RSCH 600: Research Methodologies & Inquiry

Running head: THE EFFECT OF LIGHTING CONDITIONS ON EMPLOYEE PRODUCTIVITY IN
AN OFFICE ENVIRONMENT 1
The Effects of Lighting Conditions on Employee Productivity in an Office Environment.
Loujeine Kamoun (1510363)
University Canada West
Professor: Dr. Abera B. Demeke
RSCH 600: Research Methodologies & Inquiry
March 20, 2016
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The Effects of Lighting Conditions on Employee Productivity in an Office Environment.
The Topic
The effects of lighting conditions on employee productivity in an office environment.
The Research Problem
In today’s world, leading organisations have a clear understanding that in order to
achieve their set objectives, the development and increase of their employees’ performance is
essential. In fact, employees are considered to be the engine that allows an organisation to grow,
improve, and innovate (HOK, n.d.). Therefore, every organisation must provide the correct
atmosphere to encourage well being and promote the productivity of their employees. One of the
main factors to look at is the physical environment where an employee spends an average of
eight hours a day.
Many small developing organisations have expressed concern about the decline in mood
and productivity in some departments. As an example, Special Events Company has been
gradually growing, and therefore more employees have been hired, and in order to accommodate
them, all walls and offices have been eliminated and an open-space workplace has been adopted.
As a consequence, employees have reported insufficient lighting and in parallel, a decline in
productivity has been noted. I believe that the decline in productivity is linked to insufficient
lighting, and want to further investigate the issue. Naturally, there are many factors that can
affect productivity, nevertheless for this paper, it was decided to select only lighting, while
keeping all things constant, to have a more thorough understanding of the link between lighting
and productivity.
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The Evidence from Literature Justifying Problem
Over the last two decades, specialists, such as architects and interior designers, have been
more focused on studying the influence of lighting conditions on employee well being and
productivity. This was prompted after the 1970s energy crisis that urged designers and architects
to reassess the existing lighting standards, which in turn resulted in a steady decrease in lighting
quality in offices (Marans, 1989). Lighting has been proven to have a great impact on people’s
psychological and physical health, which then affects their performance and consequently overall
productivity (Dilani, 2004). For instance, inadequate lighting levels may lead to fatigue and
discomfort. Important factors to consider when talking about lighting are colour, brightness, and
direction. Moreover, upon further investigation, it has been established that workers who
consider having high quality lighting in their office, have a better and more positive attitude.
The Research Objectives
The aim of this research is to determine how lighting is perceived by employees working
in an office environment, as well as its ramifications on their productivity.
The Research Questions
1. What lighting options constitute “good” or “bad” workspace conditions for a productive
atmosphere?
2. Are employees provided with adequate lighting in order to efficiently carry out their daily
goals?
3. Does good lighting conditions impact the productivity of employees working in an
office?
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The Research Approach
In order to successfully tackle these main questions, I will be conducting two main
research projects. The first will be an assessment of employee satisfaction with the lighting, and
how they feel this affects their work. A survey will be handed to and filled by a sample of
diverse professionals working in different workplaces. The second will consist of employees’
productivity assessment done by their respective department heads. The results of both
assessments will be studied to find the link between the employees’ answers and their
department heads. A comparison between the results will be done in order to analyse the
correlation between employees who assessed the lighting as insufficient and their productivity
rating.
Lighting satisfaction assessment (LSA).
The LSA project will be a survey given to employees that will answer the following main
questions:
LSA 1: Do the employees feel that the lighting they are being provided is sufficient for work
maximization?
LSA 2: Do the employees think that by changing the lighting in their floor, they can become
more comfortable thereby maximizing their productivity?
LSA 3: Do different employees prefer different lighting conditions?
LSA 1: This question will provide us with crucial information about whether or not they feel that
the company has not provided the adequate atmosphere for efficient production. A majority
answer in this question may be the deciding factor in making the decision to change.
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LSA 2: Here, the employees share their beliefs on the matter at hand. This question may not be a
decision changer, but it will make the employees feel that they are at least part of the decisionmaking process within the company. It is also a way for the employees to feel somewhat
responsible for the decisions they make on behalf of their departments.
