Supply Chain Management and Innovation in the UK Health Care Sector 1
[SUPPLY CHAIN MANAGEMENT AND INNOVATION IN THE UK HEALTH CARE
SECTOR]
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Supply Chain Management and Innovation in the UK Health Care Sector 2
RESEARCH METHODOLOGY
Research methodology represents the different procedures and approaches that a researcher uses
to identify, select, process, and analyse data and information on a given topic (Mukherjee, 2020).
This is helpful to the readers for them to understand and evaluate research validity, accuracy, and
reliability. This research methodology specifies and discusses the research techniques to be used
in this study on supply chain management and innovation in the United Kingdom care sector. Some
of the sections included in this chapter include the research approach that will be adopted, the
method to be used in collecting data, the sampling technique, the analysis techniques, and the
ethics to be considered.
Research Philosophy
Greenwood and Levin (1998) explained that research philosophy refers to knowing that specific
methods should be used to acquire data items connected to a particular phenomenon. Scholars with
the awareness of philosophical worldviews find it easy to outline reasons for using precise methods
effectively in a study. In the research onion shown below, Saunders, Lewis, and Thornhill (2012)
outline the primary research philosophies as interpretivism, positivism, pragmatism, and realism.
In this proposed study, the two philosophies considered for use are positivism and interpretivism.
Figure 1 Research Onion Source: Saunders, Lewis, and Thornhill (2012)
Supply Chain Management and Innovation in the UK Health Care Sector 3
Positivism Philosophical Approach
The positivism approach has the view that the social world can be objectively understood.
Saunders et al. (2012) acknowledged that the positivism approach has the intuition that the factual
knowledge acquired from observation should be trusted. In the positivism approach, gathering and
interpreting information are the only roles given to the researcher. The positivism philosophy
allows the researcher to use the deductive approach while focusing on the facts. The philosophy
assumes that a researcher is a separate entity from the research being carried out, which means
having that he/she has minimum interactions with participants during the research. Positivism
philosophy is highly quantitative, highly structured, and it involves the use of large samples.
Consequently, considering that the researcher will use the survey method which will allow the
collection of both qualitative and quantitative data, this philosophy will be adopted in the proposed
study. Thus, the fact that positivism largely relies on quantitative data makes the philosophy
qualify to inform the research proposed. Using survey method, the research seeks to collect
quantitative data through close ended questions. Positivism philosophy has been preferred because
it is based on empiricism which means verified data often obtained from senses.
Interpretivism Philosophical Approach
Interpretivism is the other philosophical approach to be used in the study proposed. In this
approach, the researcher integrates human interests in the research while interpreting the study
variables. The interpretivism philosophy has the assumption that reality requires assessment using
social constructions only, and they include; shared meanings, consciousness, language, and shared
instruments (Myers, 2008). The current study will be conducted under the inductive technique,
which involves searching for patterns in the collected data and developing explanations
Supply Chain Management and Innovation in the UK Health Care Sector 4
(Dantlgraper, Kuhlmann, and Reips, 2019). According to Pulla and Carter (2019), interpretivism
research philosophy promotes qualitative research methods leading to a better interpretation of the
research study variables and elements. Bevir and Blakely (2018), supports the selection of
interpretivism philosophy because it helps integrate the interests of individuals in the study.
Besides, the interpretivism research approach makes it easier for readers to understand reality and
truths in social constructions. Kivunja (2017) notes this philosophy accommodates diversity in
reality by evaluating a single phenomenon and can generate multiple interpretations. Here, the
researcher will be the social actor who will appreciate the differences between people and social
issues on the subject of supply chain management and innovation in the United Kingdom care
sector. In this case, the researcher will focus on the desired meaning in this study because it is
easier to interpret various issues through interactions with social issues and the social environment
(Kivunja, 2017). According to Bevir and Blakely, (2018), this philosophy allows for integration
of primary and secondary data for facilitating research validity and reliability.
Rationale of Using both Positivism and Interpretivism Research Philosophies
Pulla and Carter (2019), emphasised that research philosophies such as positivism and
interpretivism are essential for generating meaning through the research data collection process.
