Strategies For Building Trust In Business Research

The Issue of Trust in Business Research

Business research issue of interest-

There are ample numbers of issues that arise while doing a business research work. One of such issues is the trust, which the different business units have on the researchers. Despite the assurance, which is given by the researcher for securing the confidential data, different business units have a higher degree of doubts on whether the data will be kept safe. This is indeed a problematic situation for the research as the research will not be provided the needed data. Hence, the research work will suffer due to the absence of quality and reliable data (Chen, Chiang and Storey 2012).

Appropriate research strategy-

 In the highlighted business research-related issue, it is important for the researcher that it tries to get to get the confidence of the participants. This is indeed difficult; however, there are ways using which the research can actually think of doing such thing. The research needs to show the objective of the research. Along with that, the researcher should also explain the purpose behind the research. This will help in building a trustworthy relationship in between the researcher and the target participant. Additionally, there is also a need to ensure that all the data will be kept safe under the Data Protection Act of 1998 (Makulilo 2012). Such strategies might really work in forming a comfortable binding between the researcher and the participant.

Appropriate theoretical framework-

Shield Privacy Framework appears to be a suitable framework for resolving the highlighted business research-related issue. It indeed provides a holistic solution to the problem. It resolves the issue through four major models to provide protection to the data. The four different models are as follows (Lau et al. 2014):

• PDM-ADM: Personal Data Minimization – Anonymous Data Maximization
• SDD: Separation of Duty and Data
• HPP: Hippocratic Privacy Policies for Information Systems
• IT security for Privacy Protection

1. This is unpractical to rely on such statements. The current work is very unpredictable indeed. It is never controllable through Star Signs. There are several kinds of literature on the generational differences in the workplace. Different kinds of literature indeed contradict each other in their beliefs on the topic of study. Generational stereotypeswill be difficult to manage according to what the Star Signs says. An ample number of workplace behavior has been highlighted with respect to the different generations. However, such differences are not true at all the time. For example, one of the baby boomers at the selected workplace may have a sound knowledge of technical thing. On the other hand, there can be some Millennials who are not social and are very traditional in their business approach. Precisely, it can be said that becoming judgmental on generational differences is never true (Lester et al.2012).  
2. I work as a programmer in a private firm. My company is based in Sydney in Australia. At my workplace, the stereotype is little different to many contemporary workplaces. The project team is formed on the basis of relevant skills as required for a particular project. Few baby boomers have also been found in some of such projects. This simply signifies a fact that the management team at my workplace tries to figure out the most appropriate personnel for the project (McGregor 2013). Required personnel may be from the millennial group or from the baby boomers. The identified stereotype by Dr. Malcolm Johnson in ‘Beyond Belief: The Management Reality of Generational Thinking’ is contradicting to the practices that occur at my workplace.  
3. The stereotyped nature that occurs at my workplace is very distinguishing to what is publically popular. The workplace has examples of baby boomers who are tech-savvy. Moreover, there is few older millennial as well who do not even use Facebook. The idea behind the generational differences has least concerns for literature that keep baby boomers out of the box when technology matters the most (Gouldner 2016).
4. Highlighting the essentials of contemporary business nature will be a key thing to be implemented at my workplace. Such essentials include following the traditional method of doing business. This will also include implementing the latest technologies to gain a much needed competitive advantage.

