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Light-Weighting Perception Study Bangorr University

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Table of Contents

1.0 S U M M ARY 1

2.0 I NTRODUCTION 3

2.1 Project Context 3

2.2 Research Questions 3

2.3 Outline of the Experimental Design 4

3.0 M ETHODS 6

3.1 P a r t i c i p a n ts 6

3.2 M a t e r i a l s 7

3.3 P r o c e d u r e 1 1

4.0 R E S U L TS 1 6

4.1 Shopping Task 1 6

4.2 Choices 1 8

4.3 Magnitude Estimation 2 1

4.4 P o s t - e x p e r iment Questionnaire 2 4

5.0 CONCLUSIONS 2 7

APPENDIX A: PARTICIPANT

DEMOGRAPHICS 2 8

APPENDIX B: PRODUCT DETAILS 2 9

APPENDIX C: PRE-EXPERIMENT

QUESTIONNAIRE 3 6

APPENDIX D: POST-EXPERIMENT

QUESTIONNAIRE 4 0

1.0 Summary

his report details research undertaken by the Centre for Experimental Consumer Psychology in the School of Psychology at Bangor University for the Faraday Packaging Partnership and the Waste & Resources Action Programme (WRAP).

The purpose of the project was to measure the effect of glass light-weighting of household food and drink products on consumers’ preferences and perception of product value and quality.

Methods: 1. In the course of a five-part experiment, we measured in 100 consumers the perception of 4

product categories:

1) Flavoured Alcoholic Beverages-FAB 2) Coffee 3) Jam 4) Sauce

2. Each product was packaged in containers (without brand labels) of three different shape types. For each combination of category and shape type, we assessed perception of value and quality (and observed handling) of product filled containers of three different weights:

1) Original: weight unchanged 2) Light: equivalent to container being 15% lighter 3) Superlight: equivalent to container being 30% lighter

3. Participants completed five tasks:

1) A shopping questionnaire to collect demographic information and shopping habit information.

2) A shopping task requiring each participant to guess the price of each product whilst taking them from a shelf and placing them into a hand-held basket. Behaviour was videotaped and analysed.

3) A choice task where a “favourite” was chosen between two same-category products that differed in shape and weight.

4) A quality estimation task, where participants made relative quality judgements about each container of a specific category.

5) A ‘recycling’ questionnaire to collect information regarding recycling habits, packaging preferences, and opinions on light-weighting information on product labels.

Results:

1. Superlight-weighting reduced consumer perception of value but light-weighting did

not. In the shopping task consumers valued light-weighted products and original weight products about the same. However, superlight products were valued at 3 pence (1.7%) less than original weight products. An expert independent observer (‘blind’ to the product’s

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weight category) was able to judge (significantly better than chance) which weight category group a product belonged to by observing the actions, gestures and facial expressions of participants in the shopping task. This suggests that light-weighting had a systematic but modest effect on consumer actions.

2. In the choices task, participants were more likely to prefer the product with weight at or closest to the original weight than a product with an altered weight. However, container shape was the main driver of preference.

3. Light-weighting had no effect on relative quality estimates. However quality estimates increased with product weight for FABs, coffees and jams. For sauces, the opposite held; the lighter the actual product, the greater their perceived value.

4. It is important to note that in all of the experiments container shape appears to be the main driver of consumer perception and any effect of light-weighting is small.

5. Results from the post-experiment questionnaire suggest that communicating to consumers that a product has been light-weighted may be helpful and is unlikely to hinder consumer purchase decisions.


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2.0 Introduction

2.1 Project Context “In July 2005, thirteen top grocery retailers demonstrated their commitment to waste minimization by signing up to an agreement, known as the Courtauld Commitment. The aim is to reduce the amount of packaging and food waste that is thrown away by households in the UK.” (WRAP website, 23/10/06). www.wrap.org.uk/courtauld The purpose of this research is to support the ongoing light-weighting work undertaken as part of the WRAP funded GlassRite project. The current project provides an insight into how the light-weighting process affects consumers’ perception of products. This report aims to provide brand owners and glass manufacturers with further information to guide their decisions regarding the light-weighting of their own glass containers.

2.2 Research Questions

Five key issues related to light-weighting were identified and examined throughout the investigation: 1) How does light-weighting affect consumers’ perceptions of value while shopping? 2) When given a choice between two bottles, how does light-weighting affect consumers’ decisions? 3) How does light-weighting affect consumers’ perceptions of quality when they are explicitly evaluating the products?

A further issue of interest was the communication of light-weighting to consumers through product labelling. Do consumers want to know about light-weighting of glass containers, and would such information influence their purchase decision? This data was collected in a post-experiment questionnaire. An important concern is product shape. Products of the same category are frequently placed in containers of different shapes. An important part of the experimental design used in the research reported here is to determine whether product shape or product weight was the significant driver of consumer perception. To analyse the effects of these two factors, we presented participants with products varying in both shape and weight. The participants in the study were never told that product weight was the variable being studied. Product weight was not raised with them and they were never asked to estimate weight or to explicitly link product weight to value, quality, or preference. Consumers are typically unaware of weight variations in products, yet they may nevertheless drive perception. Our aim here was to test this possibility.


