AM6202 Research: Managerial Problems & Performance at Spark NZ

This report identifies and analyzes the major managerial problems facing Spark New Zealand and their effects on the organization's performance. It explores various research methodologies, including data mining, surveys, quantitative rating scales, questionnaires, focus groups, and qualitative rating scales, to understand the challenges. The research aims to understand the problems and measures taken by Spark New Zealand to address them, drawing from literature on organizational management and resource utilization. The report also discusses the importance of data mining and surveys in understanding customer needs and competitive pressures, as well as the application of quantitative and qualitative rating scales to gauge customer perceptions. The ultimate goal is to provide insights that can help Spark New Zealand improve its performance and address its managerial challenges effectively.

Running head: BUSINESS RESEARCH METHODOLOGY
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Business Research Methodology
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Professor’s Name
Institutional Affiliation
Date

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Spark New Zealand
1. The management question
What are the major managerial problems which face Spark New Zealand, and
what are the effects of these managerial problems on the performance of the
organization?
The research questions
In addition to the managerial problems, what are the other major problems faced
by Spark New Zealand?
What are some of the major measures taken by Spark New Zealand to address
some of the major problems it faces?
The objectives of the study
To understand the major problems which face Spark New Zealand
To understand some of the major measures and strategies which have been
taken by Spark New Zealand to address some of the major problems it faces
2. Literature search
Spark New Zealand is one of the major telecommunications companies in New
Zealand which provides mobile networks and fixed line telephone services, in New
Zealand. The company is also a major internet service provider and a major ICT
provider to many businesses in New Zealand. The company was established in 1987
and became a public company in 1990, and has been offering its services and products
to the New Zealand citizens since 1990.
Just like the other companies, Spark New Zealand faces some managerial problems
and some other problems which limit its effectiveness in offering its services to the
people. The main questions of our proposal aim to address some of the major problems
faced by this company. Some of this information can be obtained from the available
literature which discusses the major challenges faced by organizations. This knowledge
urges us to come with some annotations can help us to get some of the required
affirmation about this organization and the other organizations in general.
Annotation 1
Hislop, D., Bosua, R., & Helms, R. (2018). Knowledge management in organizations: A
critical introduction. Oxford University Press.

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This source (book) gives a detailed introduction of good management of
organizations and also gives some important hints about effective management of
organizations. The authors of the book give different management strategies which
the managers of organizations should apply for them to manage all the employees
and the other stakeholders of the organizations well, and this will make their
organizations successful. The content of this book is very important and can be used
by the management staff of Spark New Zealand for them to know the best
management strategies which they can apply in their operations to improve the
performance of their organization.
Annotation 2
Sayles, L. R. (2017). Managing large systems: Organizations for the future. London:
Routledge.
This source (book) focusses on the management of large systems such as the
systems found in organizations some of which are very large and complex. The book
clearly states that there are many challenges associated with managing large systems
and the managers must be very skilled and competent for them to manage these
systems properly. For effective management of these large and complex systems, all
the experts from different fields working in the organizations need to work together to
manage these organizations effectively. The information of this source is very important
to the management staff of Spark New Zealand as it advises them the importance of
working together to solve the many challenges faced by large organizations which have
very large and complex systems.
Annotation 3
Wicker, P., & Breuer, C. (2013). Understanding the importance of organizational
resources to explain organizational problems: Evidence from nonprofit sports
clubs in Germany. VOLUNTAS: International Journal of Voluntary and Nonprofit
Organizations, 24(2), 461-484.
This source (journal) discusses the importance of understanding the
organizational resources and how these resources can be used to explain the
organizational problems, and then come up with some solutions which can be used to
solve these problems. This journal gives the case study of the nonprofit sports
organizations some of which have been able to understand their problems and use the
resources they have to address most of these problems. This journal is very important
in our research as it teaches the management staff of Spark New Zealand that they can
use the resources they have to address some of the problems they face just like some
of the nonprofits sports organizations in Germany do.
Annotation 4

