A Review of Supply Chain Data Mining Publications

The use of data mining in supply chains is growing, and covers almost all aspects of supply chain management. A framework of supply chain analytics is used to classify data mining publications reported in supply chain management academic literature. Scholarly articles were identified using SCOPUS and EBSCO Business search engines. Articles were classified by supply chain function. Additional papers reflecting technology, to include RFID use and text analysis were separately reviewed. The paper concludes with discussion of potential research issues and outlook for future development

IMPLEMENTASI GREY FORECASTING MODEL GM (1,1) DAN GM (1,N) UNTUK SISTEM PRAKIRAAN JUMLAH TANGKAPAN IKAN

Meningkatnya kebutuhan ikan menimbulkan permasalahan yang berkaitan dengan jumlah tangkapan ikan di sektor perikanan. Dalam jumlah tangkapan ikan, walaupun semua informasi yang berhubungan dengan area tangkap sudah dikenal dengan tepat, tapi tidak mudah untuk memprakirakan jumlah tangkapan ikan karena informasi yang tidak jelas. Hal ini berkaitan pula dengan jumlah kapal yang melakukan trip, lama (waktu) trip, jenis alat tangkap yang digunakan, kondisi cuaca, kualitas SDM, faktor lingkungan alam, dan lain-lain. Tujuan dari penelitian ini adalah menerapkan grey forecasting model GM (1,1) dan GM (1,N) untuk memprakirakan hasil jumlah tangkapan ikan. Grey forecasting model digunakan untuk membangun model prakiraan dengan jumlah data terbatas dengan prakiraan jangka pendek akan menghasilkan prakiraan yang akurat. Penelitian ini menggunakan data bulanan jumlah tangkapan ikan dan tinggi gelombang tahun 2016 sampai 2018 untuk dilakukan analisa perhitungan menggunakan model GM (1,1) dan GM (1,N). Penelitian dilakukan dengan 2 percobaan yaitu dengan data seri waktu sebanyak 36 data dan 12 data (1 tahun dibuat 4 periode).Hasil penelitian menunjukkan bahwa model GM (1,1) memiliki akurasi lebih tinggi dibandingkan dengan model GM (1,N), dengan MAPE pada model GM (1,1) sebesar 26% pada percobaan dengan 36 data dan 12% pada percobaan dengan 12 data, sedangkan MAPE pada model GM (1,N) sebesar 51% pada percobaan dengan 36 data dan 27% pada percobaan dengan 12 data maka dapat dikatakan bahwa semakin panjang data yang digunakan semakin besar nilai kesalahan prakiraan. Selain itu, performa variabel tinggi gelombang yang digunakan pada model GM (1,N) termasuk dalam kategori mempengaruhi hasil akhir dari nilai prakiraan. Kata kunci : Grey forecasting model, GM (1,1), GM (1,N), Prakiraan, Jumlah tangkapan ikan. The increasing need for fish causes problems related to number of fish catches in the fisheries sector. In fish catches amount, all information related to fishing ground is well known, but on the other hand it is not easy to predict the number of fish catches due to unclear information. This is also related to the number of ships that make trips, the length (time) of the trip, the type of fishing gear, weather conditions, the quality of human resources, natural environmental factors, and others. The purpose of this study is to apply grey forecasting model GM (1.1) and GM (1.N) to forecast the number of fish catches. Grey forecasting models are used to build forecast models with limited amounts of data with short-term forecasts that will produce accurate forecasts. This study employs the data on monthly number of fish catches and wave height in the year of 2016 to 2018 to analyze calculations using the GM (1.1) and GM (1.N) models. The study was conducted with 2 experiments, namely 36 time series data and 12 time series data (1 year made 4 periods). The result showed that the GM (1.1) model had higher accuracy compared to the GM (1.N) model, with a MAPE on the GM (1.1) model of 26% in the experiment with 36 data and 12% in the experiment with 12 data, while the MAPE on the GM (1.N) model of 51% in the experiment with 36 data and 27% in the experiment with 12 data then it can be said that the getting the length of data are used the greater value of forecast error.In addition, the performance of wave height variable are used in the GM (1.N) model falls into the category of influencing the final output of the forecast value. Keywords : Grey forecasting model, GM (1.1), GM (1.N), Fish catches amount, Forecas

