Introduction
“The saddest aspect of life right now is that science gathers knowledge faster than society gathers wisdom.” Isaac Asimov
The fashion industry’s worldwide apparel and footwear market size forecast for 2023 is almost 2 trillion dollars, representing a 6% growth for the period 2022-2023 (
https://fashionunited.com/companies/euromonitor-international, consulted on May 29, 2023). However, the trend is to decrease its growth for the post-pandemic period, where it rescued the 18% loss. Still, the fashion industry faces numerous challenges, from the environmental cost of manufacturing (Bick et al., 2018; Pal and Gander, 2018), to the social issues (Bick et al., 2018; Adamkiewicz et al., 2022), and the economic unpredictable shifts (Hernandez and Haddud, 2018; Nikosey, 2020; Castaneda-Navarrete et al., 2021). These combined factors represent a global environmental justice dilemma supplemented with strong economic risks with no clear solution foreseen (Pedersen et al., 2018; Brydges et al., 2020; Galanakis et al., 2022).
Humankind has been using a manyfold of research approaches to explore, comprehend, develop, and test solutions for its own progress (Williams, 2007). Despite the fact that the pace of producing data (
https://explodingtopics.com/blog/data-generated-per-day, consulted on May 29, 2023) and the specialization degree of experts (Young and Muller, 2015) has been increasing, there is a need for a better understanding of the long-term impact of human activities (Mensah, 2019).
During the recent years the lack of circularity of the fashion industry has gathered interest from the mainstream media with brands like H&M and Zara finding themselves under huge scrutiny (Dragomir and Dumitru, 2022). Such attention is paving the way for the improvement of the consumers’ sustainable and more ethical buying behaviour.
Ultimately the climate crisis is a complex issue to be solved by efforts coming from many disciplines of knowledge and stakeholders, and therefore it is necessary to foster an enhanced research practice with standardized methodologies able to generate results that could be compared and widely replicable. To cite a wicked example, a broadly cited paper recently published in Nature Reviews Earth & Environment by Niinimäki and colleagues about the environmental impacts of the global clothing system used a reasonable amount of grey literature, presenting questionable methods and some contradictory estimations (Niinimäki et al., 2020). So, there is an urgent need to improve the field of fashion research by increasing the criticality of the field. Only a combined effort at a global level can represent an example and force a multitude of progressive actions towards the resolution of the current and, perhaps, upcoming crises. Therefore, this systematic review aims to critically analyse the most relevant fashion research methodologies published during the period ranging from 2015 and 2023 and delineate guidance considerations.
Methodology
The systematic approach method here used was adapted from the PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) method (Page et al., 2021). The method consists of a checklist composed of 27 items and a flow diagram that guides the reporting of systematic reviews based on transparency, accuracy, and comprehensiveness. So PRISMA 2020 is used for clear and complete identification of the relevant literature under the objective of answering the research question: how has fashion research methodologies being implemented to achieve sustainable goals?
Identified studies
For the purpose of this study the records were identified through Scopus databases (
Table 1). For the identification phase, a different combination of appropriate keywords was searched using “AND” or “OR” whenever applicable in the database. The first search on Scopus used the combination “fashion research” AND “fashion design” AND “sustainability”, resulting in 29,825 articles. The second search on Scopus used the combination “fashion research” AND “fashion design” AND “sustainability” AND (“methods” OR “methodology” OR “methodologies”) and was limited to Business, Management and Accounting, and Environmental Science, resulting in 7,351 articles. Finally, the third search used the combination “fashion research” AND “fashion design” AND “sustainability” AND (“methods” OR “methodology” OR “methodologies”) AND (“limitations” OR “challenges”) AND “fashion industry” AND “environmental impact” AND “fashion research methods”, limited to the same fields, resulting in 3,144 articles. All searches found in Scopus were limited to Research Articles and Case Reports published between the years 2015 and 2023. Only Open access & Open archive were considered resulting in a total of 656 articles (
Table 1).
