Search Results (15)

In response to growing environmental pressures and material constraints, circular economy principles are gaining traction across manufacturing sectors. However, most existing frameworks emphasize design and supply chain considerations, with limited focus on how circularity can be operationalized within internal manufacturing systems. This paper proposes a conceptual model that embeds circular operations at the core of production strategy. Grounded in circular economy theory, operations management, and socio-technical systems thinking, the model identifies four key operational pillars: circular input management, looping process and waste valorization, product-life extension, and reverse logistics. These are supported by enabling factors—digital infrastructure, organizational culture, and leadership—and mediated by operational flexibility, which facilitates adaptive, closed-loop performance. The model aims to align internal processes with long-term sustainability outcomes, specifically resource efficiency and operational resilience. Practical implications are outlined for resource-intensive industries such as automotive, electronics, and FMCG, along with a readiness assessment framework for guiding implementation. This study offers a pathway for future empirical research and policy development by integrating circular logic into the structural and behavioral dimensions of operations. The model contributes to advancing the Sustainable Development Goals (SDGs), particularly SDG 9 and SDG 12, by positioning circularity as a regenerative operational strategy rather than a peripheral initiative. Full article

Supply chain resilience (SRES) is essential for firms aiming to alleviate the impact of interruptions and maintain operational continuity and sustainability in performance. In the context of the FMCG industries of Pakistan and Saudi Arabia, characterized by intricate and vulnerable supply chains, there exists an urgent necessity for solutions that bolster resilience. This study examines the influence of critical factors resilient suppliers (RS), transportation capacity (TC), flexibility (FLEX), network complexity (NC), and supply chain dynamism (SPD) on SRES. A quantitative methodology was utilized, examining survey data from 611 participants with Partial Least Squares Structural Equation Modeling (PLS-SEM) and Necessary Condition Analysis (NCA). The results indicate that RS and TC are essential for directly improving SRES, whereas FLEX and SPD facilitate increased adaptability and reactivity. The NCA emphasizes the need to control NC to avert bottlenecks that may impede resilience. This study indicates that SRES emerges from the dynamic interplay of several elements, rather than from separate enhancements. Although NC exerts a negligible direct influence, adeptly managing complexity is crucial for reducing disruptions and inefficiencies. The results underscore that fortifying RS, TC, and FLEX in unison improves resilience and adaptation to market volatility and disturbances. This study provides various theoretical and managerial insights. A systems theory approach highlights the interdependence of supply chain components, whereas the Theory of Constraints (TOC) posits that excessive NC can hinder resilience. Management should concentrate on maximizing RS and TC until declining returns are evident, thereafter redirecting efforts towards improving FLEX and minimizing NC. Furthermore, optimizing processes and facilitating swift decision-making are essential for maintaining resilience. Full article

This study investigates the effects of the mediations of economic utility and moderation of perceived risk on supply chain performance as determined by the organization factors (innovation, organizational culture, and employee motivation) in the Egyptian Fast-Moving Consumer Goods (FMCG) Industry. Although previous research has identified an excess of factors affecting supply chain performance, limited were the studies trying to establish relationships among those factors, especially in emerging economies. Thus, a quantitative approach was adopted, using a structured questionnaire, which was distributed to 382 FMCG supply chain professionals in Egypt. Data were analyzed using structural equation modeling (SEM) to test relations between the hypothesized variables. The results provide evidence that innovation and employee motivation have a positive impact on supply chain performance; organizational culture, however, has no significant impact. Economic utility partially mediates this relationship, of which time utility is by far the strongest mediator. Furthermore, perceived risk moderates the effects of innovation and organizational culture on supply chain performance, thus creating a necessity for risk management. Such information will benefit supply chain managers through considering organizational agility, time-efficient utility drivers, and risk reduction strategies. This research adds to the literature by providing a broad framework integrating organizational factors, economic utility, and perceived risk within supply chain performance systems in developing markets. Full article

