E-Benefits Portal Disability Claims Process in Terms of the Dimensions of Technology Acceptance Model - Research Proposal Example

The Department of Veterans Affairs: Examining E-Benefits Portal Disability Claims Process In Terms of the Dimensions of Technology Acceptance Model By [Name of the Writer] [Name of the Institution] [Date] [Subject] TABLE OF CONTENT SECTION 1: RESEARCH PROBLEM, SIGNIFICANCE, QUESTIONS AND TITLE……4 1.1 Research Study…………………………………………………………………………………4 1.2 Purpose of the Research……………………………………………………………………….5 1.3 Significance of the Study……………………………………………………………………...5 1.4 Research Questions……………………………………………………………………………6 1.5 Research Hypotheses………………………………………………………………………….6 1.6 Method Overview……………………………………………………………………………..7 1.7 Dissertation Title……………………………………………………………………………...7 SECTION 2: OVERALL METHODOLOGY AND APPROACH…………………………..8 2.1 Research Design………………………………………………………………………………8 2.2 Approach………………………………………………………………………………………8 2.3 Methodological Approach…………………………………………………………………….8 2.4 Rationale………………………………………………………………………………………9 SECTION 3: FRAMEWORK, CONSTRUCTS, OPERATIONAL DEFINITIONS………..9 3.1 Theoretical Framework………………………………………………………………………..9 3.2 Units of Analysis……………………………………………………………………………...10 3.3 Constructs…………………………………………………………………………………….10 3.4 Variables (Definitions of Constructs as Variables)…………………………………………..13 3.5 Operational Definitions………………………………………………………………………13 3.6 Relationships among the Variables…………………………………………………………..16 3.7 Contributions to the Field…………………………………………………………………….16 SECTION 4: POPULATION AND SAMPLING……………………………………………..17 4.1 The Population………………………………………………………………………………..17 4.2 The Sample Frame and Sample………………………………………………………………17 4.3 Sampling Procedures…………………………………………………………………………17 4.4 Sample Size…………………………………………………………………………………….17 4.5 Rationale……………………………………………………………………………………….18 4.6 Ethical Considerations…………………………………………………………………………18 SECTION 5: HYPOTHESES AND DATA TYPE……………………………………………..18 5.1 Restate Research Questions……………………………………………………………………19 5.2 Quantitative Hypotheses……………………………………………………………………….19 SECTION 6: MEASURES. FIELD TESTS, DATA COLLECTION AND ANALYSIS…….20 6.1 Measures……………………………………………………………………………………….20 6.2 Field Testing…………………………………………………………………………………...20 6.3 Pilot Testing……………………………………………………………………………………20 6.4 Data Collection Procedures…………………………………………………………………….20 6.5 Ethical Considerations………………………………………………………………………….21 6.6 Statistical Analysis……………………………………………………………………………..21 SECTION 7: RESEARCHER’S CRITICAL ANALYSIS OF DESIGN………………………21 7.1 Procedures Diagram…………………………………………………………………………….21 7.2 Assumptions…………………………………………………………………………………….22 7.3 Strengths………………………………………………………………………………………..22 7.4 Limitations………………………………………………………………………………………22 SECTION 8: REFERENCES……………………………………………………………………..23 SECTION 1: RESEARCH PROBLEM, SIGNIFICANCE, QUESTIONS AND TITLE 1.1 Research Study This study investigates and examines the e-Benefits claims process within the Department of Veterans Affairs (DVA). This process will be inspected on the basis of the Technology Acceptance Model (TAM). The department of Veterans Affairs has recently adopted technological tools to establish IT governance, on the organizational level to improve the disability claims process. One of the main objectives of this initiative was to centralize or improve the decision making process within the department as it relates to veterans disability claims. It has been established that several factors can affect the deployment of the e-Benefits claims process within the Department of Veterans Affairs (Kuo, 2013). One of the major factors is the behavioral intentions of the veterans and employee’s, in terms of using the e-Benefit Portal to submit and receive disability claims (Chen et al., 2011). Thereby, this research will identify different factors, which may influence the behavioral intentions of the veterans of the Department of Veterans Affairs. In this regard, the study will use the TAM. The TAM gives an idea on why, how, and at what rate new technologies and innovations spread through cultures. There are certain characteristics of innovation, which are believed to influences acceptance of technological innovations (Lin, 2011). These characteristics are usefulness, ease of use, behavioral intention, and attitude towards use (Venkatesh, 2014). To achieve coherent and reliable results, this research will attempt to establish the extent to which these factors may impact or influence the acceptance or adoption of innovations or the e-Benefit portal adoption behavior of veterans at the department of Veteran Affair. It is significant to note that, this research is intended to build up on TAM by studying its factors, which influence the behavioral intentions of the veterans, in terms of utilizing e-Benefit system in the department. Afterwards, this model will be used to investigate the relationships among the factors of ease of use, usefulness, attitude towards use, and behavioral intention. Additionally, the model will also be used to examine the relationship between the intention of the veterans to use the portal and the usefulness of the e-Benefit systems. Essentially, this research is intended to illustrate the way in which any technological innovation shifts from the stage of invention to its utilization. Particularly, this study has chosen the technology of e-benefit within the Department of Veteran Affair. 