Category: LG

Estimation of the Demand Function

OLS Regression Analysis

Table 1.

Table 2.

Table 3

Estimation of the Influence

Estimated Influence of Price of LG

The coefficient of the price of LG is negative, which means that there is a negative relationship between the price of LG and the quantity of LG. The estimated influence is that a unit change in the price of LG results in 0.001 changes in the quantity of LG in opposite direction. For example, a unit increase in the price of LG causes the quantity of LG to decline by 0.001 units.

Estimated Influence of Price of Mitsubishi

The coefficient of the price of Mitsubishi is zero (0.000), which means that the price of Mitsubishi and the quantity of LG have no relationship. The coefficient shows that price of Mitsubishi has no influence on the demand for LG air conditioners. Hence, the absence of the estimated influence means that Mitsubishi is not a substitute product of LG air conditioner.

Estimated Influence of Price of Electricity

The coefficient of the price of electricity is negative, which shows that the price of electricity and the quantity of LG have an inverse relationship. In essence, the estimated influence is that a unit change in the unit change in the price of electricity results in 0.375 changes in the quantity of LG in the opposite direction. For instance, an increase in the price of electricity by a unit results in a decline in the quantity of LG by 0.375 units. Hubbard, Garnett, and Lewis (2012) note that a product that has a negative relationship with the demand for a given product is a complementary product. Therefore, the estimated coefficient reveals that electricity is a complementary product of LG air condition.

Estimated Influence of Advertisement Expenditure

From Table 3, it is apparent that the coefficient of advertisement expenditure is zero (0.000), which implies that there is no relationship between the advertisement expenditure and the quality of LG. Regarding the estimated influence, the coefficient indicates that the advertisement expenditure has no influence on the demand for LG. In this view, it means that advertisement does not promote the demand for LG air conditioners.

Estimated Influence of Total Sales

Given that the coefficient of total sales is zero (0.000), it means that total sales and quantity of LG have no relationship. The absence of a relationship indicates that total sales do not influence the demand of LG in the market. Hence, a change in the total sales does not lead to a change in the demand of LG.

Estimation of Elasticities

Log-log Regression Analysis

The log-log model (Table 4) indicates that the predictors, namely, lots, nlADVE, lnPLG, lnPMIT, and lnPELC, have a strong relationship with lnQLG (R = 0.741). The R-square indicates that these predictors explain 54.8% of the variation in lnQLG (R² = 0.867).

Table 4.

The F-statistics of the log-log model is statistically significant in predicting the influence of lots, nlADVE, lnPLG, lnPMIT, and lnPELC on lnQLG, F(5,30) = 7.286, p = 0.000).

Table 5.

Table 6.

Computation of Elasticity Coefficients

Log-log equation

• lnQLG = 20.683  2.652lnPLG  0.011lnPMIT + 0.110PELC + 0.058ADVE + 0.605TS.

Given that:-

• lnPLG = 10
• lnPMIT = 10
• lnPELC = 1
• lnADVE = 10
• lnTS = 15
• lnQLG = 20.683  2.652 (10)  0.011(10) + 0.110(1) + 0.058(10) + 0.605(15).
• inlQLG = 20.683  26.52  0.11 + 0.11 + 0.58 + 9.075
• lnQLG = 3.818

Price Elasticity of LG Demand

According to the estimation coefficient of PLG, one percent increase in the price of LG air conditioner results in a decline of the LG demand by 2.652 percent when other predictors remain constant. The price elasticity of LG demand shows that the price and LG demand have negative relationship, which is very elastic. Sexton (2012) asserts that price elasticity of demand is an economic parameter, which quantifies the sensitivity of demand to price changes in the market.

E_PLC=(dQ/dLG)*PLC/Q

E_LG = -2.652(10/3.818)

E_LG = -6.946

PMIT Elasticity of LG Demand

The estimation coefficient of PMIT indicates that a one percent increase in the price of Mitsubishi causes a decline in the demand of LG by 0.011 percent when other predictors remain constant. The PMIT elasticity of LG demand calculated as shown below has a negative value, which means that price of Mitsubishi and the LG demand has a negative relationship, which is moderately inelastic. Nechyba (2010) explains that the elasticity coefficient that is greater than one is elastic while the elasticity coefficient that is less than one is inelastic.