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2.3 Outline of the Experimental Design

Products from four different categories were used as materials in this investigation. These categories were chosen as they exemplify the types of products within the remit of WRAP’s food project. They were:

1) Flavoured Alcoholic Beverages (FAB; 70 cl);

2) Coffee (100 g);

3) Jam (approx. 330 g);

4) Cook-in Sauce (approx. 475 g).

The product containers were weighted (by varying the contents) into three categories:

1) Original,

2) Light (filled to be 15% lighter than the original empty container) and

3) Superlight (filled to be 30% lighter than the original empty container).

The product containers used in this study also varied in shape and were grouped into categories in order to compare the effects of container weight against the effects of container shape. Participants completed five tasks:

1) a shopping questionnaire to collect demographic information and shopping habit information;

2) a shopping task requiring each participant to guess the price of each product whilst taking them from a shelf and placing them into a hand-held basket;

3) a choice task where a choice between a series of two alternative bottle was made;

4) a quality estimation task, where participants made relative quality judgements about each bottle of a specific category;

5) a recycling questionnaire to collect information regarding recycling habits, packaging preferences, and opinions on light-weighting information labelling on products.

The following chart describes the flow of participants through each of the experimental tasks.


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Figure 2.3.1 The flow of participants through the experiment including approximate time taken to complete each step.

Pre-experiment Questionnaire N = 100

Shopping Task N = 100

Choices Task N = 100

Magnitude Estimation

FAB N = 25


Coffee N = 25


Jam N = 25


Sauce N = 25

Post-experiment Questionnaire N = 100

Start

15 mins

20 mins

30 mins

15 mins

10 mins

Total approx. 1 hr 30 mins


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3.0 Methods

his section of the report describes the participants recruited to take part in the study, the materials used and how they were prepared, and detailed descriptions including the design and procedure of each component in the study.

3.1 Participants One hundred participants were recruited to come to the Centre for Experimental Consumer Psyhology for one and a half hours to take part in the series of experiments outlined below. Participants gave informed consent and were paid £14 for their time (including £2 ‘winnings’ described in the Shopping Task, page 13). Participants were selected to represent a cross-section of the community, aiming to reflect a sample of consumers buying British products. The following graphs describe the sex, age and socio-economic class of the participants.

The method of obtaining the socio-economic status of the participants was sourced from the National Readership Survey (NRS) website and is described in Appendix A.

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Figure 3.1.1 Sex of the participants

Figure 3.13 Socio-economic status of the participants

Figure 3.1.2 Age of the participants


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3.2 Materials

3.2.1 Product Preparation

Lists of the products used, and photos of them, can be found in Appendix B. It was important that the participants did not use pre-existing attitudes towards particular brands to inform their value judgments in the experiments. Therefore, all products used in the experiments were disguised and given a uniform appearance. Labels were removed and lids were spray-painted black. In the case of FABs, the bottles were spray-painted silver (this was necessary in order to disguise the light-weighting procedure, discussed below). The labels were replaced with generic black and white labels depicting only the product identification number (numbers 1 to 9, referred to as Brand number). The contents were all replaced with a generic equivalent, so that participants did not use the perceived quality of the contents to guide their decisions. Participants were informed that the contents had been replaced and that they should not use this to guide any of their decisions. The FABs were replaced with water, the coffees and jams were replaced with a catering brand instant coffee and mixed fruit jam, respectively, and the sauces were replaced with a catering brand tomato ketchup. Figure 3.2.1.1 Examples of the four product categories after being disguised. In order to investigate how a container’s weight might impact consumer perception, three different weight categories were investigated: 1) Original; 2) Light (15% weight reduction) and; 3) Superlight (30% weight reduction). The weight reductions refer to 15% and 30% of the container weight only, not the container plus content weight.


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This light-weighting was achieved by filling the containers so that they contained less of the contents than originally contained. For example, the container of Jam 1 weighed 177g. If this container were to be light-weighted by 15% it would weigh 150g, a reduction of 27g. So, when re-filling the container with the generic jam, 27g less jam was put in the Light container than the Original container. Weightings were accurate to plus or minus 1g of the actual weight. In order to ensure that the participants were not able to see that less contents had been put into any of the products, a tube was inserted into the middle of the containers, and contents were put around it. This way the empty part of the containers was in the middle of the containers, hidden from the participants. As the contents of the coffee jars were so light, it was not possible to remove enough of the contents in order to account for 30% of the container weight. So, for the coffee category only, a Heavy weight was used. This was done by fixing weights (pennies) to the inside of the lid of the coffee jars, to the amount of 15% of the container weight. The three coffee categories (Heavy, Original, and Light) are different in increments of 15% of the container weight, like the other product categories. It was not possible to put a tube down the FAB containers, and it was important that the contents did not “slosh about” as participants handled them. Therefore, some of the liquid that filled the FAB containers was replaced with vermiculite, a cork-like substance that allowed us to fill up space in the bottles without adding weight. The vermiculite was visible through the glass, and so the FAB bottles were spray-painted silver in order to: a) disguise this and; b) more accurately reflect the packaging of FABs on the market, most of which are packaged in opaque plastic sleeves.


