This study analyzes the role of innovation in the development of smart cities in Latin America. It focuses on how emerging technologies and sustainable strategies are being integrated into urban planning and urban development. In this sense, this study seeks to contribute to the smart city literature by answering the following research questions: (i) To what extent smart city innovative initiatives have been addressed in Latin America? and (ii) To what extent scholars have addressed sustainable innovation strategies in the smart city literature? To this end, this is the first comprehensive bibliometric analysis of smart city research in Latin America, with a structured and systematized review of the available literature. This methodological approach allows cluster visualization and detailed analysis of inter-node relationships using the VOSViewer software. The research comprises 4 stages: (a) search criteria; (b) selection of documents; (c) software and data extraction; and (d) analysis of results and trends. Results indicate that studies on the Latin America region began to develop in 2012, with Brazil as a leader in this field and the tourism sector as the most relevant. Nevertheless, strong international collaboration was identified in co-authoring studies, underscoring a cooperative approach to solving common urban problems. The most active research area is technological innovation and sustainability, with focus on solutions for urban mobility, quality of life and smart governance. Finally, this work underlines the need to continue exploring the integration of technology in urban development, suggesting an agenda to guide future research to evaluate the sustainability and long-term impacts of smart city initiatives in Latin America. From the policy perspective, smart city initiatives need to be human-centered to boost smart solutions adoption and to guarantee long term local impacts.
Purpose—Quality service plays a significant role in enhancing customer satisfaction and loyalty. The main objective of this research is to investigate the effect of Salalah port service quality on customer satisfaction. Design/methodology/approach—This paper used a quantitative research design. Data were collected from 300 repeated customer of Salalah Port in Oman. Statistical Package (SPSS) version 25.0 was used for analysis of data and adopted to test the hypothesized model. Findings—The research findings confirm the positive influence of the five dimensions of service quality – tangible, empathy, reliability, responsiveness, assurance (TERRA) on customer satisfaction. Originality/value—The findings of this study develop the literature by adding empirical research evidence that the TERRA of Salalah port service quality which have a significant effect on customer satisfaction. The result also provide evidence from the Arab region where the data and research in this region are limited.
This research presents a novel approach utilizing a self-enhanced chimp optimization algorithm (COA) for feature selection in crowdfunding success prediction models, which offers significant improvements over existing methods. By focusing on reducing feature redundancy and improving prediction accuracy, this study introduces an innovative technique that enhances the efficiency of machine learning models used in crowdfunding. The results from this study could have a meaningful impact on how crowdfunding campaigns are designed and evaluated, offering new strategies for creators and investors to increase the likelihood of campaign success in a rapidly evolving digital funding landscape.
Social and environmental issues gain more importance for society that stimulates companies to adopt and integrate more sustainability practices into their business activities. This study is embedded in almost uncovered in the literature context of Russian business that undergoes its ESG transformation in conditions of unprecedented sanctions and hostile institutional environment. The study aims to reveal the role of internal stakeholders (top managers, line managers, and employees) in successful implementation of a company’s ESG practices along various dimensions. Using the primary data from 29 large Russian companies the fsQCA method is applied to identify various configurations of contingencies that stimulate their ESG performance. The analysis results in identification of two alternative core conditions for high ESG performance in Russian companies: high top management commitment to sustainability and low employees’ commitment to sustainability or the employees’ awareness about sustainability. At the end, the study results in two generic profiles composed of top management commitment, line management support, and employees’ awareness, behavior, and commitment towards ESG performance. The results show two different approaches towards ESG transformation that may bring a company to the comparably similar desired outcome. The study has a potential for generalization on a wider scope of emerging market contexts.
Lack of knowledge, attitude, and behavior in managing leftover foods in households impacts the natural ecosystem and food chain, particularly in developing countries. This research aims to analyze appropriate methods for reducing and processing food waste produced in household areas. This research method uses qualitative research with operational research methods carried out for 6 months on 25 housewives in Pondok Labu Village in South Jakarta, Indonesia. The research was carried out in 3 stages, the first stage before the intervention, the second stage providing the intervention, and the third stage after the intervention. Results showed that before the intervention, on average each respondent produced 351 g of food waste each day. This amount decreased to 8.43 g/day after respondents participated in socialization to reduce food waste and training to manage food waste. The concluded that a combination of education and training improves knowledge, attitude, and behavior in household food waste management and helps moderate food waste generation.
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