Supply chain sustainability risk assessment model using integration of the preference selection index (PSI) and the Shannon entropy

Sutrisno, Agung; Kumar, Vikas

doi:10.1108/ijqrm-06-2021-0191

Cited by 15 publications

(3 citation statements)

References 136 publications

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“…Metode ini berguna bila ada konflik dalam memutuskan kepentingan relatif antar atribut (Maniya and Bhatt, 2010). Metode ini efektif secara khusus jika ditemukan konflik dalam memutuskan kepentingan relatif antara atribut (Sutrisno and Kumar, 2023) dan itu menjadi keunggulan dari metode PSI (Luan and Phu, 2021). Pada metode PSI, hasil yang diperoleh dengan perhitungan minimal dan sederhana seperti apa adanya berdasarkan konsep statistik tanpa keharusan bobot atribut (Syahputra et al, 2018).…”

Section: Tinjauan Literaturunclassified

Efektifitas Metode Preference Selection Index (PSI) dalam Menentukan Penyaluran Dana Bantuan Sosial COVID-19 pada Kecamatan Mandau

Radillah,

Fauzansyah,

Widodo

et al. 2023

JTIIK

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COVID-19 merupakan pandemi global yang penyebarannya sangat cepat, termasuk di Indonesia. Untuk memulihkan perekonomian di tengah kondisi pandemi ini, pemerintah berupaya memberikan dana bantuan sosial (bansos) COVID-19 disetiap kecamatan di berbagai wilayah, termasuk Kecamatan Mandau di Kota Duri seperti bantuan bahan pokok makanan. Namun dalam pelaksanaannya terdapat kendala dalam penyaluran dana bantuan sosial tersebut karena data yang diterima oleh petugas kecamatan masih menggunakan sistem pencatatan manual sehingga pendataan penerima bantuan tidak akurat dan tidak memiliki acuan kriteria persyaratan sebagai penerima bantuan, yang menyebabkan penerima bantuan sosial tidak tepat sasaran. Dalam penelitian ini, untuk mengatasi masalah tersebut telah dirancang analisa perhitungan berbasis website dengan menggunakan metode Preference Selection Index (PSI) yang mampu mengklasifikasikan penerima bantuan sesuai kriteria yang diharapkan. Hasil dari penerapan metode PSI kedalam aplikasi berbasis web ini memberikan kemudahan bagi calon penerima bantuan untuk mendaftar secara online, dan untuk proses penyaluran bantuan sosial menjadi lebih mudah, transparan, dan tepat sasaran. dengan kriteria data yang akurat dengan skala prioritas pengurutan secara descending untuk nilai tertinggi yaitu 0.883, dan hasil nilai terendah atau non prioritas yaitu 0.322. Abstract COVID-19 is a global pandemic with rapid spread, including in Indonesia. To restore the economy amid this pandemic, the government is trying to provide COVID-19 social assistance funds in every sub-district in various regions, including Mandau District in Duri City, such as assistance with staple foods. However, in practice there are obstacles in the distribution of social assistance funds because the data received by sub-district officials still uses a manual recording system so that the data collection on beneficiaries is inaccurate and does not have a reference to the eligibility criteria as beneficiaries, which causes social assistance recipients to be not on target. In this study, to overcome this problem a website-based calculation analysis has been designed using the Preference Selection Index (PSI) method that can classify the beneficiaries according to the expected criteria, and after this calculation analysis is implemented in this sub-district, the social assistance distribution process becomes easier and on target with accurate criteria.

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Section: Tinjauan Literaturunclassified

Efektifitas Metode Preference Selection Index (PSI) dalam Menentukan Penyaluran Dana Bantuan Sosial COVID-19 pada Kecamatan Mandau

Radillah,

Fauzansyah,

Widodo

et al. 2023

JTIIK

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“…Scientific publications address the issue of SRM mainly in relation to sustainable SC development (Giannakis & Papadopoulos, 2016;Ocicka & Turek, 2021;Sutrisno & Kumar, 2022), product development process (Palousis et al, 2010), or project management process (Bai et al, 2017). The currently avail-able literature, therefore, does not cover many relevant issues, i.e.…”

