Chapter three

Research Method

1-1- Introduction

Research includes full study of a subject in consistent manner and on the basis of objective methods in order to discover information or governing principles. (Venus et al., 2007)

The aim of all fields of science is to understand the world around us. To obtain knowledge the problems and difficulties of the social world, scientific methods have been changed significantly. Such developments has caused scientific methods to be used to explore different fields of science (Irannezhad Parizi, 2000, p. 15).

Among the features of the scientific study is that it is aimed at finding truth, uses an appropriate research methods, and requires proper choice of research method based on the nature of the subject of research and available facilities. The purpose of research to provide convenient access to research questions (Khaki, 2007, p. 29).

1-2- Research Method

Research method is a systematic method find the answer to question or the solution to a problem. The basis of any scientific knowledge is the method by which such knowledge is obtained, and value of credibility of any science depends on the method used to obtain knowledge in that science. Research method is set of rules, tools and reliable and systematic methods for study of facts, discovery of unknowns and obtaining solutions to problems (Khaki, 2008, p. 30). The objective sought by choice of research method is to adopt a method that allow the most convenient and accurate route to the answers. The research method depends on the purpose and nature of the subject, as well as facilities and resources (Naderi, 2001, p. 5).

Different categorizations of research method have been provided. One of these categorizations is one based on the purpose of the research. The present research is an applied one in terms of objective because the findings of this research can be used in applied issues. Applied research aims to achieve a scientific objective and focuses on securing public welfare and happiness. Applied research is largely dependent on time and place (Sarmand, 2003, p. 79). In terms of data collection, this is a descriptive, survey research of correlation type.

In the broadest categorization, research methods have been divided into documentary (library) and field methods. This research uses both of these methods.

1-2-1- Descriptive research

Descriptive research includes methods that aim to describe the conditions or phenomenon under investigation. Descriptive research can help to obtain knowledge of the existing conditions or assist the decision-making process. Most of behavioral science researches can be considered to be among descriptive (Sarmad et al., 2003, p. 81).

The purpose of this type research is to provide an objective, the real and systematic description of regulatory characteristics of a situation or a subject. In this type of research, researcher tried to tries to conclude concrete results from the situation. The study responded to questions such as how much? who? what is happening? Descriptive research includes data collection, test of hypotheses or answering questions about the current status of the subject of study (the main focus is on the present time), and this type study describes and interprets what is there (Khaki, 2008, p. 68).

1-2-2- Correlation research

In correlation research, the main purpose is to determine whether there is a relationship between two or more quantitative variables (measurable) and if there is such a relation, how significant such relation is. The aim of correlation research is to determine whether or not there is a relationship or relationships, and to use the relations for performing predictions. Correlation researches check a number of variables that are thought to be associated with a primary complex variable (Khaki, 2003, p. 218).

1-2-3- Survey research

Survey research is a method for gathering the data in which certain groups of people will be asked to answer specific questions (which are the same for all people). These responses make up research data. Survey is the most general form of research in human sciences (Baker, 2009, p. 196). This is probably the best available method those social researchers who are interested in collecting main data for describing huge populations incapable of direct observation. By an accurate probabilistic sampling, a group of respondents can be procured, which represent the population at large, and accurate and standardized questionnaires provide data that are similar to those that could be obtained from all respondents (Bebi, 2009, p. 530).

1-3- Steps of implementation of research

1. According the steps of implementation of this research include:

2. Library studies (review of literature)

3. Identifying research variables

4. Surveying managers and personnel of Water and Electricity Authority of Kish Free Trade Zone)

5. Designing final measurement tool

6. Field studies (data collection)

7. Data analysis

8. Conclusion and suggestions

Statistical population

Statistical population refers to all people that share characteristic(s) in certain respects related to the views introduced in the research, and covered by the results. Before the start of the study, researcher must specify the statistical population of the research so that both researcher knows what to do and researcher could conveniently present the people included in the research (Sakaran, 2003, p. 45). Thus, statistical population can be defined as follows:

"The statistical population consists of all those elements and people that share one or more characteristic(s) in a specific geographical place" (Hafeznia, 2008).

