Advancing Evidence-Based Social Sustainability in Software Engineering: A Research Roadmap

Advancing Evidence-Based Social Sustainability in Soware Engineering: A Research Roadmap Bimpe A yoola Dalhousie University Halifax, Canada bimpe.ayoola@dal.ca Anielle Andrade Federal University of Pampa Alegrete, Brazil anielleandrade@unipampa.edu.br Ronnie de Souza Santos University of Calgary Calgary, Canada ronnie.desouzasantos@ucalgary .ca Paul Ralph Dalhousie University Halifax, Canada paulralph@dal.ca Abstract Social sustainability in software development means creating and maintaining systems that promote pro-social values ( e.g., human well-being, equity), b oth now and in the future. However , social sustainability lacks clear conceptual and methodological founda- tions, and often takes a back seat to speed and prot. This paper therefore reports a narrativ e review of existing denitions of social sustainability in software dev elopment and identies key aspects of social sustainability including social equity , well-being, and com- munity cohesion. Challenges around measuring and integrating social sustainability into practice are conceptually analyzed. The paper then proposes a comprehensive denition of social sustain- ability and outlines a roadmap for measuring and integrating social sustainability into software engineering processes. CCS Concepts • Social and professional topics → Sustainability ; • General and reference → Measurement ; Evaluation . Ke ywords Sustainability , Social Sustainability , Sustainable Software, Sustain- able Software Development A CM Reference Format: Bimpe A yoola, Anielle Andrade, Ronnie de Souza Santos, and Paul Ralph. 2026. A dvancing Evidence-Based Social Sustainability in Software Engineer- ing: A Research Roadmap . In 34th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (FSE Companion ’26), July 05–09, 2026, Montreal, QC, Canada. ACM, New Y ork, NY, USA, 5 pages. https://doi.org/10.1145/3803437.3805556 1 Introduction Despite how software technology has transformed society across nearly every domain of human activity , software engineering (SE) This work is licensed under a Creative Commons Attribution 4.0 International License. FSE Companion ’26, Montreal, QC, Canada © 2026 Copyright held by the owner/author(s). ACM ISBN 979-8-4007-2636-1/2026/07 https://doi.org/10.1145/3803437.3805556 research has historically focused on technical outcomes such as per- formance, reliability , and security , often at the expense of broader considerations about societal impact [ 1 , 22 , 29 ]. Sustainability has emerged as a critical concern in SE. Develop- ment (of softwar e, cities, machines, etc.) is sustainable to the extent that it meets the needs of the present without compromising our (or our descendants) ability to meet our (or their ) future needs [ 17 ]. More broadly , sustainability includes multiple dimensions: environ- mental, economic, social, and te chnical [ 29 ]. While environmental and economic sustainability have received incr easing attention, the social dimension remains under-researched [ 1 , 20 , 29 ]. This lack of systematic attention to so cial sustainability is prob- lematic because softwar e systems can marginalize vulnerable popu- lations, fragment communities, reinforce inequalities, and degrade human well-being even when they perform well on technical met- rics. Making social sustainability central to SE requires a scientic approach with clear denitions, valid measurement strategies, and systematic evaluation of interventions intended to improv e social sustainability outcomes. Social sustainability is dicult to study because it is value-laden, context-dependent, and operates across multiple levels from indi- viduals and teams to communities and so cieties [ 29 ]. Furthermore, there is no consensus on its denition, and existing denitions often conate two targets: the social properties of software sys- tems in use and the social conditions under which software is developed [ 8 , 44 ]. This lack of conceptual clarity complicates op er- ationalization and measurement, contributing to empirical ndings that are fragmented and hard to compare [ 11 , 14 ]. This paper addresses key gaps in how social sustainability is conceptualized, measured, and studied in software engineering. W e synthesize existing denitions and propose a rened denition (Sec- tion 2 ), examine measurement challenges (Section 3 ), and present a research roadmap (Section 4 ). 