The Role of Technology in Inequality - Research Proposal Example

Research Proposal Name Course Tutor’s Name Date The Role of Technology in Inequality Introduction This research proposal will investigate whether technology plays any role in the inequality experienced in the world today. Researchers like Acemoglu and Autor (2011) indicate that inequalities have increased even among developed countries as new technology development becomes more embraced by the society. In this research proposal, technology will be used in reference to computers, communication technology and computer-assisted robotics. Inequality on the other hand will be used in reference to the differences in earnings registered by different sections of a country’s (and sometime world’s) population. Some authors (e.g. Acemoglu & Autor, 2011) have noted that technology development favours skilled workers and places the unskilled workers at a disadvantage hence contributing to more inequalities. This research proposal will predominantly indicate the research methods and processes that will be used in the main research. Literature Review Different research methods have been used to research how technology has impacted on inequalities. Wheeler, C. H. (2005). Evidence on wage inequality, worker education and technology. St. Louis Review 87(3), 375-393. Wheeler (2005) obtained data from a sample of 2, 693,370 workers across 20 years in 20 industries and computed their union membership rates and educational attainment. He then used inequality measures, which are based on real hourly wages, and restricted his sample to white males who worked for at least 30 hours a week. Further, he confined his sample to people who earned $2.60 to $150 per hour. In the end, Wheeler ended up with a sample of 1,156, 715, which he used in the inequality calculations. The sample was drawn from 230 industries in the private sector. Computer-usage is the main technology determinant that Wheeler (2005) used in the research, and respondents were asked whether they used computers at work, and for what purpose. Seemingly, Wheeler (2005) obtained some convincing results from the research. From a methodology perspective however, it is clear that Wheeler (2005) did not find it important to introduce the methodology approach that he used. Although it is clear that he adopted a quantitative approach, he does not say so in the research. He also does not indicate how the research approach fits into his research design. Wheeler (2005) however does well in describing the methods of data collection. He even indicates how the data was originally gathered. He also provides the sampling rationale and selection procedures. He for example indicates that by choosing white male respondents, he avoided any racial or gender variables that would have complicated the research. Notably however, Wheeler (2005) does not discuss the limitation of the sampling procedures he used. For instance, he does not indicate whether the white male sample has any implications on the findings. Overall, Wheeler’s (2005) methodology is arguably not thorough since it omits some details that would have helped a reader understand the procedures and processes that the researcher used. To Wheeler’s (2005) credit however, the failure to define whether the research was quantitative or qualitative was perhaps based on the assumption that readers have some basic understanding about research, implying that there was no need to go into great detail about the research approach. From Wheeler (2005), I have learnt that it is important to indicate any assumptions that a researcher may take. I have also learnt that a good methodology section provides specific research details thus making it possible for future researchers to replicate the research if they so wish. Kvasny, L. (2006). Cultural (re)production of digital inequality in a US community technology initiative. Information, Communication & Society 9(2), 160-181. Kvasny (2006) is another researcher who investigated how information communication technologies affect social inequalities. The research by Kvasny (2006) is an ethnographic study, which was done in eight months involving respondents drawn from a low-income neighbourhood in the US. The researcher used Bourdieu’s theory in data collection and analysis. The data collection techniques included participant observation, informal interviews and textual analysis. Kvasny (2006) also obtained historical and background data on a CPC initiative from published documents such as planning reports, proposals to the city council, and newspaper articles. The researcher also interviewed staff and also got into informal conversations with classroom facilitators. The informal conversations were a natural approach where the researcher interacted with respondents and asked them questions about their experiences before and after taking up technological courses. The researcher specifically wanted to find out their honest opinion about the difference that technology was making in their lives. Focused data collection took the form of participant observation and took 14 weeks of the 8 months in which the research was conducted. The researcher observed 15 respondents and one classroom facilitator as they took a 7-week course. Through the prolonged observation, Kvasny (2006) indicates that he was able to build report with the sampled informants hence making them more comfortable in providing him key insights into their lives, careers and any perceived inequalities. He however acknowledges that studying the same group over a long time restricted the variety of social types that he sampled, hence prohibiting cross-case analysis. When conducting interviews, Kvasny (2006) did not record the responses; rather, he chose to use short interviews, which he says, facilitated accurate recall of the discussions he had with respondents. Notably, the foregoing might have jeopardised the accuracy of the results, because there was no guarantee that Kvasny (2006) did indeed recall the responses accurately. However, the absence of recorders made the interaction between the researcher and his respondent seem natural; terminating the interview for example involved thanking the respondents and not switching off the recorder or shuffling papers as would have been the case if the researcher was recording or taking interview notes respectively. The observation method that Kvasny (2006) used has advantages in that it provided direct access to the inequality and technology phenomenon that was under consideration. It also provided diversity in that there are times when the researcher’s observation was unstructured and informal, while in others, it was structured and formal. The observation also complemented the triangulation approach that Kvasny (2006) adopted. Triangulation is the process of obtaining data through more than one data collection technique. In this case, Kvasny (2006) used interviews, observations and textual analysis. One of the drawbacks of using observation as a data collection technique is that the method is resource-intensive and time consuming. There is also a possibility of observer bias, which if present, could undermine the validity of the research findings. The possibility of observer effect, where the respondents behave in a specific way according to what they perceive the researcher is looking for, is also present. As Kvasny (2006) indicates however, he tried minimising the observer effect by prolonging the interaction period he had with the respondents in an attempt to get them to behave as naturally as possible. As Hoyle, Harris and Judd (2002) note, interviews require the researcher to assume the “dual goals of motivating the respondent to give full and precise replies while avoiding biases stemming from social desirability, conformity, or other constructs of disinterest”(p. 144). When applied in the research by Kvasny (2006), one cannot ascertain whether the foregoing happened. In other words, there is no way that a reader can confirm if indeed the findings were free of biases. On its part, text analysis provided a good source of historical and background data, but could also act as a source of inaccurate information or biases. Kvasny (2006) does not indicate how he confirmed the reliability of the documents (especially newspaper articles) that he used. From Kvasny (2006), I have learnt that using observational research requires the researcher to be careful against personal biases. I have also learnt that it is important to explain the details of research methods used in order to enhance the believability of results. Crawford, N. & McKenzie, L. (2011). E-learning in context: an assessment of student inequalities in a university outreach program. Australian Journal of Educational Technology 27(3), 531-545. In an investigation about technology use and inequalities in learning, Crawford and McKenzie (2011) start by noting that not all young learners (students) are tech-savvy. The researchers adopt a mixed methodology that includes student surveys and group interviews. According to Crawford and McKenzie (2011), the combined methodology enabled them to “identify the challenges, difficulties and benefits that the students experienced when using online technologies” (p. 534). Fifty-two student surveys were distributed, collected and analysed. The surveys had 23 questions, which were a mixture of open-ended and close-ended questions. The interview was used on tutors and going by the research report by Crawford and McKenzie (2011), the interview had three questions only. Notably, the researchers do not indicate how many tutors participated in the interviews. This seemingly lack of precision continues into the analysis section where data gathered from tutors is generalised. The researchers also use some of their observations which they obtained while acting as tutors during the research period. Overall, it would appear that Crawford and McKenzie (2011) have done well in introducing the methodology approach used in their research. Reading through their research however, one gets the impression that they used observations as yet another research method yet they had not included it in the methodology section. They also fail to indicate how the two methods they chose to use fit into their research design. Also, their methodology section does not explain how they analysed the results. Crawford and McKenzie (2011) further fail to provide a rationale for the research methods used in the methodology section; instead, the rationale is offered in the analysis section, where the two authors state that the two approaches – i.e. surveys and interviews – were well suited for use because the researchers were limited by time and resources. In my view, the results obtained by Crawford and McKenzie (2011) can be called to question especially because of too much generalisation that the authors have used in regard to the interviews conducted with tutors. Additionally, the two authors do not indicate the approaches they used to ensure the results’ reliability and validity. They also fail to state any assumptions they might have had, and they do not describe the limitations of their methodology. From Crawford and McKenzie’s (2011) research, I have learnt that researchers need to document their research methods in detail in order to enhance the believability of the results. Additionally, and as indicated by Elseiver (2008), a good methodology “must provide sufficient information so that a knowledgeable reader can reproduce the experiment” (p. 31). Clearly, Crawford and McKenzie’s (2011) research cannot be reproduced by other researchers because it does not provide the specific number of respondents who participated in the interviews. Moreno-Galbis, E. & Wolff, F-C. (2008). Evidence on new technologies and wage inequality in France. Applied Economics, 1-30. In a research meant to establish the link between new technologies – i.e. computers and computer technologies – and wage inequalities, Moreno-Gablis and Wolff (2008) have obtained data from a French labour force survey. In the methodology used for the research, the authors distinguish between ICT-knowledgeable workers and workers who do not possess ICT knowledge. The researchers then focus on the wage differential between the two groups in a bid to determine whether technology use is rewarded. The research is based on a sample of 8,794 people drawn from 65,000 households. The sampling criterion was set at a minimum age of 15 years. Each individual was interviewed three times in the course of the research, and a third of the research sample was renewed annually. To prevent preference issues, Moreno-Gablis and Wolff (2008) indicate that they excluded part-time workers from their sample. The researchers admit that their methodology had shortcomings that made it hard to capture the productivity spillovers that people who are not knowledgeable in ICT have by working with ICT-knowledgeable people. Moreno-Gablis and Wolff (2008) have defined the population (people over 15 years of age) and the sampling methods used. They have also described the research procedures and the research time frame. The analysis plan is also well articulated as well as the approaches that the researchers used to uphold reliability and validity of the research findings. Moreno-Gablis and Wolff (2008) have also described the limitations of their methodology. Notably however, the researchers have not stated if there were any assumptions in the research. From Moreno-Gablis and Wolff’s (2008) methodological section, I have learnt that it is also important to indicate any assumptions that a researcher may have in the methodology section especially if the guidelines provided by Elsevier (2008) are anything to go by. I have also learnt the importance of concise and clear writing in order to avoid irrelevant details in the methodology section. In their report, Moreno-Gablis and Wolff (2008) only provide information that would help a reader understand why the researchers chose the data collection methods they used, the method of data gathering, and the method of data analysis. Harrison, R. (2008). Skill-biased technology adoption: Firm-level evidence from Brazil and India. IFS Working Papers, 08(03), 1-69. In a research that sought to establish how technology adoption differs among skill sets, Harrison (2008) used face-to-face interviews in both Brazil and India. The interviews lasted from 2001 to 2004, during which time interviewers got access to 500 firms in three industries in each country. After applying different sampling criteria, which he has described in the report, Harrison (2008) ended up with 449 firms in India and 353 firms in Brazil. Collectively therefore, the results were based on 802 firms drawn from three industries. Harrison (2008) indicates that stratification was done by employment size, state and industry. In India, the sampling covered nine states, while in Brazil, thirteen states were sampled. Reviewing Harrison’s (2008) methodology section, it appears that the researcher did well in defining the population in both India and Brazil, and defining the sampling methods used in both countries. The researcher also describes his research instruments as questionnaires, which were followed up with repeat visits and/or phone calls when the need to follow up arose. Harrison (2008) also describes the procedures used in the research as well as the time frame which he indicates to be between 2001 and 2004. His analysis plan is well described, but he does not provide details as to how he ensured that the research findings were reliable. He also fails to state any assumptions he might have used in the research. Harrison (2008) does not indicate the limitations of the chosen methodology. From Harrison (2008), I learn the importance of describing the instrumentation and providing as much details about the research as possible in the methodology section. Notably, if another researcher wanted to replicate Harrison’s (2008) study, he would easily do so. The only things he/she would have to find out are the limitation of the study, which Harrison (2008) has not indicated. The Proposed Study: The Role of Technology in Inequality Aims of the Proposed Study The proposed study has the following aims: To establish if indeed technology has contributed to rising inequality in the world To establish if technologically empowered people always earn more than people who have no technology skills working in similar situations The study will work with the following hypothesis: H1: Technology has contributed to rising inequality in multiple forums starting with the education sector, and later in the employment sector. H2: Technology-skilled people do not always earn more than their unskilled counterparts working in similar job roles, but a majority of them do Research Paradigm A paradigm is defined a broad perspective of view of an issue (Saunders, Lewis and Thornhill (2007). On his part, Wheeler (2005) defines paradigms as “patterns of beliefs and practices that regulate inquiry within a discipline by providing lenses, frames and processes through which investigation is accomplished” (p. 378). With the foregoing in mind, this research will adopt an interpretive paradigm, which according to Saunders, Lewis and Thornhill (2007), indicates that there are multiple realities and many truths. Further, the interpretive paradigm appears to be well suited for the proposed research because as Saunders et al. (2007) note, it provides an opportunity for researchers to consider the practices, concerns, and opinions of respondents. To accommodate the investigative qualities of the proposed research, a qualitative methodology will be adopted. Saunders et al. (2007) define qualitative research as a process of obtaining research data, examining, analysing and interpreting observations without involving mathematical models. The primary research will include observations and