This is indispensable for understanding the social issue being investigated which in this case is the
relationship between supply chain management and innovation in the UK healthcare sector
through interactions with the research phenomena. These philosophies have been selected because
they will help in establishing shared meanings in the research variables. The philosophies are
simple and straightforward, and therefore it will be easy to use them for generating the desired
quantitative and qualitative research data (Bevir and Blakely, 2018). Besides, the use of both
philosophies will improve data validity and reliability because diverse opinions on the research
Supply Chain Management and Innovation in the UK Health Care Sector 5
problem will be generated. Importantly, each of these philosophies advocates for qualitative and
quantitative data methods. Therefore, combining them in the proposed study provides justification
for the researcher to collect both qualitative and quantitative data using a survey questionnaire as
the main instrument as described below.
Research Method
Survey Method
In the proposed study, the researcher suggests using the survey method. The survey method
involves questioning participants to collect data on the study topic (Jansen, 2010). Surveying is
the process of conducting research sends questions to research participants to respond to, and then
analyse the data statistically to draw a meaningful research conclusion. Surveys may be used as
primary methods for collecting data to test concepts, conduct segmentation research, establish the
level of customer satisfaction, reflect attitudes of people, and a set of other purposes (Krause et al.,
2018). Surveys can also be used in qualitative and quantitative research to test hypotheses about
the nature of relationships with a population and describe the population's specific aspects or
characteristics. The study will adopt the survey approach to collect data from the hospital managers
to replace the scheduled interviews due to the coronavirus pandemic. The method will guide the
researcher on recruiting the participants, collecting data, and utilising the research instruments to
answer the research questions (Knoke et al., 2017). The researcher intends to distribute the
questionnaires to 30 respondents (hospital managers) across different UK healthcare sector
institutions.
Survey methods in quantitative research use structured questionnaires to collect numeric data,
while qualitative surveys use open-ended questions to collect non-numeric data (Rahi et al., 2019).
Supply Chain Management and Innovation in the UK Health Care Sector 6
To test data validity and reliability, the researcher will use the test-retest reliability where a
question can be asked in different ways, and the respondent should provide consistent answers.
The survey will combine both closed-ended questions and open-ended questions to collect
qualitative and quantitative data in mixed research. The formulation of both sets of questions will
be dependent on research objectives. Rather than having a set of two questionnaires containing
open-ended and close-ended questions, the researcher will formulate a single questionnaire that
includes both. The close-ended questions will be prepared using a Likert scale such as (Strongly
agree, agree, neutral, disagree and strongly disagree). On the other hand, open-ended questions
will have a space that respondents will type their responses.
Survey research is useful in collecting data from large populations to obtain information
describing the characteristics of a large sample of participants in a shorter time. Survey research
can also be used in descriptive, exploratory, and descriptive studies (De Vaus, 2016). The
qualitative aspect of the survey will be included for this study because it is useful in data collection
and analysis, leading to understanding diverse concepts and opinions (Aspers and Corte, 2019).
This is essential for gathering in-depth insights and generating new ideas for answering the
research problem. Qualitative research methods will be used in the study because they are designed
in a way that helps to reveal behaviours and perceptions of the research target audience on a given
topic (Hammarberg, Kirkman, and de Lacey, 2016). The researcher will adopt the case study
research method in the current study, where open-ended and close-ended questions will be used.
These methods have been selected because they generate highly descriptive data and information
(Timans, Wouters, and Heilbron, 2019).
The close-ended questions included in the survey will amount to providing quantitative data.
Quantitative data methods are used for providing emphasis on objective measurements and the
Supply Chain Management and Innovation in the UK Health Care Sector 7
mathematical, statistical, and numerical analysis of the data, which is gathered by surveys in the
case of the proposed study. The focus of the quantitative aspect of the survey through close-ended
questions is collecting numerical data and generalising it across a large population while
explaining a specific phenomenon, which is the relationship between supply chain management
and innovation in the UK healthcare sector. The goal of the quantitative aspect of the study will
be establishing the relationship between the dependent and the independent variables with the
target population. Various research designs can be utilised in such a study, and they include
descriptive, exploratory, and explanatory.
