3. Methods

The study was carried out in collaboration with the main actors of the project, and external researchers, practitioners from retailers that work within circular business models and large fast fashion companies, and end-customers interested in remanufactured apparel. The study followed different methods for the three sub-studies. For the first two sub-studies, a mixed methods approach was taken, where the qualitative and quantitative data support each other, while in the third sub-study the focus is on analysing quantitative data for economic feasibility analysis.

3.1 Data collection and analysis

The following sections describe the data collection and analysis specific to each of the sub-studies.

3.1.1 Business strategy implementation

The sub-study follows a modified Delphi approach, where the systematic literature review is forming the foundation for identifying enabling conditions to transitioning towards circularity with remanufacturing as a business strategy. The Delphi method is a consensus development tool applicable in topics with limited evidence (Avella 2016), and the knowledge from a practical perspective from professionals working in the industry is relevant (Hsu and Sandford 2007). As Delphi has already been used by other researchers as a key method for identifying factors of business model transformation (Melynk et al. 2009), it was found to be applicable to this study, by using online surveys for data collection.

The systematic literature review follows explicit criteria for article inclusion, to ensure a focus on the topic of this study, and quality of the data collected. ABI/INFORM was utilised as the primary database, and Science Direct and Scopus as secondary databases to improve the reliability of the data collected (Oghazi & Mostaghel 2018). The initial sample consisted of 129 peer-reviewed articles, of which 28 were selected based on analysing the abstract. The final sample from the literature review consisted of 12 articles, that were categorised after the aim, focus and used methods in order to obtain a descriptive analysis of each. The step was followed by categorisation of the collected data following a modified three-level model introduced by Kurilova-Palisaitiene et al. (2018), that is industry-level, system-level and process-level. The propositions, representing the enabling conditions and challenges for transitioning to circularity, were developed as an outcome of the key points presented under each category.

The online survey was piloted for content validity, reliability and feasibility (Gill et al. 2013) to two externals, of which one of them had knowledge in the field investigated, and one with limited knowledge. The survey was delivered using SurveyMonkey, and included information about the purpose of the study. The first two rounds of the survey entailed the probability of the proposition, its impact on the industry, and desirability of the outcome, with controlled feedback provided to the participants in the second round. The third round offered the same controlled feedback from the first round, while focusing on ranking the propositions instead, in order to understand which of the propositions the participants thought were most relevant for transitioning towards circularity through remanufacturing.

Sampling followed the process described by Okoli and Pawlowski (2004), focusing on practitioners active in Sweden. A list of members of the Swedish textile trade and employers’ association TEKO (TEKO 2019) was taken as a basis, where the selection criteria included being a fabric manufacturer or an apparel brand, and communication of their sustainability work. Additional practitioners included companies and researchers involved in the project and with the topics, and those interested in the study through personal networks. The participants from the respective companies or institutions are experienced in areas such as sustainability, purchasing, R&D, and retail, etc., allowing to generate knowledge sharing between different perspectives to shred light in remanufacturing within the industry.

Interquartile range (IQR) was used to measure agreement in the first two rounds. It is suggested a value less than 25 to represent agreement between the practitioners (Gnatzy et al. 2011; Melander et al. 2019). In this study both a 0-100% scale and a 5-point Likert scale were used, with the value less than 25% to be a consensus among the practitioners. To measure the ranking from the third round of the online questionnaire, the methodology by Schmidt (1997) was followed. Schmidt (1997) uses a nonparametric statistic Kendall’s W, which is preferable as it emphasises whether any agreement has been reached among the practitioners (Schmidt, 1997). The result of Kendall’s W goes between 0 to 1, where 1 indicate that all practitioners agree, a result of 0,5 shows a moderate agreement and 0,3 and lower indicates of a lower degree of agreement. Comments from the first round were analysed and synthesised to provide controlled feedback in the second and third round for each proposition respectively.

3.1.2 Consumer perceived values

For this sub-study, qualitative data was collected to develop an instrument for quantitative data collection. The foundation of the study is developed through a literature review, in order to form an overview of the concepts addressed in the study, and to develop a foundation for the interviews and online surveys. With the PERVAL scale proposed by Sweeney and Soutar (2001) as a basis for testing consumer perceived values, the review supported the forming of the statements, and adding an additional value group due to its relevance as motivation for purchasing remanufactured apparel.

Pre-testing of the self-completion online surveys was carried out, in order to validate the respondents´ comprehension of each developed item, and if that understanding answers the researchers´ intentions. In this study, think-aloud cognitive interviews were carried out with seven respondents that were local to the researchers. The respondents were asked to think aloud while simultaneously answering the survey in order to reveal the thought process in interpreting the question and arriving to the answer (Peterson et al. 2017). The data was collected by taking notes during the interview, and then analysed by one researcher, by examining each interview notes individually, followed by studying key phrases relevant to item interpretation across respondents (Peterson et al. 2017). The findings from the cognitive interviews will not be addressed separately, as they describe the item development from literature review to the final items presented in the survey, as presented in the results section.

The survey was structured as follows: (1) respondent profile, including their age, level of education, profession, and monthly income; (2) shopping habits, including frequency, purchase amounts, brand segments, and preference to types of garments; (3) environmental know-

ledge related true/false statements regarding the textile and apparel industry and environmentally friendly apparel. The fourth and last section (4) focused on the consumer perceived values as identified from literature, by asking the respondents to evaluate whether the statements in each group were found to be important when purchasing new or remanufactured garments in a 5-point Likert scale, from strongly disagree to strongly agree.

The survey was offered both in Swedish and English, and the potential respondents were targeted through: (1) posters, (2) Re:textile´s social media, and (3) the participating brand´s social media and subscription lists, as the aim was to reach consumers that are interested in environmental issues and solutions for them, and additionally those interested in the brand to gain an understanding of brand-specific interest for remanufactured apparel. An incentive in the form of a lottery to win a freely chosen jacket from the partnering apparel brand was offered to the respondents of the online survey.

In total, 81 complete responses were collected through the online surveys. As the survey was shared through off- and online calls with an added incentive, the snowball sampling effect was expected to lead to a higher number of individuals sharing the previously described characteristics of the research interest of this study (Crouse and Toni 2018). However, the snowball sampling method leads to an unknown response rate, as it is not known how many people were reached and decided not to participate in the study. Nevertheless, the final sample size was assessed to be sufficient due to the quality of additional qualitative data provided by the respondents.

The data collected through the self-completion online surveys was analysed through frequency of an answer occurring for the first three sections of the survey. The fourth section of the survey was analysed using arithmetic mean and standard deviation, allowing to answer the first research question. Pearson’s r correlation was used to find causality between the customer profile, shopping habits, environmental knowledge, and consumer perceived values, thus allowing to answer the second research question.

3.1.3 Economic feasibility

The data for the economic feasibility was collected from the stakeholders in the project, and was analysed by adapting the “Leeway model for process cost” 1 developed by Re:textile, due to the nature of the presented case. A detailed description of the analysis is presented in section 6.