LSA 3: This is a kind of control question; it shows us the preferences of the employees in
comparison with each other. It may give us a majority in a specific preference and therefore
dictate the next course of action, choosing a light setting.
Employee productivity assessment (EPA).
The EPA questionnaire will be given to the department heads who will assess the
productivity of the employees who will be taking part in the LSA. The aim of the EPA
questionnaire is to be a guiding factor in the comparative result of the overall project. This will
aim at answering the following main control questions:
EPA 1: Who was chosen for the LSA project?
EPA 2: What are the productivity ratings of the people who were chosen?
EPA 1: The answer to this question will provide us with the necessary comparative information
on which we will base our link between the EPA and the LSA.
EPA 2: This question is designed to give us a non-biased assessment of the employees’
productivity levels in that they do not see this number and are unaware of its existence. The
result of which will be used as the comparative data to the LSA on which a general decision will
be made on the main research question.
Literature Review
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It has been widely contested and researched that lighting has a direct effect on a person’s
psychological welfare. In the studies conducted by Kuller, Ballal, Laike, Mikellides, and Tonello
(2006), and Mills, Tomkins, and Schlangen (2007), one can make very educated assumptions on
how light can affect one’s moods. This relationship is evident in the persistence of Seasonal
Affective Disorder (SAD) during seasons when people are exposed to less daylight. People with
sub-syndromal SAD have reported improvements in their mood, energy, alertness, and
productivity while being exposed to bright lighting in the mornings and evenings. Moods were
tested and results show that there was a substantial difference between people who lived near the
equator and those who did not (Kuller, Ballal, Laike, Mikellides, Tonello, 2006). We can deduct
from the tests that people who live in areas that are exposed to more daylight are evidently
happier than those who live in areas with generally less daylight. This result was also shown with
lighting that was said to be at its best in the workplace (Kuller, Ballal, Laike, Mikellides,
Tonello, 2006). The aim of this literature review is to find relevant precedents to support this
paper’s theories, as well as scientific studies to endorse the research questions.
In a more detailed view on lighting with its regard to business, we see studies by the
aforementioned authors that reveal very similar data. Tests that measured personal preference
showed a partiality to workplaces with windows; the lack of which could affect performance and
well being negatively (Kuller, Ballal, Laike, Mikellides, Tonello, 2006). The importance of
brightness and the wavelength of ambient light have been increasingly evident in relation to their
effects on task completion, human biology, circadian system regulation, the biological clock,
mood, and alertness (Mills, Tomkins, Schlangen, 2007). Many elements come into play when
attempting to figure out which lighting option should be considered for illuminating the
workplace. Whether it be daylight or electric light, full or non-full spectrum, blue or white
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spectrum, dynamic or traditional, direct or indirect, and low or high intensity, a company facing
productivity issues should view this as a money-saving and an energy-saving waving to salvage
the situation; and maybe even improve it. A study conducted by Kaida et al. showed that the
natural light through a window increases pleasure and decreases sleepiness within 30 minutes of
exposure (De Kort, Smolders, 2010). In another study of preference, results show that a vast
majority of people would like to work in a place with a window, furthermore, having control of
the blinds, has an even higher preference (Veitch, Newsham, 2000). In a workplace, it is now
believed that symptoms of stress were present in people who were working under lighting that
was non-full spectrum, while in people working under full spectrum lighting showed none
(Martel, 2005).
In comparison with white light, blue-enriched light resulted in an improvement in
irritability, eyestrain, eye discomfort, eye fatigue, blurred vision, and difficulty focussing and
concentrating. It was also proven to improve alertness, performance, and evening fatigue (Viola,
James, Shlangen, Dijk, 2008). A very notable addition was the study that concluded that bluelight illumination was more effective in alertness and information processing speed than yellow
light (Hoffman, Gufler, Griesmacher, Bartenbach, Canazei, Staggl, Schobersberger, 2008).