E_PMIT=(dQ/dPMIT)*PMIT/Q

E_PMIT = -0.011(10/3.818)

E_LG = -0.0288

PELC Elasticity of LG Demand

The estimation coefficient of PELC shows that a one percent increase in the price of electricity results in a 0.11 percent increase in the demand of LG when other predictors remain constant. The PELC elasticity of LG demand determined as indicated below shows that the price of electricity and LG demand have a positive relationship, which is relatively inelastic.

E_PELC=(dQ/dPELC)* PELC/Q

E_PELC = 0.11(1/3.818)

E_PELC = 0.0288

ADVE Elasticity of LG Demand

The estimation coefficient of ADVE predicts that a one percent increase in the advertisement expenditure causes a 0.058 percent increase in the demand of LG. The ADVE elasticity of LG demand reveals that the advertisement expenditure and the LG demand have a positive relationship, which is relatively elastic.

E_ADV=(dQ/dADV)*ADV/Q

E_PMIT = 0.058(10/3.818)

E_LG = 0.1519

TS Elasticity of LG Demand

The estimation coefficient of TS shows that a one percent increase in the total sales causes the demand for LG to increase by 0.605. Thus, the TS elasticity of LG demand indicates that total sales and LG demand have a positive relationship, which is moderately elastic.

E_TS=(dQ/TS)*TS/Q

E_PMIT = 0.605(15/3.818)

E_LG = 2.3769

Determination of Statistical Significance

The linear demand model as shown in Table 1 indicates that total sales (TS), price of LG (PLG), advertisement expenditure (ADVE), price of electricity (PELC), and price of Mitsubishi (PMIT) are determinants of the quantity of LG because they have a very strong relationship (R = 0.857). The R-square reveals that these determinants of demand explain 73.5% of the variation in the demand for LG air conditioners (R² = 0.735).

The F-test determines if the regression model is statistically in predicting the influence of independent variables on a dependent variable. The F-test indicates that the regression model is statistically significant in predicting the influence of total sales, price of LG, advertisement expenditure, price of electricity, and price of Mitsubishi on the quantity of LG air conditioner, F(5,30) = 16.624, p = 0.000).

Table 3 below indicate that price of LG (p = 0.005), advertisement expenditure (p = 0.001), and total sales (p = 0.000) are statistically significant predictors of LG demand because their t values are greater than 2 or their p values are less than 0.05. In contrast, the price of Mitsubishi (p = 0.292) and price of electricity (p = 0.929) are statistically insignificant predictors of LG demand because their t values are less than 2 or their p values are greater than 0.05.

References

Hubbard, G., Garnett, A., & Lewis, P. (2012). Essentials of Economics. New York: Person Higher Education.

Nechyba, T. (2010). Microeconomics: An Intuitive Approach with Calculus. New York: Cengage Learning.

Sexton, R. (2012). Exploring Economics. New York: Cengage Learning.

I am one of those people who cannot keep their clothes in order. Even if I put everything in the closet, it will be wrinkled when I need it. So almost every day I am struggling with my iron and hoping to win this fight. That is why I have always dreamed of something that would make my clothes look clean and tidy without affords.

Recently, I have got to know about LG Styler, which is an innovative clothes care system. Just as in professional cleaning services, it provides the users with the opportunity to remove odors with the help of hot steam (Prigg par. 5). It makes the clothes look like new ones and even absorbs moisture. To my mind, this innovation is a salvation for lazy bones and people like me. Moreover, it has special hangers for different clothes, which proves that they will not get wrinkled after the cleaning (“LG Styler” par. 8).

Works Cited

LG Styler 2015. Web.

Prigg, Mark. The £1500 Closet That Can Dry Clean Your Clothes: LG Reveals New Hi-Tech Laundry Machine. 2015. Web.

Demand Estimation

The estimation of demand for a specific product a company sells is a significant component for conducting performance analysis of any business. Thus, all decisions related to whether a company should enter the market, whether there is a need for lowering or increasing the prices, how the production capacity should be planned directly relate to demand estimation. Using calculating the estimated demand, a manager can direct the business decisions linked to the future demand for a particular product (“Demand Estimation” 1).