Surveys measure a wide range of valuables, including factual information, behaviours, beliefs,
attitudes, traits, and people’s preferences. For this reason, the approach is used in several research
designs to deliver the desired results. Additionally, surveys are useful in collecting data remotely
from a large population (Draugalis et al., 2018). In a study population where the research
respondents are geographically in different locations, the approach can help the researcher collect
the data without moving to the participants' physical location. As a result, the researcher saves both
time and resources which would have otherwise been spent in the research process. In the current
technology era, online surveys are used to collect data from a large population in the cheapest and
fastest way, increasing the research processes' efficiency (Rahi et al., 2019). Also, the approach is
useful in the current period when people are observing social distance following the World Health
Organisation guidelines on the prevention of spreading of the Covid-19 virus.
Surveys are unobstructed, giving the participants the space to respond at their convenience and
without disruption from the researcher, making it a preferred method for respondents.
Additionally, the surveys allow the respondents to provide honest answers where there is minimal
human interaction. In a questionnaire survey, respondents provide real answers (Krause et al.,
Supply Chain Management and Innovation in the UK Health Care Sector 8
2018). The researcher is not present as they complete the questions, thus will not feel the need to
give a specific answer to create a different impression from the truth. However, the researcher
must reassure the respondents of privacy and confidentiality of their personal information. Surveys
also help study undefined populations like the homeless population and unregistered immigrants
who are not easy to sample. The survey helps detect small effects even while analysing multiple
variables. Surveys allow comparative analysis of different groups, which gives more detailed
results for a study.
The research will use the questionnaire surveys, which can be administered online, via email, or
through group administration (Krause et al., 2018). The research participants will be informed
about the research purpose and the questionnaires given. The respondents will be expected to
answer the questions in writing, unlike the interview surveys where the respondent provides the
answers through verbal response. A questionnaire survey consists of questions to get responses
from the respondents in a standardised manner. The questionnaire surveys may contain structured
and unstructured questions depending on the data the researcher seeks to collect and the research
design (Draugalis et al., 2018). Unstructured questionnaires allow the respondent to provide
answers in their own words, thus not limiting them to select a response among those provided by
the researcher. This allows the researcher to collect qualitative data and may enable new facts to
emerge. The structured questionnaires provide multiple answers for the respondent to choose
(Berends, 2016). The structured questionnaires are analysed through statistical analysis, while the
unstructured are more complex and require coding to identify the themes in the data for analysis.
The survey questions are designed to be easy to read and understandable for the respondent, as the
researcher will not be with them to explain what they require in each question. This will ensure
the respondent answered in a meaningful manner to achieve the research objectives effectively.
Supply Chain Management and Innovation in the UK Health Care Sector 9
However, surveys will be administered through the internet, and this may lead to having a lower
response rate. Some participants may receive the questionnaire and fail to complete and send it
back to the researcher. There may also be delayed response, which may affect the researcher’s
timeline. Therefore, the researcher must continuously follow up with the respondents to ensure a
higher response rate within a shorter time (Knoke et al., 2017). The approach is also not effective
for topics that may require clarification to make a question understandable. The method is also not
appropriate for research that would require detailed written responses as the respondents may find
it too demanding and fail to complete the questions. The current method of administering survey
questions is through online and web surveys. The respondents will receive an email notification
requesting them to participate in the survey and a link where they are redirected to the
questionnaire (Knoke et al., 2017). Alternatively, the questionnaire may also be attached in the
email and where the respondent should download, complete, and resend it.