"A characteristic is an attribute common between all elements of the statistical population and distinguish(es) the statistical population from other population " (Azar & Momeni, 2006). The statistical population in this study comprised managers and personnel of Water and Electricity Authority of Kish Free Trade Zone.

1-5- Sample and sampling and sample size

Since the statistical population of a large size, and it is not possible for researcher to approach all of them, researcher has to select a number of them as sample and extend the result to all of them, hence sampling.

Sampling may be performed in two ways: all members of population have the chance to be selected, or the non-probabilistic method, in which not all members have an equal chance to be chosen. Thus, when researcher intends to obtaining some knowledge of the statistical population through study of samples from it, researcher must choose the first method, so that sample represents statistical population through similarity between their characteristics.

Thus, sample can be defined as follows:

"Sample refers to a number of people who share characteristics with the population, represent the population, and are homogeneous with population" (Hafeznia, 2008, p. 121).

Given size of the statistical population in this research was 191, sample size was 128 (and 128 questionnaires were collected) as calculated using Cochran’s formula as follows:

where,

n = Sample size

Z α2 = 95% confidence level

N= (191) Size of limited population

σ 2= Variance of population

ε 2= Margin of error

Here, simple randomized sampling was used, because selected sample was well represented the population.

In this method, all member of statistical population have equal chances to be chosen as subject. When this method is used, it is highly likely that distribution pattern of characteristics of concern is the same as that of elements of sample, thus, this method is least biased, and most extendable (Omaskaran, 2002).

1-6- Data collection methods

Data collection is mainly conducted in one of the two following ways:

1-6-1- Library Studies

By this type of study, the secondary data are obtained that has been collected by the researcher before the start of the study. Library method is mainly derives the literature and major focuses of the research from library sources including books in Persian and Latin, Persian and English papers, theses and websites.

1-6-2- Field studies

Alternatively, field method use observation, interviews, questionnaires, etc.; questionnaire is one of the commonly used tools for data collection, which makes uniform evaluation, coding and analysis and interpretation easy and comfortable because the respondent is asked to replace check one of the provided answers instead of writing down his opinion. (Bazargan et al., 1998, p. 166-171).

In this research, documentary (library) method was used for obtaining theoretical framework and literature, and field method (questionnaire) was used to collect information from the subjects.

1-7- Data collection instrument

Data collection is one of the most important stages of the research. Information for the study can be collected in different ways. Various tools such as observation, interviews, questionnaires and documents, etc. are used to obtain data. Each of these instruments has advantages and disadvantages that must be considered when using them in order to ensure that they don’t undermine the credibility, at the same time as increasing other strengths of the tool. The author must choose one or more tool given the nature of the question and hypotheses of the research, and then, having established their validity, he should use them to collect data, which will be then analyzed to judge the truth of hypotheses. The tools must be chosen so that the author can defend his choice and thus give credit to the conclusions of his research (Khaki, 1999, p. 159). In this research, questionnaire was used for data collection from sample. Quantitative scoring and evaluation of specialized questions was conducted using five-point Likert’s scale. The structure of the questionnaire is presented in table 3-1.

Table 3-1 Scale of items included in the questionnaire

Variable 1 2 3 4 5

Leadership functions

Quite disagree

Disagree Undecided Agree Fully agree

Functions paying attention to the customers requirements

Quite disagree

Disagree Undecided Agree Fully agree

Function of human resources

Quite disagree

Disagree Undecided Agree Fully agree

Function of process management

Quite disagree

Disagree Undecided Agree Fully agree

Strategic planning function

Quite disagree

Disagree Undecided Agree Fully agree

Customer Satisfaction

Quite disagree

Disagree Undecided Agree Fully agree

After having the questionnaire approved, reliability and credibility of it must be established.

a) Validity

Valid means true, and validity means truth. A questionnaire is valid when it can measure the characteristic concerned. Validity is important because improper and insufficient measurement can undermine value of any research. Validity depends on accuracy of measurement conducted by researcher (Khaki, 2002, p. 288).

