The investigation of influential factors on the productivity of broiler farming units (case study: Markazi province).
The increasing population of developing countries leads to rising demand for food. On one hand, the increased income will directly enhance the supply and demand cycle of food due to the relatively high income elasticity of food items. The simultaneous effect of these two factors is so significant that it challenges the production process in developing and developed countries and the agriculture section might not be able produce sufficient food. The scarce production resources resource can be used for those infrastructures which increase the level of production. Therefore, if the agriculture section cannot fulfill its assigned functions, the importation of food products will be inevitable as a result of which the production process becomes slow, the gap between supply and demand will rise and severe underdevelopment might continue. Due to the fact that the access to sufficient food is one of the basic rights of humankind, the governments have to implement detailed plans to improve the nutritional status of the public. Therefore, the provision of food security requires endeavors to provide access for all families to nutritional products, especially the vulnerable families and poor families. On the other hand, a major number of experts believe that rural and agricultural sections are have strategic significance among the other economic sectors.
In Iran, the poultry industry has a background of fifty years and it is one of the most investment-demanding industrial industries in the country. Therefore, the consideration of its economic aspects and productivity is highly significant. Of the measures which should be done in this regard, one could point to reduction in types and volume of wastes, especially animal waste, during different stages of production cycle of poultry industry which reduces the income and generates environmental problems.
Despite of the presumed significance of productivity, the managers of organizations in different sectors lack sufficient knowledge regarding the concept of productivity and measurement methods. As Sink (1985) stated, despite of the fact that the issue of productivity is regarded as a common subject of management circles in the present era it is less practically comprehended.
The endeavors to functionalize the association between inputs and outputs along with determination of the maximum achievable output lead to the design of parametric production functions in economic studies. Functions such as Cobb-Douglas and Leontief in the microeconomic theories are instances of such endeavors. Farrel (1957) first introduced a frontier method called "Farrel Productivity Frontier". He used mathematical equations to measure the distance of a decision-making unit from the above-mentioned productivity frontier as the productivity of that unit.
Udoh and Etim (2009) analyzed the technical productivity of 100 aviculture farmers through estimation of random frontier production function in one of the Nigeria states and reported the level of productivity as 0.62. The results showed that some factors such as technical equipment and experience exert significant effects upon the technical productivity.
Adepojo (2008) used the Cobb-Douglas random frontier production function and estimation of factors affecting productivity to verify the technical productivity of egg products in one of the states of Nigeria. The range of productivity was 24-93 percent the mean of which was 76 percent. Based on the findings of this study, the units that were closer to the city had higher productivity.
H.1-There is a significant difference of productivity among broiler farming units based on the managerial characteristics of managers.
H.2-There is a positive association between personal characteristics of managers and productivity of broiler farming units.
H.3-There is a positive association between managerial activities and productivity of broiler farming units.
To measure the characteristics of managers of the aviculture units, a questionnaire designed by the researcher was used. The dependent variable for the present study is the productivity of broiler farming units of Markazi Province the measurement of which was done through a questionnaire designed by the researcher. Eviews, Excel and SPSS applications were used to sum up the values of each items of the dependent variables. The items were coded as Likert scale.
To measure the productivity, the estimation of production function was used and total productivity was determined through the estimated production function. To calculate the total productivity, the following equation was used:
InY = [lna.sub.0] + [[SIGMA].sup.n.sub.i=1] [[alpha].sub.i]Ln([X.sub.i])+ [[SIGMA].sup.n.sub.i=1]bXi (1.2)
In the above equation, Y refers to gross income of production unit, [X.sub.i] is ith input and [b.sub.i] and [a.sub.i] are respectively the coefficients of parameters in linear and logarithmic modes. The reason for using such a function form is its ability to measure the extension of production variable compared with inputs. The calculation of total productivity in this function can be done through equation 2.3.
[MP.sub.i] = dy/dxi = y(ai/xi + bi) (2.2)
The values of total productivity (MPi) and obtained product (Py) can be used to calculate the value of total productivity of each input.
[VMP.sub.i] = Py.M[P.sub.i] (2.3)
In this type of productivity, the mean value of production from an input is measured. To determine the mean productivity, the ratio of production to input might be used (APi = Y/Xi) which is a mistake. This equation is correct only when it is used for production of one item. To remove this defect, the shares of inputs in the final production should be distinguished from each other. Therefore, the mean productivity is determined through the following equation in which MPi is the final productivity and Ei is the value of production extension.
[AP.sub.i] =[MP.sub.i]/[E.sub.i] (2.4)
In the present study, the calculation of partial productivity is followed by determination of total productivity so as to consider the mutual effects and substitution of factors, obtain a higher level of confidence and provision of realistic viewpoint of performance of units. To calculate the total productivity of all factors in the productive units, the following equation was used:
[TFP.sub.i]= T[R.sub.i]/[SIGMA] [W.sub.j]/[C.sub.ij]) (2.5)
In the above equation, TRi is the total received value, Cji is refers to current expenses and [W.sub.i] denotes the coefficients of mean share of expenses for each input compared with total expenses of units.