Secondary Data
The researcher will supplement the survey data with secondary data to answer the research
questions or examine an alternative view of the study question from previous studies. The
comparison helps build new knowledge (Draugalis et al., 2018). Questionnaire surveys are
effective when the respondents have knowledge about the study topic and can confidently answer
the questions to the best of their ability. Also, with the interest of time and finances, the survey
method will provide data that will be easier to analyse while providing all the necessary details to
answer the research questions. A questionnaire survey will help collect data from a larger audience
instead of interviews, which would be limited to a smaller sample as it is time-consuming and may
involve more cost than surveying (De Vaus, 2016). The researcher will use secondary data to
overcome the human bias of respondents. Since the questionnaire surveys are self-administered,
Supply Chain Management and Innovation in the UK Health Care Sector 10
the respondents may provide inaccurate information. Using secondary data that is evidence-based
will help identify any irregularities and give a conclusion that highlights any such data
inconsistencies (De Vaus, 2016). Some of the data sources that will be used to obtain the secondary
data include journal articles, past study reports, government reports and credible websites that
relate to supply chain management and innovation in the UK healthcare sector. The keywords to
be used in searching for appropriate data sources are; supply chain management in the healthcare
sector, supply chain management and innovation in the healthcare sector, and supply chain
management and innovation in the UK healthcare sector. The inclusion criteria for sources will be
full articles, written in the English language, and sources related to healthcare, innovation and
supply chain. Sources not in English, only abstracts articles, and those not associated with the
study’s topic will be excluded.
Research Design
Exploratory research studies the hypothesis of research and also investigates research findings.
Exploratory research utilises qualitative research, as explained by Saunders et al. (2012). The
design uses inductive research methods to generate new insights. Moreover, exploratory research
designs assess issues that lack appropriate definitions. The research method gives the researcher a
better understanding of the study question, although the results are not conclusive. Characteristics
of the design include; it is interactive and open-ended, it has low costs, and it is time-consuming.
Exploratory research enables a researcher to get more findings making it essential for a researcher
to have flexibility when adapting to various research changes as the study progress.
On the other hand, explanatory research design highlights a research phenomenon. Saunders et al.
(2012) depicted that explanatory research describes the study and the connection of its variables.
Supply Chain Management and Innovation in the UK Health Care Sector 11
The study outlines the cause-effect relationship. Moreover, it gives answers to why, how, and what
questions regarding the phenomena. The approach is also essential in that it connects qualitative
and quantitative data. Researchers use explanatory research to address poorly researched issues.
Therefore, the researcher must prioritise the issues and provide well-researched models and
operational definitions. The research design does not conclude issues. However, it helps the
researcher to know the cause of the issue efficiently. Explanatory research helps the researcher
better understand a research question, formulating better conclusions, and enhances the availability
of various research sources (Blatter and Haverland 2012). Examples of popular explanatory
research designs are focus groups, depth interviews, literature research, and case analysis.
For the proposed research, the descriptive research design will be used to examine the relationship
between supply chain management and innovation in the UK healthcare sector. It is vital to have
a robust research design because it offers an opportunity of describing the subject under study,
often formulating a study hypothesis through grounded theories. A descriptive research design was
favoured because it attempted to establish associations between the dependent and independent
variables. According to Saunders et al. (2012), it is significant in highlighting the study question’s
characteristics as the concentration is on the “what” and not the “why.” Using the descriptive
research design in a study means the researcher can determine multiple questions using the same
sample group. Analysis of the selected target population is done at a certain period. Also, it is the
best research design for enhancing the reliability and validity of the findings. The researcher can
identify the correlations, frequencies, categories, and trends of the study’s focus through it. Among
the critical rationale of using descriptive research, it supports using survey instruments,
particularly open-ended and close-ended questions.
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In summary, the data collection process will focus on identifying research variables and issues in
line with the research problem. Using the research approach, data will be collected, analysed,
interpreted, and acted upon for answering the study issue. The data collection process will focus
on the questionnaires that will include open-ended and closed-ended questions. In this case, a case
study approach will be adopted where participants will be recruited by the researcher using
telephone calls, social media platforms, and email. They will be informed of the study objectives,
and informed consent will be sought for their participation. The selected respondents will then be
provided with the questionnaires to respond to in line with the research problem. Observation will
also be used in the collected data. Supplementary secondary data will be collected from diverse
online and physical secondary sources, such as books, journals, government publications, health
care reports, among others.
Population and Sampling Technique
Convenience Sampling
The study focuses on supply chain management and innovation in the United Kingdom health care
sector. In this case, the study population will be composed of the United Kingdom health care
sector stakeholders, policymakers, and organisations. Convenience sampling is the sampling
method that will be used in this study. Chiefly, the researcher will depend on the respondents'
convenience when selecting the members of the population to participate in the research study
(Palinkas et al., 2015).