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3.2.2 Product Groups For each of the product categories, there were nine different brands that could be grouped into three different shape types (A, B or C). Three examples of each container was used, each a different weight. Brands to be used in the experiment were specifically chosen because they fit into one of the shape categories. Grouping the jars in this way allowed us to compare the effects of weight on evaluation to something more explicitly obvious to the participants, the appearance. As the products and contents were disguised in every other way, the shape of the containers is the only visual cue left to discriminate between them. For each brand, there were three different examples: the Original, the Light and the Superlight (or Heavy, Original and Light in the case of coffee). These were identifiable only by a small code placed underneath the container. The participants had no way to tell which weight they were receiving. In fact, at no time throughout the experiment were participants informed that there were different weights of each brand, and they only saw one example of each brand at any one time. So, for four categories, with three different shape types, each with three different brands, each with three exemplars at different weights, there were a total of 108 containers used in this experiment (4 x 3 x 3 x 3). A further four containers (one of each product type) were used as “standard’ containers for the Magnitude Estimation task (described below). The standard containers were chosen to represent an approximate average shape of the containers in that product category. This product was only represented at Light weight (Original in the case of coffee).


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FAB Shape

A

B C

Smooth Shoulder

Curvy Hard Shoulder Standard

Weight

Original 3 3 3 - Light 3 3 3 1 Superlight 3 3 3 -

Coffee Shape

A

B C

Square Squat Tall Standard

Weight

Heavy 3 3 3 - Original 3 3 3 1 Light 3 3 3 -


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Jam Shape

A

B C

Short Base and Shoulder

Regular Standard

Weight

Original 3 3 3 - Light 3 3 3 1 Superlight 3 3 3 -

Sauces Shape

A

B C

Tapered Straight Rounded Standard

Weight

Original 3 3 3 - Light 3 3 3 1 Superlight 3 3 3 - Figure 3.2.2.1 The number of brands in each product condition. Numbers are described by weight type and shape type per product category. Pictures represent examples of each of the shape types: a full list of products and weights can be found in Appendix B. Note: Hereafter, when referring to Original, Light and Superlight categories, we are including the Heavy coffee with the Original, the Original coffee with the Light and the Light coffee with the Superlight data from the other three product categories. FABs were referred to as “alcopops” to the participants.


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3.3 Procedure

3.3.1 Pre- and Post-Experiment Questionnaires The first questionnaire (Appendix C) was given to the participants before they took part in any tasks, and contained questions concerning demographic information. This data was used to obtain the sex, age and socio-economic status information described above. The shopping habit data from the pre-experiment questionnaire was also used to assign people to product groups in the Magnitude Estimation task (described below). The post-experiment questionnaire was administered following completion of all the experimental tasks. This questionnaire investigated the recycling habits and the packaging preferences of the participants, and their attitudes to a variety of packaging materials, including glass. It was here that we collected the data regarding explicit labelling regarding light-weighting. This questionnaire can be found in Appendix D.


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3.3.2 Shopping Task Participants saw four shelves of containers. Each shelf had product brands 1 to 9 in a particular category. Participants received a shopping list and were told that they must find each item on the list, in turn, and take it from the shelf. Once they had picked up the item, they must guess its price and then place it in the basket. The participant then found the next item on the list and did this until they had found every item on the list (and the shelves were empty). Participants received feedback to tell them how good their price guess was. They were informed at the beginning of the experiment that if they guessed within 10p of the “real” price three times, they would win an extra £2 in addition to their £12 participation payment. Feedback was given after every trial informing participants how accurately they had guessed. This was done in order to keep the participants motivated and trying hard throughout the task, so that their prices estimations reflected genuine evaluations of value. On each shelf there was only one product category. There was one of each brand on each shelf (brands 1 to 9). Three of these were Original weight items, three were Light weight items, and three were Superlight weight items. These were counterbalanced across participants so that one third of the participants saw Jam 1 at its Original weight, one third saw Jam 1 at Light weight and the remaining third saw Jam 1 at Superlight weight, for example. The shopping list had 36 items on it, in a random order. The 36 items were each a unique product brand. There were four product categories, each with nine brands. The items are placed in a random order on the shelf. The shelf order was also balanced so that 25% of participants saw coffees on shelf 1, 25% saw them on shelf 2 and so on. Participants were informed at the beginning of the task that the coffees and the sauces cost approximately £1.50 and the alcopops and jams cost approximately £2. The feedback that was given to the participants after every price guess was false: the “real” prices of the products were randomly generated by the computer, based on the receipts from the product purchases. The participants were informed at the end of the task that the prices had been false, and that they would receive the £2 “winnings” anyway. In total, the data generated from this task were 33 price guesses (100 participants, one third seeing each container) for each product brand (9 brands x 4 categories), at each weight. The data were analysed by weight and by shape (which weights or shapes received higher price guesses) to determine the most salient


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features participants used when making their value judgments. With their consent, the participants were videotaped whilst performing this task. After the experiment, an expert independent observer ‘blind’ to the weight classification of each product viewed all the videotapes and analysed the participants’ actions, gestures and facial expressions. From this, the observer judged which three of each product category belonged to each weight category. The observer placed each item on a scale of 1 to 5 of how likely it was to belong to either the Original, light or Superlight groups. Using these ratings the observer then assigned three items from each product category to each weight category. Data were analysed relative to chance performance on the part of the observer.