2 Dening So cial Sustainability T o ground our work, we conducted a conceptual review of how social sustainability has been dened across SE, sustainability re- search, and related elds ( e.g. urban planning). The sustainability literature emphasizes intergenerational equity and the fulllment of human needs [ 7 ]. Within SE, denitions highlight themes such as intergenerational equity , so cial justice, inclusion, participation, community well-being, and long-term societal impact [ 4 , 26 , 29 ]. FSE Companion ’26, July 05–09, 2026, Montreal, QC, Canada A yoola et al. Promoting social equity and inclusion is a recurring theme. Denitions frequently highlight the need for softwar e to foster fair- ness, e quity , and inclusion across all user groups—regardless of their socioeconomic status or geographical location—to minimize the dig- ital divide [ 24 , 30 – 32 ]. Human well-being is another signicant theme, extending beyond basic functionality to encompass users’ physical, mental, and social health. Socially sustainable software should meet user needs while being secure and promoting a higher quality of life [ 10 , 15 ]. Community well-being and social co- hesion also appear frequently , framing social sustainability as the capacity of communities to thrive and adapt over time [ 26 , 28 , 30 ]. In SE contexts, this translates into software that enhances rather than fragments communities, supports collective action, and fos- ters b elonging [ 4 , 26 , 30 ]. Developer well-b eing and working conditions emerge as an additional theme in some SE denitions, though less frequently than user-focused themes. Some highlight the social conditions of software development, including w orking conditions, human dignity , participation in decision making, and professional well-being within development envir onments [ 8 , 28 ]. Beyond the SE, insights from urban literature oer additional perspectives on social sustainability . These studies emphasize har- monious social evolution, cultural diversity , and improved quality of life [ 35 , 47 ]. In these contexts, social sustainability is tied to social equity and the sustainability of community [ 12 ], a just and e qui- table society capable of adapting to evolving risks [ 13 ], creating environments that promote peaceful coexistence, social integration, and improved quality of life for ev eryone [ 35 ]. Although these themes provide valuable guidance, existing de- nitions of so cial sustainability in SE var y in scop e and emphasis. Some denitions focus primarily on the so cial impacts of software systems: what software does to the world and how it aects users, communities, and society [ 10 , 15 , 24 , 31 ]. Others incorporate con- cerns about development practices and working conditions, com- bining both product and process considerations within a single denition [ 8 , 28 , 30 ]. This variation reects the breadth of so cial sustainability , but it can also introduce ambiguity about what e x- actly is being evaluated in a given context. Such ambiguity has practical and scientic implications. For researchers, unclear conceptual boundaries make it dicult to op- erationalize social sustainability constructs, develop appropriate measurement instruments, or compare ndings across studies. For practitioners, varying denitions create conicting guidance ab out what social sustainability requires in software projects. T o address these challenges, we synthesize key themes from existing denitions, including social equity , human well-being and quality of life, community cohesion, human dignity , participation, and developer well-being, into tw o denitions that address dierent aspects of social sustainability in SE. Unlike prior denitions that vary inconsistently in which constructs they include [ 24 , 26 , 30 , 31 ] or conate product and process concerns [ 8 , 28 ], treating social sustainability as a single unied concept, our two denitions explic- itly separate socially sustainable software (addressing the impacts of software systems on users and society), and so cially sustain- able software development (the conditions under which software is created and maintained). W e propose the following denition of socially sustainable soft- ware, focusing specically on the social impacts of software systems in use. Definition 1. Socially Sustainable Soware refers to a sys- tem that equitably ser ves diverse users, advances social justice and inclusion, protects privacy and well-being, strengthens rather than fragments communities, respects autonomy , and creates long-term positive value for all stakeholders without shifting