Purpose Quality improvement initiatives (QII) frequently begin with a diagnosis but stall in the “diagnose-but-not-act gap.” This article examines why diagnosis results do not reliably convert into owned, executed and closed improvement actions, and what a higher-fidelity conversion infrastructure looks like in practice. Design/methodology/approach The study compares what the quality/operations and change literature prescribes about diagnosis-to-action conversion with how high-performance organization (HPO) diagnosis trajectories unfold in practice. The comparison is organized around diagnosis phases and the governance routines that connect diagnosis outputs to prioritization, ownership, cadence and closure. Findings The comparison suggests that failure is less about the diagnostic instrument itself and more about weak conversion mechanisms: ambiguous decision rights, insufficient prioritization rules, unclear ownership, lack of a disciplined follow-up cadence and limited feedback loops that sustain learning and accountability. Effective trajectories show explicit translation of diagnosis outputs into a small set of owned actions, embedded in recurring performance dialogue and closure routines. Practical implications Managers should design diagnosis trajectories with an explicit conversion architecture (decision rules, ownership logic, cadence and closure discipline) before data collection begins, thereby increasing the probability that diagnosis leads to measurable improvement. Originality/value By conceptualizing the step between diagnosis and implementation as a conversion problem, and by examining this step in a corpus where the diagnostic instrument is relatively stable, the article offers a more fine-grained explanation of why ostensibly similar diagnosis exercises produce uneven follow-through.
PurposeThis research aims to develop and validate a comprehensive machine learning (ML)-driven Quality 4.0 maturity assessment framework for service organizations grounded in Socio-Technical Systems (STS) theory. Design/methodology/approachAn STS-integrated framework comprising 18 Quality 4.0 dimensions across People, Process, and Technology subsystems was developed through systematic literature synthesis and expert validation. Survey data were collected from 285 service organizations and analysed using Latent Class Analysis to empirically derive five maturity levels. Six supervised machine learning algorithms were evaluated, with the Random Forest classifier achieving the highest predictive performance (accuracy = 0.963). Model interpretability was ensured using SHAP (Shapley Additive Explanations) to quantify the relative importance of individual maturity dimensions. FindingsThe ML-based model reliably classifies organisations into five empirically derived maturity levels. The SHAP analysis highlights Big Data Analytics, Digital Quality Management, and Technology Integration as the strongest predictive signals for Quality 4.0 maturity classification. The empirical results show that 41% of service organizations operate at a Basic Quality level, whereas only 7% demonstrate maturity aligned with Quality 4.0 excellence. Practical implicationsManagers can use an ML-driven model to assess their current Quality 4.0 maturity, identify critical improvement areas, and prioritize investments in AI, digital quality management, cultural readiness, and capability development. The model's explainable ML outputs also support evidence-based decision-making and clearer alignment between technological adoption and organizational development. Originality/valueThis study introduces an empirically grounded, socio-technical, and explainable ML based Quality 4.0 maturity assessment framework tailored to service organizations in a developing economy context. By combining Latent Class Analysis with interpretable machine learning, the framework advances both methodological rigor and practical transparency in maturity assessment.
Purpose This study examines how consumers interpret differentiated food quality labels in complex markets, focusing on cognitive accessibility and heuristics to explain why signals such as local origin can outweigh formal or technically complex certifications. Design/methodology/approach The article combines bibliometric analysis with a qualitative scoping review. A corpus of 510 publications from 1996–2026 was analysed using science-mapping techniques, followed by a cluster-guided synthesis of evidence on label proliferation, consumer interpretation, willingness to pay and territorial outcomes. Findings The literature has shifted from information provision and attitudes towards the economic valuation of sustainability attributes. The synthesis identifies label overload, attention competition, cue substitution, hypothetical bias and divergence between consumer valuation and territorial outcomes. Local origin often functions as an accessible cue bundling authenticity, trust, freshness and community support, which can increase its influence relative to more complex certifications. Practical implications Regulators, certification bodies and firms should assess overlap before adding labels, organise information hierarchically and combine credible verification with intuitive design. Consumer education should clarify what accessible claims such as “local” do and do not guarantee. Originality/value The study develops a multi-label heuristic framework distinguishing technical credibility from cognitive accessibility and specifying how their relative influence changes with label density. It integrates insights on trust, comprehension, label proliferation and heuristic choice to explain cross-label substitution, local-cue dominance and sub-additive valuation.
Purpose Service quality remains fragmented across professional domains, creating challenges for theory and practice, particularly in underexplored areas. This review aims to map the existing literature, synthesise the current understanding, and propose strategic directions for future research. Design/methodology/approach This study conducted a systematic scoping review of 60 peer-reviewed journal articles across diverse professional domains between 1985 and 2025. The literature was sourced primarily from Scopus and Web of Science, supplemented by Google Scholar. The PRISMA flow diagram guided the selection process to ensure transparency and rigour. Data were systematically coded and categorised to identify key characteristics and themes. VOSviewer (v1.6.20) and MS Excel were used for organisation, frequency, and thematic synthesis. Findings Four thematic characteristics formed five distinct patterns: a client-centric perspective, structured frameworks leading to quantitative dominance, contextual disparity, pre-decided determinants, and ambiguity in definition. Using the PAGER framework, these patterns were synthesised to guide future research towards dual perspectives, methodological shifts, contextual expansion, service-specific determinants, and achieve definitional precision for a theoretically and practically enhanced perception of service quality across multiple professional disciplines. Originality/value This review is the first to synthesise the understanding of service quality in professional services across multiple disciplines. It provides a comprehensive overview of conceptual and contextual development, outlining research avenues to foster a more inclusive, context-sensitive approach to service quality.
Purpose The purpose of this paper is to explore the Six Sigma Barriers Factors (SSBF) in Tunisian service companies. Furthermore, it aims to assess the causal link between SSBF and Six Sigma Project Success (SSPS). Design/methodology/approach This study adopts a mixed-methods design, integrating qualitative case studies from twelve service firms and a quantitative survey involving 98 Tunisian companies. The research model is tested using the partial least squares (PLS) technique based on SmartPLS3 software. Findings The result reveals a significant relationship between cultural barriers (BR) and Training BR as well as between Statistical BR and Financial BR, and between Organizational BR and Cultural BR. Furthermore, the finding confirms the direct significant impact of Financial Barriers (FB) on Six Sigma Project Success (SSPS). However, it shows a statistically insignificant effect of ORGBR on SSPS. Practical implications This study provides academics and practitioners with streamlined guidance and critical insights enabling them to anticipate and overcome potential obstacles, thereby ensuring successful implementation and ongoing organizational growth and optimization. Originality/value This study is unique as it is the first to explore and develop a measurement instrument for SSBF in Tunisian service firms and to analyze their impact on SSPS using the PLS technique.