1. According to Buckley, a sequential mixed methodis a combination of quantitative analysis techniques and the qualitative archival data & semi-structured interview. The mixing method in this way provides the data triangulation and requisite methodological that addresses the research question. In such study, qualitative data is corroborated by the quantitative findings or vice-versa. In such an approach, both the qualitative and the quantitative approaches act as a complementary figure to each other. It is indeed the use of multiple measures to uncover the variances (Buckley 2015).
2. Potential benefits of triangulationinclude highlighting the overall philosophy chosen for the particular research. The benefits can be well described as pragmatic. For pragmatists, the research context, the scenery of the research questions and the expected consequences are the essential elements that they use to choose their style of research design. They give values to both kinds of research design such as the qualitative and the quantitative. According to the research context, they decide on the appropriate research design. Such sequential research method prepares an analytical platform using which the researcher can have a broad range of ideas occurring from the different study (Buckley 2015). This is helpful in reaching a solid conclusion.     
3.  The sequential mixed research method used by Buckley is beneficial for the research works. This can help to get a broad range of ideas, which is rarely possible with the other approaches. The sequential mixed research approach will help to analyze the research topic in numerous ways. Moreover, this will bring different results, which will provide ample of data on the chosen research topic. However, this can be problematic as well if the data contradict to each other.

1. Qualitative analysis is relay helpful in designing the research work and getting the required results. According to Birchall (2014), the mentioned method of analysis is really effective in deriving the results. This is helpful indeed as it allows going deeper into the personal narratives. In such approach, the researcher will be able to get the insights of the target applicant supposedly one of the members of the top management. This will indeed help to get the much-needed data, which is necessary to get the required data. One of the examples of such approach is conducting an interview with one of the members of the top management team. Such interviews will expectedly produce important data, which is important to understand the exact problem behind the identified research concern.
2. Reflexive strategies can be used to avoid personal biases at the time of interview. The biases can be minimized by asking the same question from more than one or two applicants. Assuming the answers of one applicant as a sufficient find for the research will produce biases. This is indeed advisable to ask the same set of questions for more than two or three applicants. This will help to get a diverse range of opinions. Hence, biases will be significantly reduced. There can also be the cases of similar responses to the same questions; however, different opinions will also exist significantly. This is indeed a much safer way to reduce the severity of biases, which is highly possible by selecting the participants on a non-random basis. A random selection is rarely possible in the interview process (Robinson 2014).  

Hidden populations in the Australian society can be referred to those who are illegal immigrants to this country. Approximately around 64,000 illegal immigrants are there who are living in the country; however, their visas have been expired. Malaysians are the highest contributors to this number. Approximately around 9,440 illegal immigrants are the Malaysians. China comes at the second position with 6,500 illegal immigrants. This is followed by Indonesia, India, Philippines, Thailand, and Vietnam. Germany, Japan, Fiji and France citizens were also on this list (Mail Online 2017).

Snowball Sampling also knew as chain referral process is helpful in reaching to the population, which are hard to reach. They can be approached using the method and data can be sampled as well. This is indeed simple and a cost-effective process. The sampling technique is also less challenging than the other sampling method. This needs a very little planning and a smaller workforce. It allows the stud to happen with the hidden population, which is hardly possible with any other sampling method. It can also help to discover some characteristics, which were not known to the masses (Dr?gan and Isaic-Maniu 2012).

Building Trust with Participants

 There is a certain limitation as well that occur while working with the Snowball Sampling technique. One of the limitations is to verify the sampling error. This is indeed a critical issue, which might prevent the production of a quality result. Another limitation is the inference that it encourages for. Such limitation encourages making a conclusion based on the available sample data. However, this has already been stated that Snowball sampling may have errors as well. This means that the concluding result may also have the error (Etikan, Alkassim and Abubakar 2016).

There is a requirement to have some ethical considerations while collecting the samples from hidden populations. One of such population will be to maintain the Data Protection Act of 1998 (Lau et al. 2014). This will help in getting the population into confidence. Additionally, addressing the purpose behind the research work will be the other ethical consideration, which will encourage the population to respond to the sampling process (Bryman and Bell 2015).

