Upgrade Decisions Research Articles

Does AMD Spur Intel to Innovate More?

We estimate an equilibrium model of dynamic oligopoly with durable goods and endogenous innovation to examine the effect of competition on innovation in the personal computer microprocessor industry. Firms make dynamic pricing and investment decisions while consumers make dynamic upgrade decisions, anticipating product improvements and price declines. Consistent with Schumpeter, we find that the rate of innovation in product quality would be 4.2 percent higher without AMD present, though higher prices would reduce consumer surplus by $12 billion per year. Comparative statics illustrate the role of product durability and provide implications of the model for other industries.

Consumer Valuation of Modularly Upgradeable Products

Although product modularity is often advocated as a design strategy in the operations management literature, little is known about how consumers respond to modular products. In this research we undertake several experiments to explore consumer response to modularly upgradeable products in settings featuring technological change. We consider both the initial product choice (between a modularly upgradeable product and an integral one) and the subsequent upgrade decision (replacement of a module versus full product replacement). First, we show that consumers tend to discount the cost savings associated with modular upgrades excessively (insufficiently) when the time between the initial purchase and the upgrade is short (long). This suggests that modular upgradability as a product feature has higher profit potential for slowly rather than rapidly improving products. Second, we observe a preference reversal between the initial purchase and the point of upgrade: At the point of initial purchase, people foresee making a full product replacement in the future, yet, when faced with the actual upgrade decision, they are more likely to revert to modular upgrades. Finally, we discuss and test several pricing and product design strategies that the firm can use to respond to these cognitive biases. This paper was accepted by Kamalini Ramdas, entrepreneurship and innovation.

Consumer Valuation of Modularly Upgradeable Products

While product modularity is often advocated as a design strategy in the operations management literature, little is known about how customers respond to modular products. In this research we undertake several experiments to explore consumer response to modularly upgradeable products in settings featuring technological change. We consider both the initial product choice (between a modularly upgradeable product and an integral one) and the subsequent upgrade decision (replacement of a module vs. full product replacement). First, we show that consumers tend to discount the cost savings associated with modular upgrades excessively (insufficiently) when the time between the initial purchase and the upgrade is short (long). This suggests that modular upgradability as a product feature has higher profit potential for slowly rather than rapidly improving ones. Second, we observe a preference reversal between the initial purchase and the point of upgrade: At the point of initial purchase, people foresee making a full product replacement in the future, yet, when faced with the actual upgrade decision, they are more likely to revert to modular upgrades. Finally, we discuss and test several pricing and product design strategies that the firm can use to respond to these cognitive biases.

Multi‐hazard upgrade decision making for critical infrastructure based on life‐cycle cost criteria

AbstractThe life‐cycle cost can be regarded as a benchmark variable in decision making problems involving the retrofit and upgrading of existing structures. A critical infrastructure is often subjected to more than one hazard during its lifetime. Therefore, the problem of evaluating the life‐cycle cost involves uncertainties in both loading and structural modeling parameters. The present study is a preliminary study aiming to calculate the expected life‐cycle cost for a critical infrastructure subjected to more than one hazard in its service lifetime. A methodology is presented that takes into account both the uncertainty in the occurrence of future events due to different types of hazard and also the deterioration of the structure as a result of a series of events. In order to satisfy life safety conditions, the probability of exceeding the limit state of collapse is constrained to be smaller than an allowable threshold. Finally, the methodology is implemented in an illustrative numerical example which considers a structure subjected to both seismic hazard and blast hazard in both upgraded and non‐upgraded configurations. It is demonstrated how expected life‐cycle cost can be used as a criterion to distinguish between the two choices while satisfying the life safety constraint. Copyright © 2011 John Wiley & Sons, Ltd.

Does AMD Spur Intel to Innovate More?

We estimate an equilibrium model of dynamic oligopoly with durable goods and endogenous innovation to examine the effect of competition on innovation in the PC microprocessor industry. Firms make dynamic pricing and investment decisions while consumers make dynamic upgrade decisions, anticipating product improvements and price declines. Consistent with Schumpeter, we find the rate of innovation in product quality would be 4.2 percent higher without AMD present, though higher prices reduce consumer surplus by $12 billion per year. Comparative statics illustrate the role of product durability and provide implications of the model for other industries.

TYING, COMPATIBILITY AND PLANNED OBSOLESCENCE*

According to the hypothesis of planned obsolescence, a durable goods monopolist without commitment power has an excessive incentive to introduce new products that make old units obsolete, and this reduces its overall profitability. In this paper, I reconsider the above hypothesis by examining the role of competition in a monopolist's upgrade decision. I find that, when a system add‐on is competitively supplied, a monopolist chooses to tie the add‐on to a new system that is only backward compatible, even if a commitment of not introducing the new system is available and socially optimal. Tying facilitates a price squeeze.

