This book addresses a variety of advanced topics in Necessary Condition Analysis (NCA) to support users, readers and reviewers of the method. The book supplements existing methodological publications that describe NCA at the basic level (Dul, 2016b, 2020; Dul, Van der Laan, et al., 2020). Also summaries of the method have appeared in different substantive fields including Human Resource Management (Hauff et al., 2021), Marketing (Dul, Hauff, et al., 2021), Tourism Management (Tóth et al., 2019), Education (Tynan et al., 2020), Creativity (Dul, Karwowski, et al., 2020), Supply Chain Management (Bokrantz & Dul, 2022), and International Business (Richter & Hauff, 2022).

NCA is an emerging research method that is rapidly entering a variety of research fields in the social, medical and technical sciences. The publication in 2016 of NCA’s core paper (Dul, 2016b), which Bergh et al. (2022) consider a ‘gold standard’ of a methodological contribution, marks the start of NCA. Since then, the number of publications that apply NCA in Web of Science (Clarivate) ranked journals has increased to a total of 62 articles by the end of 2021 (see Figure 0.1).

Cumulative number of publications in Web of Science (Clarivate) ranked journals that apply NCA. 'Q' stands for the journal quality in terms of category journal rank by impact factor. Q1 = first quartile, etc. (Situation of 31 December 2021).

Figure 0.1: Cumulative number of publications in Web of Science (Clarivate) ranked journals that apply NCA. ‘Q’ stands for the journal quality in terms of category journal rank by impact factor. Q1 = first quartile, etc. (Situation of 31 December 2021).

About a quarter (26%) of the articles use NCA as the sole or primary research method. Another about a quarter (23%) combine NCA with Qualitative Comparative Analysis (QCA). About half (51%) of the articles are multi-method articles that apply NCA in combination with regression based methods like Multiple Linear Regression (MLR), variance-based Structural Equation Modeling (SEM), or Partial-Least-Squares Structural Equation Modeling (PLS-SEM).

Recent examples of articles with NCA as the main method are Frommeyer et al. (2022), Camitan IV & Bajin (2021),Kumar (2021), Tuuli & Rhee (2021), Chaurasia et al. (2020) and Lee & Jeong (2020).

Recent examples of articles that combine NCA with QCA are Eggers et al. (2022), Gantert et al. (2022), Du & Kim (2021), Kopplin & Rösch (2021), Mazumder & Garg (2021), Torres & Godinho (2021), Bouncken, Fredrich, et al. (2020), Bouncken, Ratzmann, et al. (2020) and Delgosha et al. (2021).

Recent examples of articles that combine NCA with regression-based methods are for MLR Sharma et al. (2022), Costa et al. (2021), Bakır et al. (2022), Jain et al. (2021), Jaiswal & Zane (2022), Klimas et al. (2021), Korman et al. (2022), Kobarg et al. (2020), Karwowski et al. (2020) and Richter, Schlaegel, et al. (2020), for SEM Lee & Jeong (2021) and Franke & Foerstl (2021), and for PLS-SEM Sukhov et al. (2022), Pangarso et al. (2022), Ortigueira-Sánchez et al. (2022), Cheung et al. (2022), Ortigueira-Sánchez et al. (2022), Pangarso et al. (2022), Koay et al. (2022), Zahrai et al. (2022), Della Corte et al. (2021), Richter et al. (2021), Kopplin & Rausch (2021), Kopplin et al. (2021), Liu et al. (2021) and Lyu et al. (2021).

Some articles that apply NCA did not find a necessary condition (Batey et al., 2021; Golini et al., 2016) but the majority identified at least one. Not finding a necessary condition might be a valuable result, because such result tells that a supposed essential factor for an outcome does not need to be present and its absence can be compensated (e.g., Arenius et al., 2017). On the other hand, finding a large number of potential necessary conditions in an explorative study may not be informative when several conditions do not have a theoretical meaning or are trivial (e.g., Gantert et al., 2022; Klimas et al., 2021; Stek & Schiele, 2021).

NCA can be used in any type of research that aims to find causal relationships between causes and effects. With conventional regression based research methods (e.g, multiple linear regression, structural equation modeling), research questions about cause-effect relationships are often formulated like ‘what is the effect of \(X\) on \(Y\)?’ and related hypotheses similar to ‘\(X\) has a positive (or negative) effect on \(Y\).’ Such causal relationship can be graphically shown as an arrow between \(X\) and \(Y\) indicating a temporal direction: first \(X\), then \(Y\), with a + or - sign shown above the arrow indicating that \(X\) increases or decreases \(Y\). However, the type of causality is usually not specified. The regression equation consisting of terms that are added to produce the effect including an ‘error term,’ implicitly assumes additive causal logic and average effects. Consequently, cause \(X\) is assumed to contribute to producing effect \(Y\) on average, and the absence of \(X\)can be compensated by other causes. In other words: \(X\) is a sufficient but not necessary contributor to \(Y\).

