Value creation by Turkish enterprises

This study focuses on the resurgence of the automotive and appliance sectors in Turkey’s recent years. The analysis of both these sectors reveals some interesting lessons about technology management and investment strategies for companies to invest in Turkey. We discuss the major changes and project the future in both industries. Turkey seems to be a clear winner though there are some factors that could reverse the trend. The research is a joint field study partne rship between Carnegie Mellon and Sabanci Universities

Cost of Quality in Software Products: An Empirical Analysis

Computer software has emerged as a major worldwide industry, estimated at $450B for 1995 of which$225B is attributable to US firms [Boehm, 1987]. Yet, in many organizations, costs and schedules for software projects are largely unpredictable, and product quality is often poor [DeMarco and Lister, 1993]. This underscores the need to study both the quality of the software product and the life-cycle cost incurred in the development and maintenance of the products. Increasing expenditure in software has caught the attention of researchers. Identifying software productivity factors and estimating software costs continue to be important research topics [Mukhopadhyay and Kekre, 1992; Banker et al., 1993]. Researchers have adopted both empirical and theoretical approaches to better understand the process of software development and maintenance. Though software cost continues to be an important research question, competition in the software industry and the increased role of software in everyday life have also made development cycle time and quality important research issues. The quality of software has been studied mainly from defect analysis and software maintenance perspectives. Empirical research has analyzed tradeoffs between software quality and maintenance, and examined drivers of software maintenance costs [Banker, et al., 1993]. Practitioners in the software industry are still faced with the challenge of understanding the key tradeoffs in a software project in order to deliver quality products to customers on time and without cost overruns. This underscores the need to study the various factors that influence the life-cycle cost and quality in software products. Moreover, the effect of the process used in a software project on the outcome of the project in terms of cost to the software developer and quality of the product has not been examined rigorously. Thus in this research, we propose to model the life-cycle cost and quality of software products based on the factorsrelated to product, people, process and technology deployed in the software project

Comparative Analysis of Incumbent and Emerging Liquefied Natural Gas Regasification Technologies

Energy plays a fundamental role in both manufacturing and services, and natural gas is quickly becoming a key energy source worldwide. Facilitating this emergence is the expanding network of ocean-going vessels that enable the matching of natural gas supply and demand on a global scale by transporting it in the form of liquefied natural gas (LNG) for eventual regasification at its destination. Until very recently only one type of technology has been available for transporting and regasifying LNG: Conventional LNG vessels and land based LNG regasification. It is now possible to transport and regasify LNG onboard special LNG vessels. Companies such as Excelerate Energy and Höegh LNG are currently developing LNG supply chains based on this new technology. Motivated by this recent development we engaged executives at Excelerate Energy to develop and apply to data an integrated analytic framework to compare these incumbent and emerging technologies. Our analysis brings to light basic principles delineating when to deploy each technology and how to configure the emerging technology. Some of our findings challenge conventional wisdom on the role to be played by the emerging technology; others provide answers to open questions faced by companies currently engaged in the commercial deployment of this technology. In addition, our integrated analytic framework has potential relevance for the evaluation of new technologies beyond this specific application

Multi-item Batching and Minimization of Queueing Delays

Queueing delays in complex manufacturing facilities are a major component of manufacturing lead times. Lead times are in turn a primary determinant of manufacturing performance since they affect work-in-process inventory levels, safety stock requirements and schedule performance. Similarly, in service contexts, the costs of waiting in queues are an important aspect of service performance. In many manufacturing and in some service facilities, it is possible to control queueing behavior through batching policies. Here a single facility multi-item (multi-class) model relating batching to queueing delays is formulated. Heuristic batching rules are developed, which also give insights into the relationship of batch size to system parameters

Optimal Energy Procurement in Spot and Forward Markets

Storage capacity for energy, such as electricity, natural gas, and oil, is limited. Thus, spot and forward purchases for delivery on the usage date play an important role in matching the supply and the uncertain demand of energy. Transaction costs tend to be larger in spot than forward energy, and more generally commodity, markets. Hence, partially procuring supply in the forward market, rather than entirely in the spot market, is a potentially valuable real option. We call this option the forward procurement option. The study of this option from the perspective of differential transaction costs has received little attention in the literature. We thus formulate and analyze a parsimonious procurement model with differential spot and forward transaction costs and correlated spot demand and nominal price random variables. Our analysis, in part based on natural gas data, sheds novel light on the value of the forward procurement option and its optimal exercise, as well as their sensitivities to parameters of interest. Our main insight is that procuring the demand forecast in the forward market is nearly optimal on the instances that we consider. This greatly simplifies the management of this option. We obtain analogous results with a richer model in which the supply procured in the forward market is delivered at multiple dates. Beyond energy, our research has potential relevance for the procurement of other commodities, such as metals and agricultural products.</p

Commodity Procurement with Demand Forecast and Forward Price Updates

Commodities, ranging from natural gas to memory chips, can be procured both by trading on the date in spot markets and in advance in forward markets. Transaction costs, such as brokerage fees, are typically higher in spot markets than in forward markets. Moreover, the forecast of a ¯rm's commodity requirement (demand) for a given future date typically changes in an uncertain fashion over time. Thus, although the dynamics of forward and spot prices are notoriously uncertain, firms that procure commodities face the dilemma of choosing between early and possibly less expensive commitments with residual demand uncertainty and late and possibly more expensive sourcing of the exact amount needed. We investigate this issue by developing and analyzing a model of commodity procurement for a single future date. Our model generalizes models available in the real options and operations management literature, by simultaneously considering correlated demand forecast and forward price updates in a setting characterized by multiple forward transactions and a single spot transaction. We derive the structure of the optimal procurement policy and discuss its computation in cases of practical interest. In a numerical study, based on applying our model to natural gas data, we offer managerial insights on the effects that demand forecast and forward price updates, both in isolation and combined, have on the value of a firm's procurement policy. We also assess the sensitivities of these effects to parameters of interest and the potential managerial relevance of the combined effect. Our model and results have significance beyond the specific application