negative impacts to marginalized groups, future generations, or other sustainability dimensions. W e propose the following denition of socially sustainable soft- ware development, focusing on the social conditions and practices under which software is created: Definition 2. Socially Sustainable Soware Development is the process of maintaining equitable and humane working conditions for all practitioners involved, enabling diverse participation in tech- nical decisions, systematically incorporating methods for assessing and addressing social impacts, engaging meaningfully with aecte d stakeholders, and sustaining this process over time without degrading the dignity , well-being, or professional growth of those who create and maintain software. 3 Measuring So cial Sustainability Measuring social sustainability presents distinct challenges for re- searchers and practitioners. Social sustainability involves latent, value-laden constructs—such as equity and w ell-being—that cannot be observed directly in software artifacts [ 36 ]. By contrast, other sustainability dimensions in SE b enet from more established mea- surement approaches. Envir onmental sustainability is commonly assessed using green software metrics such as energy consump- tion [ 25 ], and technical sustainability from established approaches to softwar e quality metrics and technical debt [ 34 ]. How ever , social sustainability lacks comparable observable indicators or standard- ized measurement frameworks [ 1 ]. Three challenges complicate measurement. First, what constitutes socially sustainable software varies across geographical, cultural, legal, and so cioeconomic contexts [ 33 ]. A system that promotes e quity in one region may b e ineective or harmful in another . Measurement frameworks that insuciently attend to context risk producing misleading or ethically problematic interpretations. Second, social sustainability manifests simultane ously at indi- vidual, team, organizational, and societal levels [ 29 ]. A system may appear socially sustainable at one level while causing harm at an- other . Without explicitly modeling levels, assessments may show positive outcomes at one level while masking adverse eects else- where, risking drawing invalid conclusions. Third, social sustainability involves constructs that resist straight- forward operationalization [ 1 , 27 ]. Human well-being, e quity , com- munity cohesion, diversity , and quality of life are abstract and dicult to quantify or operationalize as simple metrics. These three challenges explain why existing evidence r emains fragmented. Usable measurement approaches must instead make explicit the target of evaluation, the level of analysis, the stakeholder groups involved, and the value assumptions they encode. Without Advancing Evidence-Based Social Sustainability in Soware Engineering: A Research Roadmap FSE Companion ’26, July 05–09, 2026, Montreal, QC, Canada this clarity , measurement risks b ecoming fragmented, inconsistent, or disconnected from the social outcomes it aims to improve. 4 A Roadmap for Evidence-Based Measurement and Integration Advancing social sustainability requires co ordinated progress across conceptual clarity , measurement, and empirical evaluation. This roadmap outlines a methodical and evidence-based approach to driving social sustainability within software development. 4.1 Create Social Sustainability Interventions Moving beyond discussion, we nee d concrete, empirically-evaluated interventions: deliberate actions or strategies implemente d within the software development process to achieve sustainability goals [ 4 ]. These interventions must address both targets identied ear- lier: socially sustainable software and socially sustainable software development. T raining based interventions can help developers an- ticipate social impacts by building skills such as empathy [ 9 , 19 ], ethical responsibility [ 37 ], and cultural sensitivity [ 23 ], support- ing more inclusive design decisions and awareness of downstream social eects. Nudge-based inter ventions leverage subtle cues to in- uence developer behavior toward social sustainability by making sustainable options and impacts mor e salient at decision points, for example by agging potential bias risks, highlighting accessibility concerns, or surfacing the persp ectives of diverse user personas dur- ing design and implementation. Process-level inter ventions formalize social sustainability checks within development workows by intro- ducing new development pr ocesses