Behavioral considerations of automation (joint work Iman Moosavi and Jan Fransoo)
This work explores human-algorithm interaction in a planning context, focusing on interactions resulting from task automation. Unlike typical augmentation interactions —where algorithms provide recommendations to human decision-makers for a single task— we investigate scenarios in which a human and an algorithm collaborate across sequential decision-making tasks. To examine this interaction, we designed an experiment involving a demand-forecasting task followed by a newsvendor inventory planning task. Our findings show that the behavior of both human planners and human forecasters change when they interact with an algorithm versus a human taking the other role. Furthermore, we show that automating the inventory planning task does not lead to an overall increase in profit due to the changes in the behavior of human demand forecasters who provide demand information for the planning task. Our findings highlight that when deploying algorithms in decision-making tasks, managers should consider not only the improvements within the specific task for which the algorithm is implemented, but also the behavior of human decision-makers in other parts of the organization who are responsible for related tasks.
Supply Chain Planning Decisions and AI recommendations (joint work with Lijia Tan and Willem van Jaarsveld)
Sophisticated AI algorithms are often employed in practice to help supply chain planners make decisions (e.g., forecasting, ordering, production). How are these algorithmic suggestions used by humans and do decision makers learn from AI tools? We look at a complex supply chain decision setting with uncertainties, delays, and interrelated decisions. We conduct incentivized lab experiments where decision makers have a sophisticated AI tool avaible, based on a neural network algorithm, which can significantly improve operational outcomes. Decision makers largely use the black-box algorithmic suggestions but in most of the cases modify them. Trust in AI recommendations depends on the type of decision (i.e., order, assembly, transport), the decision maker’s task experience, and their general attitude towards AI tools.
Authentication Service as a Signal of Quality on Second-Hand Platforms (joint work with Masoud Fazlavi and Chong Zhang)
The potential of second-hand product markets to decrease the negative environmental impact of production is high. One obstacle to developing such online markets is consumers’ uncertainty about products' quality. This work investigates the potential of an authentication service, offered by the platform, to mitigate such quality uncertainty for second-hand products. Using a signaling model, we find that a product authentication service offered as an option at a cost can act as a reliable signal of high-quality sellers. This service increases the high-quality sellers’ probability of sale and also their profits, making the platform more attractive for such sellers.
Regulatory Focus and Emotions in Supply Chain Coordination (joint work with Santiago Kraiselburd, Konstantina Tzini and Priscilla Rodriguez)
Regulatory focus orientation affects people’s emotions, thoughts and actions. We conjecture that beyond an individual’s regulatory fit to a task, the fit between decision makers in a supply chain may also play a role in achieving coordination. We study a repetitive capacity matching game under information asymmetry and information sharing (Hyndman, Kraiselburd and Watson, 2013) under different profit scenarios and observe how regulatory fit, emotions and decisions interact.
Service-level agreements and supplier capacity decisions: the impact of incentive framing on trust (joint work Wendy van der Valk)
The goal of this project is to study the effect of incentive framing on the development of trust in supply chains and shed light on the underlying mechanism (e.g., violation of expectations, attributions of benevolence and emotions). We focus on the framing of service-level-agreements (bonus versus reward), and study their effect on trust development in the context of demand information sharing between a buyer and a supplier who sets capacity.