This chapter offers a thorough examination of the research design, methodology, approaches, and instruments employed in this research. It presents a detailed account of the procedures undertaken to gather and analyse data, enabling the findings to be comprehended and assessed. It begins with an outline of the research design, encompassing the overarching strategy for the questionnaire. Furthermore, the chapter explores the methodology, the standards for selecting and recruiting participants, the methods used to gather data, and the strategies applied to analyse the collected data. It ultimately concludes with a discussion of the ethical principles and considerations addressed throughout this research.
3.2 Research Design
The research design is a specific framework that outlines how research will be conducted to achieve its objectives and answer the research questions. It is a crucial element of research, establishing the groundwork for all subsequent stages (Abutabenjeh & Jaradat, 2018). It encompasses elements such as data collection and analysis methods, sample size and sampling technique, data-gathering instruments, and the strategies employed for data analysis (Rahi, 2017).
Figure 3.2
This research design
Figure 3.1 presents a detailed framework of the design of this research, which adopted both positivist and interpretive paradigms, integrating a mixed-method approach that combines qualitative and quantitative methodologies. It employed a non-probability purposive sampling technique, focusing on New Zealand back-office personnel as its target population. Primary qualitative and quantitative data was collected via an questionnaire and semi-structured interviews with the participants. Data analysis tools included descriptive and statistical methods for quantitative data, alongside thematic analysis for qualitative data. Additionally, this research design encompassed an ethical considerations checklist and details instruments utilised.
3.3 Research Paradigm
Research paradigms serve as philosophical frameworks that shape the understanding and interpretation of scientific research and knowledge (Samy & Robertson, 2017). They encompass specific assumptions and beliefs about reality and science's role in influencing research design, conduct, and interpretation (Abutabenjeh & Jaradat, 2018). Varied perspectives on objectivity, subjectivity, the researcher-subject relationship, and knowledge generation can result in different
outcomes (Rahi, 2017). Essentially, a research paradigm embodies a researcher's beliefs and methods that form their perception of reality.
In academic studies, considering diverse research philosophies is crucial, as they offer a framework for understanding research problems and guide the selection of research methods and data collection techniques (Rahi, 2017). It is vital to understand ontology (assumptions about reality) and epistemology (assumptions about knowledge) to ascertain one's philosophical stance and its impact on study design (Bonache & Festing, 2020).
Epistemological assumptions can be broadly categorised into positivist and interpretive, while positivist epistemology asserts that knowledge is objective, universal, and verifiable through empirical observation and experimentation (Rahi, 2017). Conversely, interpretive epistemology posits that knowledge is subjective and influenced by individual experiences and perspectives (Bonache & Festing, 2020).
The positivist paradigm involves a systematic and rigorous investigation, starting with a well-defined problem or research question, followed by data collection, analysis, and interpretation to generate knowledge about the phenomenon being researched (Abutabenjeh & Jaradat, 2018).
Positivist researchers strive for objectivity and neutrality, believing it is possible to obtain an unbiased understanding of the world (Park et al., 2020). However, this paradigm may struggle to capture complex social phenomena and human behaviour, as it focuses on quantifiable data and overlooks individuals' subjective experiences (Bonache & Festing, 2020).
In contrast, the interpretive paradigm, often associated with qualitative research, adopts a subjective, empathetic, and reflexive approach (Park et al., 2020). Researchers engage closely with participants, listen to their narratives, and strive to understand their experiences from their perspectives. The goal is to comprehend individuals' personal experiences and the meanings they
ascribe to them (Bonache & Festing, 2020). Nevertheless, interpretive research focuses on meaning-making and individualised analysis rather than statistical methods, which may result in potential bias, limited generalisability, and challenges in verifying results (Abutabenjeh & Jaradat, 2018).
This research employs a mixed-methods approach, incorporating elements of both positivist and interpretive paradigms within a post-positivist lens, suggesting that while we can never attain absolute truth, we can get close to it through rigorous scientific inquiry (Samy &
Robertson, 2017). The employment of the post-positivist paradigm allows for a more nuanced exploration of the research problem, offering a more holistic understanding by integrating the strengths of both quantitative and qualitative research paradigms (Park et al., 2020).