Disruptive and Conventional Technologies for the Support of Logistics Processes: A Literature Review

The supply chain has become a key element of increasing the productivity and competitiveness of companies. To achieve this, it is essential to implement a strategy based on the use of technologies, which depends on knowledge of the scope and impact of logistics technologies. Therefore, this article aims to identify the main technologies supporting logistics management and supply chain processes to establish their functionality, scope, and impacts. For this, conventional technologies and technologies framed by the concept of Industry 4.0 that allow the implementation of Logistics 4.0 in companies are analyzed. As a result of searching databases such as Scopus, Web of Science, and Science Direct, we provide an analysis of 18 technologies focusing on their definition, scope, and the logistics processes involved. This study concludes that technologies in logistics management allow for a reduction in total costs, improve collaboration with suppliers and customers, increase the visibility and traceability of products and information, and support decision-making for all agents in the supply chain, including the final consumer

Reducing edible food waste in the UK food manufacturing supply chain through collaboration

A thesis submitted to the University of Bedfordshire, in fulfilment of the requirements for the degree of Master of Philosophy.The aim of this study is to examine the relationship between food manufacturing supply chain (FMSC) collaboration, collaborative effectiveness and edible food waste (EF) waste reduction; and also identify the key dimensions of collaboration and collaborative effectiveness in the context of the FMSC. A conceptual framework was built based on thorough relevant literature review and theory. Then all items of the conceptual framework were revised by academics and practitioners. The model was empirically tested with survey data using 122 responses from food manufacturing firms, using PLS-SEM. The findings indicated that the structural paths support hypotheses that FMSC collaboration has a positive effect related to collaborative effectiveness, and collaborative effectiveness has a strong contribution in EF waste (over-production of EF waste, processing of EF waste and storage of EF waste) reduction. However, the direct impact of FMSC collaboration on EF waste (over-production of EF waste, processing of EF waste and storage of EF waste) reduction is insignificant. A mediation analysis showed that the relationship between FMSC collaboration and EF waste is fully mediated by collaborative effectiveness. This research brought relational view theory for the concept of FMSC collaboration and collaborative effectiveness into the FMSC context, which has not previously been done, and developed and validated those constructs and relationships. The UK FMSC members would benefit from applying all dimensions of FMSC collaboration in this study to their supply chain operation to achieve greater collaborative effectiveness, and that will lead to reducing EF waste

Strategies to Mitigate Supply Chain Disruptions in Grocery Businesses

Supply chains have become more complex in the global economy, which has made supply chain disruptions inevitable. Disruptions can cause loss of profitability and hinder business growth. The goal of this multiple case study was to explore strategies to mitigate the effects of disruption in grocery store supply chains. The conceptual framework for this study was the resource dependency theory, which stipulates that firms rely on other businesses in the external environment for critical resources to create a competitive edge. Four purposively selected participants from 4 grocery store businesses in Northwest Arkansas participated in semistructured interviews and provided organizational documentation for this study. The participants were supply chain managers who had knowledge about disruptions and had successfully mitigated disruptions in their grocery stores\u27 supply chains. Yin\u27s 5-step process was used to analyze data, which involved compiling the database, disassembling data, reassembling data, interpreting data, and making a conclusion. Four themes emerged from the data analysis: supply chain partners\u27 collaboration, multiple supply base and supplier qualification, inventory management, and information technology and communication. The uninterrupted flow of grocery merchandise to the community could result in a positive social change by helping to ensure that community members have timely access to food