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3.3.3 Choice Task In this experiment, participant and experimenter sat on either side of a screen, designed to obscure all the containers from the participant’s view until the moment they were to make a judgement about them. This experiment simply required participants to chose their favourite from a pair of containers with the response “left” or “right”. Participants were given no feedback regarding what they should base their decision on: they were simply instructed to pick their favourite. A computer on the experimenter side of the screen “beeped” three times, and on the third beep the pair of containers were handed to the participant through a gap in the screen. On receipt of the containers participants made their decision. Participants wore a microphone headset which allowed us to record their reaction time to make a response. Timing began after the third beep, and ceased as soon as participants spoke into the microphone. Participants were instructed that their first response should only be

“left” or “right”. The gathering of reaction time data allowed us to filter out trials in which a response was made before the participants had received the products (and so weight could not have been an influencing factor in that decision). Container pairings were critical in this experiment. Participants only ever received two items of the same product category together. So they only ever had to choose between two coffees for example, not a coffee and a jam. Also, the shape categories of the two

containers were never the same. So they never received two coffee shape A’s together. Further, participants never received two containers of the same weight category together. This way, we were able to analyse whether the influencing factor in choosing a favourite container was weight category, or shape category. See the table below for detailed container pairings. Participants were given the products in blocks: they received 18 pairs of one product, then 18 pairs of a second product and so on until 76 pairs (152 containers in total). Block order was counterbalanced across participants. For the 18 pairs (36 containers) in a block, one third of the containers received were Original, one third were Light and one third were Superlight weight. The brands and shapes chosen per pair were pseudo-randomly selected and post-hoc tests analysed their influence.


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Figure 3.3.3.1 Container pair combinations for a given product category. White cells indicate exact repetitions or redundancies. Light blue cells indicate that either weight category or shape category are repeated. Dark blue cells are the valid cells (18 cells) tested here. (O = Original, L = Light, SL = Superlight Weight Categories).

Container 1

A B C

O L SL O L SL O L SL

O

L A

SL

O

L B

SL

O

L

Conta

iner

2

C

SL


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3.3.4 Magnitude Estimation In this experiment, participants were given one container at a time. First, they received a “standard” container that they were told had a “quality value” of 100. Participants were given a short time to examine this container. The standard container was then taken away from the participant and replaced with a test container. The participants’ task was to compare this container to the standard by giving it a value. If the participant thought that the test container was half the quality of the standard container, they were told to assign it a value of 50; if they thought that the test container was twice the quality, they were told to assign it a value of 200. Participants were permitted to use any numbers they felt appropriate and were given no other guidelines as to what they should base their decision on: only the “quality”. The standard containers can be found in Appendix B. Once the participant had made the magnitude estimation to the test container, they were given back the standard container to study before receiving the next container to rate. This was a between-group experiment: 25% of participants made magnitude estimations for FABs, 25% for coffees, 25% for jam and 25% for sauces. Which group each participant was assigned to was determined by their answers to questionnaire 1. This was done using the age and sex data: it was important to balance these groups properly, so that all the younger participants did not end up giving estimations for FABs and the older participants giving estimations for coffees for example. The frequency of purchase data was also used: wherever possible, participants were assigned to a product category which they regularly bought e.g. a participant giving estimations for coffees is likely to be a high frequency coffee purchaser. The following graphs describe the distribution of participant age and sex by the four product category groups. Participants gave magnitude estimations to every product within the product category. That is, every brand, at every weight (so they would see Jam 1 three times: the Original once, the Light once and the Superlight once). Brand order and weight categories were randomly selected throughout the block of trials. Brand repetitions were distributed throughout the block of trials in order that the participants did not try to rely on memory too much to make their judgments to the same brand: they had to rely on re-evaluations to do this task. Participants thus gave magnitude estimations to 27 products.


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Figure 3.3.4.1 Distribution of Participant Age by Product Category Group

Figure 3.3.4.1 Distribution of Participant Sex by Product Category Group


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4.0 Results

his section outlines the main results of the analyses. Results are presented by experiment. For the purpose of clarification, where we report that a difference is “significant”, we mean that it is statistically significant at the p < .05 level. Error bars

on graphs represent plus and minus one standard error of the mean. These bars can be thought of as variability bars, among participants or among products. To interpret, if the bars on two columns are far apart from each other, it is likely that the two columns are statistically significantly different. If there is some overlap between the bars, it is less likely that they are different to a statistically significant level. Summary findings are presented in blue.

4.1 Shopping Task

4.1.1 Value Ratings Price guesses from the participants were first collapsed across product category and shape, to give us the overall results for the effect of light weighting on participants’ price estimations. We found a nonstatistical difference in value ratings (price estimates) between the Original and Light weight categories. Light-weighting products by 15% does not appear to change participants’ perceptions of value. However, combining Original and Light estimates and comparing them to the Superlight weight price estimates reveals that participants’ value judgments are negatively affected by light-weighting products by 30% (t (1,99) = 2.10, p < .05). Participants judge the products to be worth approximately 3 pence less than Original or Light weight products. This is approximately a 1.7% reduction in perceived price. Figure 4.1.1.1 Price estimations by weight category.

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3p


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We then collapsed the price estimations by product weight and examined the effect of shape within each product category. Interestingly, container shape had a large influence on the value estimations. FAB Shape A was thought to be about 9 pence cheaper than either B or C (A – B t (1,99) = 2.45, p < .05). Coffee C was thought to be about 21 pence cheaper than Coffees A or B (A – C t (1, 99) = 5.73, p < .05). Jam A was judged to be 13 pence more expensive than Jam B (A – B t (1, 99) = 3.06, p < .05), which in turn was thought to be 7 pence more expensive than Jam C (B – C t (1,99) = 2.37, p < .05). As for the sauces, Sauce B was thought to be about 9 pence cheaper than either A or C (B – C t (1,99) = 2.35, p < .05).

