Product Supply Chain Management Research Articles

Value of risk aversion in perishable products supply chain management

AbstractIn this paper, we study optimal procurement and inventory decisions for a supply chain with a single perishable product under demand uncertainty. To control risk, on the one hand, we use a risk-averse objective, and on the other hand, we utilize a chance constraint to satisfy demand with a high probability. We formulate the problem as a two-stage stochastic program with a chance constraint and risk-averse objective, where long-term decisions on pre-positioning products are made in the first stage, while recourse decisions on reallocation and emergency procurement are made in the second stage. To allow for different risk preferences, we incorporate conditional value-at-risk into the objective function and study its combination with the expectation or worst-case of the second-stage costs. To solve the resulting models, we develop various variants of the L-shaped method, based on dual and primal decomposition, and by leveraging the connection between the optimization of coherent risk measures and distributionally robust optimization. Through extensive numerical experiments, we demonstrate the value of risk aversion and present a comparative computational study on the performance of different algorithms.

Large-scale Probabilistic Forecasting of Consumer Engagement of CPG Products using Heterogeneous Web Data

Consumer Packaged Goods (CPG) play a pivotal role in customer-centric industries. Understanding the distinctive features of such products and how customers engage with them is essential for CPG manufacturers to create customer-winning products. In this study, we explore an innovative data-centric approach to forecast customer engagement for CPG products by monitoring their digital evolution, particularly in the Snacks category in the USA. Traditional methods for consumer analysis such as surveys, focus groups are time consuming, costly and ineffective with limited scope. They also lack a forecasting component, making it difficult for CPG companies to make forward-looking decisions. However, with the emergence of big data, we can leverage user generated public data from social media, web search, e-commerce platforms to estimate consumer engagement and make long-term forecasts. To achieve this, we propose a systematic approach to accumulate and prepare large datasets from heterogeneous web sources for CPG products. We then use state-of-the-art deep learning based time series forecasting models to efficiently train and predict consumer engagement for the next 12 months, benchmarking their computational efficiency and forecasting performance. Our findings indicate that the DeepAR model outperforms all other models, with the lowest NRMSE (=0.378), RMSE (=14.848) MSE (=220.457), MASE (=0.871), and sMAPE (=0.306) values. Furthermore, we demonstrate methods for computing single forecasting points and prediction intervals using the forecasted sample distribution from the probabilistic models. The proposed approach will provide CPG businesses with valuable insights to make informed decisions about product development, marketing strategies, and supply chain management.

Measuring The Fish Logistics Performance Index in The Indonesian Fisheries Supply Chains (A Study Case Of Poumako Fishing Port Of Mimika, Central Papua)

Indonesia is an archipelagic nation and there is an unequal population distribution, economic access, and price disparities between the islands. To tackle such challenges The Indonesian Ministry of Marine Affairs and Fisheries (MMAF) intends to establish the National Fish Logistics System to construct and develop an integrated, fishery product supply chain management. The research aims to determine the fish logistics performance index (hereafter F-LPI) in corridor Mimika-Java (Jakarta/ Surabaya) in 2021 using F-LPI measurement methoe developed by MMAF. The results of the assessment and calculations for the Mimika-Surabaya/Jakarta corridor resulted in an F-LPI score of 65.74 which is included in the "Good" category. The dimensions of benefits and governance have the largest dimension index values of 92.32 and 81.91 (very good) respectively, while the index value for fisheries product procurement management has the lowest dimension index value of 40.15 (poor) and for dimension of Efficiency and Connectivity are fair and good. These results then become the basis for several improvement steps at the location such as fishing port management, additional cold chain facilities, and consolidation of logistics actors at the location.

Digital Economy Enables Community Group-buying Fresh Agricultural Products Supply Chain Management Optimization

In the context of China's digital economy promoting social development, this paper based on the characteristics of fresh agricultural products perishable, difficult to preserve and easy to wear, with the help of digital economy enabling model, explores the practical problems of community group purchase of fresh agricultural products, and analyzes its supply chain management. The analysis results show that the optimization of supply chain management depends on the digital economy, which can effectively do a good job in factor allocation, model innovation and information transmission, and achieve win-win benefits of multiple entities by improving product quality control, forming core competitiveness, balancing supply and demand and controlling costs, and meeting the diversity requirements of consumers. This study can explain the potential problems of the current agricultural product supply chain to a certain extent, and also provide a reference for the digital economy enabling community group-buying fresh agricultural product supply chain management optimization.