A method of calculating estimated demand is illustrated in Figure 1:

2016 Demand Forecast for LG and Mitsubishi Industrial Air Conditioners

If the LG AC system’s prices have increased by 20% since 2010, the 2016 price will be approximately 38000+20% = 45600. If the price for the Mitsubishi AC has decreased by 25%, then the estimated prices will be 49500-25%=37125. The analysis of the data table on the prices and total sales of AC systems shows that there is a pattern of overall sales increase that is not threatened by the increase in the prices for air conditioners. Furthermore, it is important to note that the second quarter of the year exhibits the most demand and sales since April, May, and June are months when the air temperature significantly increases.

Substitute Commodity and Cross-Elasticities

A substitute commodity is essentially a substitute for a particular product. Thus, when the price of one commodity increases, the demand for its substitute will rise (Econogist par. 2). Cross-elasticity of demand is an estimate which indicates “the percentage change in quantity demand for a good after the change in the price of another” (Economics Help par. 1). It is calculated by dividing the percentage of change in quantity demanded of good (QD) of one good by the percentage of change in the price of another good. Concerning LG, the price of which has increased by 20%, and the GD of its substitute has increased by 5%. The estimated cross-elasticity will equal +0,25.

Complementary Commodity Price Estimation

A complementary good or commodity is a product or a service that is directly linked to the operation of another good. If a price for one item declines, the public tends to buy the complementary product regardless of whether it increases or not (Hill par. 3). In the market of AC systems, electricity is a complementary commodity, the price of which is predicted to rise by 38% in 2016, taking into account an overall pattern of electricity price changes shown in the table.

Advertisement

As mentioned in the Harvard Business Review article written by Paul Farris and David Reibstein, companies that spend more on product advertisements usually exhibit higher rates of income (par. 1). However, the table with LG and Mitsubishi AC data shows no distinct pattern of relationship between the overall sales and the prices on the advertisement. The second quarter of the year is a period characterized by lower prices on the advertisement since there is a higher demand for ad services in the sphere of air conditioning.

Total Sales

By analyzing the complete set of data on LG and Mitsubishi air conditioning systems, it can be estimated that the total sales of these products will remain stable and increase with the come of a hot season. However, when the temperature in particular areas declines, the overall sales of LG and Mitsubishi air conditioning are also estimated to decline.

Works Cited

Demand Estimation. n.d. Web.

Econogist. Economics Explained: Complements, Substitutes, and Elasticity of Demand. n.d. Web.

Economics Help. Cross Elasticity of Demand. n.d. Web.

Farris, Paul, and David Reibstein. How Prices, Ad Expenditures, and Profits Are Linked. n.d. Web.

Hill, Aaron. Complementary Goods in Economics: Definition & Examples. n.d. Web.

“Is This How It’s Done?” n.d. Web.

Estimation of the Demand Function

OLS Regression Analysis

Table 1.

Table 2.

Table 3

Estimation of the Influence

Estimated Influence of Price of LG

The coefficient of the price of LG is negative, which means that there is a negative relationship between the price of LG and the quantity of LG. The estimated influence is that a unit change in the price of LG results in 0.001 changes in the quantity of LG in opposite direction. For example, a unit increase in the price of LG causes the quantity of LG to decline by 0.001 units.

Estimated Influence of Price of Mitsubishi

The coefficient of the price of Mitsubishi is zero (0.000), which means that the price of Mitsubishi and the quantity of LG have no relationship. The coefficient shows that price of Mitsubishi has no influence on the demand for LG air conditioners. Hence, the absence of the estimated influence means that Mitsubishi is not a substitute product of LG air conditioner.

Estimated Influence of Price of Electricity

The coefficient of the price of electricity is negative, which shows that the price of electricity and the quantity of LG have an inverse relationship. In essence, the estimated influence is that a unit change in the unit change in the price of electricity results in 0.375 changes in the quantity of LG in the opposite direction. For instance, an increase in the price of electricity by a unit results in a decline in the quantity of LG by 0.375 units. Hubbard, Garnett, and Lewis (2012) note that a product that has a negative relationship with the demand for a given product is a complementary product. Therefore, the estimated coefficient reveals that electricity is a complementary product of LG air condition.

Estimated Influence of Advertisement Expenditure

From Table 3, it is apparent that the coefficient of advertisement expenditure is zero (0.000), which implies that there is no relationship between the advertisement expenditure and the quality of LG. Regarding the estimated influence, the coefficient indicates that the advertisement expenditure has no influence on the demand for LG. In this view, it means that advertisement does not promote the demand for LG air conditioners.

