mixed methods for understanding consumer behaviour: interviews and survey in the context of consumer...

Kyungeun Sung, Sustainable Consumption Research Group, College of Art, Architecture, Design and Humanities

Kyungeun Sung Supervised by Tim Cooper & Sarah Kettley Sustainable Consumption Research Group

College of Art, Architecture, Design and Humanities

Research Methods (MA + MSc Product Design) Lecture 25/10/2016

Research Methods guest lecture


Questionnaire results: Research experience in general (n=22)

yes 86%

no 14%

Resarch experience

yes 73%

no 27%

Undergraduate research module

yes 82%

no 18%

Research for design projects in university

yes 27%

no 73%

Research for professional design projects in industry

yes 9%

no 91%

Professional research projects with staff members

in university

yes 18%

no 82%

Professional research projects in industry


Questionnaire results: Research methods experience (n=22)

yes 68%

no 32%

One-to-one interviews

yes 77%

no 23%

Survey

yes 64%

no 36%

Observation

yes 64%

no 36%

Document analysis

yes 59%

no 41%

Experiments

yes 36%

no 64%

FG


Questionnaire results: Expectations

Various research methods (n=4)

New research techniques (4)

Experiments (3)

Observation (2)

Miscellaneous: document analysis / analysing products / IDEO style research / professional way / online research / real time data analysis / where to start and stop


Kyungeun Sung Supervised by Tim Cooper & Sarah Kettley Sustainable Consumption Research Group

College of Art, Architecture, Design and Humanities

Mixed methods for understanding consumer behaviour: Interviews and survey in the context of

consumer upcycling in the UK

Research Methods (MA + MSc Product Design) Lecture 25/10/2016

Research Methods lecture


Table of contents

Introduction

Interviews

Survey


Introduction


Introduction: Aim and objectives in the PhD research

Aim: develop actionable strategies for upscaling upcycling in households (and beyond) to contribute ultimately to the reduction of GHGs

Objectives:

1. Gain insights into upcycling in the UK

2. Identify UK-specific key behavioural factors for upcycling

3. Formulate design and policy interventions for upscaling upcycling


Introduction: Research questions in the PhD research



3. Formulate design and policy interventions for upscaling upcycling

1. What could be drivers or facilitators for upcycling? What could be barriers to upcycling? 2. When, where, with whom, or how often do they upcycle? 3. What materials do they use for upcycling? How or where to get them? How to choose particular materials? What do they do with end products?

1. Which behaviour factors explain the variance in upcycling frequency as key drivers, facilitators or barriers? 2. Which behaviour factors shape the intention for upcycling as key motivators?

1. What policy and design interventions can be generated for scaling up upcycling? 2. What policy and design interventions might be more effective and feasible in scaling up upcycling for short term and long term?


Introduction: Research methods in the PhD research

Objective Question Method


1. What could be drivers or facilitators for upcycling? What could be barriers to upcycling?

Interview

2. When, where, with whom, or how often do they upcycle? Observation Interview

3. What materials do they use for upcycling? How or where to get them? How to choose particular materials? What do they do with end products?

Observation Interview


1. Which behaviour factors explain the variance in upcycling frequency as key drivers, facilitators or barriers?

Survey

2. Which behaviour factors shape the intention for upcycling as key motivators?

Survey


Introduction: Mixed methods

“the class of research where the researcher mixes or combines quantitative and qualitative research techniques, methods, approaches, concepts or language into a single study” (Johnson and Onwuegbuzie 2004, p.17).

Strengths: triangulation / answering different research questions/ offsetting weaknesses and providing stronger inferences / completeness / ability to deal with complex phenomena and situations / explaining findings / illustration of data / refining research questions / instrument development and testing (Robson 2011, p.167)

Weaknesses: skills and training / cost / time-consuming (Johnson and Onwuegbuzie

2004, Robson 2011)


Technique

Sampling

Validity and reliability

Data analysis

Procedure

Instrument

Introduction: Research design


Interviews


Interviews: Techniques

Technique Characteristics

Structured For fixed design / content analysis

Semi-structured Freedom in sequencing, wording, time, attention

Unstructured Non-standardised / open-ended / in-depth

Non-directive Control by interviewees / for therapeutic settings

Focused An observation study (as situational analysis) prerequisite

Telephone Quicker, cheaper / short / no visual cues

Internet-based No travel, hire, transcription / missing non-verbal cues

FG Structured to unstructured / efficient / no extreme views / confidentiality problem

