DEVELOPING IMPLEMENTATION INDICATORS FOR PUBLIC POLICY,
CASE STUDY: TEHRAN AND QOM AGRICULTURAL ORGANIZATIONS
Mohammad Ali Haghighi
Faculty member of Shahid Beheshti University, Iran
E-mail: m-haghighi@sbu.ac.ir
Gholam Ali Tabarsa
Faculty member of Shahid Beheshti University, Iran
E-mail: G_Tabarsa@sbu.ac.ir
Hamid Reza Ghasemi
Tarbiat Modarres University, Iran
E-mail: S_Talaie@sbu.ac.ir
Rouhollah Bagheri
Shahid Beheshti (National) University, Iran
E-mail: R.bagheri@aut.ac.ir
Shahab Talaie Shokri (Corresponding Author)
Hekmat Institute for Policy and Strategic Studies, Iran
E-mail: S_Talaie@sbu.ac.ir
Submission: 01/10/2015
Revision: 02/10/2015
Accept: 14/10/2015
ABSTRACT
Public policies are problem-oriented and solve a public problem. The mere
act of making decisions and policies will not solve problems; rather policies
must also be executed effectively. As executing policies is a crucial step in
policy making, formulating indicators for policy implementation is an absolute
necessity. In this article, we conducted a content analysis of elites’ opinions
to improve implementation of public policies. Therefore, three major factors
were identified including factors involved in policy making, environment of
policy implementation, and organizational structure. Sample data were taken
from agricultural organizations of Tehran and Qom. For data gathering purposes,
library research, interviews and questionnaires were used. To analyze the data,
k-s, Pearson’s correlation coefficient, confirmatory factors analysis and means
comparisons were applied using SPSS and LISREL. Results show that all of
proposed indicators and measures are valid for implementation of public
policies. Regarding the importance of indicators between the two participant
groups, indicators in Tehran groups proved to be more important.
Key words: policy, policy making, policy
implementation, agricultural sector
1.
INTRODUCTION
Policy
making sciences have two basic aspects which are closely related to politics in
their own way. The first aspect related to
political sciences is power study. The second aspect related to public
management includes management techniques and decision making techniques
(MILANI, 2011, 46).
After
codification, ratification and signification of policies, in order to execute
policies, a number of actions are to be taken. A large number of rules,
regulations, programs and plans should be prepared, ratified and signified to
be executed by managing lines of systems and policies. Idealistic policies will
raise organizations’
hope for the future if adherence to principle is taken into their consideration
in all cases by program codification managers.
If
policies are to be left on paper and not implemented, a fruitful future cannot
be assured. The
administration and execution of policies should be carried out in a coordinated and correlative
manner. The indexes required to implement policies seem to have received little
attention. Generally, there are no codified indexes to depict the execution of
policies and each organization applies indexes in accordance to their own goal.
Concerning
the individuality of criteria for selecting indexes, i.e. trustworthiness,
appropriateness, validity, availability, and sensitivity, it is necessary to
apply indexes as a unified language in presenting comparative and operational
reports and, consequently, in execution, assessment, decision making, and
mission and activity management.
One of
the fields in which the aforesaid point is strongly felt is agriculture. The
main reason why agriculture came to mankind’s notice has been to fulfill their
requirements. The most ancient civilization appeared where agricultural
activities were possible geographically and ecologically. As a matter of fact, other economic fields
have appeared gradually according to agricultural requirements (TEHRAN CHAIN,
2007).
Also, in
Imam Khomeini and the Supreme Leader’s viewpoint, agriculture is of utmost
importance to the country’s economy. As for the codification of general policies of the
government, he says: “Concern for rebuilding industrial centers should not
impede attaining agricultural self-sufficiency, rather, the priority of this matter should be
preserved and officials are required to take responsibility for its execution more
than before. Certainly, self-sufficiency in agriculture is the gateway to
freedom and to self-sufficiency in other domains” (IMAM KHOMEINI; JAMARAN,
1988).