1.2 Purpose of the Research The purpose of this paper is to examine the adoption of the e-Benefits portal and disability claims process at the Department of Veterans Affairs in terms of the dimensions of the Technology Acceptance Model. 1.3 Significance of the Study E-benefits portal is one of the greatest initiatives of the Veterans Affairs Department towards the attainment of integrated and state-of-the-art operations. It has been documented in a study of Chen et al (2011) that the e-Benefit portal is a joint project by the Department of Defense and the Department of Veterans Affairs. Cheung and Voge (2013) have termed e-Benefit as a one-stop shop developed for managing and storing the benefits-related information for service members, veterans, wounded warriors, their caretakers, and their families. Precisely, it can be affirmed that e-Benefits is aimed at providing highly responsive and integrated services to the families of service members, retirees, service members, and veterans. It is expected that these services will enable all personnel to have integrated and effective access to the benefits-related resources and information. It is a fact that this innovation has intended to considerably improve the functions of the department, but it is also observed that the development of this innovation has also impacted the behavior of the veterans, in the context of adopting the innovation. This study will help in the assessment and the understanding of different concepts related to TAM literature by assessing the relationships among the TAM variables. In addition, the research will examine the impacts of motivational determinants on the constructs of TAM. Thereby, the study will employ the factors of perceived usefulness, perceived ease of use, attitude towards use, and behavioral intention, as the determinants of BI (behavioral intention to use). It is perceived that this study is quite significant, in terms of testing and developing TAM, which is instrumental to the acceptance and adoption of the e-Benefits claims process acceptance in the department of Veteran Affairs. 1.4 Research Questions To achieve these objectives, the research will answer the following research questions RQ1: Does perceived ease of use have significant impacts on the adoption of the e-benefits claims process by veterans in the Department of Veterans Affairs? RQ2: Does perceived usefulness have significant impacts on the adoption of the e-benefits claims process by veterans in the Department of Veterans Affairs? RQ3: Does attitude towards use have significant impacts on the adoption of adoption of the e-benefits claims process by veterans in the Department of Veterans Affairs? RQ4: Does behavioral intention have significant impacts on the adoption of the e-benefits claims processes by veterans in the Department of Veterans Affairs? 1.5 Research Hypotheses The study will use a theoretical framework, based on the TAM. The research model will perceive that the five innovative and highly integrated factors of perceived ease if use, perceived usefulness, attitude towards use, and behavioral intention affect the intention of veterans to adopt or use the e-Benefits claims portal. Thereby, the study will consider following hypothesis, in order to test the applicability and validity of the model. H1-1: Perceived ease of use has significant impacts on the adoption of the e-benefits claims process by veterans in the Department of Veterans Affairs? H1-2: Perceived usefulness has significant impacts of the adoption of the e-benefits claims process by veterans in the Department of Veterans Affairs H1-3: The attitude towards use an innovation has significant impacts on the adoption of the e-benefits claims process by veterans in the Department of Veterans Affairs H1-4: The behavioral intention has significant impacts on the adoption of the e-benefits claims processes by veterans in the Department of Veterans Affairs 1.6 Method Overview This research study will utilize a mailed and web based survey, to gather data and carry out the quantitative testing of the research model. In addition to this the current research study will implement a non-random technique of sampling (which is, convenience sampling), in order to gather the required sample data. It is significant to bring into the notice that sample data will be gathered from 200 veterans, making disability claims from the Department of Veteran Affairs. It is significant to notice that the veterans will be randomly selected for this research. Afterwards, the collected data will be tested by the help of descriptive statistics and structural equation modeling (SEM). 