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The traditional newsvendor model has focused on deriving the optimal order quantity that minimises the balance between stocking too much or too less number of products. However, the managers make inventory decisions based on intuitions and shortcuts, which may involve human errors and biases. The effect of cognitive biases and heuristics influencing the inventory ordering decisions in newsvendor settings is highlighted. The advancement of research associated to the newsvendor biases is reviewed to appreciate the behavioral aspects of the minds underlying this process.

The use of experimental and non-experimental methods to investigate the ordering behaviour of newsvendors is described and we present a framework of the existing literature and highlight the research gaps to point to future research possibilities and priorities.

The proposed framework gives a systematic approach to confirm the existence of a substantial scope of research opportunities and points to specific areas for further research. It synthesizes the existing results of behavioral newsvendor research and will act as a key reference paper. In addition, it will help the practitioners and software tool vendors to comprehend the behavioral perspective of newsvendor preferences and design strategies to mitigate this effect. The insights will be helpful for academicians, researchers and practitioners working in the areas of experimental economics, behavioral economics, behavioral operations, bounded rationality theory, newsvendor modelling and supply chain contracts.

A summary of literature in this evolving area of research is very scarce. Considering the impact of behavioral economics on managerial decisions in the contemporary world, it is highly important to have an educational summary which can act as a tool for the practitioners and researchers in the area of behavioral operations management.

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 purpose of this paper is to discuss the role of reference effect on newsvendor’s decision behavior in a market with strategic customers and work out the newsvendor’s optimal pricing policy and ordering quantity.

This study utilizes the prospect theory and strategic customer framework to analyze the decision-making behavior on the newsvendor’s optimal pricing policy and ordering quantity. The paper further presents an extension of newsvendor model and provides the model’s properties. The paper finally analyzes the results with various parameters on the model and reports on the insights generated by the model.

The paper indicates that the ordering quantity is not altered with the changing proportion of strategic customers and myopic customers, but the ordering quantity and the pricing strategy are influenced in terms of newsvendor’s reference effect, loss aversion, product cost, and salvage price.

The research findings have important implications for decision makers. Previous researches have studied the incomplete rationality newsvendor’s decision-making behavior mainly by analyzing the vendor’s risk preferences or loss aversion, but the effect of reference point also plays an important role in analyzing the decision-maker’s behavior. The paper provides the optimal pricing policy and ordering quantity with the reference effect considering the strategic customers behavior. This model is also a valid complementarity to behavioral operations management research area.

The paper examines the role of reference effect in newsvendor problem with the strategic customers and analyzes the impact of parameters such as loss aversion on the newsvendor’s decision behavior.

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.

The purpose of this paper is to investigate cultural and individual differences in newsvendor decision making.

The online experiment, programmed in the PHP scripting language, had 107 participants: local managers of four large, well-known and supply chain–intensive firms in China (Lenovo, Shenhua, CMST and GM).

The authors find that, as compared with American subjects, Chinese subjects engage in more demand chasing, order quantities that are closer to the mean demand, have a lower expected profit and exhibit greater variance in order quantities. However, these observations may not hold when the cross-cultural comparison is conducted for each pair of ethnic subgroups whose members have the same cognitive reflection test score, a measure of individual differences. Moreover, cultural differences also affect how individual differences manifest in newsvendor decisions.

The authors findings have important implications for employee selection, training and management in any cross-cultural business environment.

Little attention has been paid, in the behavioural operations literature, to individual differences and how they interact with culture. This paper is the first to examine the interaction effects of cultural and individual differences in newsvendor decisions, and it highlights an important research area that is currently understudied in operations management.

Contracting is an important issue in supply chain management. In this paper, the authors aim to discuss and compare the manufacturer's contracting options when the retailer faces a traditional newsvendor problem with a fixed retail price: a wholesale price only contract, a wholesale price discount contract, a returns policy contract, and a returns policy with the wholesale price discount contract. The paper also aims to examine how these contracting options affect decisions of the manufacturer and the retailer, as well as the supply chain efficiency.

Models are developed based on the manufacturer's four contracting options. The manufacturer's optimal wholesale prices have been obtained. The ordering decisions of the retailer are discussed in each of the manufacturer's four contracting options. The paper also uses numerical examples to illustrate the author's managerial insights and results.

As compared to the wholesale price only contract, it is found that implementing a wholesale price discount policy effectively encourages the retailer to order more product and enhances the retailer's profit at the expense of lowering the manufacturer's profit. It is also found that when the manufacturer offers a returns policy and if this policy cannot enhance the retailer's profit, a returns policy with the wholesale price discount contract can lead to a win‐win situation for both the manufacturer and the retailer.