(Robson 2011, pp.285-295)


Interviews: Sampling methods

Probability sampling vs. non-probability sampling

Method Description

Quota A quota of each category (e.g. PhD/masters/bachelors) / market research

Dimensional An extension of quota sampling (e.g. study level*gender)

Convenience Nearest and most convenient

Purposive Satisfying specific needs in a project

Snowball Participants becoming informants to identify other potential participants

(Robson 2011, pp.274-276)


Interviews: Sample sizes

Theoretical saturation: successive interviews have reached the point where new data no longer stimulate new theoretical understanding or new dimensions of the principal theoretical categories (Bryman 2012, Charmaz 2006)

A rule of thumb: the broader the scope and the more comparisons required, the bigger sample should be (Warren 2002)

Approximation: 6 to 12 (Thomas and Pollio 2002); 5 to 25 (Polkinghorne 2005); 20 to 30 (Warren 2002); 30 (meta-analysis by Thomson 2011)


Interviews: Sampling in the PhD research

Purposive sampling (+ snowball)

Target population: UK-based consumers with practical upcycling experience

Sampling area: UK

Approach: recruiting advertisement on Hackspace fora

Sample size: 23


Interviews: Validity and reliability

Validity: “the integrity of the conclusions that are generated from a piece of research” (Bryman 2012, p.47); “being accurate, or correct or true” (Robson 2011,

p.156)

Reliability: “whether the results of a study are repeatable” (Bryman 2012, p.46)


Interviews: Validity and reliability in the PhD research

Description: (accuracy and completeness of data) full audio record

Interpretation: themes emerge from the ground

Theory: open to alternative theories

Common pitfalls: equipment failure, environmental distraction, transcription errors

A full record of the activities as audit trails

Pilot study (interview schedule, procedure, answers)


Interviews: Data analysis approaches

Approach Characteristics

Quasi-statistical Content analysis

Grounded theory Develop a theory ‘grounded’ in the data

Thematic A general approach not linked to a particular theoretical perspective

Narrative Sensitive to the sense of temporal sequence (e.g. life history research)

(Bryman 2012, Robson 2011)


Interviews: Procedure in the PhD research

Building quick rapport

Introduction: general purpose + rules + procedure and duration + informed consent form + QnA (10 mins)

Demographic information

Topic 1: Current upcycling behaviour (20 mins)

Topic 2: Behaviour-influencing factors (20 mins)

Closing


Interviews: Instrument example from the PhD research

Category Question

Upcycling frequency How often do you upcycle items?

Upcycling materials What kinds of materials do you use for upcycling?

Ways of material acquisition Where or how do you get those materials?

Material selection criteria How or why do you choose particular materials?

End product usage What do you do with the end products after upcycling?

When When do you usually upcycle items?

Where Where do you usually upcycle items?

With whom Do you upcycle items by yourself or with others? If with others,

who are they? What is the occasion?


Interviews: Thematic coding analysis in the PhD research

Thematic analysis with QSR Nvivo 10

Step1: familiarise yourself with the data

Step2: categorise into manageable chunks

Step3: generate initial codes

Step4: identify themes

Step5: fine-tune the codes and themes

Step6: produce a report with integration and interpretation


Interviews: Result example from the PhD research

Category Theme Code Quote

Roles Occupational role

Work-related

F01: “I don't think I have to use any of it in my work. But you know things like choosing colours and things I do in XXX [employer company], choosing colours and choosing finishing, choosing shapes, so they are kind of design aspect and starting of things. I think it’s relevant.” M11: “I think that comes down to work because again work doesn't want you to spend so much money. You then have to think about… ok, sometimes easier way to solve a problem is to throw money on the problem, whereas you have to maybe think about it in a different way. Through my work, you don't just […] throw a computer away. If I can actually repair or upgrade it, and then it doesn't have to be thrown away.”

Student-role

M01: “As a student, um, yes, because there’s no way of doing this otherwise. I guess you could buy all the parts but it would costs a lot of money, and… take a lot longer.” M13: “I think, as a student, yes, because it’s kind of like you want to do new things, doing new cultures.”