Also, the starring role of
agriculture can be easily traced in the Supreme Leader’s economic thinking. In
order to draw public and official attention to agriculture, he has made such
statements as: “pure life and new civilization are in close connection with the
availability of resources and
the prosperity of agriculture (THE SUPREME LEADER, 2004), agriculture
should be of concern to senior administration officials and people (THE SUPREME
LEADER, 2001) investment in agriculture is an important solution for job
creation” (THE SUPREME LEADER, 2009).
Concerning
the aforementioned importance attached to agriculture, it seems that public
policies of this field are afflicted with poor execution. Thus, the present
essay aims to take steps forward through codification of indexes of policy
execution based on agricultural literature and the views of Qom and Tehran
Agricultural Organization
experts.
2.
THEORIES
Since
the appearance of the science of public policy, political studies have been
limited to normative and moral fields of governments and political
institutions. By studying the works of great Western philosophers, scholars developed and
explored topics such as the nature of society, government’s role, government
and citizen rights and liabilities (GHOLIPURE; AHANGAR, 2010, 4).
Public
policies are the free distribution of public interests. The topics of public
policy are the
consequences of public events related to public interests (LIANG ZHIMING, 2011,
2478). Taras believes that public policy studies problems of common or
particular features which,
however, cause public worries and are irritating (TARAS, 2007, 568).
Effective
reinforcement of public policies requires governments’ rational justice and
practical planning (LIANG ZHIMING, 2011, 2478). From Islam’s viewpoint, public
policy is a type
of guidance of a political society based on Islamic principles and values and
is carried out by qualified persons to further the society’s interests (AMID
ZANJANI, 1995, 10).
Generally,
the process of public policy making can be presented through six phases: 1.
identifying public problems, 2. finding alternative solutions (policies), 3.
predicting consequences, 4. selecting a favorable policy, 5. legitimating
policy, and 6. execution & evaluation of policy (ALVANI, 2001, 40).
2.1.
Execution as the gravity center of
policies
In a
standard dictionary, the term “execution” is defined as accomplishing a work
based on a particular plan or
method (GHOLIPURE, 2008, 193). In table 1, a number of theories
concerning execution are presented.
Table 1: Execution theoreticians and the presented theories
|
Theoretician |
Year |
Theory interpretation |
|
Pressman & Wildavsky |
1973 |
Execution is a part of the process of policy making. It is an
interactive process between what
policy maker wants and the procedures to accomplish it. |
|
Bardash |
1977 |
Based on the metaphor,
play field, different kinds of bargaining and negotiation. |
|
Porter |
1981 |
Executive structure as an analysis unit |
|
Mezmanian & Sabtyre |
1980 |
Designing a conceptual framework for execution analysis and effective
execution conditions. |
|
Clista & Elmor |
1980 |
Execution as an institutional
concept and the representation of a four-layer model, the organizational
models of social plans execution, the introduction of two approaches, top-
down and bottom-up execution analysis. |
|
Sabtyre |
1986 |
The presentation of two approaches, top down and bottom up, a synthetic
approach to effective execution analysis. |
|
Hays |
2001 |
A well-thought-out and orderly
collection of some sort of activities |
|
Krut & Wayshow |
2003 |
Making policies subject to practice. |
|
Khalid |
2008 |
The process of changing direction of goals related to a policy |
|
Zehming |
2011 |
Careful, serious, determined practice |
|
Chu hyu lee |
2011 |
Public interests or the majority interests. |
Before the term “execution” was
coined the importance of the execution of public policy was ignored.
Ultimately, Pressman and Wildavsky conducted a research to fill the gap of
execution in their study of public policy. However, as James Slack says,
research on the execution of public policy did not evolve very much from the
mid 1980s to the first decade of twenty first century (SLACK, 2005,3).
Different
definitions of execution have been presented by different researchers.
Krutwaysho, in his definition of public policy execution, quoted Lester &
Sterwart saying that: Simply, execution is making policies subject to practice
(HAFIZ KHALID, 2005, 88).
In
another definition, the execution of public policies is defined as a careful,
serious, determined practice which is in coordination with the decision making
group (LIANG ZHIMING, 2011, 2476).
Also, in
recent years, change in governments’ structure and the formation of democratic
governments culminated
in enhancing public interests in the social relationship between the
government, the private sector, and the society (CHUI-HUA LIU,
2011, 414).
