Managerial Economics And Marginal Analysis In Decision Making

Common Elements of Decision Making Process

This is the initial stage of decision making process, problem acknowledgement is well-defined as the aspiration to overcome some particular issues in a person’s life. One person need to explain the necessity of some exact choice of purchasing new goods and services for improvement of their life (Brander & Perloff, 2018).

The second part of elements of decision making process is searching for facts and relevant information regarding the issue identified and accepted. The information search entails thorough research through internet, print media, making inquiry from friends and any other source that might be having information regarding the specific product one intends to purchase (Bloch, et al., 2018). Like for instance, one might be interested to purchase an electronic product he or she must consider the cost from various outlets for example amazon.com or Walmart, the durability of the product, the mode of shipping and payment of the product (Bridge & Dodds, 2018).   

The other integral part in decision making process is the assessment of the available choices. One has to establish whether in the list of preference the product is of necessity or not. It involves narrowing down to a single decision that could be a need to purchasing a product.

The buying decision comes after careful assessment of the available choices analysis and the consumer single out on one product over the others in the market.  

The consumer finally makes the decision to purchase a product, from any of the outlet store he considers it offers a reasonable price. The consumer has a variety of option to navigate at the store he is not limited to the decision reached at the purchase decision (Viswanath, 2017).

The post purchase evaluation is very important part in decision making process, this is because if the consumer is contented with the product he will always go back to the store to purchase the same product hence establishing a brand loyalty through experience but if he is dissatisfied then he will have to look for other options (Hirschey, 2016).

Marketers can use consumer behaviour analysis and other techniques like provision of promotional tactics to decide the consumer behaviour and influence their purchasing behaviour toward purchasing their particular products (Solomon, Dahl, White, Zaichkowsky, & Polegato, 2014). They can provide discounts to particular products and making promotions along with consumer response forms can be helpful in familiarizing the consumers towards particular products. 

Marginal analysis entails finding cost and benefits of diverse options by inspecting the result of increase on total income and total cost that is triggered by minimal variation in output or input of each choice (Borgonovo, Cappelli, Maccheroni, & Marinacci, 2018). Marginal analysis is very important tool in making managerial decision and managerial economics. For instance, when a company requires to increase their activities by introducing of varieties of goods and services in the current production line, a marginal analysis of the cost and benefits is very important. Some cost examined include but not limited to the rise in production, large factories producing or storing finished goods and as the cost of extra manufacturing resources to make the products after all the cost are recognised and projected, the amount are equated to the projected rise in trades accredited to the extra manufacturing, it takes projected rise in returns and subtract the projections of cost (Bush, et al., 2018). If the rise in revenue prevail over the rise in the total cost, then the enlargement of the firm might be a wise investment decision.

Marginal Analysis Concept

Marginal production cost is equivalent to the twin variables related to the demand restrictions, at least there is no malice. When one compares the demand for a given product while maintaining the demand for the other goods and services unaffected, the marginal expense for the goods and services is the equal and stable as long as the ideal result resembles the same basic results, which is the curve representing the marginal cost as a function of quantity produced (Letmathe & Wagner, 2018). Consider the ideal results of a long-term problems, determined by taking into account a fixed demand  for each product . The short run marginal expense for rises the long-run marginal expenditure curve for demand  in size consequently being adjusted, which agrees with the normal micro-economic theory. The distinctive characteristic of a production system is represented by linear programming that is related to stare-step profit curve (Grieco, Pinkse, & Slade, 2018).

Economist Alfred Marshall developed microeconomics theory of marginalism. He indicated that creation is only helpful for a company when MR>MC, and he also stated that it is more importance when the variance is largest (Caldari, 2018). For example, a car company should only produce cars up to the point where the marginal expenditure is equal to marginal benefits. Narrowing down the decisions into reduced, quantifiable and understandable decision, the car manager can boost returns margins (Granovetter, 2018) 

Assuming a firm is capable of quantifying the amount of an extra benefits and costs of an extra economic activity. The theory of marginal analysis dictates that in the instance where the marginal benefit surpasses marginal expenditure, a manager needs to do more activities to attain the maximum net benefit. On the other hand, when the marginal expenditure is greater than the marginal benefit, the activities needs to be reduced (Ghisellini, Ripa, & Ulgiati, 2018). Sunk costs, fixed costs and average costs do not have any effect on the marginal analysis and therefore, they are not relevant to forthcoming ideal decision-making (Tietenberg & Lewis, 2016). Marginal analysis can only rectify what transpires when the company employs an extra worker, produces an extra good, dedicates extra efforts to research and development.

