Competitive Strategies
For the information to be effective, it should be gathered from a vast pool of available resources, ideally, international in scope. For them to be efficient, however, requires the intervention of technology through web-based information. In this view, search engines emerged such as Google, which means one followed by one hundred zeros to portray the strength of its database, to ensure speed, accuracy, objectivity and ease of use of the available information gathered in any part of the earth. The information, however, collated by Google is so enormous that classification of data which is sensible to the user is undermined. As such, web-portal like Alexa caters to specific niche of web users to segregate the most relevant data from others to avoid jumping to websites that could be “time risky” for the user. Although it is debatable that Google’s technology assures accurate search, web-portals post in the interface the exact needs of the busy user that can range from local news to product information.
In internet parlance, network externality is a network effect when the consumer of the service is affected, either positively or otherwise, by the changes in customer base purchases of the same service. Google has greater dependence to network externality, therefore, give more importance to market share rather than profitability while the reverse is true to Alexa. The search engine Google is a general and raw platform for all kinds of information that can cater to all types of users with simple classification in search results like academic and advertising page contents. Vertically-integrated, this model also serve as system for the income generating activities of the company like AdWord and AdSense. As a result, it maintains its reputation that entices the market share to go its way and give Google the network externality advantage.
In contrast, Alexa caters to a specific niche of customers who want to obtain searches in reliable and popular websites through their statistics services that gives the user the option to select from the vast number of web links based on web-traffic, user reviews and other site statistics. As a common feature of the web portal, Alexa provides its customers a personalized interface wherein the quantity and quality of information are filtered to suit their needs. To maintain its position, Alexa obtains partnership with Google (for search services) and Amazon.com (for other essential services cannot be provided by Google). As a result, efficiency and scalability advantages from Google are enjoyed by Alexa while providing subscribers the “advance search” lacking in Google.
As observed, Alexa has lower dependence to network externalities and the risk of loosing the customers is passed to Google. When the time comes that a more efficient search engine emerged in the market, Alexa will be relatively in safer mode than Google. The large customer base of Google will shift to the new better technology, in effect, exhaustion of all the users could ensue. As network externality highly relies in the critical mass, where the value of the service is greater or equal to the price being paid, the replacement of the new technology against Google will weaken the value of service of the latter. On the other hand, Alexa is flexible, as it can divert its resources and change market due to lower and well-defined customer base, wherein it can easily withdraw partnership with Google and transfer to the new technology.
With regards to threat of entry, web-portals could be possible competitors to their servers as long as they have the large, competent and valuable workforce to operate its research and development facilities. Since Google’s search technology such as PageRank and Hypertext Matching Analysis is protected by patents, even if Alexia arrives on those discoveries, it is required to refine the research and aim for an original version of its own. On the other hand, Google is continuously working on efficiency at both ends of the search service which is faster response and larger scalability at lower costs. They even out-matched Yahoo when it emphasized on silent research rather than advertisement.
Further, Alexa and other web-portals whose search engines are powered by Google are in marketing and advertising jeopardy as their interfaces plug the Google brand itself (even though some resorted to minimized the font of mentioning “powered by Google”). There entry to the business of search engine giants requires their companies to get-out from the risk-averse stance and plunge to the complex and growing sophistication of technology and customers. The move calls for getting out of customization that protects web-portals customers and inferior technology from any unpredicted discovery boom from big competitors like Yahoo, MSN and Google itself.
Pricing Methods
Hedonic price equation post problems of bias when not tested. One factor to consider is that its inability to infuse time constraints. Another, the changes of non-obvious prices related to the dependent variable is not covered by the raw equation. For example, in the product market, hedonic price only measures well-known products or those that are profitable while not accounting to those who intend to run out of business or those who improve their quality. In addition, not all variables of a product is recognized by the equation which make the equation low goodness of fit.
Hedonic price equation also assumes that product features are not developed over time which is detrimental for the purpose of high-tech companies whose innovation is the cornerstone of corporate culture. In the study of Bajari & Benkard (2005), it is found that hedonic approach is more convenient to use compared to matched-model alternative because the latter demands more data than the former. In addition, the housing industry is perfectly fitted to the assumption of the hedonic price equation like unobserved characteristics would not likely change quickly. There is synergy existed between certain business industry and certain assumptions of the hedonic price equation which can be beneficial to companies especially on cost-effective pricing management.
Price Elasticity of Demand
Demand curve represents the relationship of price and quantity demanded for a certain good for a specific time frame (Sloman & Sutcliffe 2001). It is a theoretical evidence of their negative association due to downward sloping curve (i.e. increase in unit of one will decrease the unit of the other). In Figure 3-A, changes in the demand of web search services and the corresponding changes in prices is illustrated in Figure 3-B. The original line is the one that is plotted according to Figure 3-A. Here, it is clearly shown that movements within the demand curve are caused by price changes (i.e. consistent with the law of demand). However, other determinants of demand will cause it to shift to the left (i.e. the broken line or reduction in demand) or to the right (i.e. the bold line or increase in demand) of the original line which goes beyond price considerations of this particular product. They are the number and price of substitute products (e.g. Yahoo!), number and price of complementary goods (e.g. hardware), income, distribution of income, tastes and expectations of future price changes. For example, when frozen carrots increased in quantity it will become cheaper and will cause the demand curve for raw carrots to shift to the left.
Price elasticity of demand is a tool to gauge how responsive quantity demanded to price movements (Sloman & Sutcliffe 2001). There are two main types of demand elasticity; namely, inelastic demand and elastic demand. In Figure 4-A, inelastic demand is shown in the left side while elastic demand is shown in right side. As observed, the former exhibits minimal change in quantity demanded (i.e. from 100 units to 90 units) after a substantial change in price (i.e. from $6 to $10). In contrast, the latter exhibits substantial change in quantity demanded (i.e. from 100 units to 40 units) after a minimal change in price (i.e. from $6 to $7). Elastic demand is more responsive to changes in price either it increases or decreases while inelastic demand is not much responsive to the same price impact. In numerical expression, elastic demand has a value of greater than 1 (e.g. larger figure divided by smaller figure) while inelastic demand has a value less than 1 (e.g. smaller figure divided by the larger figure. Elasticity of demand can also be determined by several factors such as the number and closeness of substitute goods, proportion of income spent on the god and the time period. For example, when substitute goods become more and more comparative to the features of specific good, minimal increase of price of the latter can lead to substantial decrease in the demand of such good and subsequently increase in demand of the available substitute goods.
Figure 4-B shows the of elasticity concept on the total revenues of a business. Elastic demand is on the right side that suggests that rise in price from $4 to $5 is not profitable strategy because it will only lead to proportionately larger fall in quantity demanded. This is not helpful to maximize the formula for total revenues (i.e. TR = P x Q). In the previous strategy, TR = $4 per unit x 20 units = $80 while the current strategy TR = $5 per unit x 10 units = $50 which is lower than the earlier TR. As a result, the business must lower its price because its products have high elasticity. However, the reverse scenario is true if the product is inelastic (i.e. in the left side of Figure 4-B). When the price of inelastic products is increased (i.e. TR = $8 per unit x 15 units = $120), the previous TR will be inferior (i.e. TR = $4 units x 20 units = $80).
Bibliography
Internet (2006). Managing the Digital Enterprise. Retrieved April 10, 2008, from
http://digitalenterprise.org/index.html.
Sloman, J., & Sutcliffe, M. (2001). Economics for Business. (2nd edition). Prentice Hall.
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