Time Of Product Launch Research Articles

Implementation of risk-sharing agreements in Saudi Arabia: Comparison and reflection on the NICE Model

In recent years, healthcare spending has increased, due to factors such as aging population, lifestylebased diseases, and high-cost health technologies. These factors have put enormous pressure on policymakers to curtail costs and shift towards value-based healthcare system. In this system, drug companies must demonstrate the value of their products in real-world settings. However, evidence may not be available at the time of product launch, leading to delays in reimbursement decisions and access of patients to products. To address this gap, risk-sharing agreements (RSA) have been introduced between manufacturers and payers. The most common type of RSA is the financial-based agreement which may take various forms such as annual sales caps, price-volume agreements, and comparator rebates. These agreements allow for rapid access to innovative medications. Another type of RSA is the outcome-based agreement which ties reimbursement to the real-world outcomes of products. These agreements are more complex, but they are expected to grow rapidly with the availability of real-world data. In the Middle East, the use of RSA is limited, although it is expected to increase with the ongoing shift towards a value-based healthcare system and introduction of health technology assessment. Saudi Arabia is leading these efforts in the region. This study was aimed at describing the current status of RSAs, trends in utilization of RSAs, and challenges of RSA implementation in Saudi Arabia (KSA). Real-world examples of RSAs in various healthcare sectors are also provided. Overall, the use of RSA facilitates access to innovative medications while ensuring value for money and efficient utilization of limited healthcare resources

The impact of external reference pricing on pharmaceutical costs and market dynamics

Growth in the cost of prescription drugs in the US has generated significant interest in the use of external reference pricing (ERP) to tie prices paid for drugs to those in other countries. We used data from the Pricentric ONE™ database, an international drug pricing database, to examine product launch timing, launch price, and price changes from January 2010 – October 2021 in both ERP and non-ERP settings, with a focus on 100 high-priced drugs of interest to Medicare and Medicaid. We found that ERP policies were associated with a 73% reduction in the likelihood of drug launch within 9 months of regulatory approval relative to non-ERP settings. In addition, while ERP was associated with statistically significant reductions in annual drug price changes, such policies did not impact launch price. In addition, no single ERP feature (e.g., number of countries referenced, ERP calculation) was materially associated with the outcomes of interest. We conclude that ERP policies do not appear to impact drug launch price and may delay access to new therapies, raising questions about the utility of such policies in the US and potential consequences abroad.

Transformation of triple helix model in the conditions of innovative ecosystems formation in industry

Growing attention to innovations as one of the key factors for ensuring sustainable development in the strategic perspective has determined their active study, analysis of causes and sources of occurrence, creation of formation and dissemination models. Models of innovative development have become the object of this study. The constant increase in the volume of interactions, the increased specialization of individual elements, the need for a sharp reduction in the time of product launch to the market and the increase in the number of subjects involved in the innovation process, closely interconnected within a single continuous flow, are reflected in spiral cycle models, one of the most common among which is the triple helix model. Innovative development presentation in the form of spiral cycles and triple helix models, in particular, served as the object of research. The subject of the study was changes in the triple helix model caused by modern transformations of the external environment and subjects of interaction themselves, modification of their roles and management specifics to achieve sustainable development based on the innovation flow. The aim was to develop methodological support for regional innovation potential strengthening through the formation of a unified environment based on the principles of open innovation and contributing to the creation of scientific and technical information networks, as well as opportunities for their commercialization. As a result of the study: noting problems highlighted in the analysis of conceptual models of innovative processes implementation at the present stage, as well as taking into account peculiarities of their practical existing application conditions and their development trends, the article describes the developed modified model of the triple helix. Authors highlight the need for an ecosystem approach to the consideration of innovation processes implementation and management. Such modular structural representation of it can be used to innovative processes implementation model, monitoring and forecasting the nature and dynamics of the structure and behavior of these ecosystems constituent elements.