Screened studies
In order to filter the retrieved papers, their titles and abstracts were assessed to check the relevance for the research objective. From the initial 656 entries, a total of 49 were selected for relevance in answering the research question under analysis. A total number of 607 entries were excluded from the records identified throughout the databases for the following reasons: not aligned with the research objective (n = 511), no relevant outcome, or not focused on fashion (n = 50), literature review-based articles or perspectives (n = 24), focus on COVID-19 pandemic (n = 17), and potential conflict of interests or bias (n = 5).
Analyses of studies and bias
Since the entries were filtered manually there is a potential risk of bias or exclusion of relevant papers. However, since the PRISMA 2020 method was applied this risk is considered throughout the study and the results and discussion presented must be interpreted as potentially relevant but not final (Supplemental material 1). One important thing to be considered is the fragmentation of the literature in the scope here studied. Such fragmentation increases the challenge of reporting, comprehending, and comparing between research projects and increase difficulties of further studies, not to mention the potential limitation of implementation and replication of the results in the field. Thus, the transfer of results and knowledge may be hindered. For the purpose of this study literature reviews included as part of the selected and screened studies were neglected since they do not represent truly experimental and verifiable approaches.
Results
The starting scope of this research was intended to span a longer timeline to take into account initiatives about fashion design methodologies tackling sustainable challenges happening earlier than 2015. However, the high number of entries retrieved by the database in the recent years revealed that a strong interest in the sustainable aspect of fashion design and fashion industry is huge and presenting an increasing trend, despite the fragmented and unclear approaches documented.
In regard to the methods implemented and described by the analysed entries, the most used research methods was interviews (n = 13), surveys (n = 11), and life cycle assessments (LCA) (n = 7). There were several research methods only used by one study, such as adaptive choice-based conjoint analysis, focus groups, and the two-round disaggregative Delphi approach (
Table 2). Despite the recent interest in biodesign and related subareas (
e.g., biofabrication (Moroni
et al., 2018)), there was no screened study that explored those areas.
In terms of the limitations found during this study, they can be summarized in:
Low number of participants/objects under study, limited geographies included (namely one country or in the same region), and limited range of time of the participation (Padilha and Gomes, 2016; Camacho-Otero et al., 2019; Brydges, 2021; Dhir et al., 2021; Fontana et al., 2021; Gossen and Heinrich, 2021; Sandberg and Hultberg, 2021; Siderius et al., 2021; Turunen and Halme, 2021; Bocken and Konietzko, 2022; Bhandari et al., 2022; Dangelico et al., 2022; de Oliveira et al., 2022; Fuchs and Hovemann, 2022; Gossen and Kropfeld, 2022; Louma et al., 2022; Nayak et al., 2022; Salmi and Kaipia, 2022; Valor et al., 2022; Xue et al., 2022; Aydin et al., 2023; Garcia-Ortega et al., 2023; Kautish et al., 2023; Román-Collado et al., 2023; Pandey and Yadav, 2023; Scott et al., 2023; Shamsuzzaman et al., 2023).
Limited knowledge and few technological tools from and for the stakeholders to enhance sustainability and/or collaborative actions (Repp et al., 2021; Pal et al., 2021; Siderius et al., 2021; Cooper and Claxton, 2022; Bhandari et al., 2022; Dragomir and Dumitru, 2022; Fuchs and Hovemann, 2022; Gossen and Kropfeld, 2022; Laukkanen and Tura, 2022; Louma et al., 2022; Nayak et al., 2022; Shou et al., 2022; Valor et al., 2022; Kautish et al., 2023; López et al., 2023; Millward-Hopkins et al., 2023; Román-Collado et al., 2023).
Limited scope of the developed method (Padilha and Gomes, 2016; Dhir et al., 2021; Repp et al., 2021; Martin and Herlaar, 2021; Turunen and Halme, 2021; Angelis-Dimakis et al., 2022; Bhandari et al., 2022; Bocken and Konietzko, 2022; Dragomir and Dumitru, 2022; Fuchs and Hovemann, 2022; Laukkanen and Tura, 2022; Mölsä et al., 2022; Schmutz and Som, 2022; Shou et al., 2022; Valor et al., 2022; Aydin et al., 2023; Kautish et al., 2023; López et al., 2023; Millward-Hopkins et al., 2023; Sandberg, 2023; Scott et al., 2023; Shamsuzzaman et al., 2023).