In the fast-moving consumer goods (FMCG) industry, inventory management is a critical component of supply chain management because it directly impacts cost efficiency and customer satisfaction. For instance, effective inventory management can minimize overstocking and reduce replenishment delays, which are particularly important in multi-echelon supply chain systems characterized by high complexity and dynamic demand. This study proposes a method based on deep reinforcement learning (DRL) aimed at optimizing replenishment decisions in multi-echelon inventory systems for FMCG industries. We designed a Dynamic Replenishment FMCG Multi-Echelon Optimization (ME-DRFO) model and incorporated a Markov Decision Process (MDP) to model the multi-echelon inventory system. By applying an improved Soft Actor–Critic with an adaptive alpha and learning rate (SAC-AlphaLR) algorithm, which introduces adaptive temperature parameters and adaptive learning rate mechanisms, our approach not only dynamically adapts to environmental changes but also effectively balances exploration and exploitation, ultimately achieving global replenishment cost minimization while ensuring supply chain stability. Through numerical experiments, our method demonstrates excellent performance by reducing replenishment costs by 12.31% and decreasing inventory shortages to 2.21%, significantly outperforming traditional methods such as overstocking, Particle Swarm Optimization (PSO), and the standard Soft Actor–Critic (SAC). This research provides new theoretical insights into multi-echelon inventory optimization and practical solutions for effectively managing complex supply chains under uncertain and dynamic conditions. Full article

In today’s dynamic business environment, the accurate prediction of sales orders plays a critical role in optimizing Supply Chain Management (SCM) and enhancing operational efficiency. In a rapidly changing, Fast-Moving Consumer Goods (FMCG) business, it is essential to analyze the sales of the products and accordingly plan the supply. Due to low data volume and complexity, traditional forecasting methods struggle to capture intricate patterns. Domain Adversarial Neural Networks (DANNs) offer a promising solution by integrating transfer learning techniques to improve prediction accuracy across diverse datasets. This study presents a new sales order prediction framework that combines DANN-based feature extraction and various machine learning models. The DANN method generalizes the data, maintaining the data behavior’s originality. The approach addresses challenges like limited data availability and high variability in sales behavior. Using the transfer learning approach, the DANN model is trained on the training data, and this pre-trained DANN model extracts relevant features from unknown products. In contrast, Machine Learning (ML) algorithms are used to build predictive models based on it. The hyperparameter tuning of ensemble models such as Decision Tree (DT) and Random Forest (RF) is also performed. Models like the DT and RF Regressor perform better than Linear Regression and Support Vector Regressor. Notably, even without hyperparameter tuning, the Extreme Gradient Boost (XGBoost) Regressor model outperforms all the other models. This comprehensive analysis highlights the comparative benefits of various models and establishes the superiority of XGBoost in predicting sales orders effectively. Full article

Background: Fast-moving consumer goods (FMCG) supply chains are experiencing various challenges due to the interactions between consumers and decision-makers during physical distribution, manufacturing, wholesale and retail. One possible strategy to address these challenges for smoothing the supply chain (SC) and logistics operations is to adopt Industry 4.0 (I4.0) based technologies in the FMCG business processes. In this regard, digitalization and automation of the FMCG supply chain can be strengthened by the alluring properties of I4.0 technologies. Methods: This study identified nine significant challenges through a literature review and expert validation. Later, the challenges were evaluated using a novel multicriteria decision-making (MCDM) framework, the Bayesian best worst method (BWM). Results: The findings indicated that “requirement for substantial investment and resources”, “incompatible technological infrastructure” and “poorly structured value chain” are the most significant challenges to implementing I4.0 in the FMCG industry. Conclusions: The study is expected to significantly contribute to improving the FMCG supply chain’s resilience, sustainability, visibility, traceability and responsiveness. Additionally, the research can provide industrial practitioners valuable insights into implementing I4.0 in FMCG and similar sectors and thus promote SC sustainability and resilience in those industries. Full article

This study aims to identify the sustainability programs introduced in their supply chains by the Indian retailing (FMCG and Pharma) sector and the various problems encountered in managing their supply chains. The researchers collected the opinions of 200 companies from the FMCG and pharma sectors after checking the questionnaire’s internal consistency and validity using Cronbach’s α and Kaiser–Meyer–Olkin (KMO) tests. After data collection, the data were summarized, coded, and controlled using R Studio and Microsoft Excel. The hypotheses were analyzed using the Kruskal–Wallis (K-W) hypothesis technique. Manufacturers emphasized that their supply chains impact toxic waste and pollution, that wholesalers and retailers are highly influenced by poor cost control and management, that there is a difficulty in forecasting demand, and that there are supply related problems. Full article

