Peningkatan dan Efisiensi Operasional Supply Chain Management (SCM) dengan Memanfaatkan Teknologi

Abstract- Abstract Supply chain management (SCM) is an integral part of any business that involves the movement of goods and services from one place to another. It covers a wide range of activities, from sourcing raw materials to delivering finished products to customers. However, traditional supply chain management systems are plagued with challenges such as lack of transparency and others. In recent years, emerging technologies such as blockchain, machine learning (ML) and artificial intelligence (AI) have shown promise in improving supply chain management efficiency, security, and transparency. This research investigates the potential of blockchain, machine learning (ML), and artificial intelligence (AI) technologies in improving supply chain management. This paper will summarize the challenges of traditional supply chain management systems and how blockchain, Machine Learning (ML), and Artificial Intelligence (AI) technologies can overcome these challenges. The paper will also evaluate real-life examples of blockchain and Artificial Intelligence (AI) use in supply chain management and their impact on operational efficiency and security. The purpose of this research is to identify the impact of Artificial Intelligence (AI) in supply chain management, the impact of Machine Learning in supply chain management, and the impact of Blockchain in supply chain management. With the results of the study Integrating new technologies such as AI and blockchain in managing supply chains can provide great benefits to organizations. These technologies can increase work efficiency, reduce costs, strengthen the footprint of goods, and increase security. AI can help with predictive analysis, demand forecasting, and automation. Meanwhile, blockchain can provide a guaranteed, open, and secure record for end-to-end tracking, and reduce the risk of fraud and errors. Keywords: Supply chain management 1, Efficiency 2, Technology 3, Blockchain 4, Machine Learning 5, Artificial Intelligence

The Digitalisation of African Agriculture Report 2018-2019

An inclusive, digitally-enabled agricultural transformation could help achieve meaningful livelihood improvements for Africa’s smallholder farmers and pastoralists. It could drive greater engagement in agriculture from women and youth and create employment opportunities along the value chain. At CTA we staked a claim on this power of digitalisation to more systematically transform agriculture early on. Digitalisation, focusing on not individual ICTs but the application of these technologies to entire value chains, is a theme that cuts across all of our work. In youth entrepreneurship, we are fostering a new breed of young ICT ‘agripreneurs’. In climate-smart agriculture multiple projects provide information that can help towards building resilience for smallholder farmers. And in women empowerment we are supporting digital platforms to drive greater inclusion for women entrepreneurs in agricultural value chains

Ethical Implications of Predictive Risk Intelligence

open access articleThis paper presents a case study on the ethical issues that relate to the use of Smart Information Systems (SIS) in predictive risk intelligence. The case study is based on a company that is using SIS to provide predictive risk intelligence in supply chain management (SCM), insurance, finance and sustainability. The pa-per covers an assessment of how the company recognises ethical concerns related to SIS and the ways it deals with them. Data was collected through a document review and two in-depth semi-structured interviews. Results from the case study indicate that the main ethical concerns with the use of SIS in predictive risk intelli-gence include protection of the data being used in predicting risk, data privacy and consent from those whose data has been collected from data providers such as so-cial media sites. Also, there are issues relating to the transparency and accountabil-ity of processes used in predictive intelligence. The interviews highlighted the issue of bias in using the SIS for making predictions for specific target clients. The last ethical issue was related to trust and accuracy of the predictions of the SIS. In re-sponse to these issues, the company has put in place different mechanisms to ensure responsible innovation through what it calls Responsible Data Science. Under Re-sponsible Data Science, the identified ethical issues are addressed by following a code of ethics, engaging with stakeholders and ethics committees. This paper is important because it provides lessons for the responsible implementation of SIS in industry, particularly for start-ups. The paper acknowledges ethical issues with the use of SIS in predictive risk intelligence and suggests that ethics should be a central consideration for companies and individuals developing SIS to create meaningful positive change for society

Information technology and performance management for build-to-order supply chains

En las siguientes líneas se plantea un artículo de reflexión que tiene en cuenta parte del marco teórico que sustenta la investigación titulada “Prácticas pedagógicas que promueven la competencia argumentativa escrita (CAE) en niños campesinos de los grados 4° y 5° del Centro Educativo Municipal La Caldera, Sede Principal de Pasto”, desarrollada en el año 2012. En él se contemplan los aportes de las ciencias del lenguaje y la comunicación, la teoría de la argumentación, la didáctica de la lengua escrita y los géneros discursivos, que dan cuenta de la necesidad de desarrollar la capacidad crítica en los estudiantes a través de la argumentación, lo cual implica transformar las prácticas pedagógicas para que se alejen de la transmisión de conocimientos y den paso a la comunicación, para que la palabra escrita sea apropiada de manera significativa

Procurement push and marketing pull in supply chain management: the conceptual contribution of relationship marketing as a driver in project financial performance

? The agenda for supply management practices on construction projects originated from clients. It is largely procurement driven, the dominant strategy of contractors being to emulate the client approach, and hence push the procurement model along the chain.? This procurement push along the supply chain translates the intrinsic client interest in value into a contractor interest in repeat business from the same client or through referral markets, the consequence being: (i) loss of interest in adding further value along the chain, (ii) continuous improvement prematurely reaches the law of diminishing returns through a primary cost reduction focus, (iii) supply chains may be rationalised in terms of the number of suppliers for each link in the chain, yet the procurement push increases chain length in order to squeeze the lowest costs possible, hence those doing the work at the bottom of the chain will not have the resources to add value nor necessarily be aware of the strategic principles at the top of the chain. ? Marketing is the other side of the same ?procurement coin?; relationship marketing (RM) soliciting a pull in the supply chain, potentially adding value for continuous improvement. ? Finally, the RM approach will be related to the theoretical and actual decoupling point for construction, with the potential to move the point towards the start of the chain, hence increasing the potential for agile manufacturing

Dynamic real-time risk analytics of uncontrollable states in complex internet of things systems, cyber risk at the edge

The Internet of Things (IoT) triggers new types of cyber risks. Therefore, the integration of new IoT devices and services requires a self-assessment of IoT cyber security posture. By security posture this article refers to the cybersecurity strength of an organisation to predict, prevent and respond to cyberthreats. At present, there is a gap in the state of the art, because there are no self-assessment methods for quantifying IoT cyber risk posture. To address this gap, an empirical analysis is performed of 12 cyber risk assessment approaches. The results and the main findings from the analysis is presented as the current and a target risk state for IoT systems, followed by conclusions and recommendations on a transformation roadmap, describing how IoT systems can achieve the target state with a new goal-oriented dependency model. By target state, we refer to the cyber security target that matches the generic security requirements of an organisation. The research paper studies and adapts four alternatives for IoT risk assessment and identifies the goal-oriented dependency modelling as a dominant approach among the risk assessment models studied. The new goal-oriented dependency model in this article enables the assessment of uncontrollable risk states in complex IoT systems and can be used for a quantitative self-assessment of IoT cyber risk posture

Feasibility of Warehouse Drone Adoption and Implementation

While aerial delivery drones capture headlines, the pace of adoption of drones in warehouses has shown the greatest acceleration. Warehousing constitutes 30% of the cost of logistics in the US. The rise of e-commerce, greater customer service demands of retail stores, and a shortage of skilled labor have intensified competition for efficient warehouse operations. This takes place during an era of shortening technology life cycles. This paper integrates several theoretical perspectives on technology diffusion and adoption to propose a framework to inform supply chain decision-makers on when to invest in new robotics technology