1.7 Dissertation Title The Department of Veterans Affairs: Examining E-Benefits Portal Disability Claims Process In Terms of the Dimensions of Technology Acceptance Model SECTION 2: OVERALL METHODOLOGY AND APPROACH 2.1 Research Design This research study will use primary quantitative method of research, in order to draw reliable and coherent results, about the given topic of research. In order to collect primary quantitative data, the researcher will carry out web based survey. In addition to this, the researcher will also e-mail the survey questionnaire to the selected participants of the research, in order to get more validate results. One of the major objectives behind the adoption of research approach is that it is cost effective in nature and it helps the researcher to gather first hand information about the given area of research (Savin-Baden & Major, 2013). After the accomplishment of data collection data, the acquired findings will be tested by the help of two statistical tools, including descriptive analysis and SEM (Structural Equation Modeling). The approach of descriptive statistics was adopted, because it helps in understanding the mean value within the data, while presenting the deviations, with respect to the pre-determined values. Besides that, SEM was adopted because; it provides an opportunity to conduct a test amid obtained data and research model. This approach also plays an indispensable role in simultaneously examining and assessing a sequence of the dependence relationships, specifically when there is an indirect and direct impact amid the elements of the model (Savin-Baden & Major, 2013). 2.2 Approach This research study will use quantitative research approach, to accumulate ample amount of data 2.3 Methodological Approach The statistical model, which will be used in this research, includes SEM (structural equation modeling). Structural equation modeling is the general term, which is commonly utilized to demonstrate or illustrate the family of the statistical methods, which are usually developed to examine a theoretical or conceptual model (Lippert & Govindarajulu, 2015). Some of the most prominent methods, which are associated with SEM, include latent growth modeling, path analysis, and confirmatory factor analysis. Specifically, this research will utilize the approach of path analysis, in order to test the hypotheses, which have been developed in the preceding section. 2.4 Rationale One of the major objectives behind the adoption of this research design is to gather first hand information from the veterans using the eBenefit claim process at the Department of Veteran Affairs. It is expected that the developed research design will assist in gathering unbiased information; hence, will help in drawing coherent and credible results. This research design is also found to be cost and time effective in nature, as it save the excessive time and cost, which is usually required for travelling and approaching the research participants. SECTION 3: FRAMEWORK, CONSTRUCTS, OPERATIONAL DEFINITIONS 3.1 Theoretical Framework It is a fact that several research studies have supported an idea that TAM is the most effective model, in terms of explaining the acceptance of the IT/IS (Chiu & Hofer, 2015). On the other hand, it is also found to be one of the greatest questions that whether or not this model can be used to analyze every instance of IT/IS implementation and adoption. It has been established from the analysis of the study, which was conducted by Chen, et al (2011) that TAM can be integrated with several different theoretical perspectives, in order to deal with continual changes, which are occurring in the IT/IS . Some of the theoretical perspectives include DeLone & McLean’s success model or IDT). In this regard, this integration may also help in improving the explanatory power as well as the overall specificity. According to Cheung and Voge (2013), several researchers have claimed that the elements integrated in the TAM, are primarily a combination of the perceived innovation characteristics; thereby, the incorporation of both of these theories may help in acquiring more cohesive model (Stone, 2012). Study of Cho, et al (2012) has also revealed the fact that the integration of both of these theories usually provides higher levels of accuracy as well as the predefined outcomes. This study will implement two most prominent and highly integrated theoretical model of TAM. 3.2 Units of Analysis The unit of analysis, which will be used in this study, includes 200 veterans at the Department of Veteran Affairs. One of the major objectives for the selection of this unit of analysis is to collect more organized and integrated data, in order to draw authentic and reliable results. 