Abstract

Leaf blowers are essential gardening tools that blow leaves and other contaminating materials. Our goal through this survey was to compute consumers’ preferences for “green” Leaf blowers instead of gas leaf blowers. Green leaf blowers are corded electric (plug-in) and cordless electric (battery-powered), hence leaf blowers that don’t produce greenhouse gas emissions. We were also interested in seeing how: weight,airspeed,run time and leaf blower shape affect consumers’ preferences. Our findings were concluded from 155 respondents’ feedback. We found that consumers’ preferred green leaf blowers, as battery leaf blowers scored highest at our utility model,coming next were runtime then airspeed. Our consumers’ did not prefer high weight,price,and handheld leaf blowers respectively.

Introduction

Leaf blowers, commonly known as blowers, are gardening tools that blow air through a nozzle for cleaning yards from leaves, grass cuttings, dirt, and sometimes even snow. They come in different sizes and shapes depending on the work volume. Mainly the mechanics of these tools: air is blown through powered engines with different air-power and airspeed depending on workload. Some blowers work as vacuums that suck leaves and grass cuttings through a tube and then shred them into small pieces that are kept in a bag. Through this project, we will only focus on air blowers. Leaf blowers vary in size, shape, power type, and design. In this project, we will classify them based on how they are powered by gas leaf blowers and green leaf blowers (corded electric and cordless electric -battery-powered-leaf blowers).

Types of Leaf Blowers

Leaf blowers Types

Product Attributes & Decision Variables

We are especially interested to know our consumer’s preferences concerning green blowers; that is why power type is a major player in deciding all other specifications and was given special attention. For other attributes, we focused on price, weight, shape, runtime, and airspeed as our primary analysis attributes. We chose these attributes because they were repeatedly mentioned in consumers’ feedback comments on top leaf blowers selling websites.[1]

Below are the levels of the attributes:

Attributes	Continuous/Discrete	Value/Range
Power Type	Discrete	Gas, battery, plugin
Price	Continuous	40 - 275 USD
Shape	Discrete	Handheld, Backpack
Weight	Continuous	4 - 40 lbs
Runtime	Continuous	8 - 1000 mins
airspeed	Continuous	50-270 MPH

Survey Design

1. Eligibility

Our eligible population was chosen based of: - People who answered “yes” to our consent age question - People who answered “yes” to our consent understand the question - People who answered “yes” to owning a leaf blower now, in the past or interested in buying a leaf blower in the future. We wanted to filter through and get to people interested in buying a leaf blower. The survey is designed to dig in depth into consumer preferences when buying a leaf blower, though anyone with no interest would not ideally engage with our survey.

2. Respondent information

Along with our choice question, which will be demonstrated in other parts of this report, we were interested in obtaining the following information: - What do our consumers think about banning leaf blowers.

With rising concerns about pollution, noise or others. This question was attempted to weigh our consumers’ general motion on leaf blowers; we found that 41.9% preferred banning gas leaf blowers, which is a high percentage.

Birth year
Gender identity
Race
Educational level
Annual household income

3. Educational Material

We have demonstrated clearly for our respondents what we mean with each attribute:

“Price” refers to the price to buy this leaf blower measured in US$.
“Weight” refers to the actual weight of leaf blowers that furthermore depends upon the type of engine used to build the whole product measured in lbs.

Weight Attribute Explainers

“Run-time” is the time that leaf blowers are operational after charging measured in mins.Unlimited ~ is the associated option for plug-ins leaf blowers measured in mins.
“Airspeed” refers to the force that blows out to move leaves and debris.Measured in MPH.

Additionally we have used the below icons to indicate powertype.

Power Attribute Icons

Changes from Pilot Survey

Initially, we were considering noise, air volume, and pollution. Still, we took them out as they were to skew respondents’ choices towards gas or electric leaf blowers, knowing that noise and pollution are highly associated with gas leaf blowers. We eliminated the air volume attribute, which can be correlated to airspeed. We have kept airspeed which is easier to understand. We had to narrow our weight and price levels to a range that is not very wide to push consumers to think through proximate options and pick the best one; this approach would be more reflective. Through designing our survey, we encountered an issue catering to the unlimited runtime coupled with a plug-in leaf blower; unfortunately, the model can only work for purely numeric values in level choices. Or, otherwise, strictly categorical variables (we can have them replaced with dummy variables), but in our case, the unlimited runtime was an unaccounted combination of an attribute that consisted of both numeric and categorical level values that halted the model. Eventually, we decided to cater to this fact by replacing~ unlimited ~with a zero in our model calculations. We carefully examined classmates’ feedback and decreased the level of weight to only two values as opposed to previously, where we had three; one of them being unreasonably too heavy. We have also eliminated a question about whether a consumer had a leaf blower in the past and why they don’t have it now; we thought it could be a large pool of reasons to the point where maybe we wouldn’t be able to extract insight from it.