The identification of economic features of broiler farming units is done through correlation tests. Nonparametric tests were used to determine the managerial features and measures. Excel Software was used to process the data and calculation of productivity for each production factor was done through Eviews Software.
Estimation of Production Function:
To calculate productivity, the production function was used. To select the type of production function of broiler, the estimations of Cobb-Douglas and transcendental functions were used. In this regard, the independent quantative and qualitative variables such as the value of feed, value of labor, administrative and productive payments, capacity of aviculture units, hygiene expenses, other expenses, capital, age, experience and level of education were modelled and then, different tests were used to estimate model based on four variables of the value of feed, the value of broiler chicken, the value of labor and hygiene costs. The other variables were excluded due to the statistical insignificance of coefficients. The above four variables were used to estimate the function through Cobb-Douglas and transcendental functions.
The Cobb-Douglas estimation is shown in table 1.3. In this model, the function coefficients were production extensions. [R.sup.2] shows that 78 percent of changes is explained by four variables of consumed feed, broiler, labor and hygiene expenses.
To select the proper production function, the test of significant difference between Cobb-Douglas, transcendental functions and bound F-test were used. In this regard, the following equation was used because the transcendental function has four new variables.
F = (0.83 - 0.78)/4 /(1-0.83)/(92-8) = 6.18 (3.1)
The total and mean productivity of production factors:
As observed before, the mean productivity of consumed feed for the intended 92 broiler farming units was 0.607. Based on the purchase price of feed, the mean value of total productivity of feed in the intended units was 2674391120 Rial.
The mean productivity of broiler for the 92 broiler farming units was 2.609 which ranges from 1.75 to 3.5. It should be noted that this value has been defined based on the loss of broiler chickens in this units. The total productivity of broiler chicken was 63093880. This means that adding one unit of broiler chicken can averagely add 630938800 Rial to the income of broiler farming unit. Due to the fact that the mean price of each broiler chicken is 11860 Rial, the addition of more broiler chickens will be economically profitable based on the above value.
The mean productivity of labor is 19474.73. The maximum and minimum productivity of labor were respectively 5000 and 47500 (in average).
Quantity Mean Maximum Minimum Mean Productivity 19474.73 47500 5000 Total Productivity 2.12 4 2 Value of Total 8124 15328 7664 Productivity (VMPX) VMPX/PX 0.002 0.003 0.0018 Source: Research Findings
The mean productivity of hygiene for all samples was 0.0048 which ranged from 0.0083 to 0.002. The mean value of total productivity in the intended sample was 8700946 which means that usage of an additional unit for hygiene issues will averagely add 8700946 units to the final product.
As shown in table (3.7), the comparison of mean and total productivity of production inputs in CobbDouglas function shows that maximum values of mean and total values of productivity are associated with hygiene and labor.
As shown in the following table, the comparison of mean and total values of productivity for the production inputs as determined through transcendental function show that maximum levels of mean and total productivity are associated with hygiene and labor.
Productivity of All Production Factors:
The equation used for the transcendental function is the following:
[TFP.sub.i] = X1/ 0.57X2+0.13X3 + 0.06X4+0.06X3 (3.2)
In the above equation, X1 is the received value of broiler sale. X2, X3, X4 and X8 respectively refer to the prices of feed, broiler, labor and hygiene issues the coefficients of which show their mean share in the total costs of units.
Based on the results, the mean value of total productivity for the intended productive units is 87.2. In average, one-unit (Rial) additional expense in the broiler farming unit leads to 87.2 unit increase (Rial) for the producers. The least value of total productivity for production factors is 86.1 and the maximum value is 33.4.
Findings of Managerial Characteristics:
1-Planning Skills and Targeting:
The results of the following table show that the respondents believe that mean level of their competency and productivity in managerial skills is 3.24 which is higher than the average. The analysis of skills showed that the respondents had the highest level of competency in planning during difficult situations and following such plans whole the least level of competency among them was observed regarding prediction of production in a cycle of broiler farming.
2-Accounting and Financial Management:
The analyses show that the mean level of respondents' competency in this field is 3.25 which shows their moderate level of skills. In this regard, the ability to register and calculate the initial investment is a top priority while the ability to establish an effective and proper accounting system is the last priority due to lack of sufficient training.
The following table shows that the ability to select the best time to sell the products is the top-ranked competency among marketing skills as verified from the viewpoints of respondents. In this regard, mean value of respondents' ability in this field of management was 3.04 which shows their moderate level of ability.
As shown in table (3.13), the mean values of respondents' competency in this field of management was in a moderate to high level. The ability collect data of modern technologies of the market has the least level among the directors and managers of broiler farming units for which the most significant reason is the low level of education of managers in these units.