1. The author has addressed a very critical challenge, which has worried the non-profit organizations across the globe. The relationship of the non-profit organizations with the donors is very critical of a mutual relationship, which is very important for the betterment of society. A metrichas been postulated by the author, which can significantly help to analyze the potential donors. The metric will help to figure out the one time donor and the potential donor. Such data will help to enhance the relationship with the potential donor. This will also help to motivate the one-time donor (Khodakarami, Petersen and Venkatesan 2015).
2. The author has used a metric to collect the sample on a random basis. The author has identified the importance of a balanced relationship between the potential donors and the non-profit organization. The author has used the data of the last 20 years. Those data are from the U.S. public university. The data has helped the author to analyze the appropriate method of sampling. Those who are donating the funds for the last 20 years and are potential donors will be encouraged for an enhanced donation amount and for a sensitive donation. Those who are the one time donor, they will be encouraged to enhance their donation occurrence (Khodakarami, Petersen and Venkatesan 2015).
3. Following are the list of criteria used by the authors (Khodakarami, Petersen and Venkatesan 2015):

• Attaining the data of the last 20 years from the U.S. public university
• Separating the potential donors from the one time donor
• Encouraging the potential donors for more sensitive donations and for increasing the occurrence of donations
• Motivating the one time donor for an increased number of donation

1. Model developmentaccording to the author is an effective way to conduct the research work. This is so because it provides a guiding framework, which is necessary to have a controlled research. Moreover, the development of model will encourage being in the line of objective, which is necessary to justify the research work (Khodakarami, Petersen and Venkatesan 2015).
2. Field studyis aimed at observing the target people. The researcher has targeted both the potential and the one time donors. The field study will educate on the resource to collect the user data such as from the U.S. public university (Khodakarami, Petersen and Venkatesan 2015).
3. The target populationis attained in conducting the research according to the guidance of the author by categorizing the population into two segments such as the potential donors and the one time donors. The sampling frameis also achieved as the author has revealed one of the sources of data such as the U.S. public university to collect the required information. The sample size is also attainable as the framework guides for a two separate population such as the potential and the one time donors. Sample design will be the random selection of potential and the one time donors. Data will be derived from the U.S. public university (Khodakarami, Petersen and Venkatesan 2015).  
4. The pilot testwill be the potential source for identifying the non-sampling related error. Reliability testwill help to reduce the level of errors in the research work (Pace et al. 2012).

Focus Groups are those, which are targeted for conducting the research and collecting the samples (Krueger and Casey 2014). I have been the part of one of such Focus Groups. It gives a learning opportunity on how to collect the samples. This will be helpful for my future research work if I get any such chance. I got to know the practicality of the research method.

There is an ample number of positive aspects that I was able to derive from my focus group experience. One of such experiences is the practicality, which is very important while collecting the samples from the target group. The experience has taught me the things to consider while studying the Focus Group. Such lessons will help me to conduct a research with less error (Krueger and Casey 2014).  

The main purpose of the focus group is to draw a study on the attitudes, feelings, experiences, and beliefs of the respondents. Focus Groups help to focus on such parameters, which is not possible through any other research methods such as observation, questionnaire surveys, and the interview. I have found some negativity in the Focus Group such as the bias behavior and the rapport build-up. Based on the experiences of the Focus Group, the following are some recommendations (Savovi? et al. 2014):

• Interviews are needed to place at ease
• Confidentiality is important
• Bias behavior needs to be avoided
• Rapport build-up
• Assuring the confidentiality  

1. There are certain patterns of behaviors, which is problematic for a quality result by sampling through Focus Group. Those patterns include but are not limited to such as Overvaluing the Group, Anxiety toward Uniformity and Closed-Mindedness. Overvaluingthe groups signifies that the group looks for positive aspects in order to avoid any expected conflicts. In doing so, they miss on the realism, which may even cause the quality of information. Another issue is to be anxious towards uniformity. They remain silent on the differences in order to avoid the conflict. This is dangerous as this will not help to head in a right direction. Closed-mindednessis another issue that hampers the quality of Group Focus. This is one of such problems that encourage avoiding the minor thing. However, such minor thing can be important as well (Bénabou 2012). These are some of the issues, which indicate towards a fact that the Focus Group is in trouble.
2. There are some ways that can help to mitigate the identified issues. One of such way is to be aware of the group dynamics. Additionally, the influence of such factors should also be known to the group members. There is a need to appreciate the individual viewson the subject topic. This will help to get diverse views, which is important to reach to a quality result. However, there will be the need to emphasize the realism. A group member is required to be realistic about their advantages, risks, and options. This will eventually help in reducing the influence of groupthink (Cain 2012).