There was also observed that no discussion was presented regarding the particular method limitations (Jain et al., 2021; Johnstone and Lindh, 2022; Stone et al., 2020; Persson and Hinton, 2023; Schmutz and Som, 2022; Wesley et al., 2023).
All the limitations summarized above were highlighted by the respective authors which means that there is a chance of an underrepresentation of the limitations of particular methods. This is exemplified by Bocken and Konietzko (2022) since the authors assumed the replicability limitation of their interviewing methodology which was not assumed by the other researchers who also perform interviews. The same occurred with surveys (Dhir et al., 2021).
Discussion using ChatGPT1
First round
Reply from ChatGPT
Fashion design research faces several challenges in terms of achieving the global sustainability goals. Here are some of the main challenges:
Finding sustainable and eco-friendly materials is a significant challenge. Many traditional materials used in fashion, such as polyester and conventional cotton, have a high environmental impact due to their production processes and use of harmful chemicals. Researching and developing alternative materials that are biodegradable, recycled, or derived from renewable sources is crucial.
- (2)
Supply Chain Transparency
Ensuring transparency and traceability throughout the fashion supply chain is a complex task. It involves understanding the origins of raw materials, manufacturing processes, and the environmental and social impacts associated with each stage. Fashion design research must focus on developing tools, technologies, and standards that enable brands to track their supply chains effectively and make informed sustainable decisions.
- (3)
Waste Management
Addressing the issue of textile waste is a significant challenge. The fashion industry generates a substantial amount of waste through production cut-offs, unsold inventory, and discarded garments. Design research should focus on developing innovative techniques for recycling, upcycling, and repurposing textile waste, as well as exploring circular economy models that minimize waste generation.
- (4)
Consumer Behaviour
Shifting consumer behaviour towards more sustainable choices presents a challenge. Fashion design research needs to understand consumer attitudes, preferences, and motivations to develop products that align with sustainable values. Educating consumers about the environmental and social impacts of their fashion choices is essential to encourage more responsible consumption patterns.
- (5)
Collaboration and Industry Transformation
Achieving sustainability goals requires collaboration among various stakeholders, including designers, manufacturers, policymakers, and consumers. Fashion design research needs to foster interdisciplinary collaboration and facilitate knowledge sharing to drive industry-wide transformation. This includes engaging with policymakers to create supportive regulations and standards that promote sustainable practices.
- (6)
Scaling Sustainable Solutions
While there are many innovative and sustainable fashion solutions, scaling them up to an industry-wide level remains a challenge. Research needs to focus on developing scalable technologies, production methods, and business models that can be adopted by fashion brands across the globe. This involves considering factors like cost, scalability, and compatibility with existing industry infrastructure.
- (7)
Longevity and Timelessness
Fast fashion, with its focus on disposable and short-lived trends, contributes to environmental degradation. Fashion design research needs to explore concepts like durability, longevity, and timelessness in garment design. Creating timeless designs and encouraging the use of quality materials can contribute to reducing the environmental impact associated with frequent fashion consumption.
By addressing these challenges, fashion design research can play a vital role in driving the industry towards more sustainable practices and achieving the global sustainability goals.
Reply from ChatGPT
Certainly! Here’s a research methodological framework that combines elements of the scientific method and creativity methods to test the feasibility of potential solutions for sustainable fashion design:
- (1)
-
Problem Identification and Research Question
- (2)
-
Literature Review
Conduct a comprehensive review of existing literature and research related to sustainable fashion design, materials, supply chains, waste management, consumer behaviour, collaboration, and industry transformation.
Identify gaps and areas that require further exploration.
- (3)
-
Hypothesis Generation
Based on the literature review, generate hypotheses or potential solutions that address the identified challenges.
These hypotheses should propose innovative and sustainable approaches to the problem.
- (4)
-
Data Collection
Design and implement data collection methods that align with your research question and hypotheses.
This may involve qualitative methods such as interviews, focus groups, and observations, as well as quantitative methods like surveys and data analysis.
