Guest editorial: Synthesizing knowledge in service research: an introduction to the special issue on meta-analyses and systematic reviews

As service research expands rapidly, the need for rigorous synthesis has never been greater. This editorial introduces a special issue of the Journal of Service Theory and Practice featuring nine papers – five meta-analyses and four systematic reviews – consolidating knowledge across major areas of service theory and practice. We argue that scientific progress depends on the corroboration of findings across independent studies and that synthesis approaches provide a stronger foundation for empirical generalization than single empirical studies alone. Topics range from service robots and service innovation to parasocial relationships, servitization and service quality models, with cross-cutting themes including the context-dependence of service outcomes, technology–human integration and the evolving adequacy of existing theories. The editorial concludes by calling for synthesis research in underexplored areas including digital customer engagement, AI-driven personalization, service ecosystems, frontline employee–technology interaction and organizational culture and service innovation.The field of service research has grown substantially over the past several decades, generating a rich and diverse body of empirical studies that examine the drivers of service quality, customer experience and firm performance. As this literature continues to expand, however, so does the challenge of interpreting findings that are often fragmented, context-specific or at times contradictory. Synthesizing this growing body of knowledge in a rigorous and systematic manner has therefore become one of the most pressing needs in service theory and practice.It is against this backdrop that this special issue of the Journal of Service Theory and Practice was conceived. This issue, titled Advancing the Understanding of Service Theory and Practice: Meta-Analysis and Systematic Review, brings together nine papers that employ rigorous quantitative and qualitative synthesis methods to consolidate, analyze and advance our understanding of key issues in service research. By prioritizing synthesis over single-study empiricism, this special issue responds to growing calls in the marketing and service disciplines for more robust, generalizable and evidence-based research contributions (Hanssens, 2018; Hulland and Houston, 2020; Hunter and Schmidt, 2004).Meta-analyses and systematic reviews occupy a uniquely important place in the research landscape. Unlike individual empirical studies, which are often constrained by sample size, geographic context or methodological choices, these synthesis approaches aggregate evidence across multiple studies, thereby reducing bias, enhancing reliability and generating broader empirical generalizations. Meta-analysis, in particular, employs statistical techniques to combine the results of multiple studies addressing the same research question, offering a cumulative weight of evidence that no single study could achieve alone. Systematic reviews, by contrast, provide comprehensive and transparent qualitative assessments of the existing literature, making them invaluable for theory building, identifying research gaps and critically evaluating the current state of knowledge in a given field. Together, these methods represent powerful tools for advancing both theoretical frameworks and evidence-based practice in service research.The nine papers included in this special issue reflect the breadth and depth of contemporary service research. Five papers employ meta-analytic methods to statistically synthesize findings across studies, while four papers adopt systematic review approaches to generate qualitative and conceptual insights into important service phenomena. Collectively, these contributions address a wide range of topics, identify critical gaps in literature and offer meaningful implications for both researchers and practitioners in the service domain.The advancement of scientific knowledge depends not only on the generation of new findings but also on the corroboration of findings across independent studies, contexts and methodologies (Babin et al., 2021). Corroboration – the process through which a scientific claim is confirmed and strengthened by multiple independent lines of evidence – lies at the heart of rigorous inquiry (Popper, 1959). In marketing and service research, however, the dominant reliance on single empirical studies has posed a challenge to this principle. Individual studies, however carefully designed, are inherently constrained by a range of limitations that make it difficult to draw broad and reliable conclusions from any single piece of research in isolation. Academic researchers become socialized by the academic journal review process to believe a “first strike” is necessary to make a “novel” contribution. All too often, journal acceptance puts considerable weight on novelty defined in this way, that true scientific knowledge building is neglected (Babin et al., 2021). When novelty is defined in such a way, a reviewer trying to re-examine some previously published finding faces the hard result of a rejection because “it has already been done.” Meta-analytic approaches attempt to provide some avenue for corroboration and even present procedures that try to assess and correct for the file-drawer effect, which refers to the body of work now published because of a lack of statistical significance.First, single empirical studies are often limited by sample size and sampling context. A study conducted with a specific population in a particular