“Controllable lighting conditions were rated as more comfortable than conventional fixed
conditions” (Veitch, Stokkermans, Newsham, 2011, p. 199). Statistics prove that in the cases of
multi-directionality, ease of movement, and the power to switch lights on and off individually,
people will opt for the control over their lighting system (Veitch, Newsham, 2000). In conclusion
to a study, it was said that, “Individual control over lighting can help to overcome reductions in
motivation and attention that develop over the course of a working day” (Boyce, Veitch,
Newsham, Jones, Heerwagen, Myer, Hunter, 2006). If a company is careless about lighting, it
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may lead to many issues that hinder productivity. Short-term illness, physical and psychological
long-term issues can be the result of negative stress; and negative stress can be caused by
prolonged exposure to poor lighting conditions (Bluyssen, Aries, Van Dommelen, 2010).
With all the information and gathered statistics that are available to us in this day and
age, it is surprising to know that “The American Society of Interior Designers reported that 68
percent of employees complain about light in their offices” and that “51 percent of the US
workforce reported sleepiness on the job interfering with their work” (Martel, 2005). This
information shows that though the information exists and is mostly available, companies have
still not taken the lighting issue of their workplaces to be of high enough priority to make
changes that could potentially benefit them greatly. Since there is such a high percentage of
people who complain about the lighting conditions in their work, this begs the question of
whether or not lighting actually impacts productivity. It has been revealed that having lighting
that mimics natural light can in fact improve performance greatly. In a case study done at Xerox,
productivity was increased and complaints about health decreased significantly when they
changed their lighting system. In addition, tasks were measured to have been completed 13
percent faster than before the change (Martel, 2005).
General performance is said to improve under high colour temperature and bright lighting
systems due to its positive psychological effects (de Kort, Smalders, 2010). Work engagement
levels stem from work satisfaction; this in turn is affected by the work environment. Hence, if a
room or office is deemed attractive, the positive mood then translates into productivity (Veitch,
Stokkermans, Newsham, 2011). It has been shown that performance in tasks improved with
lighting systems that improved visibility (Veitch, Newsham, Boyce, Jones, 2007). With lighting
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that is controllable, Juslen et al. reported a 4.5 percent rise in productivity in offices that had the
option (Hoffman, Gufler, Griesmacher, Bartenbach, Canazei, Staggl, Schobersberger, 2008).
In conclusion, as studies have shown, lighting can affect a person’s well being in general;
depending on the geographic location and the amount of natural light exposure, people’s moods
can differ. To tackle the topic at hand, after examining and exploring research on the “bigger
picture”, we could therefore confidently narrow it down. After reviewing a wide range of
literature about lighting in workplaces, we can see that there is a very strong coloration between
the appropriate lighting and productivity. In fact, when talking about the appropriate lighting, we
discovered that there are many different ways to categorise the factors that affect well being
which in turn affects productivity: the amount of light, the nature of light, the colour of light, the
direction of light among many other factors. All this information will help guide and define the
necessary elements and research methods to challenge while advancing within this research
paper.
Methodology
Study design.
The nature of this study is exploratory; the main focus here is uncovering insights and
defining the issues. Since the problem is not distinctly proven, an exploratory approach must be
taken. Consequently, as this type of research mainly uses secondary research, reviewing existing
literature is crucial. As the purpose of this research is to gain a better understanding of a
phenomenon there is a prerequisite in gaining experience in formulating a more definitive study.
Since the outcomes of this type of research are not definitive, it is not usually projected onto the
general population. Due to the nature of this study, a quantitative method of data collection will
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be used. The results in this method are easier to compare and summarize (Saunders, Lewis, &
Thornhill, 2012). For this research, we chose to use quantitative methods because we need the
data collected to translate into numerical results. These results will help us measure and quantify
productivity. Productivity can be measured in many different ways, one of the most commonly
used is by measuring output per unit of input, in other words, it is conveyed as a ratio of units of
product per worker per hour, and therefore the formula is: units of output divided by units of
input. However, due to time constraints and lack of information about the different targeted
companies’ figures, it was decided that the way to determine productivity in these companies
was to have the supervisor fill in a form determining the different productivity rates of every
employee participating in the research, which will be further explained later. The method is not
the most reliable and therefore the results will not be generalised on the population; instead, we
can only assume the results on the sample basis. The study in itself will consist of two surveys;
the first is an Employee Productivity Assessment (EPA), which will be given to the manager of
the department conducting the second survey. This specific survey will be a brief overall
assessment where the division head will fill in the details of the chosen employees and then
proceed to grade the productivity by rating the overall performance (see annex 1.1). The Second
is the Lighting Satisfaction Assessment (LSA), which will be given to employees. This will
assess the employees’ satisfaction with the lighting provided and how they feel this affects their
productivity. The surveys are designed to develop a theory of what lighting conditions should be
standard in office spaces in order to maximize employee productivity, hereinafter to be known as
Lighting Standard for Productivity (LSP).
