Push verse pull:Inventory-leadtime tradeoff for managing system variability

We study a two-stage push–pull system in an assemble-to-order manufacturing environment. Modelling the system as an inventory-queue model, we construct a decision model to determine the optimal stock level of the semifinished base product and the optimal leadtime of the finished products that will minimize the total operational cost. We analytically characterize the structure of the optimal policy. For systems with moderate demand and upstream processing time variabilities, there exists a threshold determined purely by the tradeoff of operational costs so that when the upstream utilization is above the threshold, the push–pull strategy is optimal; otherwise the pure-pull strategy is optimal. When the inter-arrival time or the upstream service time follows a general probability distribution, the optimal policy depends on the demand or process variability at the upstream stage. Our results can be used to guide managers in selecting the right inventory and leadtime strategy to cope with system variability. We find that in comparison of the downstream variability, under some mild condition, the upstream variability has a more significant impact on the choice of the optimal policy, the corresponding inventory, and lead time. Further, the guaranteed/constant downstream processing time does not always benefit the supply chain performance

Information-shared postponement strategies in supply chain management

Ph.DDOCTOR OF PHILOSOPH

Manufacturer Product Line Decisions In Growing Consumer Technology Markets: A Case of Digital Cameras

The objective of this dissertation is to deepen our understanding of competitive and demand drivers of manufacturer new product introductions in consumer technology markets. Researchers in economics and marketing commonly view differentiated products as combinations of attributes that are located in multi-attribute space. In first study presented in Chapter 2 of this dissertation, I conform to this common view of products as multi-attribute bundles and, therefore, carefully construct both a multi-attribute product space, as well as, and even more importantly, product clusters within this multi-attribute product space. I focus on the early stages of US Digital Cameras category: 1998-2000). Operationalizing and classifying all existing products in the category, as well as each new product introduction: when it occurs), on a common space of objective product attributes allows us to: 1) explicitly understand whether a given introduction is an incremental innovation or a radical innovation, and: 2) whether it is an introduction in to a cluster where the firm already has a strong presence or not etc. Further, it allows us to understand whether the new product introduction decisions of a firm are influenced by relative cluster characteristics which, in turn, are influenced by competitors\u27 new product introductions in the different clusters etc. In the Chapter 2 of this dissertation I focus on two specific new product introduction decisions of digital camera manufacturers: timing and positioning. Additional insights are obtained from empirically estimating a pricing model using the same product cluster conceptual framework. In Chapter 3, I study new product preannouncements, which have become commonplace in manufacturers product strategy in consumer technology markets. Here I undertake a detailed empirical analysis of the demand effects of product preannouncements within the digital cameras category. I estimate a new product adoption model using monthly data on product-level availability, sales and prices across hundreds of digital cameras that were introduced over a period of 4 years. I study the effects of the incidence and timing of a product preannouncement on demand for the preannounced product: i.e., digital camera model), as well as demand for its competitors. In doing this, I implicitly accommodate the impact of product preannouncements for individual products on category-level demand growth. Using a detailed model-based accounting of preannouncement effects, I separate the effects of a preannouncement on: 1) innovation and word-of-mouth components underlying demand for the preannounced product, and: 2) consumer preferences for preannounced product attributes. I demonstrate the managerial implications of the estimated preannouncement effects using a numerical experiment

