This study aims to explore research and to identify research clusters on sustainable development by using bibliometric analysis. The sustainable development field is examined using the selected research articles. A co-citation unit is used to analyze the relationship between cited documents, and then science mapping is used to identify clusters in this relationship. The results show that there are four main distinct clusters, of which the most important concerns sustainable supply chains and logistics management. This cluster is then classified into five bunches of knowledge sources. These bunches illustrate the need for a trend in sustainability issues that includes a social dimension to balance economic and environmental dimensions for long-term development. There are logistics management and lean concepts that can be applied to sustainable development to move toward business sustainability. The future direction of sustainable business concerns economic values, environmental policy and stakeholder engagement for business opportunities. The contribution of this article is to identify trends in sustainable development by means of bibliometric analysis, to develop research in the future.

Sustainable development is of growing importance to the agriculture sector because the current lacking utilization of resources and energy usage, together with the pollution generated from toxic chemicals, cannot continue at present rates. Sustainability in agriculture can be achieved through using less (or no) poisonous chemicals, saving natural resources, and reducing greenhouse gas emissions. Technology applications could help farmers to use proper data in decision-making, which leads to low-input agriculture. This work focuses on the role of smart technology implementation in sustainable agriculture. The effects of smart technology implementation are analyzed by using a case study approach. The results show that the plant factory using intelligence technology enhances sustainability performance by increasing production productivity, product quality, crop per year, resource use efficiency, and food safety, as well as improving employees’ quality of life.

Industry 4.0 revolution offers smart manufacturing; it systematically incorporates production technology and advanced operation management. Adopting these high-state strategies can increase production efficiency, reduce energy consumption, and decrease manufacturer costs. Simultaneously, small and medium-sized enterprises (SMEs) were the backbone of economic growth and development. They still lack both the knowledge and decision-making to verify this high-stage technology’s performance and implementation. Therefore, the research aims to define the readiness indicators to assess and support SMEs toward Industry 4.0. The research begins with found aspects that influence the SME 4.0 readiness by using Bibliometric techniques. The result shows the aspects which were the most occurrences such as the Industrial Internet, Cloud Manufacturing, Collaborative Robot, Business Model, and Digital Transformation. They were then grouped into five dimensions by using the visualization of similarities (VOS) techniques: (1) Organizational Resilience, (2) Infrastructure System, (3) Manufacturing System, (4) Data Transformation, and (5) Digital Technology. Cronbach’s alpha then validated the composite dimensions at a 0.926 level of reliability and a significant positive correlation. After that, the indicators were defined from the dimension and aspects approach. Finally, the indicators were pilot tested by small enterprises. It appeared that 23 indicators could support SMEs 4.0 readiness indication and decision-making in the context of Industry 4.0.

Abstract:In this work, operational performance in the green supply chain management (SCM) of the Thai auto parts industry was investigated. A green supply chain performance measurement (GSPM) model was developed from the combination of various concepts including an SCM logistics scorecard, a supply chain operations reference model, a balance scorecard, and green supply chain management. The GSPM has been designed for use as a self-evaluation tool focusing on five decisive areas, or factors, and 28 sub-factors. A factor analysis was conducted using the survey results of the GSPM in order to identify significant factors that represent the green supply chain operation performance. Grouped as three major factors, namely green procurement, green transportation, and green manufacturing; reverse logistics and eco-design; and reuse and recycle of manufacturing, their significance and impact on the auto parts industry in Thailand were highlighted. Specifically, the factor of green procurement, green transportation, and green manufacturing, as major factor 1, in relation with the factor of reverse logistics and eco-design, as major factor 2, were found to have a strong positive relationship with the asset turnover ratio.

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