or modifying existing ones to incorporate social impact che cks into workows. This may involve incorporating a “Sustainability Impact Assessment” (SIA ) [ 5 ] into backlog prioritization, where dev elopment teams would e valuate each user story or task for its potential sustainability impact before it is added to the sprint backlog. Regulatory and policy interventions play a crucial role in shaping sustainable software development practices across the industry . These interventions typically rely on laws, regulations, guidelines, and policies that mandate or incen- tivize social sustainable practices in software development. These policies can be formalized practices, standards, or rules that align teams and developers with broader sustainability goals [ 43 ]. Research Challenge 1. Develop many practical, sustainability promoting interventions for software professionals, teams, and organizations. 4.2 Create Measurement Infrastructure Progress on social sustainability requires credible, usable measure- ment approaches that align with what is being evaluated. Existing work shows that social sustainability lacks standardized metrics within SE [ 14 ], and importing measures from other disciplines is not straightforward [ 6 ]. While psy chology and sociology or related elds oer validated instruments for constructs such as psychoso- cial well-being [ 21 ], organizational inclusion [ 38 ], and community engagement [ 45 ], these require substantial adaptation and valida- tion for software contexts and may not be suitable for short term or lab base d studies common in SE research. A comprehensive measurement model for social sustainability does not yet exist, and developing one requires validated measures for its constituent components. One promising direction is the development of tar- geted metrics for common social sustainability concerns, such as accessibility ( user accessibility score [ 40 ]), inclusivity ( social inclu- sivity index [ 18 ]), well-being (user well-being impact scale [ 42 ]), or community impact( community engagement score [ 16 ]), grounded in established standards where possible. Surveys, interviews, and case studies can also supplement these quantitative metrics by providing qualitative insights into the soft- ware ’s impact on users, developers, stakeholders and communities. Measures should explicate whether they target individual experi- ence, team working conditions, organizational practices, or societal outcomes. Without this clarity , ndings will remain dicult to compare or synthesize across studies. Research Challenge 2. Establish a standard measurement model for social sustainability construct. 4.3 Design Appropriate Intervention Studies Most SE researchers create interventions that ostensibly improve project outcomes when used by professional developers, but shy away from inter vention studies . Case studies, grounded theor y , ques- tionnaires, repositor y mining, nonexperimental simulation, and exploratory data science can all help establish feasibility and plausi- bility , especially given the cost of intervention studies. Longitudinal analysis or meta-analysis may also provide evidence when inter- ventions are widely adopted. However , such methods alone cannot determine whether an intervention actually improves social sus- tainability outcomes in real development contexts. W e need either action research (if we pr efer a qualitative appr oach) or randomized, controlled experiments (if we prefer a quantitative appr oach). 1 In other words, to empirically evaluate a social sustainability intervention [ 36 ], the appropriate dependent variable must target social sustainability outcomes, or a closely related concept; the ap- propriate hypothesis is that our invention improves the dependent variable; and the best method is either action design research [ 39 ] or a randomized, controlled experiment. 