Survey


Survey : Approaches

Postal questionnaire

Internet survey Face-to-face interview

Telephone interview

Cost Low Very low High Low/medium

Data collection time Long Short Medium/long Short

Sample distribution May be wide May be wide Must be clustered May be wide

Questionnaire complexity

Must be simple May be complex may be complex May be complex

Question complexity Simple to moderate Simple to moderate May be complex Short and simple

Use of personal records Very good Very good Good Fair

Response rate Poor/medium Poor/medium Medium/very high Medium/high

Response bias Medium/high Medium/high Low Low

(Robson 2011, pp.244-245)


Survey : Sample sizes

Depending on: a) need for precision; b) constraints of time and cost (Bryman

2012, Robson 2011)

A rule of thumb: the bigger the sample, the more representative it is likely to be (+ offering more precision)

Approximation: 100 for major subgroupings and 20 to 50 for minor subgroupings (Borg and Gall 1984); 1000 (Bryman 2012)


Purposive sampling

Target population: UK-based consumers (interested in making)

Sampling area: UK

Approach: using websites identified from the interviewees

Sample size: 122

Survey : Sampling in the PhD research


Tested and proven measures + construct validity (based on relevant theory) face validity (for new measures)

Participant bias: no detailed context of the study

Observer error: SPSS-entered data double checked

observer bias: no further inference beyond the statistical analysis

A full record of the activities as audit trails

Pilot study (Cronbach’s Alpha >0.7) + pre-tests

Survey : Validity and reliability in the PhD research


Google forms

Topic description + incentive for respondents

Survey questions based on Theory of Interpersonal Behaviour and Theory of Planned Behaviour

Socio-demographic information

Survey : Procedure in the PhD research


Behaviour factor Item (scale)

Attitude

To me, taking part in upcycling is…

(1: unpleasant – 7: pleasant; 1: bad – 7: good; 1: worthless – 7: worthwhile; 1: harmful

– 7: beneficial; 1: unenjoyable – 7: enjoyable)

Subjective norm

How much do you agree or disagree with the following sentences? Please read the

wording very carefully.

(1) Most people who are important to me think that I OUGHT TO upcycle things; (2)

Most people who are important to me EXPECT me to upcycle things; (3) Most people

who are important to me WOULD APPROVE of me upcycling

(1: strongly disagree – 7: strongly agree)

Survey : Instrument example from the PhD research


Survey : Data analysis in the PhD research

Statistical analysis with SPSS version 22.0.

Descriptive statistics (min., max., mean, SD)

Correlation analysis (Spearman’s correlation)

Logistic regression

Non-parametric statistics for group comparisons (Mann-Whitney U Test + Kruskal-Wallis H Test)


1. List up all the questions

2. Find the questionnaire items and scales

3. Identify the nature of each variable (e.g. categorical, ordinal, continuous)

4. Draw a diagram for each research question

5. Decide whether a parametric or a non-parametric statistical technique is appropriate

6. Make the final decision (Pallant 2013)

Survey : Six steps to choose the right statistical test


Survey : Result example from the PhD research

Perceived benefit Descriptive statistics

Min. Max. Mean SD

Save money 1.0 7.0 5.39 1.35

Reduce environmental impact 1.0 7.0 5.82 1.19

Be fun 1.0 7.0 6.03 1.02

Allow me to personalise products 2.0 7.0 6.04 0.98

Offer learning experiences 1.0 7.0 6.05 1.06

Result in a high quality product 1.0 7.0 4.67 1.28

Result in a high value product 1.0 7.0 5.17 1.20

Provide me with extra income opportunities 1.0 7.0 4.17 1.68

Allow me to get recognition and appreciation 1.0 7.0 4.66 1.35

Kyungeun Sung, Sustainable Consumption Research Group, College of Art, Architecture, Design and Humanities Image sources: http://image.slidesharecdn.com/clapresentation-talisopenday-march14-140328085008-phpapp01/95/cla-presentation-talis-open-day-march-14-14-638.jpg?cb=1395996639

Thank you! Any question?

[email protected] http://kyungeunsung.com https://www.researchgate.net/profile/Kyungeun_Sung

http://image.slidesharecdn.com/clapresentation-talisopenday-march14-140328085008-phpapp01/95/cla-presentation-talis-open-day-march-14-14-638.jpg?cb=1395996639



























mailto:[email protected]

http://kyungeunsung.com/

https://www.researchgate.net/profile/Kyungeun_Sung