Identifying New Product Successes in China

To examine the generalizability of the work of Cooper regarding the correlates of new product success and failure, Mark Parry and Michael Song surveyed new product development managers at 129 state-owned enterprises in the People's Republic of China. Their analysis of 258 reported product successes and failures indicated that relative product advantage and the acquisition of marketing information were highly correlated with new product success, just as in Canada. In addition, several factors not significantly correlated with success in Canadian firms emerged as significant correlates of success in the PRC. These included the level of competitive activity, the timing of the product launch, and the level of proficiency in executing activities in the early stages of the product development process.     

The R&D Effectiveness Index: A Metric for Product Development Performance

Measuring the overall success of product development efforts has been frustrating because there is no generally recognized metric to measure effectiveness. The R&D Effectiveness Index is introduced to address this need. It measures effectiveness by comparing the profit from new products to the investment in new product development. The article provides the details for calculating the index along with alternative interpretations. Michael McGrath and Michael Romeri report that this index was validated through a study of 45 electronic systems companies. They found a strong relationship between the R&D Effectiveness Index and other performance factors and believe that the R&D Effectiveness Index can be used to compare performance, measure improvement, and evaluate business units. Its application is illustrated in a case study.     

Managing Relations Between R&D and Marketing in New Product Development Projects

This article examines the R&D/marketing interface conditions found within an extensive data base of new product development innovation projects. The incidence of different types of problems between these two important functions are analyzed and the effects of these observations on project outcomes are discussed. The article contains a number of recommendations for increasing the success rates of innovation projects by using a model that improves conditions at the R&D/marketing interface.     

Applying Hedonic Pricing Models and Factorial Surveys at Parker Pen to Enhance New Product Success

Walking the path from new product concept to successful commercialization is a tightrope act. Product developers must carefully balance a variety of factors, including predictions of consumer price sensitivity as well as which combination of product attributes will be most valued by the intended market. A well-chosen mix of analytical tools can enhance a firm's chances of accurately predicting market demand. Chuck Tomkovick and Kathryn E. Dobie describe how the integration of two product attribute assessment techniques–hedonic pricing models and factorial surveys–allows product designers to more accurately gauge price sensitivity and market receptivity to new product designs. They also describe how these analytical tools were used to improve decision-making in product development at the Parker Pen Company, and they discuss the role these tools can play in facilitating the transition from concept to commercialization. Hedonic price analysis is an econometric method for determining the value purchasers place on attributes of existing products. In product development, factorial surveys are used to identify the value members of the target market place on new product concepts and prototypes. When used in combination with identified hedonic prices, the responses to a factorial survey allow product developers to predict consumer willingness-to-pay for various combinations of new product attributes. Following development of prototypes for two new product lines, product developers at the Parker Pen Company used hedonic pricing models and factorial surveys as a means for reducing demand uncertainty and for clarifying what consumers were willing to pay for various combinations of product attributes that were under consideration. The integration and use of these techniques involved a five-step process of target market identification, product attribute identification, hedonic price estimation, administering of the factorial survey, and determination of consumer willingness-to-pay. The results of these analyses allowed Parker Pen to better focus product development efforts on those design elements for which test market customers indicated both demand and willingness-to-pay. The Parker Pen Company found hedonic pricing and factorial surveys useful for predicting both the rate and the degree of change in consumers' marginal utility for specific product attributes. The usefulness of these techniques also extends beyond the early stages of new product conception. These techniques are helpful in the development and implementation of dynamic new product marketing mix strategies, including such elements as product design, pricing, channel selection, and promotion.     

On the robustness of the fat-tailed distribution of firm growth rates: a global sensitivity analysis

Firms grow and decline by relatively lumpy jumps which cannot be accounted by the cumulation of small, “atom-less”, independent shocks. Rather “big” episodes of expansion and contraction are relatively frequent. More technically, this is revealed by the fat-tailed distributions of growth rates. This applies across different levels of sectoral disaggregation, across countries, over different historical periods for which there are available data. What determines such property? In Dosi et al. (The footprint of evolutionary processes of learning and selection upon the statistical properties of industrial dynamics. Industrial and corporate change. Oxford University Press, Oxford, 2016) we implemented a simple multi-firm evolutionary simulation model, built upon the coupling of a replicator dynamic and an idiosyncratic learning process, which turns out to be able to robustly reproduce such a stylized fact. Here, we investigate, by means of a Kriging meta-model, how robust such “ubiquitousness” feature is with regard to a global exploration of the parameters space. The exercise confirms the high level of generality of the results in a statistically robust global sensitivity analysis framework.     

Mining History of Gamification Towards Finding Expertise in Question and Answering Communities: Experience and Practice with Stack Exchange

Recently, an online Q&A tool has become an essential part of individual communities and organizations of experts on specific topics. Using the answers to questions about specific topics will help such communities work more efficiently in their fields. Currently, Q&A online communities are adopting gamification to engage users by granting awards to successful users. In this paper, we investigate how to mine award achievement histories to find expertise. We propose the use of sequence analysis and clustering techniques. Specifically, we study the history of Stack Exchange, a large Q&A community that employs gamification. To the best of our knowledge, this is the first study of using award achievement history to find expertise in Q&A communities.     

Gay tourism in a sun and beach destination

Gay tourism is seen as an attractive business opportunity for many destinations. However, there is a lack of research at identifying the resources necessary for success in this type of tourism. This work is aimed at filling this gap by using the premises of the resource based view and transfers them to the analysis of territories to identify the valuable resources that are required for a sun and beach destination to attract gay tourists. To this end, this study has focused on a gay tourism sub niche, tourists lodged in gay-exclusive resorts in Gran Canaria. In order to confirm the validity of this approach, the relationship between the satisfaction of gay tourists and the condition of the valuable resources was studied by means of a robust statistical new method, namely Bayesian model averaging. That method permits the inclusion of uncertainty in the theoretical models that determine destination competitiveness, thus reducing many of the problems that arise in the application of the more conventional statistical methods in this type of analysis.