Sample Choice Question

Data Analysis

Sample Description

Our initial population consisted of 417 respondents’ feedback. After filtering consent and eligibility criteria, our sample dropped to 236; finally, we only kept respondents’ who completed our survey in a reasonable time (to filter inattentive and too fast responses). The highest age group was (30-40) marking 34.2% of our sample, followed by (40-50) with 25.16% followed by (18-30) with 21.9% followed by (60-70) with 10.3%. For gender, however, we have had 66 males and 84 females.

Data Cleaning

We added formr respondents data per each survey.
We combined them into one data frame
We filtered out respondents who responded “No” to consent age, consent understanding, and our screenout question, which was (Did you own a leaf blower in the past, own a leaf blower or think about getting a new leaf blower)?.
We filtered out respondents who did not finish the survey.
We filtered out respondents who replied too fast using the time column.
We filter people who got our attention-check questions wrong
The remaining data was our analysis and model-building data.

Modeling

The utility model we estimated for our product contains four continuous variables - price, weight, airspeed, and runtime; and two discrete variables - power and shape, which have values of gas, battery, plug-in, and handheld and backpack, respectively.

\[ u_j = \beta_1 x_j^{price} + \beta_2 x_j^{weight} + \beta_3 x_j^{airspeed}+ \beta_4 x_j^{runtime} + \beta_5 \delta_j^{PowerGas} + \beta_6 \delta_j^{PowerBattery}+ \beta_7 \delta_j^{ShapeHandheld} + \varepsilon_j \]

Model Coefficients:

Attributes	Estimate	Std. Error
price	-0.00616587	0.00053525
weight	-0.05423541	0.00663762
airspeed	0.00394858	0.00043332
runtime	0.00457275	0.00072330
shape_handehld	-0.07128652	0.07884164
power_gas	-0.65827450	0.12419395
power_battery	0.58479280	0.11612488

Comments

What is noticed from these coefficients is that Price, weight are negative in utility which is somewhat expected.
Similarly, airspeed and runtime are desirable attributes in a leaf blower; thus, they have positive utility values.
However, handheld scored negatively in utility, meaning consumers preferred backpack leaf blowers over handheld, which is an interesting insight. -As for the power attribute, consumers preferred battery leaf blowers. Which goes pro-our survey goal! This is yet to be checked by further analysis. -Std. Errors are minimal, giving us more confidence in our model utility estimates.

Model Certainity

Coeffients Uncertainity

The uncertainty plots show that model coefficients are tightly estimated for most coefficients (minor std. errors). Price has a negative effect but is almost unnoticeable because it is minimal compared to the weight, which is more disliked. Airspeed and runtime are both likable, and people prefer battery leaf blowers that are positive as opposed to gas leaf blowers.

Results

Willingness to pay

Below we have computed the willingness to pay per each attribute as an extra layer of attributes validation.

Willingness To Pay Per Attributes

This figure shows the willingness to pay, an abstract concept that illustrates to what extent our consumers (“willing to pay on a product”-hence maximum price) measured for a particular attribute.

From this figure,It’s very hard to tell as consumers’ willingness to pay is centered around the mean but the winning motion would be that as weight increases price is likely to increase too. This is a counter intuitive result, but it could be because heavier leaf blowers have collectively better other attributes. Or it could be simply because we have had two levels of weight, whereas the heaviest wasn’t at all heavy~20lbs. Consumers’ willingness to pay for airspeed is almost centered to the mean too but skewed towards less price for having lesser airspeed. This can be associated with battery leaf blowers which were consumers’ top choice. Gas willingness to pay scored low; looking at the power type, we would notice less willingness to pay for gas-leaf blowers and, oppositely, higher for battery. Plug -in is centered because it was our reference level.