The research provides managerial insights on how different contracts affect decisions and efficiency of the supply chain.

The purpose of this paper is to investigate the impact of demand uncertainty on inventory turnover performance through empirical modeling. In particular the authors use the inaccuracy of quarterly sales forecasts as a proxy for demand uncertainty and study its impact on firm-level inventory turnover ratios.

The authors use regression analysis to study the effect of various measures on inventory performance. The authors use a sample financial data for 304 publicly listed US retail firms for the 25-year period from 1985 to 2009.

Controlling for the effects of retail segments and year, it is found that inventory turnover is negatively correlated with mean absolute percentage error of quarterly sales forecasts and gross margin and positively correlated with capital intensity and sales surprise. These four variables explain 73.7 percent of the variation across firms and over time and 93.4 percent of the within-firm variation in the data.

In addition to conducting an empirical investigation for the sources of variation in a major operational metric, the results in this study can also be used to benchmark a retailer’s inventory performance against its competitors.

The authors develop a new proxy to measure the demand uncertainty that a firm faces and show that this measure may help to explain the variation in inventory performance.

Procurement planning has always been a huge and challenging activity for business firms, especially in manufacturing. With government legislations about global concern over carbon emissions, the manufacturing firms are enforced to regulate and reduce the emissions caused throughout the supply chain. It is observed that procurement and logistics activities in manufacturing firms contribute heavily toward carbon emissions. Moreover, highly dynamic and uncertain business environment with uncertainty in parameters such as demand, supplier and carrier capacity adds to the complexity in procurement planning. The paper aims to discuss these issues.

This paper is a novel attempt to model environmentally sustainable stochastic procurement (ESSP) problem as a mixed-integer non-linear program. The ESSP optimizes the procurement plan of the firm including lot-sizing, supplier and carrier selection by addressing uncertainty and environmental sustainability. The model applies chance-constrained-based approach to address the uncertain parameters.

The proposed ESSP model is solved optimally for 30 data sets to validate the proposed ESSP and is further demonstrated using three illustrations solved optimally in LINGO 10.

The ESSP model simultaneously minimizes total procurement cost and carbon emissions over the entire planning horizon considering uncertain demand, supplier and carrier capacity.

The paper aims to explore how power and gender influence decision making in an operational and risky context.

The authors run a laboratory experiment. The experimental factors are power and operational profitability. Power is manipulated using an episodic priming task, while profitability, by changing a newsvendor-type product’s procurement cost. Participants’ risk attitude is captured using a risk lottery.

Participants deviate from the optimal order regardless of the power condition and their risk profile. Risk-seeking women order consistently more than risk-seeking men, which allow women to offer a higher service level. In the low-profit condition, men prefer to make more conservative decisions, which allow them to place orders that are closer to the economical benchmark, where both men’ induced power and the risk-seeking tendencies from both genders play a role. Behavioural models in the high-power condition explain the observed differences in ordering behaviours.

This paper provides behavioural research to explore how differences in power and gender, and their links with risky decision making, influence decision making in an uncertain operations management context, representing thus an important departure from mainstream studies.

Group buying (GB) is a shopping strategy through which customers obtain volume discounts on the products they purchase, whereas retailers obtain quick turnover. In the scenario of GB, the optimal discount strategy is a key issue because it affects the profit of sellers. Previous research has focused on exploring the price discount and order quantity with a fixed selling price of the product assuming that customer demand is uncertain (but follows a known distribution). This study aims to look at the same problem but goes further to examine the case where not only customer demand is certain but also the demand distribution is unknown.

In this study, optimal price discount and order quantity of a GB problem cast as a price-setting newsvendor problem were obtained assuming that the distribution of customer demand is unknown. The price–demand relationship is considered in addition form and product form, respectively. The bootstrap sampling technique is used to develop a solution procedure for the problem. To validate the usefulness of the proposed method, a simulated comparison of the proposed model and the existing one was conducted. The effects of sample size, demand form and parameters of the demand form on the performance of the proposed model are presented and discussed.

It is revealed from the numerical results that the proposed model is appropriate to the problem at hand, and it becomes more effective as sample size increases. Because the two forms of demand indicate restrictive assumptions about the effect of price on the variance of demand, it is found that the proposed model seems to be more suitable for addition form of demand.

This study contributes to the growing literature on GB models by developing a bootstrap-based newsvendor model to determine an optimal discount price and order quantity for a fixed-price GB website. This model can assist the sellers in making decisions on optimal discount price and order quantity without knowing the form of customer demand distribution.