Microeconomics On The Automotive Industry A Study Essay

Length: 10 pages Sources: 2 Subject: Transportation Type: Essay Paper: #18937225 Related Topics: Microeconomics, Automotive, Bmw, Econometrics
Excerpt from Essay :

Microeconomics on the Automotive Industry

A Study of Elasticity and Demand Generation

Global and national economic cycles have a direct effect on demand for the majority of durable goods consumers purchase, with the automotive industry being the most influenced by the cost of capital, interest rates, and elasticity of demand that varies by type of auto and market segment. The intent of this analysis is to evaluate how pricing strategies can be defined to attain the optimal level of profitability in the auto industry given specific microeconomic conditions. Included in this analysis is an assessment of how economic and liquidity impact the purchase of vehicles over the long-term, and how automotive manufacturers strive to attain lower costs of manufacturing through lean production and Six Sigma methods of production. In addition, the aspect of consumer behavior and its impact on the economic cycles of elasticity are also discussed. Favoritism or ethnocentric-based approaches to trade and income in the auto industry, and the converse of this, which is global collaboration and its effects on global automotive demand are also analyzed.

Pricing Strategies for Optimal Profitability in the Auto Industry

Defining the optimal pricing strategy for a given type of vehicle in a specific market, while also taking into account interest rates, cost of capital for dealers to finance their inventories, and consumer confidence requires an optimization-based approach to defining prices. The elasticity of demand in the industry is proportional to the microeconomic factors beyond control of the global manufacturers competing in this industry, yet is also defined by the frequency and innovation of new vehicle introductions, creativity in financing and leasing, and the willingness of manufacturers to allow for customization of vehicles during production (Cassel, McCormack, 1987). In short, the entire value chain of the industry has a direct and significant impact on pricing elasticity of vehicles over time, with its greatest effects in the areas of logistics, supply chain management, lean manufacturing and Six Sigma-based approaches to continual process improvement. These factors are explored in detail throughout this analysis. The continual improvement of these factors streamline and increases the value of the customer experience, thereby making demand even more elastic the higher the price of the vehicle (Wetzel, Hoffer, 1982). As auto manufacturers have continually strived to equate their highest-end models with a specific emotion or human value to more fully personalize their brands, the more luxurious a car, the greater the price elasticity as a result (Wetzel, Hoffer, 1982). This occurs because these highest-end brands have referent branding power in the minds of consumers. The referent image that these higher-end vehicles have leads to price elasticity when a per unit change in the price upward can actually increase sales over time. This may seem counterintuitive from a demand curve-based analysis of the industry, yet the higher the price of a luxury vehicle, the more status it communicates and the greater the upward-driven elasticity and demand becomes. The higher a price for a luxury car the greater the assumption of value, which also leads to more upward-driven elasticity and exclusivity as well. The price-quality relationships in automotive demand is evident in how easily the premium brands of BMW, Lexus, Maybach or Mercedes can easily raise prices and still achieve record financial results (Bajic, 1988). The analysis of this premium segment of the...


It also has implications for pricing strategies by automotive vehicle strata or product group for each automotive manufacturer's product lines, and the customer segments and the behavior that drives their purchasing. Taken together, these factors contribute to insights that demand curves are significantly different and often contrary to one another throughout each segment of the automotive market. These delineations of these demand curve variations can vary by model class, price points (which is the most common due to the breadth of research in this area) (Wetzel, Hoffer, 1982) and by psychographics or consumer attributes of each class or segment of automotive buyer, a practice that is very common in European marketing of cars (Visnic, Wielgat, Winter, 1998).