Applied probabilistic forecasting

In any actual forecast, the future evolution of the system is uncertain and the forecasting model is mathematically imperfect. Both, ontic uncertainties in the future (due to true stochasticity) and epistemic uncertainty of the model (reflecting structural imperfections) complicate the construction and evaluation of probabilistic forecast. In almost all nonlinear forecast models, the evolution of uncertainty in time is not tractable analytically and Monte Carlo approaches (”ensemble forecasting”) are widely used. This thesis advances our understanding of the construction of forecast densities from ensembles, the evolution of the resulting probability forecasts and methods of establishing skill (benchmarks). A novel method of partially correcting the model error is introduced and shown to outperform a competitive approach. The properties of Kernel dressing, a method of transforming ensembles into probability density functions, are investigated and the convergence of the approach is illustrated. A connection between forecasting and Information theory is examined by demonstrating that Kernel dressing via minimization of Ignorance implicitly leads to minimization of Kulback-Leibler divergence. The Ignorance score is critically examined in the context of other Information theory measures. The method of Dynamic Climatology is introduced as a new approach to establishing skill (benchmarking). Dynamic Climatology is a new, relatively simple, nearest neighbor based model shown to be of value in benchmarking of global circulation models of the ENSEMBLES project. ENSEMBLES is a project funded by the European Union bringing together all major European weather forecasting institutions in order to develop and test state-of-the-art seasonal weather forecasting models. Via benchmarking the seasonal forecasts of the ENSEMBLES models we demonstrate that Dynamic Climatology can help us better understand the value and forecasting performance of large scale circulation models. Lastly, a new approach to correcting (improving) imperfect model is presented, an idea inspired by [63]. The main idea is based on a two-stage procedure where a second stage ‘corrective’ model iteratively corrects systematic parts of forecasting errors produced by a first stage ‘core’ model. The corrector is of an iterative nature so that at a given time t the core model forecast is corrected and then used as an input into the next iteration of the core model to generate a time t + 1 forecast. Using two nonlinear systems we demonstrate that the iterative corrector is superior to alternative approaches based on direct (non-iterative) forecasts. While the choice of the corrector model class is flexible, we use radial basis functions. Radial basis functions are frequently used in statistical learning and/or surface approximations and involve a number of computational aspects which we discuss in some detail

Strategic Remanufacturing Decision in a Supply Chain with an External Local Remanufacturer

This paper develops a model for remanufacturing decisions in a two-stage supply chain with one manufacturer, one retailer and one external local remanufacturer, who collects used products and then reproduces them into a new one if the manufacturer does not join in remanufacturing process. This paper is different from most of the extant studies about remanufacturing because they consider decisions of firms rather than supply chains. We mainly focus on the remanufacturing strategy of the manufacturer when there is a local remanufacturer. We derive the equilibrium results for all players and do some comparative studies under different cases. We find that product substitutability can invert the effect of manufacturer’s extension decision on the retailer’s profit. We also consider the effect of channel structure by comparing the decentralized channel with the centralized channel. We find that the manufacturer has a higher incentive to extend its product line in the centralized channel than the decentralized channel; and the competition can strengthen its motivation to extend the line

The Inner Dynamics and Long-term Value Creation Potential of Operational Excellence

Operational excellence is an executional competency that reflects a firm’s ability to run its day-to-day operations efficiently, effectively, and profitably. Differing views have been expressed regarding the inner dynamics and value creation potential of operational excellence. From an inner dynamics perspective, the competency’s dimensions of efficiency and effectiveness are viewed by some as conflicting and difficult to reconcile (the tradeoff model), and by others as synergistic and mutually supportive (the cumulative model). From a value creation perspective, operational excellence is portrayed by some as an effective cash-flow generator and a potent enabler of firm growth, and by others as a source of excessive routinization that hinders strategic adaptation and limits long-term value creation. The present dissertation revisits these conflicting views. Drawing on Porter’s profit maximization prescription, essay 1 empirically examines the individual and collective effects of operational efficiency and operational effectiveness on firm profitability. In so doing, it assesses the respective merits of the tradeoff and cumulative perspectives. Empirical findings based on a multi-industry panel of 595 public US manufacturing firms provide relative support for the cumulative perspective; concurrent improvements in efficiency and effectiveness are shown to have a compounding positive effect on firm profitability. The findings also show that the individual benefits of isolated improvements to either efficiency or effectiveness tend to be curvilinear with diminishing returns. Addressing the value creation question, essay 2 draws on signaling theory to empirically examine the stock market’s ex-ante assessment of operational excellence as an instrument for long-term value creation. Contrary to the productivity dilemma narrative, empirical results show that market participants tend to have a positive outlook on the value creation potential of operational excellence. The positive outlook is, however, found to be dampened by the stock market’s expectations of firm short-term revenue growth and amplified by firm R&D efforts. In a third exploratory essay, I discuss environmental and organizational learning factors that have the potential to cause firms to grow over-invested in operational excellence at the expense of strategic foresight and market adaptation. Essay 3 is conceptual in nature and provides theoretical propositions for future empirical investigation