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Schiavone, F. (2017). Incompetence and Managerial Problems Delaying Reward
Delivery in Crowdfunding. Journal of Innovation Economics & Management, (2),
185-207.
This source (journal) describes how incompetence and managerial problems
delay rewards in crowdfunding projects. The incompetent leaders delay or fail to give
the awards where necessary and at the right time and this makes most of the
crowdfunding projects end up failing. This source clearly explains the negative impacts
of incompetence leadership and other managerial problems on the expected outcomes,
which means if there are incompetent leaders and other managerial problems in
organizations, most of the projects of the organizations will end up failing. This
information is very important to the management staff of Spark New Zealand, and they
should do all that it takes to eliminate incompetent leaders and try as much as possible
to solve its managerial problems which can make most of its projects to fail if not solved.
Annotation 5
Heerkens, H., & van Winden, A. (2017). Solving managerial problems systematically.
Noordhoff.
This source (book) explains in details how the managerial problems can be
solved systematically. According to the book, there are some strategic steps which
should be followed systematically and strictly to solve managerial problems. These
steps mainly involve first understanding the managerial problems well and their sources
and then developing and implementing the best solutions which can be used to solve
the problems. After implementing the solutions, they should then be evaluated to see
their performance, and if they did not perform as expected, they can be replaced by
other better solutions. This source is very important and helps the management staff of
Spark New Zealand to understand how they can effectively solve the management
problems they face.
3. Analysis of:
Data mining
Data mining is the process of examining and sorting large and complex pre-
existing databases to generate new and more useful information or data (Shmueli,
Bruce, Yahav, Patel, and Lichtendahl, 2017). Data mining is done using some useful
data mining tools, and this process of data mining helps organizations to predict their
future trends and thus implement the necessary measures which can help to improve
their performance. Spark New Zealand can use data different data mining techniques to
predict its future performance and know what the customers may need in the future, and
by getting this information, the company can do the required modifications which will
help to keep on performing well in the market. Again, this prediction and implementation
of the measures which will help to improve the performance of the company will help it

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to address the problem of competition in the market which greatly affects its
performance by robbing some of its customers.
Surveys
Surveys are important in organizations and help many organizations to solve
some of the problems they face. As already mentioned, Spark New Zealand faces
managerial problems and other non-managerial problems which affect its performance
greatly. One of the major problems which Spark New Zealand faces is stiff competition
from other companies such as Vodafone which offer similar products and services.
Surveys are very important in addressing such problems since they will help the
company will collect the views and the perceptions of the customers about their
products and services for it know what it needs to improve or add for it to perform better
than the competitors (Callegaro, 2017). Therefore, the company should make use of
surveys to understand its customers’ demands and implement them for it to compete
well in the market and this will help to improve its overall performance.
Quantitative rating scales
Quantitative rating scales are types of numerical scales which are used by
researchers or organizations when they want the respondents of the research to rate
various products or services in the research. These rating scales are normally given
some numerical values such as 0 to 5, 0 to 10, or any other numerical values where
each numerical value represent a certain aspect of the research questions or issues
being investigated. Quantitative rating scales help the researchers to understand the
perceptions of the respondents about the issues or questions under investigation. Spark
New Zealand can make use of quantitative rating scales to understand the customers’
perceptions about its products and services by looking at the different scores given to
different products and services, and this will help the company to make the necessary
improvements which will help to improve the rating scores of its products and services
which will mean improved satisfaction to the customers.
4. An overview of:
Questionnaires
A questionnaire is a set of printed or handwritten questions which are prepared to
aid in the process of data collection in research (Brace, 2018). The questionnaire
questions can be closed, or open-ended questions. In the closed questions, the
respondents are restricted in their responses and are supposed to answer by either yes
or no, true or false, or chose their responses from the set of answers given by the
researchers. The open-ended questions, on the other hand, allow the respondents to
give their answers and express themselves about the issues being investigated (Züll,
2016, pp.2-5). Questionnaires are very important and can be used in our research
proposals to understand the major problems faced by Spark New Zealand. The