A Value Modeling Approach for Product Development Processes and Supply Chain Management

This research presents a quantifiable value modeling approach for tracking and optimizing value addition at different stages of the product development process (PDP) and supply chain management (SCM). While there is a vast abundance of papers in the literature harping on the need to maximize the value, especially in lean thinking context, in PDP and SCM, there is a dearth of propositions on how to quantitatively measure and optimize value at each stage of product development and supply chain. This paper presents a multi-dimensional value modeling approach that incorporates parameters and variables from different stages of PDP and SCM by mathematically mapping them on to two macroscopic metrics, namely Product Information Evolution and Risk Reduction. These two metrics are in turn modeled by incorporating value attribute variables such as performance, risk, schedule, cost, form, fit, function and timeliness from different stages of PDP-SCM such as customer needs ideation, product functions, inventory management, logistics management and product delivery. The efficacy of the proposed model was tested by utilizing it to measure value additions at different stages of PDP-SCM as well as the total value addition for an ordinance disposal (OD) robot product family, once developed and supplied using traditional production method and once using lean production method, with the underlying axiom being the lean method will result in higher value. To ensure a fair and accurate comparison, both production methods used the proposed mathematical value model and worked toward maximizing total value using nonlinear programming. The results showed that lean PDP-SCM method added higher value at each of the stages as well as total value when compared to the traditional PDP-SCM method thus establishing the proposed value model as a viable mathematical way to measure value. While the proposed value model passed test of efficacy against the lean axiom, further research is needed to test it against other established axioms to establish it as a robust mathematical way to measure value in PDP-SCM.

Can blockchain technologies enhance environmental sustainable development goals performance in manufacturing firms? Potential mediation of green supply chain management practices

AbstractThe nexus between manufacturing firms and the green environment is unavoidable. It is merely due to the huge waste generation and greenhouse gas emissions resulting from large‐scale production and complex supply chain management processes involved in manufacturing firms. Continuation of the traditional business practices during Industry 4.0 made it impossible for the manufacturing firm to commit to green environmental practices and comply with environmental SDGs. At odd, it requires novel business strategies to ensure compliance of manufacturing firms with environmental sustainable development goals (SDGs). Blockchain is an ideal technology for delivering green environmental‐related information because it offers real‐time, shareable, and entirely transparent data kept on an immutable ledger that is accessible to members of a network. These green environmental‐related information received in real‐time through blockchain technology help in the transformation of the traditional supply chain management practices into a more green supply chain management practice. This green transformation ensures business compliance with environmental SDGs and that compliance is shared with multiple stakeholders through blockchain technology in real‐time, thus approving a positive mediating role of green supply chain management practices between blockchain technology and environmental SDGs performance. The proposed strategic framework through various propositions development will mainly offer policy insights toward (a) identifying novel antecedents of blockchain technology, (b) offering insights toward upgrading the traditional supply chain management framework into a green supply chain management framework, and (c) illuminating novel mediating role of green supply chain management practices between blockchain technology and environmental SDGs performance.

Research on the Supply Chain Management of Fresh Agricultural Products in Shenyang Yonghui Supermarket

Fresh agricultural products have become the most important part of supermarkets. Since fresh agri-products are perishable and have a relatively short shelf life, there are always some key problems that need to be solved in the operation of fresh agricultural products in supermarkets, such as building an efficient fresh agricultural product supply chain management system, improving logistics efficiency and storage level, reducing the cost and loss of products, and ensuring the standardized quality and safety of fresh agri-products. This article takes Shenyang Yonghui Supermarket, which operates fresh agricultural products as an example. Firstly, by analyzing the structure, logistics and procurement of Yonghui's fresh food supply chain, and combined with SWOT analysis, it puts forward countermeasures and suggestions for the optimal design of Shenyang Yonghui's fresh food supply chain.

Analysis of green certification standards related to recycled materials involving textiles based on life cycle thinking

Enterprises have been increasingly required by international brands to obtain green certification. As green certification has become an important tool for evaluating suppliers and securing environmental performance along the supply chain, and textile-related recycled materials are one of the most affected industries, this study aims to examine the differences among various certification schemes in the recycled materials industry involving textiles. We identify a set of clear and consistent evaluation metrics for the criteria in green certification, and investigate the standardized contents of green certifications for recycled materials-related industries based on life cycle thinking. It is found that “requirements on recycled material content” are required by all the green certifications examined. From the perspective of life cycle stages, the “raw material stage”, “manufacturing stage” and “disposal stage” are emphasized by the green certifications related to the recycling industry. Finally, this study combines an environmental perspective incorporating life cycle thinking (LCT) with a social and economic perspective of implementation feasibility to provide ways to strengthen certification regimes related to recycled materials and promote long-term product life cycle management and supply chain management.

