Addressing service grand challenges through inductive research

Purpose The paper advocates inductive methods and qualitative data for grand service challenges that are complex, uncertain and context-dependent. Revisit the inductive origins of core service concepts and show why such challenges suit induction. Offer pragmatic guidance, demonstrate how induction explicates mechanisms and builds theory (often via extreme cases and understudied actors) and outline a future agenda spanning sustainability, nonprofit and informal care, more-than-human perspectives and diverse tech- and low-tech service experiences. Design/methodology/approach This is a methodological essay and integrative review defining qualitative data and collection modes, synthesizing inductive analysis approaches and offering practical guidance for conducting inductive research. Clarifies complementarities with experiments and quantitative modelling, including abductive iteration and illustrates practices with exemplars. Findings Four insights emerge: (1) Qualitative data flexibly capture multifaceted, co-created, culturally embedded service experiences across contexts and actors. (2) Emergent inductive designs reveal unanticipated mechanisms, boundary conditions and theory – especially from extreme cases. (3) Rigorous interpretive practice leverages embodied knowledge to craft midrange, process explanations that identify causal mechanisms in context, complementing regularity-based inference. (4) Induction augments deduction by informing stimuli and measures, clarifying endogeneity and mediation and strengthening ecological validity. Inductive work forged pivotal constructs and remains vital for complex, uncertain service problems. Research limitations/implications Evidence is illustrative and selective, with Western-leaning exemplars. Recommendations assume training, ethics and access are not uniformly available. Qualitative inference privileges analytic over statistical generalization and requires transparency about positionality, robustness and saturation. Implications: expand underused approaches; develop rigorous hybrids with computational text/LLMs while centering human interpretation; prioritize process theorizing, scale development and triangulated mixed-method programs. Practical implications The authors recommend that researchers start with consequential contexts, map stakeholders and use flexible qualitative toolkits. Employ emergent designs; pursue saturation and robustness via triangulation, discrepant cases and member checks; translate insights into service design, recovery, journey orchestration, inclusion and tech deployment. Use qualitative work to craft realistic stimuli, refine constructs, reveal mechanisms and mitigate endogeneity; invest in training and cross-disciplinary mentorship; leverage extreme/understudied cases for scalable interventions. Originality/value The paper reframes qualitative, inductive inquiry as the first and best approach for grand service challenges, integrating historical lineage with actionable “how-to” guidance. Positions embodied, interpretive reasoning as indispensable alongside computation and shows how process-oriented induction identifies contextual mechanisms and enables impactful mixed-method research.