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The increasing popularity of ERP solutions has provided dietary supplement manufacturing companies with modules to manage pricing and inventory. However, the decisions made by these modules are often independent and rely on deterministic forecasts. This paper studies a multi-product dietary supplement manufacturing system under stochastic demands. The purpose is to maximize the long-run expected profit by jointly considering pricing and inventory strategies.

The authors investigate both the general cases and three special cases including stable demand, negligible backlog and instantaneous replenishment. A two-stage algorithm named PAS is proposed. In the strategy construction stage, the constructed objective bounds are combined to provide estimates which then help to derive the optimal product prices. In the system operation stage, replenishment decisions are further made based on the prices generated from the previous stage.

It is proved that base-stock policy is optimal for the studied system, and the optimal based-stock level is provided. The global optimal strategies are obtained for three important special cases. For the general case, theoretical objective bounds are established. These bounds provide quick and reliable performance estimates for practical applications.

Very few studies have jointly considered pricing and inventory strategies with uncertainty demands in the dietary supplement industry. The PAS algorithm developed integrates these decisions and consistently generates high-quality solutions even under highly varying demands. Such algorithm could be a valuable add-on to the pricing and inventory management modules in ERP systems.

Managing inventory continues to be a growing area of concern for many retailers due to the multitude of issues that arise from either an excess or shortage of inventory. This study aims to understand how a large-scale retail chain can improve its handling of excess seasonal inventory using three common strategies: information sharing, visibility, and collaboration.

This study has been designed utilizing a case study method focusing on one retail chain at three key levels: strategic (head office), warehouses, and retail stores. The data have been collected by conducting semi-structured interviews with senior-level employees at each of the three levels and employing a thematic analysis to examine the major themes.

The results show how three common strategies are being practiced by this retailer and how utilizing these strategies aids the retailer in improving its performance in regard to seasonal inventory. Among our research findings, some challenges were discovered in implementing the strategies, most notably: human errors, advanced forecasting deficiencies, and the handling of return merchandise authorizations.

This research takes a case study approach and focuses on one big-box retailer. The authors chose to study three levels (head office, warehouses, and retail stores) to gain a deeper understanding of the functions and processes of each level, and to understand the working relationships between them. Through the collection of primary data in a Canadian context, this study contributes to the literature by investigating supply chain strategies for managing inventory. The Canadian context is especially interesting due to the multi-cultural demographics of the country.

The purpose of this paper is to investigate the opaque inventory information disclosure strategy for an online retailer who sells two substitutable products to customers in two selling periods.

The authors develop a two-period model where an online retailer sells two substitute products with two inventory composition structures to maximize profits. The authors investigate the optimal inventory disclosure decision from both ex post and ex ante perspectives. Sensitivity analysis is performed to investigate the effects that discount rate, transaction cost and the probability of agreeable inventory situation have on the equilibrium disclosure outcome. The authors also consider risk-averse customers and horizontally differentiated products to highlight the robustness of our results.

The authors find that the online retailer will choose the opaque information disclosure when attempting to increase revenue and reduce the mismatch of supply and demand in both ex post and ex ante inventory information conditions. Comparing with ex post disclosure strategies, ex ante opaque disclosure is optimal in a larger price region, and the total revenues gap between opaque disclosure and complete disclosure gradually increase as discount rate, transaction cost or the probability of agreeable inventory situation decreases. Furthermore, strategic customers may tend to be risk neutral when faced with opaque inventory information in a two-period sales setting.

This current paper is the first paper to study the online retailer's inventory information disclosure strategy in two selling periods. Moreover, this paper presents the conditions under which the online retailer should share complete or opaque inventory information with customers to maximize the online retailer's total revenues.

This study aims to identify empirically proven strategies for reducing healthcare supply chain inventory costs.

The author conducted in-depth interviews in 80 hospitals covering different supply chains. The author treated the healthcare firm as the unit of analysis and examined Vrat's taxonomy of inventory models based on the static and dynamic complexity theories of inventory models to identify an appropriate approach. The author addressed 33 highly priced and moderately priced stock-keeping units from 1,432 items and test several inventory policies. Next, the author applied combinations of inventory models, testing probabilistic hybrid inventory models.