4.3.1 Designing Smarter Experiments. Experiments should use re- alistic tasks, authentic development environments, and decision contexts where social sustainability trade-os naturally arise. Ide- ally , such studies would use stratied random sampling (see [ 3 ]) to select companies and then teams, randomly assign these teams to either a control group or a treatment group, have them per- form specic tasks, and measure social sustainability outcomes. In practice, this lev el of realism and sampling rigor is rar ely feasi- ble. Merely recruiting a reasonable-sized convenience sample of software professionals to participate in a lab-based study is nearly impossible be cause few , if any , granting agencies are willing to provide sucient nancial incentives. W e hav e three suggestions for overcoming the pr ofessional recruiting problem: (1) Acknowledge that, in many cases, a convenience sample of SE (or computer science, etc.) students is a reasonable 1 W e are glazing over quasi-experiments be cause they are only justied when random assignment is impractical, which should be rare in the circumstances we ar e discussing. FSE Companion ’26, July 05–09, 2026, Montreal, QC, Canada A yoola et al. simplication, and certainly better than researchers testing their interventions themselves. (2) Use a randomize d block design [ 2 ] combining undergrad- uate students, graduate students, and a smaller number of professionals. Instead of excluding participants with little experience, model experience as a covariate and empirically assess whether experience moderates the main eect. (3) T o recruit a mo dest number of professional participants, or- ganize a social event in which participating in the study is one of several activities. Consider including a short keynote talk, panel discussion, tutorial, or ask-me-anything session. Consider working with an organization that frequently orga- nizes such events ( e.g. an incubator or meetup group), rather than going it alone. (4) A void online recruiting or crowdsourcing services due to the risk of participant fraud (e.g. pe ople pretending to have skills or experience they do not have, and using AI or other tools to complete experimental tasks for pay). Conduct experiments in-person, where participants can be observed. 4.3.2 Utilize Action Research. Action research refers to a family of research methods that involv e iterative cycles of making sense of a site, planning an intervention, intervening, assessing outcomes, and reworking the intervention; adopting a critical philosophical position that research aims to improve our world; and primarily qualitative data collection and analysis. Several variations on action research have be en proposed including Action Design Research (ADR) [ 39 ], which combines action research with building innova- tive artifacts; and participatory action research (P AR) [ 46 ], which emphasizes including people aected by research as partners (not subjects). ADR and P AR are good choices for assessing sustainabil- ity interventions be cause they: (1) take place in real organizations, with real developers, doing real pr ojects; (2) emphasize theor y de- velopment; (3) do not require a sophisticated, a priori, quantitative measurement model; (4) are naturally longitudinal, which matches the long-term eects of sustainability; and (5) have well-understood applicability to SE research [ 41 ]. Research Challenge 3. Evaluate social sustainability interven- tions using rigorous randomized, controlled experiments and Action Design Research ( ADR) 4.4 Facilitate Interdisciplinar y Collab oration and Longitudinal Social Sustainability Research Social sustainability sits at the intersection of SE, social science, ethics, and user-centered design. Interdisciplinary collaboration is essential for dening constructs, validating instruments, and engag- ing aected stakeholders in meaningful ways. Partnerships across industry , academia, and government can accelerate the develop- ment of social sustainability metrics and tools. While researchers provide the theoretical underpinnings and inno vative methodolo- gies for measuring social sustainability , engaging industr y partners will help researchers ensure that the metrics are applicable in real- world scenarios. In addition, many social sustainability outcomes emerge over long time horizons. Capturing cumulative eects on wellbeing, labor conditions, or community cohesion requires multi- year longitudinal studies, which are dicult to fund under typical grant cycles and challenging for junior researchers building pub- lication records. A ddressing this gap requires gr eater support for interdisciplinary and longitudinal research designs for investigating long-term social outcomes. Research Challenge 4. Support interdisciplinary collaboration and multi-year longitudinal studies to evaluate long term social sustainability outcomes. 