Sample design.
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The study will be conducted via the use of the specifications and methods of Quota sampling
but within the context of Convenience Sampling. Because this research paper is an exploratory
paper, and my lack of contacts in Canada, the Quota methods would be the best approach to the
collection of data. The Quota Sampling method is the procedure of obtaining participants by
classifying the population as per specific properties. Afterwards, once the preferred proportion to
sampling from each category is decided, a fixed quota will be determined. This type of sampling
insures the surveys’ completion in a timely manner, and with moderate cost. I believe that this
sampling method is ideal for this type of research, as it does not require a list of population, is
efficient to gain insight on a chosen research question, and is time and cost efficient. It also
covers a wide range of differences as it tries to emulate and represent the general situation.
The target population for this study is people that work full-time desk jobs in the offices
of four companies that represent different industries; architecture, banking, telecommunications,
and insurance. I believe that these four industries are adequate representation for most office
environments, and I believe each category will provide the research with different insights and
inputs that would help us acquire the maximum and most accurate information for this study.
The other reason we chose four different companies is to minimize sampling errors. By having a
larger number of sampling units to represent as much of the population as possible, we hope to
diminish sampling errors. Therefore, we decided that these four companies could be
representative of the different offices in the workforce. As previously mentioned, this study is of
an exploratory nature because a trend can be observed, and the purpose of this paper is to seek a
better understanding of the theory.
In the first category, an architecture and design firm was selected; AGI Architects is a
Spanish and Kuwaiti firm that is well known and established in both countries. The company has
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undertaken many big projects and was granted many awards. I chose this company because it is
neither small nor big. It is a medium sized company but its projects have earned it the accolade
of one of the best architectural firms in both Kuwait and Spain. The employees are from different
backgrounds and cultures and that would be beneficial to our study. For the second category, a
local bank called Commercial Bank of Kuwait has been selected. It is the third largest and most
prestigious banks in the country, and has recently undergone major renovations due to
rebranding, which I believe would give us a great opportunity to explore whether adequate
lighting has been given importance. In the third category, Vodafone, an international
telecommunication company has been selected. This company was selected because it is a huge
multinational organization and the work standards of every branch around the world are closely
regulated to match specific sets of standards. In this case, it will be interesting to see the response
of the employees of Vodafone Kuwait and compare them to the overall standards. Finally, for the
last category, Warba Insurance was selected because it is one of the oldest and biggest insurance
companies in Kuwait, but also their offices are in an old building that has not had any
renovations or made adequate changes over the years. For this case, it would be interesting to see
the result in comparison to the newer and most advanced buildings.
The sample will be selected by my contacts within each industry; the ideal number of
complete surveys is ten from each company. Since there is a time limit on the completion of this
research, and the ideal Quota may not be met, as a result of the quota sampling, a predicted
margin of error of two per company has been set; making the maximum number of participants
forty and the minimum number thirty-two. The following will be the criteria that will be given to
the contacts to advise them of which participants they should choose from: (1) current employees
of the company, (2) full-time employees working six to eight hours a day, (3) five male, and five
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female, (4) two employees aged 20 – 30, three aged 31 – 40, three aged 41 – 50, and 2 aged over
51, and (5) employee must have been working at the company for a year or more. The Human
Resource department will be asked to overlook the selection of the participants. These criteria
have all been set to avoid bias from the department heads.
