The Design and Development of a Causal Bayesian Networks Model for the Explanation of Agricultural Supply Chains

Kliangkhlao, Mallika; Limsiroratana, Somchai; Sahoh, Bukhoree

doi:10.1109/access.2022.3199353

Cited by 4 publications

(2 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, looking at other social aspects (entrepreneurial aspects), the results of empirical research have found positive and prospective phenomena such as innovative work behavior, the need for achievement, and the courage to bear risks, as reflected in the emergence of the fiberglass shipbuilding business groups in Manna District, Bengkulu Selatan Regency. There are 2 important implications resulting from the emergence of an entrepreneurial spirit in this fishing community, including: (1) if this entrepreneurial spirit is empowered consistently, then gradually (due to the trickle-down effect) in the future it will become a form of entrepreneurship that can be developed into a large-scale fiberglass fishing boat industry; and (2) demanding market research (about the interaction between the supply side and the demand side) seriously and consistently (Kliangkhlao et al, 2022;Grymak, 2018).…”

Section: Socio-economic and Entrepreneurial Analysis Of The Developme...mentioning

confidence: 99%

“…Judging from the economic advantages (cost efficiency), the important urgency of this fiberglass-based ship is seen from its ability to increase its product offerings based on increasing market demand, especially demand from small fishing communities. Another economic advantage (especially in the form of entrepreneurship) is the advantage seen from the impact of fiberglass boat innovation on improving performance through increasing the workability of fishermen (Kliangkhlao et al, 2022;Apriliani et al, 2020;Suardi, 2018).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Innovation in Fiberglass Ship Assembly: Social-Economic and Entrepreneurship Study of Coastal Communities

Ridwan,

Novi Yarsah

2024

J. AGRISEP: Kaj. Mas. Sos. Ek. Pert. n. Agr.

View full text Add to dashboard Cite

The problem of low performance of fishing communities in producing capture fisheries is generally related to the low quality of the capital ships used. This research aims to reveal the factors that caused the emergence of innovation in the business of assembling fiberglass fishing ships, the level of business development, and its impact on improving the socio-economic performance of fishing communities in rural areas. The research sample included small fishing communities and a group of fishermen who had built a business assembling fiberglass fishing ships in Bengkulu Selatan Regency. Because the data collected is mostly in the form of qualitative data, the analysis method used is a descriptive-qualitative method supported by statistical analysis methods. The results indicate that the emergence of innovation in assembling fiberglass fishing ships is driven by evidence highlighting the superior quality of fiberglass over wood in ship construction. The growth of the fiberglass ship assembly business is evident through its expanding market reach and increased sales turnover. Qualitatively, the study demonstrates that the innovation in assembling fiberglass ships has a positive impact on the socio-economic performance of fishermen, manifested through improved workability, heightened work motivation, and increased capture fisheries production. Three key recommendations emerge from the findings: (1) Stakeholders should consistently support the sustainability of fiberglass ship assembly businesses; (2) Relevant agencies are encouraged to actively contribute to the substantial development of the fiberglass ship assembly sector; and (3) Fishing communities greatly benefit from socialization, empowerment, literacy, and education programs.

show abstract

Section: Socio-economic and Entrepreneurial Analysis Of The Developme...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Innovation in Fiberglass Ship Assembly: Social-Economic and Entrepreneurship Study of Coastal Communities

Ridwan,

Novi Yarsah

2024

J. AGRISEP: Kaj. Mas. Sos. Ek. Pert. n. Agr.

View full text Add to dashboard Cite

show abstract

Artificial intelligence in supply chain decision-making: an environmental, social, and governance triggering and technological inhibiting protocol

Hao

Demir

2023

JM2

View full text Add to dashboard Cite

Purpose Decision-making, reinforced by artificial intelligence (AI), is predicted to become potent tool within the domain of supply chain management. Considering the importance of this subject, the purpose of this study is to explore the triggers and technological inhibitors affecting the adoption of AI. This study also aims to identify three-dimensional triggers, notably those linked to environmental, social, and governance (ESG), as well as technological inhibitors. Design/methodology/approach Drawing upon a six-step systematic review following the preferred reporting items for systematic reviews and meta analysis (PRISMA) guidelines, a broad range of journal publications was recognized, with a thematic analysis under the lens of the ESG framework, offering a unique perspective on factors triggering and inhibiting AI adoption in the supply chain. Findings In the environmental dimension, triggers include product waste reduction and greenhouse gas emissions reduction, highlighting the potential of AI in promoting sustainability and environmental responsibility. In the social dimension, triggers encompass product security and quality, as well as social well-being, indicating how AI can contribute to ensuring safe and high-quality products and enhancing societal welfare. In the governance dimension, triggers involve agile and lean practices, cost reduction, sustainable supplier selection, circular economy initiatives, supply chain risk management, knowledge sharing and the synergy between supply and demand. The inhibitors in the technological category present challenges, encompassing the lack of regulations and rules, data security and privacy concerns, responsible and ethical AI considerations, performance and ethical assessment difficulties, poor data quality, group bias and the need to achieve synergy between AI and human decision-makers. Research limitations/implications Despite the use of PRISMA guidelines to ensure a comprehensive search and screening process, it is possible that some relevant studies in other databases and industry reports may have been missed. In light of this, the selected studies may not have fully captured the diversity of triggers and technological inhibitors. The extraction of themes from the selected papers is subjective in nature and relies on the interpretation of researchers, which may introduce bias. Originality/value The research contributes to the field by conducting a comprehensive analysis of the diverse factors that trigger or inhibit AI adoption, providing valuable insights into their impact. By incorporating the ESG protocol, the study offers a holistic evaluation of the dimensions associated with AI adoption in the supply chain, presenting valuable implications for both industry professionals and researchers. The originality lies in its in-depth examination of the multifaceted aspects of AI adoption, making it a valuable resource for advancing knowledge in this area.

show abstract

Management of Shipment Content using Novel Practices of Supply Chain Management and Big Data Analytics

Rathor¹,

Mandawat

Pandya

et al. 2022

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)

View full text Add to dashboard Cite

The Design and Development of a Causal Bayesian Networks Model for the Explanation of Agricultural Supply Chains

Cited by 4 publications

References 40 publications

Innovation in Fiberglass Ship Assembly: Social-Economic and Entrepreneurship Study of Coastal Communities

Innovation in Fiberglass Ship Assembly: Social-Economic and Entrepreneurship Study of Coastal Communities

Artificial intelligence in supply chain decision-making: an environmental, social, and governance triggering and technological inhibiting protocol

Management of Shipment Content using Novel Practices of Supply Chain Management and Big Data Analytics

Contact Info

Product

Resources

About