Behavioral analyses of retailers’ ordering decisions

The main objective I pursue in this thesis is to better understand how different factors may independently and in combination influence retailers' ordering decisions under different supply chain structures (single agent and multi agent), different demand uncertainty (deterministic and stochastic), and different interaction among retailers (no interaction, competition and cooperation). I developed three different studies where I build on different formal management model and then run multiple behavioral studies to better understand subjects’ behavior. The first study analyzes order amplification in a single-supplier single-retailer supply chain. I used a behavioral experiment to test retailers’ orders under different ordering delays and different times to build supplier’s capacity. Results provide (i) a better understanding of the endogenous dynamics leading to retailers’ ordering amplification, and (ii) a description of subjects’ biases and deviation from optimal trajectories; despite subjects have full information about the system structure. The second study analyzes how order amplification can also take place when there is fierce retailer competition and limited supplier capacity. I study how different factors (different time to build supplier capacity, different levels of competition among retailers, different magnitudes of supply shortage and different allocation mechanisms) may independently and in combination influence retailers’ order in a system with two retailers under supply competition. Results show that (i) the bullwhip effect persists even when subjects do not have incentives to deviate, (ii) subjects amplify their orders in an attempt to build an unnecessary safety stock to respond to potential deviations from the other retailers, and (iii) retailers’ underperformance varies with the allocation mechanism used by the supplier. In the last study, I analyze retailers’ orders in a system where there is uncertainty in the final customer demand. I experimentally explore the effect of transshipments among retailers in a single-supplier multi-retailer supply chain. Specifically, I explore retailers’ orders under different profit and communication conditions. In addition, I integrate analytical and behavioral models to improve supply chain performance. Results show that (i) the persistence of common biases in a newsvendor problem (pull-to-center, demand chasing, loss aversion, psychological disutility), (ii) communication could improve coordination and may reduce demand chasing behavior, (iii) supply chain performance increases with the use of behavioral strategies embedded within a traditional optimization model, and (iv) dynamic heuristics improve overall coordination, outperforming a simple Nash Equilibrium strategy

Online Decision Making for Trading Wind Energy

This paper proposes and develops a new algorithm for trading wind energy in electricity markets, within an online learning and optimization framework. In particular, we combine a component-wise adaptive variant of the gradient descent algorithm with recent advances in the feature-driven newsvendor model. This results in an online offering approach capable of leveraging data-rich environments, while adapting to non-stationary characteristics of energy generation and electricity markets, and with a minimal computational burden. The performance of our approach is analyzed based on several numerical experiments, showing both better adaptability to non-stationary uncertain parameters and significant economic gains

Decision Making and the Price Setting Newsvendor: Experimental Evidence

We present an experimental study of the price-setting newsvendor problem, which extends the traditional framework by allowing the decision maker to determine both the selling price and the order quantity of a given item. We compare behavior under this model with two benchmark conditions where subjects have a single decision to make (price or quantity). We observe that subjects deviate from the theoretical benchmarks when they are tasked with a single decision. They also exhibit anchoring behavior, where their anchor is the expected demand when quantity is the decision variable and is the initial inventory level when price is the decision variable. When decision makers set quantity and price concurrently, we observe no significant difference between the normative (i.e., expected profit-maximizing) prices and the decision makers' price choices. Quantity decisions move further from the normative benchmarks (compared to when subjects have a single decision to make) when the ratio of cost to price is less than half. When this ratio is reversed, there is no significant difference between order levels in single- and multi-task settings. In the multidecision framework, we also observe a tendency to match orders and expected demand levels, which subjects can control using prices. © 2016 Decision Sciences Institute

COOPERATION OR COMPETITION: A STUDY OF SOCIAL CAPITAL AND PRODUCTION DECISION UNDER POTENTIAL VERTICAL COMPETITION

Since the 2000s when retailers recognised the huge market potential, the growth of private labels has been unstoppable worldwide. As a result of the recession of national brands, manufacturers are in a relatively weaker position when dealing with large retailers. The relationship between manufacturers and retailers has transformed from pure cooperation to a delicate balance of cooperation and competition. Yet, how such a balance influences supply chain dynamics is an intriguing and overdue issue. This thesis explores the influence of social capital over manufacturers’ perceptions regarding their retailers’ trustworthiness in the presence of potential vertical competition, as well as the consequential performance from the perspective of cognitive abilities. Data was collected through an online scenario-based role play (SBRP) experiment, where 371 participants were recruited and put in three groups. In each group, participants were provided with a scenario depicting the product substitution level between a newly launched private label and a national brand. The data was analysed statistically to test the hypotheses. The results identify relational capital as the most influential dimension of social capital in suppressing manufacturer’s perception of opportunistic information sharing behaviour from retailers, and suggest that such suppression is moderated by the level of product substitution between private labels and national brands. This thesis has reference value to academia by looking into the overlapping issues of supply chain management and marketing and providing empirical evidence of the influences induced by the introduction of private labels. It also benefits industry, especially manufacturers, by giving a brief standard regarding whether to cooperate or compete when faced with potential vertical competition with retailers

