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Five hundred financial executives from North American companies were surveyed by means of a mailed questionnaire to gain a view from outside the operations functions of the basis on which aggregate inventory decisions are taken. The response indicated that more functions than might have been expected were involved in the process of determining inventory levels and, partly because of this, policy tended to be of a shorter rather than longer term nature.

An integrated model for distribution network design is proposed which explicitly represents the required level of customer service.

The success of a supply chain is highly reliant on effective inventory and ordering decisions. This paper systematically reviews and analyzes the literature on inventory ordering decisions conducted using behavioral experiments to inform the state-of-the-art.

This paper presents the first systematic review of this literature. We systematically identify a body of 101 papers from an initial pool of over 12,000.

Extant literature and industry observations posit that decision makers often deviate from optimal ordering behavior prescribed by the quantitative models. Such deviations are often accompanied by excessive inventory costs and/or lost sales. Understanding how humans make inventory decisions is paramount to minimize the associated consequences. To address this, the field of behavioral operations management has produced a rich body of research on inventory decision-making using behavioral experiments. Our analysis identifies primary research clusters, summarizes key learnings and highlights opportunities for future research in this critical decision-making area.

The findings will have a significant impact on future research on behavioral inventory ordering decisions while informing practitioners to reach better ordering decisions.

Previous systematic reviews have explored behavioral operations broadly or its subdisciplines such as judgmental forecasting. This paper presents a systematic review that specifically investigates the state-of-the-art of inventory ordering decisions using behavioral experiments.

The paper provides a comprehensive overview of the biases in inventory decisions, under the umbrella of behavioural operations, considering research findings that used experimental methods. Research in this field has gained traction but, to the best of our knowledge, review articles that summarize these research findings are scarce. Hence, there is a need to synthesize the anomalies and biases reported in inventory decision-making literature to gain a more integrated understanding.

This study reviews themes relevant to inventory and behavioural operations management from the articles published in recognized top-tier journals during the period between 2000 and 2020 with an aim to build a classification framework. Further, using a systematic review procedure, the relevant research studies are divided into sub-sections and appropriate search strategies are adopted to pleat more information on inventory ordering biases.

This study presents a classification framework by highlighting the factors influencing the biases in inventory decisions and describes the effects of utility preferences on the decision-making behaviour. It highlights the inventory ordering pattern under unconventional settings and also for different supply chain settings. This systematic review helps in identifying the research gap and in giving directions for future researchers.

The study presents a systematic review and detailed analysis of the research in inventory decision making through a behavioural lens. The study shows a clear direction of progress over the years, and implies new directions for looking beyond placing orders and for moving towards a more integrated approach while making supply chain decisions. It will be useful for researchers and practitioners working on newsvendor decisions, supply chain contracts, behavioural economics, behavioural operations management, bounded rationality theory and experimental economics.

Logisticians must make strategic level decisions in order to manage uncertainty, customer service and cost. This research explores the relationships between three strategic level decisions and selected product, operational and demand variables. The three strategic decisions are: make to order vs make to stock; push vs pull inventory deployment; and inventory centralization vs decentralization. The data used to study the relationships were collected in an international environment and analyzed with correlation analysis and logistic regression. Results suggest that the three strategic decisions are each explained by specific product, operational and demand variables.

The purpose of this paper is to describe the issues, tradeoffs, and models relating to two important sets of problems that arise in supply chain management – complexities in extended supply chains and network coordination in globally dispersed supply chains. This paper highlights the role of logistics in enhancing the competitiveness of firms that operate a global supply chain.

The methodology used in this paper encompasses conceptual research and detailed literature review of key issues.

This review indicates that the key challenges faced by supply chain managers due to extended supply chains are non‐stationary demand, variability propagation, and inventory imbalances. For network coordination managers must determine the role of facilities in a global network, identify the optimal location and capacity of facilities as well as role of consolidation hubs. For the above challenges, the tradeoffs in terms of four key drivers of supply chain performance – transportation, inventory, information, and facilities and relate these to key measures of supply chain performance are described. Important directions for future research are also identified.

Test cases are needed to validate and refine the framework presented. Developing case studies that gather appropriate data to test out the models described would be important.

Companies with a global supply chain as well as third party logistics companies will find the framework presented in this paper very useful.

A new integrated framework that incorporates key decision issues like complexities of extended supply chains and network coordination into the firm's decision making has been presented. This has not been reported in previous research.