Dynamic Resource Capabilities: Managing Workforce Knowledge with a Technology Upgrade

Although managers invest in new technology to improve performance, often the benefits sought are elusive while the costs incurred far exceed expectations. The literature offers insights to help explain this phenomenon. Evidence suggests that, while carefully considering the purchase cost, managers often underestimate the costs and planning necessary for proper implementation. Consequently, short-term problems arise and long-term benefits are not realized. A model is introduced that integrates workforce knowledge management with the technology upgrade decision. The manager upgrades technology or pursues general training of the workforce in response to depreciation in the ability of each resource to drive net income over time. Depreciation occurs because of changes in consumer preferences and competition. Although adding to technology capability, an upgrade makes a portion of workforce knowledge obsolete. The manager invests in preparatory training prior to the upgrade to reduce obsolescence. Whereas general training is pursued to respond to depreciation by enhancing the ability of the workforce to improve existing products or create new products, preparatory training is technology-specific and focused on preparing for a technology upgrade. We find that the rates of preparatory and general training follow entirely different paths over time. Conditions are given where a manager uses one training strategy as a substitute for or complement to the other. We show that training strategies are not only impacted by learning phenomena such as the rate of forgetting, but also by the rates of technology depreciation and advancement. We show how workforce learning phenomena impact the technology upgrade decision.

Split sovereign ratings and rating migrations in emerging economies

This paper presents evidence on sovereign rating heterogeneity in emerging economies. Split rated sovereigns are prone to be upgraded (downgraded) by the agency from whom a lower (higher) rating exists. The harsher the split ratings between two agencies, the greater the effect on probabilities of future rating changes. Split ratings among Moody's, S&P and Fitch are influential on their rating migrations. The rating dynamics of Capital Intelligence, Japan Credit Rating Agency and Japan Rating & Investment Information are affected by their rating disagreements with the larger agencies. Only Moody's upgrade decisions are influenced by rating differentials with the smaller agencies.

Racing to market leadership: Product launch and upgrade decisions

Firms might not launch a next generation product as soon as a more efficient technology or a better product design is ready. We use a stylized model to analyze firms’ product launch and upgrade decisions in an incumbent-vs-entrant setting. We find that large profit margins from the next generation product alone do not provide the entrant sufficient incentives to launch the next generation product, although small profit margins will deter the entrant from joining the competition. If the entrant intends to enter the market at an earlier time, it should consider process improvements that lower the firm's launch costs of the current generation product. In addition, the incumbent must respond strategically to the entrant's arrival. In particular, when anticipating a late arrival of the entrant, the incumbent should upgrade to the next generation earlier. The incumbent also has a cost advantage in the race to launch the next generation product.

Social and Private Learning with Endogenous Decision Timing

Firms often face choices about when to upgrade and what to upgrade to. We discuss this in the context of upgrading to a new technology (for example, a new computer system), but it applies equally to the upgrading of processes (for example, a new organizational structure) or to individual choices (for example, buying a new car). This paper uses an experimental approach to determine how people address such problems, with a particular focus on the impact of information flows. Specifically, subjects face a multi-round decision, choosing when (if ever) to upgrade from the status quo to either a safe or a risky new technology. The safe technology yields more than the status quo, and the risky technology may yield either less than the status quo or more than the safe technology. Every round, subjects who have not yet upgraded receive noisy information about the true quality of the risky technology. Our focus on the timing of endogenous choice is novel and differentiates the results from previous experimental papers on herding and cascades. We find that, in the single-person decision problem, subjects tend to wait too long before choosing (relative to optimal behavior). In the second treatment, they observe payoff-irrelevant choices of other subjects. This turns out to induce slightly faster decisions, so the irrationality of fads actually improves profits in our framework. In the third and final treatment, subjects observe payoff-relevant choices of other subjects (that is, others who have the same value for the risky technology but independent private signals). Behavior here is very similar to the second treatment, so having real information does not seem to have a strong marginal effect. Overall we find that social learning, whether or not the behavior of others is truly informative, plays a large role in upgrade decisions and hence in technology diffusion.

