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.

The Circular Economy is one of the most prominent cross-disciplinary and cross-sectoral concepts to emerge in recent decades. It has permeated academia, policymaking, business, NGOs, and the general public, leading to numerous applications of the concept, some of which only partially overlap. In this article, we review recent debates and research trends in the Circular Economy, outlining the ten most common groups of its conceptualizations using the PRISMA (Preferred Items for Systematic Reviews and Meta-Analysis) method. We then propose a post disciplinary and transnational research program on the Circular Economy that would not only combine hard and soft sciences in unprecedented ways but also have important practical applications, such as developing tools to embed the Circular Economy in natural, technical, economic, and socio-cultural settings.

The urgency of adapting urban areas to the increasing impacts of climate change has prompted the scientific community to seek new approaches in partnership with public entities and civil society organizations. In Malaysia, Penang Island has developed a nature-based urban climate adaptation program (PNBCAP) seeking to increase urban resilience, reduce urban heat and flooding, strengthening social resilience, and build institutional capacity. The project includes a strong knowledge transfer component focused on encouraging other cities in the country to develop and implement adaptation policies, projects, and initiatives. This research develops a model adopting the most efficient processes to accelerate the transfer of knowledge to promote urban adaptation based on the PNBCAP. The methodology is developed based on a review of literature focused on innovation systems and change theories. The integration of success strategies in adaptation contributes to informing the creation of solutions around the alliance of local, state, and national government agencies, scientific institutions, and civil society organizations, in a new framework designated the Malaysian Adaptation Sharing Hub (MASH). MASH is structured in 3-steps and will function as an accelerator for the implementation of urban climate adaptation policies, with the target of creating 2 new adaptation-related policies to be adopted annually by each city member, based on knowledge gathered in the PNBCAP. It is concluded that, to speed up urban adaptation, it is necessary to reinforce and promote the sharing of knowledge resulting from or associated with pilot projects.

Currently, numerous companies intend to adopt digital transformation, seeking agility in their methodologies to reinvent products and services with higher quality, reduced costs and in shorter times. In the Peruvian context, the implementation of this transformation represents a significant challenge due to scarcity of resources, lack of experience and resistance to change. The objective of this research is to propose a digital transformation model that incorporates agile methodologies in order to improve production and competitiveness in manufacturing organizations. In methodological terms, the hypothetical deductive method was used, with a non-experimental cross-sectional design and a quantitative, descriptive and correlational approach. A questionnaire was applied to 110 managers in the manufacturing sector, obtaining a Cronbach’s alpha coefficient of 0.992. The results reveal that 65% of the participants consider that the level of innovation is regular, 88% think that the competition in their companies is of a regular level, and 76% perceive that the level of change is deficient. The findings highlight the importance of digital transformation in manufacturing companies, highlighting the adoption of agile methodologies as crucial to improving processes and productivity. In addition, innovation is essential to developing high-quality products and services, reducing costs and time. Digital transformation with agile methodologies redefines the value proposition, focusing on the customer and improving their digital experience, which differentiates companies in a competitive market.

This study aims to examine how marketing mix and trust theories influence users’ intentions to adopt herbal platform services in Thailand and examine the impact of these intentions on actual service usage, placing a special focus on the integration of technologies in the context. The significant potential for growth in Thailand’s herbal business and the currently underutilized online platforms, it is crucial for stakeholders to understand the determinants of investment intentions. Merging marketing mix and trust theories, this research offers a comprehensive analysis of factors influencing the use of herbal platform, highlighting the relevance of herbal in enhancing service adoption. This study utilized a quantitative approach, gathering data through online surveys from 416 users of online herbal platforms in Thailand using SEM to examine the impact of gender on consumers’ decisions to use these platforms. This study provides insights into effective business strategies for herbal companies and contributes novel perspectives to the literature on herbal services. It specifically examines cognitive and emotional trust impacts and explores gender dynamics within the context of Health development. The study clarifies the roles of these factors and assesses the impact of gender on platform adoption, highlighting the importance of m-Health services in facilitating this process. Enhancing user engagement with herbal platform services requires prioritizing influential determinants, streamlining the investment experience, and underscoring the sector’s contribution to economic revitalization. Authorities should prioritize simplifying the investment landscape and initiating advocacy campaigns, while platform developers are advised to improve the user experience, bolster educational efforts, and heighten awareness of the investment advantages within the herbal industry. This research provides stakeholders with insights into the factors that enhance Thais’ engagement with herbal market platforms, especially via online channels. Identifying these key drivers is anticipated to boost participation in the herbal market, thereby contributing positively to Thailand’s economy.

This study aims at analyzing the consumers’ perception towards online purchasing bakery goods on subjective norm (SN), computer self-efficacy (CSE), and technology acceptance model (TAM). Convenience sampling was used and the final sample of respondents was made of 344 participants, with an effective recovery rate of 96%, who bought bakery goods on the LINE social platform in Nantou County. Descriptive statistics, confirmatory factor analysis, and SEM structural equation model were used to test the research hypothesis. The results show that after adding external variables to the technology acceptance model (TAM), the application of purchasing bakery goods online is significant; the consumers’ behavior of purchasing bakery goods online, subjective norm (SN), computer self-efficacy (CSE), and technology acceptance model (TAM) have cause-and-effect relationships. This research concludes that it is easy, helpful, and worthy to use the Internet to buy bakery goods.