3.4 Research Methodology
The research methodology determines the overall approach and strategies for collecting and analysing data, ultimately impacting the validity and reliability of the research findings (Rahman, 2016). Research approaches can be divided into three main types: quantitative, qualitative, and mixed methods (Mccrudden et al., 2019). Quantitative research focuses on measuring and collecting numerical data, using statistical analysis to make inferences about the population (Onwuegbuzie et al., 2009). In contrast, qualitative research aims to understand individual's experiences, attitudes, and perspectives through qualitative data, such as observations and interviews (Williams, 2007). The third approach, mixed methods, combines elements of quantitative and qualitative research to gain a more comprehensive understanding of the research question (Mccrudden et al., 2019).
In this research, the post-positivism paradigm has been embraced, wherein descriptive statistics were used to analyse quantitative data and qualitative data were utilised to enhance
comprehension and refine the findings. This research employs a mixed-methods approach, incorporating both qualitative and quantitative methodologies to achieve the research its objectives and address the research questions. The mixed-method approach enhances confidence in the findings by counterbalancing the limitations of using either qualitative or quantitative methods exclusively and leveraging the complementary strengths of both approaches (Williams, 2007).
Mixed-methods research offers several advantages, including data triangulation to increase the validity and reliability of findings, consideration of multiple perspectives to enhance understanding of complex phenomena and greater flexibility in data collection and analysis (Mccrudden et al., 2019).
The mixed-methods approach comprised of a combination of various research techniques and involved reviewing open information sources, including scientific articles on telework and CSR. The literature review informed the design of a set of questions for interviews and a questionnaire employed in this research. The questionnaire was administered to New Zealand back-office personnel who had teleworking experience during the COVID-19 pandemic. While the interviews were conducted with a subset of the respondents who completed the survey.
Data analysis for this research involved both quantitative and qualitative techniques. For the quantitative data obtained from the questionnaire, descriptive statistics and correlation analysis methods were used to summarise the data and identify relationships between variables. For the qualitative data gathered from the interviews, a thematic analysis approach was employed. The quantitative data was analysed and then combined with the qualitative data for a thorough understanding of the data, enhancing the validity of the findings. This multi-facet approach aimed to provide a comprehensive understanding of the subject and provide insights that may have been missed using only one research method.
3.5 Data Collections Tools
After careful consideration of the subject matter, the most effective methods for collecting the necessary information were determined to be interviews and a questionnaire from the participants. These methods were specifically chosen for their efficiency and cost-effectiveness, as they required minimal investment of time and financial resources, while still allowing a substantial number of participants to be involved (Bryman, 2016). The researcher believed that the questions included in both the interviews and the questionnaire were unambiguous and free of bias. It was also important that the answer options provided were mutually exclusive and comprehensive. To guarantee the efficacy and accuracy of these research tools, both the interview and questionnaire underwent a thorough review process by the research supervisor, and co- supervisor, and received approval from the Ethical Committee of Otago Polytechnic Auckland International Campus (OPAIC). This process ensured that these research instruments adhered to ethical standards and guidelines, addressing any potential issues or gaps prior to their use with the participants.
The number of interviews conducted was ten, with each participant from the pool of survey respondents, offering a rich, in-depth perspective on the research questions. The Qualtrics eXperience Management (XM) platform was selected for gathering quantitative data due to its reputation as a highly professional and advanced tool for data collection. This platform features a user-friendly interface, making it easy to design and customise questionnaires, as well as advanced analytics and data visualisation tools that simplify the analysis and interpretation of collected data (Qualtrics, n.d.). In addition, Qualtrics XM takes the privacy and security of participant data very seriously and provides robust security measures, including secure data storage, backup and recovery options (Qualtrics, n.d.).