Expanding Business-to-Business Customer Relationships: Modeling the Customer's Upgrade Decision

This article develops a model of a business customer's decision to upgrade service contracts conditional on the decision to renew the contract. It proposes that the firm's upgrade decision is influenced by (1) decision-maker perceptions of the relationship with the supplier, (2) contract-level experiences, and (3) interactions between firm- and contract-level variables. The authors model the firm's decision as a binary logit model with random parameters for the contract-level variables and fixed parameters for the firm-level variables. They estimate the model with data describing more than 2000 service contracts and find that decision-maker satisfaction, service quality, and price have a significant effect on the decision to upgrade; price and satisfaction also moderate the effect of service quality on the decision. Simulations indicate that modest improvements in service quality for a focal contract can have a relatively large, positive effect on the likelihood that the firm will upgrade. The results suggest that suppliers need to manage their firm relationships at both the individual contract level and the overall firm level. In addition, the results suggest specific windows of opportunity for suppliers when firms may be more likely to upgrade to higher-level service contracts.

Expanding Business-to-Business Customer Relationships: Modeling the Customer's Upgrade Decision

This article develops a model of a business customer’s decision to upgrade service contracts conditional on the decision to renew the contract. It proposes that the firm’s upgrade decision is influenced by (1) decision-maker perceptions of the relationship with the supplier, (2) contract-level experiences, and (3) interactions between firmand contract-level variables. The authors model the firm’s decision as a binary logit model with random parameters for the contract-level variables and fixed parameters for the firm-level variables. They estimate the model with data describing more than 2000 service contracts and find that decision-maker satisfaction, service quality, and price have a significant effect on the decision to upgrade; price and satisfaction also moderate the effect of service quality on the decision. Simulations indicate that modest improvements in service quality for a focal contract can have a relatively large, positive effect on the likelihood that the firm will upgrade. The results suggest that suppliers need to manage their firm relationships at both the individual contract level and the overall firm level. In addition, the results suggest specific windows of opportunity for suppliers when firms may be more likely to upgrade to higherlevel service contracts.

A non-invasive method for link upgrade planning using coarse-grained measurements

A basic problem faced by network operators concerns the provisioning of bandwidth to meet quality of service (QoS) requirements. In the network core, the preferred solution is simply to overprovision link bandwidth. We propose a new approach to making link upgrade decisions based only on readily available coarse SNMP measurements.

Deciding to upgrade packaged software: a comparative case study of motives, contingencies and dependencies

Packaged software is widely adopted and has become an integral part of most organizations’ IT portfolios. Once packaged software is adopted, upgrades to subsequent versions appear to be inevitable. To date, research on packaged software has not paid attention to the upgrade decision process. To explore this area, we studied cases of upgrades to two widely used packaged software products (SAP and Windows) in a multi-billion dollar division of a Fortune 500 company. From an analysis of the cases, we induced a theoretical model explaining the influences affecting the decisions to upgrade. Our model suggests that upgrade decisions are the outcome of interaction between motivating forces that can originate from internal and external environments, and contingency forces. Business need was found to be one of the key internal requirements, along with organizational risk mitigation policies. Organizational reliance on packaged software also creates dependence on vendors that gives them influence over the organization's upgrade decision. The decision to upgrade is also contingent on the availability of internal resources. Although scarcity of internal resources can postpone an upgrade when the need to upgrade is deferrable, organizations will prioritize internal resources when the upgrade is deemed necessary.

Same vendor, version‐to‐version upgrade decision support model for commercial off‐the‐shelf productivity applications

AbstractCommercial Off‐the‐Shelf (COTS) Productivity Applications have provided a reliable, convenient, and consistent productivity environment for commercial, government, and personal users for over two decades. Vendors today, such as Microsoft and Adobe, typically deliver new capabilities as follow‐on versions or upgrades to existing product lines. Annually, corporations needlessly spend millions of dollars investing in follow‐on versions of currently deployed applications without adequately evaluating upgrade decisions. Exacerbating the problem, vendors release new versions of their productivity applications with increasingly shorter intervals, advertising them as full of new and ‘‘must have’’ capabilities. The decision to upgrade is challenging. Unfortunately, there is a lack of ‘‘same vendor, version‐to‐version’’ upgrade decision support models to assist Information Technology (IT) decision‐makers whether to upgrade or not. As a result, IT decision makers typically employ general strategies that are not based on clear, well‐defined decision attributes, which, in turn, waste valuable IT resources. This research effort proposes an upgrade decision support model for COTS productivity applications based on a multivariable, scenario‐based survey of IT professionals. Using logistic regression analysis, a model is developed using an iterative approach to isolate contributing survey attributes and to produce a statistically significant model. The proposed logistic regression model produces an output based on the probability of upgrading intended to assist an IT professional in productivity application upgrade decisions. © 2006 Wiley Periodicals, Inc. Syst Eng 9: 296–312, 2006