Figure 4.1.1.2 Price estimations by shape category, per product category. Summary: Light-weighting (15%) had no effect on value judgments, but superlight-weighting (30%) came at a cost of approximately 3 pence in participants’ value judgments. This can be viewed as a 1.7% reduction in the product’s actual price. These differences are very small compared to the effects of shape. Varying the shape of the products can cause differences of 20 pence (11.4%) to participants’ value judgments.


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4.1.2 Observer Video Analysis

Figure 4.1.2.1 Observer’s performance on categorising products according to weight category. The dotted blue line represents chance performance (33%). The expert observer viewed the video of each participant ‘shopping’ for each product whilst being uninformed about which weight category each product belonged to. Nevertheless the observer was able to correctly categorise the heaviest and lightest weight category products significantly better than chance guessing. The observer was best at spotting the Original weight products (t (1, 99) = 2.25, p < .05), and was approximately 4.5% better than chance. The observer was somewhat able to spot Superlight products (t (1, 99) = 2.22, p < .05), performing about 2% better than chance. While performance on the two extreme weight categories was statistically better than chance guessing, performance on the Light category was not.

Summary: Participants’ behaviour changed to an observable degree when handling products belonging to different weight categories. The independent observer was able to tell, to a level above chance, when they were handling either Original or Superlight weight products.


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4.2 Choices

Product preferences were first analysed by weight category. The product in the heavier weight category was chosen more often than the product in the lighter weight category of the pair, F (1, 99) = 5.96, p < .05. This can be seen in the figure below, although the effects are small, in the order of 3%.

Figure 4.2.1 The percentage of times each weight category was chosen from a pair The data were re-analysed according to the actual weight of the products in the pair. Whereas the left product might belong to the Light category, and the right product might belong to the Superlight category, it may be that the left product is actually heavier than the right product, depending on the starting weights of the containers in question. Analysing the likelihood of choosing the heavier item of the pair revealed that for FABs and sauces, participants were actually more likely to choose the lighter item of the pair (FAB t (1, 99) = 2.24, p < .05; Sauce t (1, 99) = 5.16, p < .05). There was no difference for coffees or jams. Again, these differences were small: the largest effect was for the sauce category, approximately 10%.


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Figure 4.2.2 Percentage of times participants chose the heavier (positive) v. the lighter (negative) product As the categories were behaving in different ways, and this seemed to contradict the findings from the weight category, it seemed likely that container shape was having an influence. Therefore, the data were examined by shape type per product category. In the FAB category, B was preferred to A (t (1, 99) = 5.69, p < .05) and C (t (1,99 = 6.12, p < .05), and A was preferred to C (t (1, 99) = 2.33, p < .05).

4.2.3 FAB product category by shape pair combinations

Choose Heavy

Choose Light

A Smooth Shoulder

B Curvy

C Hard

Shoulder


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In the coffee category, B was preferred to A (t (1, 99) = 2.50, p < .05) and C (t (1,99 = 2.63, p < .05), but there was no difference between A and C.

4.2.4 Coffee product category by shape pair combinations In the jam category, B was preferred to C (t (1, 99) = 2.81, p < .05), but there were no differences between A and B or A and C.

4.2.5 Jam product category by shape pair combinations

A Square

B Squat

C Tall

A Short

B Base and Shoulder

C Regular


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Finally, in the sauce category, large differences were found. A was preferred to both B (t (1, 99) = 7.19, p < .05) and C (t (1, 99) = 5.74, p < .05), and C was preferred to B (t (1, 99) = 6.72, p < .05). It is here that the actual weight difference effect (figure 4.2.2) becomes clear: shape category A was on average much lighter than C (about 155 g lighter), which was in turn slightly lighter than B (about 10 g lighter).

4.2.6 Sauce product category by shape pair combinations Compared to the effects of container weight, the effects of container shape were very large, in the order of 20% to 50%.

Summary: From a pair of products, participants were more likely to prefer the product belonging to a heavier weight category. This effect did not carry through to actual weights, where participants were more likely to choose the lighter product. While these effects were statistical, they were very small. In fact, these effects were dwarfed by the effects of container shape on container preference. It appears that the actual weight effect was being driven by shape preferences.

A Tapered

B Straight

C Rounded


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4.3 Magnitude Estimation When explicitly asked to assess product quality, the weight category of the product made no difference to the magnitude estimation made by the participants. There were no differences between any of the weight categories for any of the product categories. Figure 4.3.1 Magnitude estimations by weight category It was a different story for the shape categories of the products though. Within the FABs, shape B was thought to be of higher quality than A (t (1, 99) = 2.40, p < .05) which was in turn thought to be of higher quality than C (t (1, 99) = 4.08, p < .05). This pattern is consistent with the choice data. In the coffee product category, shape A was thought to be of higher quality than C (t (1, 99) = 2.94, p < .05), but there was no difference between B and either A or C. This pattern was different from that seen in the choice data, suggesting that preference and quality are not the same for this category. In the jams, like the coffees, A was thought to be of higher quality than C (t (1, 99) = 4.68, p < .05), but there was no difference between B and either A or C. As with coffee, this pattern was different from that seen in the choice data, suggesting that preference and quality are not the same for this category.