1. Brief summary-

The research was on physical wellbeing of the children. Obesity has become a common issue with the contemporary children. This is for such reasons physical activity; children’s sport and physical education have become the areas of attraction for the researchers. The chosen example is one of those few studies on the identified areas, which have used the grounded theory. The research is a diagrammatical representation, which is less common with the researchers. However, the research work has proved that indeed the diagrammatical representations are a good way to reduce the pressure of complex data sets. The research work has indeed highlighted the importance of diagrammatical representation. According to the chosen example, this will be a good shift from the traditional approach that is limited only to the texts. The example has indeed proved that using the internet communication will be a good move to bring a much transparent result (Buckley and Waring 2013).

1. The justificationthat the author has provided to use the grounded theory in research works is the use of diagrammatical representation and making this available to a mass audience through internet communication (Buckley and Waring 2013).  
2. The research has used one elementand one toolof the grounded theory approach. A diagrammatical representation of the research topic was the one element, which very few researchers use in their research works. Additionally, the use of internet communication is the one tool, which has been highlighted in the chosen research work (Buckley and Waring 2013). The researchers are yet to use the internet communication tool in their research works.
3. The researcher has used the “a la carte” approachto the grounded theory.  
4. The author has identified that many researchers do not use the diagrammatical representation in their research works on one of such topics. This is the most common approach to the grounded theory. However, there are very few researchers who are using the approach (Buckley and Waring 2013).
5. The research could be generalized to other contexts. This can be related to the fast food consumption, which has been believed as one of the reasons behind the increasing obesity cases in children (Garcia, Sunil and Hinojosa 2012).

The Shield Privacy Framework

There are ample of differences between the NVivo and Leximancer. Both the software has their separate area of scope in research. NVivo is appropriate for researcher oriented study. On the other hand, Leximancer is suitable for predictive and exploratory studies. NVivo is suitable for a small sample size whereas Leximancer is appropriate for a larger volume of data. NVivo is appropriate for the interpretive approach whereas Leximancer is suitable for a positivistic move.

Both the NVivo and the Leximancer are useful for the different research works. Both the software tools can be used in a broader research topic like the sports management in the chosen research topic (Sotiriadou, Brouwers and Le 2014). This is because the combination will allow integration and a comparison of the different source of analysis. NVivo is effective for semi-structured interview. Moreover, reliability is doubtful. This is because there is a possibility of manual intervention from the researcher. On the other hand, Leximancer is reliable because there is comparatively a very lesser manual intervention of the researcher. Leximancer is easy to use, which may attract the inexperienced researchers. However, they might fall into the danger of oversimplifying the process of data analysis. This might lead to incorrect findings and conclusion. On the other hand, some researchers have recommended the use of NVivo because it enables the level of data interrogation. This is indeed important for an improved severity of analysis (Sotiriadou, Brouwers and Le 2014).  

 Social Desirability Bias can be defined as a weapon, which the different social groups use to be based on their responses. They may try to over-report the good behavior. On the other hand, they may also under-report the bad behavior. For example, on asking the respondents on the use of drugs they might under-report their bad habits by saying that they use drugs only when their friends are around them. They might feel pressurized and would try to keep them away from rational behavior. This is one of the examples of such characteristics, which are known as social desirability bias (Antin and Shaw 2012).

This can really affect the quantitative research either through a structured interview or the questionnaire surveys. Social desirability bias can be of various types, which means the findings of the survey or the interview will produce a biased result. This is so because the respondents are biased in their responses. Hence, the results of the survey or the interview will have biases as well. This will affect the sampling as well. The researcher will find this difficult to select the number of respondents, so that, a considerable amount of biases could be reduced. Additionally, there are large lists of characters that are expected to attract the bias responses. Such lists include but are not limited to such as personal income, religion, physical appearance, illegal acts and intellectual achievements (Kelly et al. 2013).