Section: Literature Reviewmentioning

confidence: 99%

Industry 4.0 technologies as enablers of sustainability risk management

Ocicka

Rogowski²,

Turek³

2022

EiP

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Motivation: Companies operate in a volatile, uncertain, complex, and ambiguous (VUCA) business environment, as evidenced by massive collapses in commodity prices, acts of terrorism, cyber security threats, natural disasters, technological failures, and pandemics. Numerous reports indicate that the top risks with the highest probability of occurrence in the next decade include extreme weather events, failure of climate protection measures, and man-made environmental damage (The Global Risk Report 2021 of the World Economic Forum, The World Business Council for Sustainable Development report and many others). The UN Sustainable Development Goals (SDGs) cover the above challenges and define the agenda for solving them to 2030. The intensification of environmental and social risks reinforces the need to deepen research and explore new ways of managing sustainability risks (SRs). At the same time, businesses are undergoing the technology transformation (Industry 4.0) accelerated by the COVID-19 pandemic. It became necessary to shift some investment to this business area, which also needs to be supported by additional capital. The technology-driven transformation can significantly support companies in managing SRs. Aim: The aim of the study is to diagnose the importance of investments in Industry 4.0 technologies (T4.0) as potential enablers supporting sustainability risk management from the perspective of supply chains. Results: SRs represent one of the critical risk areas of the 21st century. Despite the well-recognized potential of the T4.0 implementation for sustainable supply chain management, the research studies concentrated on their potential role within SR management in international supply chains are limited and fragmented. The diagnosis of the growing importance of T4.0 supporting risk management at strategic and operational levels of business activities implies the recommendation to integrate their use in this area into the technological transformation, and then consistently into planning and financing of development and implementation projects. Companies may attempt to address these challenges through Environmental, Social, and Governance (ESG) initiatives.

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“…, 2013). To overcome,To overcome, researchers try to explore by embracing unconventional approaches that work better with imprecise information and answer the (uncertainty part) of risk (Sutrisno and Kumar, 2023; Meybodi, 2021). …”

Section: Introductionmentioning

confidence: 99%

Supply chain risk prioritization: a multi-criteria based Intuitionistic Fuzzy TOPSIS approach

Mukherjee,

De,

Roy

2024

IJQRM

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Purpose Identifying and prioritizing supply chain risk is significant from any product’s quality and reliability perspective. Under an input-process-output workflow, conventional risk prioritization uses a risk priority number (RPN) aligned to the risk analysis. Imprecise information coupled with a lack of dealing with hesitancy margins enlarges the scope, leading to improper assessment of risks. This significantly affects monitoring quality and performance. Against the backdrop, a methodology that identifies and prioritizes the operational supply chain risk factors signifies better risk assessment.Design/methodology/approach The study proposes a multi-criteria model for risk prioritization involving multiple decision-makers (DMs). The methodology offers a robust, hybrid system based on the Intuitionistic Fuzzy (IF) Set merged with the “Technique for Order Performance by Similarity to Ideal Solution.” The nature of the model is robust. The same is shown by applying fuzzy concepts under multi-criteria decision-making (MCDM) to prioritize the identified business risks for better assessment.Findings The proposed IF Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) for risk prioritization model can improve the decisions within organizations that make up the chains, thus guaranteeing a “better quality in risk management.” Establishing an efficient representation of uncertain information related to traditional failure mode and effects analysis (FMEA) treatment involving multiple DMs means identifying potential risks in advance and providing better supply chain control.Research limitations/implications In a company’s supply chain, blockchain allows data storage and transparent transmission of flows with traceability, privacy, security and transparency (Roy et al., 2022). They asserted that blockchain technology has great potential for traceability. Since risk assessment in supply chain operations can be treated as a traceability problem, further research is needed to use blockchain technologies. Lastly, issues like risk will be better assessed if predicted well; further research demands the suitability of applying predictive analysis on risk.Practical implications The study proposes a hybrid framework based on the generic risk assessment and MCDM methodologies under a fuzzy environment system. By this, the authors try to address the supply chain risk assessment and mitigation framework better than the conventional one. To the best of their knowledge, no study is found in existing literature attempting to explore the efficacy of the proposed hybrid approach over the traditional RPN system in prime sectors like steel (with production planning data). The validation experiment indicates the effectiveness of the results obtained from the proposed IF TOPSIS Approach to Risk Prioritization methodology is more practical and resembles the actual scenario compared to those obtained using the traditional RPN system (Kim et al., 2018; Kumar et al., 2018).Originality/value This study provides mathematical models to simulate the supply chain risk assessment, thus helping the manufacturer rank the risk level. In the end, the authors apply this model in a big-sized organization to validate its accuracy. The authors validate the proposed approach to an integrated steel plant impacting the production planning process. The model’s outcome substantially adds value to the current risk assessment and prioritization, significantly affecting better risk management quality.

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Supply chain sustainability risk assessment model using integration of the preference selection index (PSI) and the Shannon entropy

Cited by 15 publications

References 136 publications

Efektifitas Metode Preference Selection Index (PSI) dalam Menentukan Penyaluran Dana Bantuan Sosial COVID-19 pada Kecamatan Mandau

Efektifitas Metode Preference Selection Index (PSI) dalam Menentukan Penyaluran Dana Bantuan Sosial COVID-19 pada Kecamatan Mandau

Industry 4.0 technologies as enablers of sustainability risk management

Supply chain risk prioritization: a multi-criteria based Intuitionistic Fuzzy TOPSIS approach

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