ekaterina (kate) astashkina
PhD Candidate at INSEAD
On the academic job market 2018/2019


INFORMS 2018: SC16 (Sun, 4 Nov, 1:30pm), TA25 (IBM Student Comp) (Tue, 6 Nov, 7:30am),
WB16 (Wed, 7 Nov, 11:00am), WD11 (Wed, 7 Nov, 3:20pm)

Papers under Review / Working Papers
The Environmental Impact of Online Grocery Retailing - [Abstract]

with Elena Belavina (Cornell) and Simone Marinesi (Wharton), under review at Management Science
Finalist, 2018 IBM Service Science Best Student Paper Award

We study the environmental impact of the entry of online grocery retailers. We build a stylized three-tier model of geographically-dispersed traditional and online fresh grocery retail chains. We endogenize (i) individual replenishment decisions of customers, retailers and a supplier, (ii) customer choice of the shopping channel, and (iii) online grocer's fleet routing decisions. We incorporate emissions from food waste and transportation. We formally characterize the conditions and isolate the drivers that lead to lower/higher emissions upon entry of an online retailer. Our findings suggest that entry of online grocer reduces market emissions whenever online grocer's pricing scheme induces (1) moderate online customer shopping frequency and (2) intermediate or very high online adoption levels. Violating these increases market emissions by activating at least one of the following detrimental for the environment drivers: (a) excessive consumer food waste, (b) excessive last-mile travel, (c) retail-level inventory decentralization (due to extra stocking location of an online grocer), and (d) adverse conversion of (low-emission) offline customers into (higher-emission) online customers. The model calibration suggests that, for most reasonable scenarios, the changes in the market emissions follow the changes in the consumer waste. More importantly, under all practical scenarios, online grocer's entry reduces market emissions by 8-41%, with biggest reduction in more congested, wealthier, lower store density cities. In such cities, online entry provides substantial shopping convenience to customers, who thus extensively cut their food waste. Finally, we show that, compared to delivery from a separate online hub, executing deliveries from existing offline stores is greener.
Impact of Workforce Flexibility on Customer Satisfaction: Empirical Framework & Evidence from a Cleaning Services Platform - [Abstract]

with Ruslan Momot (HEC Paris) and Marat Salikhov (INSEAD), under review at M&SOM

Problem definition: Contrary to classic applications of matching theory, in most contemporary on-demand service platforms, matches can not be enforced because workers are flexible – they choose their tasks. Such flexibility makes it difficult to manage workers while keeping customers satisfied. We build a framework to compare platform matching policies with less flexible and more flexible workers, and empirically quantify by how much worker flexibility hurts customer satisfaction and customer equity.

Academic/Practical relevance: In academic literature, there is no established framework that allows for the comparison of matching policies in on-demand platforms. Further, the link between worker flexibility and customer satisfaction is understudied.

Methodology: We propose a tripartite framework for empirical evaluation and comparison of the operational policies with different degrees of worker flexibility. Step 1: Predictive modeling of customer satisfaction based on estimation of individual unobservable characteristics: customer difficulty and worker ability (item-response theory model). Step 2: Evaluation of the effect of matching policy (under a given level of flexibility) on customer satisfaction (bipartite matching). Step 3: Quantification of the associated monetary impact (customer lifetime value model).

Results: We apply our framework to the dataset of one of the world's largest on-demand platforms for residential cleanings. We find that customer difficulty and cleaner ability are good predictors of customer satisfaction. Granting full flexibility to workers reduces customer satisfaction by 3% and customer lifetime revenue by 0.2%. We propose a family of matching policies that provide sufficient flexibility to workers, while alleviating 75% of the detrimental effect of worker flexibility on customer satisfaction.

Managerial implications: Our results suggest that, in platforms with flexible workforce, the presence of worker and customer heterogeneity translates into matching inefficiency – the drop in customer satisfaction. Our empirical framework helps practitioners to decide on the right level of worker flexibility and the means for achieving it.
Sustainable Sharing of a Scarce Resource with Uncertain Refill

working paper available upon request

Work in Progress
On the Efficacy of Fiscal Instruments that Combat Household Food Waste

with Elena Belavina (Cornell), results are available upon request

Hyperlocal Food Sharing – A Myth or the Future?

work in progress, data collection stage

Choosing the Optimal Campaign Mode in Reward Based Crowdfunding

with Simone Marinesi (Wharton) and Karan Girotra (Cornell Tech), work in progress

Cases and Teching Materials
“Sberbank: No Queues!”, INSEAD Business School Case

with Serguei Netessine (Wharton), Case and teaching note published by Harvard Business Publishing. Case is available in English and in Russian and has been in use in Executive Training Program “Sberbank 500” for 4 years.