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Collaborative public networks have become increasingly important as policy tools to address complex social and health problems. However, despite the broad literature on network effectiveness, there is still insufficient insight in...
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Collaborative public networks have become increasingly important as policy tools to address complex social and health problems. However, despite the broad literature on network effectiveness, there is still insufficient insight into the different determinants of whole network effectiveness, and particularly on how these determinants are related. Based on an empirical comparison of 13 mature networks, this study identified potential environment, structural, and management determinants. Moreover, configurations of the identified determinants leading to network effectiveness were generated using configurational comparative methods. We gained insights into how configurations of determinants impacted network effectiveness and found a dominance of structural and managerial determinants.
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Empirical research methods provide the necessary means to extract relevant information from data. Qualitative Comparative Analysis (QCA), one such method, is currently making first inroads into the development and planning (D&P) community. On the one hand, QCA is well suited for building empirically founded theories emphasizing causal complexity. On the other hand, however, current use of QCA in D&P research is marked by problematic applications of this method whose results misrepresent the empirical evidence marshaled to support them. Policy recommendations that stand on shaky grounds have been issued in consequence. By reanalyzing a recent empirical study on school sanitation maintenance in Belize, this method workshop article shows how the use of QCA can be improved, which should in turn lead to more solid, evidence-based policy recommendations for development interventions....
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Empirical research methods provide the necessary means to extract relevant information from data. Qualitative Comparative Analysis (QCA), one such method, is currently making first inroads into the development and planning (D&P) community. On the one hand, QCA is well suited for building empirically founded theories emphasizing causal complexity. On the other hand, however, current use of QCA in D&P research is marked by problematic applications of this method whose results misrepresent the empirical evidence marshaled to support them. Policy recommendations that stand on shaky grounds have been issued in consequence. By reanalyzing a recent empirical study on school sanitation maintenance in Belize, this method workshop article shows how the use of QCA can be improved, which should in turn lead to more solid, evidence-based policy recommendations for development interventions.
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Background: In recent years, the method of Qualitative Comparative Analysis (QCA) has been enjoying increasing levels of popularity in evaluation and directly neighboring fields. Its holistic approach to causal data analysis reson...
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Background: In recent years, the method of Qualitative Comparative Analysis (QCA) has been enjoying increasing levels of popularity in evaluation and directly neighboring fields. Its holistic approach to causal data analysis resonates with researchers whose theories posit complex conjunctions of conditions and events. However, due to QCA's relative immaturity, some of its technicalities and objectives have not yet been well understood. Objectives: In this article, I seek to raise awareness of six pitfalls of employing QCA with regard to the following three central aspects: case numbers, necessity relations, and model ambiguities. Most importantly, I argue that case numbers are irrelevant to the methodological choice of QCA or any of its variants, that necessity is not as simple a concept as it has been suggested by many methodologists, and that doubt must be cast on the determinacy of virtually all results presented in past QCA research. Method: By means of empirical examples from published articles, I explain the background of these pitfalls and introduce appropriate procedures, partly with reference to current software, that help avoid them. Conclusion: QCA carries great potential for scholars in evaluation and directly neighboring areas interested in the analysis of complex dependencies in config-urational data. If users beware of the pitfalls introduced in this article, and if they avoid mechanistic adherence to doubtful "standards of good practice" at this stage of development, then research with QCA will gain in quality, as a result of which a more solid foundation for cumulative knowledge generation and well-informed policy decisions will also be created.
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This paper analyzes the impact of business incubators on firm survival. Using a configurational comparative method, namely fuzzy-set qualitative comparative analysis (fsQCA), the article also examines whether degree of business in...
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This paper analyzes the impact of business incubators on firm survival. Using a configurational comparative method, namely fuzzy-set qualitative comparative analysis (fsQCA), the article also examines whether degree of business innovation, size, sector, and export activity affects firm survival. Results show that, when combined with other variables (i.e. sector, technology), business size is a sufficient condition for firm survival. Likewise, incubators alone cannot affect survival. A combination between incubators and other factors is necessary to ensure firm survival.
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Researchers need approaches for analyzing complex phenomena when assessing contingency relationships where specific conditions explain an outcome only when combined with other conditions. Using a mixed methods design, we paired co...
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Researchers need approaches for analyzing complex phenomena when assessing contingency relationships where specific conditions explain an outcome only when combined with other conditions. Using a mixed methods design, we paired configurational methods and qualitative thematic analysis to model contingency in veteran community reintegration outcomes, identifying combinations of conditions that led to success or lack of success in community reintegration among US military veterans. This pairing allowed for modeling contingency at a detailed level beyond the capabilities of either approach alone. Our analysis revealed multiple contingent relationships at work in explaining reintegration, including social support, purpose, cultural adjustment, and military separation experiences. This study contributes to the field of mixed methods by pairing a mathematical cross-case method with a qualitative method to model contingency.
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Multi-value Qualitative Comparative Analysis (mvQCA) is a variant of QCA that continues to exist under the shadow of crisp and fuzzy-set QCA. The lack of support for parameters of fit and intermediate solutions has contributed to ...
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Multi-value Qualitative Comparative Analysis (mvQCA) is a variant of QCA that continues to exist under the shadow of crisp and fuzzy-set QCA. The lack of support for parameters of fit and intermediate solutions has contributed to this undeserved status. This article introduces two innovations that put mvQCA on a par with its two sister variants. First, consistency and coverage as the two most important parameters of fit are generalized. Second, the concepts of easy and difficult counterfactuals for deriving intermediate solutions are imported. I demonstrate how to leverage these features in the QCA software package for the R environment. For researchers who do not use QCA, I explain how to exploit Veitch-Karnaugh maps instead for solving set-theoretic minimization problems of low to moderate complexity.