Upgrades and New Purchases

In many industries, firms introduce successive generations of new and enhanced product models to remain competitive. Product enhancements target first-time purchasers and consumers who already own an existing product and are considering upgrading to a new and enhanced product. Upgrade decisions differ from new purchase decisions because they are hindered by the psychological costs associated with the purchase price spent on the existing product. This research examines how the enhanced product can be positioned relative to the existing product to mitigate the psychological costs and facilitate upgrade purchases. A series of studies demonstrate that consumers with existing products are more likely to upgrade when the enhanced product is generally dissimilar to the existing product. Upgraders have stronger preferences than first-time purchasers for enhanced products with new features rather than for improvements on existing features, and they prefer enhancements that focus on a few key features rather than a general enhancement of all features.

Upgrades and New Purchases

Abstract In many industries, firms introduce successive generations of new and enhanced product models to remain competitive. Product enhancements target first-time purchasers and consumers who already own an existing product and are considering upgrading to a new and enhanced product. Upgrade decisions differ from new purchase decisions because they are hindered by the psychological costs associated with the purchase price spent on the existing product. This research examines how the enhanced product can be positioned relative to the existing product to mitigate the psychological costs and facilitate upgrade purchases. A series of studies demonstrate that consumers with existing products are more likely to upgrade when the enhanced product is generally dissimilar to the existing product. Upgraders have stronger preferences than first-time purchasers for enhanced products with new features rather than for improvements on existing features, and they prefer enhancements that focus on a few key features rath...

Managing capacity for telecommunications networks under uncertainty

The existing telecommunications infrastructure in most of the world is adequate to deliver voice and text applications, but demand for broadband services such as streaming video and large file transfer (e.g., movies) is accelerating. The explosion in Internet use has created a huge demand for telecommunications capacity. However, this demand is extremely volatile, making network planning difficult. Modern financial option pricing methods are applied to the problem of network investment decision timing. In particular, we study the optimal decision problem of building new network capacity in the presence of stochastic demand for services. Adding new capacity requires a capital investment, which must be balanced by uncertain future revenues. We study the underlying risk factor in the bandwidth market and then apply real options theory to the upgrade decision problem. We notice that sometimes it is optimal to wait until the maximum capacity of a line is nearly reached before upgrading directly to the line with the highest known transmission rate (skipping the intermediate lines). It appears that past upgrade practice underestimates the conflicting effects of growth and volatility. This explains the current overcapacity in available bandwidth. To the best of our knowledge, this real options approach has not been used previously in the area of network capacity planning. Consequently, we believe that this methodology can offer insights for network management.

A decision framework for enterprise resource planning maintenance and upgrade: A client perspective

AbstractOver the last decade, many large organizations have been shifting from developing their own information system (IS) to licensing and installing large software packages known as enterprise resource planning (ERP) systems. These organizations now face the challenge of maintaining these costly systems and many are about to make their first upgrade decisions. The study reported herein aims to address the following research questions from the ERP‐client perspective: (1) What are the fundamental factors driving ERP maintenance and upgrade decisions? (2) How do these factors differ from those for traditional custom, in‐house software? and (3) Do existing software and hardware replacement models suffice for ERP maintenance and upgrade decision modeling? A single case study method and empirical data analysis were conducted and are presented here. We observe that ERP maintenance and upgrade characteristics are indeed unique in three ways: (1) most organizations maintain and upgrade their ERP systems in order to realize increased business benefits from the systems; (2) a new version upgrade reduces the number of ERP‐client‐done enhancement modifications; and (3) a new version upgrade potentially reduces future legal change patch (LCP) maintenance distributed by the ERP vendor. It was also found that on average LCP maintenance is almost as costly as user enhancements. Based on these findings, we conclude that the existing in‐house software and hardware replacement models are insufficient for ERP situations. We propose a preliminary ERP decision model that overcomes the observed insufficiencies. Copyright © 2001 John Wiley & Sons, Ltd.

Policy analysis for warranty, maintenance, and upgrade of software systems

AbstractMaintenance of large software systems is one of the least‐structured problems in information systems. In this paper, we present a framework to analyze warranty, maintenance, and upgrade decisions for software packages under different market conditions. We discuss the impact of various factors, such as quality, market volatility, and technological obsolescence, on the software supplier's policies and economic return. We identify a class of optimal (or near optimal) policies that are surprisingly robust and easy to implement, and report on the effectiveness of these policies under different market conditions. Copyright © 2001 John Wiley & Sons, Ltd.