The most
complicated problem of execution is that, having made the decision for activity
execution, it should be done in a way that there would be a rational similarity
with what is decided on and that it would operate well in its framework (ALVANI;
SHARIFZADE, 2009, 107).
Regarding
policy execution, different models and approaches have been presented that we
are going to mention in brief. Lester and Sterwart identified two approaches for execution:
control and ordering approach and economic motives or market approach (KRUTWAYSHO,
2003).
Also, in
the most recognized analytical framework of policy execution analysis,
executive approaches are classified as top-down approaches such as Mazmanian
and Sabatier (1983), and bottom-up approaches such as Elmor’s research, and
synthetic approaches such as Majun and Wildavsky’s research.
In
another classification of policy execution approaches, we can name classic and
neoclassic approaches (PEYKANI, 2009, 50). Samuel R. Staley believes that
effective factors of successful execution of policies are as follow: clarifying
the measurement tools of policies, codifying standards and identical indexes,
avoiding forcing the use of technology or specific approaches for policy
execution, employing encouraging approaches instead of imperative approaches,
terminating ineffective policies, concern for citizens’ interests and
preferences, involving local governments more than before (STALEY, 2006, 246).
Also, Babrow claims that social and cultural factors, achieving cooperative
relationships and active connections between people and groups are significant
in the policy process (BABROW, 2006, 573, 579).
Therefore,
in order to determine the definitions of execution, initially, a definition of
the index is required to determine the indexes of execution. Lexically,
index is defined as high, ridged, elevated, diagram, representative, origin,
base, road guide, something or someone among other people or things,
outstanding. Other definitions of the index are as follow:
·
Index is a tool of representing the quality
of execution or the extent of goal realization
·
Indexes determine the favorability
level and expected points of a specific topic.
·
Indexes are quantitative and qualitative features
employed in assessing inputs, processes, staff,
and consequences.
·
Indexes are tools of assessing the extent of goal
achievement and the accuracy of move in the specified direction (NEJAT; YAVARI,
2009, 130).
This
research, due to its explanatory nature, is an applied research and
researchers, apart from identifying the indexes of public policy execution, are
trying to classify them. Since this research deals with the present situation,
it is a descriptive research and since it studies individuals’ preferences
through questionnaires, it is a survey.
To
identify the indexes of policy execution, content analysis method is used and
experts’ views are applied which are presented in the form of a questionnaire.
To analyze data, Kolmogroph-Smirnoph test is used to determine the normality of
each variable and then Speerman’s correlative test is done on variables.
Furthermore,
for the purpose of the examination and assessment of the effective index in the
execution of the public policies of Tehran and Qom Agricultural Organization,
confirmatory factor analysis, from among factors identified from the literature
and the theories, is applied to determine the meaningfulness and effectiveness
of each index.
The
statistical population of this research includes the experts and managers of
Tehran and Qome Agricultural Organization along with university professors of
policy making. Sampling was used because of the broadness and the large number of individuals. Since the sampling framework was not
clarified, snowball sampling method was used in the research (COOPER, 2003).
Finally, the theoretical framework is presented in table 2.