Marginal Analysis and Opportunity Cost

Managers should also identify the concept of opportunity cost. In case the manager is aware that there are enough resources in the company financial plan that can sustain to hire an extra employee. Marginal analysis tells the manager that the extra company employee offers a worthy to note net marginal benefit (Boardman, Greenberg, Vining, & Weimer, 2017). This should not be used to prove that the employment of extra worker was the right decision in the factory. In case the manager is cognizant of the fact that hiring of an extra sales and marketing person will yields a larger net marginal benefit, then hiring an employee at the factory section will be wrong decision since it will not be beneficial to the company (Weimer & Vining, 2017).  

Question A

1. The Dependent variable is represented by SALES (Y) which is in thousands gallons (‘000 gallons)

The Independent Variables is represented by

                   – Advertising Expenses (A)

– Selling Price (P)

Short-Run and Long-Run Investments

– Disposable Income (M)

Table 1: Regression results

Dependent Variable : SALES (Y) (‘000 gallons)	Coefficients	Standard Error	t-statistics	p-value
Y- Intercept	321.24	91.80	3.50	0.01
Advertising Expenses (A)($ ‘000)	0.03	0.19	0.16	0.88
Selling Price (P)   ($ ‘000)	-12.44	4.31	-2.89	0.03
Disposable Income (M) ($ ‘000)	2.08	3.02	0.69	0.52

Where Y is Sales

            A is Advertising Expenses

            P is Selling Price

            M is the Disposable Income.

            321.24 is the Y intercept.

Table 2: Regression Statistics

Multiple R	0.807724
R Square	0.711586
Adjusted R square	0.74925
Standard Error	0.445
Observation	10

The R value from the Model summary above represent a simple correlation 0.807 which indicates that there is a high degree of correlation between the variables. R Squared represented by 71.1% indicate the degree of total variation in the dependent variable (Fama & French, 2017).

1. We can look at the adjusted R Squared which is 0.749 representing 74.9% of variation in sales is explained by the independent variables above and this results indicate that the model is good to test the goodness of fit(D’Agostino, 2017).

Joint significance of coefficients Can also be used to determine the goodness of fit.

Table 3: Anova.

ANOVA
	df	SS	MS	F	Significance F
Regression	3	6986.814	2328.938	8.40	0.01
Residual	6	16663.186	277.1977
Total	9	8650

The last column shows P-Value of 0.01 this value is less than 0.05 or 5% hence this indicates that these coefficients are jointly significant at 5% precision level or rather level of significance.

The selling price is the only statistically significant variable at 5%. The others are not statistically significant (Halsey, Curran-Everett, Vowler, & Drummond, 2015).

• The advertisement expenses have no statistically significant effect on the sales. The disposable income has no significant effect on the sales. They both have a positive $0.03 and $2.08 respectively which implies that as the price of advertisement increases by $1 the Sales volumes increase by $0.03 and when the price of disposable income increases by $1 the Sales volume also increases by $2.08. On the other hand, the coefficient of selling price is negative which implies that as the price increases by $1 the sales volumes decrease by $12.44.

1. Price elasticity =%

Income elasticity = %

Elasticity =

   Price elasticity=

The price elasticity is positive 12.25 which means that the quantity demanded does not change proportionately (Zhang, Ji, & Fan, 2018). When the value is greater than one it is said to be elastic. 

Income elasticity =

The income elasticity is used to measure the responsiveness of the quantities demanded for products to a unit change in income (Hummels & Lee, 2018). The figure is also positive because the goods here are not inferior goods.

Part 2

Question B. 

Where is the estimated number of units of goods Y demanded

A is the price of Y

P is the price of related good X

M is the income.

The logarithmic indication of the slant on equation proves that there is a positive relationship between the interest for A and the cost of M for instance, the interest for A goes up when the cost of M goes up so products A and M are substitutes (Davidian, 2017).