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Sauce shape C was thought to be of higher quality than shape B (t (1, 99) = 2.95, p < .05), as was shape A, although marginally (t (1, 99) = 1.99, p = .06). There was no difference in the perceived quality between shape categories A and C. As with coffee, this pattern was different from that seen in the choice data, suggesting that preference and quality are not the same for this category.

Figure 4.3.2 Magnitude estimations by shape category When the magnitude estimations were analysed by actual weight, some interesting patterns emerged. Product weights were sorted by the percent different from the standard container’s weight, and the estimations were sorted by the difference from 100 (the standard container’s value). These two variables were then correlated for each product category. The FAB category had a significant positive correlation (r = .076, p < .05). This means that as the containers became lighter than the standard FAB, they were given quality scores lower than 100, and as the containers became heavier than the standard FAB, they were given scores higher than 100. The coffee category also followed this trend with a significant positive correlation (r = .12, p < .05). The jam category had a positive trend that was not significant. However, the jams that were brand 2 stood out as outliers: they were given much higher scores than the other jams, regardless of their weight. Once these outliers were removed from the analysis, this positive correlation also became significant (r = .095 p < .05).


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Interestingly, the sauces revealed a significant negative correlation (r = -1.39, p < .05). As the sauces became lighter than the standard FAB, they were given scores higher than 100, and as the bottles became heavier than the standard FAB, they were given scores lower than 100. The evaluations of this category appear once again to be driven by the shape: the “tapered” shape containers receiving much more favourable rates. This seems to be emphasised when the container is lighter.

Figure 4.3.3 FAB category magnitude estimations plotted for each container type (brand x weight category) relative to the standard container


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Figure 4.3.4 Coffee category magnitude estimations plotted for each container type (brand x weight category) relative to the standard container

Figure 4.3.5 Jam category magnitude estimations plotted for each container type (brand x weight category) relative to the standard container

Outliers


30

Figure 4.3.6 Sauce category magnitude estimations plotted for each container type (brand x weight category) relative to the standard container

Summary: When explicit quality judgements were assessed via magnitude estimations, it appears that the shape of the products is the driving factor. There was no effect of weight categories in any of the product categories. However, when the containers were examined by their actual weight relative to the standard, it was found that for FABs, coffees and jams, the heavier the container, the higher the estimated quality value. This trend was reversed for the sauces for which lighter containers were estimated to have a higher quality value.


31

4.4 Post-experiment Questionnaire

The following charts describe the recycling habits of the participants. The majority of participants recycle, and recycle most products, although plastic to a lesser degree. Participants tend to recycle at home where possible, using council collections.

Figure 4.4.1 Do participants recycle?

Of the participants who said “yes”… Figure 4.4.2 What do participants recycle?

Figure 4.4.3 Where do participants recycle?


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When asked about their preferred packaging materials, most participants selected glass. When asked specifically about each of the product categories, glass was preferred to plastic in all four, especially for jams and sauces for which approximately 92% of participants selected glass packaging as their favourite.

Figure 4.4.5 Participants’ packaging preferences by product category

Figure 4.4.4 What are participants’ favourite packaging materials?


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Participants were asked about the advantages and disadvantages of plastic and glass as packaging materials. The tables below summarise their responses. Any response which was cited by less than 10% of participants is not reported. Figure 4.4.6 Advantages and disadvantages of plastic and glass as perceived by participants. The numbers refer to the percentage of participants who reported each advantage or disadvantage. Plastic

Advantages

Disadvantages

Light 66 Environmentally unfriendly 47 Unbreakable 39 Not biodegradable 43 Cheap 30 Hard to recycle 36 Crushable 20 Weak 20 Malleable 19 Source of litter 13 Durable 18 Affects food 12 Recyclable 17 Unattractive 11 Impermeable 12 Hard to reuse 10

Glass

Advantages

Disadvantages

Recyclable 61 Breakable 70 Reusable 35 Heavy 69 Attractive 30 Dangerous 26 Transparent 27 Expensive 15 Does not affect food 23

Durable 17

% %

% %


34

When asked how they would react to a specific “light-weight” label on a product’s packaging, very few participants reported that this would put them off buying the product. Of the remaining participants, responses were split fairly equally between light-weight labelling encouraging purchase, and having no influence (with “encouraged” having a slightly larger margin).

Figure 4.4.7 Light-weight labelling and purchase decisions

Summary:

The majority of the participants tested in this study recycle and prefer glass as a packaging material to plastic. When asked about the advantages and disadvantages of plastic and glass it was found that participants perceive the advantages of plastic to be light and unbreakable, and its main disadvantages are that it is bad for the environment and weak. Glass by contrast is thought to be good for the environment, attractive, and strong, but heavy and dangerous if broken. Very few of the participants would be discouraged by explicit labelling on the product explaining that the packaging had been light-weighted.


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5.0 Conclusions

eight is a driver of consumer perception. In a series of three tasks we found that weight has a small, but statistical, influence on consumer estimations of value and quality.