Table 2:
theoretical framework
|
Indexes |
Variables |
Factors |
Meanings |
|
Clear & real goal–setting (STEELMAN,1996) |
Standards & Goals |
Factors arising from policy making |
Factors affecting the execution of public policies |
|
Distinct standards |
|||
|
Rationality in policy codification (SAGHAFI,1999) |
The Accuracy of policy theories |
||
|
Effectiveness of policies |
|||
|
The relevance of policies to goals |
|||
|
Information flow monitoring by politicians (STEELMAN, 1996) |
Politicians’commitment |
||
|
Execution of play regulations by politicians (STEELMAN, 1996) |
|||
|
Application of appropriate techniques & strategies (STEELMAN, 1996) |
|||
|
A small gap between ratification and execution (PALMBO; CALISTA, 1990) |
|||
|
Dynamisms (YANOW,1990) |
Collective consensus & agreement on the execution of determined
policy |
||
|
Dynamisms (YANOW, 1990) |
|||
|
Defeating crisis and uncertain conditions (STEELMAN,1996) |
Predictable and unpredictable events |
Factors arising from policy making
environment an its execution |
|
|
Work place safety & health |
|||
|
Natural, organizational, social crisis |
|||
|
Financial resources & Facilities (STEELMAN, 1996; ALVANY; GHASEMY,
1998) |
Time &
Resources |
||
|
Finance & manpower (MIRSALIM, 2001) |
|||
|
Executive facilities (MIRSALIM, 2001) |
|||
|
The effectiveness of public thoughts (GHAFURY; KAMALI, 2010) |
Public support |
||
|
National will (public communion) (MIRSALIM,1380) |
|||
|
Principles & beliefs |
Compatibility of policies with social norms & values |
||
|
Correspondence between work requirements, values and behaviors |
|||
|
Correspondence with social customs |
|||
|
Proper informative technology (PORTZ, 2005) |
Proper Technology |
||
|
Computer & Electronic government |
|||
|
Fax & Email |
|||
|
Efficient Executives (administrators) (ALVANI; GHASEMI, 1998) |
Executives |
Factors arising from organizational structure |
|
|
Individual experts with executive
knowledge (HAFEZ KHALID, 2008; YANO, 1990) |
|||
|
Relative freedom in executive principles . |
|||
|
The motive of executive principles
(ACHUFIELD, 2004) |
|||
|
Administrators’ tendencies & preferences (STEELMAN, 1996) |
|||
|
The structures of project teams (YANO, 1990) |
|||
|
Distinct responsibilities (PORTZ, 2005) |
distinctive liabilities& responsibilities of the private sector |
||
|
Responsibilities based on rules & regulations |
|||
|
Distinctive job
description & conditions of job taking |
|||
|
Inter-organizational & executive operation communications (STEELMAN,
1996) |
Communications |
||
|
Network management (PORTZ, 2005) |
|||
|
The use of the media (PORTZ, 2005) |
|||
|
Appropriate financial incentives & penalties (PORTZ, 2005) |
Operation assessment system |
||
|
Operation report (formal & informal) |
Possessing quick, total feedback |
||
|
Gathering opinions from opinion bo |
3.
DATA
ANALYSIS
Before
conducting any statistical tests, it should be made clear whether the data were
gathered from a normal population or not. Having examined the normality of each
data, we do the respective hypothesis test concerning the normality or
abnormality.
3.1.
The statistical test of Kolmogrogh-Smirnogh is presented
in the following way:
·
The data are normal (the data are not from a
normal population):
·
The data are not normal (the data are from a
normal population):
If
the quantity of the meaningful level is small (smaller than error amount
(0.05), hypothesis zero, that is the normality hypothesis, is rejected;
otherwise, zero hypothesis is not rejected (HABIBPOUR; SAFARI, 2009).
Table 3:
Kolmogragh-Smirnogh one-sample test:
|
policy making |
Executive structure |
policy environment |
Research variables |
|
96 |
96 |
Number of samples |
|
|
4.14 |
4.13 |
4.19 |
Average |
|
1.177 |
1.096 |
Kolmogragh-Smirnogh Z test |
|
|
.125 |
.181 |
Mutual meaningfulness |
Based on diagram 3, all
meaningfulness ratios are more than 0.05. So, zero hypothesis (H( which is the
normal distribution of the variables, is not rejected. All the 3 variables of
the research are of normal distribution.
3.2.
Pearson’s correlation coefficients between research
variables
Table 4: Kronbach alpha coefficients and
correlation matrix between hidden variables (sample amount
= 96)
|
Kronbach alpha |
3 |
2 |
1 |
Research variables |
|
0.810 |
|
|
1.00 |
1. Policy environment |
|
0.857 |
|
1.00 |
** 0.755 |
2. Executive structure |
|
0.851 |
1.00 |
**0.600 |
** 0.678 |
3. Policy making |
The meaningfulness level of
correlation coefficient of research variables **p<0.01 *p<0.05
Table
4 shows correlation coefficients matrix between hidden variables. The last
column shows Kronbach alpha coefficients of variables indicating that all the
variables are higher than the accepted minimum amount (0.7) and also representing
the stability and validity of measurement tools.
