Skip to main content
Working papers
ESMT Working Paper
ESMT Working Paper No. 19-02 (R3)
Işık Biçer, Florian Lücker, Tamer Boyaci (2021)
Subject(s)
Management sciences, decision sciences and quantitative methods; Product and operations management
Keyword(s)
Product proliferation, lead-time reduction, process redesign, delayed differentiation
Product proliferation occurs in supply chains when manufacturers respond to diverse market needs by trying to produce a range of products from a limited variety of raw materials. In such a setting, manufacturers can establish market responsiveness and/or cost efficiency in alternative ways. Delaying the point of the proliferation helps manufacturers improve their responsiveness by postponing the ordering decisions of the final products until there is partial or full resolution of the demand uncertainty. This strategy can be implemented in two different ways: (1) redesigning the operations so that the point of proliferation is swapped with a downstream operation or (2) reducing the lead times. To establish cost efficiency, manufacturers can systematically reduce their operational costs or postpone the high-cost operations. We consider a multi-echelon and multi-product newsvendor problem with demand forecast evolution to analyze the value of each operational lever of the responsiveness and the efficiency. We use a generalized forecast-evolution model to characterize the demand-updating process, and develop a dynamic optimization model to determine the optimal order quantities at different echelons. Using anonymized data of Kordsa Inc., a global manufacturer of advanced composites and reinforcement materials, we show that our model outperforms a theoretical benchmark of the repetitive newsvendor model. We demonstrate that reducing the lead time of a downstream operation is more beneficial to manufacturers than reducing the lead time of an upstream operation by the same amount, whereas reducing the upstream operational costs is more favorable than reducing the downstream operational costs. We also indicate that delaying the proliferation may cause a loss of profit, even if it can be achieved with no additional costs. Finally, a decision typology is developed, which shows effective operational strategies depending on product/market characteristics and process flexibility.

 


View all ESMT Working Papers in the ESMT Working Paper Series here. ESMT Working Papers are also available via SSRN, RePEc, EconStor, and the German National Library (DNB).

Pages
52
ISSN (Print)
1866–3494
Subject(s)
Management sciences, decision sciences and quantitative methods; Product and operations management; Technology, R&D management
Keyword(s)
Machine-learning, rational inattention, human-machine collaboration, cognitive effort
The rapid adoption of AI technologies by many organizations has recently raised concerns that AI may eventually replace humans in certain tasks. In fact, when used in collaboration, machines can significantly enhance the complementary strengths of humans. Indeed, because of their immense computing power, machines can perform specific tasks with incredible accuracy. In contrast, human decision-makers (DM) are flexible and adaptive but constrained by their limited cognitive capacity. This paper investigates how machine-based predictions may affect the decision process and outcomes of a human DM. We study the impact of these predictions on decision accuracy, the propensity and nature of decision errors as well as the DM's cognitive efforts. To account for both flexibility and limited cognitive capacity, we model the human decision-making process in a rational inattention framework. In this setup, the machine provides the DM with accurate but sometimes incomplete information at no cognitive cost. We fully characterize the impact of machine input on the human decision process in this framework. We show that machine input always improves the overall accuracy of human decisions, but may nonetheless increase the propensity of certain types of errors (such as false positives). The machine can also induce the human to exert more cognitive efforts, even though its input is highly accurate. Interestingly, this happens when the DM is most cognitively constrained, for instance, because of time pressure or multitasking. Synthesizing these results, we pinpoint the decision environments in which human-machine collaboration is likely to be most beneficial.

 

View all ESMT Working Papers in the ESMT Working Paper Series here. ESMT Working Papers are also available via SSRN, RePEc, EconStor, and the German National Library (DNB).

