作物生産에 있어서의 新計劃과 Activity Analysis에 關한 考察 : Cut worse of for Better = THE "NEW" PLANNING OF CROP PRODUCTION AND ACTIVITY ANALYSIS
저자
李弼圭 (全南大學校 農科大學 農業經營學敎室)
발행기관
全南大學校 農漁村開發硏究所(INSTITUTE OF AGRICULTURAL SCIENCE & TECHNOLOGY CHONNAM NATIONAL UNIVERSITY)
학술지명
권호사항
발행연도
1963
작성언어
Korean
KDC
520.5
자료형태
학술저널
수록면
1-44(44쪽)
제공처
The linear model of production such as activity analysis or linear programming, has other uses beside its obvious one as a practical way of computing solutions to practical maximinum problems. It doubles as a useful theoretical tool, a convenient way of idealizing the production and profit-maximizing side of a model designed for answering abstract economic questions.
Actually, it is a method of more normative pranning and an analysis in finding the optimum level programming with the same value of production by fact which activity or process* choice and its technical substitution are possible than marginal analysis with production function or transformation function. [*If it is invested with fixed-coefficient of production(input pre unit of output), output is hold the same value of production].
This study attempts to exhibit activity analysis in its role, descrbing production possibilities in the theory of farm management planning. And in this paper two problems are studied from theoretical and practical points of view.
One is how much resources (being constraint) are to be allocated to what kind of production activity for the efficient value of production in optimum porgramming. The other is how to allocate resources for the optimum level of activity, ie: the maximum value of objective function, when a farm enterprise is organized newly.
The drift of this study is largely divided as following three chapters;
1. Various activities and Iso-product contour lines are studied in connection with basic principls of activity analysis in production enterprise. Production attainable area determined by the property(impossibility of the Land of Cockaige) and the Constraint techniques of factor is an available point of optimum production which indicates the maximum production as well as minimum cost as production frontier.
2. Lineal activity analysis is used to choose the optimum programming in the same production value by the simultaneous uses and substitution of activities not asa marginal production analysis by factor-factor substitution.
3. Practical study with Experimental Data of Crop Production
Data in this study are gotten from the Agricultural College, Chonnam National University, Kwangju, and the office of Rural Development, Suwon.
(ⅰ) Activity analysis was applied for the optimum programming with capital 40,000Won on paddy field 7 Tanbo(1.75acres) where rice (x₁, former-culture) and naked barley(x₂, after-culture) were to be produced as a model of small size of farm management (Thefore cultivated area totals 14 Tanbo=3.5 acres, x₁=7, x₂=7 respectively).
Once those are given to farm orginization as a whole with given available resources, we can get optimum programming of production. Those have been worked within a Jinear technology which defines farmer's feasible input-output combinations by a system of jinear inequalities. Thus if production is feasible within the given area, the feasible set of input-output points is a convex polygon. In the linear model which is shown by the combination of constant returns to scale and the additivity of processes, gets us convexity.
And all required is that farmer's ultimate feasible set should be convex. The efficient frontier or transformation curve (or surface) must show nonincreasing marginal rates of transformation. Namely, efficient production as a production frontier in the attainable area of broken-line convex polygon could be gotten by maximum production level. Once this is assumed, the proofs go through much as we sketched them.
One set of weights is such that the given efficient point is a solution of the farm programming maximum problem with those weights in the objective function.
Consequently, result from this graphic analysis with main geometrical or mathematical otols indicated optimum solution as fallowings;
x₁=16.79 Suk (2.384.76kg),
x₂=10?? Suk (1,512.00kg),
nad the net revenue=31,306 Won
This optimum solution of the farm programming is an efficient programming is an efficient production because of being correspondent with criterion equation,
-ΔZ = -??C₂-C₁, when Z=objective function,
X₁= rice, X₂= naked barley, and C=profit coefficient.
(ⅱ) a; As a model of newly·organized farm enterprise, the problem how much labour power and capital should be invested for net revenue 5,000 won was discussed using the production coefficients from upper-mentioned two agences' experiment data.
In this programming, soybean culture was exempted in the profit competitive relation with other crops.
As a result of those, rice(2,34 Suk) and naked barley (2,17 Suk) was produced respectively, and for them man·power (38 days) and capital (6,6000 won) were required.
Accordingly, this type of programming can be judged as effective to enlarge the size.
b; It was orginally intended to serve as an illustration of optimum programming under the condition of canstraint factors such as capital 11,500 won, man power 62 days, rice field 605 Pyung, and barley field 417 Pyung.
Conseguently, net revenue 8,815 won was returned.
The linear model such as the above(a) and (b) being associated with the ray of each activity which makes cone standing right up in the two or three-dimentional fan-space, and being consisted of the constant right up in the two or three-dimentional fan-space, and being consisted of the constant returns to scale, decreasing returns, additivity, and divisibility of activity would result in getting convexity. University decreasing returns to scale would result in even more convexity(not flat place on the efficiency frontier).
So we could get long with a mixture of constant and decreasing returners to scale scattered through the seperate activities available.
Drawing the diagram is simplified by geometrical methods; the ray through each production activity and Iso-revenue line is optimum solution obtained by the ratios of one or more production coefficients and perpendicular line to constants.
For an approach slightly more similar in sprit to activity analysis of the present paper, the reader is referred to the fundamental paper by T.C. Koopmans (ed), "Activity analysis of production and Allocation"(Selected reference(2)).
Conclusion
We can say that the activity analysis do contains various assumptions, lineality, additivity, independency and divisibility in its characteristics.
From the view·point of three fectors, ie: resources restriction, alternative method of activity or process, and maximization of objective function, it is not a problem of small scoped-optimum value in the frame work of production attainable area, but an all scoped-problem.
Also, it is the very programming which choose a profictable production activity in relation with fixed-coefficient of production which guarantees constant out-put , if resources are invested as a constant rate, and which maximizes objective function under constraint linear inequation of constant rate, and which maximized objective function under constraint linear inequation of activity analysis computations.
At the same time, it proceeds within the condition of non minus activity level.
However, even though activity analysis for optimum solution has many superior characteristics to marginal production analysis using one-purposed production function or transformation functions as a available and normative programming, it is required to use together or corresponed closely with budgeting method game theory because of varieties in farm management.
In brief, we conclude that it is a effective method as a technical tool which lead to effective programming in decision making of activities combination.
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