Estimated Influence of Total Sales

Given that the coefficient of total sales is zero (0.000), it means that total sales and quantity of LG have no relationship. The absence of a relationship indicates that total sales do not influence the demand of LG in the market. Hence, a change in the total sales does not lead to a change in the demand of LG.

Estimation of Elasticities

Log-log Regression Analysis

The log-log model (Table 4) indicates that the predictors, namely, lots, nlADVE, lnPLG, lnPMIT, and lnPELC, have a strong relationship with lnQLG (R = 0.741). The R-square indicates that these predictors explain 54.8% of the variation in lnQLG (R² = 0.867).

Table 4.

The F-statistics of the log-log model is statistically significant in predicting the influence of lots, nlADVE, lnPLG, lnPMIT, and lnPELC on lnQLG, F(5,30) = 7.286, p = 0.000).

Table 5.

Table 6.

Computation of Elasticity Coefficients

Log-log equation

• lnQLG = 20.683 – 2.652lnPLG – 0.011lnPMIT + 0.110PELC + 0.058ADVE + 0.605TS.

Given that:-

• lnPLG = 10
• lnPMIT = 10
• lnPELC = 1
• lnADVE = 10
• lnTS = 15
• lnQLG = 20.683 – 2.652 (10) – 0.011(10) + 0.110(1) + 0.058(10) + 0.605(15).
• inlQLG = 20.683 – 26.52 – 0.11 + 0.11 + 0.58 + 9.075
• lnQLG = 3.818

Price Elasticity of LG Demand

According to the estimation coefficient of PLG, one percent increase in the price of LG air conditioner results in a decline of the LG demand by 2.652 percent when other predictors remain constant. The price elasticity of LG demand shows that the price and LG demand have negative relationship, which is very elastic. Sexton (2012) asserts that price elasticity of demand is an economic parameter, which quantifies the sensitivity of demand to price changes in the market.

E_PLC=(dQ/dLG)*PLC/Q

E_LG = -2.652(10/3.818)

E_LG = -6.946

PMIT Elasticity of LG Demand

The estimation coefficient of PMIT indicates that a one percent increase in the price of Mitsubishi causes a decline in the demand of LG by 0.011 percent when other predictors remain constant. The PMIT elasticity of LG demand calculated as shown below has a negative value, which means that price of Mitsubishi and the LG demand has a negative relationship, which is moderately inelastic. Nechyba (2010) explains that the elasticity coefficient that is greater than one is elastic while the elasticity coefficient that is less than one is inelastic.

E_PMIT=(dQ/dPMIT)*PMIT/Q

E_PMIT = -0.011(10/3.818)

E_LG = -0.0288

PELC Elasticity of LG Demand

The estimation coefficient of PELC shows that a one percent increase in the price of electricity results in a 0.11 percent increase in the demand of LG when other predictors remain constant. The PELC elasticity of LG demand determined as indicated below shows that the price of electricity and LG demand have a positive relationship, which is relatively inelastic.

E_PELC=(dQ/dPELC)* PELC/Q

E_PELC = 0.11(1/3.818)

E_PELC = 0.0288

ADVE Elasticity of LG Demand

The estimation coefficient of ADVE predicts that a one percent increase in the advertisement expenditure causes a 0.058 percent increase in the demand of LG. The ADVE elasticity of LG demand reveals that the advertisement expenditure and the LG demand have a positive relationship, which is relatively elastic.

E_ADV=(dQ/dADV)*ADV/Q

E_PMIT = 0.058(10/3.818)

E_LG = 0.1519

TS Elasticity of LG Demand

The estimation coefficient of TS shows that a one percent increase in the total sales causes the demand for LG to increase by 0.605. Thus, the TS elasticity of LG demand indicates that total sales and LG demand have a positive relationship, which is moderately elastic.

E_TS=(dQ/TS)*TS/Q

E_PMIT = 0.605(15/3.818)

E_LG = 2.3769

Determination of Statistical Significance

The linear demand model as shown in Table 1 indicates that total sales (TS), price of LG (PLG), advertisement expenditure (ADVE), price of electricity (PELC), and price of Mitsubishi (PMIT) are determinants of the quantity of LG because they have a very strong relationship (R = 0.857). The R-square reveals that these determinants of demand explain 73.5% of the variation in the demand for LG air conditioners (R² = 0.735).