3.3 Constructs This research will study the following constructs: Perceived Ease of Use and Technology Adoption: Through reasoned action, users apply their beliefs to influence their attitudes, which further shapes their intentions and behaviors towards adopting and using a given technology or innovation. Cheung and Vogel (2013) thus conceive that TAM’s dimensions of belief, attitude, intention, and behavior greatly influence and predict users’ acceptance of IT. Perceived ease of use refers to the extent to which a group or an individual considers using a particular system as free of strain or effort. The PEU and PU are closely related to the other TAM constructs of attitude towards use and behavioral intention to use. Perceived ease of use is perhaps the most studied and well-established element of the TAM approach to IT adoption. It simply implies that less complex IT systems or innovations are easier to comprehend, easier to apply, and less annoying to use. Consequently, considering other factors constant, the lower the users’ perception on complexity, the more likely they are to adopt an IT innovation. Kent (2012) and Oliveira and Martins (2011) assert that “it is valuable to have software measures that are instinctively straightforward to understand. Likewise, earlier research suggested that software measures should be uncomplicated and basic besides being easy to use, otherwise, it might be rejected by users and eventually get redundant and terminated (Cheung & Vogel, 2013; Cho, Hwang & Lee, 2012). What is more, the effort required to collect the information required from a system should not significantly add to the individual or organizational workload and time. Hence, any model that contains the concept of ease of use or that is consistent with the TAM is advised for studies and developments on technology adoption (Venkatesh, Brown & Hoehle, 2012). Perceived Usefulness and Technology Adoption: Perceived usefulness, almost similar to ease of use, refers to potential users’ beliefs that result in their acceptance of IT applications or systems. Perceived usefulness fundamentally refers to the extent to which an individual or a group believes a given information system would augment their performance or use (Cheung & Vogel, 2013). The ways in which the performance or usability of an information system can be augmented include through the reduction of the time taken to finish a task or the provision of accurate and timely information (Straub, Keil & Brenner, 1997).. When examining the impacts of perceived usefulness on the adoption of IT systems and applications based on the TAM, often, the TAM’s dependent variable is the actual IT application or system usage (Holden & Karsh, 2010). The actual usage in this sense refers to the user-reported measure of time or frequency of using an IT application. The perceived usefulness of an IT application or system relates to the ability of users to apply the IT to improve job performance, effectiveness at job, and timeliness, thoroughness, relevance and accuracy of information (Legris, Ingham, & Collerette, 2003). Attitude towards use and Technology Adoption: Developed from the theory of reasoned action, the technology acceptance model (TAM) focuses on the specific constructs of ease of use and usefulness (Zao et al., 2011). TAM is extensively applied in studies of user adoption of different technologies as a rather reliable and robust model. Besides it two main constructs, researchers have incorporated other constructs to the original model as they quest for increased predictive power of TAM (Zao et al, 2011; Wenger, White & Smith, 2010). Attempts are being made to explain consumer intention to use IT systems and applications using attitude towards acceptance and use. Quite many studies have shown that the intention to use technology is strongly influenced by attitude towards the product, normative beliefs, and self-efficacy among other factors (Lederer et al., 2000). If potential users of a given IT system or application have a negative perception of the system, it is likely that quite a few are likely to embrace