Different methods are used to test validity of questionnaire:

1. content – related validity;

2. criterion – related validity; and

3. construct validity.

To validate this questionnaire, measured variables were extracted from literature, and then they were localized using opinion of experts (Sarokhani, 2002). Since conceptual model here based on which the research’s tool is designed was derived from the literature, thus representing opinion of relevant scholars (Sarmad et al., 2008), its apparent validity was approved. Besides, the content-related validity was approved by the advisor and reader and several other scholars.

b) Reliability

Reliability is a feature of measurement tool. It refers to the extent to which measurement tool gives identical results under identical circumstances. Coefficient of reliability rangers from zero to one (zero denotes unreliability and one full reliability). The minimum required coefficient of reliability is 0.7. Reliability is ability of a measurement tool to keep its stability over time. There different method to determine this, one of which is measuring internal consistency (Konka et al., 2004).

The most important for ordinal scales is Cronbach’s alpha method, which not only gives an indicator for approval of measures obtained from groups and individuals but also determines the extent to which such measures can be extended to other measures (Zohuri, 1999).

Here, Cronbach’s alpha method was used to determine reliability. This method is used to measure internal consistency of measurement tool, which measures different characteristics. To calculate Cronbach’s alpha method, first variance of scores from each the questionnaire’s items, and overall variance must be calculated. Then, Cronbach’s alpha is calculated using the following formula.

rα = JJ−1

(1−∑j=1

n

s j2

S2)

where

J = Number of subset of the questionnaire’s items

Sj2 = Variance of jth item

S2 = Overall variance of questionnaire

Therefore, in order to measure the reliability, the Cronbach's alpha and SPSS 19 software were used. The reliability of variables is presented in Table 3-2.

Table 3-2 The reliability of variables

Research variables Cronbach's alpha statistic

Leadership functions 78/0

Functions paying attention to the customers’ requirements

914/0

Function of human resources 905/0

Function of process management 879/0

Strategic planning function 884/0

Customer Satisfaction 96/0

According to the table above, it can be concluded that the reliability of the questionnaire variables is approved as the alpha in this case is more than 0.7.

1-9- Data analysis method

Having determined his method, and collected required data for test of hypotheses, he must use proper statistical techniques consistent with research methodology, type of variables, etc. to classify and analyze data, and finally test the hypothesis that have directed him up to this stage of the research, and finally find an answer (solution) to the question, the answer which is supposed to be the outcome of the systematic attempts made in the course of the research (Khaki, 2008).

In this study, to analyze data from samples, descriptive statistics and inferential statistics methods were used.

In fact, first the variables have been tested with the help of descriptive statistics.

Statistical methods used in this research include:

1-9-1- Structural equation modeling (SEM)

In human sciences and social sciences researches, data analysis is performed in a uniform process with a predetermined framework. Many data analysis methods have been introduced so far. The structural equation model was introduced in the late 1960s as a tool in the hands of researchers to study the relationships among several variables in a model. The power of this technique to develop theories has led to its widespread use. One of the main reasons why many researchers use the SEM is its ability to test theories in form of equations articulating the relations between variable. Another reason is consideration of measurement error in this method, which allows the researchers to analyze their data with consideration of measurement error (Davari & Rezazadeh, 2013, p. 15).

When this book was being written, structural equation modeling had been introduced in two generations of data analysis. The first generation includes covariance-based methods with their main objective being confirming the model, and requiring large sample (over 200) for doing this task. LISREL, AMOS, EQS, MPLUS software are the most widely used in this generation. Due to weaknesses of this method (such as the need for a large sample size, normal distribution of data, presence of at least three indicators for each structure, etc.), the second generation of SEM methods, which were component-based, was been introduced . These methods, which later were renamed as Partial Least Squares (PLS), use a different process to analyze data, compared with the first generation methods, which has two main phases:

Testing the fit of the measurement models, the structural model and the overall model; and

Testing the relationships between constructs.