geographic or cultural setting may produce results that do not generalize beyond that context (Hunter and Schmidt, 2004). For example, findings on service quality perceptions derived from a sample of North American consumers may not accurately reflect the experiences of consumers in Asia or Europe, where cultural norms and service expectations differ considerably. Second, individual studies are susceptible to methodological idiosyncrasies, including variations in measurement instruments, construct operationalizations and analytical approaches, all of which can introduce noise and inconsistency into the literature (Palmatier et al., 2006, 2018). Third, publication bias – the tendency for journals to favor statistically significant results over null findings – further distorts the cumulative body of evidence, creating an inflated and potentially misleading picture of the phenomena under investigation (Rothstein et al., 2005).These limitations are particularly pronounced in service research, a field characterized by a vast and rapidly growing body of empirical studies that frequently produce inconsistent or even contradictory findings. The diversity of service contexts – spanning healthcare, hospitality, retail, financial services and beyond – further compounds the challenge of drawing generalizable conclusions from any single study. Empirical generalizations are the lifeblood of a cumulative science, yet they remain elusive when research is evaluated on a study-by-study basis rather than synthesized across the broader literature (Borenstein et al., 2009; Hanssens, 2018).Meta-analyses and systematic reviews directly address the limitations of single empirical studies by aggregating and synthesizing evidence across multiple independent investigations. In doing so, they provide the cumulative foundation on which marketing knowledge advances. Rather than relying on the findings of any one study, these evidence-synthesis approaches draw on the collective weight of the literature to identify recurring patterns, reconcile inconsistent findings and generate conclusions that are generally more robust and generalizable than those derived from isolated studies (Hulland and Houston, 2020; Palmatier et al., 2018).Systematic reviews accomplish this through a transparent and replicable process used to identify, evaluate and synthesize all relevant studies addressing a clearly defined marketing question. This structured approach reduces the subjectivity often associated with traditional narrative reviews, in which study selection and interpretation may be influenced by the reviewer's prior assumptions or theoretical preferences. By systematically examining the available evidence, review studies help ensure that conclusions are grounded in the full body of relevant marketing research rather than a selective subset of studies (Palmatier et al., 2018).Meta-analyses extend this process by statistically combining the quantitative findings of multiple studies to produce pooled effect-size estimates that better reflect the underlying magnitude of relationships across contexts. This statistical integration increases precision by leveraging larger combined samples and enables researchers to test moderators that explain why effects vary across industries, consumer groups or research settings. In marketing, such analyses have been especially valuable for clarifying boundary conditions, refining theory and informing managerial practice in areas such as relationship marketing, advertising effectiveness, innovation adoption and customer satisfaction (Hulland and Houston, 2020; Eisend, 2015). Accordingly, meta-analyses do not merely confirm prior findings – they strengthen theory development and provide a more reliable evidentiary base for cumulative progress in marketing literature.A cautionary note is in order. The ability to synthesize the literature can be hampered by poor reporting and uncooperative members of the research community. Researchers pour through hundreds of articles to find a few with reporting complete enough to be used in a meta-analysis. All too often, basic descriptive statistics are not provided or details in calculations are missing. For instance, means are often reported without standard deviations or standard errors. Sample sizes by experimental condition are often missing. Studies that use SEM often report correlations between factors but seldom provide detail as to whether the raw correlation estimates are disattenuated for measurement error. In other words, were they computed by the SEM software (AMOS, lavaan, LISREL, etc.)? If so, they are almost certainly disattenuated. If not, they are almost certainly not corrected for measurement error. Furthermore, researchers often are unresponsive to requests for more details about data from recently published studies or uneager to reply to requests appealing to the grey (unpublished) literature. The preciseness of research syntheses depends on a cooperative research community.The case for synthesis research in marketing theory and practice has never been stronger. As the service literature continues to expand rapidly pace, the need to consolidate, evaluate and extend accumulated knowledge becomes increasingly urgent. Scholars in marketing have argued that the discipline should place greater emphasis on research that produces empirical generalizations – findings that hold across studies, contexts and populations – rather than relying primarily on isolated single-study contributions that may add only incrementally to a fragmented evidence base (Hulland and Houston, 2020; Palmatier et al., 2018). 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