There are two concepts which encompass the new business order worldwide; this has vast implications, especially in the Indian business scenario. The first blanket is the phenomena of digitalization which was present in the undercurrents of all the business activities from the past two decades, and second one is circular economy practices. But in today’s Indian scenario, after the popular reform of “Notebandi”, forcing digitalization of the currency puts it to the forefront of all economic activities, especially in India. The economic reform of demonetization highlighted digitalization of economic transactions in the public eye. The phenomenon of digitalization is commonly referred to as the bundle of novel technologies that aim to improve things constantly. Organizations must take advantage of emerging technology to ensure that operations are both economically and environmentally feasible. Technologies based on sustainable solutions might aid companies in becoming more sustainable and economical. Therefore, this research is derived through the desire to measure the economic and environmental performance and how they were influenced by technology and circular practices of Indian Fast Moving Consumer Goods (FMCG) companies as they are most suited for this research. The sample (n = 203) was derived from senior managers of these companies. The study utilized Structural Equation Modeling (SEM) approach to analyze the results, it was found that digital transformation and circular economy practices are pervasive in nature and influence both Economic and Environmental performance of Indian FMCG companies. One of the main contributions of the study is that it also examines the relationship between technological advancements and economic and environmental performance directly; to date, there is not a single study, to the author’s knowledge, to have studied this relationship. Full article

Determining the optimal price of products is essential, as it plays a critical role in improving a company’s profitability and market competitiveness. This requires the ability to calculate customers’ demand in the Fast Moving Consumer Goods (FMCG) industry as various effects exist between multiple products within a product category. The substitution effect is one of the challenging effects at retail stores, as it requires investigating an exponential number of combinations of price changes and the availability of other products. This paper suggests a systematic price decision support tool for demand prediction and price optimise in online and stationary retailers considering the substitution effect. Two procedures reflecting the product price changes and the demand correlation structure are introduced for demand prediction and price optimisation models. First, the developed demand prediction procedure is carried out considering the combination of price changes of all products reflecting the effect of substitution. Time series and different well-known machine learning approaches with hyperparameter tuning and rolling forecasting methods are utilised to select each product’s best demand forecast. Demand forecast results are used as input in the price optimisation model. Second, the developed price optimisation procedure is a constraint programming problem based on a week time frame and a product category level aggregation and is capable of maximising profit out of the many price combinations. The results using real-world transaction data with 12 products and 4 discount rates demonstrate that including some business rules as constraints in the proposed price optimisation model reduces the number of price combinations from 11,274,924 to 19,440 and execution time from 129.59 to 25.831 min. The utilisation of the presented price optimisation support tool enables the supply chain managers to identify the optimal discount rate for individual products in a timely manner, resulting in a net profit increase. Full article

Synchromodality is an emerging concept in supply chain management. A synchromodal supply chain can be defined as a multimodal transportation planning system, wherein the different agents work in an integrated and flexible way that enables them to dynamically adapt the transport mode based on real-time information from stakeholders, customers, and the logistic network. The potential of synchromodality for the fast-moving consumer goods (FMCG) industry is related to the nature of business. The FMCG market is characterized by relatively low margins and high turnover, which is especially important in export supply chains. However, for a company, it may be challenging to objectively evaluate the costs and benefits, not to mention the design of a synchronized supply chain. In order to facilitate the adoption of the concept and guide the practitioners, our study put forward the following research questions: What should be considered in incorporating synchromodality in the export supply chain for FMCG? How should companies approach tradeoffs among factors affecting the supply chain? To answer these questions, we propose an adaptable framework, which should be considered a primary contribution of our study. The framework incorporates the center of gravity model, mixed integer linear programming, and sensitivity analysis. The framework is validated using a real-world problem from a multinational FMCG company. The problem involves the optimal volume allocation and the selection of the most efficient transportation mode for inland freight. Our study demonstrates that incorporating synchromodality in the export supply chain could reduce the overall cost by 9% and enhance flexibility by allowing multiple modes of transportation. Full article