1. X is a normal good. On the other hand, interest for these products will increase when prices fall.  In case price impact of X is negative, then the sales impact of the values will work in inverse course to the substitution impact.

• Linear form is a good estimator as compared to non-linear, this is because it gives the actual results as opposed to non-linear which dwell more on the estimates. 

Question A.

1. Table 4: Production schedule.

Crew Size (L)
2	3	–	1.5
3	6	3	2
4	11	5	2.75
5	19	8	3.8
6	24	5	4.0
7	28	4	4.0
8	31	3	3.875
9	33	2	3.67
10	34	1	3.40
11	34	0	3.09
12	33	-1	2.75

The Marginal Product trend determines whether there is an increasing, decreasing, constant or negative returns (Tschopp, 2017). The increasing returns occurs when the marginal product is increasing, the decreasing returns occurs when the marginal returns is decreasing, the constant returns occurs when the marginal returns is constant and negative returns occurs when the marginal returns is negative (Friedman, 2017). From the above scenario then we can conclude that crew size of 3, 4 and 5 exhibit an increasing return, the crew size 5, 6, 7, 8, 9, 10 and 11 experienced a decreasing return, crew size 12 exhibited a negative returns and lastly, there was no constant returns in this production schedule (Grafton, Kirkley, & Squires, 2017).

1. The Total product is at maximum where the Marginal Product is equal to zero. If the owner of trawler aims to maximize the total amount of fish caught, then the labour of the crew size should be 10 or 11.

• If the owner of trawler is interested in maximizing the average amount of fish caught, then crew size 6 or 7 is the best ideal place because at that position the average product is maximized(Grafton, Kirkley, & Squires, 2017).  

Part 3

Question B.

Table 5: PRODUCTION SCHEDULE

L	TPL	AR OR P	TR	TC	PROFIT =TR-TC
2	3	75	225	300	-75
3	6	75	450	450	0
4	11	75	825	600	225
5	19	75	1425	750	675
6	24	75	1800	900	900
7	28	75	2100	1050	1050
8	31	75	2325	1200	1125
9	33	75	2475	1350	1125
10	34	75	2550	1500	1050
11	34	75	2550	1650	900
12	33	75	2475	1800	675

Total Revenue = Total Product of Labour * Average Revenue/ Price

                        At L=5, the TR = 19*75=1425

                        At L=10, the TR = 34*75=2550

Total Cost = Quantity of Labour * Wage Rate (Wage Rate is $150 per worker)

                  = at L=7, the TC =7*150=1050

                  = at L=12, the TC=12*150=1800

                  = at L= 3, the TC = 3*150 = 450

Profits = Total Revenue – Total Cost

Consumer Behavior Analysis and Promotional Tactics

               = at L= 4, the Profit = 825 – 600=225,

               = at L=7, the Profit = 2100-1050=1050

               = at L= 10, the Profit = 2550-1500=1050

The profit is maximized when the labour is at 8 or 9 that is $ 1125 which is the maximum profits. 

Part 4

Question A

Demand Function.

TR=Price X Quantity 

To get the Marginal Revenue we differentiate the Total Revenue

………………………………………….. (1)

Cost Function

To get the Marginal cost we differentiate the Total Cost Function.

…………………………………………………… (2)

      = 10

The profit maximization Condition is MC=MR

The profit maximizing output is 800

We therefore substitute the value of output in the demand function.

$130 is now the profit miximizing price.

Total Profit = Total Revenue –Total Cost 

Rate of return =

                        =

                        =   14.2  

Consequences of charging price $100 per unit.

Total Profit = Total Revenue – Total Cost

                   =

                   =

                   = $65,000

The observation is that when the profit maximizing price is set at $ 100 or rather reduced from $130, this has an adverse effect to the total profits which also reduces by $6000 from $71,000 to $65,000.

Rate of return =

                       =

                        = 13% 

Question C.