Also,
Kronbach alpha coefficient of the whole questionnaire is 0.926 showing the
proper stability of the questionnaire. Other numbers are the correlative
coefficients between the variables of the research. All of these coefficients
are meaningful at 99 percent certainty level marked by (**) sign.
The
largest amount of correlative coefficients is between the two variables of
policy environment and executive structure (0.755) showing the powerful, positive,
meaningful connection between the two variables. In order to analyze the inner
structure of the questionnaire and discovering the constituting elements of
each variable, confirmatory factor analysis tools are applied.
The
confirmatory factor analysis of the variables of the research are presented in
the following way. The abbreviations used in the confirmatory factor analysis
are presented in table 5.
Table 5: Titles related to the variables in confirmatory factor
diagram and structural equations
|
Factors arising from policy making Environment |
Environment |
Events |
E |
|
Time |
Ti |
||
|
Support |
S |
||
|
Conflict |
C |
||
|
Technology |
Te |
||
|
Factors arising from
structural organization |
Structure |
Executive |
Ex |
|
Function |
F |
||
|
Communication |
Co |
||
|
Factors arising from
policy making |
Policy |
Standard |
St |
|
Theory |
Th |
||
|
Commitment |
Com |
||
|
Consensus |
Con |
Generally, when working with Lizrel
software, each of the indexes of the model is not a reason for the fitness or
non-fitness of the model by itself, rather these indexes should be interpreted
as a whole. Table 6 presents the most important of these indexes
and shows that the model has a suitable condition for fit.
Table 6: the fit indexes of conceptual model
|
Index |
Proper limit |
|
|
Less than 3 |
|
GFI[1] |
higher than 0.9 |
|
RMSEA[2] |
less than 0.08 |
|
CFI[3] |
higher than 0.9 |
|
AGFI[4] |
higher than 0.9 |
3.3.
Confirmatory factor analysis and measurement equations
related to policy making environment variable
Figure 1:
the confirmatory factor analysis model of policy making environment variable (The
meaningfulness of coefficients)
The fit index obtained from the
confirmatory factor analysis)
K on df 2.08، GFI=0.95 ، AGFI=0.93
، CFI=0.97 ، NFI=0.98 and RMSEA=0.070) shows the
proper fit of confirmatory factor analysis. Concerning the meaningfulness of
the results of confirmatory factor analysis, all factor loads related to
indexes are at 99 percent meaningful certainty level (all factor loads are out
of +2 and -2 limit).
Consequently, all the indexes
described for the variables are of importance and are considered as indexes. By
taking the standardized equations into consideration, it can be understood
which index has the major role in the measurement of each dimension. For
example, concerning the predictable events variable (Event), the index 2 (E2) (workplace
safety & health) with the load factor 0.95 has the major role in its
measurement. Also, index 3 (E3) (natural, organizational, social crisis) with
the load factor 0.28, has the minor role
in measuring the predictable events variable.
Confirmatory factor analysis and
measurement equations related to the policy making variable.
Figure 2: the confirmatory
factor analysis model of policy making variable
(meaningfulness of coefficients)
The fit index obtained from the
confirmatory factor analysis (K on df 2.97 , GFI=0.94, AGFI=0.91, CFI=0.96, NFI=0.9, and RMSEA=0.038)
shows the proper fit of confirmatory factor analysis. Concerning the
meaningfulness of the results of confirmatory factor analysis, all factor loads
related with indexes are at 99 percent meaningful certainty level (all factor
loads are out of +2 and -2 limit).
Consequently, all the indexes described for the variables are of
importance and are considered as indexes.
Confirmatory factor analysis and
measurement equations related to the organizational structure variable.
Figure 3: confirmatory factor analysis model of the
organizational structure variable (Meaningfulness of coefficients)
The fit index obtained from the
confirmatory factor analysis (K on df 2.68, GFI=0.98, AGFI=0.95, CFI=0.97,
NFI=0.96, and RMSEA=0.057) shows the proper fit of confirmatory factor
analysis. Concerning the meaningfulness of the results of confirmatory factor
analysis, all factor loads related to indexes are at 99 percent meaningful
certainty level (all factor loads are out of +2 and -2 limit). Consequently,
all the indexes described for the variables are of importance and are
considered as indexes.