5-Skills of Rationality in Decision Making:
The results of table (3.14) shows that the ability of managers in rational decision-making is moderate to high. To measure this skill, six items were used and the results show that managers regard themselves as more competent in quick identification of production problems and proper attention to solving them compared with other characteristics.
6- Skills of Mobilizing Resources:
The ability to complete activities in the best possible time and with the lowest duration and highest performance was reported as the highest competency among the skills of mobilizing resources which was verified through the answers of directors of broiler farming units.
The data analysis showed that the ability of respondents in risk-taking skill is in a moderate to high level. As shown in the following table, the ability to properly use the insurance of agricultural and livestock insurances is in a high level while the low level of essentiality of risk-taking shows the high level of risk aversion among the managers of production units.
The results of data analysis show that the mean value of respondent's communicational skills is 3.81 which shows a middle to high level. Among the verified characteristics in this field, communication with others about the problems to attain proper solutions and ability to help the employees to improve their competencies and skills are respectively high ranked in the answers of respondents. On the other hand, the ability to authorize to do definite procedures has the lowest value which shows that managers of broiler farming units follow traditional management styles and they have failed to realize the measures of participatory management. The ability to establish good relationships with buyers and vendors has the third top position which implies attention to clients and significance of human relation management.
9-Occupational and Production Skills:
The mean value of manager's ability in realizing occupational and production skills is 3.70 which shows their high to very high level of competency in this regard. Most of the items underlying this field of skills were in proper levels. In this regard, the ability to prepare the saloon before the arrival of a new shipment of broiler chickens, ability to run the seed holders and water tanks have the best status.
As shown in table (3.19), the managers have the highest ability in communicational skills and the least level of competency in marketing skills.
10-Categorization of Competencies of Directors of Broiler Farming Units:
To group the competencies of directors of the desired broiler farming units, the method of distance between standard deviation and mean is used (Feli et.al, 2008; Tavasoli et.al, 2008)
A= Low: A< Mean-SD
B=Moderate: Mean- SD <B< Mean
C=Good: Mean< C< Mean+ SD
D=Excellent: Mean+ SD < D
In this regard the mean value of managerial ability is 3.47 and its standard deviation was 0.27. The above formulas were used to group the directors of broiler farming units. Most of the directors were in a range of moderate (35 percent) to high (27 percent).
11-Ananlysis of Influential Managerial Factors upon Productivity:
Due to the fact that the variables of productivity, age, experience, education and competency are relative and interval variable, the Pearson test was used to verify the association of two interval variables, two relative variables, one relative variable and one interval variable. This test was done through SPSS Software. The Pearson Test was used to determine the association between productivity and managerial characteristics the results of which are shown in the following.
4-Conclusion and Further Suggestions:
Based on the results of present study, only 32 percent of the verified units have managers with B.A degree or higher. The educational degree of others was diploma or lower. Over 60 percent of managers were higher than 41 years old. Due to the negative association between the age of managers and productivity, it is recommended to employ managers with lower ages.
The analysis of input items for the broiler farming units showed that feed is the most important factor of production with a share of 57 percent of total expenses. On the other hand, the cost of buying one broiler chicken consists 13 percent of total costs. In general, the results of present study showed that the mean level of competencies of directors of broiler farming units is 3.81 which is in a range of moderate to high level so that 59 percent of respondents were in this range.
Based on the results of present study, the following recommendations are suggested to improve the productivity of broiler farming units:
1- Proper procedures should be applied for employing technical managers so that their technical abilities can be completely utilized. In this regard, holding specialized compact courses for the managers of broiler farming units can be useful.
2- As stated before, hygiene has the highest coefficient and effect among other factors. This factor can increase the production level of broiler farming units. Therefore, it is suggested that such units in different towns sign contracts in cumulative manner and consult with specialists of livestock diseases so that during difficult situations, they can act in a more integrated manner.
3- The associated organizations, especially Agricultural Jihad Organization should pay attention to training for managers of broiler farming units. An educational-promotional course for efficient management of these units should attend to the following items: 1-production and marketing as two complementary concepts 2-education of applied managerial skills based managers' techniques of administration 3-consultation of production affairs based on production history, performance and analysis of profitability as well as accounting records and evaluation of available production resources 4-ability of managers' entrepreneurship skill, interests and authorities should be integrated with those of their peers to help them take the special market opportunities.