Competitive Interplay of Production Decisions: Rivalry Between Established and Startup Firms

This paper's novelty is the modeling of competition in production quantity and product-launch timing, which has been silent regarding the impact of these interdependent decisions on firm survival. We rigorously address the competitive interplay between a startup and an established rival by developing a game-theoretic model that captures the startup's vulnerability to failure through maximizing its survival likelihood. We allow the established rival to behave strategically by anticipating the startup's timing and production decisions prior to making its own production decision. We propose that unless the market-entry investment is low, a survival-maximizing startup should wait to launch its product, and do so with a larger production output than the established rival, when delaying the product launch enables the startup to charge a high price. Insights on the established firm involve the benefit from behaving strategically, which is when competing with either a survival-maximizing or profit-maximizing startup. If the market-entry investment is large, comparing a survival-maximizing startup with a profit-maximizing startup suggests that the former produces at a larger scale than the latter when either startup competes with an established rival, which in turn is forced to reduce its production level.

The Effects of Autoscaling in Cloud Computing

Web-based firms often rely on cloud-based computational resources to serve customers, but the number of customers they will serve is rarely known at the time of product launch. A recent innovation in cloud computing, known as autoscaling, allows companies to automatically scale their computational load up or down to match customer demand. We build a game theory model to examine how autoscaling will affect firms’ decisions to enter a new market and the resulting equilibrium prices, profitability, and consumer surplus. The model produces novel results depending on the likelihood of a firm’s success in the new market, differentiation among potential entrants, and the cost of computational capacity. For instance, in contrast to previous capacity commitment models with demand certainty, we show that autoscaling can mitigate price competition if the likelihood of a firm’s success in the market is moderate and the cost of capacity is sufficiently low. This is because without autoscaling, the firms’ uncertainty about demand would lead to excessive computational capacities and thus aggressive price competition. We also find that when the likelihood of success is sufficiently high, autoscaling facilitates entry for one firm yet deters a second firm from simultaneously entering the market. The online appendix is available at https://doi.org/10.1287/mnsc.2017.2891 . This paper was accepted by Juanjuan Zhang, marketing.

When marketing strategy meets culture: the role of culture in product evaluations

This research investigates how national culture interacts with marketing strategy to influence consumers’ organic post-consumption satisfaction ratings of entertainment products rich in cultural content. Drawing upon a communication theory framework, we develop hypotheses concerning multiple interaction effects between culture and marketing strategies on consumers’ product evaluations. We test these hypotheses by analyzing consumer reviews of 260 movies in 25 country markets. In support of our hypotheses, we find that the cultural congruence between the product and the market improves consumer reviews, and that the effect is stronger in cultures characterized by collectivism, femininity, and uncertainty avoidance, as well as for products more heavily loaded with cultural content. In addition, we find that the negative effect of delay in product launch timing weakens for cultures characterized by long-term orientation, and that the positive effect of advertising spending on consumer evaluations is stronger in cultures characterized by high power distance belief. These results provide practical insights into how managers should make decisions concerning product design, launch timing, and advertising strategies in international markets.

Competitive Interplay of Production Decisions: Rivalry between Established and Startup Firms

This article’s novelty lies within the modeling literature on competition in production quantity and product-launch timing, which has been silent regarding the impact of these interdependent decisions on firm survival. We rigorously address the competitive interplay between a startup and an established rival by developing a game-theoretic model that captures the startup’s vulnerability to failure through maximizing its survival likelihood. We allow the established rival to behave strategically by anticipating the startup’s timing and production decisions prior to making its own production decision. We propose that unless the market-entry investment is low, a survival maximizing startup should wait to launch its product, and do so with a larger production output than the established rival, when delaying the product launch enables the startup to charge a high price. Insights on the established firm involves when it profits from behaving strategically, which is only when competing with a survival-maximizing startup and not when competing with a profit-maximizing startup. If the market-entry investment is large, comparing a survival-maximizing startup to a profit-maximizing startup suggests that the former produces at a larger scale than the latter when either startup competes with an established rival, which in turn is forced to reduce its production level.