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questionnaires will be given to the staff of the organization and the customers of Spark
New Zealand for them to explain various problems which they feel affect the
organization. The management staff and the customers of Spark New Zealand are the
most suitable respondents of the research since they are directly involved in the
operation of the company, and so they know the major challenges or the problems
which face the organization.
Focus groups
Focus groups are some groups made of a small number of participants (normally
about 6 to 12 participants) who are selected from the company’s target market. The
participants are selected from the company’s main customers, and these customers
discuss with the company’s moderators to see what can be done to improve to improve
the company’s products or services (Edley and Litosseliti, 2018, pp.6-9). Focus groups
can be effectively used in our research proposal where Spark New Zealand will select a
few of its loyal customers and engage them in the discussion about the company’s
performance and request them to give some areas which they feel to be improved by
the company for the customers to benefit from the services and products offered by the
company. The focus groups are very important as they represent the customers in the
decisions made by the company, and we know the customers are very important
stakeholders who should be engaged in the company’s decisions for it to thrive well.
Qualitative rating scales
Qualitative rating scales are some special non-numerical scales used by
researchers and organizations to help them to understand the respondents’ views and
perceptions about their research questions or other issues being investigated. These
scales normally use some comparative words such as good, very good, excellent,
agree, strongly agree, among many other words which can be used to express the
respondents’ perceptions or satisfaction on the issues being investigated. Qualitative
rating scales can also be used in our research proposal to help the researchers to
understand the respondents’ perceptions and views of the major challenges which
affect the organization’s performance. The researchers can come with some proposed
problems and come up with some qualitative rating scales which will help them to
understand the respondents’ perceptions about those problems, and these results can
be used by the organization to improve its products and services as suggested by the
respondents.
Coding
In research, coding is an analytical process which involves categorizing the data
obtained from the data collection to facilitate its analysis. Coding is very important as it
helps the data to be categorized as required and transformed into the most appropriate
forms which can be easily analyzed by the tools and the software to be used in

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analyzing the data (Woolf, 2017). Some of the major types (examples) of the coding
process include source coding also called data compression, channel coding also called
error control, cryptographic coding, and line coding. Data compression is done to
remove redundancy from the raw data and thus enhance its transmission while error
control is done to minimize the errors which may be in the data and thus enhance its
processing.
5. Primary and secondary data in research
Primary data
In research, primary data is the original or the first-hand data which is collected
or observed directly from the field of research. Primary data may be obtained through
some methods such direct observation from the field, direct interviews, direct
questionnaires, or other methods which involve interacting directly with the respondents
of the research (Fallon, 2016, pp.147-155). Some of the examples of primary data
include recorded speeches, filled questionnaire forms obtained from the field of
research, and different samples or other materials obtained from the field during the
research. Primary data is used by the researchers who want to get accurate or specific
results in their research, and so they prefer collecting the data from the field themselves
other than using the data which was collected by other people (researchers) which may
not be accurate or may have been tampered with by other people. Again, we have
some kinds of data which keep on changing and using the data collected by other
researchers may not give the required results.
Secondary data
Secondary data is the data which is used by people (researchers) who did collect
it from the field but rather obtained it from some sources where it was recorded by the
people who did the actual research (Johnson and Sylvia, 2018, pp.2-11). Secondary
data simply means that the data was not obtained from the field but from other
secondary sources where it was stored by the people who collected it. Examples of
secondary data are census data stored in government websites, health data stored in
some hospitals websites, and different data stored on websites of companies.
Secondary data is mainly used by researchers when the actual process of data
collection is really difficult and complex and faced with many challenges such as high
financial costs and so much time needed, and this makes it quite hard or impossible to
conduct the actual data collection process. It’s good to note that although using
secondary may not give very accurate or specific results like the primary data, it helps to
obtain satisfactory results which meet the demands of the researchers.
6. Ethics in research
Ethics is the term used to describe the moral principles which govern the lives of
the people for them to live peacefully with the other members of their societies. The