Annex 1: Estimation of Transcendental Production Function through EViews Software Dependent Variable: LY Method: Least Squares Date: 12/05/13 Time: 01:07 Sample: 1 93 Included observations: 92 Variable Coefficient Std. Error C -0.419699 2.358863 LDAN -0.028497 0.256279 LJOJ 0.841613 0.265271 LKAR 2.244351 2.133141 LBEH 0.215403 0.221327 DAN 2.86E-06 4.06E-06 JOJ -1.92E-06 1.77E-05 KAR -0.873012 0.876438 BEH -2.30E-08 2.61E-08 R-squared 0.937525 Mean dependent var Adjusted R-squared 0.931503 S.D. dependent var S.E. of regression 0.134662 Akaike info criterion Sum squared resid 1.505103 Schwarz criterion Log likelihood 58.65231 Hannan-Quinn criter. F-statistic 155.6912 Durbin-Watson stat Prob(F-statistic) 0.000000 Included observations: 92 Variable t-Statistic Prob. C -0.177924 0.8592 LDAN -0.111197 0.9117 LJOJ 3.172654 0.0021 LKAR 1.052134 0.2958 LBEH 0.973233 0.3333 DAN 0.705088 0.4827 JOJ -0.108449 0.9139 KAR -0.996091 0.3221 BEH -0.882732 0.3799 R-squared Mean dependent var 10.51947 Adjusted R-squared S.D. dependent var 0.514528 S.E. of regression Akaike info criterion -1.079398 Sum squared resid Schwarz criterion -0.832701 Log likelihood Hannan-Quinn criter. -0.979829 F-statistic Durbin-Watson stat 1.487944 Prob(F-statistic) Annex 2: Estimation of Total Productivity through Variables of Personal and Managerial Characteristics of Managers through Eviews Software Dependent Variable: TFP Method: Least Squares Date: 10/22/13 Time: 07:38 Sample: 1 92 Included observations: 92 Variable Coefficient Std. Error C 8.071676 7.837770 A -0.952050 1.238097 AM 1.103184 0.654423 BM -1.182538 0.884799 RP 0.769384 0.766121 MT 0.485780 0.822392 MM -0.041514 0.500568 MI 0.409652 0.690910 MB -1.247670 0.990506 SEN -0.077105 0.076649 TAH -0.251635 0.420106 TAJ 0.085263 0.062147 TG -0.315670 0.537262 TH 0.143006 0.763988 R-squared 0.124570 Mean dependent var Adjusted R-squared -0.021335 S.D. dependent var S.E. of regression 3.064718 Akaike info criterion Sum squared resid 732.6146 Schwarz criterion Log likelihood -225.9846 Hannan-Quinn criter. F-statistic 0.853775 Durbin-Watson stat Prob(F-statistic) 0.603298 Included observations: 92 Variable t-Statistic Prob. C 1.029843 0.3063 A -0.768962 0.4442 AM 1.685735 0.0958 BM -1.336504 0.1853 RP 1.004259 0.3184 MT 0.590691 0.5564 MM -0.082933 0.9341 MI 0.592916 0.5550 MB -1.259629 0.2116 SEN -1.005955 0.3175 TAH -0.598980 0.5509 TAJ 1.371960 0.1740 TG -0.587553 0.5585 TH 0.187183 0.8520 R-squared Mean dependent var 3.354600 Adjusted R-squared S.D. dependent var 3.032539 S.E. of regression Akaike info criterion 5.217056 Sum squared resid Schwarz criterion 5.600807 Log likelihood Hannan-Quinn criter. 5.371941 F-statistic Durbin-Watson stat 2.230339 Prob(F-statistic) Annex 3: Estimation of Productivity through Personal Characteristics of Managers through EViews Software Dependent Variable: TFP Method: Least Squares Date: 10/22/13 Time: 07:40 Sample: 1 92 Included observations: 92 Variable Coefficient Std. Error SEN -0.101949 0.065891 TAJ 0.089820 0.055773 TAH -0.289385 0.406626 C 7.758168 3.302583 R-squared 0.043517 Mean dependent var Adjusted R-squared 0.010909 S.D. dependent var S.E. of regression 3.015952 Akaike info criterion Sum squared resid 800.4452 Schwarz criterion Log likelihood -230.0578 Hannan-Quinn criter. F-statistic 1.334564 Durbin-Watson stat Prob(F-statistic) 0.268310 Included observations: 92 Variable t-Statistic Prob. SEN -1.547246 0.1254 TAJ 1.610460 0.1109 TAH -0.711674 0.4785 C 2.349121 0.0211 R-squared Mean dependent var 3.354600 Adjusted R-squared S.D. dependent var 3.032539 S.E. of regression Akaike info criterion 5.088213 Sum squared resid Schwarz criterion 5.197856 Log likelihood Hannan-Quinn criter. 5.132466 F-statistic Durbin-Watson stat 2.295071 Prob(F-statistic) Annex.4: Pearson Test of Association between Productivity and Characteristics of Managers through SPSS Software Correlations tfp tah sen tfp Pearson Correlation 1 .144 -.141 Sig. (1-tailed) .085 .090 N 92 92 92 tah Pearson Correlation .144 1 -.509 ** Sig. (1-tailed) .085 .000 N 92 92 92 sen Pearson Correlation -.141 -.509 ** 1 Sig. (1-tailed) .090 .000 N 92 92 92 taj Pearson Correlation -.059 -.535 ** .752 ** Sig. (1-tailed) .288 .000 .000 N 92 92 92 th Pearson Correlation .177 * .101 -.127 Sig. (1-tailed) .046 .168 .114 N 92 92 92 mm Pearson Correlation .104 .050 -.131 Sig. (1-tailed) .161 .317 .106 N 92 92 