3.4.
The second
confirmatory factor analysis of the research model
Figure 4: confirmatory factor analysis of the policy
making variable (standard)
Figure 5: confirmatory factor analysis model
of the policy making variable
(meaningfulness of coefficients)
The fit index obtained from the
second confirmatory factor analysis (K on free dimension 33/2, GFI=0.99,
AGFI=0.97, CFI=0.98, NFI=0.97, RMSEA=0.067) shows the proper fit of
confirmatory factor analysis. Concerning the meaningfulness of the results of
confirmatory factor analysis, all factor loads related to indexes are at 99
percent meaningful certainty level (all factor loads are out of +2 and -2
limit). Consequently, all the indexes described for the variables are of
importance and are considered as indexes.
In respect of the factor loads
(standard coefficients) obtained from the second confirmatory factor analysis
(Table 7-10), we are to prioritize the indexes and effective factors of policy
making and execution by the Tehran and Qom Agricultural Organization.
Table 7:
Prioritization of factors arising from policy making environment and its
execution
|
(grade)priority |
Factor load |
(factor)index |
|
3 |
**0.35 |
Event |
|
2 |
**0.75 |
Time |
|
5 |
**0.20 |
Support |
|
4 |
**0.30 |
Conflict |
|
1 |
**0.77 |
Technology |
Meaningfulness level of
factor loads
Table 8:
Prioritization of factors arising from policy making
|
(factor)index |
Factor load |
(grade)priority |
|
Standard |
**0.83 |
1 |
|
Theory |
**0.53 |
4 |
|
Commitment |
**0.64 |
2 |
|
Consensus |
**0.60 |
3 |
Meaningfulness level of factor loads
Table 9:
Prioritization of factors arising from organizational structure
|
(factor)index |
Factor load |
(grade)priority |
|
Executive |
**0.89 |
2 |
|
Function |
**0.92 |
1 |
|
Communication |
**0.72 |
3 |
Meaningfulness level of factor loads
Table 10:
Prioritization of effective factors in public policy execution
|
index
(factor) |
Factor load |
priority (grade) |
|
Factors due to
policy making environment |
**0.57 |
2 |
|
Factors due to policy making |
**0.75 |
1 |
|
Factors due to
organizational structure |
**0.35 |
3 |
Meaningfulness level of factor loads
Also, in order to assess the
importance of public policy execution indexes of Tehran and Qom Agricultural
Organization, the averages of the research variables between Tehran and Qom
respondent groups were compared. The results of the comparison are presented
below.
3.5.
Policy making environment variable
·
The averages of variable amounts of policy making
environment are not equal in the two groups.
·
The averages of variable amounts of policy making
environment are equal in the two groups.
·
In order to analyze data, a test of comparison was done
on the average of the whole grades of policy making environment between the two
respondent groups of Tehran (1) and Qom(2)
·
The results of these computations presented through SPSS
software output are given in table 11.
Table 11:
Groups statistics
|
Test variable |
Sample group |
Numbers |
Average |
Criterion deviation |
|
Policy making environment |
Tehran |
63 |
4.297 |
.614 |
|
Qom |
33 |
3.996 |
.499 |
Table 11 describes the statistics in
respect of the two respondent groups in which the number of data and
descriptive statistics of policy making environment variable in respect of the
two groups are presented individually.
Table 12:
the result of the average comparison test of the two populations
|
|
|
Levin test for equality of ariances |
T test for the equality of averages |
|||||
|
F statistics |
Meaningfulness |
T statistics |
meaningfulness |
variance of averages |
95% certainty distance of variances |
|||
|
Low limit |
High limit |
|||||||
|
Policy making environment |
equality of variances Non-equality of variances |
.724 |
.397 |
2.427 2.589 |
.017 .011 |
.301 .301 |
.055 .069 |
.547 .533 |
Table 12 presents the results of the
test and has two parts: the first part deals with the equality test of the
variance of the two populations and the second part presents the equality of
the average of the two populations in both cases as well as the equality and
non-equality of variances.
The statistical hypothesis of the
equality of variance test of the two populations (levin) test is as follows:
The variance of the two populations
(Tehran & Qom) are different.