Data supply chain (DSC): Research synthesis and future directions

In the digital economy, the volume, variety and availability of data produced in myriad forms from a diversity of sources has become an important resource for competitive advantage, innovation opportunity as well as source of new management challenges. Building on the theoretical and empirical foundations of the traditional manufacturing Supply Chain (SC), which describes the flow of physical artefacts as raw materials through to consumption, we propose the Data Supply Chain (DSC) along which data are the primary artefact flowing. The purpose of this paper is to outline the characteristics and bring conceptual distinctiveness to the context around DSC as well as to explore the associated and emergent management challenges and innovation opportunities. To achieve this, we adopt the systematic review methodology drawing on the operations management and supply chain literature and, in particular, taking a framework synthetic approach which allows us to build the DSC concept from the preexisting SC template. We conclude the paper by developing a set of propositions and outlining an agenda for future research that the DSC concept implies

Blockchain technology to improve supply chain management - a systematic literature review

This study followed the systematic literature review approach to analyse how blockchain technology can improve supply chain management and to promote a future research agenda. The search was carried out at Web of Science Core Collection between September 2019 and February 2020 by using the keywords “blockchain” AND “supply chain” OR “blockchain” AND “logistics” in the title. In this review 127 studies were identified for screening and a final sample of 67 studies met the inclusion criteria and were analysed to answer the research questions. After examining the selected studies, our findings uncover a range of approaches showing how blockchain can enhance the supply chain management and point out which sectors are most likely to benefit from its implementation. This study contributes to the existing literature by systematising the most relevant information on blockchain implementation in supply chains. In addition, the findings of this study also provide managers and researchers with insights about the likely consequences of blockchain adoption in various sectors. Although there are already some literature reviews on blockchain technology in the supply chain management, this is one of the first studies that brings together the main issues focused on the consequences of blockchain adoption in the supply chain management.A gestão da cadeia de abastecimento está a passar por um processo de digitalização das suas operações justificada pela Quarta Revolução Industrial (Indústria 4.0) que prevê a adoção de novas tecnologias com o objetivo de reduzir custos operacionais, aumentar a eficiência da cadeia de abastecimento e agregar valor aos produtos e serviços. Ferramentas tecnológicas como a internet das coisas (IoT), identificação por radiofrequência (RFID) e Big Data, estão a ser utilizadas na melhoria dos controlos de produção, compra, procura, na tomadas de decisões dos gestores, entretanto, a recente tecnologia blockchain tem chamado atenção de pesquisadores e especialistas devido ao seu potencial transformador nos negócios e principalmente na gestão da cadeia de abastecimento. Por este motivo, este estudo propõe uma revisão sistemática de literatura com o objetivo de analisar como a tecnologia blockchain pode melhorar a gestão da cadeia de abastecimento e propor uma agenda de investigação para o futuro. A pesquisa foi realizada na base de dados Web of Science Core Collection entre setembro de 2019 e fevereiro de 2020 usando as palavras-chave "blockchain" E "supply chain" OU "blockchain" E "logistics" no título. O critério de seleção dos artigos considerou apenas estudos revistos por pares, anais de conferência e livros nos idiomas inglês, espanhol, francês e português. A seleção dos estudos ocorreu em duas etapas. Na primeira etapa, foram analisados títulos e resumos. Na segunda etapa, foi realizada a leitura integral dos estudos que não foram excluídos na primeira fase. Os critérios de exclusão foram: artigos de revisão de literatura, relatórios, estudos focados em informações técnicas, estudos que enfatizaram outras tecnologias (IoT, RFID), gestão financeira da cadeia de abastecimento e/ou estudos relacionados com bitcoins. Os artigos que preencheram um desses critérios foram excluídos com justificativa. Embora tenhamos excluído artigos de revisão de literatura, esses documentos ainda foram utilizados para identificar estudos-chave que não haviam sido capturados da base de dados Web of Science. Por fim, nesta revisão foram