A Representation of Tactical and Strategic Precursors of Supply Network Resilience Using Simulation Based Experiments

Modern supply chains are becoming increasingly complex and are exposed to higher levels of risk. Globalization, market uncertainty, mass customization, technological and innovation forces, among other factors, make supply networks more susceptible to disruptions (both those that are man-made and/or ones associated with natural events) that leave suppliers unavailable, shut-down facilities and entail lost capacity. Whereas several models for disruption management exist, there is a need for operational representations of concepts such as resilience that expand the practitioners’ understanding of the behavior of their supply chains. These representations must include not only specific characteristics of the firm’s supply network but also its tactical and strategic decisions (such as sourcing and product design). Furthermore, the representations should capture the impact those characteristics have on the performance of the network facing disruptions, thus providing operations managers with insights on what tactical and strategic decisions are most suitable for their specific supply networks (and product types) in the event of a disruption. This research uses Agent-Based Modeling and Simulation (ABMS) and an experimental set-up to develop a representation of the relationships between tactical and strategic decisions and their impact on the performance of multi-echelon networks under supply uncertainty. Two main questions are answered: 1) How do different tactical and strategic decisions give rise to resilience in a multi-echelon system?, and 2) What is the nature of the interactions between those factors, the network’s structure and its performance in the event of a disruption? Product design was found to have the most significant impact on the reliability (Perfect Order Fulfillment) for products with high degrees of componentization when dual sourcing is the chosen strategy. However, when it comes to network responsiveness (Order Fulfillment Cycle Time), this effect was attenuated. Generally, it was found that the expected individual impact these factors have on the network performance is affected by the interactions between them

First come, first served: an analysis of pioneer and follower firms' market and nonmarket actions in the European mobile telephone industry

This study examines the relationship between erosion of the first-mover's market share and the differences in competitive behaviour of pioneer firms and followers. Particularly, we pay particular attention to market actions related to innovation, pricing and promotion, and to non-market actions related to judicial issues. The empirical study has been carried out with companies that are present in a dynamic context, such as the European mobile telephone industry. Our results show that when followers take more non-market actions than pioneers the negative effect on the firstentrant's advantage is more significant. On the contrary, we have not found a significant impact of innovating and pricing actions

FIRST COME, FIRST SERVED: AN ANALYSIS OF PIONEER AND FOLLOWER FIRMS' MARKET AND NONMARKET ACTIONS IN THE EUROPEAN MOBILE TELEPHONE INDUSTRY

This study examines the relationship between erosion of the first-mover’s market share and the differences in competitive behaviour of pioneer firms and followers. Particularly, we pay particular attention to market actions related to innovation, pricing and promotion, and to non-market actions related to judicial issues. The empirical study has been carried out with companies that are present in a dynamic context, such as the European mobile telephone industry. Our results show that when followers take more non-market actions than pioneers the negative effect on the firstentrant’s advantage is more significant. On the contrary, we have not found a significant impact of innovating and pricing actions.

Performance analysis of hybrid MTS/MTO systems with stochastic demand and production

We present a comprehensive numerical approach with reasonably light complexity in terms of implementation and computation for assessing the performance of hybrid make-to-stock (MTS)/make-to-order (MTO) systems. In such hybrid systems, semi-finished products are produced up front and stored in a decoupling inventory. When an order arrives, the products are completed and possibly customised. We study this system in a stochastic setting: demand and production are modelled by random processes. In particular, our model includes two coupled Markovian queues: one queue represents the decoupling inventory and the other the order backlog. These queues are coupled as order processing can only occur when both queues are non-empty. We rely on matrix analytic techniques to study the performance of the MTO/MTS system under non-restrictive stochastic assumptions. In particular, we allow for arrival correlation and non-exponential setup and MTS and MTO processing times, while the hybrid MTS/MTO system is managed by an (s,S)-type threshold policy that governs switching from MTO to MTS and back. By some numerical examples, we assess the impact of inventory control, irregular order arrivals, setup and order processing times on inventory levels and lead times