The variance of the two populations
(Tehran & Qom) are the same.
The meaningfulness related to Levin
test is equal to 0.397 and higher than 5% meaningful level. Thus, the equality
hypothesis of variances is not rejected. Therefore, we examine the data of the
first line for the sake of a conclusion in respect of the average. The average
equality test is meaningful in case of the equality of a variance less than 5%.
As a result, is rejected and the claim of the average
equality of the importance of policy making environment in the two respondent
groups, Tehran (1) & Qom (2), is accepted at 5% error level.
The results presented in table 12
show that both high and low limits are positive; therefore, the average of the
first population (Tehran respondents) is higher than the average of the second
population (Qom respondents). As a result, the average of the importance of
policy making environment in the Tehran Agricultural Organization is higher
than that of the Qom Agricultural Organization.
3.6.
Organizational structure variable
The averages of variable amounts of
organizational structure are not equal in the two groups.
The averages of variable amounts of
organizational structure are equal in the two groups.
In order to analyze data, a test of
comparison was done on the average of the whole grades of organizational
structure between the two respondent groups of Tehran (1) and Qom (2).
The results of these computations
presented through SPSS software output are given in table 13.
Table13:
Groups statistics
|
Test variable |
Sample group |
Numbers |
Average |
Criterion deviation |
|
Organizational structure |
Tehran |
63 |
4.243 |
.714 |
|
Qom |
33 |
3.926 |
.691 |
Table 13 describes the statistics in
respect of the two respondent groups in which the number of data and
descriptive statistics of organizational structure variable in respect of the
two groups are presented individually.
Table14:
the result of the average comparison test of the two populations
|
|
|
Levin test for equality of ariances |
T test for the
equality of averages |
|||||
|
F statistics |
Meaningfulness |
T statistics |
meaningfulness |
variance of
averages |
95% certainty
distance of variances |
|||
|
Low limit |
High limit |
|||||||
|
Organizational
structure |
equality of
variances Non-equality of
variances |
.004 |
.950 |
2.091 2.112 |
0.039 0.038 |
0.317 0.317 |
0.016 0.017 |
0.619 0.617 |
Table 14 presents the results of the
test and consists of two parts: the first part deals with the equality test of
the variance of the two populations and the second part presents the equality
of the average of the two populations in both cases as well as the equality and
non-equality of variances.
The statistical hypothesis of the
equality of variance test of the two populations (Levin) test is as follows:
The variance of the two populations
(Tehran & Qom) are different.
The variance of the two populations
(Tehran & Qom) are the same.
The meaningfulness related to Levin
test is equal to 0.950 and higher than 5% meaningful level; thus, the equality
hypothesis of variance) is not rejected.
Therefore, we examine the data of the first line for the sake of a conclusion
in respect of the average.
The average equality test is
meaningful in case of the equality of a variance less than 5% (, so,
is rejected. Therefore, the claim of the
average equality of the importance of the organizational structure in the two
respondent groups, Tehran (1) & Qom (2) is accepted at 5% error level.
The results presented in table 14
show that both high and low limits are positive, therefore, the average of the
first population (Tehran respondents) is higher than the average of the second
population (Qom respondents). Therefore, the average of the importance of
organizational structure in the Tehran Agricultural Organization is higher than
that of the Qom Agricultural Organization.
3.7.
policy making variable The averages of variable amounts
of policy making are not equal in the two groups.
The averages of variable amounts of
policy making are equal in the two groups.
In order to analyze data, a test of
comparison was done on the average of the whole grades of policy making between
the two respondent groups of Tehran (1) and Qom (2).
The results of these computations
presented through SPSS software output are given in table 15.
Table15:
Group statistics
|
Test variable |
Sample group |
Numbers |
Average |
Criterion deviation |
|
Policy making |
Tehran |
63 |
4.286 |
.647 |
|
Qom |
33 |
3.848 |
.518 |
Table 15 describes the statistics in
respect of the two respondent groups in which the number of data and
descriptive statistics of policy making variable in respect of the two groups
are presented individually.