Willingness To Pay BarPlot

Market Simulation

Blower1:80$,8lbs,50MPH,unlimited,plug-in& handheld
Blower2:40$,20lbs,125MPH,15mins,gas,& handheld
Blower3:200$,15lbs,200MPH,60min,battery,&handheld
Blower4:275$,6lbs,225MPH,100mins,plug-in& packback
Blower5:100$,13lbs,270MPH,200mins,battery& packback

Blower	MarketShare	Ranking
Blower 1	19.6%	Fourth
Blower 2	18.6%	Least-favorite
Blower 3	21.08%	First
Blower 4	20.2%	Third
Blower 5	20.95%	Second

In this experiment, we devised different alternatives to tightly weigh consumers’ preferences for blowers based on each attribute. The percentages are not very dispersed because the levels are tightly controlled. The main takeaway is people avoid possible gas leaf blowers. Although we placed the lowest price on gas leaf blowers, our consumers’ would still rank it as their least favorite. Blower3, Although not the best price, consumers chose it as their favorite option for probably the high runtime, battery-powered and medium weight. We can see that consumers overlooked shape and went for handheld, which was primarily negative in utility. This gives us high confidence that consumers care for power type, runtime, and weight as their significant purchase drivers. Overall below figure shows very relative probabilities.

Market Simulation

Sensitivty Analysis

Market Simulation

Figure shows that as prices go up market share does not react as much to this; which is an odd result that we will explain in the conclusion.

Price Sensitivity Plot

The price and revenue plot showing an almost linear relationship for the revenue.

Final Recommendation and Conclusion

Our findings showed that consumers’ preferred green leaf blowers over gas leaf blowers. Our model coefficient estimates showed -0.00616587 for price utility coefficient, which is a very small in comparison to other coefficients. Indicating that leaf blowers is a price insensitive market. Now our results did show that but we are very conservative making this statement for other possible reasons which may have drove us to this result listing some of them is that:The sample size which we conducted our analysis on after the filtering consisted of 155 rows which is small. Additionally, the educational information that we provided about power type at the beginning of our survey might have caused a testing confound where respondents “tried to score right” based on the information they received at the beginning making them focus on power type more than price. For future surveys ; more neutral tone should be used in designing the questions and perhaps mix the order of questions before and after the educational material information to mitigate this possible confound.

Limitaions

A great limitation to our survey was mentioned in the changes to the survey section. We couldn’t computationally capture the runtime~unlimited attribute associated with the plug-in leaf blowers. We have replaced it with a zero but is this really producing the right utility model or could it be biased in a way.

Appendix

Welcome to our survey!

Thank you for participating in this survey, which is part of a research effort by The George Washing University. For this survey, we will ask you about your preferences for different types of leafblowers.

Great work!

Now that you’ve shared a bit about yourself, we’d like you to consider a shopping scenario in which you can purchase from a set of leaf blowers with different attributes.

Let’s learn about these attributes:

Price :

refers to the price to buy this leaf blower measured in US$.

Weight :

refers to the actual weight of leaf blowers that furthermore depends upon the type of engine used to build the whole product measured in lbs.

8lbs : About the weight of a Milk gallon

20lbs : About the weight of a Sledge Hammer

Run-time :

is the time that leaf blowers are operational after charging measured in mins. - unlimited ~ is the associated option for plug-ins leaf blowers.

Airspeed :

refers to the force that blows out to move leaves and debris. Measured in MPH.

We’ll now begin the choice tasks. On the next few pages we will show you three options of leaf blowers and we’ll ask you to choose the one you most prefer.

For example, if these were the only leaf blowers available, which would you choose?

Through those questions you will see these icons for power-type; here is what we mean by them.

Option 1

power-type: battery

Option 2

power-type: Gas

Option 3

power-type: plug-in

Great work!

We will now show you 8 sets of choice questions starting on the next page.

[mc_button type question with the following three options]

(1 of 8) If these were your only options, which would you choose?

Option 1

power: gas shape: backback price: $ 80 weight: 20 lb runtime: 60 mins airspeed: 125 MPH

Option 2

power: gas shape: backback price: $ 200 weight: 8 lb runtime: 60 mins airspeed: 270 MPH

Option 3

power: battery shape: handheld price: $ 275 weight: 8 lb runtime: 100 mins airspeed: 50 MPH

Thank you for your feedback! The next section will ask some basic questions about leaf blowers.Please answer to the best of your knowledge.