92 mb Pearson Correlation .062 .058 -.254 ** Sig. (1-tailed) .279 .292 .007 N 92 92 92 mi Pearson Correlation .155 .024 -.227 * Sig. (1-tailed) .071 .410 .015 N 92 92 92 tg Pearson Correlation .020 .075 -.052 Sig. (1-tailed) .424 .237 .311 N 92 92 92 bm Pearson Correlation .015 .029 -.090 Sig. (1-tailed) .443 .393 .196 N 92 92 92 rp Pearson Correlation .112 .099 -.190 * Sig. (1-tailed) .144 .173 .035 N 92 92 92 a Pearson Correlation .120 .022 -.163 Sig. (1-tailed) .127 .418 .061 N 92 92 92 Correlations taj th mm tfp Pearson Correlation -.059 .177 * .104 Sig. (1-tailed) .288 .046 .161 N 92 92 92 tah Pearson Correlation -.535 ** .101 .050 Sig. (1-tailed) .000 .168 .317 N 92 92 92 sen Pearson Correlation .752 ** -.127 -.131 Sig. (1-tailed) .000 .114 .106 N 92 92 92 taj Pearson Correlation 1 -.039 -.058 Sig. (1-tailed) .355 .292 N 92 92 92 th Pearson Correlation -.039 1 .310 ** Sig. (1-tailed) .355 .001 N 92 92 92 mm Pearson Correlation -.058 .310 ** 1 Sig. (1-tailed) .292 .001 N 92 92 92 mb Pearson Correlation -.189 * .057 .276 ** Sig. (1-tailed) .035 .294 .004 N 92 92 92 mi Pearson Correlation -.018 .124 .283 ** Sig. (1-tailed) .434 .120 .003 N 92 92 92 tg Pearson Correlation .009 .048 .123 Sig. (1-tailed) .464 .325 .121 N 92 92 92 bm Pearson Correlation -.065 .085 .257 ** Sig. (1-tailed) .271 .211 .007 N 92 92 92 rp Pearson Correlation -.196 * .352 ** .292 ** Sig. (1-tailed) .031 .000 .002 N 92 92 92 a Pearson Correlation .049 .265 ** .167 Sig. (1-tailed) .323 .005 .055 N 92 92 92 Correlations mb mi tg tfp Pearson Correlation .062 .155 .020 Sig. (1-tailed) .279 .071 .424 N 92 92 92 tah Pearson Correlation .058 .024 .075 ** Sig. (1-tailed) .292 .410 .237 N 92 92 92 sen Pearson Correlation -.254 -.227 ** -.052 Sig. (1-tailed) .007 .015 .311 N 92 92 92 taj Pearson Correlation -.189 -.018 ** .009 ** Sig. (1-tailed) .035 .434 .464 N 92 92 92 th Pearson Correlation .057 * .124 .048 Sig. (1-tailed) .294 .120 .325 N 92 92 92 mm Pearson Correlation .276 .283 .123 Sig. (1-tailed) .004 .003 .121 N 92 92 92 mb Pearson Correlation 1 .493 .287 ** Sig. (1-tailed) .000 .003 N 92 92 92 mi Pearson Correlation .493 1 .303 * Sig. (1-tailed) .000 .002 N 92 92 92 tg Pearson Correlation .287 .303 1 Sig. (1-tailed) .003 .002 N 92 92 92 bm Pearson Correlation .128 .279 .166 Sig. (1-tailed) .111 .003 .057 N 92 92 92 rp Pearson Correlation .353 .340 .180 * Sig. (1-tailed) .000 .000 .043 N 92 92 92 a Pearson Correlation .094 .219 .116 Sig. (1-tailed) .187 .018 .135 N 92 92 92 Correlations bm rp a tfp Pearson Correlation .015 .112 * .120 Sig. (1-tailed) .443 .144 .127 N 92 92 92 tah Pearson Correlation .029 ** .099 .022 Sig. (1-tailed) .393 .173 .418 N 92 92 92 sen Pearson Correlation -.090 ** -.190 -.163 Sig. (1-tailed) .196 .035 .061 N 92 92 92 taj Pearson Correlation -.065 -.196 .049 Sig. (1-tailed) .271 .031 .323 N 92 92 92 th Pearson Correlation .085 .352 .265 ** Sig. (1-tailed) .211 .000 .005 N 92 92 92 mm Pearson Correlation .257 .292 ** .167 Sig. (1-tailed) .007 .002 .055 N 92 92 92 mb Pearson Correlation .128 * .353 .094 ** Sig. (1-tailed) .111 .000 .187 N 92 92 92 mi Pearson Correlation .279 .340 .219 ** Sig. (1-tailed) .003 .000 .018 N 92 92 92 tg Pearson Correlation .166 .180 .116 Sig. (1-tailed) .057 .043 .135 N 92 92 92 bm Pearson Correlation 1 .288 .123 ** Sig. (1-tailed) .003 .122 N 92 92 92 rp Pearson Correlation .288 * 1 ** .023 ** Sig. (1-tailed) .003 .413 N 92 92 92 a Pearson Correlation .123 .023 ** 1 Sig. (1-tailed) .122 .413 N 92 92 92 Correlations mt Am tfp Pearson Correlation .147 .166 Sig. (1-tailed) .080 .057 N 92 92 tah Pearson Correlation .023 .073 Sig. (1-tailed) .415 .244 N 92 92 sen Pearson Correlation -.144 -.318 ** Sig. (1-tailed) .085 .001 N 92 92 taj Pearson Correlation .072 -.201 ** Sig. (1-tailed) .247 .027 N 92 92 th Pearson Correlation .230 * -.077 Sig. (1-tailed) .014 .232 N 92 92 mm Pearson Correlation .188 .136 Sig. (1-tailed) .036 .099 N 92 92 mb Pearson Correlation .240 .157 Sig. (1-tailed) .011 .068 N 92 92 mi Pearson Correlation .365 .200 Sig. (1-tailed) .000 .028 N 92 92 tg Pearson Correlation .192 .074 Sig. (1-tailed) .033 .242 N 92 92 bm Pearson Correlation .255 .219 Sig. (1-tailed) .007 .018 N 92 92 rp Pearson Correlation .142 .172 Sig. (1-tailed) .089 .051 N 92 92 a Pearson Correlation .310 .143 Sig. (1-tailed) .001 .086 N 92 92 *. Correlation is significant at the 0.05 level (1-tailed). **. Correlation is significant at the 0.01 level (1-tailed).
