Posibilidad de entrada y competencia

Reliability refers to the degree to which the data collection techniques will produce consistent and truthful findings (Saunders, Lewis & Thornhill, 2012). According to Singh (2014) reliability and validity promote transparency in research, and this reduces the chances of

77 researcher biasness. Reliability focuses on establishing whether or not the outcomes of a study are repeatable. It also relates to whether or not the methods that were developed for concepts are unswerving (Bryman & Bell, 2007). Threats that can hinder reliability of study results are: respondent or researcher errors and respondent or researcher biasness (Saunders et al., 2009). Similarly Wilson (2010) stated that reliability issues are closely linked with the researcher having a subjectivity approach to the study which could manipulate the research findings and compromises the truthfulness of the entire study.

In quantitative research, reliability is the constancy, steadiness and repeatability of results. Results are considered reliable if constancy is attained in undistinguishable situations (Twycross & Shields, 2004). In this study, reliability was achieved by conducting a pilot study which involved pre-testing the questions on two Project Managers (from other the EPWP projects), who were not part of this study‟s sample. This pilot study was included in the data analysis chapter as a pilot study. The questions for the interviews were objective with the motive of getting the most accurate and just research findings.

3.16.2. Validity

Leedy & Ormrod (2010:52) stated that “the validity of a research instrument is if the research instrument measures what it is supposed to measure accordingly”. Similarly, McNiff (2014) stated that validity denotes the accurateness of an assessment instrument; for example, whether it measures what it is supposed to measure or not. It is the extent to which the research findings are accurate and truthful. According to Pallant (2011), validity involves getting the research instrument to measure the concepts being studied properly. This is regarded as an essential requirement for research. According to Forza (2002) if a study does not assess reliability and validity, it will be challenging to identify and quantify errors on theoretical relationships being analysed. Validity in research has two categories, content and construct validity (Forza, 2002).

Content validity: Content validity measures the extent to which the measuring tools

adequately cover the objectives of the study (Cooper & Schindler, 2003; Sekaran & Bougie, 2016). To ensure content validity in this study, the researcher conducted a thorough literature review in order to gain an in-depth understanding of the subject matter. Hence, the research instrument was developed based on the information gathered from the literature.

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Construct validity: An instrument has construct validity if it measures the constructs that it is

intended to measure. In other words, the instrument should measure the variable which it is intended to measure (Welman et al., 2007). In this regard, the in-depth interview guide was subjected to pre-testing (pilot study) in order to evaluate whether or not it encompassed most of the variables that are required to address the research objectives. The piloting of the in- depth interview guide is discussed in the following section.

According to Mohajan (2018) there are four ways to warrant validity of a research;

 Time frame for the study needs to be appropriate;

 The methodology chosen has to be tailored for the research, considering the characteristics of the study;

 The sample method chosen for the study has to be the most suitable; and

 The respondents must be truthful in answering questions and should not be pressured in any way (Mohajan, 2018).

Applying reliability and validity to this study has enhanced the quality of the content.

3.16.3. Piloting of the in-depth interview questions

According to Leedy & Ormrod (2010) the data collection instrument needs to be pretested on a few people to test if there are any flaws or if the data collection instrument is well understood by the participants. After pretesting it, it is often necessary to make amendments and to refine the questions. According to Saunders, Lewis, & Thornhill (2003) the pretesting process is completed prior to the data collection process. The pilot study assists in identifying any weaknesses in the research instrument whilst validating it (Sekaran & Bougie, 2016). An in-depth interview guide was created for this study. A pilot test was administered to two individuals who are working for the EPWP, but who were not part of this study sample. This was done to observe the design and viability of the planned research instrument. The outcome of the pilot test was used to analyse the quality of the questions in addressing the research questions (Henn et al., 2009). According to Henn et al., (2009) participants who have participated in the pilot study will be included in the data analysis; this is done to evade testing defects, which could influence the validity of the study.

3.16.4. Trustworthiness

According to Gunawan (2015) using qualitative research with detailed transcripts and audio recordings are some of the ways to ensure thoroughness and trustworthiness. The researcher

79 is employed by the Department of Economic Development, Tourism and Environmental Affairs under the Invasive Alien Species Programme (IASP) which is the organisation this study is investigating. For quality content, it is imperative that the researcher applies utmost trustworthiness. The researcher warranted trustworthiness by ensuring that all information gathered was recorded and analysed without any personal influences. There were no forced or artificial findings. Conformability was applied as the findings were grounded on data presented to the researcher. The researcher took personal notes which recorded the impressions and resolutions taken during the data collection process.

3.16.5. Credibility

Thomas (2010) defined credibility in qualitative research as the degree to which the data analysis is authentic and trustworthy. Credibility is similar to validity in a sense that the findings of the research match reality. It‟s been said that qualitative research has the prospect of representing multiple realities (Thomas, 2010). It is up to the reader to analyse the credibility of the study based on the readers understanding of the study. Some researchers have stated that there is no single reality, instead the reader creates their own reality (Thomas, 2010) According to Thomas & Magilvy (2011), to achieve credibility, the researcher must check for the authenticity of the data. Credibility can be ensured by quoting the participants responses verbatim (Thomas & Magilvy, 2011). Therefore, the researcher analysed the transcribed text after the interview process and assessed the similarity within the information that was collected. Furthermore, the researcher assessed the themes throughout the study that identified the challenges affecting the implementation of Project Management practices in the EPWP.