New product launch decisions with robust optimization

We consider a problem where a company must decide the order in which to launch new products within a given time horizon and budget constraints, and where the parameters of the adoption rate of these new products are subject to uncertainty. This uncertainty can bring significant change to the optimal launch sequence. We present a robust optimization approach that incorporates such uncertainty on the Bass diffusion model for new products as well as on the price response function of partners that collaborate with the company in order to bring its products to market. The decision-maker optimizes his worst-case profit over an uncertainty set where nature chooses the time periods in which (integer) units of the budgets of uncertainty are used for worst impact. This leads to uncertainty sets with binary variables. We show that a conservative approximation of the robust problem can nonetheless be reformulated as a mixed integer linear programming problem, is therefore of the same structure as the deterministic problem and can be solved in a tractable manner. Finally, we illustrate our approach on numerical experiments. Our model also incorporates contracts with potential commercialization partners. The key output of our work is a sequence of product launch times that protects the decision-maker against parameter uncertainty for the adoption rates of the new products and the response of potential partners to partnership offers.

Commercialization of Platform Technologies: Launch Timing and Versioning Strategy

Many emerging entrepreneurial applications and services connect two or more groups of users over Internet‐based information technologies. Commercial success of such technology products requires astute business practices related to product line design, price discrimination, and launch timing. We examine these issues for a platform firm that serves two markets—labeled as user and developer markets—such that the size of each market positively impacts participation in the other. In addition, our model allows for sequential unfolding of consumer and developer participation, and for uncertainty regarding developer participation. We demonstrate that product versioning is an especially attractive strategy for platform firms, that is, the trade‐off between market size and margins is tilted in the direction of more versions. However, when expanding the product line carries substantial fixed costs (e.g., marketing cost, cost of additional plant, increased distribution cost), then the uncertainty in developer participation adversely impacts the firm's ability to offer multiple versions. We show that for established firms with lower uncertainty about developer participation, the choice is essentially between an expanded or minimal product line. Startups and firms that are entering a new product category are more likely to benefit from a “wait and see” deferred expansion strategy.

Common Drug Review Recommendations

The Common Drug Review (CDR) was created to provide a single process to review the comparative clinical efficacy and cost effectiveness of new drugs, and then to make formulary listing recommendations to Canadian publicly funded drug benefit plans. The objective was to conduct an in-depth analysis of Canadian Expert Drug Advisory Committee (CEDAC) recommendations to date, to explore predictors and possible explanatory factors associated with negative recommendations. Final recommendations were identified from inception (September 2003) to 31 December 2009. Using only publicly available information, recommendations were analysed under the following categories: submission specifics, drug characteristics, clinical factors and economic factors. Descriptive analyses were conducted, followed by statistical analyses, to determine which factors independently predicted a 'do not list' (DNL) recommendation. The database consisted of 138 unique final recommendations. The overall DNL rate was 48%. Significant differences in DNL rates were observed between therapeutic areas, ranging from 0% for HIV antivirals up to 88% for analgesic drugs. In the univariate analysis, several factors were significantly associated with a DNL recommendation, including first-in-class drugs and use of clinical scales as an outcome. In the multivariate regression, four factors were significantly predictive of a DNL recommendation: clinical uncertainty (odds ratio [OR] 14), price higher than comparators (OR 9), request for reconsideration (OR 10) and price as the only economic evidence used (OR 18). Incremental cost-effectiveness thresholds were not predictive of recommendations. The hypothesis that economic factors did not impact recommendations when clinical factors were included first was supported by the analysis. This analysis documented an evidence-driven process that simultaneously weighted multiple factors. Clinical uncertainty and price considerations, but not economic results, had a strong impact on the recommendations. Insufficiency of clinical evidence may have resulted from the gap in evidence available at the time of product launch and the absence of demonstrated benefits to support innovative drugs.

