Beyond net effects: why fuzzy-set qualitative comparative analysis is the future for modeling social media artrepreneurial success

Artrepreneurship is the process of combining an artist's creative abilities with the marketplace for commercial success. It is the practice of bringing artistic endeavours to translate them into money (Hoffmann et al., 2021). Success of present world artrepreneurs is rarely a straight line-artrepreneurs rely significantly on social media, but it cannot be justly regarded that there is a direct relationship between artrepreneurship and social media mastery. The notion of entrepreneurial success itself is multifaceted, encompassing financial achievement, personal satisfaction, innovation, and social contribution, yet it has also faced criticism for being conceptually ambiguous and overly focused on economic outcomes (Fisher et al., 2014). A digital artist who masters algorithms and networking may thrive just as much as a talented painter who gains followers through genuine art creation and storytelling. Both succeed-but in entirely different ways.Most of the available models, however, simply simplify these complex, contextspecific results into single-variable measures, or additive measures, as though success can be reduced to net effects of independent factors. With social media-based artrepreneurship, this simplification is what clouds the dynamism of the artistic creativity, the technological involvement and contextual flexibility that, in fact, are the qualities that determine success within the digital creative economies. These artistic, technological and algorithmic interrelations show why traditional neteffect models such as regression, SEM and correlational approaches are inadequate.They make the assumptions of linearity, independence, and symmetrical causation, and social media artrepreneurship can be characterized as consisting of conjunctural processes, path-dependent processes, and asymmetric processes. This complexity logically demands a set-theoretic approach like fsQCA, which is intended to examine equifinality, causal asymmetry and context-dependent interaction between conditions. Fuzzy Set Qualitative Comparative Analysis takes prominence here. Often denoted as fsQCA, it provides information on what combinations of causes or conditions make a certain outcome occur, rather than just answering how much one variable has an effect on another variable. The method is particularly applicable to the creative industries where there might be various paths towards success-or as it has been referred to as equifinality. Through the adoption of fsQCA, research in social media artrepreneurship will be able to detect the context-specific, subtle structures that constitute digital creative success, and provide deeper, more accountable modes of explaining success in the arts.With this topography of causal complexity laid out, it is clear why a framework that is able to model multitrack paths, asymmetrical relations and context-specific interactions is not only desirable but also indispensable. fsQCA explicitly responds to such a methodological requirement by complying with the realities of digital creative labour.Success in entrepreneurship as it is captured in this study is conceived to be a multifactorial construct to the point of going beyond financial measures. It is the personal perception and evaluation of how the criteria that are considered of relevance to the entrepreneur were met. There are many business indicators of success that the entrepreneur may prefer and monetary returns are just one of the possible alternatives. The five major aspects used by the entrepreneur to measure success include the performance of the firm, the relations at work, personal gratification, contribution to the community, and personal monetary gains. This is a wider definition as compared to the conventional perception which tends to lay more emphasis on financial profit or objective economic measures of firm performance (Wach et al., 2016). These multidimensional metrics of success are further disaggregated in the case of social media artrepreneurship since the creators operate within algorithmic visibility, artistic identity, community engagement, and monetization at the same time.Entrepreneurial success is a multidimensional construct that does not have a universal definition and measurement in the existing literature. This effect can be explained by its pointers and surroundings, including personal and business-level performance. Even the entrepreneurs themselves define success as a combination of personal fulfilment, accomplishment of the business objectives and a positive impact of their businesses. It is marked by the existence of personal as well as macro-level variables implying that it cannot be quantified using only financial or economic quantification (Fisher et al., 2014).Fuzzy set theory is a mathematical domain that deals with uncertainty, ambiguity or variability in data and reasoning, by classifying objects to a continuum of grades ranging from 0 to 1, rather than the binary membership of ordinary sets. It is a way of describing groups of objects where membership isn't just yes or no but a matter of degree. The 'membership function' assigns a value between 0 and 1 to each object, indicating how strongly it belongs. Unlike probabilistic approaches, the notion of a fuzzy set is entirely non-statistical (Gupta & Ragade, 1977).Fuzzy-set Qualitative Comparative Analysis (fsQCA) is an asymmetric data modelling approach that integrates fuzzy sets and fuzzy logic theories with Qualitative Comparative Analysis. It enables the analysis of real-life phenomena by developing simple logical statements that explain distinct combinations of conditions leading to a particular effect. Unlike linear-relationship-based traditional methods that prioritize estimating net effects of individual variables, fsQCA explicitly rejects net-effect logic. Instead, it examines causal configurationscombinations of conditions that jointly produce an outcome. Its purpose is not to isolate the impact of a single factor but to understand how multiple conditions cooccur to generate success (Pappas & Woodside, 2021).The adoption of fsQCA in business and management domain studies a systematic approach used to explore causal complexities inherent within