Price = Average Total Cost + Average Profit / Unit

Solve the quadratic equation using the quadratic formula  

Substitute the value of output in the demand function and here we choose the highest positive value which is 1174.16

                           P = $ 250 – $0.15Q

                              = $250 – $0.15(1174.16)

                         = 250-176.12

                          = $73.88

Total Profit = Total Revenue – Total Cost

                   = 73.88 X 1174.16-$25,000-$10(1174.16)

                   = 86,735.2 -25,000 – 11,741.6

                   = $49,993.60 

Collusion occurs when firms operating in a market makes a silent pact to avoid competition among the rival’s firms in the market. The agreement may take a form of price fixation or quantity fixation (Haraguchi & Matsumura, 2018). Collusion occurs when rival firms in an industry co-operate for their own good by setting higher prices in order to make supernormal profits (Marshall, Marx, & Meurer, 2014). Collusion mostly occurs in oligopoly market structure, where few firm’s decisions to engage in a silent agreement can significantly influence the whole market (Head & Spencer, 2017). 

The figure above shows a competitive industry that has price  and competitive. The results of collusion of the firms in the industry confines the output to  and consequently results to rise in price to . Collusion usually comprises some form of secret arrangement to increase prices. This may include increasing customer prices for instance vertical price fixing, Monopsony pricing where the retailers enter into a pact to reduce the amount paid to suppliers and lastly collusive tendering (Naidu, Nyarko, & Wang, 2016).

Cartel activities is an association by the producer to manage the prices or quantity and restricts the competition, they include the oil and petroleum exporting countries (OPEC). The cartel activities require an in elastic product demand for it to be successful. Secondly, the Oligopoly is the other type of collusion where small enter a pact to sell almost the same products at set quantities and prices. Thirdly, price signalling is the other type of collusion where the firms operating in the market decides to raise the price hoping that other firms will follow suit (Stiefel, Nakamura, Terui, & Ishitani, 2018). Last but not least, price leadership is the other type of collusion where the firm operating in the industry will occasionally announce the price changes so that others abide with the changes. 

Opportunity Cost

Oil cartels operating under the umbrella of OPEC have been successful as opposed to their counterpart milk cartels. The main difference between the two cartels is that OPEC operation is fully supported by the government unlike the milk cartel which is a group of individual milk farmers operating on voluntary secret agreement among themselves. This therefore implies that, the OPEC has an added advantage in terms of structure and command. The cartel can control the oil industry and eventually control the prices of oil in the market. The members of the oil industry will abide and by decision because it is binding and enforceable (Yaseen, Aldwairi, Jararweh, Al-Ayyoub, & Gupta, 2018). The OPEC is well organised and has minimal number of members not abiding by the decision reached by the top management. The milk cartel on the other hand, is led by members coming together on voluntary basis, they do not have a legally binding agreement hence their contract is not enforceable. In their case even if a production limit is reached, different individual farmers can decide to produce more and more milk and in turn sell in the market (Burlando & Motta, 2015). With a production control in place, it will be an encouragement for some other farmers to sell more and more milk, when others are selling less abiding by the association rule in order to push the prices of milk up. As more and more individual farmers engage in selling more milk in the market, the prices eventually go down due to low demand and a high supply of the milk. This eventually collapses the whole idea of cartel purpose.

Secondly, the other distinct feature between milk and oil is that price changes for milk does not affect the utilization as compared to price changes for oil. A small change in production of oil has no significant effect on the prices. 

OPEC is an amalgamation of many countries and should a single country defies the order of OPEC then there is no problem because the organization can operate by imposing sanctions to the defying country. The sanction will make it hard for the defying country to operate in the market.  

References

Bloch, H., Acs, Z. J., Audretsch, D. B., Acs, Z. J., Audretsch, D. B., Aghion, P., & … & Metcalfe, J. S. (2018). Money and Business Fluctuations in the Schumpeterian System. In Schumpeter’s Price Theory (Vol. 14). Cambridge, MA: Cambidge University Press.

Boardman, A. E., Greenberg, D. H., Vining, A. R., & Weimer, D. L. (2017). Cost-benefit analysis: concepts and practice. Cambridge University Press.

Borgonovo, E., Cappelli, V., Maccheroni, F., & Marinacci, M. (2018). Risk analysis and decision theory: A bridge. European Journal of Operational Research, 264(1), 280-293.

Brander, J. A., & Perloff, J. M. (2018). Managerial Economics and Strategy, (Global Edition. ed.). Pearson Education, Incorporated.