interviews, while the secondary research will include a literature review of sources from the Internet, books, journals and case studies. Research Methods The main research method for the proposed study will be semi-structured interviews. The interviews will be administered by the researcher to sampled employees and IT managers in order to determine the employees’ experiences and get their performance ratings from the IT managers. The target sample for the proposed research is approximately 90 employees divided into six groups of 15 people each. Three groups will have technology-savvy people while the remainder will comprise people who have no technology skills. The researcher will also involve 15 IT Managers, who will be individually interviewed. The sampled respondents will be representatives of the larger tech-knowledgeable population, people who are yet to acquire technology skills, and the managers who have to handle both skills categories at the workplace. All interviews will be audio taped in order to enhance effective analysis thereafter. Observations will also be used, and together, the interviews and observations will form some kind of a mixed research approach, which according to Saunders et al. (2005), is ideal for testing, proving and verifying hypothesis. In line with grounded theory, the analysis of findings obtained from the proposed research will be done as data collection progresses. The sampling of respondents will be random within departments where some workers use different technologies while others do not. An age criteria of 20 years to 45 years will however be applied. At high ages (e.g. 35-45 years) it would be expected that people with work experience would still be earning more that the technology-savvy workers in the early 20s and 30s. To determine the respondents’ earnings, each interview sheet will have a leading question regarding the same. The researcher will however need to assure respondents that their answers will be confidential, and that no personal information will be released to third parties. Data Collection Tools Interviews will form the primary data collection tool for the proposed study. To maintain consistency, the researcher will develop two sets of interview questions – one set will be used with employees, and the second with managers. The employees will be subdivided further into groups of the tech-savvy employees and those that have not acquired technology skills. Group discussions and interviews will then be used on each group, with the view of understanding the similarities and differences among the two groups. The group discussions will involve topics related to each group’s income and its relation to having or lacking technology skills. Focused groups use organised discussion, and researchers can gain the views and experiences of each participant (Gibbs, 1997; Morgan, 1997). The expectations (or perceptions) of the group that does not have technology skills will then compared to the reality of the experiences of the technology-savvy group of employees. For example, if the unskilled group indicates that they would acquire the same skills that their technology-savvy counterparts have with the intention of obtaining better remuneration, the research (in the analysis) section will indicate whether indeed the tech-savvy population are well remunerated based on their skills. In other words, the research will be seeking to verify whether wage inequality is affected by the presence or lack of technology skills among workers. The researcher will train and coach one research assistant to help in the interview processes, especially because of time limitations. The use of the standardised interview questions will arguably enhance data reliability during the research process, while training and coaching the research assistant will enhance consistency between the data gathered by the primary researcher and the assistant. During group discussions, the researcher will assume an observatory role, and in addition to documenting the interaction between group members, will note other side-shows that may occur. For example, members of the same group may disagree on something. The older higher earning non-skilled employees may for example differ with the younger counterparts on the effect of technology skills on wages. As an observer, the researcher will be best positioned to document such disagreements. Analysis The first step of the analysis process will involve identifying themes or patterns that emerge in the data; for example, the incidents, interactions, concepts, and behaviours that emerge through group discussions. Next, the researcher will organise the themes into categories which will summarise the findings. As indicated by Taylor-Powell (2003), the forgoing process is labour intensive; however, it is an essential component in qualitative analysis. In this part of the analysis, the researcher will have to read and re-read the research findings in an attempt to identify coherent categories. The researcher may also have to assign codes as a means of categorising data. A code is a descriptive label that the researcher uses in organising data into categories (Taylor-Powell, 2003). Grounded theory will also be used during the analysis, whereby, constant comparisons will be made in the data obtained from research. According to Lingard, Albert and Levinson (2008), the grounded theory’s “main thrust is to generate theories regarding social phenomena: that is, to develop higher level of understanding that is grounded in, or derived from, a systematic analysis of data” (para. 3). It is most suited for use where an existing theory is not being proven. In this case, grounded theory will be used in both H1 and H2. Ethical Issues As Orb, Eisenhauer and Wynaden (2000) note, every research has some ethical issues to deal with. The proposed research is no different. In a bid to uncover whether technology contributes to inequalities, the proposed research will be required to