To address these challenges, stakeholders can be engaged throughout QSD. When, how, and which stakeholders are engaged depends on the objectives of the QSD study and resource availability, and the engagement methods can range from low to high stakeholder input and influence (corresponding to the least to the most resource intensive). In the first step, indicators can be selected by domain experts (the lowest stakeholder input and influence option), selected or supplemented by stakeholders from pre-generated options or "master lists", 183-185 or generated by stakeholders through focus groups, photovoice, and interviews (the highest stakeholder input and influence). Likewise, during the indicator evaluation step, stakeholders can be engaged through data collection methods of varying stakeholder input and influence. For instance, some structured approaches rely on quantitative data from existing census data or with close-ended surveys (e.g., user cost, number of annual meetings, number of jobs ). These approaches are common in the technology development literature because they are often less resource intensive and enable data collection across multiple contexts with limited incremental cost (i.e., the cost of gathering data from another location or context is low). In contrast, approaches such as semi-structured interviews and case studies 199 are more open to stakeholder elaboration, and they are therefore more resource intensive. When time and resources permit, sample size of the interviews can be set to achieve thematic saturation, when the collection of new data does not shed any further light on the issue under investigation. Therefore, these approaches can collect more case-specific and qualitative data, which can inform quantitative data collection 201 and processing. For instance, these more engaging approaches can be used to adapt indicators to local contexts 203 or to support quantitative indicator scoring using methods such as the fuzzy set theory method. Finally, when needed, stakeholders can also be engaged in the indicator prioritization step. This can be performed in conjunction with MCDA to generate a single score or recommendation. When aggregating indicators, their weights can be determined by experts (the lowest stakeholder input and influence option), derived from archetypal schemes representing different societal groups, 206 or developed for the specific study by stakeholders that directly interact with the technology (the highest stakeholder inputs and influence option). Overall, as each stakeholder engagement method has limitations, the selection of stakeholders should be a careful process that balances resource requirements, social dynamics, resources than interviewing each of the individuals, may not reflect individual goals 209 and can suppress marginalized voices, 210 resulting in a lack of comprehensive goals, 186,211 influences, and decision criteria. Ultimately, substantively addressing social sustainability necessitates the engagement of experts from relevant domains (e.g., the social sciences and humanities) and, when explored in a specific deployment context, local stakeholders who will be directly or indirectly impacted by the project. b Non-exhaustive list in the example paper.