Research design is a thorough plan for data collection in research project. It must cover the main process in the research; the data collection process, the instrument development process and the sampling process (Bhattacherjee, 2012).
This study meant to found out the main factors that could affect the adoption of M-health for Jordanian people. The behavioral point of view in M-health and technology usage in general has a strong theoretical foundation. Researchers can pick up the relevant models and factors which can be used to predict the behavioral intentions toward new technological systems. In other words one of the positive designs (Field Survey) is chosen; as the research aim is to test the theories not build it (Orlikowski and Baroudi, 1991; Bhattacherjee, 2012).
Field Survey is “a non-experimental design that do not controls for or manipulate independent variables or treatments, but measure these variables and test their effects using statistical methods” (Bhattacherjee, 2012, P.39). Field Survey has been used in this research because of the ability of this design to capture several variables, which allow studying multiple theories. It also suites large number of people, wide geographic areas and examine several kinds of data that cannot be clearly observed such as believes and behaviors (Bhattacherjee, 2012).
Population can be defined “as all people or items with the characteristics that one wishes to study. The unit of analysis may be a person, group, organization, country, object, or any other entity that you wish to draw scientific inferences about” (Bhattacherjee, 2012, P.65). The main aim of this study is to examine the factors that affect the behavioral intentions for Jordanian to adopt M-health apps; that means the current study defined the population as all Jordanian people who use smart phone and consider use apps in the time of the study. Such study has a large population scattered over a wide region. This study cant target the whole population considering the shortage related to financial support, effort and time. It’s more realistic to consider a reasonable sample in specific areas to represent the whole populations.
Sampling Frame is the next step which defined as “an accessible section of the target population from where a sample can be drawn” (Bhattacherjee, 2012, P.66). The researcher needs to make sure that the sample represents the whole population so the study can generalize the result from the sample to the entire population (Bhattacherjee, 2012). For this study; the sample frame consist of all Jordanian people who use smart phone and consider use apps in three cities in Jordan; Amman, Irbid and Aqaba.
The last step is Sampling Technique. According to Blanche et al., (2006) the population, the objective and the parameters of the study guided the sampling process. The current study adopted a non-probability sample; the convenience sampling technique which is defined as “a technique in which a sample is drawn from that part of the population that is close to hand, readily available, or convenient” (Bhattacherjee, 2012,P.69). There were several reasons to choose this specific technique; the population of this study is large and spread throughout a wide geographical area. also there is no way to get a list of all Jordanian people who using smart phone and have interest in using apps. It is an accepted technique considering the cost and the effort needed in the other sampling technique (Alalwan, 2013).
The Sample Size is important because it has a major role in both; the guarantee of reliable and valid results and the generalization of the result (Hair et al., 2006). For this study, a structural equation modeling (SEM) was selected as a statistical technique for testing the research hypotheses. Therefore a sample size of at least 200 responses is highly recommended to be used when the proposed model is complex and comprising of many constructs (Kline, 2005). a sample of 424 responses had been extracted for this study.
4.3 Data Collection Method:
Data collection method is a technique or strategy for acquiring the information from the respondents (Blanche, et al., 2006). The field survey is “a data collection method involving the use of questionnaires or interviews to collect data about people and their preferences, thoughts, and behaviors in a systematic manner” (Bhattacherjee, 2012, P.73).
For this study a structured questionnaire is chosen; in which a seven-point Likert scale was used to measure the main items of the UTAUT2 constructs along with awareness, privacy and technology anxiety, which ranging from strongly agree to strongly disagree scale (Churchill, 1995). The questionnaire was categorized into two key parts. The first part of the questionnaire comprised of questions aimed at collected categorical data concerning respondent’s age, gender, academic level, smart phone use, area and disease (if any) . The second part of the questionnaire consist of questions aimed at collecting categorical data regarding the effect of UTAUT2 along with awareness, privacy and technology anxiety on the behavioral intention to adopt M-health apps. In total, the questionnaire comprised of 41 questions.
The questionnaire questions were derive from previous studies (as shown in Table 4.1); the main constructs of UTAUT2 (PE, EE, FC, HM, PV, and BI) were measured by items adapted from Venkatesh et al. (2012), Awareness items was adapted from Rogers (2003), Privacy items were adapted from Aktar (2013), Hossain (2016) and cocosila(2012), where Technology Anxiety were adapted from Deng (2014) and cocosil (2012).
For this study a draft of the questionnaire (English version and Arabic version) was sent to three experts in business administration department in Jordan university, who were asked to evaluate the questionnaires in the aspects related to items quality, the simplicity of language used and if there are any suggestions, and weak points that should be considered.
475 questionnaires were distributed in Amman, Irbid and Aqaba during the first week of May 2018. However, the returned valid responses were 424 questionnaires.
4.4 Data Analysis:
The structural equation modeling (SEM) has been adopted in this study. SEM can be defined as “a collection of statistical techniques that allows a set of relationships between one or more independent variables, either continuous or discrete, and one or more dependent variables, either continuous or discrete, to be examined”( Tabachnick and Fidell ,2007, P. 676).