- (5)
-
Idea Generation and Ideation
Utilize creative methods and ideation techniques, such as brainstorming sessions, design thinking workshops, or participatory design, to generate a wide range of potential solutions.
Encourage diverse perspectives and collaboration among stakeholders to foster creativity.
- (6)
-
Prototyping and Testing
Select a subset of the generated ideas and develop prototypes or minimum viable products (MVPs) that represent the potential solutions.
Test the prototypes in controlled environments or real-life scenarios to assess their feasibility, functionality, and sustainability performance.
Gather feedback from users, experts, and other relevant stakeholders to refine the prototypes.
- (7)
-
Evaluation and Analysis
Analyse the data collected from testing and prototype evaluation.
Assess the potential solutions based on predefined criteria, such as environmental impact, social implications, economic viability, scalability, and compatibility with industry practices.
Use statistical analysis, qualitative analysis, or a combination of both to draw meaningful conclusions.
- (8)
-
Iteration and Refinement
Based on the evaluation results, refine and iterate on the potential solutions.
Modify the prototypes or generate new ideas if necessary.
Repeat the testing and evaluation process to continuously improve and validate the feasibility of the solutions.
- (9)
-
Documentation and Reporting
Document the research methodology, data collection process, results, and conclusions.
Communicate findings through research papers, reports, presentations, or other appropriate mediums.
Share insights with the academic community, industry professionals, policymakers, and other relevant stakeholders.
By integrating elements of the scientific method (hypothesis generation, data collection, evaluation) with creativity methods (idea generation, prototyping, iteration), this framework allows for a systematic and rigorous approach to testing the feasibility of potential solutions in sustainable fashion design research.
Second round
Prompt by the author
Now assume you are a decision-maker with full powers in your region, country and continent. You also have influence globally. You were asked to develop a research plan to create and validate a framework for fashion practitioners (designers and professionals in companies) to fully transform the field. You have control on the budget to perform the project and to hire the necessary people to help you throughout the process. The brief is the following: 1) timeline of 3 years; 2) the outcomes of the project must be easily actionable across the fashion industry, despite further necessary adaptations and particular validations and optimizations; 3) take into consideration the following handicaps of current methodologies: i) Low number of participants/objects under study, limited geographies included (namely one country or in the same region), and limited range of time of the participation, ii) Limited knowledge and technological tools from and for the stakeholders to enhance sustainability and/or collaborative actions, and iii) Limited scope of the developed methodology. Now please develop the research plan in less than 1000 words.
Reply from ChatGPT
Research Plan:
Developing a Transformative Framework for Sustainable Fashion Design
Objective:
The objective of this research plan is to develop and validate a transformative framework for fashion practitioners (designers and professionals in companies) that can drive sustainable practices across the fashion industry. The framework should be easily actionable, adaptable to different contexts, and capable of addressing the handicaps of current methodologies.
Timeline:
The research plan will span a period of three years, structured into the following phases:
Year 1: Preparatory Phase
Assemble a multidisciplinary research team consisting of experts in sustainable fashion, design, supply chain management, consumer behaviour, and technology.
Conduct an extensive literature review to gather existing knowledge on sustainable fashion practices, methodologies, and frameworks.
Identify and engage with key stakeholders in the fashion industry, including designers, manufacturers, policymakers, and NGOs, to understand their challenges, needs, and perspectives.
Year 2: Framework Development Phase
Design and implement a large-scale global research study that overcomes the handicaps of current methodologies:
Ensure a diverse and representative participant pool from various countries and regions, involving designers, professionals, and other stakeholders from different fashion sectors.
Employ advanced technology tools, such as data analytics, machine learning, and blockchain, to enhance sustainability and collaborative actions within the study.
Develop an expansive and adaptable methodology that encompasses different geographies, cultures, and timeframes to capture a comprehensive understanding of sustainable fashion practices.
Collect data through mixed methods, including surveys, interviews, observations, and industry case studies, to generate rich insights into sustainable fashion practices, challenges, and opportunities.
Apply iterative and participatory design processes, involving stakeholders in co-creation sessions to refine and validate the framework’s components.
Continuously assess the feasibility and practicality of the framework to ensure its actionability and adaptability across the fashion industry.
