Specialty Retail – Page 2 – CSCR® Research Portal

Behavioral Ordering, Competition and Profits: An Experimental Investigation

By B. Quiroga, B. B. Moritz^📧, and A. Ovchinnikov

In Production and Operations Management, 2019, 28 (9): 2242–2258. https://doi.org/10.1111/poms.13032

We investigate the impact of behavioral ordering on profits under competition. Specifically, we use controlled laboratory experiments to evaluate the differences in profits between a behavioral competitor (where a human places orders), and a management science‐driven competitor (where orders are placed according to one of several plausible policies based on existing literature and managerial practice). Unlike the full‐information game‐theoretic models that assume rational decision‐makers, these policies mimic practical situations by using less information and do not assume that their human competitors make fully rational decisions. Most prior literature focuses on non‐competitive settings, where behaviorally biased deviations from optimal order quantities result in small expected profit losses. In contrast, under competition, we find that human decision‐makers receive a substantially lower profit than the equilibrium expected profit, even as their competitors receive substantially higher profit.

Keywords: Behavioral operations; Experimental economics; Newsvendor; Decision biases; Inventory competition

Supply Chain Network Robustness Against Disruptions: Topological Analysis, Measurement, and Optimization

By K. Zhao, K. Scheibe, J. Blackhurst, and A. Kumar^📧

In IEEE Transactions on Engineering Management, 2019, 66 (1): 127–139. https://doi.org/10.1109/TEM.2018.2808331

This paper focuses on understanding the robustness of a supply network in the face of a disruption. We propose a decision support system for analyzing the robustness of supply chain networks against disruptions using topological analysis, performance measurement relevant to a supply chain context, and an optimization for increasing supply network performance. The topology of a supply chain network has considerable implications for its robustness in the presence of disruptions. The system allows decision makers to evaluate topologies of their supply chain networks in a variety of disruption scenarios, thereby proactively managing the supply chain network to understand vulnerabilities of the network before a disruption occurs. Our system calculates performance measurements for a supply chain network in the face of disruptions and provides both topological metrics (through network analysis) and operational metrics (through an optimization model). Through an example application, we evaluate the impact of random and targeted disruptions on the robustness of a supply chain network.

Keywords: Decision support; Disruption; Optimization; Robustness; Simulation; Supply chain network topology

Redesign of the Fragile Item Department S.O.P. for an Off-Price Department Store Retailer

By Kara Nardi, supervised by Robert A. Novack^📧(Thesis Supervisor) and John C. Spychalski^📧(Honors Advisor) (2019)

Company X is a discount department store retailer that was founded over forty years ago, offering off-price, name-brand clothing, shoes, jewelry, and home and bath items. Within these categories, mainly the home and bath departments, Company X distributes a large amount of “fragile” items. Fragile items are defined as anything liquid or breakable, such as shampoos, perfumes, or glassware. The current fragile work area was designed within the pre-existing warehouse footprint and with limited resources. The Standard Operations Procedure (SOP) within this area includes a large number of touches per item, inefficient packing, and many manual operations. The goal of this thesis is to identify any opportunities to improve the SOP processes (prep, put, or pack) to increase the overall productivity of the department and provide details on how to simplify the tasks of the associates as much as possible. After an onsite visit, best practice research, and data analysis it is recommended that Company X make changes to the box sizes, shelving racks, and pallet organization in the current East Coast processing center. If the SOP was to be recreated given no limitations, in addition to the changes made to the current processing center, it is also recommended that Company X increase automation and alter their put-to-light system to accommodate multiple SKUs at the same time. The incorporation of these changes to Company X’s Standard Operations Procedure for packaging and shipping fragile items will help to improve productivity and lead to a more efficient operation.

Access the paper at Electronic Theses for Schreyer Honors College (ETDA) website here.