document the wages earned by the respondents. In a bid to uphold ethics however, the researcher will need to ensure that the level of earning will not be used for any other reason apart from the research. Gaining access to wage records will also present an ethical issue in that the researcher will not only be required to acquire permission from respondents, but from their employers. To uphold ethics, the researcher will need to be honest about the research objectives. Additionally, participation in the research will be voluntary and through informed consent. As such, none of the respondents will be coerced or given monetary incentives in order to participate. Informed consent involves negotiation of the trust relationships between respondents and the researchers, but may also involve renegotiations of the same during the research process. The researcher will also need to uphold anonymity when reporting the research findings in order to uphold the respondent’s confidentiality. This means that the researcher will not indicate the specifics of where the research was conducted. At most, the only details that the researcher can give include the country and industry from where the respondents were drawn. Specifics about the employing firm may mean that their confidentiality has been compromised. Notably, upholding the respondents’ anonymity and confidentiality may present an ethical dilemma to the researcher especially because it may interfere with the ability of other researchers to review the research process and the data gathered during the research (Orb et al., 2000). The researcher will also need to recognise the vulnerability of respondents during the research. Such would especially be relevant if the respondents make comments that would jeopardise their job security. A respondent may for example say that in spite of being technology-savvy, he has not yet benefitted from his skills thus his conviction that the management consists of incompetent people who are unable to value some workers’ worth. Such a comment if voiced in a group discussion would most likely get to the management, hence jeopardising the respondent’s job security. The researcher would then have to play a moderating role, especially in ensuring that comments generated during the discussions should remain within the discussion groups. The researcher could also negotiate with the management to omit any possibility that comments generated during the research would be used to victimise respondents. My ethical approval arrangements will include seeking approval from corporate institutions first. Next, I will seek approval from IT managers mainly for their participation in the research, and for engaging employees working in their departments. When seeking approval I will inform the IT managers about the research objectives, the intended confidential handling of data, and the informed consent participation of employees. Since the research will involve some time away from their stations of work, I will seek to find the most appropriate time for conducting the research. The time will have to be convenient for both employees and the employer. Finally, I will seek employees’ participation through informed consent. The Strengths and Weaknesses of the Proposed Study Strengths Using the qualitative approach will enable the researcher to describe the characteristics of the tech-savvy and unskilled workers; their income differentials and their perceptions about the same will also be documented. The qualitative approach will also enable the researcher to examine issues raised in the data collection stage in detail (Silverman, 2011). Moreover, the researcher will have more flexibility in the scheduling and engaging respondents. There is also the probability that the researcher will revise the research framework in case new information related to the topic of research emerges. Weaknesses One of the outstanding weaknesses of qualitative research is that the trends established during research cannot be subjected to statistical analysis (Silverman, 2011). This implies that one cannot validate trends through calculating an effective size. Another weakness relates to the need to continually verify data. The limitations of time and money may make such continual verification of data hard to attain. In relation to time constraints, the qualitative approach will also require me to spend a lot of time collecting data and analysing it. Assumptions in Research The proposed research will be conducted on the assumption that there is more to wage inequalities than technology development. The researcher hopes that the findings obtained during the research will prove that technology is a minor issue compared to other factors such as work experience and age. The researcher has assumed that young a majority of technology workers still have a long-way to go before attaining similar wage levels as a majority of their more experienced counterparts. The researcher further assumes that technology complements skills that a person has, and that in most cases, being tech-savvy by itself, without having the experience of working in specific job roles does not guarantee a person better or equitable earnings. Budget Particulars Estimated budget (AUD) Phone expenses 75 Library charges 50 Internet expenses 65 Travel charges to research location 100 Hiring a research assistance at $20 per hour for 40 hours 800 Contingency items 150 Total 1,240 Research Plan Date Item Antecedent August 2013 Write a methodological research proposal and submit it for approval None September 2013 Conduct a detailed literature review Proposal approval October- Mid December Conduct the field interviews and observations Literature review Mid-December to January 2014 Analyse the research findings Data collection February 2014 Write the research findings and submit them Data analysis. References Acemoglu, D., & Autor, D. (2011). Skills, tasks, and technologies: Implications for employment and earnings. In