Convenience sampling is a non-probability method where the research participants will be selected
due to their proximity and convenient accessibility to the researcher (Sedgwick 2013). Convenient
sampling is the most common sampling method since it is economical, simple, incredibly prompt,
Supply Chain Management and Innovation in the UK Health Care Sector 13
and fast. The sampling method is also known as availability sampling, grab sampling, or accidental
sampling. The respondents included in this study criteria do not have to be part of a sample.
Therefore, researcher will a simplified job of including elements in convenience sampling. The
respondents depend on the researcher’s proximity to be part of the research sample. An example
of convenient sampling is when a health facility distributes pamphlets to random participants in a
street. The facility uses the information to address critical health issues that arise regarding their
study phenomenon, and they also use the feedback to assess how the treatment is perceived.
Sedgwick (2013) explained researchers use convenience sampling to observe opinions,
viewpoints, and habits in the easiest way possible. The researcher will use convenience sampling
due to its benefit to other studies. For instance, in a pilot study, the samples are used since they
allow the researcher to acquire essential information and trends in the research without using
complicated samples such as randomised samples. The method is also essential for documenting
that a certain quality of a phenomenon or a substance occurs in a particular sample. Convenient
sampling enables the researcher to detect relationships among the study subjects.
Researchers use convenience sampling in the initial stages of a research survey due to its ability
to produce easy and quick results (Suen Huang and Lee 2014, p.105). The method is vital for
researchers who wish to get insights quickly without using heavy investments in the research. The
method is also preferred due to the few rules one has to follow. The researcher does not need to
filter participants from the audience or to go through a checklist. Additionally, this process wastes
time for other techniques, but the data is easily collected from readily available subjects in
convenience sampling.
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Compared to alternative sampling methods, convenience sampling is easier to analyse. This,
therefore, means that finding research participants, data collection, and analysis is done with ease,
thus making convenience sampling the most efficient method for generating a hypothesis and a
quick method of concluding research. Convenient sampling helps the researcher to acquire data
from difficult sources (Sedgwick 2013). For instance, if a company researcher needs to acquire
data from a rival company, they might find it difficult to acquire access to the premises. Moreover,
employees might be busy to participate in research. Therefore, by using convenience sampling,
the researcher can collect data from the employees during their free time, such as lunchtime hours
or departing. Convenience sampling is one of the few techniques that researchers use when they
cannot get a list of participants from a population. Moreover, when a researcher is on a shoestring
budget, convenience sampling is the best method for data collection.
Data Analysis and Measurement
The selected approach to analysing qualitative data obtained through open-ended questions and
secondary data sources is thematic analysis while quantitative data from close-ended questions
will be analysed through descriptive statistics (Bruce et al., 2016; Stroud et al., 2017). Inductive
reasoning will be applied to making broader generalisations (Dantlgraper et al., 2019). The data
analysis process will facilitate the deriving of absolute meaning from the collected data. The
analysis process will begin with the familiarisation of data, revisiting the research objectives,
developing a framework before the researcher identifies all patterns and connections that exist
between the collected data and research objectives. The ordinal approach will facilitate data
measurement because it depicts the relationship between research variables (Arvidsson, 2019).
Supply Chain Management and Innovation in the UK Health Care Sector 15
Thematic Analysis
Thematic analysis will be done using a six phased approach (Alhojailan 2012). The researcher
familiarises themselves with the data (in this case both the qualitative primary data and secondary
data) in the first phase. Here, the researcher watches video data, listens to audio-recordings, and
reads written data such as transcribed interviews. This phase aims to make the researcher familiar
with the content featured in the dataset and observe the crucial components of the study question.