identificados 127 estudos para triagem e uma amostra final de 67 estudos atendeu aos critérios de inclusão e foram analisados para responder às perguntas da pesquisa. As perguntas a que a pesquisa teve por objetivo responder foram: quais os benefícios e riscos da tecnologia blockchain; quais os setores que já adotaram a tecnologia blockchain na gestão da cadeia de abastecimento e sua fase de implementação; quais as características das empresas que utilizam a tecnologia; quais são os fatores facilitadores e barreiras para a adoção da tecnologia blockchain nas empresas; qual a influência da tecnologia blockchain na garantia da sustentabilidade da cadeia de abastecimento dentro da estratégia organizacional e dos níveis operacionais; como avaliar o desempenho da tecnologia blockchain na gestão da cadeia de abastecimento. Os estudos selecionados apontam que a partir de 2017 houve um aumento expressivo de estudos relacionados ao uso da tecnologia blockchain na cadeia de abastecimento. Os Estados Unidos, China e Índia são os países com a maior percentagem de publicações sobre o tema e representam aproximadamente 44% do total. Os estudos foram publicados em jornais especializados em sistema de produção e processos, engenharia industrial, tecnologia, gestão, logística, cadeia de abastecimento e sustentabilidade. Quanto aos benefícios e riscos da adoção da tecnologia blockchain, os estudos indicam que a transparência dos dados, rastreabilidade e a redução dos custos operacionais são um dos maiores benefícios da adoção da tecnologia blockchain na cadeia de abastecimento, enquanto a escalabilidade e interoperabilidade foram identificados com os maiores riscos/limitações da implantação da tecnologia. No que tange aos fatores facilitadores da adoção da tecnologia blockchain, a gestão de topo apresenta-se como agente principal no incentivo à adoção do blockchain nas organizações, além disso, a perceção de utilização da tecnologia pelos funcionários também influencia o sucesso de implantação da tecnologia blockchain. Outras características que afetam a adoção da tecnologia são a infraestrutura das empresas, políticas governamentais e a cultura do país, entretanto esses fatores tendem a ter níveis diferentes de acordo com o país onde a empresa está instalada. No que diz respeito aos fatores que dificultam a implantação do blockchain nas organizações, são apontados a falta de conhecimento da tecnologia blockchain e dos seus potenciais benefícios, a existência de um número reduzido de aplicações do blockchain nas empresas, a coordenação e comprometimento dos parceiros de negócios na resolução de problemas e no tratamento de dados, fatores externos, como a legislação e incentivos governamentais. Após examinar os estudos selecionados, a nossa análise revela uma série de abordagens que mostram como a blockchain pode melhorar a gestão da cadeia de abastecimento e identifica os setores mais propensos a retirar benefícios de sua implementação. A indústria de alimentos e a indústria farmacêutica são apontados como os setores com maior vantagem na adoção do blockchain devido a criticidade dos seus produtos, a procura crescente por informações referente a proveniência dos bens e seu alto valor agregado. O perfil das organizações que adotaram a tecnologia blockchain são geralmente multinacionais de grande e médio porte, com capilaridade de parceiros de negócios, grande volume de produção e alto valor agregado aos seus bens. Quanto a sustentabilidade, a tecnologia blockchain pode influenciar, através da transparência e rastreabilidade dos produtos, na redução da produção de lixo e das emissões de carbono no meio ambiente, no controlo das leis e práticas laborais, evitando-se trabalho escravo e, relacionado com as questões económicas, redução dos custos com auditorias, controlo de pedidos de compra, produção e procura. Os indicadores de performance, de acordo com os estudos revistos, podem ser melhorados com a utilização da tecnologia blockchain, promovendo novas métricas sustentáveis baseadas na rastreabilidade e na transparência dos dados. Apesar da fase inicial da tecnologia blockchain, alguns estudos propõem indicadores que avaliam a eficiência da cadeia de abastecimento após a adoção do blockchain, como o tempo de processamento das transações, a utilização de recursos (água, energia elétrica) e níveis de emissão de carbono. Embora já existam algumas revisões de literatura sobre a tecnologia blockchain na gestão da cadeia de abastecimento, este é um dos primeiros estudos que reúne questões importantes focadas nas consequências da adoção do blockchain na gestão. Além disso, os resultados deste estudo fornecem implicações para a gestão e para a teoria sobre as prováveis consequências da adoção de blockchain em vários setores da economia

