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This chapter presents a description on the nature of work franchisees perform at Star Muffler. Mark Spinelli, Star Muffler's chief executive officer, faced the monumental task of transforming “car guys” into managers. Star Muffler has a lack of differentiation among service providers and a poor industry image. To improve the image and consistency of the shops, Spinelli started a new program to rate shops on cleanliness and other factors. The profitability of each franchise unit and the relationship between franchisees has been changed by Spinelli's new customer oriented strategy. In general, the warranty system, the image and maintenance program, and the focus on customer satisfaction has made some effect in altering the old practices of Star Muffler, and the increased market share and customer loyalty can be attributed to them.

This chapter deals with the causes for differential franchisee success. It also specifically covers the critical role that social capital plays in franchisee performance. The social capital within franchise systems extends to five basic relationships—franchisor–franchisee, franchisee–franchisee (peer-to-peer), kinship network, franchisee–customer, and franchisee–supplier. The first three relationships affect the franchisee survival and profits. Relationships among franchisees are difficult to develop and sustain. The factors that limit the development of social capital within franchisee networks are then explained. The profile of a successful franchisee requires high degrees of social capital. The dense and extensive kinship networks that characterize franchising can result to severe management problems for franchisors. Franchise companies have retained the family enterprise, which is one of the oldest organizational forms in existence.

The introduction provides an overview of the book’s content and gives the reader a roadmap of what he or she can expect to gain from its various chapters. It starts by discussing a few examples, Google’s Glass and Apple’s Watch, in order to motivate the need for better models to forecast the commercial potential of innovations. The introduction then explains the genesis of the book and what experiences prompted the three authors to write it. The central framework developed in the book, the innovation equity framework, is described briefly. In particular, the key idea of combining the rich academic knowledge on the pace of consumer adoption of innovations with firms’ efforts to acquire, manage, and retain customers is conveyed. Finally, the various themes covered in each chapter are outlined.

This chapter begins by establishing that each first-time adoption of an innovation can be thought of as the start of a customer-firm relationship in which the adopter generates a stream of profits for the firm. The financial value of this profit stream is termed the customer’s lifetime value. Four main elements drive customer lifetime value: the per-period profit margin, the retention rate, the discount factor, and the acquisition cost. Linking the number of new customers expected to adopt in a given time period, by using the basic diffusion model developed in chapter 1, with the future profits each acquired customer is expected to generate, by using the customer lifetime value model, yields the monetary value of all new customers adopting in that period. Conducting this analysis for every period over the desired time horizon, applying financial discounting to future contributions, and summing the results yields the innovation equity of a new product or service. Innovation equity, the book’s central framework, is thus a monetary assessment of the total future cash flows—across customers and time—associated with the diffusion of an innovation. The chapter concludes with an example showing how to evaluate the innovation equity of XM Satellite Radio.

Although owners had always maintained their homes, the home improvement industry did not become recognized until the early 1950s, when it began to draw the attention of retailers, advertisers, consumer magazines, and the general public. Contractors and tradesmen had a large share of the market, but home owners themselves were doing a substantial and growing amount of the work. The do-it-yourself culture became popular, triggering an aggressive response from manufacturers and retailers. Before the first serious attempt to measure home improvement came in 1954, estimates had relied on building permit data combined with the impressions of building suppliers and contractors. Revival of home improvement was driven by an increase in household size and rising incomes. Two decades after 1945, “customer-finished houses” sprung up everywhere.

This chapter explores the diffusion saddle phenomenon, whereby an innovation’s unit sales exhibit an early peak followed by a decline and a subsequent second sales peak. The average duration of the dip in sales is four years and the maximal depth of the decline is over 15 percent. The saddle pattern can be attributed to the existence of multiple adopter segments: Innovation forwards who have a strong individual force, and innovation moderates who have a modest individual force and who are only weakly affected by the innovation forwards’ social force. Given that the bulk of innovation forwards embrace the innovation soon after the launch yet are relatively small in number, while the innovation moderates tend to adopt much later, the former segment can be thought of as early adopters and the latter as mainstream adopters. The chapter introduces a multi-segment diffusion model that can capture differences in diffusion parameters between segments and allows for social effects across segments. This model can yield a saddle-like diffusion pattern. The chapter provides several examples of innovations that exhibited a saddle, such as the PC and electric-drive vehicles, and illustrates how the multi-segment diffusion model can be integrated into the innovation equity framework.

This concluding chapter serves as a review of the material covered throughout the book and addresses issues often encountered when implementing the various concepts in practice and in different business settings. The presentation takes on a “Frequently Answered Questions” (FAQ) format, i.e., it outlines each issue as a question readers may be wondering about and then provides a comprehensive answer to it. FAQs are organized as follows: those pertaining to the diffusion of innovations, those dealing with customer lifetime value (CLV), and those related to the innovation equity framework. Examples of diffusion FAQs include: Can I use the various diffusion models covered in the book for any type of innovation? I am ultimately interested in running the analysis for my specific brand; should I start with assessing diffusion at the category level or go directly to the brand level? Is the social force always positive? Examples of CLV FAQs include: How can I obtain reasonable estimates for the CLV parameters? Are some of the CLV parameters likely to change over time? If so, how? The chapter ends with a check list that delineates the key steps to follow, and important issues to be aware of, when crafting innovation equity assessments.

This chapter focuses on the fact that the Consumer Price Index (CPI) does not compare the prices charged for the same items at different outlets. It describes how the Bureau of Labor Statistics assumes that any price differences can be explained by differences in outlet characteristics valued by consumers, such as locational convenience or customer service. This may result in the failure to incorporate the gains to consumers from the continuing growth in sales at Wal-Mart and other low-price, high-volume superstores. The authors employ the A.C. Nielsen Homescan consumer panel data to identify the price differentials for twenty food product categories between supercenters, mass merchandisers, and club stores (SMCs) and other outlets. These differentials, combined with the SMCs' increasing market share, lead the authors to conclude that CPI food at home inflation is too high by about 0.32–0.42 percentage points annually.