The second phase involves generating initial codes. The researcher codes the data to analyse
information systematically. The codes identify labels for data features that may be important to the
study question. Coding provides a vital summary of the information and also describes data
content. Coding ends when all the data relevant to a code has been collated. The number of codes
generated depends on the topic at hand and the coding precision. Phase three involves searching
for themes. The researcher’s analysis now takes the form of themes rather than codes. Themes take
note of essential data aspects in relation to the phenomenon under study. Moreover, they represent
part of the generated response from the dataset. In this phase, the researcher reviews the code and
identifies similarities between them. The themes are then generated by collapsing similar codes to
ensure that they describe a coherent data pattern. The researcher also evaluates the relationship
between themes in this phase. The generated themes are then reviewed in relation to the dataset in
phase four. In case of a mismatch, revision, discarding, or creation of additional themes is done.
In phase five, the researcher defines and names the themes where their uniqueness is specified.
Phase six involves producing the results. Since deep analytic work begins in phase five, the
transition from phase five to six is blurry. A good theme has a concise, informative, and catchy
name.
Supply Chain Management and Innovation in the UK Health Care Sector 16
Thematic analysis is used when a researcher wants to know about people’s opinions, experiences,
views, values, or knowledge from a set of qualitative data such as survey responses, social media
profiles, and interview transcripts (Alhojailan 2012). Researchers mostly use thematic analysis due
to its accessibility and flexibility. Thematic analysis is useful in qualitative research since it
provides a way of systematically analysing data and teaching the mechanics of coding, linked to
broader conceptual or theoretical issues. The thematic analysis makes research findings available
to the larger population. When using this method, the researcher gets the flexibility to use other
approaches such as inductive and deductive research approaches. If the researcher uses an
inductive approach, then the themes are created depending on the data. In a deductive approach,
the researcher uses preconceived themes that are expected to be reflected based on existing
knowledge and theory (Braun Clarke and Terry 2014). The researcher proposes to use Nvivo
software for qualitative analysis.
Descriptive Statistics
While thematic analysis will be used in analysing qualitative data, descriptive statistics shall be
utilised in the analysis of quantitative data. Describe statistics refers to analysing data in a manner
that shows, describes, or summarises data in a meaningful way that patterns emerge (Saunders,
Lewis, and Thornhill, 2012). Descriptive statistics do not allow a researcher to make conclusions
beyond the data that has been analysed or make conclusions on the hypothesis made. These
statistics only describe the data. These statistics give raw data meaning, which makes it easier to
interpret collected data. Simple graphical presentations such as charts and graphs, frequency tables,
and a percentage will present the analysed data.
Supply Chain Management and Innovation in the UK Health Care Sector 17
Descriptive statistics have been selected to analyse the quantitative data because of the ability to
present quantitative descriptions in a manageable manner. Through descriptive statistics, the
researcher will be able to simplify large amounts of data from the close-ended questions sensibly
and accurately. Each of the descriptive statistics used, such as percentages or graphics, will help
the researcher reduce lots of extensive data into simple summaries. At the same time, the use of
descriptive statistics enables the researcher to have a powerful summary that facilitates
comparisons. If the researcher presents the raw data from the close-ended questions, it would be
a challenge to visualize what the data shows or means in relation to the questions being
investigated. Therefore, descriptive statistics are preferred because they will ensure the
researcher presents data meaningfully and subsequently make valid conclusions regarding the
research question. The researcher will use SPSS (Statistical Package for the Social Sciences) for
quantitative analysis.
Ethical Considerations
One of the critical ethics to be considered will be obtaining informed consent from the respondents.
Informed consent will be sought from the study participants before the data collection process
commences (Burles and Bally, 2018). In the course of conducting the study, no harm will be done
to the respondents. Moreover, their privacy and confidentiality will be observed throughout the
study. Here, the researcher will respect the participant's anonymity (Cacciattolo, 2015). This means
that neither the participants' names nor their designations will be revealed in any study’s material.
Role conflict, biases, and any issues to do with the researcher's interests will be addressed to ensure
the study generates accurate, valid, and reliable results (Burles and Bally, 2018). Only the relevant
components will be assessed. The collected data and information will only be used in this study
and serve academic purposes. The data collected will be stored in a well-protected folder in the
Supply Chain Management and Innovation in the UK Health Care Sector 18
computer to ensure unauthorised persons do not access it. Additionally, all respondents will be
informed of their right to withdrawal from the study without giving any meaningful reason.
Supply Chain Management and Innovation in the UK Health Care Sector 19
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