5 Conclusion Social sustainability represents a critical yet underexplored dimen- sion of SE. While environmental and economic sustainability have gained increasing attention, the social dimension r emains poorly dened, inadequately measured, and rarely evaluated through rig- orous empirical research. This paper makes three main contributions: (1) a novel, com- prehensive denition of social sustainability in the SE context, emphasizing the dierence between socially sustainable software and socially sustainable software development (Section 2 ); (2) a discussion of measurement challenges (Section 3 ), highlighting that social sustainability involves latent and value-laden constructs that vary across contexts and op erate at multiple le vels of analysis; (3) a research roadmap (Section 4 ) center ed on four imp eratives: develop- ing empirically evaluated interventions, establishing credible and standardized measurement infrastructure, designing more rigor- ous experimental studies to evaluate social sustainability interven- tions, and fostering interdisciplinar y collaboration and longitudinal research. Realizing this agenda will require sustained eort and coordination across research communities, funding bodies, and industry partners. W e also acknowledge that this paper is primar- ily conceptual and reects the perspectives of its authors and our understanding of the eld’s needs. As software increasingly mediates access to resources, oppor- tunities, and social participation, ensuring that it promotes equity , human well-being, and long-term societal value should be a central research priority . Preventing social harm warrants at least as much attention as optimizing technical p erformance in SE research. This paper aims to provide a foundation for advancing social sustain- ability as an evidence-based practice in software engineering and to encourage the community to invest sustained research eort in this neglected but essential area. Acknowledgments This study was supported by the National Sciences and Engine ering Research Council of Canada (RGPIN-2020-05001). References [1] Maryam Al Hinai and Ruzanna Chitchyan. 2014. Social sustainability indicators for software: Initial review . Science 79, 68 (2014), 29. [2] Barak Ariel and David P. Farrington. 2010. Randomized block designs. In Handbook of Quantitative Criminology . Springer, New Y ork, NY, 437–454. doi:10. 1007/978- 0- 387- 77650- 7_21 [3] Sebastian Baltes and Paul Ralph. 2022. Sampling in software engineering research: a critical review and guidelines. Empirical Software Engineering 27, 4 (July 2022), 31 pages. doi:10.1007/s10664- 021- 10072- 8 [4] Christoph Becker , Ruzanna Chitchyan, Leticia Duboc, Steve Easterbrook, Birgit Penzenstadler , Norbert Sey, and Colin C. V enters. 2015. Sustainability design Advancing Evidence-Based Social Sustainability in Soware Engineering: A Research Roadmap FSE Companion ’26, July 05–09, 2026, Montreal, QC, Canada and software: The Karlskrona manifesto. In Procee dings of the 37th IEEE/ACM International Conference on Software Engineering , V ol. 2. IEEE Press, Piscataway , NJ, USA, 467–476. doi:10.1109/ICSE.2015.179 [5] Gerald Berger . 2010. Sustainability Impact Assessment: European Approaches. In Better Policies för Development: Recommendations for Policy Coherence . OECD Publishing, Paris, France, 45–68. [6] Matthijs Brink, Geerten M. Hengeveld, and Hilde T obi. 2020. Interdisciplinary measurement: A systematic review of the case of sustainability . Ecological Indi- cators 112 (2020), 106145. doi:10.1016/j.ecolind.2020.106145 [7] Gro Harlem Brundtland and W orld Commission on Environment and Develop- ment. 1987. Rep ort of the W orld Commission on Environment and Development: Our Common Future. O xford University Press, Oxford. [8] Coral Calero, Mo Angeles Moraga, and Felix Garcia. 2022. Software, sustainability, and UN sustainable de velopment goals. I T professional 24, 1 (2022), 41–48. doi:10. 1109/MI TP.2021.3117344 [9] Lidiany Cerqueira, Sávio Freire, João Bastos, Rodrigo Spínola, Manoel Mendonça, and José Santos. 2023. A thematic synthesis on empathy in software engineering based on the practitioners’ perspective. In Proceedings of the XXX VII Brazilian Symposium on Software Engineering . ACM, New Y ork, N Y, USA, 332–341. doi:10. 1145/3613372.3613407 [10] Nelly Condori-Fernandez and Patricia Lago. 2018. Characterizing the contribution of quality requirements to software sustainability . Journal of Systems and Software 137 (2018), 289–305. doi:10.1016/j.jss.2017.12.005 [11] Vincenzo De Martino, Stefano Lambiase, Fabiano Pecorelli, Willem-Jan van den Heuvel, Filomena Ferrucci, and Fabio Palomba. 2025. Sustainability of machine learning-enabled systems: The machine learning practitioner’s perspective. ACM Transactions on Software Engineering and Methodology 34, 1, Article 15 (Nov . 