it. Similarly, if for one reason or the other potential or target users have a positive perception on an IT application, their desire to use it increases. In other works, users might consider an IT application easy to use, quite useful, affordable and quick to understand and access, translating to increased acceptance (Dishaw & Strong, 1999; Cheung & Vogel, 2013). Behavioral intention and Technology Adoption: Potential users’ behavioral intention (BI) refers to the perceived likelihood that a person or a group will use a certain IT system or application. Often, BI is studied by asking respondents questions related to their intention to undertake a certain activity or to adopt, buy or use a given product. It is worth noting that users’ strength of intention varies. Hence, Likert scale is often recommended for studies seeking to determine the levels of BI among certain groups or individuals (Cheung & Vogel, 2013). For instance, while some respondents may have started using a product and intent to continue using it, others may just be simply planning or intending to use it in the near future. Still, a third group may only have a desire to use a given innovation (Venkatesh, Brown & Hoehle, 2012). In essence, BI is all about the extent to which a potential user is willing to try out a new product and the level, type, and source of motivation to try it out (Cheung & Vogel, 2013).. Theoretically, BI is a rather accurate predictor of behavior, which is the ultimate construct of IT adoption that technological products and producers should influence the most (Schoonenboom, 2014). In any BI framework, the group or individual adoption or acceptance behaviors pursue bigger goals such as better performance, accessibility, understanding and quality information from IT applications and systems (Choi, Kim & Lee, 2010). BI has been established as having a highly predictive validity in relation to behavior. Although the main theories used in communication that focus on BI are the Theory of Reasoned Action (TRA) and the Theory of Planned Behavior (TPB), TAM has found more use in BI studies in recent times, especially in examining user’ adoption of IT applications and systems (Fan & Suh, 2014; Zao et al, 2011). It is worth noting that all these theories have a high regard to the variable of attitude towards innovation or product use and performance (Zao et al, 2011). 3.4 Variables (Definitions of Constructs as Variables) PEU: Perceived ease of use (PEU) can be understood as the degree to which a person perceives that the use of any system is feasible and hassle free (Yun, 2013). It has been analyzed that PEU significantly influences the behavioral intention of the end users, in the context of using any system (Wallace & Sheetz, 2014). PU: Perceived usefulness (PU) can be understood as the extent to which a person perceives that a specific system will improve and enhance her or his performance at job (Saleem, 2013). Attitude towards use: Refers to a user’s evaluation of the attractiveness of applying a given information system or application. Behavioral intention to use: A measure of the probability that a group or a person will accept and use an IT system or application. 3.5 Operational Definitions The above section has incorporated the definitions of different variables, including perceived ease of use, perceived usefulness, behavioural intention to use and attitude towards use. All these variables have imperative significance in this research, as they have notable influence on users’ acceptance or adoption of information technology systems and applications within the Department of Veteran Affairs. Objectives Variable Indicator Scale Instrument Data Analysis Dependent variable Adoption of the e-Benefits Portal and Disability Claims Process at the Department of Veterans Affairs Speed of acceptance Ordinal and Likert Questionnaires Descriptive statistics, structural equation modelling (SEM). User reactions Ordinal and Likert Questionnaires Descriptive statistics, structural equation modelling (SEM). Type of user decision making Ordinal and Likert Questionnaires Descriptive statistics, structural equation modelling (SEM). Independent Variables Nominal and Likert Objective 1: To establish whether Perceived ease of use has significant impacts on the adoption of the e-Benefits claims process at the Department of Veterans Affairs Perceived ease of use Familiarity Likert and nominal Questionnaire Descriptive statistics, structural equation modelling (SEM). consistency Likert and nominal Questionnaire understandable Ordinal and Likert Questionnaire Descriptive statistics, structural equation modeling (SEM). Objective 2: To establish whether perceived has significant impacts on the adoption of the