Key advances in the presilicon functional verification of the IBM zEnterprise microprocessor and storage hierarchy

This paper highlights key advances in the presilicon verification effort of the IBM zEnterprise® 196 (z196) microprocessor and storage hierarchy. It focuses on the unique set of verification challenges as well as the process innovations that address them. At the time of product launch, the z196 system represented the industry's fastest and most scalable enterprise system, with up to 80 customer-configurable out-of-order core processors operating at 5.2 GHz. In addition to offering industry-leading performance, the z196 system builds upon its leadership in reliability by introducing a new redundant array of independent memory (RAIM) technology into its memory subsystem. The new product features in this system drove innovations in all aspects of processor functional verification, including stimulus generation, functional checking, debugging, and coverage. A new hybrid RAIM verification methodology, which includes both formal and random methods, is described. Many process and methodology improvements were made to improve developmental collaboration across a global team. These enhancements include a simulation development environment that uses common shared components across functional partitions, as well as a shared cache loader that was used across multiple environments. We also present a self-configuring test-case generation process that focused on the coverage of functional stimulus.

Use of the self-controlled case series method in drug safety assessment

The randomized double-blind controlled clinical trial (RCT) is the undisputed gold-standard for assessing drug efficacy. However the RCT is usually insufficiently powered, or too brief, to detect rare but serious adverse effects or modest but important increases in the risk of common disease outcomes (such as coronary heart disease events) that can have a major population impact in absolute terms. Pooling individual trials via meta-analyses sometimes helps but the reporting of information on adverse effects in clinical trials is often incomplete or poorly quantified, particularly when compared to the efficacy endpoints. Clinically significant and unexpected abnormal laboratory values may not be detected as not all are routinely included in trial protocols. Most RCTs also tend to exclude the elderly, patients with co-morbidity or pregnancy, and this reduces the generalisability of these data. Therefore, at the time of product launch, there are often limited safety data of any new drug, in both the short- and longer-term which is directly applicable to that of the target population. Drugs in use therefore need to remain under constant surveillance (pharmacovigilance) and study by observation (pharmacoepidemiology) Pharmacovigilance systems identify safety signals (signal detection) and thus serve to generate hypothesis. Pharmacoepidemiology tests such hypothesis (signal validation) and quantifies the risk. Both pharmacovigilance and pharmacoepidemiology have limitations, are complementary and only partially overlap.

Commercialization of Platform Technologies: Launch Timing and Versioning Strategy

Many emerging entrepreneurial applications and services connect two or more groups of users over Internet-based information technologies. Commercial success of such platform technology products requires adoption of astute business practices related to product line design, price discrimination, and launch timing. We examine these issues for a platform firm that serves two markets, labeled as user and developer markets, with the latter emerging after the user market is proven. While the size of each market positively impacts participation in the other, our model allows for uncertainty regarding developer participation. We demonstrate that product versioning is an especially attractive strategy for platform firms, i.e., the tradeoff between market size and margins is tilted in the direction of more versions. However, when expanding the product line carries substantial fixed costs (e.g., marketing cost, cost of additional plant, managing multiple sets of inventory, increased distribution cost) then the uncertainty in developer participation adversely impacts the firm’s ability to offer multiple versions. We show that for established firms with lower uncertainty about developer participation, the choice is essentially between an expanded or minimal product line. Startups and firms that are entering a new product category are more likely to benefit from a “wait and see” deferred expansion strategy. Still, we demonstrate that uncertainty in developer participation can make early expansion desirable because it expands the installed base and, with the consequent increase in developer participation levels, increases the long-term incremental gain from product line expansion.

Contributors

Contributors

Correction to the Paper “Optimal Product Launch Times in a Duopoly: Balancing Life-Cycle Revenues with Product Cost”

The aim of this note is to correct an error in the formulation of Theorem 1 by Savin and Terwiesch [Savin, S., C. Terwiesch. 2005. Optimal product launch times in a duopoly: Balancing life-cycle revenues with product cost. Oper. Res. 53(1) 26–47].

