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This paper explores how two understudied characteristics of a firm's product portfolio, namely, aging of products and (non)innovativeness of products, affect firm survival. The influence of these product portfolio characteristics on organizational mortality can be observed both at the firm and at the industry levels. Paradoxically, the portfolio's influence at the firm and at the industry levels may go in opposite directions. Specifically, I predict that portfolios with aging products make their firms weaker competitors and survivors. However by weakening these firms, “aging” portfolios reduce competitive pressures at the industry level and, therefore, improve firm survival indirectly by changing industry vital rates. In contrast, firms with innovative product portfolios should be stronger survivors. At the same time, they are likely to intensify competition in the industry and, as a result, diminish survival chances of all firms, including those with innovative products. The analyses of all firms’ product portfolios in the worldwide optical disk drive industry, 1983–1999, support these predictions.

Resource redeployment may occur when a firm exits from one line of business and enters another. We suggest that when multiproduct firms identify opportunities in new high-growth markets, their entry will occur alongside exit from low-growth markets when the firm is resource-constrained. For our sample of over 47,000 high-tech US firms in CorpTech from 1993 to 2004, 5% of the firm-years include simultaneous entry and exit at the product market level, which we term “product turnover.” Firms are more likely to engage in product turnover when there is a larger spread between the highest and lowest growth rates for the product markets in the firm’s portfolio. This effect is strongest for small- and medium-sized firms, which tend to be privately held. Therefore, future research on resource redeployment might find fruitful ground in samples of mid-size firms.

Discrete choice models are widely used for estimating the effects of changes in attributes on a given product's likely market share. These models can be applied directly to situations in which the choice set is constant across the market of interest or in which the choice set varies systematically across the market. In both of these applications, the models are used to determine the effects of different attribute levels on market shares among the available alternatives, given predetermined choice sets, or of varying the choice set in a straightforward way.

Discrete choice models can also be used to identify the “optimal” configuration of a product or service in a given market. This can be computationally challenging when preferences vary with respect to the ordering of levels within an attribute as well the strengths of preferences across attributes. However, this type of optimization can be a relatively straightforward extension of the typical discrete choice model application.

In this paper, we describe two applications that use discrete choice methods to provide a more robust metric for use in Total Unduplicated Reach and Frequency (TURF) applications: apparel and food products. Both applications involve products for which there is a high degree of heterogeneity in preferences among consumers.

We further discuss a significant challenge in using TURF — that with multi-attributed products the method can become computationally intractable — and describe a heuristic approach to support food and apparel applications. We conclude with a summary of the challenges in these applications, which are yet to be addressed.

The chapter briefly reviews the eight volumes in my Legend series – organizational buying behavior, consumer behavior, product and new product management, marketing strategy, market segmentation, global marketing, marketing research and modeling, and the future of marketing. In addition, the chapter highlights the three driving forces of much of my research: (a) the real world challenges facing corporations and organizations, (b) the search for new methodological developments, and (c) the continuous challenge of the prevailing marketing concepts and approaches. The chapter concludes with some reflections on the evolution of marketing in the past five decades and my wish list for the discipline and my future activities.

Strategy Question: How do I assess the “market health” of my products or services?

Summary: This isn’t really a new tool per se, as it is based on the original Boston Consulting Group’s Growth–Share matrix and General Electric/McKinsey Consulting 9-box version. We base our tool on the 9-box version that plots a point for each product/service form relative to our preferred elements of “Competitive Position” and “Market Attractiveness.” The chapter explains how to breakdown the products/services, construct plot points for the matrix (in qualitative fashion that most companies can easily construct) for both the “competitive position” and “market attractiveness” metrics. The tool consists of a one-page, 3 × 3 matrix along with a process to gather, assess, and organize the information so the strategist can determine how the various products and services of the business are positioned in the respective markets, how well each is performing, how much each contributes to overall firm performance, which have potential for future performance, and what types of approaches might be appropriate for allocating resources. Once products/services are respectively plotted and grouped in common ways suggested, the output is extremely helpful in framing the competitive state and providing a baseline for constructive intercompany debate.

The paper provides an overview of research published in the innovation and operations management (IOM) literature on 15 methods for cost management in new product development, and it provides a comparison to an earlier review of the management accounting (MA) literature (Wouters & Morales, 2014).

This structured literature search covers papers published in 23 journals in IOM in the period 1990–2014.

The search yielded a sample of 208 unique papers with 275 results (one paper could refer to multiple cost management methods). The top 3 methods are modular design, component commonality, and product platforms, with 115 results (42%) together. In the MA literature, these three methods accounted for 29%, but target costing was the most researched cost management method by far (26%). Simulation is the most frequently used research method in the IOM literature, whereas this was averagely used in the MA literature; qualitative studies were the most frequently used research method in the MA literature, whereas this was averagely used in the IOM literature. We found a lot of papers presenting practical approaches or decision models as a further development of a particular cost management method, which is a clear difference from the MA literature.

This review focused on the same cost management methods, and future research could also consider other cost management methods which are likely to be more important in the IOM literature compared to the MA literature. Future research could also investigate innovative cost management practices in more detail through longitudinal case studies.

This review of research on methods for cost management published outside the MA literature provides an overview for MA researchers. It highlights key differences between both literatures in their research of the same cost management methods.