e-Benefits claims process at the Department of Veterans Affairs Perceived usefulness Relevance Ordinal and Likert Questionnaire Descriptive statistics, structural equation modeling (SEM). Accuracy Likert and ordinal Questionnaire Timeliness Ordinal and Likert Questionnaire Descriptive statistics, structural equation modeling (SEM). Objective 3: To establish whether attitudes towards use have significant impacts on the adoption of the e-Benefits claims process at the Department of Veterans Affairs Attitude towards use Information quality Likert and nominal Questionnaire Descriptive statistics, structural equation modeling (SEM). Information availability Likert and nominal Questionnaire Descriptive statistics, structural equation modeling (SEM). Cultural norms Ordinal and Likert Questionnaire Descriptive statistics, structural equation modeling (SEM). Objective 4: To establish if behavioral intention has significant impacts on the adoption of the e-Benefits claims process at the Department of Veterans Affairs Observability intentions to use Ordinal and Likert Questionnaire Descriptive statistics, structural equation modeling (SEM). future plans to use Ordinal and Likert Questionnaire Descriptive statistics, structural equation modeling (SEM). Application trials Ordinal and nominal scale Questionnaire Descriptive statistics, structural equation modeling (SEM). 3.6 Relationships among the Variables Independent Variables Dependent Variable Mediating Variables 3.7 Contributions to the Field This study will commendably contribute in the field of technology acceptance model. Specifically, this research will imperatively contribute in analyzing the acceptance and adoption of the innovation, through the TAM. SECTION 4: POPULATION AND SAMPLING 4.1 The Population In this research, the selection of the chosen sample will be done on the basis of probability sampling approach. One of the major objectives behind the utilization of this approach is to collect the desired data, in an adequate, feasible, and cost effective manner. The target population of the study will be veterans who use the system for disability claims at the Department of Veteran Affairs. 4.2 The Sample Frame and Sample For this research study, the data will be collected from veterans of the Department of the Veteran Affairs. One of the major reasons behind this selection is that the veterans are currently interacting with the e-Benefits claim process at the department; thereby, it will be more feasible for the researcher to acquire the desired data for the research. 4.3 Sampling Procedures In accordance with the study of Chen, et al (2011), the sampling of any research must be performed in an adequate manner, in order to minimize the occurrence of potential risks. Cautious sampling assists the researcher to ascertain the accuracy and reliability of data collection, while controlling the issues, which are associated with money and time. It has been established that the random sampling can be of two types, including non-probability sampling as well as probability sampling. This research will utilize the probability sampling approach. Probability sampling approach can be understood as the technique of data sampling, which uses some specific types of random selection. On the basis of this approach, the research study has selected 200 veterans from the Department of Veteran Affairs. 4.4 Sample Size The sample size, which is considered for this research are the veterans using the e-Benefit claims process at the Veteran Affair’s Department. The selected size of this sample is 200 veterans. 4.5 Rationale The selected sample size as well as the procedure of the sampling are adequately aligned and are consistent with the questions, which have been developed for the present study. It is due to the fact that the large sample size will assist in having extensive data, which will help in examining the required variables, 4.6 Ethical Considerations According to Hodgson, et al (2015), a several ethical issues are encountered by the researcher, while conducting a research. Thereby, it is essential for the researcher to adequately consider different aspects, which are related to the research ethics. Some of the most prominent research ethics, which are needed to be considered by the researcher, includes basic ethics and values, presentation of the collected findings, and credibility of the provided recommendations (Denzin & Lincoln, 2011). According to Hsiao and Yang (2011), the researcher holds the responsibility to adequately mention and report the procedures, methods, results, data, and publication status. Additionally, it is also essential for the researcher not to misinterpret, falsify, or fabricate the collected information (Creswell, 