Bridge, J., & Dodds, J. C. (2018). Managerial decision making. Routledge.

Burlando, A., & Motta, A. (2015). Collusion and the Organization of the Firm. American Economic Journal: Microeconomics, 7(3), 54-84.

Bush, J. L., Bush, H. M., Coker, A. L., Brancato, C. J., Clear, E. R., & Recktenwald, E. A. (2018). Total and marginal cost analysis for a high school based bystander intervention. Journal of school violence, 17(2), 152-163.

Caldari, K. (2018). Alfred Marshall and François Perroux: the neglected liaison. . The European Journal of the History of Economic Thought, 25(1), 134-174.

D’Agostino, R. (2017). Goodness-of-fit-techniques. Routledge.

Davidian, M. (2017). Nonlinear models for repeated measurement data. Routledge.

Fama, E. F., & French, K. R. (2017). International tests of a five-factor asset pricing model. Journal of financial Economics, 123(3), 441-463.

Friedman, M. (2017). Price theory. Routledge.

Ghisellini, P., Ripa, M., & Ulgiati, S. (2018). Exploring environmental and economic costs and benefits of a circular economy approach to the construction and demolition sector. A literature review. Journal of Cleaner Production, 178, 618-643.

Grafton, R. Q., Kirkley, J., & Squires, D. (2017). Economics for fisheries management. Routledge.

Granovetter, M. (2018). The sociology of economic life. Routledge.

Grieco, P., Pinkse, J., & Slade, M. (2018). Brewed in North America: Mergers, marginal costs, and efficiency. International Journal of Industrial Organization, 59, 24-65.

Halsey, L. G., Curran-Everett, D., Vowler, S. L., & Drummond, G. B. (2015). The fickle P value generates irreproducible results. Nature methods, 12(3), 179-198.

Haraguchi, J., & Matsumura, T. (2018). Government-leading welfare-improving collusion. International Review of Economics & Finance, 56, 363-370.

Head, K., & Spencer, B. J. (2017). Oligopoly in international trade: Rise, fall and resurgence. Canadian Journal of Economics/Revue canadienne d’économique, 50(5), 1414-1444.

Hirschey, M. (2016). Managerial economics. Cengage Learning.

Hummels, D., & Lee, K. Y. (2018). The income elasticity of import demand: Micro evidence and an application. Journal of International Economics, 113, 20-34.

Letmathe, P., & Wagner, S. (2018). “Messy” marginal costs: Internal pricing of environmental aspects on the firm level. International Journal of Production Economics, 201, 41-52.

Marshall, R. C., Marx, L. M., & Meurer, M. J. (2014). The economics of bidder collusion. In Game Theory and Business Applications. Springer, Boston, MA.

Naidu, S., Nyarko, Y., & Wang, S. Y. (2016). Monopsony power in migrant labor markets: evidence from the United Arab Emirates. Journal of Political Economy, 124(6), 1735-1792.

Solomon, M. R., Dahl, D. W., White, K., Zaichkowsky, J. L., & Polegato, R. (2014). Consumer behavior: Buying, having, and being. 10.

Stiefel, F., Nakamura, K., Terui, T., & Ishitani, K. (2018). The Collusion Classification Grid: A Supervision and Research Tool. Journal of pain and symptom management, 55(2), e1-e3.

Tietenberg, T. H., & Lewis, L. (2016). Environmental and natural resource economics. Routledge.

Tschopp, J. (2017). Wage Formation: Towards Isolating Search and Bargaining Effects from the Marginal Product. The Economic Journal, 127(603), 1693-1729.

Viswanath, N. S. (2017). Managerial Economics. DHARANA-Bhavan’s International Journal of Business, 4(1), 61-63.

Weimer, D. L., & Vining, A. R. (2017). Policy analysis: Concepts and practice. Routledge.

Yaseen, Q., Aldwairi, M., Jararweh, Y., Al-Ayyoub, M., & Gupta, B. (2018). Collusion attacks mitigation in internet of things: a fog based model. Multimedia Tools and Applications, 77(14), 18249-18268.

Zhang, Y., Ji, Q., & Fan, Y. (2018). The price and income elasticity of China’s natural gas demand: A multi-sectoral perspective. Energy Policy, 113, 332-341.