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A significant body of social-scientific literature has developed contextual theories. In a recent contribution to Quality & Quantity, Denk and Lehtinen (Qual Quant 48(6): 3475-3487, 2014) present Comparative Multilevel Analysis (CMA) as an innovative method whereby the effects of contexts on outcomes of interest can be studied configurationally if combined with Qualitative Comparative Analysis (QCA). In contradistinction, I argue that CMA is neither innovative in nor necessary for ascertaining the influence of context in a configurational-comparative manner. QCA is appreciably more powerful than the authors acknowledge and provides all required functionality. In repetition of Rohlfing's (Int J Soc Res Methodol 15(6): 497-506, 2012) verdict on Denk's (Int J Soc Res Methodol 13(1): 29-39, 2010) earlier version of CMA, I conclude that QCA need not be extended in the direction proposed by Denk and Lehtinen. Researchers interested in the contextual analysis of configurational data are well-served by the existing toolbox of QCA....
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A significant body of social-scientific literature has developed contextual theories. In a recent contribution to Quality & Quantity, Denk and Lehtinen (Qual Quant 48(6): 3475-3487, 2014) present Comparative Multilevel Analysis (CMA) as an innovative method whereby the effects of contexts on outcomes of interest can be studied configurationally if combined with Qualitative Comparative Analysis (QCA). In contradistinction, I argue that CMA is neither innovative in nor necessary for ascertaining the influence of context in a configurational-comparative manner. QCA is appreciably more powerful than the authors acknowledge and provides all required functionality. In repetition of Rohlfing's (Int J Soc Res Methodol 15(6): 497-506, 2012) verdict on Denk's (Int J Soc Res Methodol 13(1): 29-39, 2010) earlier version of CMA, I conclude that QCA need not be extended in the direction proposed by Denk and Lehtinen. Researchers interested in the contextual analysis of configurational data are well-served by the existing toolbox of QCA.
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Background: The Department of Veterans Affairs (VA) cares for more patients with hepatitis C virus (HCV) than any other US health care system. We tracked the implementation strategies that VA sites used to implement highly effecti...
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Background: The Department of Veterans Affairs (VA) cares for more patients with hepatitis C virus (HCV) than any other US health care system. We tracked the implementation strategies that VA sites used to implement highly effective new treatments for HCV with the aim of uncovering how combinations of implementation strategies influenced the uptake of the HCV treatment innovation. We applied Configurational Comparative Methods (CCMs) to uncover causal dependencies and identify difference-making strategy configurations, and to distinguish higher from lower HCV treating sites. Methods: We surveyed providers to assess VA sites’ use of 73 implementation strategies to promote HCV treatment in the fiscal year 2015. CCMs were used to identify strategy configurations that uniquely distinguished higher HCV from lower HCV treating sites. Results: From the 73 possible implementation strategies, CCMs identified 5 distinct strategy configurations, or “solution paths.” These were comprised of 10 individual strategies that collectively explained 80% of the sites with higher HCV treatment starts with 100% consistency. Using any one of the following 5 solution paths was sufficient to produce higher treatment starts: (1) technical assistance; (2) engaging in a learning collaborative AND designating leaders; (3) site visits AND outreach to patients to promote uptake and adherence; (4) developing resource sharing agreements AND an implementation blueprint; OR (5) creating new clinical teams AND sharing quality improvement knowledge with other sites AND engaging patients. There was equifinality in that the presence of any one of the 5 solution paths was sufficient for higher treatment starts. Conclusions: Five strategy configurations distinguished higher HCV from lower HCV treating sites with 100% consistency. CCMs represent a methodological advancement that can help inform high-yield implementation strategy selection and increase the efficiency and effectiveness of future implementation efforts.
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Abstract Evidence-based home visiting services (EBHV) are available in states and localities nationwide through the federally-funded Maternal, Infant, and Early Childhood Home Visiting (MIECHV) program. Nevertheless, the anticipat...
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Abstract Evidence-based home visiting services (EBHV) are available in states and localities nationwide through the federally-funded Maternal, Infant, and Early Childhood Home Visiting (MIECHV) program. Nevertheless, the anticipated benefits of EBHV, such as improved child developmental outcomes and increased positive parenting practices, may be undermined by the fact that most families withdraw from services earlier than the model developers planned. Prior studies have linked family attrition with staff turnover. The current study used a mixed methods design to investigate the conditions under which families remained active in the home visiting program after their assigned home visitor resigned. Coincidence Analysis revealed that giving families advance notice (at least 1?month) prior to the home visitors’ upcoming resignation or developing a strong positive working alliance with the inheriting home visitor appears to independently make a difference for ongoing family engagement at 3 and 6?months following a staff transition. These findings suggest that emphasizing how staff turnover is managed may mitigate the risk of family withdrawal during these transitions.
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Some methodologists take the search target of Qualitative Comparative Analysis (QCA) to be causal INUS-conditions, others contend that QCA should instead be used to search for some form of sufficiency that is more substantive than...
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Some methodologists take the search target of Qualitative Comparative Analysis (QCA) to be causal INUS-conditions, others contend that QCA should instead be used to search for some form of sufficiency that is more substantive than mere Boolean sufficiency. While the notion of an INUS-condition has a long and uncontroversial definitional history, Adrian Dusa, in a recent paper, is the first to explicitly define a notion of substantive sufficiency, which he labels robust sufficiency. Dusa's definition, however, is vacuous in real-life research contexts. As an alternative, the first part of this paper non-vacuously defines robust sufficiency and supplies a corresponding notion of minimality, which--I argue--captures Dusa's conceptual intentions. In the second part, I then report and discuss the results of a series of simulation experiments benchmarking the performance of the different QCA solution types in recovering robust sufficiency and minimality.
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