduction of AI technologies is insufficient for reducing burnout; instead, a holistic strategy that includes thorough employee training, tailored personalization, and continuous feedback is crucial for leveraging AI’s potential to alleviate workplace stress. This study provides valuable insights for organizational leaders and policymakers aiming to develop informed AI deployment strategies that prioritize employee well-being.

The present study is designed to analyse how the Public-Private Partnership (PPP) model is helping to create sustainable livelihood opportunities for women. It draws an inference from ‘Marudhara Rangsaaz’, a producer company operating in the textile sector in Rajasthan, India. It explains how this woman-based organisation operates in a PPP model to create economic value for women. It also tries to understand the specific role of the Rajasthan Grameen Aajeevika Vikas Parishad (RAJEEVIKA), The Rajasthan Government partner and ‘Rang Sutra’, the private partner, and the women members of ‘Marudhara Rangsaaz’ in the PPP model. The paper adopted a case study research design. The data was collected using in-depth interviews with all stakeholders and analysis of the documents. The findings indicate that in the said PPP model, Government took the role of mobilizer, financer, mentor, and private player, took the responsibility of building up capacity and arranging market links, and the women members worked together to help themselves sustain the project.