How should a firm decide which of four choices – i.e. inventory speculation, inventory postponement, inventory consignment, and reverse inventory consignment – is most appropriate to adopt for a given purchased item in a particular context? This paper seeks to identify and explain the critical factors that drive this decision.

By conducting a review of relevant literature and deriving anecdotal observations from four case studies.

This decision is influenced by three factors – customer demand or usage requirements, nature of the supply line and bargaining power of a firm relative to the supplier.

From the perspective of science, the conduct of both empirical research to augment the reported anecdotal evidence and conceptual research along a number of directions (e.g. to juxtapose the research findings in existing theories, to examine variations of the four “pure” inventory management approaches, or to consider the vantage point of the supplying firm rather than that of the buying firm) is encouraged.

As for the perspective of practice, the critical factors serve as the basis for the articulation of a decision framework – one that should help firms not only pin‐point the most relevant issues concerning a particular purchased item but also to avoid the costly mistake of selecting a less‐than‐ideal inventory management approach.

These critical factors, along with the proposed decision framework, extend prior research which has focused only on choosing between the inventory speculation approach and the inventory postponement approach.

Planning inventories for emergency supplies such as bottled water, non‐perishable foods, batteries, and flashlights can be challenging for retailers situated within the projected path of a severe storm. The retailer's inventory decisions are complicated by the inherent volatility of storm forecasts and the corresponding demand predictions. The purpose of this paper is to explore both proactive and reactive inventory control policies within the context of probable pre‐storm demand surge for a fast‐moving emergency supply item, and identify the conditions that are most conducive to each strategy according to the minimax decision criterion.

The inventory system is formulated based on an underlying economic order quantity framework. Minimax decision rules are developed analytically. Sensitivity analysis is facilitated by both analytic and numerical methods.

The conditions that are conducive to a proactive ordering strategy are limited supplier flexibility, acute demand surge, and exorbitant reorder costs; otherwise, the minimax inventory control policy is given by a reactive ordering strategy.

The above‐mentioned findings are based on a stylized inventory model characterized by assumptions that are consistent with the academic literature. In order to assess the implications of these results in practice, the model should be extended according to the relevance of each assumption to specific real‐world inventory systems.

Householders preparing for probable evacuation or post‐storm power outages typically overwhelm grocery and home improvement stores during a brief period prior to the impact of an approaching weather system. This phenomenon triggers a temporary spike in demand for several stock keeping units, which is oftentimes accompanied by pervasive inventory shortages that proliferate community vulnerability and engender a sense of disarray throughout the local populace. Effective inventory management of emergency supply items during this period can help alleviate some of these social dilemmas.

Few academic publications address inventory management from the perspective of humanitarian relief. Among existing studies, the emphasis has been coordination of emergency supplies for post‐disaster relief and recovery activities. This paper appears to be the first academic investigation of an inventory system driven by the pre‐storm demand surge for emergency supplies that typically occurs in the presence of an ominous and potentially devastating weather system. Additionally, this study conceivably represents the first minimax distribution free approach to inventory control within the context of humanitarian logistics and disruption management.

This paper aims to develop efficient decision support tools for a firm’s environment protection by using greening effort while yet improving profitability by utilizing pricing and inventory decisions with discount consideration.

This study proposed a mathematical model for price- and greening effort-dependent demand rate with discount considerations. Later, the mathematical model is extended to the situation in which the demand rate is also dependent on the stock level, in addition to the price and greening effort. Efficient solution methodologies are developed for finding the optimal solution to the proposed models.

Simple yet elegant models are proposed to mimic real-life applications. Structural properties of the models are explored to outline efficient algorithms with quantity discounts.

The paper considers monopoly and assumes deterministic demand. Only a more commonly observed all-units discount scheme is studied.

The models provide decision support tools for firms in pursuit of joint profit maximization and environment consciousness goals.

The study develops environment-friendly approaches for inventory management and improving the profitability alike.

This study is among the first to consider environmental protection with an investment in greening effort along with inventory management and pricing decision. The study also explored the effect of all-unit quantity discounts.

Aims to explain the driving forces for networked inventory management. Discusses major developments with respect to customer requirements, networked organizations and networked inventory management. Presents high level specifications of networked inventory management information systems (NIMISs). Reviews some decision systems for inventory management, and compares traditional inventory management to networked inventory management. Uses these insights to outline NIMISs for several types of inventory management decision systems. Summarizes the results of the study, and provides an outlook on further research.