Pages
40
ISSN (Print)
1866–3494
ESMT Working Paper
ESMT Working Paper No. 18-04 (R1)
Caner Canyakmaz, Tamer Boyaci (2020)
Subject(s)
Management sciences, decision sciences and quantitative methods
Keyword(s)
Service operations, rational inattention, strategic customers, rational queueing, information costs, system throughput, social welfare
Problem description: Classical models of queueing systems with rational and strategic customers assume queues to be either fully visible or invisible while service parameters are known with certainty. In practice, however, people only have “partial information” on the service environment in the sense that they are not able to fully discern prevalent uncertainties. This is because assessing possible delays and rewards is costly as it requires time, attention, and cognitive capacity which are all limited. On the other hand, people are also adaptive and endogenously respond to information frictions. Methodology: We develop an equilibrium model for a single-server queueing system with customers having limited attention. Following the theory of rational inattention, we assume that customers optimize their learning strategies by deciding the type and amount of information to acquire and act accordingly while internalizing the associated costs. Results: We establish the existence and uniqueness of a customer equilibrium and delineate the impact of service characteristics and information costs. We numerically show that when customers allocate their attention to learn uncertain queue length, limited attention of customers improves throughput in a congested system that customers value reasonably highly, while it can be detrimental for less popular services that customers deem rather unrewarding. This is also reflected in social welfare if the firm's profit margin is high enough, although customer welfare always suffers from information costs. Managerial implications: Our results shed light on optimal information provision and physical design strategies of service firms and social planners by identifying service settings where they should be most cautious for customers' limited attention. Academic/practical relevance: We propose a microfounded framework for strategic customer behavior in queues that links beliefs, rewards, and information costs. It offers a holistic perspective on the impact of information prevalence (and information frictions) on operational performance and can be extended to analyze richer customer behavior and complex queue structures, rendering it a valuable tool for service design.

 

View all ESMT Working Papers in the ESMT Working Paper Series here. ESMT Working Papers are also available via SSRN, RePEc, EconStor, and the German National Library (DNB).

Pages
42
ISSN (Print)
1866–3494
ESMT Working Paper
ESMT Working Paper No. 16-04 (R3)
Frank Huettner, Tamer Boyaci, Yalçın Akçay (2018)
Subject(s)
Product and operations management
Keyword(s)
Discrete choice, rational inattention, information acquisition, non-uniform information costs, market inference
JEL Code(s)
D40, D80
Consumers often do not have complete information about the choices they face and therefore have to spend time and effort in acquiring information. Since information acquisition is costly, consumers trade-off the value of better information against its cost, and make their final product choices based on imperfect information. We model this decision using the rational inattention approach and describe the rationally inattentive consumer’s choice behavior when she faces alternatives with different information costs. To this end, we introduce an information cost function that distinguishes between direct and implied information. We then analytically characterize the optimal choice probabilities. We find that non-uniform information costs can have a strong impact on product choice, which gets particularly conspicuous when the product alternatives are otherwise very similar. There are significant implications on how a seller should provide information about its products and how changes to the product set impacts consumer choice. For example, non-uniform information costs can lead to situations where it is disadvantageous for the seller to provide easier access to information for a particular product, and to situations where the addition of an inferior (never chosen) product increases the market share of another existing product (i.e., failure of regularity). We also provide an algorithm to compute the optimal choice probabilities and discuss how our framework can be empirically estimated from suitable choice data.

 

View all ESMT Working Papers in the ESMT Working Paper Series here. ESMT Working Papers are also available via SSRN, RePEc, EconStor, and the German National Library (DNB).

Pages
52
ISSN (Print)
1866–3494
ESMT Working Paper
ESMT Working Paper No. 16-02
Tamer Boyaci, Vedat Verter, Michael R. Galbreth (2016)
Subject(s)
Product and operations management
Keyword(s)
Reusability, reuse, innovation, Markov decision process
Many industries, including consumer electronics and telecommunications equipment, are characterized with short product life-cycles, constant technological innovations, rapid product introductions, and fast obsolescence. Firms in such industries need to make frequent design changes to incorporate innovations, and the effort to keep up with the rate of technological change often leaves little room for the consideration of product reuse. In this paper, we study the design for reusability and product reuse decisions in the presence of both a known rate of incremental innovations and a stochastic rate of radical innovations over time. We formulate this problem as a Markov Decision Process. Our steady-state results confirm the conventional wisdom that a higher probability of radical innovations would lead to reductions in the firm's investments in reusability as well as the amount of reuse the firm ends up doing. Interestingly, the design for reusability decreases much more slowly than the actual reuse. We identify some specific scenarios, however, where there is no tradeoff between the possibility of radical innovations and the firms reusability and reuse decisions. Based on over 425,000 problem instances generated over the entire range of model parameters, we also provide insights into the negative impact of radical innovations on firm profits, but show that the environmental impact of increased radical innovation is not necessarily negative. Our results also have several implications for policy makers seeking to encourage reuse.

 

View all ESMT Working Papers in the ESMT Working Paper Series here. ESMT Working Papers are also available via SSRN, RePEc, EconStor, and the German National Library (DNB).

Pages
36
ISSN (Print)
1866–3494