*3.1.1 Literature review methods*

We conducted a keyword search following the PRISMA framework [32] for reporting systematic literature reviews (up to article selection) which is detailed in the *Supplementary Materials* document<sup>8</sup> (see **Appendix**). The identified sources were critically analysed to identify significant research gaps. A first worthy observation is the low number of sources we were able to identify, with only 40 articles being identified after removal of the duplicates from both utilised databases, Scopus and Web of Science. After exclusion of articles based, first, on screening of the abstracts, and second, on the content of the full articles, the final dataset was comprised of 24 studies, based on whether the consumer behavioural role was central or not, to their analyses. Additionally, a second dataset, built under less strict conditions, i.e. including articles whose main focus is not understanding consumer behaviour in *e*CLSC. The latter dataset was comprised of 31 articles. Moreover, the oldest study our search was able to capture was from 2013 [33]. These results alone illustrate well the fact that consumer behaviour in the context of *e*CLSC is still a nascent field.

#### *3.1.2 Taxonomy building methods*

Research has found some confusion around the definitions of typology and taxonomy. While the main differences emerge from the approach used, i.e.

<sup>8</sup> The *Supplementary Materials* document is available upon request from the authors.

inductive (empirical-to-conceptual; objects to dimensions/characteristics) vs. deductive (conceptual-to-empirical; theory to dimensions/characteristics), they have often been used interchangeably [34]. We employ the term taxonomy more generally to refer to the classification system, without requiring that it is constructed only inductively or deductively, as it has been suggested in the literature [34]. Specifically, we use the following definition: "A taxonomy *T* is a set of *n* dimensions *Di* (*i* ¼ 1, … , *n*) each consisting of *ki* (*ki* ≥2) mutually exclusive and collectively exhaustive characteristics *Cij* (*j* ¼ 1, … , *ki*) such that each object under consideration has one and only one *Cij* for each *Di*" [34] (p. 340). That is:

$$T\_i = \left\{ D\_i, i = \mathbf{1}, \dots, n \middle| D\_i = \left\{ \mathbf{C}\_{\vec{\eta}}, j = \mathbf{1}, \dots, k\_i; k\_i \ge \mathbf{2} \right\} \right\}. \tag{1}$$

In **Section 3.3**, we develop a taxonomy of EEE categories which aims to facilitate the identification of potential EEE-characteristic-related changes in behaviours that are relevant to *e*CLSC. We draw from [34], to employ robust and transparent methods in the construction of the taxonomy. The resulting taxonomy is presented in **Table 2** and discussed in more depth in Section 3.3. We offer a more detailed account of the procedure we applied, which went through five iterations before reaching its final version, in the *Supplementary Materials* file (see **Appendix**).

#### **3.2 Conceptualisation and literature review**

#### *3.2.1 The consumer's role in CLSC*

While previous research tends to consider consumers' involvement in CLSC in terms of consumption phases (i.e. purchase, use, lifetime extension, dispose etc.) [35], in addition to this, we take a more direct approach to exploring the extant interactions. We begin by considering how consumers' decision making may influence CLSC implementation. This leads to the distinction between direct influences, where consumers decide on whether to engage or not as suppliers of discarded equipment, and indirect influences, where consumers make decisions based on addressing their functional and emotional needs by acquiring some EEE or repairing/upgrading already owned equipment that no longer fulfils the consumers' expectations. In other words, direct-influence behaviours (DIB) have to do with the supply or lack thereof of discarded EEE in initiatives which aim to re-introduce outof-use equipment back into the economy, a.k.a. *reversing* behaviours, while indirectinfluence behaviours (IIB) pertain to choices that affect the sales volumes of outputs from CLSC that aim to create value. We provide a more in-depth description of our conceptualisation in the *Supplementary Materials* (see **Appendix**). For our purposes, we present the resulting classification of behaviours in **Tables 3** and **4**.

The tables show three levels (layers) of behaviours with each level breaking down its preceding levels into several other, more concrete, behaviours (as numbering increases). Behaviours within the same level are mutually exclusive, such that adoption of one implies non-adoption of the others (see *Supplementary Materials* and **Appendix**). Therefore, the benefits associated with behaviours within a given level, that are not adopted, form the opportunity cost of the adopted behaviour. The point we aim to highlight is that all these behavioural layers, based on the situations that lead consumers to engage or not with an *e*CLSC, are of interest to consumer research in this area. Some studies may explore more general behaviours, such as discarding [33, 36], or specific behaviours such as the purchase of remanufactured/recycled products, see [35] for an overview. In doing so, results offer more, or less, abstract perspectives on behaviours which may lead to different results. Here, our classification provides a basis for understanding findings on

