Leveraging downstream data in the footwear/apparel industry

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections."June 2007."Includes bibliographical references (leaf 65).Retailers collect information regarding consumer purchases on a transactional basis. This data is not completely being leveraged by manufacturers in the footwear and apparel industry to increase on-shelf availability. However, certain apparel and consumer products companies have developed best-in-class methods for collecting and utilizing data to enhance supply chain visibility and to drive increased sales. A description of these best-in-class practices is provided, strategies to use the data are presented, and the importance of collaboration among supply chain partners is discussed. Further, point of sale data from a footwear and apparel manufacturer is analyzed to illustrate how the data can be leveraged to predict subsequent season sales, to improve forecasting accuracy, and to allocate replenishment inventory more effectively.by Jeffrey Edward Axline [and] Brian Joseph Lebl.M.Eng.in Logistic

Solving Practical Dynamic Pricing Problems with Limited Demand Information

Dynamic pricing problems have received considerable attention in the operations management literature in the last two decades. Most of the work has focused on structural results and managerial insights using stylized models without considering business rules and issues commonly encountered in practice. While these models do provide general, high-level guidelines for managers in practice, they may not be able to generate satisfactory solutions to practical problems in which business norms and constraints have to be incorporated. In addition, most of the existing models assume full knowledge about the underlying demand distribution. However, demand information can be very limited for many products in practice, particularly, for products with short life-cycles (e.g., fashion products). In this dissertation, we focus on dynamic pricing models that involve selling a fixed amount of initial inventory over a fixed time horizon without inventory replenishment. This class of dynamic pricing models have a wide application in a variety of industries. Within this class, we study two specific dynamic pricing problems with commonly-encountered business rules and issues where there is limited demand information. Our objective is to develop satisfactory solution approaches for solving practically sized problems and derive managerial insights. This dissertation consists of three parts. We first present a survey of existing pricing models that involve one or multiple sellers selling one or multiple products, each with a given initial inventory, over a fixed time horizon without inventory replenishment. This particular class of dynamic pricing problems have received substantial attention in the operations management literature in recent years. We classify existing models into several different classes, present a detailed review on the problems in each class, and identify possible directions for future research. We then study a markdown pricing problem that involves a single product and multiple stores. Joint inventory allocation and pricing decisions have to be made over time subject to a set of business rules. We discretize the demand distribution and employ a scenario tree to model demand correlation across time periods and among the stores. The problem is formulated as a MIP and a Lagrangian relaxation approach is proposed to solve it. Extensive numerical experiments demonstrate that the solution approach is capable of generating close-to-optimal solutions in a short computational time. Finally, we study a general dynamic pricing problem for a single store that involves two substitutable products. We consider both the price-driven substitution and inventory-driven substitution of the two products, and investigate their impacts on the optimal pricing decisions. We assume that little demand information is known and propose a robust optimization model to formulate the problem. We develop a dynamic programming solution approach. Due to the complexity of the DP formulation, a fully polynomial time approximation scheme is developed that guarantees a proven near optimal solution in a manageable computational time for practically sized problems. A variety of managerial insights are discussed

Innovative Revenue Management Practices with Probabilistic Elements

Sale of products with a probabilistic nature, where customers do not know which product they will receive at the time of service, has become popular over the recent years. In the revenue management literature, there has been a growing interest in understanding these modern approaches using analytical techniques. On the other hand, customer-centric revenue management has been replacing the long-standing inventory-centric approach because of the availability of rich data sets by focusing on understanding and predicting customer behavior and then optimizing price and/or quantity related decisions. In this dissertation, we take a customer-centric approach and do not only provide analytical results, but also empirically investigate how customers make their decisions, which is crucial in order to implement appropriate strategies. We first focus on an innovative hotel revenue management practice called standby upgrades, i.e., a practice where the guest is only charged for the discounted upgrade if it is available at the time of arrival. In particular, Chapter 2 discusses how to optimally price standby upgrades and evaluates their benefits through an analytical model. Chapter 3 uses a major hotel chain’s booking and standby upgrades data to investigate the extent of strategic guest behavior through empirical analysis. Then, we focus on another innovative revenue management practice, but in the mega event industry, called team-specific ticket options. Chapter 4 studies fans’ decision-making process for the 2015 College Football season using a unique data set