Received 13 September 2014
Received in revised form 26 November 2014
Accepted 25 December 2014
Available online 15 January 2015
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(1) Sayed Nematollah Mosavi and (2) Sayed Mehrdad Dast Varz
(1) Department of Agricultural Economics, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran
(2) PhD Student, Agricultural Economy, Islamic Azad University, Marvdasht, Iran
Corresponding Author: Sayed Nematollah Mosavi, Department of Agricultural Economics, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran
Table 1.3: Estimation of Production Function in Cobb-Douglas Model. Coefficient Variable Value Sign Fixed Value 7.73 - Logarithm of Feed Value 0.14 + Logarithm of Broiler Value 0.28 + Logarithm of Labor Value 0.22 + Logarithm of Hygiene 0.48 + Expenses Variable t-statistic Significance Fixed Value -6.18 5% Logarithm of Feed Value 2.28 5% Logarithm of Broiler Value 3.39 5% Logarithm of Labor Value 2.25 5% Logarithm of Hygiene 3.82 5% Expenses n = 92 F = 79.13 D.W = 1.79 [bar.[R.sup.2]] = 0.77 [R.sup.2] = 0.78 Source: Research Findings Then, the transcendental production function was estimated the results of which are shown in table 3.2. Coefficient Level of Variable Value Sign t-statistic ignificance Fixed Value 6.18 - -1.57 5% Logarithm of 0.42 + 3.47 5% Feed Value Logarithm of 0.68 + 3.71 5% Broiler Value Logarithm of 0.14 - -0.54 5% Labor Value Logarithm of 0.01 + 0 5% Hygiene Expenses Value of Feed 0.01 - -2.74 5% Value of Broiler 0.01 - -3.03 5% in Each Cycle Value of Labor 0.01 + 1.16 5% Hygiene Expenses 0.01 + 1.27 5% n = 92 F = 51.58 D.W = 2.23 [bar.[R.sup.2]] = 0.82 [R.sup.2] = 0.83 Source: Research Findings Table. 3.3: Partial Productivity of Feed in Broiler Farming Units through Transcendental Function. Quantity Mean Maximum Minimum Mean Productivity 0.607 0.947 0.389 Total Productivity 69791 300000 17000 Value of Total 267439112 1149600000 65144000 Productivity (VMPX) VMPX/PX 199730 858551 48651 Sources: Research Findings Table 3.4: Partial Productivity of Broiler Chicken in the Aviculture Units (Transcendental Function). Quantity Mean Maximum Minimum Mean Productivity 2.609 3.5 1.75 Total Productivity 16465.6 750000 4000 Value of Total Productivity 63093880 487400000 15328000 (VMPX) VMPX/PX 53199 410961 12924 Source: Research Findings Table 3.6: Productivity of Hygiene and Treatment in Intended Broiler Farming Units (Transcendental Function). Quantity Mean Maximum Minimum Mean Productivity 0.0048 0.0083 0.002 Total Productivity 8700946 28500000 2400000 Source: Research Findings Table 3.7: Comparison of Total and Mean Productivity of Inputs in Cobb-Douglas Function (In Average). Production Factors Total Mean Productivity Productivity Feed 0.29 2.10 Broiler Chicken 2.51 9.12 Labor 5.12 22.8 Hygiene 9.52 19.75 Source: Research Findings Table 3.8: Comparison of Average Values of Mean and Total Productivity of Inputs through Transcendental Function. Production Factors Total Productivity Mean Productivity Feed 69791 0.607 Broiler Chicken 16465.6 2.609 Labor 2.12 19474.73 Hygiene 8700946 0.0048 Source: Research Findings Table 3.9: Total Productivity of Broiler Farming Units through Transcendental Function. Quantity Mean Maximum Minimum Total Productivity 2.87 4.33 1.86 Source: Research Findings Table 3.10: Frequency Distribution of Viewpoints of Respondents regarding Competency in Planning and Targeting . Row Item Mean Standard Deviation 1 Do you have a plan for difficult 3.95 0.64 situations and to what extent do you follow it? 2 To what extent you can predict the 3.52 0.69 necessary inputs for a definite broiler farming cycle? 3 To what extent you can plan for 3.42 3 production domain and define your short-and long-term objectives? 4 To what extent you can properly 2.97 0.95 estimate the production costs during a cycle of broiler farming? 5 To what extent you can properly 2.91 0.92 estimate the income of production during a cycle of broiler farming? 6 To what extent you can properly 2.72 0.94 predict the production during a cycle a broiler farming? Mean 3.24 0.83 Sources: Research Findings Table 3.11: Frequency Distribution of Viewpoints of Respondents regarding Competency in Accounting and Financial Management Row Item Mean Standard Deviation 1 To what extent you have the ability to 3.61 0.64 register and calculate the value of initial investment in broiler farming unit? 2 To what extent you have the ability to 3.43 0.70 register the value of consumed items in broiler farming unit? 3 To what extent you have the ability to 3.27 0.71 purchase large values of materials to get discounts? 