If you used to have a leaf blower, or don’t have one yet, what prevents you from having one?

I dont need one any more
They are expensive
They are bad for the environment
They are banned in my state
They are too loud.
I use a rake.

Gas powered leaf blowers can be polluting and noisy and have a handful of health problems.

Have you experienced that before? What aspects of Leaf blowers most concern you?

Noise
Pollution
Health Risk (human health risk from exhaust, e.g., unburned gasoline, carbon monoxide, fine particulates)
Others. (Please specify your answer)

You have been Great!

Did you know that some electric leaf blowers can perform the same tasks as gas-powered leaf blowers without the use of fossil fuel?!

Would you be in favor of banning gas leaf blowers if electric leaf blowers give the same performance?

Ban gas powered.
Ban all.
Do not ban any.

Nice job!

We’re almost done! We’d just like to ask just a few more questions about you which we will only use for analyzing our survey data.

In what year were you born?

(Drop down menu including Prefer not to say and years 1920 - 2003)

What is your current gender identity? Different identity (please state):

Male
Female
Trans male/trans man
Trans female/trans woman
Genderqueer/gender non-conforming
Prefer not to say

I identify my race as (select all that apply): Different identity (please state):

Asian
African American or Black
White (Not of Hispanic or Latino origin)
Hispanic or Latino
American Indian or Alaska Native
Native Hawaiian or Pacific Islander
Prefer not to say

What is the highest degree or level of school you have completed? If currently enrolled, please use the highest degree received.

Less than a high school diploma
High school degree or equivalent (e.g. GED)
Some college or university, no college degree
Trade/technical/vocational training, no degree awarded
Associate’s degree (e.g. AA, AS)
Bachelor’s degree (e.g. BA, BS)
Graduate or Professional Degree (e.g. PhD, MD, JD, MS)
Prefer not to say

What is your annual household income (from all sources) before taxes and other deductions from pay?

Less than $10,000
$10,000 - $14,999
$15,000 - $24,999
$25,000 - $34,999
$35,000 - $49,999
$50,000 - $74,999
$75,000 - $99,999
$100,000 - $149,999
$150,000 - $199,999
$200,000 or more
Prefer not to say

Please let us know if you have any other thoughts or feedback on this survey.

Your feedback will help us make future improvements :)

(Open text response)

Your completion code is: 8.12795^{5}

Finish

Survey Link: Leaf blowers Live Survey Link [https://leafblowers.formr.org/]

Acknowledgment

A special thank you is extended to Dr. John Paul Helveston for his support throughout this research project.

Consumer Preference Analysis of Leaf Blowers

Raffa Nimir,Piryanka Desai & Sameer Bhosle

December 12, 2022

Abstract

Introduction

Types of Leaf Blowers

Product Attributes & Decision Variables

Survey Design

1. Eligibility

2. Respondent information

3. Educational Material

Changes from Pilot Survey

Sample Choice Question

Data Analysis

Sample Description

Data Cleaning

Modeling

Model Coefficients:

Comments

Model Certainity

Results

Willingness to pay

Market Simulation

Sensitivty Analysis

Final Recommendation and Conclusion

Limitaions

Appendix

Welcome to our survey!

Great work!

Price :

Weight :

Run-time :

Airspeed :

Great work!

Nice job!

Your completion code is: 8.12795^{5}

Acknowledgment

Consumer Preference Analysis of Leaf Blowers

Raffa Nimir,Piryanka Desai & Sameer Bhosle

December 12, 2022

Abstract

Introduction

Types of Leaf Blowers

Product Attributes & Decision Variables

Survey Design

1. Eligibility

2. Respondent information

3. Educational Material

Changes from Pilot Survey

Sample Choice Question

Data Analysis

Sample Description

Data Cleaning

Modeling

Model Coefficients:

Comments

Model Certainity

Results

Willingness to pay

Market Simulation

Sensitivty Analysis

Market Share Plot

Final Recommendation and Conclusion

Limitaions

Appendix

Welcome to our survey!

Consent form

Great work!

Price :

Weight :

Run-time :

Airspeed :

Great work!

Nice job!

Your completion code is: 8.12795^{5}

Acknowledgment