A questionnaire is a widely used research tool that allows the researcher to gather information from participants regarding their attitudes, experiences, or opinions (Taherdoost, 2019). Various types of questions can be included in a questionnaire, including closed-ended questions, such as multiple-choice or Likert scale questions, and open-ended questions that allow for elaboration and expression in the participants' own words (Jablokow et al., 2019). The questionnaire used in this research was designed with the guidance of existing literature, focusing on perceived benefits, challenges, and attitudes towards telework. The questionnaire used in this research consisted of a total of 33 questions. Of these 33 questions, 12 were multiple-choice, and 21 were on a five-point Likert scale. The five-point Likert scale provided a standardised and easy- to-use method for measuring participants' opinions, attitudes, or beliefs on various topics (Jablokow et al., 2019). At the same time, multiple-choice questions offer a more straightforward way of gathering data on specific topics. The combination of these two question types in the questionnaire allowed the researcher to gather a well-rounded understanding of the participants' perspectives and opinions (Taherdoost, 2019).
The interviews were accurately planned with the objective of obtaining insightful information about the research questions from the participants. The interviews consisted of nine open-ended questions, each question mapping to themes identified from the literature review.
These interviews were designed in a semi-structured format, providing the researcher with a flexible approach to the questioning process. While a pre-determined set of questions was prepared, the researcher was also able to probe further based on the participants' responses. The semi-structured nature of the interviews facilitated the collection of rich qualitative data by exploring the participants' experiences, perspectives, and opinions regarding the research topic (Husband, 2020). The interview consisted of nine open-ended questions, which allowed the
participants to elaborate on their thoughts and experiences, thereby granting the researcher a deeper understanding of the research topic from the perspective of the participants. The questions explore the participant's timeline of teleworking and their attitudes towards telework before, during, and after the COVID-19 pandemic. The questions also research the perceived benefits and challenges of telework. Additionally, the questions probed the experiences and opinions of the participants regarding telework and its impact on various aspects of their work and personal lives, including job satisfaction, work-life balance, and their views on telework as a benefit offered by organisations.
By combining both quantitative and qualitative data collection methods, this research aims to provide a comprehensive understanding of the subject matter, addressing the research questions from multiple perspectives and offering a more nuanced analysis (Jablokow et al., 2019). The final versions of the questions for the interview and the questionnaire can be found in Appendices 1 and 2, respectively.
3.6 Research Participants
The target population for this research comprised of New Zealand back-office personnel who utilised telework to perform tasks and interact with colleagues and clients during the COVID- 19 pandemic. The research was designed to be inclusive and not biased towards any specific demographic characteristics such as age group, ethnicity, or gender. However, the inclusion criteria for participants included being at least 18 years old and having worked in their current position during periods of COVID-19 lockdowns in New Zealand. To specify, nationwide level four lockdowns were generally implemented in August and November 2020 in response to local outbreaks of the COVID-19 pandemic (Cumming, 2022). However, some regions, such as Auckland, experienced additional lockdowns in other periods according to the history of the
COVID-19 alert system (Mayer & Boston, 2022). Another valuable but not mandatory criterion was that participants have continued to telework, either full-time or on a hybrid telework schedule combining remote and office-based work. This criterion reflects the trend towards increased flexibility and telework that has emerged in many industries as a result of the COVID-19 pandemic (Brunelle & Fortin, 2021).
This research applied a targeted sampling strategy, as the required data would be more accurate from participants who meet the specific criteria represented in a sample rather than selecting a sample randomly from a larger population (Thiblin et al., 2022). Stratton (2021) claims that using a targeted sampling strategy increases accuracy by selecting a sample that resents a subgroup of specific interest because the study findings are more likely to reflect the characteristics of that subgroup correctly. Also, targeted sampling implies a better generalisation by reducing bias and focusing on the particular subgroup's interest, which makes the research more meaningful and relevant to that group (Stratton, 2021).
Nevertheless, the anonymous nature of the questionnaire, which was promoted via social media, presented some challenges in thoroughly verifying the professional background of all participants. Utilising social media as a platform for conducting questionnaires has the advantage of reaching a wider audience and collecting a larger number of responses, but it may also lead to less control over the participants' characteristics (Ali et al., 2020). Anonymity in this research was essential, as it encourages participants to provide open and honest responses without fear of any repercussions or judgement (Roberts & Allen, 2015). The benefits of anonymity outweighed the potential limitations in verifying the professional background of participants. To mitigate these limitations, the researcher included screening questions at the beginning of the questionnaire.
These screening questions required participants to confirm their job roles and teleworking
experience, ensuring that only participants who met the research criteria proceeded with the questionnaire. Therefore, this research's targeted sampling strategy, combined with anonymity and screening questions, aimed to accurately represent the attitudes towards telework among the participants while ensuring a secure and supportive environment for participants to share their experiences.