4 To what extent you have the ability to 3.26 0.79 register the level of production in broiler farming unit? 5 To what extent you have the ability to 3.22 0.84 register and calculate the values of profit and loss in broiler farming unit? 6 To what extent you have the ability to 3.17 0.85 follow trainings to improve your financial management skills? 7 To what extent you have the ability to 3.08 0.74 effectively use different financial and credit resources? 8 To what extent you have the ability to 2.97 4.19 create an effective accounting system? Mean 3.25 1.18 Sources: Research Findings Table 3.12: Frequency Distribution of Viewpoints of Respondents regarding Competency in Marketing Management Row Item Mean Standard Deviation 1 To what extent you have the ability to 3.44 0.70 select the best time to sell the products? 2 To what extent you have the ability to 3.25 0.83 directly provide products to consumers (instead of slaughterhouse)? 3 To what extent you have the ability to 3.00 0.75 analyze the supply and demand as well as the price of eggs? 4 To what extent you are familiar with 2.95 0.76 the role of forums in direct sale of products? 5 To what extent you can analyze the 2.85 0.75 governmental policies regarding your market? 6 To what extent you are familiar with 2.75 0.80 modern methods of packing? Mean 3.04 0.76 Sources: Research Findings Table 3.13: Frequency Distribution of Viewpoints of Respondents regarding Competency in Knowledge Skill Row Item Mean Standard Deviation 1 To what extent you have the ability to 3.19 0.70 search for newer methods to do the procedures? 2 To what extent you have the ability to 3.17 0.82 collect information on prices of input items and market? 3 To what extent you have the ability to 2.98 0.90 collect information on the state policies of market? 4 To what extent you have the ability to 2.98 0.77 collect information regarding state policies of modern technologies? Mean 3.08 0.80 Sources: Research Findings Table 3.14: Frequency Distribution of Viewpoints of Respondents regarding Competency in Rational Decision-making. Row Item Mean Standard Deviation 1 To what extent you have the ability to 3.68 0.64 quickly identify the production problems and properly solve them? 2 To what extent you have the ability to 3.53 3.06 quickly analyze unprecedented situations? 3 To what extent you have the ability to 3.42 0.60 effective use production consultants (economy, veterinary, nutrition, etc.)? 4 To what extent you have the ability to 3.31 0.64 apply the best managerial methods in production operations of broiler farming unit? 5 To what extent you have the ability to 3.20 0.72 make correct decisions during the application or awareness of new technologies? 6 To what extent you have the ability to 3.16 0.84 make correct decisions on the technologies which should be reviewed or used? Mean 3.38 1.08 Sources: Research Findings Table 3.15: Frequency Distribution of Viewpoints of Respondents regarding Competency in Skills of Mobilizing Resources . Row Item Mean Standard Deviation 1 To what extent you have the ability to 3.46 0.06 execute activities in the least possible time, the lowest period of time and with the highest performance? 2 To what extent you have the ability to 3.19 0.65 use the materials with the lowest prices to obtain maximum productivity? 3 To what extent you have the ability to 3.06 0.62 select technologies and methods which can enhance the usage of resources? 4 Mean 3.24 0.62 Sources: Research Findings Table 3.16: Frequency Distribution of Viewpoints of Respondents regarding Competency in Risk-taking Skill. Row Item Mean Standard Deviation 1 To what extent you have the ability to 4.02 0.88 properly use insurances of agricultural and veterinary products? 2 To what extent you have the ability to 3.97 0.89 save and deposit in emergency financial accounts? 3 To what extent you have the ability to 3.54 0.65 predict and develop strategies to inhibit the threats against production? 4 Do you agree that "risk-taking 3.33 0.78 is sometimes essential"? 