Effective judgmental forecasting in the context of fashion products

We study the conditions that influence judgmental forecasting effectiveness when predicting demand in the context of fashion products. Human judgment is of practical importance in this setting. Our goal is to investigate what type of decision support, in particular historical and/or contextual predictors, should be provided to human forecasters to improve their ability to detect and exploit linear and nonlinear cue-criterion relationships in the task environment. Using a field experiment on new product forecasts in the music industry, our analysis reveals that when forecasters are concerned with predictive accuracy and only managerial judgments are employed, providing both types of decision support data is beneficial. However, if judgmental forecasts are combined with a statistical forecast, restricting the decision support provided to human judges to contextual anchors is beneficial. We identify two novel interactions demonstrating that the exploitation of nonlinearities is easiest for human judgment if contextual data are present but historical data are absent. Thus, if the role of human judgment is to detect these nonlinearities (and the linearities are taken care of by some statistical model with which judgments are combined), then a restriction of the decision support provided would make sense. Implications for the theory and practice of building decision support models are discussed

Addressing the sample size problem in behavioural operational research: simulating the newsvendor problem

Laboratory-based experimental studies with human participants are beneficial for testing hypotheses in behavioural operational research. However, such experiments are not without their problems. One specific problem is obtaining a sufficient sample size, not only in terms of the number of participants but also the time they are willing to devote to an experiment. In this paper, we explore how agent-based simulation (ABS) can be used to address the sample size problem and demonstrate the approach in the newsvendor setting. The decision-making strategies of a small sample of individual decision-makers are determined through laboratory experiments. The interactions of these suppliers and retailers are then simulated using an ABS to generate a large sample set of decisions. With only a small number of participants, we demonstrate that it is possible to produce similar results to previous experimental studies that involved much larger sample sizes. We conclude that ABS provides the potential to extend the scope of experimental research in behavioural operational research

Behavioral Implications of Demand Perception in Inventory Management

The newsvendor problem is one of the rudimentary problems of inventory management with significant practical consequences, thus receiving considerable attention in the behavioral operational research literature. In this chapter, we focus on how decision makers perceive demand uncertainty in the newsvendor setting and discuss how such perception patterns influence commonly observed phenomena in order decisions, such as the pull-to-center effect. Drawing from behavioral biases such as over precision, we propose that decision makers tend to perceive demand to be smaller than it actually is in high margin contexts, and this effect becomes more pronounced with increases in demand size. The opposite pattern is observed in low margin settings; decision makers perceive demand to be larger than the true demand, and this tendency is stronger at lower mean demand levels. Concurrently, decision makers tend to perceive demand to be less variable than it actually is, and this tendency propagates as the variability of demand increases in low margin contexts and decreases in high margin contexts. These perceptions, in turn, lead to more skewed decisions at both ends of the demand spectrum. We discuss how decision makers can be made aware of these biases and how decision processes can be re-designed to convert these unconscious competencies into capabilities to improve decision making

Behavioral Operations Management: A Review of the Field

Behavioral operations management (BOM) is one of the new areas in operations management. In the past 12 years, the field has made huge progress and researchers have become interested in this new perspective to solving operational problems. BOM is now one of the major subfields of operations management. In this paper, we examine and categorize areas of BOM based on the mainstream literature. Key areas include behavioral issues in new product development and project management, quality management, production management, inventory management, service operations, and forecasting. Studies in each area are divided into three subcategories, including OM context, individual attributes, heuristics, and biases, and individual differences. In OM context category, feedback and reward, training, work monitoring, teamwork and group decision making, goal setting, task assignment, and flexibility are among the main topics. In individual attributes, heuristics, and biases category, sunk cost effect and escalation of commitment, endowment effect, overprecision bias, planning fallacy, pull-to-center effect, anchoring and insufficient adjustment, and misperceptions of feedback are mainly discussed. In individual differences, analytic thinking and system thinking are mainly studied. New areas for research are suggested in each related section and are summarized in future directions and conclusion sections. In contexts such as new product development, project management, and inventory management, a shift to finding solution to performance improvement is beneficial instead of focusing on heuristics and biases and considering them as a deficiency in human decision making. Regarding individual differences category, a shift toward attributes other than cognitive abilities, such as global processing, creative thinking, and design thinking are recommended

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