Hidden Populations and Snowball Sampling

How would you rate your table service experience today?

This question is biased because it gives only three options such as excellent, good and average. However, there are possibilities that the table service experience was bad for someone or they have disliked the experience. Above all providing multiple options for answers is the other fact that shows the manual biases in the researcher. Respondents could have different answers as well. This can also be understood from the social desirability bias, which states that respondents have desires in them to be biased. They desirably give bias responses to the unexpected questions. They try to over-report their good behavior. On the other hand, they try to under-report their bad behavior. The question asked here is in the relation to their experience of food, which has been served to them today. Some respondents might not be eager to respond to the question with the three highlighted options. They are more comfortable with some other responses such as “not interested”. The question should be rewritten as follows to remove the bias:

Would you like to respond on “how was your table service experience today”?

Should dog owners socialize their pets?

 This is again a biased question as it denotes a closed-ended discussion. Respondents will be required to respond in either yes or no. They have not been given enough options to reduce the level of biases. Options could have been like “agree, strongly agree, neutral, disagree, completely disagree or not interested”. The question can be rewritten as follows to reduce the bias in it:

Will it be beneficial to socialize the pets?

Options will be as follows:

• Agree
• Strongly agree
• Neutral
• Disagree
• Completely disagree
• Not interested

 Yes, the Predictive Validity can be assessed based on retrospective data. However, the records need to be usable. This means that the records should be in accordance with the target future outcome. This further exemplifies the importance of relevancy (Schoene et al. 2013). For example, previous academic qualification will be required while applying for postgraduate courses in a university.

 The example attached to the question is about the coaching behavior of managers. Two conditions have been given such as going by the existing emotional intelligence test record or conducting a fresh test on emotional intelligence and then monitor the one-year coaching behavior. The first option indeed looks the fittest choice for the coaching purpose. Moreover, this will be a competitive selection to go with the existing emotional intelligence records and appoint the most competent manager for the coaching purpose (Fazel et al. 2012). On the other hand, going by the other option that is to conduct an emotional intelligence test and then observe the coaching behavior will be a waste of time. Additionally, this will also be the loss of extra expenses required to be made on the emotional intelligence test (Tellez et al. 2013).

Ethical Considerations for Sampling Hidden Populations

References-

Antin, J. and Shaw, A., 2012, May. Social desirability bias and self-reports of motivation: a study of amazon mechanical turk in the US and India. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 2925-2934). ACM.

Bénabou, R., 2012. Groupthink: Collective delusions in organizations and markets. Review of Economic Studies, 80(2), pp.429-462.

Birchall, J., 2014. Qualitative inquiry as a method to extract personal narratives: Approach to research into organizational climate change mitigation. The Qualitative Report, 19(38), p.1.

Bryman, A. and Bell, E., 2015. Business research methods. Oxford University Press, USA.

Buckley, A.P., 2015. Using Sequential Mixed Methods in Enterprise Policy Evaluation.

Buckley, C.A. and Waring, M.J., 2013. Using diagrams to support the research process: Examples from grounded theory. Qualitative Research, 13(2), pp.148-172.

Cain, S., 2012. The Rise of the New Groupthink.”. New York Times, 13.

Chen, H., Chiang, R.H. and Storey, V.C., 2012. Business intelligence and analytics: From big data to big impact. MIS quarterly, 36(4).

Dr?gan, I.M. and Isaic-Maniu, A., 2012. Snowball sampling developments used in Marketing Research. International Journal of Arts and Commerce, 1(6), pp.214-223.

Etikan, I., Alkassim, R. and Abubakar, S., 2016. Comparision of Snowball Sampling and Sequential Sampling Technique. Biometrics & Biostatistics International Journal, 3(1), p.00055.