The study finds that medical supplies, equipment, and medications are indispensable for a quality healthcare system. Hence, healthcare supply chain management (SCM) professionals must adopt basic inventory cost-reduction strategies, implementing inventory software functionalities effectively and efficiently. This study shows that probabilistic hybrid inventory techniques in healthcare SCM effectively determine an optimal stocking level, significantly reducing costs.

This study analyzes data from primary care and (to some extent) secondary care institutions. Although tertiary and quaternary care systems do not represent a large portion of the healthcare system, future research should also address these highly specialized organizations' needs.

This study proposes practical strategies to help continuously improve supply chain operations in healthcare organizations worldwide.

This study suggests probabilistic hybrid inventory models as empirically proven solutions for evaluating stock-keeping units in the healthcare sector. In doing so, the study provides a new healthcare supply chain approach, proposing a modified taxonomy of inventory models.

The existence of the advertising delay effect and its impact on supply chain operations have been demonstrated in the current study. Therefore, this study develops a timely inventory control strategy for the fresh produce supply chain to address the advertising delay effect in the fresh produce supply chain.

This study proposes a game model based on the Nerlove-Arrow time delay differential equation and Pontryagin's maximum principle. Through comparative analyses of the optimal equilibrium strategies, the authors compare the optimal equilibrium strategies, product goodwill and optimal inventory trajectories for suppliers and retailers under secondary replenishment decisions and decentralized decisions.

The authors find that (1) Only when the sales cycle meets certain conditions can the overall profit of the supply chain under the secondary replenishment decision be greater than that under the decentralized decision. As the price markup coefficient increases, the total profit of the supply chain first increases and then decreases. (2) With the increase in the delay time, the replenishment quantity during the initial period gradually decreases. After the delay time elapses, the inventory depletion rate under secondary replenishment decisions is faster than that under decentralized decision-making. (3) Although there is a continuously increasing maximum value of product goodwill with the increase in delay time, it becomes difficult to achieve this value for longer delays.

The authors’ findings provide a theoretical basis for supply chain members of fresh agricultural products to select replenishment and inventory control strategies when adopting different levels of delay in advertising marketing.

Firstly, this paper explains the impact of advertising delay effect on fresh produce supply chain from a dynamic perspective, and secondly, it provides guidance on advertising formulation and inventory replenishment for fresh produce retailers under the influence of advertising delay effect.

This study explores the intricate relationship between inventory leanness, financial constraints and digital transformation in listed Chinese manufacturing firms.

Using a large panel data collected from 2,563 Chinese listed manufacturing enterprises over the period from 2012 to 2021, this research employs the instrumental variable method combined with two-stage least squares estimators to explore the U- shaped relationship between inventory leanness and financial constraints. Furthermore, the moderating role of digital transformation is demonstrated.

Contrary to traditional assumptions, our research uncovers a U-shaped relationship between inventory leanness and financial constraints, indicating that excessive inventory reduction can exacerbate financial constraints. Digital transformation plays a significant moderating role, particularly in highly digitalized environments.

Our findings have practical significance for top managers and policymakers. We advocate for a balanced approach to lean inventory management to mitigating financial constraints. The study emphasizes the pivotal role of digital transformation in alleviating the impact of inventory leanness on financial constraints, highlighting the need for digital transformation strategies.

This research provides a comprehensive analysis of inventory leanness, financial constraints and digital transformation dynamics. It challenges conventional thinking by revealing the nonlinear nature of the inventory leanness–financial constraints relationship. The concept of moderation highlights the moderating effect of digital transformation. This study offers practical guidance for practitioners and policymakers.

Metacognitive strategies are learning strategies that involve planning, self-monitoring, and self-evaluation. Metacognition is characterised as a build that alludes to considering one’s reasoning or the human capacity to be aware of one’s mental processes. According to Flavell (1976) metacognitive learning is ‘one’s learning concerning one’s own particular intellectual procedures and items or anything identified with them, e.g., the learning-applicable properties of data or information’. The purpose of the study is to investigate to what extent the university English as a Foreign Language (EFL) learners employ metacognitive reading strategies in reading comprehension. Further, it aims to research the most used strategy of MARSI inventory subscale: reading performance in reading EFL. Statistical analysis has been calculated by using ANOVA, correlation, and metacognitive awareness reading strategy inventory (MARSI), which in fact is the self-report instrument. The study has identified that EFL students of Kosovo universities possess considerable amount of awareness over metacognitive strategies in reading comprehension.