In the shopping task it was found that while products light-weighted by 15% of their empty container’s weight were valued the same as containers at their original weight, light-weighting to 30% produced a 3 pence drop in participants’ estimated value compared to containers at their original weight. 3 pence in this task, for these products is equivalent to 1.7%. It is important to note that these effects are small: when the effects of the container shape were analysed, differences of up to 20 pence (11.4%) were found. From this we would extrapolate that superlight-weighting a £20 bottle of whiskey would cause consumers to value that bottle 34 pence less than the original, at £19.66. A 15% light-weighted container though is most likely to be within an ‘acceptable variation’ zone, and appears not to affect perceived price. The expert independent observer of the participants in the shopping task also produced some interesting results. The observer was able to tell, by actions, gestures and facial expressions, which weight category group an item belonged to. Again this was a small but statistical effect. The observer was particularly good at detecting when an item was at its original weight. This suggests than when a container’s weight varies from the expected or familiar weight, consumers’ handling of that container changes. Interestingly, it did not change enough for Light products to be detected but did for Superlight containers, suggesting again that a 15% light-weighted container is within this ‘acceptable variation’ zone.

In the choices task, weight had a consistent but small effect. When given a pair of containers, participants were likely to prefer the container whose weight was closest to its original weight. When given a choice between a light-weighted container and a container at its original weight, they were likely to go for the original-weight container. When given a choice between a light-weighted container and a superlight-weighted container, they were likely to choose the light-weighted container. Again, it appears that participants were sensitive to the familiar weight of the container, and preferred containers that were presented at weights that matched their expectancies. It is important to think of these effects in terms of familiarity

W


36

though, because they did not translate to actual weights of the items. In fact, participants were more likely to prefer a lighter container than a heavier one, an effect that is most likely being driven by the shape of the containers. This is most evident for the sauces where shape A (the tapered conrainers) are a clear favourite of the participants, but they also weigh less than the other two sauce shape types. The effects of weight found in this experiment was dwarfed by the effects of shape. The nominal weight categories produced no effects in the magnitude estimation task. The effect of familiarity was obscured in this task because we were asking participants to compare a given container to a standard container. Now, instead of comparing the container to their own expectancies of it, they were explicitly comparing it to another container, therefore removing their own expectancies from the evaluation process. When the results were analysed by actual weight, some

interesting patterns emerged. For the FABs, coffees and jams, as a product became heavier; it was more likely to be given a higher estimation of value. For the sauces, it was the opposite: as the containers became lighter they were more likely to be given a higher estimation of value. Importantly, these effects were small and were surpassed by the effects of container shape. Throughout the series of experiments the weight of the containers was found to have small, but consistent effects. Analysing the nominal weight of the containers suggested that consumers prefer items that match their expectancies, that are familiar. Analysing the actual weight of the containers suggested that, in general, consumers prefer items that are heavier (although the effects of the sauce category make these results less than clear-cut). Finally, both of these effects were vastly overshadowed by the effects of container shape, which appears to be the main driver in consumer perceptions of value. From the post-experiment questionnaire, it was found that the communication of light-weighted glass to consumers may be helpful to, and it is unlikely to hinder consumer purchase decisions. Indeed, if weight does indeed have this small but consistent effect as found here, communicating this process to the consumer may allow them to put aside product weight as a factor in their decision processes, reducing any possibility that modest light-weighting might be detrimental.


37

Appendix A: Participant Demographics

Source: nrs.co.uk

Social Grade is determined by the occupation of the Chief Income Earner (CIE) in each household

Grade Social Status CIE’s Occupation

A Upper Middle Class

Higher managerial, administrative or professional

B Middle Class Intermediate managerial, administrative or professional

C1 Lower Middle Class Supervisory or clerical and junior managerial, administrative or professional

C2 Skilled Working Class

Skilled manual workers

D Working Class

Semi and unskilled manual workers

E Those at lowest level of subsistence

State pensioners or widows (no other earner), casual or lowest grade workers


38

Appendix B: Product Details

FABs

Shape Shape Description

Product ID

Brand

Product Weight

Container Weight

Original

Light

Super-light

A Smooth Shoulder

1

Taboo

70

570

1287

1202

1116

2

TVX

70

420

1140

1077

1014

3

VK Vodka Blue

70

418

1137

1074

1012

B Curvy

4

Archers Aqua

70

440

1173

1107

1041

5

Caribbean Twist

70

478

1195

1123

1052

6

Tamova Vodka Twist Blush

66

444

1130

1063

997

C Hard Shoulder

7

Bacardi Breezer

70

514

1234

1157

1080

8

Red Square

70

418

1141

1078

1016

9

Tamova Vodka Twist

Blue

70

430

1147

1083

1018

Standard

Summer Blush

70

494

1216

1142

1068


39

Figure 6.1 FABs with original packaging Figure 6.2 FABs after disguising and weighting


40

Coffees


Product ID

Brand

Product Weight

Container Weight

Heavy1

Original

Super-light

A Square

1

Clipper

100

228

356

390

322

2

Co-op Fair Trade Organic

100

206

350

381

319

3

Morrison's Gold

100

262

386

425

347

B Squat

4

Specially Selected

100

218

341

374

308

5

Percol Espresso

100

220

354

387

321

6

Tesco Gold

100

230

351

386

317

C Tall

7

Maxwell House

100

216

339

371

307

8

Morrison's Full Roast

100

212

316

348

284

9

Asda Decaffinated

Rich Roast

100

198

321

351

291

Standard

Buendia

100

250

376

414

339

1 Note that instead of Original, Light and Superlight weight categories, the coffees were weighted to be Heavy, Original, and Light.


