Several studies have shown that pioneers have long-lived market share advantages and are likely to be market leaders in their product categories. However, that research has potential limitations: the reliance on a few established databases, the exclusion of nonsurvivors, and the use of single-informant self-reports for data collection. The authors of this study use an alternate method, historical analysis, to avoid these limitations. Approximately 500 brands in 50 product categories are analyzed. The results show that almost half of market pioneers fail and their mean market share is much lower than that found in other studies. Also, early market leaders have much greater long-term success and enter an average of 13 years after pioneers.

A consistent pattern observed for really new household consumer durables is a takeoff or dramatic increase in sales early in their history. The takeoff tends to appear as an elbow-shaped discontinuity in the sales curve showing an average sales increase of over 400%. In contrast, most marketing textbooks as well as diffusion models generally depict the growth of new consumer durables as a smooth sales curve. Our discussions with managers indicate that they have little idea about the takeoff and its associated characteristics. Many managers did not even know that most successful new consumer durables had a distinct takeoff. Their sales forecasts tend to show linear growth. Yet, knowledge about the takeoff is crucial for managers to decide whether to maintain, increase, or withdraw support of new products. It is equally important for industry analysts who advise investors and manufacturers of complementary and substitute products. Although previous studies have urged researchers to examine the takeoff, no research has addressed this critical event. While diffusion models are commonly used to study new product sales growth, they do not explicitly consider a new product's takeoff in sales. Indeed, diffusion researchers frequently use data only from the point of takeoff. Therefore, nothing is known about the takeoff or models appropriate for this event. Our study provides the first analysis of the takeoff. In particular, we address three key questions: (i) How much time does a newly introduced product need to takeoff? (ii) Does the takeoff have any systematic patterns? (iii) Can we predict the takeoff? We begin our study by developing an operational measure to determine when the takeoff occurs. We found that when the base level of sales is small, a relatively large percentage increase could occur without signaling the takeoff. Conversely, when the base level of sales is large, the takeoff sometimes occurs with a relatively small percentage increase in sales. Therefore, we developed a “threshold for takeoff.” This is a plot of percentage sales growth relative to a base level of sales, common across all categories. We define the takeoff as the first year in which an individual category's growth rate relative to base sales crosses this threshold. The threshold measure correctly identifies the takeoff in over 90% of our categories. We model the takeoff with a hazard model because of its advantages for analyzing time-based events. We consider three primary independent variables: price, year of introduction, and market penetration, as well as several control variables. The hazard model fits the pattern of takeoffs very well, with price and market penetration being strong correlates of takeoff. Our results provide potential generalizations about the time to takeoff and the price reduction, nominal price, and penetration at takeoff. In particular, we found that: • On average for 16 post-World War II categories: — the price at takeoff is 63% of the introductory price; — the time to takeoff from introduction is six years; — the penetration at takeoff is 1.7%. • The time to takeoff is decreasing for more recent categories. For example, the time to takeoff is 18 years for categories introduced before World War II, but only six years for those introduced after World War II. • Many of the products in our sample had a takeoff near three specific price points (in nominal dollars): $1000, $500 and $100. In addition, we show how the hazard model can be used to predict the takeoff. The model predicts takeoff one year ahead with an expected average error of 1.2 years. It predicts takeoff at a product's introduction with an expected average error of 1.9 years. Even against the simple mean time to takeoff of six years for recent categories, the model's performance represents a tremendous improvement in prediction. It represents an immeasurable improvement in prediction for managers who currently have no idea about how long it takes for a new product to takeoff. The threshold rule for determining takeoff can be used to distinguish between a large increase in sales and a real takeoff. Some limitations of this study could provide fruitful areas for future research. Our independent variables suffer from endogeneity bias, so alternative variables or methods could address this limitation. Also, the takeoff may be related to additional variables such as relative advantage over substitutes and the presence of complementary products. Finally, examination of sales from takeoff to their leveling off could be done with an integrated model of takeoff and sales growth or with the hazard model we propose. Generalizations about this period of sales growth could also be of tremendous importance to managers of new products.

Several researchers have advocated historical or longitudinal approaches to study marketing phenomena. Although some have applied this approach, more often it has been overlooked or denigrated. The author argues that historical method is capable of producing scientific knowledge that is currently useful, rather than simply a remembrance of the past. The author presents a complete description of the historical method, so researchers can use this article as a guide when applying this method. The value of the method is illustrated by examining the prevailing finding in the marketing literature that market shares are stable over time. Although this finding is considered an empirical generalization, an analysis of more than 650 brands in 100 categories raises doubts about the longevity of market share stability.

Research on the product life cycle (PLC) has focused primarily on the role of diffusion. This study takes a broader theoretical perspective on the PLC by incorporating informational cascades and developing and testing many new hypotheses based on this theory. On average, across 30 product categories, the authors find that: (i) New consumer durables have a typical pattern of rapid growth of 45% per year over 8 years. (ii) This period of growth is followed by a slowdown when sales decline by 15% and stay below those of the previous peak for 5 years. (iii) Slowdown occurs at 34% population penetration and about 50% of ultimate market penetration. (iv) Products with large sales increases at takeoff tend to have larger sales declines at slowdown. (v) Leisure-enhancing products tend to have higher growth rates and shorter growth stages than nonleisure-enhancing products. Time-saving products tend to have lower growth rates and longer growth stages than nontime-saving products. (vi) Lower probability of slowdown is associated with steeper price reductions, lower penetration, and higher economic growth. (vii) A hazard model can provide reasonable predictions of the slowdown as early as the takeoff. The authors discuss the implications of these findings.product life cycles, sales takeoff, cascades, new product growth, innovation, product management, diffusion, high-tech marketing

Quality is a central element in business strategy and academic research. Despite important research on quality, an opportunity for an integrative framework remains. The authors present an integrative framework of quality that captures how firms and customers produce quality (the quality production process), how firms deliver and customers experience quality (the quality experience process), and how customers evaluate quality (the quality evaluation process). The framework extends the literature in several ways. First, the authors describe important linkages between the three processes, including links reflecting the role of co-production. Second, they point to overlooked aspects of the quality processes that influence how quality is conceptualized and should be managed. These include customer heterogeneity in measurement knowledge and motivation; the role of emotion in quality production, experience, and evaluation; and a new typology of attributes. Third, they propose a quality state residing within each quality process and describe what gives rise to these states, which will enhance decision makers' ability to measure and manage quality processes. Finally, they offer theoretical and managerial implications derived from their integrative quality framework including 20 strategies to increase customer satisfaction.