organizations. These complexities are often asymmetric and multilayered. Detailed insights on concepts like organisational and management decision making, employee performance and appraisal, market behaviours and adaptability, etc, can be captured by combining qualitative and quantitative evidence. This is why fsQCA is regarded as a catalyst in studying complexities in the area of business (Ott et al., 2018). Dominant net-effect models, especially regression-based modelling, and SEM assume that causes are independent and additive to effects. This does not fit the essence of artrepreneurial success, where algorithmic exposure, artistic identity and communal co-production all interact in mutually reinforcing ways. This conjunctural causation cannot be narrowed down to the peripheral effect of individual variables.The success of social media artrepreneurial is configurational by its very nature.The success of artrepreneurial activities is not the result of a single determinant like posting frequency or follower count. Instead, it is a consequence of the interplay of multiple factors like artistic creativity, content types, interactive mechanisms, algorithm visibility, collaborations, timing and so on. This causal complexity of the conditions leads to equifinality, asymmetry, and conjunctural causation, which are causal issues that fsQCA can uniquely analyse. These multi-path mechanisms cannot be accounted for by linear models since success is assumed to be uniform in its effects, though fsQCA treats success as a result of configurations and therefore is naturally better adapted to digital creative ecosystems.Artrepreneurial success is subjective in nature, i.e. success can take different meanings to different artists. Success can mean income or increased sales for one creator, artistic joy of creation for another and self-actualisation for a third. This subjectivity cannot be computed precisely using traditional statistical tools like regression or correlation. Fuzzy logic enables integration of these incomplete and coinciding meanings to co-exist within a single analytical framework.Asymmetry is another important factor emphasised in fsQCA. For instance, the absence of collaborations doesn't necessarily predict failure, but may act as a fuel for artistic autonomy. fsQCA allows us to explain realities of artrepreneurial ventures as they are-nuanced, fluctuating and multidimensional.All the methodological strengths of fsQCA directly resolve the weaknesses of neteffect models. Where regression isolates variables, their interplay with each other, as a combination, is captured by fsQCA. Where SEM also needs model fit to a single dominant pathway, the multiple and equally valid pathways to success are discovered by fsQCA. The subsequent subsections place each of the advantages of fsQCA in a way as to respond to a particular weakness of the conventional analytical models.Traditional regression models struggle to detect such combinational causation, which fsQCA captures explicitly. Using logical reasoning, fsQCA examines how various combinations of conditions or events lead to specific outcomes. Instead of just producing coefficients in traditional statistical analysis, fsQCA generates logical equations, or "if-then statements", which generate a summary of the set of conditions that led to success. This is noteworthy in medium-N studies, which are more common in creative research, when either there are too many cases or items for purely qualitative enquiries or too few for large-scale statistical applications.Unlike opaque algorithm-driven metrics, fsQCA's calibration foregrounds researcher reasoning. The calibration process of fsQCA is one of its core advantages. From a specific given dataset, researchers can exactly decide what counts as "high" or "low" affiliation. Of course, this needs to be theoretically supported; the choices cannot be solely based on data inference. In a field that is frequently dominated by opaque algorithms and automated measurements, this sense of transparency exhibits reflexivity toward measurement, which can be duly regarded as a progressive move.This contrasts with net-effect outputs that offer limited interpretive depth for creative sectors. fsQCA provides intelligent and interpretable results. Rather than giving a seemingly complex abstract coefficient, say, β = 0.32, fsQCA offers statements like "High artistic expression and consistency →Success". These claims provide valuable insights into established theories, such as effectuation, resource-based views and social capital frameworks; they facilitate productive debates between theory and findings. This interpretability is important to artrepreneurs since knowledge needs to address creative strategy;-authenticity, reach and aesthetic consistency.Symmetry assumptions in regression obscure these multidirectional pathways. Since fsQCA examines an outcome's presence or absence independently, it naturally follows an element of asymmetry. It might not always be possible to explain failure by merely reversing the pathways that lead to success. This reflects an important reality of creativity, where the lack of one essential requirement-say, a high number of followers-may be compensated by another, say, aesthetic uniqueness.Where conventional methods force artificial uniformity, fsQCA integrates diverse types of evidence. fsQCA allows cross-disciplinary integration by incorporating quantitative indicators with qualitative ones, say engagement rates with perceived originality. This method is more holistic as it provides a bridge between numerical and narrative evidence, enabling the capture of fruitful nuances on "impact" beyond numbers.Social media artrepreneurship exemplifies the very problem that research metrics also face: complex outcomes being reduced to simple indicators.The paradigm shift toward fuzzy-set and configurational thinking holds implications not only for artrepreneurship research but also for the wider field of research metrics and analytics. Similar tensions exist between both domains-the need to assess complex phenomena by applying indicators that are often crude to capture complexities. In the context of research evaluation, traditionally, citation counts stood as the ultimate indicator of influence. But now more emphasis is given to the recognition that impact