Managing Product Returns in Retailing

By J. Petersen and A. Alptekinoglu^📧

In Handbook of Research on Retailing, 2018, Chapter 10: 220–233 (Invited. Peer-reviewed/refereed). https://doi.org/10.4337/9781786430281.00019

Product returns continue to challenge retailers, especially as retail channels and product variety proliferate. The purpose of this chapter is to first highlight the ongoing research on product returns in both the marketing and supply chain/operations areas in an effort to encourage more research that has the potential to span boundaries across these two areas. Further, the goal is to highlight some of the new product return-related developments in retailing that are attempting to solve the ongoing challenge of better managing customer product return behavior to maximize customer profitability. Specifically, the authors pose several still unanswered research questions to inspire ongoing research on product returns across the marketing and supply chain/operations areas.

Promoting Change from the Outside: Directing Managerial Attention in the Implementation of Environmental Improvements

By S. Dhanorkar^📧, E. Siemsen, and K. W. Linderman^📧

In Management Science, 2018, 64 (6): 2473–2972. https://doi.org/10.1287/mnsc.2017.2748

Regulatory agencies, auditing firms, and supply chain partners externally promote change in firms. To this end, they commonly employ two different and somewhat contradictory intervention approaches. One approach uses punitive tactics to coerce firms to change, while the other approach uses supportive tactics to encourage change. Using the context of government agencies promoting environmental improvements in firms, we examine whether such punitive (e.g., regulatory inspections with possible sanctions) and supportive (e.g., environmental assistance, improvement recommendations) tactics can be administered in a complementary manner. Using a unique and novel longitudinal data set collected from two state-level environmental agencies in Minnesota, we analyze over 1,000 supportive environmental improvement (EI) projects in combination with intermittent (but currently uncoordinated) punitive tactics. One key finding from our research is that the timing, severity, and relatedness of punitive tactics is critical for directing managerial attention and thus improving the efficacy of supportive tactics (i.e., EI implementation). Contingent on their timing, inspections can increase EI implementation rates by up to 60% but can also reduce implementation rates by up to 50% compared with EIs in facilities that do not experience inspections. Classifying regulatory inspections as (1) either clean or adverse and (2) either related or unrelated allows us to further explain the influence of such punitive tactics on EI implementation. Finally, we provide evidence for a positive effect of successful EI implementation on long-term environmental compliance.

Keywords: Sustainable operations; Operations-environmental policy interface; Attention-based view; Inspections; Hazard model

From Brick to Click & Click to Brick: The Retail E-Volution

By Rachel Fay Gimuriman, supervised by Robert A. Novack^📧(Thesis Supervisor) and John C. Spychalski^📧(Honors Advisor) (2018)

The new age of business revolves around data, technology, and the incredible capabilities said advancements have brought every company and consumer in the world. The retail sector, in particular, has been completely transformed and catalyzed because of the revolutionary vision of companies like Amazon or Walmart. They have focused on creating new strategies that are fueled by data and technology, and furthermore, being the ones who create the consumer expectation; no customer knows what they need to make their life better or more convenient…until Amazon or Walmart tells them. This thesis aims to delve into the history and evolution from solely traditional brick and mortar stores to click and mortar stores, and vice versa, and how the octopus that is Amazon and the hippo that is Walmart have disrupted retail as we know it. This publication creates a platform that students and professionals can reference to gain a deeper understanding of the evolution of “brick to click” and “click to brick” over the recent decade and begin to understand where these two animals will take us next. The main foci include: developing consumer trends, competitive strategies, pricing, operations, product assortment, private label, store formats, and supply chain management. The industries and companies studied includes grocery (Whole Foods Market, Kroger, Instacart, and Blue Apron), wholesale (Costco, Sam’s Club, Boxed Wholesale), department stores (Lord and Taylor, Kohl’s and Nordstrom), home delivery companies, big box retailers (Walmart and Target), private label manufacturing, and the future of the retail store. This thesis aims to examine the entire retail industry.

Access the paper at Electronic Theses for Schreyer Honors College (ETDA) website here.