The F-test determines if the regression model is statistically in predicting the influence of independent variables on a dependent variable. The F-test indicates that the regression model is statistically significant in predicting the influence of total sales, price of LG, advertisement expenditure, price of electricity, and price of Mitsubishi on the quantity of LG air conditioner, F(5,30) = 16.624, p = 0.000).

Table 3 below indicate that price of LG (p = 0.005), advertisement expenditure (p = 0.001), and total sales (p = 0.000) are statistically significant predictors of LG demand because their t values are greater than 2 or their p values are less than 0.05. In contrast, the price of Mitsubishi (p = 0.292) and price of electricity (p = 0.929) are statistically insignificant predictors of LG demand because their t values are less than 2 or their p values are greater than 0.05.

References

Hubbard, G., Garnett, A., & Lewis, P. (2012). Essentials of Economics. New York: Person Higher Education.

Nechyba, T. (2010). Microeconomics: An Intuitive Approach with Calculus. New York: Cengage Learning.

Sexton, R. (2012). Exploring Economics. New York: Cengage Learning.

Introduction

Texting is an important aspect for teens. Teens view texting as a means to communicate and socialize. A research conducted by LG found that text bullying is a behavior common in the lives of teenagers. The research established that teens consider texting gossips as normal and part of socialization and communication process. However, adults view text harassment as a significant problem that affects many teens.

The following paper discusses the promotional measures that LG could adapt to change teens’ attitude about mean texting. The promotion will be critical in ensuring that LG brand stays true to its “Life’s Good” which is geared to making a positive impact on the world.

Changing Teens’ Mean Texting Attitude

According to Heikki and Tapio (2002), attitudes of consumers lead to beliefs, feelings, and behavioral intentions towards a particular activity or object. The attitudes are engrained in the lives of consumers, and thus they are difficult to change.

The research by LG found that text harassment by teens has been assumed; hence, many teens have normalized the habit. In order to change the engrained attitudes, LG should apply classical conditioning approach. Wiley, Krisjanous and Cavana (2007) noted that classical conditioning entails pairing a product with a stimulus that discourages the bad attitudes.

For example, classical conditioning will entail a campaign program that emphasizes the goodness of text messages, but at the same time discourages mean texting. The campaign will serve as corporate social responsibility taken by LG to increase the engagement of its brands among the teens. This will have a two-fold effect because it will lead to attitude change and increase brand value.

LG should also discourage mean texting by creation of advertisement that depicts a lifestyle that is ideal for teens but not based on mean texting. The advert should be based on functional approach. For example, the advert should apply value expressive function which makes consumers reflect on their habits (Wiley et al., 2007).

In this case, the advert will be designed to encourage positive lifestyle and outlook that is ideal for the teens but at the same time portray mean texting as anti-social behavior. LG should also use strategies that are aimed at changing the behavior of teens. Hassan and Michaelidou (2013) stated that people believe that the behavior they have is rational; thus, they continue with the behavior until someone enlightens them on the inappropriateness of the behavior.

Therefore, the campaign must focus on motivating the teens to consider the consequences of sending mean texts. Bearing in mind that teens view texting as a talkative process that enhances their socialization, the strategy should entail the use of one-sided versus two-sided appeal advertisements.

According to Hassan and Michaelidou (2013), consumers react positively to advertisements that admit a behavior but at the same time challenge it by promoting an alternative to the behavior. Thus, LG should have an advertisement that recognizes the beauty of texting but also challenges it by an advert caption that shows how responsible texting is more rewarding and right for the teen’s lifestyle compared to mean texting.

Conclusion

The adoption of the appropriate campaign strategies will create a new perspective among the teens in the matters that relate to texting. Thus, the approaches will raise awareness about the consequences related to the vice and bring about attitude change from mean texting to responsible texting. The strategies will motivate teens to be conscious when texting and at the same time promote LG as a socially responsible company.

References

Hassan, L., & Michaelidou, N. (2013). Challenges to attitude and behavior change through persuasion. Journal of Consumer Behavior, 12 (2), 91-92.

Heikki, K., & Tapio, P. (2002). Factors underlying attitude formation towards online banking in Finland. International Journal of Bank Marketing, 20 (6), 261-272.

Wiley, J., Krisjanous, J., & Cavana, E. (2007). An experimental study of female Tweeners’ evaluative beliefs regarding ads, attitude toward the ad, and purchase intent for fashion apparel. Young Consumers, 8 (2), 119-127.