2003). Besides that, it is also important for the researcher to avoid biasness, while selecting the size of the sample. SECTION 5: HYPOTHESES AND DATA TYPE 5.1 Restate Research Questions RQ1: Does perceived ease of use have significant impacts on the adoption of the e-benefits claims process by veterans in the Department of Veterans Affairs? RQ2: Does perceived usefulness have significant impacts on the adoption of the e-benefits claims process by veterans in the Department of Veterans Affairs? RQ3: Does attitude towards use have significant impacts on the adoption of adoption of the e-benefits claims process by veterans in the Department of Veterans Affairs? RQ4: Does behavioral intention have significant impacts on the adoption of the e-benefits claims processes by veterans in the Department of Veterans Affairs? 5.2 Quantitative Hypotheses H1-1: Perceived ease of use has significant impacts on the adoption of the e-benefits claims process by veterans in the Department of Veterans Affairs? H1-2: Perceived usefulness has significant impacts of the adoption of the e-benefits claims process by veterans in the Department of Veterans Affairs H1-3: The attitude towards use an innovation has significant impacts on the adoption of the e-benefits claims process by veterans in the Department of Veterans Affairs H1-4: The behavioral intention has significant impacts on the adoption of the e-benefits claims processes by veterans in the Department of Veterans Affairs 5.3 Types of Data Hypothesis # Dependent Variable Name & Level of Measurement Independent Variable and Level of Measurement (Including moderating and mediating variables) H1-1 Acceptance of e-Benefits by veterans at the Department of Veteran Affairs Perceived Ease of Use H1-2 Acceptance of e-Benefits by veterans at the Department of Veteran Affairs Perceived Usefulness H1-3 Acceptance of e-Benefits by veterans at the Department of Veteran Affairs Attitude towards use H2-4 Acceptance of e-Benefits by veterans at the Department of Veteran Affairs behavioral intention SECTION 6: MEASURES. FIELD TESTS, DATA COLLECTION AND ANALYSIS 6.1 Measures The data will be collected in this research study by the help of model, which has been developed to address the purpose and objectives of the study, as outlined in the conceptual framework. The conceptual framework or model is expected to provide adequate ways of recognizing different variables, including perceived ease of use, perceived usefulness, behavioral intentions and attitude towards use. 6.2 Field Testing No field testing will be conducted, as the survey will be carried out through e-mails and web based approach. 6.3 Pilot Testing Pilot testing is found to be one of the greatest techniques of ascertaining the reliability of the questionnaire (Kiesling, 2012). In order to carry out the pilot testing for the questionnaire, the researcher will distribute the questionnaire in 10 veterans of the same department, so as to ensure that the questionnaire is comprehensible and the questions can be easily answered. 6.4 Data Collection Procedures Data will be collected by conducting a web based and mailed survey with the veterans at the Department of the Veteran Affair. In this regard, the study will adopt non-random technique of sampling. 6.5 Ethical Considerations During the accomplishment of this study, the researcher will consider all ethical concerns and potential issues, which are usually involved in the process of data collection. In this regard, it will be ensured by the researcher to protect the originality of the data. 6.6 Statistical Analysis In order to assess the collected data, the researcher will utilize the approach of descriptive statistics and structural equation modeling (SEM). SECTION 7: RESEARCHER’S CRITICAL ANALYSIS OF DESIGN 7.1 Procedures Diagram 7.2 Assumptions The study will use the presented hypotheses; hence, no assumption has been made for the study. 7.3 Strengths One of the biggest strengths of the research includes the methodology, which is adopted in the research. It is due to the fact that the primary quantitative method of data collection helps in attaining first hand and more cohesive information about the given topic of research, in a cost effective and well timed manner. Moreover, the adopted testing method, i.e., descriptive statistics and SEM are also found to be the greatest strength of the research, as both of these approaches provides highly reliable and credible analysis of the data. 7.4 Limitations The biggest limitation of the research is the sample used. SECTION 8: REFERENCES Cheung, R., and Vogel, D. (2013). Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model for e-learning. 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