An Experimental Comparison of News Vending and Price Gouging

The newsvendor problem is a workhorse model in operation management research. We introduce a related game that operates in the price dimension rather than the inventory dimension: the price gouging game. Using controlled laboratory experiments, we compare news vending and price gouging behavior. We replicate the standard pull-to-center effect for news vending and find that the equivalent pattern occurs with price gouging. Further, we find that the pull-to-center is asymmetric both for newsvendors and price gougers. More broadly, the experimental results reveal that choices are similar across the theoretically isomorphic games, suggesting that observed behavior in newsvendor experiments is representative of a broader class of games and not driven by the operations context that is often used in newsvendor experiments. Finally, we do not find evidence that behavior in these games is systemically affected by sex, risk attitude, or cognitive reflection

Opportunity Loss Minimization and Newsvendor Behavior

To study the decision bias in newsvendor behavior, this paper introduces an opportunity loss minimization criterion into the newsvendor model with backordering. We apply the Conditional Value-at-Risk (CVaR) measure to hedge against the potential risks from newsvendor’s order decision. We obtain the optimal order quantities for a newsvendor to minimize the expected opportunity loss and CVaR of opportunity loss. It is proven that the newsvendor’s optimal order quantity is related to the density function of market demand when the newsvendor exhibits risk-averse preference, which is inconsistent with the results in Schweitzer and Cachon (2000). The numerical example shows that the optimal order quantity that minimizes CVaR of opportunity loss is bigger than expected profit maximization (EPM) order quantity for high-profit products and smaller than EPM order quantity for low-profit products, which is different from the experimental results in Schweitzer and Cachon (2000). A sensitivity analysis of changing the operation parameters of the two optimal order quantities is discussed. Our results confirm that high return implies high risk, while low risk comes with low return. Based on the results, some managerial insights are suggested for the risk management of the newsvendor model with backordering

Explaining retailer's ordering behavior in supply chain experiments

In this thesis, we study the retailer’s ordering behavior in a manufacturer-retailer supply chain where the retailer faces the newsvendor problem. Analytical literature predicts that the retailer will use the critical ratio solution when determining her order quantity from the manufacturer. When real human beings play the roles of manufacturer and retailer in controlled experiments, however, the retailer decisions are observed to deviate from these theoretical predictions. The deviations are due to (1) individual biases and heuristics, (2) the strategic interaction between the two players. Literature has studied the effects of individual biases and heuristics using simple newsvendor experiments. However, very few researchers have conducted experiments where both sides are human. This extension is valuable because supply chain relations in practice depend on human-to-human interaction between managers. In this study, using data from the supply chain experiments of Şahin and Kaya (2011), we aim to answer the following questions: (1) Do retailer subjects follow the heuristics observed in simple newsvendor experiments? (2) What are the factors affecting retailer decisions? (3) Do retailer subjects learn to make better decisions over time? We find that retailer behavior is highly heterogeneous. While there is support for the use of decision heuristics at the aggregate level, we have mixed results at individual level. Likewise, the factors that affect retailer order quantity are found to be subject-dependent. The extent of learning is also found to differ from subject to subject

Individual goals and social preferences in operational decisions

Purpose: The purpose of this paper is to develop propositions explaining the influence of individual goals and social preferences on human decision making in transport planning. The aim is to understand which individual goals and social preferences planners pursue and how these influence planners’ decisions. Design/methodology/approach: Propositions are developed based on investigation of decision making of transport planners in a Dutch logistics service provider using multiple data collection methods. Findings: The study shows how decision making of transport planners is motivated by individual goals as well as social preferences for reciprocity and group identity. Research limitations/implications: Further research including transaction data analysis is needed to triangulate findings and to strengthen conclusions. Propositions are developed to be tested in future research. Practical implications: Results suggest that efforts to guide planners in their decision making should go beyond traditional (monetary) incentives and consider their individual goals and social preferences. Moreover, this study provides insight into why transport planners deviate from desired behaviour. Originality/value: While individual decision making plays an essential role in operational planning, the factors influencing how individuals make operational planning decisions are not fully understood