is multifaceted, which includes social relevance, novelty in methodology, policy reach and many more. fsQCA offers a conceptual bridge between these debates, showing the importance of relying on combinations of complementary conditions rather than depending on a single indicator.Traditional analytics assumed that "more is better"-more followers, more likes, more engagement. Yet, creative success is usually a result of a balance of several conditions. For instance, extremely high visibility may reduce authenticity, whereas niche focus might increase community trust. fsQCA gives due recognition to such conditional interdependencies directly. This approach persuades researchers and scholars to rethink digital metrics themselves-not as distinct numbers but as ingredients which must be combined to produce meaningful insights. This is not just a methodological revamp; it is philosophical, which helps understand performance in digital ecosystems.A configurational viewpoint also aligns with the increasing demand for responsible metrics in academia and beyond. Instead of pursuing a single dominant success narrative, fsQCA shows that various forms of success can exist together, with some based on integrity and influence, while others on reach and visibility. It suggests that boosting one indicator may possibly worsen others.By adopting fuzzy reasoning, institutions and policy makers can develop multi-dimensional evaluation frameworks that honour outcome variabilities. This is particularly significant in the creative economy as value and innovations frequently emerge in unexpected, context-specific ways.For organizations that foster creative endeavours like art councils and digital platforms, fsQCA promotes customized interventions. Instead of looking for a universal formula for success, they can find clusters of favourable circumstances. The synergy between peer networking and digital literacy instructions, for instance, may be highlighted in one configuration, while algorithmic fluency and novel creativity could be highlighted in another.Such findings can direct training and funding programs that represent the plurality of creative pathways, instead of forcing a one-size-fits-all strategy. This is consistent with broader research metric goals -to assess human endeavour in a fair, open and sensitive way.Despite of its benefits, fsQCA has its drawbacks. Just like any other approach that deals with interpretation, fsQCA mostly relies on the judgement and theoretical clarity of the researcher.One recurring concern is calibration-deciding what counts as "high" or "low" membership in a fuzzy set. The thresholds that a researcher fixes can have a high impact on the results. Thus, solid theoretical justification, triangulation of data sources and robustness checks are essential. Both a virtue and a weakness, calibration necessitates interpretative discipline and forces openness.Another issue is the limited diversity problem-the fact that not all logically possible combinations of conditions are observed in real data. This can constrain generalizability. fsQCA's logic of sufficiency rather than prediction means that findings describe what works in specific contexts, not universal laws. But arguably, this contextualism is an advantage in studying creative domains, where uniqueness is the rule rather than the exception.fsQCA also requires balance. Results become cumbersome when there are too many conditions; crucial nuances are lost when there are too few. Instead of overcomplicating models, researchers should let theoretical logic direct the addition of conditions.Lastly, a more profound epistemic change is necessary to embrace a configurational framework. Scholars are urged by fsQCA to shift from probabilistic to set-theoretic thinking, from determining the likelihood of an occurrence to determining the circumstances in which it occurs. Those who have been taught in variable-based traditions may find this reorientation unsettling, yet it offers up new conceptual avenues. It pushes us to view causality as compositional and context-bound, which is a viewpoint that feels much more in line with the actual experience of creative work.A recurring critique from quantitative traditions concerns dynamic endogeneity-where successful outcomes reshape the very conditions that produced them. Although the estimation of temporal feedback loops is not the same in fsQCA as it is in econometric models, new extensions like Temporal QCA (TQCA) promise fruitful applications of temporal sequencing in configurational analysis.The second criticism that has been made is related to the failure to estimate individual variables marginal effects. It is a design aspect and not a limitation: fsQCA does not aim to dispel independent contributions but to expose the way conditions interact. However, scholars can supplement fsQCA with variance-based techniques when they want to get policy-level interpretation.There are several promising directions for extending fsQCA's application to creative industries and beyond:Most existing fsQCA studies treat time as static, yet creative success is inherently dynamic. Longitudinal fsQCA could trace how configurations evolve as platforms, algorithms, and audience preferences change. This would help identify which combinations remain stable and which adapt over time. TQCA or sequence-sensitive calibration rules could be employed to track configuration evolution.A multi-group fsQCA design would allow systematic comparison across platforms. Comparative fsQCA could explore whether the conditions for success on one platform, such as Instagram, differ fundamentally from those on TikTok or YouTube. This would illuminate both platform-specific logics and cross-cutting patterns that the broader creative may need calibration to meanings of or context not only creative but also the of success studies might how fuzzy innovation, or audience across research would the of configurational thinking, both theory and could identify which fsQCA using set-theoretic logic. The of fsQCA may in can help detect configurations or while fsQCA interpretability and theoretical A approach could the strengths of producing insights that are yet conceptually must how measure fuzzy such as creative satisfaction, or perceived influence. 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