The first criterion was chosen, as I would like the people filling the surveys to have a
fresh memory or a current experience of the main questions of lighting and productivity. The
second was chosen because of the need for prolonged exposure to light in the workplace. Parttime employees will have a smaller probability of complication or even noticing the issue we are
researching. The third criteria was chosen for gender equality purposes and it may lead us to
information regarding lighting affecting productivity differently between women and men. The
fourth is to get fair representation for all age groups within the company. If the minimum
accepted surveys, 8, are to be filled, then the recommendation will be for the omission of one of
each of the three-person groups. The fifth criteria is there for the guarantee that the employee
filling in the survey is not new and has not been exposed to the lighting conditions for them to
affect the person, and for there to be sufficient information on that person’s productivity within
the company.
Measurement/variables.
Due to the fact that this research paper will be using quantitative research methods,
numerical data will be of outmost importance. (Charles & Mertler, 2002). In order to further
develop knowledge, hypotheses, measurement tools, and test theories, postpositivist statements
will be relied on. To be able to present accurate and consistent results or scores, variables must
be isolated and linked to determine the relationship between them, to do so, the variables and
tools to investigate must be well determined.
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The research question “Does good lighting impact the productivity of employees working
in an office?” determines this study’s variables. Employee productivity is considered to be the
dependent variable, where the result may vary as a reaction to changes in other variables. The
quality of lighting, in this case, is believed to be the independent variable, which is being
manipulated to assess and determine its bearing on the dependent variable (Saunders, Lewis, &
Thornhill, 2012). My hypothesis is that the better the lighting conditions, the more productive the
employees are. Hence, the productivity variable is dependent since it relies on the results of the
lighting for it to change.
Data collection instruments.
The ways in which data is to be collected are a form that will be given to the heads of
department or managers of the participating departments; these are also the contacts mentioned
earlier. This form will give us a managerial view on the individuals’ productivity ratings.
However as previously stated, the selection of the participants will be overseen by the Human
Resources departments to eliminate bias. These individuals are then to fill in the LSA survey that
primarily asks about their satisfaction levels with the lighting conditions in the workplace. It
gives us an idea of the times in which they feel more inclined to work, and the reasons why there
are times in which they do not. The survey also touches on some basic productivity questions
that may shed a more descriptive light on the form that was given to the manager, the EPA.
Data collection methodology.
Collection and interpretation methods.
To make sure that the survey is completed in a timely manner, the researcher will deliver
a package with both the LSA and EPA surveys to the four different companies by hand, and will
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then be present at the company during the procedure but without being in contact with the
employees to avoid the feeling of coercion and make sure that they are comfortable and relaxed
whilst answering the questions. The contacts will then choose the employees that will partake in
the survey. Once the EPA and LSA have been filled, the surveys will be collected by the
researcher and put into a sealed package to ensure the privacy and anonymity of the participants.
Once all the completed forms are collected, the data will be entered into an excel table that will
be designed to translate the information into various forms of usable displays such as graphs or
models.
Challenges to data collection.
The main challenges to this study will be the lack of insurance that other variables that also
affect productivity will remain unchanged. For this we are relying on the workplace’s daily
routine to be constant and that the employee taking part in the survey will answer the questions
in accordance to their overall experience and not just the recent experience. Since the EPA is
being measured and quantified by the contacts, preference of staff likeability could cause bias.
Hence, the research will be given only to people whose judgement have never been in question,
are known to have high ethical values, as well as having the HR department oversee the
selection. Also, the employees could want to portray their company in the best light thus
answering the survey in a biased manner. The employees’ possible lack of knowledge on the
issue at hand could lead to an inaccurate assessment of the current conditions. More empirical
evidence cannot be obtained due to the lack of lighting measurement apparatus, which is lacking
due to the lack of a lighting engineer or designer on site to compare the current lighting
conditions to the ideal. This point is countered by the questions available to the employees in the
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survey; if the employee feels that the lighting is inadequate, it is most likely that the lighting
conditions are not up to par.
Data analysis.