PLS has significant advantages compared to the first generation, the most important of which is lack of need for a large sample size and normal distribution of data (Davari & Rezazadeh, 2013, p. 16).

Therefore, given that the sample size in this study was 200 (128) is software that is part of the second generation Smart PLS structural equation modeling is used.

Therefore, given that the sample size in this study was smaller than 200 (128), Smart PLS software that is part of the second generation of structural equation modeling, was used.

In the following, a brief description of the theoretical bases of SEM and PLS method is provided.

1-9-2- Structural equation modeling

This method is called SEM due to two reasons: 1) the relationship between the variables in this method is analyzed using a series of structured equations; and 2) These structured equations are presented in models enabling the researcher to conceptualize the theories of research using the data (Byrne, 2010).

The researchers use this method to test the complex relationships between variables and between latent and manifest variables. This approach tests the structure of internal relations in a set of equations. These equations capture all the relationships between the constructs (dependent and independent latent variables) that are present in the analysis. Constructs are the latent elements that are incapable of study and can be defined using one or more manifest variable (indictor or items) (Davari & Rezazadeh, 2013, p. 20).

1-9-2-1- Steps of modeling in SEM

To analyze the relationships between variables and the interpretation of results, some steps must be taken. These steps are outlined in the following figure: 

Figure 3-1 process modeling in SEM

1- Determining the model: At this stage, first theoretical literature on a subject and its derivatives are investigated and the constructs involved in that particular subject are identified. The relations between these constructs are then identified to develop the research model.

2- Identifying criteria-constructs: After having drawn the model containing the constructs (latent variables) and relations between them, the turn comes to drawing the manifest variables of the model. In fact, at this stage, we will determine how to measure the constructs. To do this, you can read information sources related to constructs or use other methods of data collection, measurement tools (questionnaires) to measure constructs.

3- The estimating model’s relations: At this stage, the relationship containing latent and manifest variables in the model are estimated. It should be noted that the models and relationships common in the SEM consists of two parts: Measurement model (relations), which studies how to explain latent variables by manifest variables (items) and the structural (relations) model that shows how latent variables are related to each other. Estimation of the relations varies depending on the choice of SEM approach and software related to that approach; however, values are defined as significance level in all of them, which are used by the researcher to interpret the results. In the present study, that uses Partial Least Squares method and Smart PLS software, factor loadings and t values are provided by this software, which are used in the interpretation of the model’s relations.

4- Evaluation Model: In order to be able to interpret the results from estimating the model’s relations, the model fit must first be determined. This means that it should be determined whether the model that is based on the literature is consistent with data collected from the

Determining the model

Identifying criteria-constructs

Estimating relations of the

model

Evaluation of the model

Modifying the model

Interpreting the results from the

model

statistical sample. Again, manner of studying the model’s fit varies depending on the choice of SEM approach and respective software.

5- Modify the model: After the results of the model showed fit or non-fit of the model, the model must be modified in different ways. Sometimes, removing one or more items can lead to improved criteria of the model’s fit.

Interpretation of the results from the model: After having modified the model and ensured the adequacy of the model, the researcher is allowed to interpret the results of his research. At this stage, the values obtained from data analysis are reported in simple and understandable terms for communication to the audience (Davari & Rezazadeh, 2013).

Figure3-2 Conceptual model of research

Function of leadership

Q3Q5 Q4 Q1Q2

Function of concentrated customer

Q6

Q7

Q8

Q9

Q10

Q11

Customer satisfaction Comprehensive quality

management

Q16

Q17

Q18

Q12

Q13

Q14

Q15

Function of concentrated manpower

Q26

Q27

Q28

Q25

Q29