Value‐driven Systems Engineering Approach addressing Manufacturing, Supply‐chain and Aircraft Design in the Decision‐Making Process

AbstractIn the last decades, some studies have highlighted that the integration of the product design and supply chain management leads to an increase of the profitability and efficiency of companies. However, considering manufacturing, supply chain and overall aircraft design variables in the early design phase increases the size of the solutions tradespace and thus the complexity in performing the decision‐making process. This paper, follow‐up of previous research activities addressed within the European project AGILE4.0, demonstrates how to leverage the value‐model theory to simplify the decision‐process when multiple criteria are accounted in the design phase.

Human Resources Readiness of Small Medium Enterprises (SMEs) for Halal Product in Indonesia

The halal industry has caught the attention of the world today. The halal industry is not only in demand by Muslim countries but also by countries with non-Muslim majority populations. The implementation of the halal certification program for Small and Medium Enterprises (SMEs) also affects the process of developing SMEs' human resources in Indonesia. Increasing the capacity of human resources is needed to improve the competence, skills, innovation, and creativity of individuals in carrying out productive activities to increase domestic production. This study is expected to be able to provide an overview (steps that need to be achieved, policy strategies, and various efforts that need to be made) related to the role of government bureaucracy, academics, and business actors in optimizing the halal product guarantee system to support the halal industry in Indonesia. This study uses a combination of qualitative and quantitative data. The method used is literature study, in-depth interview, benchmark, and Analytical Networking Process (ANP). A strategic solution for SMEs in increasing the halal market segment is the need for socialization of assistance and submission of halal certification. In addition, the implementation of integrated halal product supply chain management is very necessary to ensure the quality of halal products and services.

Factors Influencing Small Business Success in Medical Equipment Manufacturing Industry

Research Question, Aim and Objectives What aspects of the business environment encourage the growth of minor medical equipment manufacturers? How much do the difficulties small businesses face when attempting to manufacture medical equipment hinder their possibilities of achieving financial and operational success? How much do factors such as product quality, pricing, marketing, and supply chain management contribute to the success of small enterprises in the medical equipment manufacturing industry?

Sickle effect: A hybrid model of product life cycle and supply chain management for achieving sustainable development

This paper gives a basic study of Sickle effect which is a new concept developed through combination of product life cycle (PLC) and supply chain management (SCM). Various studies were being done in the field of sustainable manufacturing (SM) majorly to design a product which can be environmentally sustainable. This present concept gives a basic idea of any product which goes through various stages of PLC and represents the amount of product that can be recycled.

The need for vendor development programmes to increase the efficiency of the automotive industry in Pakistan

Although there is always a need for further development in business models and industrial organisations via gradual improvements in their operations including production activities, warehouse management and supply chain management, it is quite obvious that from the present rise in inflation, a gap between the employees and the employers has been observed in the automotive sector due to a lack of vocational training or vendor development programmes causing uncertain attributes. The study aimed to highlight the significance of vendor development programmes in the automotive sector along with hindering factors and uncover the impediments that do not allow the encouragement of vendor development programmes in the said industry in Pakistan. The methodology for this research is qualitative, which will take the best measures by collecting the data from the vendors, especially from the operations department as this department is having deep insight and core knowledge about the organisation. The study concluded that financial constraint is the major factor that limits vendor development programmes in the automotive industry of Pakistan. Keywords: Automotive industry, training programmes, vendor, vendor development programmes

The design of intelligent fuzzy cognitive system of music emotion by product supply chain management

AbstractThe classification of musical emotion is a challenging problem due to the subjectivity of human perception. In order to analyse the emotion contained in music from the perspective of product supply chain management, the psychological model and characteristics of music emotion are introduced. Additionally, the current product supply chain and the composition of the two contracts are analysed based on the characteristics of online music products. Finally, a speech emotion recognition model based on a Fuzzy Cognitive Map (FCM) is proposed. Two corpora containing five emotions (sadness, anger, happiness, surprise, and boredom) are selected to test the performance and characteristics of the network. In order to evaluate the system performance, different acoustic features are extracted, including prosodic features, formant features, marginal spectral features, and Mel‐Frequency Cepstral Coefficients (MFCC). The results show that the average recognition rate of MFCC features on the Berlin emotional speech database is 70.36%, which is 0.75% higher than the second‐highest edge spectrum features and achieves better results. Meanwhile, on this database, the Musical Emotion Recognition System based on FCM (MERS‐FCM) is improved by 20.36%, 7.34%, and 4.12% compared with Back Propagation, K‐nearest neighbour, and support vector machine, respectively, which shows that MERS‐FCM has better performance. The research of the music emotion recognition system based on FCM can provide more reference paths for the use and development of music emotion information.