3.7 Recruitment and Data Collection
Following the identification of the criteria for the participants and the finalisation of the sets of questions for the questionnaire and interviews, the researcher composed the recruitment message text, which served as the foundation for the invitation to participate in this research. The recruitment message text included details regarding the research, such as its purpose, the eligibility criteria for potential participants, and the URL link to the questionnaire.
In order to recruit a sample that met the specified criteria for the research, the researcher employed a combination of personal networking strategies. The primary method employed was the distribution of an invitation post to various New Zealand community groups on Facebook, which was complemented by sending personalised messages to acquaintances via various distribution channels. These personalised messages offered the researcher the opportunity to engage with potential participants directly and to provide them with additional information regarding this research, including the steps involved in the participation process. This approach was advantageous as it allowed the researcher to reach potential participants who met the desired criteria and with whom the researcher already had established relationships, thereby increasing the likelihood of their participation (Thiblin et al., 2022). Additionally, the researcher utilised personal networks by seeking the assistance of people who were employed in New Zealand back-office positions. These individuals were asked to share the invitation with their colleagues within their
respective organisations. This approach allowed the researcher to engage with employees from several IT and accounting firms located in different cities in New Zealand.
If a potential participant consented to undertake the questionnaire, they clicked on the URL address in the recruitment message text and were redirected to the questionnaire. This was hosted on the Qualtrics XM platform and was structured in a series of blocks, each containing a set of questions that needed to be completed to proceed to the next section. Using a platform like Qualtrics XM ensured the secure collection and storage of data and provided the researcher with tools to manage and analyse the collected data (Qualtrics, n.d.). By dividing the questionnaire into blocks, the researcher aimed to reduce the potential for participant fatigue and enhance the overall questionnaire experience (Roberts & Allen, 2015). The initial page of the questionnaire consisted of a message for the participants that detailed the purpose of this research and the eligibility criteria for participation and provided links to both the consent form and the participant information sheet.
This was crucial in ensuring that participants fully understood the nature of this research and the expectations of those who chose to participate. The inclusion of the consent form and participant information sheet also provided participants with additional information regarding their rights as research participants and the steps involved in the participation process. By presenting this information upfront, the researcher aimed to increase transparency, build trust with the participants, and comply with the research ethics regulations.
The final page of the questionnaire expressed gratitude to the participants their time and willingness to engage in this research. This also, included information advising that the researcher was looking for participants for the interview on the same topic, estimated to take between 15-25 minutes. If the participant agreed to take part in the interview, they were asked to email the researcher, with the heading "Interview participation". This approach was adopted due to the
anonymous nature of the questionnaire, which required that participants' personal information and contact details would not be collected. By asking participants to email the researcher directly, this enabled the collection of the necessary information for scheduling an interview and ensuring that the questionnaire responses remained anonymous. In addition, participants were informed that they could request a copy of the completed research through the same email address.
The data collection process lasted for approximately two months, January and February 2023. During this time, the researcher was able to gather a total of 125 responses to the questionnaire. Out of these responses, 101 were fully completed, while the participants left the rest with varying levels of completion. Also, the researcher received 10 emails from participants expressing their willingness to participate in interviews which were scheduled and conducted shortly after receiving their consent. The researcher believed that the sample size for the interviews was adequate for reaching saturation, as qualitative research often achieves saturation with a relatively small sample size (Hennink & Kaiser, 2022). The interviews were conducted online via Microsoft (MS) Teams and Zoom platforms, selected for their ease of use and accessibility (Husband, 2020). These platforms facilitated the recording, saving, and transcription of the data, ensuring its accuracy and suitability for analysis (Husband, 2020). Moreover, the use of these online platforms enabled the researcher to conduct interviews with participants from different regions of New Zealand, including the South island, thereby increasing the geographical diversity of the sample.
3.8 Data Analysis
The process of data analysis involved multiple stages, including gathering data, cleaning, transforming, creating models, and interpreting the results (Schoonenboom & Johnson, 2021). A common method for approaching data analysis is using a linear, structured approach that helps to