41

Figure 6.3 Coffees with original packaging

Figure 6.4 Coffees after disguising and weighting


42

Jams

Shape Shape

Description

Product

ID

Brand

Product

Weight

Container

Weight

Original

Light

Super-

light

A Short

1

Asda Extra Special Conserve

340

177

568

541

515

2

La Vieja Fabrica

375

156

540

517

493

3

Morrison's The Best Strwberry Conserve

340

174

555

529

503

B Base and Shoulder

4

Asda Good for you peach and apricot

320

214

598

566

534

5

Hartley's Reduced Sugar

340

200

582

552

522

6

Morrison's Eat Smart

340

192

592

563

534

C Regular

7

Mackay's Preserve

300

176

547

521

494

8

Wilkin & Sons

340

164

498

473

449

9

Asda Bramley Apple

280

152

516

493

470

Standard

Marks and Spencer

340

218

590

557

525


43

Figure 6.5 Jams with original packaging

Figure 6.6 Jams after disguising and weighting


44

Cook-in Sauces


Product ID

Brand

Product Weight

Container Weight

Original

Light

Super-light

A Tapered

1

Lloyd Grossman

425

252

749

711

673

2

Napolina

400

212

684

652

620

3

Cucina

420

222

720

687

653

B Straight

4

Morrison's Indian

Sauces

500

286

897

854

811

5

Uncle Ben's

490

258

856

817

779

6

Bisto

500

298

917

872

828

C Rounded

7

Asda Creamy

Tomato

500

280

900

858

816

8

Homepride Pasta Bake

500

274

865

824

783

9

Knorr Chicken Tonight

525

248

869

832

795

Standard

Baroni

530

236

874

839

803


45

Figure 6.7 Cook-in Sauces with original packaging

Figure 6.8 Cook-in Sauces after disguising and weighting


46

Appendix C: Pre-experiment Questionnaire We would like to invite you to participate in our study on glass jars. The session will last approximately 2 hours, for which you will receive £12 total. You are asked to sign an informed consent form before starting the study. All information gathered will remain confidential. No sales or soliciting will result from your participation.

1) Gender:

� M � F

2) Ethnic background:

� White British � Black British � African � African Carribean � Chinese � Bengal Indian � Arab � Mixed � Bangladeshi � Pakistani � White other � Other (Specify) ___________________________

3) How long have been living in UK? � less than 1 year � 2-4 years � 5 years or more 4) Age: � 18 years or under � 19-29 � 30-39 � 40-49

� 50-65 � 66 or older


47

5) Number of family members � 1 (single) � 2 � 3 � 4 � more than 4 (specify)__________

6) Which is your school level? � none � complete secondary school

� complete college � complete university � complete post graduate degree � vocational

7) What is the current occupation of the main earner of the house? � Higher managerial, administrative or professional

� Intermediate managerial, administrative or professional � Supervisory or clerical and junior managerial, administrative or professional � Skilled manual worker � Semi and unskilled manual worker � State pensioner or widow (no other earner), casual or lowest grade worker

8) Who usually does the shopping? � you � other (specify)__________________ 9) How often do you go shopping? � once a week � 2- 3 times a week � 4 or more


48

10) Usually, where do you go shopping? � Aldi � Asda � Lidl � Iceland � Morrisons � Kwiksave � Sainsbury's � Tesco � Other (specify)____________________ 11) How do you usually go shopping? � by car � by walking � by bicycle � by coach

12) How many jars of jam do you buy in a month? � none

� 1-2 � 3-4 � 5 or more 13) Which brand of jam do you usually buy? ____________________ 14) How many jars of coffee do you buy in a month? � none

� 1-2 � 3-4 � 5 or more

15) Which brands of coffee do you usually buy? ____________________


49

16) How many jars of cook-in sauce do you buy in a month? � none

� 1-2 � 3-4 � 5-6 � 7 or more

17) Which brand of cook-in-sauce do you usually buy? ___________________

18) How many bottles of Alcopop do you buy in a month? � none � 1-2 � 3-4 � 5 or more 19) Which brand of Alcopop do you usually buy? ___________________


50

Appendix D: Post-Experiment Questionnaire 1a) Do you recycle? � Yes � No

If yes: 1b) Which materials?

� Plastic � Glass � Paper � Cans

If no: 1c) Why don't you recycle?

� I don't think it's useful

� I don't have enough time � I have no space at home � I'm not used to doing it

� Other _______________ 2) Where do you recycle? � at home � at recycle points

3) Which one do you prefer as packaging material? � Plastic � Glass � Cans � Other____________________


51

4a) Try to list the advantages of plastic as packaging material: � ______________________________ � ______________________________ � ______________________________ � ______________________________ 4b) Try to list the disadvantages of plastic as packaging material: � ______________________________ � ______________________________ � ______________________________ � ______________________________ 5a) Try to list the advantages of glass as packaging material: � ______________________________ � ______________________________ � ______________________________ � ______________________________ 5b) Try to list the disadvantages of glass as packaging material: � ______________________________ � ______________________________

� ______________________________

� ______________________________


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6) For each product-category, mark which material is more suitable as packaging material:

7) Did you notice that some of the containers were lighter than others? � Yes � No

8) What would do you, if you saw “light weighted” on the packaging, (meaning that less glass is used to make the container)? � be put off by it

� be encouraged by it � it wouldn't influence me

PRODUCT-CATEGORY GLASS PLASTIC

JAM

COFFEE

COOK-IN SAUCE

ALCOPOP

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