Essays in Retail Operations and Humanitarian Logistics

This dissertation introduces and analyzes research problems related to Retail Operations and Humanitarian Logistics. In Retail Operations, the inventory that ends up as unsaleable at primary markets can be significant (up to 20% of the retail product). Thus retailers look for strategies like selling in secondary markets at a discounted price. In such a setting, the decisions of how much to order for a product of limited shelf life and when (if at all) to start selling the product in the secondary market become critical because these decisions not only affect the retailer's cost of procurement and sales revenues obtained from the product but also affect utilization of shelf space, product rollover and assortment decisions of the retailer. Apart from using secondary markets, retailers that sell seasonal products or products with sales horizons shorter than the typical production/procurement lead time also enter into contractual agreements with suppliers. These contracts are in place to share risks associated with unknown or uncertain demand for the product. Presence of such contracts does affect a retailer's order quantity as well as the time to start selling in the secondary market. In our two essays on retail operations, we analyze a retailer's optimal order quantity and when he/she starts selling in the secondary market. We refer to the former as the 'ordering decision' and the latter as the 'timing decision.' These two decisions are studied first without risk sharing contracts in Essay 1, and then in the presence of contracts in Essay 2. In Essay 1, we build a two-stage model with demand uncertainty. The ordering decision is made in the first stage considering cost of procurement and expected sales revenue. The timing decision is made in the second stage and is conditional on the order quantity determined in the first stage. We introduce a new class of aggregate demand model for this model. We study the structural properties of the retailer's timing and ordering problem and identify optimality conditions for the timing decision. Finally, we complement our analytical results with computational experiments and show how retailer's optimal decisions change when problem parameters are varied. In Essay 2, we extend the work in first essay to include the contracts between the retailer and a supplier. In this essay, we introduce a time-based Poisson demand model. We define three di®erent types of contracts and investigate the effect of each of these contracts on the retailer's ordering and timing decisions. We investigate how the analytical structure of the retailer's decision changes in the presence of these contracts. For a given order quantity, we show that the timing decision depends on the type of contract. Our analytical results on the timing decision are complemented with computational experiments where we investigate the impact of contract type on the optimal order quantity of the retailer. In Humanitarian Logistics, non-profit organizations receive several-billion-dollars-worth of donations every year but lack a sophisticated system to handle their complex logistics operations; the absence of expertly-designed systems is one of the significant reasons why there has been a weak link in the distribution of relief aid. The distribution of relief aid is a complex problem as the goal is humanitarian yet at the same time, due to limited resources, the operations have to be efficient. In the two essays on humanitarian logistics, we study the distribution of aid using homogeneous fleet, with and without capacity restrictions. In Essay 3, we discuss routing for relief operations using one vehicle without capacity restrictions. Contrary to the existing vehicle routing models, the key property of our routing models is that the nodes have priorities along with humanitarian needs. We formulate this model with d-Relaxed Priority rule that captures distance and response time. We formulate routing models with strict and relaxed forms of priority restrictions as Mixed Integer Programs (MIP). We derive bounds for this problem and show that this bound is attained in limiting condition for a worst-case example. Finally, we evaluate the optimal solutions on test problems for response time and distance and show that our vehicle routing model with priorities captures the trade-off between distance and response time unlike existing Vehicle Routing Problem (VRP) models without priorities. In Essay 4, we extend the problem dealt in third essay to consider fleet consisting of multiple vehicles (homogeneous) with capacity and route length restrictions. First, we show that the humanitarian aspect imposes additional challenges and develop routing models that capture performance metrics like fill rate, distance traversed, response time and number of victims satisfied. Proposed routing models are formulated as Mixed Integer Programs and are solved to optimality for small test problems. We conduct computational experiment and show that our models perform well on these performance metrics

An educational game with dragons’ den experiences for supply chain management training