2025), 35 pages. doi:10.1145/3777553 [12] Nicola Dempsey , Glen Bramley , Sinéad Power , and Caroline Brown. 2011. The social dimension of sustainable development: Dening urban social sustainability . Sustainable Development 19, 5 (2011), 289–300. doi:10.1002/sd.417 [13] Efrat Eizenberg and Y osef Jabareen. 2017. Social sustainability: A new conceptual framework. Sustainability 9, 1 (2017), 68. doi:10.3390/su9010068 [14] Gabriel Alb erto García-Mireles, Ma. Ángeles Moraga, Félix García, and Coral Calero. 2025. Sustainability in the Field of Software Engine ering: A T ertiary Study . ACM Transactions on Software Engine ering and Methodology 34, 2, Article 28 (2025), 42 pages. doi:10.1145/3747178 [15] Amir Ghahramanpouri, Hasanuddin Lamit, and Sepideh Sedaghatnia. 2013. Urban social sustainability trends in research literature. Asian Social Science 9, 4 (2013), 185. doi:10.5539/ass.v9n4p185 [16] Melody S Goodman, V etta L Sanders Thompson, Cassandra Arroyo Johnson, Renee Gennarelli, Bettina F Drake, Pravleen Bajwa, Maranda Witherspoon, and Deborah Bowen. 2017. Evaluating community engagement in research: quan- titative measure development. Journal of community psychology 45, 1 (2017), 17–32. [17] David L. Greene. 2009. Measuring energy sustainability . In Energy , Economic Growth, and the Environment , Georges Zaccour (Ed.). The MI T Press, Cambridge, MA, USA, 353–378. doi:10.7551/mitpress/9780262013581.003.0020 [18] T Lalithasiri Gunaruwan and D Harshane e W Jayasekera. 2015. Social inclusivity through public transportation: a strategic approach to improve quality of life in developing countries. Journal of advanced transportation 49, 6 (2015), 738–751. doi:10.1002/atr .1302 [19] Hashini Gunatilake, John Grundy, Rashina Hoda, and Ingo Mueller . 2024. Enablers and barriers of empathy in software de veloper and user interactions: A mixed methods case study . ACM Trans. Softw . Eng. Methodol. 33, 4, Article 109 (April 2024), 41 pages. doi:10.1145/3641849 [20] Johanna Liz Gustavsson and Birgit Penzenstadler . 2020. Blinded by simplicity: locating the social dimension in software development process literature. In Proceedings of the 7th International Conference on ICT for Sustainability (Bristol, United Kingdom) (ICT4S2020) . Association for Computing Machiner y , New Y ork, NY, USA, 116–127. doi:10.1145/3401335.3401643 [21] Peter Hills and Michael Argyle. 2002. The O xford Happiness Questionnaire: a compact scale for the measurement of psychological well-being. Personality and individual dierences 33, 7 (2002), 1073–1082. doi:10.1016/S0191- 8869(01)00213- 6 [22] W aqar Hussain, Harsha Perera, Jon Whittle, Arif Nurwidyantoro, Rashina Hoda, Rifat Ara Shams, and Gillian Oliver . 2022. Human values in software engineering: contrasting case studies of practice. IEEE Transactions on Software Engineering 48, 5 (2022), 1818–1833. doi:10.1109/TSE.2020.3038802 [23] Hannu Jaakkola. 2012. Culture sensitive aspects in software engine ering. In Conceptual Modelling and Its Theoretical Foundations , Antje Düsterhöft, Meike Klettke, and Klaus-Dieter Schewe (Eds.). V ol. 7260. Springer , Berlin, Heidelberg, 291–315. doi:10.1007/978- 3- 642- 28279- 9_20 [24] Juliette Koning. 2001. Social sustainability in a globalizing world: conte xt, the- ory and methodology explored. In Proceedings of the UNESCO/MOST Meeting . UNESCO, The Hague , The Netherlands, 22–23. [25] Patricia Lago, Qing Gu, and Paolo Bozzelli. 2014. A systematic literature review on green software metrics . VU Technical Report, Amsterdam, The Netherlands. [26] Patricia Lago, Sedef Akinli Koçak, Ivica Crnkovic, and Birgit Penzenstadler . 2015. Framing sustainability as a property of software quality . Commun. ACM 58, 10 (2015), 70–78. doi:10.1145/2714560 [27] Giuseppe Lami, Fabrizio Fabbrini, and Luigi Buglione. 2014. An ISO/IEC 33000- compliant Measurement Framework for Software Process Sustainability Assess- ment. In Proc. of the 2014 Joint Conf. on the Int. W orkshop on Software Measurement and the Int. Conf. on Software Process and Product Measurement . IEEE, W ashington, DC, USA, 50–59. doi:10.1109/IWSM.Mensura.2014.34 [28] Beate Littig and Erich Griessler . 2005. Social sustainability: a catchword between political pragmatism and so cial theory . International Journal of Sustainable Development 8, 1-2 (2005), 65–79. doi:10.1504/IJSD.2005.007375 [29] Sean McGuire, Erin Schultz, Bimpe A yoola, and Paul Ralph. 