Fazel, S., Singh, J.P., Doll, H. and Grann, M., 2012. Use of risk assessment instruments to predict violence and antisocial behaviour in 73 samples involving 24 827 people: systematic review and meta-analysis. Bmj, 345, p.e4692.

Garcia, G., Sunil, T.S. and Hinojosa, P., 2012. The fast food and obesity link: consumption patterns and severity of obesity. Obesity surgery, 22(5), pp.810-818.

Gouldner, K., 2016. Millennial Mindset: How to Attract Millennials to an Aging Industry. Gen, 75(66), p.65.

Kelly, C.A., Soler-Hampejsek, E., Mensch, B.S. and Hewett, P.C., 2013. Social desirability bias in sexual behavior reporting: evidence from an interview mode experiment in rural Malawi. International perspectives on sexual and reproductive health, 39(1), p.14.

Khodakarami, F., Petersen, J.A. and Venkatesan, R., 2015. Developing donor relationships: The role of the breadth of giving. Journal of Marketing, 79(4), pp.77-93.

Krueger, R.A. and Casey, M.A., 2014. Focus groups: A practical guide for applied research. Sage publications.

Lau, B., Chung, S.P., Song, C., Jang, Y., Lee, W. and Boldyreva, A., 2014, August. Mimesis Aegis: A Mimicry Privacy Shield-A System’s Approach to Data Privacy on Public Cloud. In USENIX Security Symposium (pp. 33-48).

Lester, S.W., Standifer, R.L., Schultz, N.J. and Windsor, J.M., 2012. Actual versus perceived generational differences at work: An empirical examination. Journal of Leadership & Organizational Studies, 19(3), pp.341-354.

Mail Online. 2017. Statistics reveal 64,000 people are living illegally in Australia. [online] Available at: https://www.dailymail.co.uk/news/article-4615632/Statistics-reveal-64-000-illegal-immigrants-Australia.html [Accessed 29 Nov. 2017].

Makulilo, A.B., 2012. Privacy and data protection in Africa: a state of the art. International Data Privacy Law, 2(3), pp.163-178.

McGregor, G., 2013. Beyond’Y’and other stereotypes: Exploring the experience of youth in the 21st Century. Social Alternatives, 32(2), p.3.

Pace, R., Pluye, P., Bartlett, G., Macaulay, A.C., Salsberg, J., Jagosh, J. and Seller, R., 2012. Testing the reliability and efficiency of the pilot Mixed Methods Appraisal Tool (MMAT) for systematic mixed studies review. International journal of nursing studies, 49(1), pp.47-53.

Robinson, O.C., 2014. Sampling in interview-based qualitative research: A theoretical and practical guide. Qualitative Research in Psychology, 11(1), pp.25-41.

Savovi?, J., Weeks, L., Sterne, J.A., Turner, L., Altman, D.G., Moher, D. and Higgins, J.P., 2014. Evaluation of the Cochrane Collaboration’s tool for assessing the risk of bias in randomized trials: focus groups, online survey, proposed recommendations and their implementation. Systematic reviews, 3(1), p.37.

Schoene, D., Wu, S.M.S., Mikolaizak, A.S., Menant, J.C., Smith, S.T., Delbaere, K. and Lord, S.R., 2013. Discriminative ability and predictive validity of the timed Up and Go test in identifying older people who fall: systematic review and meta?analysis. Journal of the American Geriatrics Society, 61(2), pp.202-208.

Sotiriadou, P., Brouwers, J. and Le, T.A., 2014. Choosing a qualitative data analysis tool: A comparison of NVivo and Leximancer. Annals of Leisure Research, 17(2), pp.218-234.

Tellez, M., Gomez, J., Pretty, I., Ellwood, R. and Ismail, A.I., 2013. Evidence on existing caries risk assessment systems: are they predictive of future caries?. Community dentistry and oral epidemiology, 41(1), pp.67-78.