There are significantly different demand curves across each of the strata or segments of the market and therefore significantly different messaging, economic packaging, dealer and channel-based incentives, and costing of auto configurations as well. All of these factors weigh on and influence the demand curve by class of vehicle and are either validated or rejected over time by the changing demographics and psychographics of purchasers. The next result of these many economic factors taken together is the need for defining the precise level of inelasticity or elasticity of a given market. In general, the higher-end the vehicle, the greater the elasticity and the paradoxical effect of upward pricing have the effect of increasing the overall market size over time (Wetzel, Hoffer, 1982), This aspect of elasticity is relied on by auto manufacturers who realize the price-quality relationship is a powerful enabler of referent demand and price increases expand a market by driving out emerging competitors at the low-end of their segments (Bajic, 1988). Aside from the referent positioning that price increases on luxury vehicles connote and powerfully communicate, pricing strategies on the part of higher-end luxury car manufacturers have proven to be an effective deterrent for driving competitors out of their markets as well (Rhys, 2005). There are many examples of how BMW, Lexus, Mercedes and others have used price increases to further differentiate themselves from potential competitors in their markets including Hyundai, Hondo, Suzuki and other manufacturers who have unsuccessfully attempted to penetrate the high-end market. BMW, Lexus, Mercedes and other high-end manufacturers have enough economic, sales and analytical data including enterprise software to interpret demand and create a demand curve by product class in real-time. Using this data and pricing further up the demand curve, these competitors continue to be very successful driving competitors out of their markets while increasing profitability at the same time. This also illustrates how effective having real-time demand curve-based data is by product class.

The low-end of the automotive market is considered to be highly price elastic as well, with a drop in price increasing unit volumes. In fact, this is not always the case, as a precipitous or significant drop in price can communicate or connote a lack of quality in a given vehicle or class of cars over time (Bajic, 1988). The elasticity of demand across the low-end of the market is more dictated by the cost of capital, flexibility and agility of financing and credit offers auto manufacturers and retailers can make, age of product designs and their relative demand with consumers, and the efficiency of manufacturing processes to support lower costs over time. Just as manufacturers have intensive levels of investment in analytics to understand and analyze the demand curve for the high-end of the market due to the high gross margin per model, the same is true at the low end where sales are often measures in tens of thousands of units sold per month (Cassel, McCormack, 1987).

The influence of auto dealers and the extent of asymmetric vs. symmetric pricing and transaction data between them and the manufacturers they rely on can also have a significant effect on the elasticity curve of car models by segment over the long-term. The greater the asymmetric pricing and transaction data provides and shared, the greater the level of transaction elasticity resulting in the potential of a lower per unit price (Cassel, McCormack, 1987). At the low-end of the market, it is production efficiency, real-time pricing and transaction data support and the ability to create low-priced models that resonate with first-time and low- to moderate income buyers (Rhys, 2005). Studies of pricing elasticity in the low-end of the auto market suggest that the breadth and scope of the financing options bring new buyers into the market and the latency of product designs are much more critical to sustaining what would otherwise turn into a highly inelastic demand curve over time (Rhys, 2005). The low-end of the automotive market is one that has the combination of factors that contribute to a flat, inelastic demand curve (Rhys, 2005). The demand curve characteristics of the low-end of the market show no significant change in volume sales when a per unit change in price is made with the best-case scenario being a unitary price elasticity being attained (Wetzel, Hoffer, 1982). The low-end of the market has a series of factors that continually move it to an inelastic market position, flattening the demand curve and making pricing less of a determinant of product demand increases vs. these other elements. First, there is the availability of credit, which has become constrained due to the economic crisis and continued economic recession. Second, the tendency on the part of auto manufacturers to treat this area of their product strategies as areas where older, more proven product designs are used as they have already been amortized. This results in a continual downward spiral however of the price-quality relationship because the…

Sources Used in Documents:


Bajic, Vladimir. (1988). Market Shares and Price-Quality Relationships: An Econometric Investigation of the U.S. Automobile Market. Southern Economic Journal, 54(4), 888.

Cassel, Herbert S., & McCormack, Vincent F.. (1987). The Transfer Pricing Dilemma -- And a Dual Pricing Solution. Journal of Accountancy, 164(3), 166.

Chu, T., & Su, Y.. (2010). Will the U.S. Auto Market Come Back? Business Economics, 45(4), 253-265.

Jeffrey H. Dyer, & Kentaro Nobeoka. (2000). Creating and managing a high-performance knowledge-sharing network: The Toyota case. Strategic Management Journal: Special Issue: Strategic Networks, 21(3), 345-367.

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