2023. Sustainability is stratied: toward a better theory of sustainable software engineering. In Pro- ceedings of the 45th International Conference on Software Engine ering (ICSE ’23) . IEEE Press, Piscataway , NJ, USA, 1996–2008. doi:10.1109/ICSE48619.2023.00169 [30] Stephen McKenzie . 2004. Social sustainability: Towards some denitions . W orking Paper 27. Hawke Research Institute, University of South Australia, Magill, South Australia. https://apo.org.au/node/565 [31] Ana Carolina Moises de Souza. 2023. Social sustainability approaches for a sustainable software product. SIGSOFT Softw . Eng. Notes 48, 1 (Jan. 2023), 38–43. doi:10.1145/3573074.3573085 [32] Ana Carolina Moises de Souza, Daniela Soares Cruzes, Letizia Jaccheri, and John Krogstie. 2024. So cial sustainability approaches for software development: A sys- tematic literature review . In Product-Focuse d Software Process Improvement: 24th International Conference, PROFES 2023 , V ol. 14415. Springer Nature Switzerland, Cham, Switzerland, 478–494. doi:10.1007/978- 3- 031- 49266- 2_33 [33] Shola Oyedeji, Ahmed Seah, and Birgit Penzenstadler . 2017. Sustainability quantication in requirements informing design. In Proceedings of the 6th Inter- national W orkshop on Requirements Engineering for Sustainable Systems (RE4SuSy ’17) (CEUR W orkshop Proce edings, V ol. 1944) . CEUR-WS.org, Aachen, Germany , 1–8. https://ceur- ws.org/V ol- 1944/paper6.pdf [34] Judith Perera, Ewan T empero, Yu-Cheng T u, and K elly Blincoe. 2024. A system- atic mapping study exploring quantication approaches to code, design, and architecture technical debt. ACM Trans. Softw . Eng. Methodol. 33, 7, Article 177 (Sept. 2024), 44 pages. doi:10.1145/3675393 [35] Mario Polèse and Richard E. Stren. 2000. The social sustainability of cities: diversity and the management of change . University of T oronto Press, T oronto, Canada. doi:10.3138/9781442682399 [36] Paul Ralph, Miikka Kuutila, Hera Arif, and Bimpe A yoola. 2024. T eaching Soft- ware Metrology: The Science of Measurement for Software Engineering. In Handbook on Teaching Empirical Software Engineering . Springer Nature Switzer- land, Cham, Switzerland, 103–157. doi:10.1007/978- 3- 031- 71769- 7_5 [37] A wais Rashid, Karenza Moore, Corinne May-Chahal, and Ruzanna Chitchyan. 2015. Managing emergent ethical concerns for software engineering in society . In Proceedings of the 37th IEEE/ACM International Conference on Software Engineering (ICSE ’15, V ol. 2) . IEEE Press, Piscataway , NJ, USA, 523–526. doi:10.1109/ICSE. 2015.187 [38] Maranah A Sauter , Diane Boyle, Debra Wallace , Janet L Andrews, Marjorie S John- son, Mary Bates, Sandra M Edeneld, Rebecca Carr , Laura Campbell, Bernita K Hamilton, et al . 1997. Psychometric evaluation of the organizational job satisfac- tion scale. Journal of Nursing Measurement 5, 1 (1997), 53–69. [39] Maung K. Sein, Ola Henfridsson, Sandeep Purao, Matti Rossi, and Rikard Lindgren. 2011. Action Design Research. MIS Quarterly 35, 1 (2011), 37–56. doi:10.2307/ 23043488 [40] Shuyi Song, Can Wang, Liangcheng Li, Zhi Yu, Xiao Lin, and Jiajun Bu. 2017. W AEM: A W eb Accessibility Evaluation Metric based on partial user experience order . In Proceedings of the 14th International W eb for All Conference . A CM, New Y ork, N Y, USA, 1–4. doi:10.1145/3058555.3058576 [41] Miroslaw Staron. 2020. Action Research in Software Engineering . Springer Nature Switzerland, Cham, Switzerland. doi:10.1007/978- 3- 030- 32610- 4 [42] Sarah Stewart-Brown and Kulsum Janmohamed. 2008. W arwick-Edinburgh Mental W ell-b eing Scale (WEMWBS): User Guide V ersion 1 . Manual. University of W ar wick and University of Edinburgh, Coventry and Edinburgh, UK. https://warwick.ac. uk/fac/sci/med/research/platform/wemwbs [43] United Nations. 2015. Sustainable Development Goals. https://sdgs.un.org/goals [44] Tiago V olpato, Ana Allian, and Elisa Yumi Nakagawa. 2019. Has social sus- tainability been addressed in software architectures? . In Proceedings of the 13th European Conference on Software Architecture - V olume 2 . ACM, New Y ork, NY, USA, 245–249. doi:10.1145/3344948.3344979 [45] Emma W aterton. 2014. Heritage and community engagement. In The Ethics of Cultural Heritage , Tracy Ireland and John Schoeld (Eds.). Springer , New Y ork, NY, USA, 53–67. doi:10.1007/978- 1- 4939- 1649- 8_4 [46] William Foote Whyte. 1001. Participator y Action Research . Sage Focus Editions, V ol. 123. Sage Publications, Newbury Park, CA, USA. [47] Oren Yiftachel and David Hedgcock. 1993. Urban social sustainability: the plan- ning of an Australian city . Cities 10, 2 (1993), 139–157.