Effective inventory management is crucial for SMEs due to limited resources and higher risks like cash flow, storage space, and stockouts. Hence, the aim is to explore how technology and know-how can be integrated with inventory practices and impact operational performance.

The basis of the analysis was collecting papers from a wide range of databases, which included Scopus, Web of Science, and Google Scholar. In the first phase of the process, a search string with as many as nine related keywords was used to obtain 175 papers. It further filtered them based on their titles and abstracts to retain 95 papers that were included for thorough analysis.

The study introduced innovative methods of measuring inventory practices by exploring the impact of know-how. It is the first of its kind to identify and demonstrate how technical, technological, and behavioral know-how can influence inventory management practices and ultimately impact the performance of emerging SMEs. This study stands out for its comprehensive approach, which covers traditional and modern inventory management technologies in a single study.

The study provides valuable insights into the interplay between technical, technological, and behavioral know-how in inventory management practices and their effects on the performance of emerging SMEs in Industry 5.0 in the light of RBV theory.

The RBV theory and the Industry 5.0 paradigm are used in this study to explore how developing SMEs' inventory management practices influence their performance. This study investigates the effects of traditional and modern inventory management systems on business performance. Incorporating RBV theory with the Industry 5.0 framework investigates firm-specific resources and technological advances in the current industrial revolution. This unique technique advances the literature on inventory management and has industry implications.

The purpose of this paper is to identify the radio frequency identification (RFID) strategic value attributes (RFIDSVAs) mechanism selections preferences and also integration of RFID tags with technology coordination tools (IRTWTCTs) alternatives ranking performance decisions in supply chain management (SCM). RFID-enabled techno-economic feasibility decisions are enhancing the SC visibility in apparel supply chains (ASCs). The RFIDSVAs mechanism selections have performed significant agility to strategic competitive advantages, namely, inventory visibility, multi-tags ownership transfer within trusted third party, etc.

Fuzzy analytical hierarchy process (FAHP) and FAHP-fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) approaches have been used to evaluate the quantitative assessment of RFIDSVA mechanisms selection decision based on weight priority orders and IRTWTCTs alternatives selection in ASC networks. The comparison of FAHP and FAHP-FTOPSIS approaches to evaluate the integrated framework develop in RFIDSVAs mechanisms and IRTWTCTs alternatives selection decisions in Indian multi-tier ASC networks.

The result found that the FAHP-FTOPSIS approaches have used to prioritizing the RFIDSVA mechanism selection weights and also identify the IRTWTCTs alternatives ranking preferences order in apparel SCM. The comparison between the FAHP and FAHP-FTOPSIS approach to quantitative assessments from RFIDSVA mechanisms and IRTWTCTs alternatives selection decisions, which enable them SC agility potential across multi-tier visibility in ASC networks. ASC stakeholders can be benefited by techno-economic feasibility decisions, RFID-enabled shop floor activities, multi-tags ownerships transfer in SCs and knowledge-based cryptography tags/items separation in SCs.

The research work has considered only five RFIDSVA mechanisms and also three integration of RFIDTWTCTs alternatives in multi-tier ASC. The strategic competitive advantages are achieved by RFID-enabled break-even tags price decisions and also techno-economic feasibility decision by contractual design multi-tier SC stakeholder’s involvements.

The pilot project study explores that the quantitative assessment decision has based on RFID-enable techno-economic feasibility in ASCs. Stakeholders can be benefited by inventory control of the financial losses, reducing the inventory inaccuracies and multi-tags ownership transfer within trusted third-party traceability in ASC networks.

This study explores the RFID-enabled apparel SC process and activities visibility (natural fibre’s fibre producer, fibre dyeing producer, yarn spinning producer, knitting and finishing producer).

This paper aims to introduce a novel structure for the physical internet (PI)–enabled sustainable supplier selection and inventory management problem under uncertain environments.

To address hybrid uncertainty both in the objective function and constraints, a novel interactive hybrid multi-objective optimization solution approach combining Me-based fuzzy possibilistic programming and interval programming approaches is tailored.

Various numerical experiments are introduced to validate the feasibility of the established model and the proposed solution method.

Due to its interconnectedness, the PI has the opportunity to support firms in addressing sustainability challenges and reducing initial impact. The sustainable supplier selection and inventory management have become critical operational challenges in PI-enabled supply chain problems. This is the first attempt on this issue, which uses the presented novel interactive possibilistic programming method.