Orley, A. & Card, D. E. (Eds.). Handbook of Labour economics volume 4. Pp. 1043-1171. Amsterdam: Elsevier. Crawford, N. & McKenzie, L. (2011). E-learning in context: an assessment of student inequalities in a university outreach program. Australian Journal of Educational Technology 27(3), 531-545. Elsevier. (2008). How to write a world class methodology paper: tips, traps and travesties. Elsevier Author Workshop 1-98. Gibbs, A. (1997). Focus groups. Social Research Update 19(winter), retrieved August 29, 2013, from http://sru.soc.surrey.ac.uk/SRU19.html Harrison, R. (2008). Skills-Biased technology adoption: Firm-level evidence from Brazil and India. IFS Working Papers 08(03), 1-69. Hoyle, R., Harris, M., & Judd, C. (2002). Research methods in social relations. London: Thompson Learning, Inc. Kvasny, L. (2006). Cultural (re)production of digital inequality in a US community technology initiative. Information, Communication & Society 9(2), 160-181. Lingard, L., Albert, M., & Levinson, W. (2008). Grounded theory, mixed methods, and action research. BMJ 337, retrieved August 29, 2013, from http://www.bmj.com/content/337/bmj.39602.690162.47 Moreno-Gablis, E. & Wolff. F-C. (2008).Evidence on new technologies and wage inequality in France. Applied Economics 1-30. Morgan, D. (1997). Focus groups as qualitative research. London: Sage. Orb, A., Eisenhauer, L., & Wynaden, D. (2000). Ethics in qualitative research. Journal of Nursing Scholarship, 93-96. Saunders, M., Lewis, P., & Thornhill, A. (2007). Research methods for business students. London: Pitman Publishing. Silverman, D. (2011). Qualitative research. London: Sage. Taylor-Powell, E. (2003). Analysing qualitative data. 1-12. Retrieved August 29, 2013, from . Wheeler, C. H. (2005). Evidence on wage inequality, worker education and technology. St. Louis Review 87(3), 375-393. Read More

From Wheeler (2005), I have learnt that it is important to indicate any assumptions that a researcher may take. I have also learnt that a good methodology section provides specific research details thus making it possible for future researchers to replicate the research if they so wish. Kvasny, L. (2006). Cultural (re)production of digital inequality in a US community technology initiative. Information, Communication & Society 9(2), 160-181. Kvasny (2006) is another researcher who investigated how information communication technologies affect social inequalities.

The research by Kvasny (2006) is an ethnographic study, which was done in eight months involving respondents drawn from a low-income neighbourhood in the US. The researcher used Bourdieu’s theory in data collection and analysis. The data collection techniques included participant observation, informal interviews and textual analysis. Kvasny (2006) also obtained historical and background data on a CPC initiative from published documents such as planning reports, proposals to the city council, and newspaper articles.

The researcher also interviewed staff and also got into informal conversations with classroom facilitators. The informal conversations were a natural approach where the researcher interacted with respondents and asked them questions about their experiences before and after taking up technological courses. The researcher specifically wanted to find out their honest opinion about the difference that technology was making in their lives. Focused data collection took the form of participant observation and took 14 weeks of the 8 months in which the research was conducted.

The researcher observed 15 respondents and one classroom facilitator as they took a 7-week course. Through the prolonged observation, Kvasny (2006) indicates that he was able to build report with the sampled informants hence making them more comfortable in providing him key insights into their lives, careers and any perceived inequalities. He however acknowledges that studying the same group over a long time restricted the variety of social types that he sampled, hence prohibiting cross-case analysis.

When conducting interviews, Kvasny (2006) did not record the responses; rather, he chose to use short interviews, which he says, facilitated accurate recall of the discussions he had with respondents. Notably, the foregoing might have jeopardised the accuracy of the results, because there was no guarantee that Kvasny (2006) did indeed recall the responses accurately. However, the absence of recorders made the interaction between the researcher and his respondent seem natural; terminating the interview for example involved thanking the respondents and not switching off the recorder or shuffling papers as would have been the case if the researcher was recording or taking interview notes respectively.

The observation method that Kvasny (2006) used has advantages in that it provided direct access to the inequality and technology phenomenon that was under consideration. It also provided diversity in that there are times when the researcher’s observation was unstructured and informal, while in others, it was structured and formal. The observation also complemented the triangulation approach that Kvasny (2006) adopted. Triangulation is the process of obtaining data through more than one data collection technique.

In this case, Kvasny (2006) used interviews, observations and textual analysis. One of the drawbacks of using observation as a data collection technique is that the method is resource-intensive and time consuming. There is also a possibility of observer bias, which if present, could undermine the validity of the research findings. The possibility of observer effect, where the respondents behave in a specific way according to what they perceive the researcher is looking for, is also present. As Kvasny (2006) indicates however, he tried minimising the observer effect by prolonging the interaction period he had with the respondents in an attempt to get them to behave as naturally as possible.

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