Canbolat, Pelin Gülşah

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Canbolat, P. G.
C., Pelin Gülşah
CANBOLAT, Pelin Gülşah
Canbolat, PELIN GÜLŞAH
Pelin Gulsah, Canbolat
Canbolat,P.G.
C., Pelin Gulsah
Canbolat,Pelin Gulsah
Canbolat, P.
Canbolat, Pelin Gülşah
Pelin Gülşah CANBOLAT
PELIN GÜLŞAH CANBOLAT
C.,Pelin Gulsah
Canbolat, Pelin Gulsah
Pelin Gülşah Canbolat
Canbolat P.
CANBOLAT, PELIN GÜLŞAH
P. G. Canbolat
P. Canbolat
Canbolat, Pelin G.
Job Title
Doç. Dr.
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Main Affiliation
Industrial Engineering
Status
Current Staff
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Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID

Sustainable Development Goals

SDG data is not available
Documents

12

Citations

84

h-index

4

This researcher does not have a WoS ID.
Scholarly Output

2

Articles

2

Views / Downloads

8/0

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

2

Scopus Citation Count

3

WoS h-index

1

Scopus h-index

1

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0

Projects

0

WoS Citations per Publication

1.00

Scopus Citations per Publication

1.50

Open Access Source

1

Supervised Theses

0

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European Journal of Operational Research1
Manufacturing & Service Operations Management1
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Scholarly Output Search Results

Now showing 1 - 2 of 2
  • Article
    Citation - WoS: 2
    Citation - Scopus: 3
    Strategic Heterogeneous Customers in a Transportation Station: Information and Pricing
    (informs, 2024) Manou, Athanasia; Canbolat, Pelin G.; Karaesmen, Fikri
    Problem definition: We consider pricing of services with strategic customers who have heterogeneous delay costs motivated by transportation systems. Customers are strategic decision makers who weigh the reward from the transport service against the waiting cost for the vehicle at a transportation station. Customers arrive at the station according to a Poisson process, and the vehicle visits the station according to a renewal process. We analyze the optimal price and the equilibrium for different levels of information available to customers. Methodology/results: We represent the service system as a stochastic clearing process, heterogeneity in delay cost as a random variable, and heterogeneity in rewards as a positive affine transformation of delay cost. For each information level, we identify the equilibrium behavior of customers and solve the revenue-maximization problem based on this equilibrium. The equilibrium turns out to be unique in each case, and it is of a threshold form in the sense that for each value of the information, it is best to join either for all types of customers, only for those who are sufficiently price sensitive, only for those who are sufficiently delay sensitive, or for none. The optimal fee is also unique in nontrivial cases. This enables us to perform comparisons across different information structures. Managerial implications: The effect of heterogeneity depends highly on model parameters as well as the available information. For a fixed fee, an increase in heterogeneity has a positive overall impact on the customer population, whereas the effect on the revenue can be positive (slow service at a high fee) or negative (fast service at a low fee). Unlike with fixed fee, for the optimal fee, an increase in heterogeneity can have a negative overall effect on customers. Ignoring heterogeneity can lead to a substantial opportunity loss for the system.
  • Article
    Markov Decision Processes: Monotonicity of Optimal Policy in Exponential and Quasi-Hyperbolic Discounting Parameters
    (Elsevier, 2026) Kilic, Hakan; Canbolat, Pelin Gulsah; Gunes, Evrim Didem
    Intertemporal preferences of decision makers, i.e., the way they discount delayed utilities, impact their decisions. Empirical evidence suggests that individuals commonly have hyperbolic discounting preferences. This can result in time-inconsistent behavior, e.g., procrastination, which may be a barrier to adopting preventive behavior such as machine maintenance and patient adherence to treatment. In this paper, we theoretically compare the actions of individuals based on their discounting characteristics. We consider the Hyperbolic Discounting (HD) model, which is more representative of individual behavior than Exponential Discounting (ED). We formulate a discrete-time finite-horizon Markov decision process with Quasi-Hyperbolic Discounting (QHD), an analytically tractable function representing HD and present sufficient conditions that ensure the monotonicity of the optimal policy in the discounting parameters. We consider submodular maximization or supermodular maximization problems. Our paper is the first to investigate the monotonicity of the optimal policy in QHD parameters for these problems. Moreover, we compare the optimal actions under ED and QHD. We apply our results to the settings of machine maintenance, individual health behavior and inventory control. We provide numerical examples that show there might not be monotonicity if our sufficient conditions are not met. Also, we explore the discrepancy between the expected total exponentially-discounted rewards of the actions obtained from QHD and of the actions that are optimal under ED, and observe that this discrepancy is affected mainly by the present bias.