Prior to the statistical analysis of the quantitative results from the survey, the methods
and models needed to extract the appropriate information must be determined. The first statistical
measure that is imperative is the Pearson product-moment correlation coefficient, which
measures the linear relationship amongst two variables; in this case the productivity (dependant
variable) and the perception of lighting conditions (independent variable). The correlation
coefficient represents the covariance, which “measures the strength of the linear relationship
between two variables”, divided by their standard deviation, which measures the dispersion of
the numbers (Investopedia, n.d.). Since we are collecting a sample, the result will be given in the
form of r, ranging from -1 to 1, where if the result is closer to 1 then there is a strong positive
relationship or correlation, and if it is closer to -1 then there is a strong negative relationship, and
if it is closer to 0 there is no or little relationship (Investopedia, n.d.).
The second statistical tool to be used is the Pearson Chi-square that similarly to the
correlation coefficient, permits us to measure the relationship between two variables. However,
unlike the correlation coefficient, that does not help us assert if one variable causes another, the
Chi-square allows us to determine if the relationship is by chance or if it is systematic. “The Chisquare is a correlation test for categorical variables” (Investopedia, n.d.).
Finally, the third statistical method to be used is the regression analysis. All three models
are very similar in concept in the sense that they are used to measure relationships between two
variables. However, regression analysis and correlation coefficient have both similarities and
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differences. The regression coefficient and the correlation coefficient are the same in the sense
that neither responds to the causality. While using the correlation methods, choosing which
variable is X and which is Y is not a concern; the result will be the same. On the other hand,
while using linear regression, one must think about cause and effect; the results predicting Y
from X will differ from the ones predicting X from Y (Statsdirect, n.d.).
Linear regression permits us to measure X as an entity to manipulate and experiment with
while Y is measured (Investopedia, n.d.). In this case, this statistical tool will be very important
for us to measure the time and degree of concentration amongst many other elements that will be
collected in the survey such as quality of lighting; for example, questions 4 and 6 in the survey:
How many hours do you spend on your desk per day? How long (in hours) does it take for you to
lose your concentration at work?
Ethical issues
Before the study is to be conducted at a given location, the contact must first be sure that
the company he or she represents approves. Also, the company must be assured that whether the
findings are to be published or not, the company name, the contact name, and the participating
employees’ names will not be mentioned. In order to preserve the anonymity of the participants,
aside from not mentioning names, the result of the study from each company will be pooled with
the other companies and shown as a whole.
Since the study is part of the coursework of UCW, the researcher will ask permission to
send the forms out to the companies. The university may then opt to include its name in the
format of the forms or not.
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Scope and limitation.
This study aims at examining the effect of lighting conditions on employee productivity.
It is not however, concerned with other factors that could affect productivity. After researching
and studying precedent peer reviewed studies, a hypothesis was developed: “the better the
lighting conditions, the more productive the employees are.” In order to accept or reject the
hypothesis, two surveys were developed. The data collected from these surveys and the statistical
tools that will be used to analyze and interpret the raw data determines the outcome of this
research. However this research has some constraints; first of all, the data sampling methods
used will not allow us to project the findings onto the general population, instead it is focused
mainly on the sample selected. In addition, due to time and contact constraints, the sample size is
not ideal, it is in fact believed to be relatively small. Furthermore, since the participants are all
selected from Kuwait due to convenience, the results provided will be especially centered on the
preferences of the people living in that area. For instance, Kuwait’s climate provides elevated
levels of exposure to very strong sunlight. People in that area may prefer less lighting or less
exposure to direct sunlight, whereas people in Vancouver who are less prone to sun exposure,
may want more sunlight. In that case the results could be read to portray the people in that
specific geographical area. Additionally, since the productivity will not be measured with a
formula, and instead will be an individual’s assessment of another’s performance, the results will
not be consistent from one company to another.
Deliverables.
By the end of this research the expected tangible output will be 32 to 40 completed LSA
surveys and all four EPA questionnaires, a 50-page report, and a presentation portraying the
breakdown of the project from initial idea to full fruition.
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Action plan.

ActionStart dateEnd dateNumber of days
ResearchJanuary 8, 2016January 15, 20165
Proposal developmentJanuary 15, 2016January 29, 201614
SurveyFebruary 8, 2016February 17, 20169
Data entryMarch 1, 2016March 4, 20163
Data analysisMarch 6, 2016March 14, 20168
Final paper deliveryMarch 20, 2016March 25, 20165
PresentationMarch 28, 2016
Total cost (including airfare)5000 CAD

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