In today’s competitive world, supply chain management is one of the fundamental issues facing businesses that affects all an organization’s activities to produce products and provide services needed by customers. The technological revolution in supply chain logistics is experiencing a significant wave of new innovations and challenges. Despite the current fast digital technologies, customers expect the ordering and delivery process to be faster, and as a result, this has made it easier and more efficient for organizations looking to implement new technologies. “Artificial Intelligence of Things (AIoT)”, which means using the Internet of Things to perform intelligent tasks with the help of artificial intelligence integration, is one of these expected innovations that can turn a complex supply chain into an integrated process. AIoT innovations such as data sensors and RFID (radio detection technology), with the power of artificial intelligence analysis, provide information to implement features such as tracking and instant alerts to improve decision making. Such data can become vital information to help improve operations and tasks. However, the same evolving technology with the presence of the Internet and the huge amount of data can pose many challenges for the supply chain and the factors involved. In this study, by conducting a literature review and interviewing experts active in FMCG industries as an available case study, the most important challenges facing the AIoT-powered supply chain were extracted. By examining these challenges using nonlinear quantitative analysis, the importance of these challenges was examined and their causal relationships were identified. The results showed that cybersecurity and a lack of proper infrastructure are the most important challenges facing the AIoT-based supply chain. Full article

The purpose of this paper is to study how advanced information about customer needs obtained through an Advance Purchase Discount (APD) contract can be exploited to coordinate the capital flow and enhance the efficiency of a two-stage supply chain (SC) under decentralized control in cases of stochastic customer demand. We developed an APD model in the form of an option contract, where the model and evaluation include the flexibility for the upstream firm to decide whether to provide a discount for an advance purchase at its own discretion. Applying the model to a Fortune 100 company, a leader in the Fast Mover Consumer Goods (FMCG) industry, showed that under certain conditions, and with suitably chosen contract parameters, management of decentralized control via APD contracts can lead to system-wide efficiency, and the individual decision makers pursue their own best interests, ensuring a win-win condition. Full article

One of the basic measures of the World Health Organization (WHO) in the fight against the COVID-19 pandemic is a lockdown policy with reduced contacts and physical distance. This presents a challenge, especially for fast-moving-consumer-goods (FMCG) supply chains, which are characterized by a large number of physical contacts between employees in production, physical distribution, wholesale, and retail. One of the ways to comply with the prescribed measures with the smooth functioning of the supply chain is the complete digitalization and automation of all business activities and operations based on the application of the Internet of Things (IoT). In this regard, this paper aims to analyze the setbacks to the digitalization of business processes and the sustainability of the FMCG supply chain based on the implementation of IoT. The research has been conducted among the participants in the standardization chain in the sectors of production, physical distribution, wholesale, and retail of FMCG in the Western Balkans region during the COVID-19 pandemic. The results showed significant differences between business sectors in terms of the intensity of setbacks to successful IoT implementation. Based on the obtained results, a set of measures and incentives was proposed that the competent institutions and the management of the FMCG supply chain should apply to encourage the digitalization process. Suggestions for future research are given in the paper. Full article

Nowadays, along with increasing companies’ activities, one of the main environmental protective tools is green supply chain management (GSCM). Since fast-moving consumer goods (FMCG) companies are manufacturing materials that usually require special warehousing as well as different distribution systems, and since companies of food products tend to fall into this area, the safety of their manufactured materials is a vital global challenge. For this reason, organizations in addition to governments have realized the importance of the green supply chain in these industries. Therefore, the present study examines the key performance indicators (KPIs) of the green supply chain in the FMCG industry. There are several performance indicators for the green supply chain. In this study, the KPIs were extracted based on the literatures as well as the opinions of experts through which key indicators in FMCG industries were identified. Using the fuzzy decision -making trial and evaluation laboratory (DEMATEL) method, the relationships and interactions of these key indices were determined. Moreover, a fuzzy nonlinear mathematical modeling was used to investigate the significance of these indicators. It is revealed that the organizational environmental management factor has the highest priority. Full article

This article empirically demonstrates the impacts of truthfully sharing forecast information and using forecast combinations in a fast-moving-consumer-goods (FMCG) supply chain. Although it is known a priori that sharing information improves the overall efficiency of a supply chain, information such as pricing or promotional strategy is often kept proprietary for competitive reasons. In this regard, it is herein shown that simply sharing the retail-level forecasts—this does not reveal the exact business strategy, due to the effect of omni-channel sales—yields nearly all the benefits of sharing all pertinent information that influences FMCG demand. In addition, various forecast combination methods are used to further stabilize the forecasts, in situations where multiple forecasting models are used during operation. In other words, it is shown that combining forecasts is less risky than “betting” on any component model. Full article