This article presents an educational game to engage university and industrial stakeholders in collaborative training for supply chain management courses. The game will help students learn complex supply chain management issues. There are two integrated parts: a case ethod through an industrial case and an activity-based game featuring role plays based on international television shows such as Dragons’ Den in Canada or Shark Tank in the United States. We developed a game framework to illustrate how the game can be prepared and played in classrooms. Although the game is primarily developed for classroom teaching, it may be adapted to other training environments. We have provided two examples to demonstrate how the game can be played as a short game in conference environments. Game experiences and feedback are presented with comments from various game participants. By interacting with stakeholders and tackling a real-world business case, students can better understand stakeholders’ business goals, the importance of supply chain collaboration, and the impacts on supply chain decisions

The Lumberjack, December 01, 1999

The student newspaper of Humboldt State University.https://digitalcommons.humboldt.edu/studentnewspaper/2329/thumbnail.jp

The significance of integrated marketing communication techniques in the 21st century marketplace

The primary purpose of this study was to examine integrated marketing communication techniques used to develop successful apparel brands. This author researched existing data and explored the IMC development of three successful brand apparel companies: Nike, Ralph Lauren Polo, and Tommy Hilfiger. The study included the process of building brand identity, including the tenets of brand management and the symbolic process, as well as the significance of brand equity and architecture. This author conducted a pen and paper quantitative survey to a random sampling of 50 Cumberland County College undergraduate students concerning the influential factors in their choice of brand selection. The data was categorized and tabulated in percentages by age into two groups, 18-25 and 26+. This author conducted two focus groups consisting of 10 students from the 18-25 age group and 10 students from the 26+ age group. The quantitative and qualitative results indicated that the respondents were very influenced by integrated brand marketing techniques in the selection of apparel items

Perceived Fitness is a Stronger Predictor of Maximal Aerobic Speed Than Submaximal Fitness in Rugby Union Players

BACKGROUND: Monitoring athlete training effects in team sports requires a systematic approach, adopting frequently implementable methods and sensitive proxy outcome measures able to detect acute and chronic training effects. Consequently, the use of submaximal fitness tests (SMFT) in team sport settings has increased, likely given their time-efficient nature, ease of administration in-season, and strong physiological rationale in observing athlete responses to a standardised exercise stimulus. However, this process has primarily favoured objective measures over subjective athlete responses, and both approaches are yet to be assessed for their respective associations and predictive qualities with maximal test outcomes. AIM: The study evaluated the relationships and predictive qualities between field-based measures of perceived, submaximal and maximal aerobic fitness in a sample of rugby union players. METHODS: Using an observational, cross-sectional approach, 47 high-performance British university rugby union players (21.1 ± 1.2 years; 184.86 ± 7.28 cm; 97.82 ± 14.31 kg) rated their aerobic capacity using a newly modified rating of perceived fitness (RPF) scale, before completing a SMFT (shuttle based, continuous-fixed, 4 min running at 12 km·h-1), and a 1.2 km shuttle run test (1.2SRT) to assess maximal aerobic speed (MAS). Data were analysed using magnitude-based inferences (MBI). RESULTS: An almost certainly [large] positive association between RPF and MAS (r = 0.58; ±0.19) was revealed, with backs reporting a higher RPF (almost certainly [small] increase) and achieving a higher MAS (possibly [small] increase) during the 1.2SRT in comparison to forwards. A likely [small] negative association between SMFT exercise heart rate (HRex) and MAS (r = -0.25; ±0.23) and a possibly [small] negative relationship between RPF and HRex (r = -0.19; ±0.27) was also identified. Regression analysis revealed RPF as the strongest predictor of MAS (R2 = 0.33; SEE: 0.28) compared to SMFT HRex (R2 = 0.06; SEE: 0.35), and both variables combined (Adj. R2 = 0.29; SEE: 0.28), and RPF was shown to be a poor predictor of SMFT HRex as a measure of submaximal aerobic fitness (R2 = 0.04; SEE: 8.48). CONCLUSIONS: Athlete RPF show promising levels of content, face and construct domains of validity in the prediction of MAS measured using the 1.2SRT; however, further work is needed to assess other domains of validity, reliability and sensitivity. Whilst SMFT HRex shows good convergent validity with some field measures of aerobic capacity, HRex is poorly related to or predictive of MAS measured using the 1.2SRT. RPF in its form derived from this study is not well related to or predictive of proxy measures of submaximal cardiovascular/aerobic fitness such as SMFT HRex. The RPF scale used in this study could be a useful monitoring tool in team sports