5 To what extent you have the ability to 2.99 0.71 effectively manage financial and production risks? Mean 3.57 0.78 Sources: Research Findings Table 3.17: Frequency Distribution of Viewpoints of Respondents regarding Competency in Communicational Skill. Row Item Mean Standard Deviation 1 To what extent you have the ability to 4.01 0.43 establish relationships with others to solve existing problems and obtain proper results? 2 To what extent you have the ability to 3.97 0.45 help the employees to improve their skills and competencies 3 To what extent you have the ability to 3.96 0.46 establish good and favorable relationships with buyers and vendors? 4 To what extent you have the ability to 3.92 0.40 establish good, precise and honest relationships with others? 5 To what extent you have the ability to 3.83 0.48 create a balance between the skills of employees and their job requirements? 6 To what extent you have the ability to 3.83 0.60 pay attention to the viewpoints of other individuals in regard to management issue of the unit? 7 To what extent you have the ability to 3.80 0.54 define distinctive tasks for each employee? 8 To what extent you have the ability to 3.78 0.55 listen to the viewpoints of employees and realize their suggestions to improve production? 9 To what extent you have the ability to 3.76 0.47 transfer experiences and knowledge to new employees in the broiler farming unit? 10 To what extent you have the ability to 3.67 0.47 avoid the dominative behaviors in relationship with employees? 11 To what extent you have the ability to 3.40 0.85 authorize others to do the associated affairs? Mean 3.81 0.52 Sources: Research Findings Table 3.18: Frequency Distribution of Viewpoints of Respondents regarding Occupational and Production Skills. Row Item Mean Standard Deviation 1 To what extent you have the ability to 4.04 0.62 prepare saloon before arrival of a new shipment of broiler chickens? 2 To what extent you have the ability to 4.03 0.67 manage the seed holders? 3 To what extent you have the ability to 4.02 0.62 manage the water tanks? 4 To what extent you have the ability to 3.98 0.58 manage the physical setting (airconditioning, setting temperature, light and humidity)? 5 To what extent you have the ability to 3.73 0.64 control density in the broiler farming unit? 6 To what extent you have the ability to 3.69 0.72 manage the accession and raising of broiler chickens? 7 To what extent you have the ability to 3.61 0.78 control the hygiene conditions through essential treatment measures? 8 To what extent you are familiar with 3.18 0.69 laws of job and insurance? 9 To what extent you have the ability to 3.15 0.88 ration the broiler farming unit? 10 Mean 3.70 0.69 Sources: Research Findings Table 3.19: Frequency Distribution of Respondents' Viewpoints of Management Characteristics. Row Domain Mean Standard Deviation 1 Communicational Skills 3.81 0.52 2 Competency in Occupational and 3.70 0.69 Production Skill 3 Competency in Risk-taking Skill 3.57 0.78 4 Competency in Rational Decision-making 3.38 1.08 Skill 5 Accounting and Financial Management 3.25 1.18 Skill 6 Competency in Skill of Mobilizing 3.24 0.62 Resources 7 Planning and Targeting Skill 3.24 0.83 8 Competency in Knowledge Skill 3.08 0.80 9 Competency in Marketing Skill 3.04 0.76 Sources: Research Findings Table 3.20: Grouping Directors of Broiler Farming Units based on Competencies in Managerial Skills. Level of Competency Frequency Percentage Cumulative Percentage Low 16 17 17 Moderate 35 38 55 High 24 27 82 Excellent 17 18 100 Source: Research Findings Table 3.21: Pearson Test of Association between Productivity and Manager's Characteristics through Transcendental Function Variable Pearson Decision Correlation Variable Coefficient Education 0.095 0.366 Age -0.040 0.707 Experience -0.118 0.264 Planning and Targeting -0.094 0.374 Accounting and Financial Management 0.088 0.404 Marketing Skill -0.017 0.871 Communicational Skill 0.052 0.621 Rational Decision-making Skill -0.166 0.114 Resource Mobilization Skill -0.012 0.909 Risk-taking Skill 0.005 0.965 Relationship Skills -0.034 0.746 Occupational and Production Skill -0.001 0.991 Training Skill 0.027 0.800 Source: Research Findings
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|Author:||Mosavi, Sayed Nematollah; Varz, Sayed Mehrdad Dast|
|Publication:||Advances in Environmental Biology|
|Date:||Dec 15, 2014|
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