technical support and enablement

This study investigates the impact of remote work on disability inclusion in software development teams. Addressing the gap in existing research—which overlooks the unique collaborative challenges faced by persons with disabilities (PWD) and insufficient awareness among managers and peers regarding their daily barriers—we employ a mixed-methods approach: online surveys and in-depth interviews with 14 disabled developers, complemented by quantitative analysis and qualitative thematic coding. Our findings reveal three systemic bottlenecks: (1) lack of accessible development tools, (2) inefficiencies in asynchronous communication, and (3) inadequate managerial adaptability. We further identify self-initiated compensatory strategies employed by PWD. Based on these insights, we propose the first actionable inclusivity framework for mixed-ability remote teams, structured across three dimensions—tool accessibility adaptation, inclusive communication protocols, and leadership interventions—rigorously validated through empirical evidence. This work advances both theoretical understanding and practical implementation of disability inclusion in remote software engineering.

The software industry faces persistent challenges in recruiting, integrating, and managing professionals with disabilities due to physical, technological, and institutional barriers. Method: This study designed and executed the world’s first fully accessible, remote affirmative hackathon. It integrated an inclusive competency assessment framework, a real-time adaptive collaborative environment, and multidimensional talent profiling. All activities were delivered via standardized remote platforms and an interoperable accessibility toolchain, ensuring end-to-end support. Contribution/Results: The initiative directly facilitated employment for 10 developers with disabilities at partner enterprises and established a high-quality talent pool of 146 individuals with disabilities. It also produced the reusable *Inclusive Technical Event Design Guidelines*. Empirical outcomes demonstrate that remote affirmative interventions effectively dismantle both physical and systemic barriers, enabling scalable, sustainable pathways for disability-inclusive technical talent acquisition—validating both efficacy and generalizability.

New software engineers often struggle to comprehend large legacy systems, leading to prolonged onboarding periods. Method: This study introduces a systems-thinking training program grounded in Labelled Transition System (LTS) modeling and a structured understanding template—the first application of LTS modeling in software engineering onboarding education—featuring differentiated learning pathways across five sessions, integrating pedagogical best practices and pre-/post-assessment design. Contribution/Results: While overall comprehension gains were not statistically significant, learners with low initial proficiency showed a robust 15-percentage-point improvement (p < 0.05). Qualitative feedback indicated high engagement and perceived practical relevance. The framework offers a scalable, low-cost, reusable instructional model for cultivating software comprehension skills, addressing a critical gap in industry onboarding programs by introducing formal modeling techniques into foundational training.

This study addresses the limited understanding of how accessibility practices influence collaboration—specifically productivity, engagement, and cohesion—in virtual hybrid-capable teams. Through semi-structured interviews with 18 team members and qualitative analysis, the research reveals that accessibility practices not only facilitate access but also serve as a foundational element for effective collaboration by shaping task coordination, relational maintenance, and responsibility allocation. Findings indicate that such practices significantly enhance team coordination and cohesion, while simultaneously introducing a novel tension between empathy and accountability. Building on these insights, the paper proposes a new perspective that deeply integrates accessibility into the design of virtual collaboration tools and offers concrete recommendations for team-level implementation.

This study addresses the systemic marginalization of users with disabilities in AI product organizations, exposing misalignments between responsible AI practices and accessibility engineering—including divergent objectives, fragmented cross-functional collaboration, and a critical lack of empirical disability-related data. Through 28 semi-structured interviews with engineers, researchers, UX designers, and AI ethics practitioners—analyzed via thematic analysis—we identify three core barriers: (1) conflicting priority-setting mechanisms, (2) scarcity of disability-inclusive training and evaluation data, and (3) process discontinuities across disciplines. We propose an “embedded inclusion mechanism” that integrates internal volunteer networks with external disability communities to co-design requirements, restructure development workflows, and jointly steward accessibility resources. Empirical evaluation demonstrates that this mechanism significantly enhances the visibility and responsiveness to disability-related needs throughout the AI development lifecycle. Our work offers a scalable, organization-level intervention to bridge the persistent gap between AI ethics and accessibility practice.

This study addresses the persistent challenges impeding the effective integration of Agile and DevOps practices, which are often constrained by cultural, organizational, procedural, and technological barriers that undermine software delivery performance. Through semi-structured interviews with six senior practitioners from Brazil and Germany, the research employs qualitative thematic analysis to systematically identify—within a cross-national context—four core integration challenges and proposes a corresponding solution framework. The findings underscore the pivotal roles of cultural alignment, team autonomy, process coordination, and infrastructure automation, highlighting that organizational and cultural factors are critical enablers of successful technical integration. By elucidating these interdependencies, the study offers actionable, cross-cultural guidance for software organizations seeking to enhance their Agile–DevOps convergence and overall delivery effectiveness.

This study addresses the prevalent tendency of organizations to treat accessibility as a compliance burden rather than an opportunity for innovation, resulting in digital products that lack genuine inclusivity. By analyzing 14 large language model–driven accessibility project proposals and conducting focus group discussions with nine participants, the research proposes and validates a disability-led participatory development model. Findings demonstrate that this approach effectively shifts accessibility from passive compliance toward proactive innovation, embedding inclusive design not merely as an add-on but as an integral component of core product development processes. Consequently, accessibility becomes a catalyst for both technological excellence and transformative organizational culture change.

This study addresses the profound transformations in user roles, workflows, and collaboration patterns within enterprise software platforms driven by artificial intelligence, which existing role frameworks—such as the BTP user type matrix—struggle to accommodate. Through 20 expert interviews and a participatory design workshop involving 24 participants, the research employs qualitative methods to investigate structural shifts in developer roles on the SAP Business Technology Platform. Findings reveal three key trends: automation of operational tasks, expanded human-AI collaboration, and increased reliance on agent-based systems. In response, the study argues for a necessary reconfiguration of role taxonomies and governance mechanisms, offering both theoretical grounding and practical guidance for designing and governing AI-native enterprise software.

The widespread adoption of artificial intelligence is blurring organizational role boundaries and eroding “invisible work”—such as mentoring and feedback—that underpins professional development and cultural health. Through semi-structured interviews with 24 product professionals in technology firms and subsequent thematic analysis, this study systematically uncovers AI’s dual impact: while enhancing peer-level collaboration, it simultaneously weakens traditional mechanisms of career support. To address these tensions, the research introduces a strategic framework that renders invisible work visible and offers actionable interventions for organizations, leaders, and individuals. These measures aim to preserve cultural sustainability without compromising operational efficiency in AI-integrated workplaces.