Today urban development lacks ecological foundations in many cities of Turkey. The purpose of this study is to reveal the relationship between urban green spaces and ecological zones in the sample of Aksaray/Turkey. In this study, a study design has been created to improve the urban ecological infrastructure and to associate the green space network with the ecological zones. This design is divided into four parts as data processing, landscape pattern of urban green spaces, analysis of the spatial boundaries of urban natural ecological zones, and determination of the importance of spatial regions by overlaying two different stratified analyses. This study proposes a methodological framework that can be integrated into efforts to identify ecological zones to increase the sustainability of urban ecology and green space quality. One potential limitation of the proposed methodology can be the lack of consensus and enthusiasm among the administrative actors regarding the issue. Therefore, it is recommended that the administrative bodies should be correctly informed by the relevant scholars and practitioners who are working on the subject.

Outsourcing logistics operations is a common trend as businesses prioritize core activities. Establishing a sustainable partnership between businesses and logistics service providers requires a systematic approach. This study is needed to develop a more effective and adaptive framework for logistics service provider selection by integrating diverse criteria and decision-making methodologies, ultimately enhancing the precision and sustainability of procurement processes. This study advocate for leveraging industry-based knowledge in procurement, emphasizing the need to define decision-making elements. The research analyzes nearly 300 logistics procurement projects, using a neural network-based methodology to propose a model that aids businesses in identifying optimal criteria for evaluating logistics service providers based on extensive industry knowledge. The goal of this study is to develop and test a practical model that would support businesses in choosing most suitable criteria for selection of logistics service providers based on cumulative market patterns. The results of this study are as follows. It introduces novel elements by gathering and systematizing unique market data using developed data processing methodology. It innovatively classifies decision-making elements, allocating them into distinct groups for use as features in a neural network. The study further contributes by developing and training a predictive model based on a prepared dataset, addressing pre-defined goals, expectations related to green logistics, and specific requirements in the tendering process for selecting logistics service providers. Study is concluded by summarizing suggestions for future research in area of adopting neural networks for selection of logistics service providers.

As autonomous vehicles (AVs) revolutionize the global transportation landscape, their implications for emerging economies like Malaysia remain a subject of significant interest. This study delves into the multifaceted world of AV technology, focusing on Malaysia’s unique transportation challenges and opportunities. Through interviews with key stakeholders and experts, the research uncovers valuable insights into AV technology’s awareness, regulatory landscape, integration hurdles, potential benefits, and inclusivity impact in the Malaysian context. The study finds that while AVs hold the promise of improved road safety, reduced traffic congestion, and enhanced environmental sustainability, addressing challenges related to regulation, infrastructure, and public acceptance is imperative for successful integration. Additionally, AV technology has the potential to significantly enhance inclusivity in transportation, benefiting individuals with disabilities. The study underscores the need for holistic policy and infrastructure development to leverage the benefits of AV technology and pave the way for a sustainable and inclusive transportation future in Malaysia.

To better analyze the tourist experience of the Jinsha Site Museum, this study adopts a mixed research method, combined with questionnaire surveys, interviews, and online review data, to comprehensively analyze the tourist experience from three dimensions: cognition, emotion, and behavior. After statistical analysis of 223 questionnaire surveys and analysis of 530 online comments, it was found that tourists’ overall satisfaction with the Jinsha Site Museum reached 95.3%. In the feedback on interactive exhibitions, 63.8% of tourists hoped to add more interactive elements and technological applications. The above results indicate that the Jinsha Site Museum has been widely recognized by tourists in providing historical and cultural exhibitions and modern facility services. However, to meet the needs of more tourists, museums should consider innovating and upgrading in interactive exhibitions, adding technological interactive elements, and improving the usability and responsiveness of equipment.

Spiritual Intelligence (SI) has become a key contributor towards enhancing employee well-being and job satisfaction (JS) in the modern competitive business world. This study examines the impact of SI on JS among Sri Lankan IT professionals, considering gender’s role in this relationship. Analyzing data from 383 respondents using Partial Least Square Structural Equation Modeling (PLS-SEM), the study reveals a strong positive correlation between SI and JS, with no moderating effect on gender. The study highlights the importance of embedding SI into HR and organizational policies to enhance workforce resilience and retention while contributing to broader industry development and global competitiveness in the IT sector.

It is important for society to know the actions implemented by companies in the construction sector to reduce the environmental pollution generated by this industry and to contribute to the solution of economic and social problems in their environment; however, the variables that allow identifying their contributions and impacts are not known. Based on this problem, the study focuses on identifying the factors that influence sustainability management within the construction sector in Colombia. The research presents a predictive approach and uses a quantitative methodology, applying statistical modeling techniques. The sample corresponds to 84 Colombian companies. As a result, a system of equations of the form y=mx+b is presented to describe the deviation of the environmental, economic, social, compensation measures, management, indicators and sustainability reports. The analysis of the intersections constitutes a projective tool to evaluate the relationships and balance points between the dimensions analyzed, helping to identify strengths and opportunities for improvement.