Behavioral perspectives on risk sharing in supply chains

Over the past decade, we have witnessed the emergence of a vast body of literature contributing to our understanding of how supply chains should be designed and executed from a normative perspective. Along the way, the gap between ever-more sophisticated theory and industrial reality increased. A growing stream of recent research relaxes the overly simplistic assumptions on human behavior commonly made in supply chain models. This thesis contains a set of research papers on human behavior, casted in a unified framework of supply chain inventory risk management

An Investigation into Factors Affecting the Chilled Food Industry

With the advent of Industry 4.0, many new approaches towards process monitoring, benchmarking and traceability are becoming available, and these techniques have the potential to radically transform the agri-food sector. In particular, the chilled food supply chain (CFSC) contains a number of unique challenges by virtue of it being thought of as a temperature controlled supply chain. Therefore, once the key issues affecting the CFSC have been identified, algorithms can be proposed, which would allow realistic thresholds to be established for managing these problems on the micro, meso and macro scales. Hence, a study is required into factors affecting the CFSC within the scope of Industry 4.0. The study itself has been broken down into four main topics: identifying the key issues within the CFSC; implementing a philosophy of continuous improvement within the CFSC; identifying uncertainty within the CFSC; improving and measuring the performance of the supply chain. However, as a consequence of this study two further topics were added: a discussion of some of the issues surrounding information sharing between retailers and suppliers; some of the wider issues affecting food losses and wastage (FLW) on the micro, meso and macro scales. A hybrid algorithm is developed, which incorporates the analytic hierarchical process (AHP) for qualitative issues and data envelopment analysis (DEA) for quantitative issues. The hybrid algorithm itself is a development of the internal auditing algorithm proposed by Sueyoshi et al (2009), which in turn was developed following corporate scandals such as Tyco, Enron, and WorldCom, which have led to a decline in public trust. However, the advantage of the proposed solution is that all of the key issues within the CFSC identified can be managed from a single computer terminal, whilst the risk of food contamination such as the 2013 horsemeat scandal can be avoided via improved traceability

Exploring the contribution of individual differences and planning policy parameters to demand planning performance.

Demand planning (DP) is important for business performance. DP depends both on managers and on supporting systems. Managers are known to increase uncertainty by systematically overriding the systems and making unnecessary judgemental adjustments. This is a behavioural problem. Systems are assumed to be represented by different policies and individual differences by measurable traits and characteristics. The contribution of individual differences and policy parameters to DP performance is not clear. A framework is proposed based on the cumulative prospect theory (CPT) and myopic loss aversion (MLA). Methodology of decision making experiment based on the newsvendor is used. Individual differences are collected using previously validated psychometric scales and demographic questions. The sample (N=339) includes three main groups: professional planners (N=84), naïve students (N=166), logistics and supply chain management (L&SCM) students (N=56). The MLA hypothesis is supported. Longer planning horizons (less frequent decisions) outperforms short planning horizons. Regarding individual differences, only experience/knowledge and naïve interventionism are significant predictors of DP performance. L&SCM students with theoretical knowledge but without practical experience perform the best. No significant difference in performance is found between professional planners and naïve students. Naïve interventionism (plan instability) contributes negatively to DP performance. Personality (Big Five), impulsiveness, propensity to plan, decision-making style or demographics (e.g. age, sex, and years of experience or managerial level) are not significant for DP performance. The view that there is a ‘right’ mind-set (personality) to be a good planner is challenged. DP policy can offset individual differences. A MLA informed policy can reduce uncertainty introduced by behaviour. System restrictiveness (binding policy for long commitment) outperforms decisional guidance (non-binding policy for optional commitment). This is one of the first applications of CPT and MLA to DP decisions