Table16:
the result of the average comparison test of the two populations
|
|
|
Levin test for equality of ariances |
T test for the
equality of averages |
|||||
|
F statistics |
Meaningfulness |
T statistics |
meaningfulness |
variance of
averages |
95% certainty
distance of variances |
|||
|
Low limit |
High limit |
|||||||
|
Policy making |
equality of variances Non-equality of
variances |
3.136 |
0.080 |
3.354 3.394 |
0.001 0.001 |
0.437 0.434 |
0.178 0.195 |
0.696 0.679 |
Table 16 includes the results of the
test and consists of two parts: the first part deals with the equality test of
the variance of the two populations and the second part presents the equality
of the average of the two populations in both cases as well as the equality and
non-equality of variances.
The statistical hypothesis related
to the equality of variance test of the two populations (Levin test) is as
follows:
The variance of the two populations
(Tehran & Qom) are different.
The variance of the two populations
(Tehran & Qom) are the same.
The meaningfulness related to the
Levin test is equal to 0.950 and higher than 5% meaningful level. Therefore,
the equality hypothesis of variance (H1) is not rejected. Subsequently, we
examine the data of the first line for the sake of a conclusion in respect of
the average.
The average equality test is
meaningful in case of the equality of a variance less than 5% (, so,
is rejected. Therefore, the claim of the
average equality of the importance of
policy making in the two respondent groups, Tehran (1) & Qom (2) is
accepted at 5% error level.
The results presented in table 16
show that both high and low limits are positive, therefore, the average of the
first population (Tehran respondents) is higher than the average of the second
population (Qom respondents). Therefore, the average of the importance of
policy making in the Tehran Agricultural Organization is higher than that of
the Qom Agricultural Organization.
4.
CONCLUSION
For years, agriculture has been a major concern for
religious and political authorities. Agriculture is of such importance that it
has been selected for a case study to develop indexes of public policy
execution. Another reason for this selection is that the need for policy
development and implementation is easy to recognize in the agricultural sector.
Without a criterion for execution, policy execution would be impossible.
So,
three classes of factors have been identified in detail for a better execution
of policies in the present study and were presented as an operational framework
(Table 2). The three classes of effective factors involved in public policy
execution are: factors arising from policy making environment, factors arising
from policy making, and factors arising from organizational structure.
Each of
these factors is divided into evaluative criteria to facilitate execution.
According to the results of the analyses, three steps need to be taken for a
better execution of agricultural policies: first, the environment should be
prepared. Subsequently, policies should be developed in concordance with the
execution environment. Finally, executive structure should be designed in the
best possible manner.
However,
what is new in this study is the comparison of the viewpoints of respondents
from the Tehran and Qom Agricultural Organizations. By comparing the average of
the research variables between the Tehran & Qom respondents, it was found
that the average importance of the effective factors involved in policy
execution in Tehran Agricultural Organization is higher than the average
importance of policy making in Qom Agricultural Organization.
In other
words, Tehran respondents attached greater importance to the indexes and
effective factors of policy execution in the agricultural sector. Another
innovation of the research is that the identified indexes can be generalized to
all other organizations.
5.
SUGGESTIONS
The
criteria presented in the research, due to the extensiveness of the questions
posed, respondents’ boredom and reluctance to answer the questions, and also
the soft questionnaire approach adopted, need further development, extension
and reexamination when applied to other organizations. According to the
results, three classes of suggestions, based on identified indexes, can be
presented in order for a better development of policy execution.
1.
Improving the
policy making environment through the application of information technology and
electronic tools such as computers, effective exploitation of human and
financial resources, predicting and defeating imminent problems, eradicating
policy conflicts by adherence to a common value system and its conformity with religious beliefs, and
finally the existance of a national concensus and a collective will in favor of
the policy execution.
2.
Promoting the quality of policies through adapting
the policies to the present goals and
standards, commitment of politicians to what should be executed, general
consensus and agreement on codified policies, exercising rationality in
codification of policies and concern for their effectiveness.
3.
Lastly, appropriate executive structures should be
designed. It would be possible through the clarification of the
responsibilities of different sectors involved in policy execution, employing
knowledgeable, higly qualified, and committed experts, developing a strong
communication network, providing feedback and making continuous assessments.
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