Uncertain green product supply chain with government intervention

Green product supply chain management is increasingly becoming a new trend due to the growing awareness of environmental issues and the continuous development of industrial eco-processes. In this study, a two-echelon supply chain with government intervention involving a single manufacturer and a single retailer is examined. Due to the lack of actual data, the market size, price elasticity, demand function, and production cost are assumed to be unreliable variables. On the basis of various risk attitudes, the uncertain expected value, optimistic value, and mini–max chance constraint game theoretic models are developed. Equilibrium decisions for different planning models are derived. An analysis of equilibrium decisions and profits is conducted through numerical experiments examining the effects of confidence level, government intervention, green level, and price sensitivity. Based on the results of the data analysis, it appears that the manufacturer and retailer are able to reach different equilibrium decisions by adopting distinct risk attitudes. Furthermore, government intervention can facilitate the coordination of parameter-based decision-making and supply chain conflicts.

Product Authentication and Traceability Using Blockchain

This article provides a comprehensive review on the use of blockchain technology in supply chain management, with a focus on product authentication and traceability. It then reviews the existing literature on the use of blockchain technology in supply chain management, including case studies and surveys. The product supply chain is a complex process that involves multiple stakeholders, including suppliers, manufacturers, distributors, retailers, and customers. Ensuring transparency, efficiency, and security throughout the supply chain is a challenging task. This paper proposes a decentralized blockchain-based product supply chain management system with QR code verification that can improve transparency, efficiency, and security. The system allows manufacturers to enter product details, including brand name, logo and generates a unique QR code for each product. The QR code can be used by buyers to verify the authenticity of the product and track its movement through the supply chain. The methodology used includes Ganache, IPFS, Blockchain, Ethereum and Truffle.

Feature-based intermittent demand forecast combinations: accuracy and inventory implications

Intermittent demand forecasting is a ubiquitous and challenging problem in production systems and supply chain management. In recent years, there has been a growing focus on developing forecasting approaches for intermittent demand from academic and practical perspectives. However, limited attention has been given to forecast combination methods, which have achieved competitive performance in forecasting fast-moving time series. The current study examines the empirical outcomes of some existing forecast combination methods and proposes a generalised feature-based framework for intermittent demand forecasting. The proposed framework has been shown to improve the accuracy of point and quantile forecasts based on two real data sets. Further, some analysis of features, forecasting pools and computational efficiency is also provided. The findings indicate the intelligibility and flexibility of the proposed approach in intermittent demand forecasting and offer insights regarding inventory decisions.

Blockchain Technology based Smart Contract Model in Indonesia

The primary task of integrated product supply chain management is distribution. The processing, storage, and distribution of high-quality pharmaceutical products makes the drug distribution process crucial in the pharmaceutical sector. The distribution of fake medications by associated parties, such as unauthorized or unregistered distributors or data collecting for unregistered medications distributed by distributors, is a concern in the pharmaceutical industry. Drug production permits that are misused up until they are distributed or circulated do not adhere to the Food and Drug Supervisory Agencies standard requirements. In order to facilitate the distribution process by recording data distribution, providing data security, and giving traceability of transactions between linked parties, these issues must be rapidly resolved with technology help. By utilizing blockchain technology, this study suggests a beneficial medicine delivery approach. A user-centered design and a qualitative methodology are used in the model creation. This study's output is a blockchain-based drug delivery mechanism that has been verified. Transparency, security, traceability, decentralization, automation, immutability, and reliability are all features of the model. By ensuring that the pharmaceuticals supplied are of high quality, this strategy can assist the government in promoting community safety, health, and trust in the drugs that are in use.

Training Path for Talents Engaged in Agricultural Product Supply Chain Management and the Assessment of Their Training Quality

The Supply Chain Management (SCM) of agricultural products (AP) is an important part of modern logistics, and cultivating talents with rich theoretical knowledge and practical operation skills of the SCM of agricultural products is particularly meaningful for China as a major agricultural country. However, at present, few studies have concerned about the training path for such talents, so to fill in this research blank, this paper studied the training path for AP-SCM talents and the assessment of their training quality, aiming to find and solve the defects in the existing training programs. At first, this paper proposed training path for AP-SCM talents and attained the conclusion that colleges and universities should pose requirements for AP-SCM talents from 9 training directions. Then, a prediction model was built for assessing the training quality of AP-SCM talents, and the specific model framework and modeling principles were given. At last, experimental results verified the effectiveness of the prediction made by the proposed model.

Speciality of food products supply chain management under martial law in Ukraine

Speciality of food products supply chain management under martial law in Ukraine