The Effects of Competition in Short Product Life-Cycle Markets: The Case of Motion Pictures

It is critically important to understand the relationship between new product launch strategies and their interaction with the competitive environment, which results in the successful introduction of new products. Deciding when to launch new products is among the most significant issues facing managers when formulating new products strategy, especially for products with short product life cycles. However, little extant research has focused on the interaction of product launch timing and the competitive market environment. This study explores the effects of four types of competitive threats on the market performance of short product life-cycle products. Threats from new products and incumbents are possible. Also, products in the same category and those in related product categories exert competitive pressures. In this paper, a framework of competitive threats is developed, and research questions are constructed and empirically tested using the motion pictures industry as the focus of this research. A set of simultaneous equations was estimated using a sample of 2,948 movies introduced in the U.S. market between 1997 and 2004. The results show that all competition types have negative direct, indirect (as mediated by distribution intensity), and total effects on the performance of a new product. For a focal product, incumbent products exert a greater negative impact on performance than new entrants. Surprisingly, products in different, but related, categories are more harmful to the performance of products than products in the same category. The results have important implications for launch timing and new product performance.

Alternative market entry strategies for medical device products. How to develop relevant data when clinical information is lacking

The introduction of new products in the medical devices market is a critical activity. However, launches are not always accompanied by clinical or economic evidence to support the products' use, and, as a consequence, a company's commercial strategy is sometimes hampered. Using a real-life example, we propose a methodology that can generate relevant information with a goal of increasing product penetration. The product is an antiseptic suture that could reduce the rate of surgical infection. Although preclinical data for the product are positive, generating efficacy data through high-quality, prospective, randomized clinical trials is a technically difficult task. This results in a lack of evidence to support the claim of surgical site infection reduction at the time of product launch. To address this, we designed two animal models replicating orthopedic surgery (knee replacement) and, in parallel, we prepared an economic analysis. Our results could be used to support commercial activities and to accelera...

Improving product launch times and product design through a service assembly environment

Surely it must be possible to bring products to market faster and do it cheaper? These two requirements have for many years challenged the entire telecommunications industry. Complexity is a characteristic of today's communications environments. Making this complexity manageable is the key to enabling these requirements to be met, but how? Within the intelligent network's area it has been possible to break down the needs of the customer into a series of blocks that can be designed and deployed in flexible arrangements. To design and run these blocks two environments are used, the service assembly environment (SAE) and the service execution environment. This paper will look at the former to examine what steps need to be taken to apply these principles to the full range of communications products that a large telecommunications company like BT offer. This paper defines the SAE as including both the design phase of a product as well as its deployment into the portfolio and systems.

Optimal Product Launch Times in a Duopoly: Balancing Life-Cycle Revenues with Product Cost

We present a model describing the demand dynamics of two new products competing for a limited target market. The demand trajectories of the two products are driven by a market saturation effect and an imitation effect reflecting the product experience of previous adopters. In this general setting, we provide analytical results for the sales trajectories and life-cycle sales of the competing products. We use these results to study the impact of launch time on overall life-cycle sales. We consider the perspective of one of the competing products and model the trade-off between the lost revenues resulting from a delayed launch and the lower unit-production costs. We find that the profit-maximizing launch time exhibits a counterintuitive behavior. In particular, we show that a firm facing a launch time delay from a competing product might benefit from accelerating its own product launch, as opposed to using the softened competitive situation to further improve its cost position. We identify conditions under which a marginal cost-benefit analysis leads to suboptimal launch-time decisions. Finally, we analyze the Nash equilibrium in launch-time decisions of the two competing products.

Economic endpoints in clinical trials

Healthcare decision makers are increasingly requesting information on the cost and cost-effectiveness of new medicines at the time of product launch. In order to provide this information, data on healthcare resource utilization and, in some cases, costs, may be collected in clinical trials. In this paper, we discuss some of the issues statisticians need to address when it is appropriate to include these economic endpoints in the trial. Several design issues are discussed, including the alternative types of and methods for collecting economic endpoint data, sample size and generalizability. Alternative approaches in the analysis of resource utilization, cost and cost-effectiveness are also presented. Finally, several of the analytic approaches are applied to actual data from a clinical trial.