Year 3: Validation and Dissemination Phase
Validate the framework through pilot implementations in collaboration with selected fashion companies and organizations.
Assess the impact of implementing the framework on sustainability performance, consumer behavior, supply chain transparency, and collaboration within the participating organizations.
Gather feedback from practitioners and stakeholders involved in the pilot implementations to refine and optimize the framework.
Develop practical guidelines, toolkits, and training materials that distill the framework’s key principles and actionable steps for easy adoption across the fashion industry.
Disseminate the research findings, framework, and associated resources through publications, industry conferences, workshops, and online platforms.
Collaborate with global fashion associations, NGOs, and policymakers to advocate for the adoption of the framework and support its implementation at a broader scale.
Budget and Resource Allocation:
Allocate a substantial budget to support the research plan, including funding for the research
team, data collection tools, technology infrastructure, participant recruitment, pilot implementations,
and dissemination activities. Establish partnerships with academic institutions, industry sponsors,
and funding agencies to secure additional financial resources.
Hire a diverse and skilled research team comprising sustainable fashion experts, data analysts,
design researchers, and project managers. Collaborate with external consultants, industry
professionals, and stakeholders to ensure comprehensive expertise and perspectives throughout the
research plan.
Conclusion:
This research plan outlines a comprehensive three-year timeline for developing and validating
a transformative framework for sustainable fashion design. By addressing the handicaps of current
methodologies, leveraging advanced technologies, and involving global stakeholders, the resulting
framework will be actionable, adaptable, and capable of driving sustainability practices across the
fashion industry.
Conclusions
This study evidences the non-trivial nature of researching within the fashion discipline. Despite the methodological arsenal social sciences provide to fashion research (
e.g., surveys, case studies) and the increasing use of more quantitative approaches (
e.g., circular economy metrics and LCA) the common goal is to improve the fashion practice in terms of its current sustainability handicaps. The scientific viewpoints highlighted during this study are manyfold. So, it is not easy to standardize the frameworks to help the decision-making. As more quantitative approaches are implemented the need of adding different competencies to the fashion design practice is becoming apparent.. As conclusion it is suggested that a broad network of universities, companies, not-for-profit organizations, alongside informed citizens combine their interests and expertise to co-design and validate a powerful set of methodologies for fashion research purposes such as seen in order initiatives like the BoSS (
https://cordis.europa.eu/project/id/101079995), EUROWEB (
https://euroweb.uw.edu.pl), CONTEXT (
https://www.context-cost.eu), REFREAM (
https://cordis.europa.eu/project/id/825647), CORENET (
https://cordis.europa.eu/project/id/260169), and MICRO-DRESS (
https://cordis.europa.eu/project/id/260113) European funded projects (happening mandatory consortia).
Finally, this study may be helpful for policy making since it uncovers the handicaps of performing relevant research in the realm of fashion design and fashion industry focusing a more sustainable practice, supplemented with a prototype guidance from ChatGPT to allow a fast and reliable discourse under the scope of the objective of this study.
Supplementary Materials
The following supporting information can be downloaded at the website of this paper posted on Preprints.org.
Funding details
The author declares no funding was used in the production of this research.
Disclosure statement
The author reports there are no competing interests to declare.
Declaration of Generative AI and AI-assisted technologies in the writing process
During the preparation of this work the author used ChatGPT in order to add a contribution to the discussion based on a broad AI-based answers to two questions related to the areas and research methodologies to be explored in fashion-related studies to achieve sustainability. After using this tool, the author reviewed the content but chose to leave it not edited. Still, the author takes full responsibility for the content of this publication.
1 |
ChatGPT, personal communication, May 26-30, 2023. |
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Table 1.
Research methodology description.
Table 1.
Research methodology description.