Advance Selling to Strategic Consumers

By Michelle M. H. Seref, Onur Seref, Aydın Alptekinoglu^📧and S. Selçuk Erengüç

In Computer Management Science, 2016, 13:597–626. https://doi.org/10.1007/s10287-016-0264-3

Advance selling of goods and services is a form of separating purchase from consumption. It is often employed when consumers are uncertain about their consumption utilities until a short time period before consumption. A book to be released, a concert to attend, or a cruise to take are some examples. Invariably, in consumers’ mind inventory availability (of copies, seats, or rooms) is a concern. In this paper we study a retailer’s inventory and pricing decisions in an advance selling scenario that involves consumers who are strategic. Some consumers not only consider advance and spot prices, but also the uncertainty in future availability of the product (during the spot period) and in their consumption utility from it. We characterize the optimal inventory management and pricing policies, and discuss several interesting aspects of the solution. For example, it can be optimal for the retailer to limit advance sales even if there is more demand for it, and it can be optimal for the retailer to limit its inventory even though there is more capacity to keep it, but not both.

Keywords: Inventory management; Advance selling; Pricing; Strategic consumers

Stockout-Based Substitution and Inventory Planning in Textbook Retailing

By J. Lee, V. Gaur, S. Muthulingam^📧and G. Swisher

In Manufacturing & Service Operations Management, 2016, 18 (1): 104–121. https://doi.org/10.1287/msom.2015.0551

We demonstrate the value of utility-based choice models to estimate demand and plan inventory for new and used textbooks in the presence of consumer choice and stockout-based substitution at a university textbook retailer. Demand information is censored, the exact time of stockout is not observed, and the short selling season often does not allow for replenishment. Using data for 26,749 book titles from 2007 to 2011 and a simulation experiment calibrated on real data, we show that an attribute-based choice model generates accurate demand estimates (mean absolute percentage error less than 1%) even when nearly 90% of the textbooks in the fit sample experience stockout. This performance is driven by the heterogeneity of product attributes and is robust to the occurrence of product returns. We implement this model at the bookstore in a controlled field experiment and obtain over 10% increase in profit. The results show that accounting for asymmetric and stockout-based substitution in demand estimation and inventory planning enables us to make systematic corrections in inventory mix and inventory level compared to the existing process.

Keywords: OM practice; Retailing; Inventory theory and control; Demand estimation; Stockout-based substitution

Omnichannel Retailing: Trends, Outlooks, and Strategies

By Kusumal Ruamsook^📧(2016)

This document is prepared as background for CSCR speakers on omnichannel retailing at the 2016 Parcel Forum. In this document, highlights of omnichannel retailing trends, outlook, and current strategies are presented. Data are based on a review of literature published within an approximately three-year time frame (up to July 2016), including managerial journals, industry reports, and relevant web resources. The review looks at the three elements of omnichannel retailing—point of interaction, point of fulfillment, and point of return.

View the document here

Suggested citation

Ruamsook, Kusumal. 2016. “Omnichannel Retailing: Trends, Outlooks, and Strategies.” Resource, Center for Supply Chain Research® (CSCR®), The Pennsylvania State University.

Rationality Analytics from Trajectories

by S. Liu^📧, Q. Qu, and S. Wang

In ACM Transactions on Knowledge Discovery from Data (TKDD), 2015, 10 (1): 10. https://doi.org/10.1145/2735634

The availability of trajectories tracking the geographical locations of people as a function of time offers an opportunity to study human behaviors. In this article, we study rationality from the perspective of user decision on visiting a point of interest (POI) which is represented as a trajectory. However, the analysis of rationality is challenged by a number of issues, for example, how to model a trajectory in terms of complex user decision processes? and how to detect hidden factors that have significant impact on the rational decision making? In this study, we propose Rationality Analysis Model (RAM) to analyze rationality from trajectories in terms of a set of impact factors. In order to automatically identify hidden factors, we propose a method, Collective Hidden Factor Retrieval (CHFR), which can also be generalized to parse multiple trajectories at the same time or parse individual trajectories of different time periods. Extensive experimental study is conducted on three large-scale real-life datasets (i.e., taxi trajectories, user shopping trajectories, and visiting trajectories in a theme park). The results show that the proposed methods are efficient, effective, and scalable. We also deploy a system in a large theme park to conduct a field study. Interesting findings and user feedback of the field study are provided to support other applications in user behavior mining and analysis, such as business intelligence and user management for marketing purposes.