On bullwhip-limiting strategies in divergent supply chain networks

The amplification of demand variation in a supply chain network (SCN) is a well-known phenomenon called the bullwhip effect. This effect generates a large volume of inefficiencies as it moves a greater number of units than necessary, increases stock and generates stock-outs. There are two different approaches for avoiding and/or limiting this detrimental phenomenon that have received attention in the literature: Collaboration and information sharing in SCNs on one hand, and the adoption of smoothing replenishment rules on the other. The effectiveness of both approaches have been often analyzed only for “serial linked” SCNs, which is a supply network structure rarely found in real-life. In order to give an insight of how these techniques would perform in more generic SCNs, a divergent SCN has been benchmarked against the classical serial SCN. The computational experience carried out show that the bullwhip effect can be considerably reduced by collaboration or the smoothing replenishment rules in divergent SCNs, but it always performs worse than the serial SCN due to its inherent complexity

Relationship of supply chain capabilities and supply chain technology adoption towards supply chain operational performance in textile and apparel industry

In today’s dynamic business environment, competition is no longer between firms, but between supply chains. The supply chain dependency leads the business focused on supply chain performance. Considering the importance given to the third industrial master plan by the Malaysia government, current supply chain environment accentuated the need of supply chain technology adoption to facilitate supply chain management. To explain the concerns, this study examined the impact of supply chain capabilities namely, relational capability, information technology capability, and organizational culture capability on supply chain operational performance and supply chain technology adoption. This study also examines the successive impact of supply chain technology adoption on supply chain operational performance and investigates whether supply chain technology adoption mediates supply chain capabilities and performance relationship under study. In order to achieve the research objectives, a two-step approach namely quantitative research method and a triangulation research approach are necessitated. 201 survey questionnaires were distributed to respondents in Malaysian textile and apparel organizations. 121 usable responses representing 60% response rate were empirically tested through structural equation modeling by using SPSS and SmartPLS. Research findings revealed that relational capability, organizational culture capability, and supply chain technology adoption contributed to firm’s supply chain operational performance, whereas, information technology capability was insignificant. The findings further revealed that supply chain capabilities have a positive influence to supply chain technology adoption. The findings also revealed a significant mediation effect of supply chain technology adoption in the model under study. A triangulation research approach was employed through face-to-face interviews with four industry practitioners to get their in-depth experiences and perceptions on the model under study. ATLAS.ti results showed that developed model had achieved agreement of industry experts with the suggestion of two emerging terms (human support and work experience) as moderators for future study on the model. Limitations and recommendations for future study are discussed

Artificial Intelligence Applied to Supply Chain Management and Logistics: Systematic Literature Review

The growing impact of automation and artificial intelligence (AI) on supply chain management and logistics is remarkable. This technological advance has the potential to significantly transform the handling and transport of goods. The implementation of these technologies has boosted efficiency, predictive capabilities and the simplification of operations. However, it has also raised critical questions about AI-based decision-making. To this end, a systematic literature review was carried out, offering a comprehensive view of this phenomenon, with a specific focus on management. The aim is to provide insights that can guide future research and decision-making in the logistics and supply chain management sectors. Both the articles in this thesis and that form chapters present detailed methodologies and transparent results, reinforcing the credibility of the research for researchers and managers. This contributes to a deeper understanding of the impact of technology on logistics and supply chain management. This research offers valuable information for both academics and professionals in the logistics sector, revealing innovative solutions and strategies made possible by automation. However, continuous development requires vigilance, adaptation, foresight and a rapid problem-solving capacity. This research not only sheds light on the current panorama, but also offers a glimpse into the future of logistics in a world where artificial intelligence is set to prevail