Identification criterion |
Description |
Research objective |
Investigate the impact of fashion research methodologies in sustainable design practice |
Database |
Scopus, assessed on April 15th 2023 |
Article types |
Research articles, Case reports |
Keywords |
Fashion research, sustainability, methods, methodology, methodologies, limitations, challenges, fashion industry, environmental impact, fashion research methods |
Language |
English |
Research criteria |
Based on 3 research criteria: (1) ‘fashion research’ and ‘fashion design’ and ‘sustainability’, (2) ‘fashion research and ‘fashion design’ and ‘sustainability’ and ‘methods’ or ‘methodology’ or ‘methodologies’ and limited to the subject areas ‘Business, Management and Accounting’ and ‘Environmental Science’, (3) ‘fashion research and ‘fashion design’ and ‘sustainability’ and ‘methods’ or ‘methodology’ or ‘methodologies’ and ‘limitations’ or ‘challenges’ and ‘fashion industry and ‘environmental impact’ and ‘fashion research methods’ and limited to the same subject areas. |
Research years |
2015–2023 |
Table 2.
Total number of studies per type of method with the respective references.
Table 2.
Total number of studies per type of method with the respective references.
Type of method (n = total) |
Reference |
Adaptive choice-Based conjoint analysis (n = 1) |
Fuchs and Hovemann, 2022 |
Case study (n = 10) |
Camacho-Otero et al., 2019; Brydges, 2021; Pal et al., 2021; Cooper and Claxton, 2022; Dragomir and Dumitru, 2022; Gossen and Kropfeld, 2022; Salmi and Kaipia, 2022; Valor et al., 2022; Garcia-Ortega et al., 2023; López et al., 2023 |
Compositional analysis (n = 1) |
Wesley et al., 2023 |
Focus group (n = 1) |
Aydin et al., 2023 |
Framework development/ Theoretical model (n = 5) |
Turunen and Halme, 2021; Shou et al., 2022; Aydin et al., 2023; Kautish et al., 2023; Shamsuzzaman et al., 2023 |
Index Decomposition Analysis through the Logarithmic mean divisia index, and decoupling analysis (n = 1) |
Román-Collado et al., 2023 |
Interactive action research (n = 1) |
Sandberg, 2023 |
Interview (n = 13) |
Padilha and Gomes, 2016; Singh et al., 2019; Fontana et al., 2021; Gossen and Heinrich, 2021; Sandberg and Hultberg, 2021; Siderius et al., 2021; Bocken and Konietzko, 2022; Laukkanen and Tura, 2022; Nayak et al., 2022; Amasawa et al., 2023; Dukovska-Poposka et al., 2023; Persson and Hinton, 2023; Shamsuzzaman et al., 2023 |
LCA (n = 7) |
Stone et al., 2020; Martin and Herlaar, 2021; Angelis-Dimakis et al., 2022; Mölsä et al., 2022; Shou et al., 2022; Amasawa et al., 2023; Wesley et al., 2023 |
Material flow analysis (n = 1) |
Schmutz and Som, 2022 |
Material flow analysis and carbon cost analysis (n = 1) |
Millward-Hopkins et al., 2023 |
Mathematical approach (n = 1) |
Peters et al., 2021 |
Scanning electron microscopy (n = 1) |
Wesley et al., 2023 |
Scenario development (n= 2) |
Repp et al., 2021; Shou et al., 2022 |
Social LCA (n = 1) |
Martin and Herlaar, 2021 |
Stakeholder analysis (n = 1) |
Singh et al., 2019 |
Survey (n = 11) |
Dhir et al., 2021; Bhandari et al., 2022; Dangelico et al., 2022; de Oliveira et al., 2022; Fuchs and Hovemann, 2022; Johnstone and Lindh, 2022; Schmutz and Som, 2022; Xue et al., 2022; Amasawa et al., 2023; Pandey and Yadav, 2023; Scott et al., 2023 |
Systematic analysis (n = 2) |
Jain et al., 2021; Cooper and Claxton, 2022 |
Systems model technique (Causal loop diagram (n = 1) |
Singh et al., 2019 |
Thematic analysis (n = 1) |
Bocken and Konietzko, 2022 |
Thermal transformation of waste cotton textile into carbon fibre (n = 1) |
Wesley et al., 2023 |
Thermo-gravimetric analysis (n = 1) |
Wesley et al., 2023 |
Two-round disaggregative Delphi approach (n = 1) |
Louma et al., 2022 |
X-ray diffraction (n = 1) |
Wesley et al., 2023 |
|
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