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data collection process needs ethics approval since it involves getting the data of the
respondents some of which may be very sensitive data and getting such information
may be against the ethics of different societies (Wong and Nather, 2016, pp.149-179).
Before conducting the data collection process in this research, ethics approval is
needed where an ethics form will be filled giving the details of the data collection
process and assuring the people that the data collection process will observe the ethics
of the society. The respondents will be assured that the data which will be collected in
the research will be used for improving the quality of products and services offered by
Spark New Zealand and will not be used for any other purposes and won’t be disclosed
to the third parties who are not involved in the research.
7. Sampling
Sampling is the technique or process of selecting representatives (samples) of a
population with the aim of using these samples to study the characteristics of the whole
population (Gentles, 2016). Sampling is very common in research where the
researchers use some few samples or members of the population they wish to analyze
and understand. Using the whole population can make the research process very bulky
and tedious, and the researchers may not end up meeting the objectives of their
research, and that’s why they prefer working with samples.
Validity
In research, validity is the term used to represent the soundness or the state of
being logical and reasonable. Selecting a good sample to represent the whole
population in the research helps to improve the validity of the results which means that
the results obtained will be more logical and more reasonable and very close to the
actual results (Jansson and Nordgaard, 2016, pp.9-16). This means that the features of
the sample will be very close to the actual features of the whole sample, and so the
sample will serve to represent the whole population well.
Representativeness
Representativeness is the term used to describe the effectiveness of the sample
in representing the actual population. Representativeness can be used to define how
accurately and effectively does the population reflects in the chosen sample (Du et al.,
2017, pp.14-26). When the chosen sample gives many and correct details of the
population it represents, this kind of study is said to have good representativeness.
Reliability
Reliability is the quality or the degree of being trustworthy and consistent. In
research, reliability is used to mean the likelihood of obtaining good and consistent
results which can be used to make meaningful deductions and conclusions (Crowder,

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2017). Selecting a good and an appropriate sample helps the researchers to obtain
reliable results which can be used to make meaningful deductions and conclusions in
the research.

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References
Brace, I. (2018). Questionnaire design: How to plan, structure and write survey material
for effective market research. Kogan Page Publishers.
Callegaro, M. (2017). Importance of Surveys in the Era of Big Data. London: Routledge.
Crowder, M. J. (2017). Statistical analysis of reliability data. London: Routledge.
Du, B., Wang, Z., Zhang, L., Zhang, L., Liu, W., Shen, J., & Tao, D. (2017). Exploring
representativeness and informativeness for active learning. IEEE transactions on
cybernetics, 47(1), 14-26.
Edley, N., & Litosseliti, L. (2018). Critical Perspectives on Using Interviews and Focus
Groups. Research Methods in Linguistics, 195(3), 6-9.
Fallon, M. (2016). Primary Data Collection. In Writing up Quantitative Research in the
Social and Behavioral Sciences (pp.147-155). Sense Publishers, Rotterdam.
Gentles, S. J. (2016). Sampling in Qualitative Research: Insights from a Systematic
Overview of the Methods Literature. Sage
Heerkens, H., & van Winden, A. (2017). Solving managerial problems systematically.
Noordhoff.
Hislop, D., Bosua, R., & Helms, R. (2018). Knowledge management in organizations: A
critical introduction. Oxford University Press.
Jansson, L., & Nordgaard, J. (2016). Validity and Reliability. The Psychiatric Interview
for Differential Diagnosis (pp. 9-16). Springer, Cham.
Johnson, E., & Sylvia, M. L. (2018). Secondary Data Collection. Clinical Analytics and
Data Management for the DNP, 61(1), 2-11.
Sayles, L. R. (2017). Managing large systems: Organizations for the future. London:
Routledge.
Schiavone, F. (2017). Incompetence and Managerial Problems Delaying Reward
Delivery in Crowdfunding. Journal of Innovation Economics & Management, (2),
185-207.
Shmueli, G., Bruce, P. C., Yahav, I., Patel, N. R., & Lichtendahl, K. C. (2017). Data
mining for business analytics: concepts, techniques, and applications in R. John
Wiley & Sons.
Wicker, P., & Breuer, C. (2013). Understanding the importance of organizational
resources to explain organizational problems: Evidence from nonprofit sports
clubs in Germany. VOLUNTAS: International Journal of Voluntary and Nonprofit
Organizations, 24(2), 461-484.
Wong, J. L. Y., & Nather, A. (2016). Ethics for Research. In Planning Your Research
and How to Write it (pp.149-179).

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Woolf, S. (2017). An Active Learning Approach to Transcript Coding for Education
Research (Doctoral dissertation, Tufts University).
Züll, C. (2016). Open-ended questions. GESIS Survey Guidelines, 3(2), 2-5.