However, in NCA, cause \(X\) is assumed to be necessary but not sufficient for effect \(Y\). The research question is formulated as ‘is \(X\) necessary for \(Y\)?’ and the corresponding hypothesis as ‘\(X\) is necessary for \(Y\).’ If \(X\) is necessary for \(Y\), single cause \(X\) can stop the outcome when it is absent or has a low value. NCA does not make a claim about the average contributing effect of necessary causes.

This means that any conventional research question or hypothesis about causal relationships can be revisited from the perspective of necessity. The cause could be necessary (essential) for the effect. It is important to know whether causes are necessary or not, because if any necessary cause is absent, the effect cannot be achieved. In practice this means that acting on other causes than the bottleneck cause has no effect (no compensation possible) and would be a waste of effort.

The entire NCA method consists of three parts:

  • Using necessity logic for developing theoretical causal statements (theory, hypotheses).

  • Data analysis for calculating necessity parameters.

  • Statistical testing for evaluating necessity parameters.

Because NCA is an emerging method, new insights are gained, and extensions are being developed. This book intends to provide the latest insights and developments of NCA. The topics are selected from interactions with the research community at conferences, webinars, workshops and in email exchanges. Some topics are extensively covered, others await elaboration.

This book was first published online in 2021. As the NCA approach is developing, the content of the book is developing as well. The book will therefore remain an online book with a version number. Please, contact the author if you want to react on the book or wish to have new topics covered in it. Your contribution will be acknowledged.

The suggested reference to the book is Dul, J. (2021) Advances in Necessary Condition Analysis. The book is hosted on https://bookdown.org/ncabook/advanced_nca2/.

Version history:

Version 0.1 (October 10, 2021). First published (draft) version. Several sections under construction.

Version 1.0 (March 20, 2022). First full version. All sections available.


Arenius, P., Engel, Y., & Klyver, K. (2017). No particular action needed? A necessary condition analysis of gestation activities and firm emergence. Journal of Business Venturing Insights, 8, 87–92. https://doi.org/10.1016/j.jbvi.2017.07.004
Bakır, M., Akan, Ş., Özdemir, E., Nguyen, P.-H., Tsai, J.-F., & Pham, H.-A. (2022). How to achieve passenger satisfaction in the airport? Findings from regression analysis and necessary condition analysis approaches through online airport reviews. Sustainability, 14(4), 2151. https://doi.org/10.3390/su14042151
Batey, M., Hughes, D. J., Crick, L., & Toader, A. (2021). Designing creative spaces: An experimental examination of the effect of a nature poster on divergent thinking. Ergonomics, 64(1), 139–146. https://doi.org/10.1080/00140139.2020.1811398
Bergh, D. D., Boyd, B. K., Byron, K., Gove, S., & Ketchen Jr, D. J. (2022). What constitutes a methodological contribution? Journal of Management. https://doi.org/10.1177/01492063221088235
Bokrantz, J., & Dul, J. (2022). Building and testing necessity theories in supply chain management. Journal of Supply Chain Management, in press. https://onlinelibrary.wiley.com/doi/10.1111/jscm.12287
Bouncken, R. B., Fredrich, V., & Kraus, S. (2020). Configurations of firm-level value capture in coopetition. Long Range Planning, 53(1), 101869. https://doi.org/10.1016/j.lrp.2019.02.002
Bouncken, R. B., Ratzmann, M., Barwinski, R., & Kraus, S. (2020). Coworking spaces: Empowerment for entrepreneurship and innovation in the digital and sharing economy. Journal of Business Research, 114, 102–110. https://doi.org/10.1016/j.jbusres.2020.03.033
Camitan IV, D. S., & Bajin, L. N. (2021). The importance of well-being on resiliency of filipino adults during the COVID-19 enhanced community quarantine: A necessary condition analysis. Frontiers in Psychology, 12, 908. https://doi.org/10.3389/fpsyg.2021.558930
Chaurasia, S. S., Kaul, N., Yadav, B., & Shukla, D. (2020). Open innovation for sustainability through creating shared value-role of knowledge management system, openness and organizational structure. Journal of Knowledge Management, 24(10), 2491–2511. https://doi.org/10.1108/JKM-04-2020-0319
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Delgosha, M. S., Saheb, T., & Hajiheydari, N. (2021). Modelling the asymmetrical relationships between digitalisation and sustainable competitiveness: A cross-country configurational analysis. Information Systems Frontiers, 23, 1317–1337. https://doi.org/10.1007/s10796-020-10029-0
Della Corte, V., Aria, M., Del Gaudio, G., Barney, J. B., Cobanoglu, C., & Sepe, F. (2021). The relevance of relational capabilities in collaborative decisions. International Journal of Contemporary Hospitality Management, 33(12), 4391–4417. https://doi.org/10.1108/IJCHM-01-2021-0037
Du, Y., & Kim, P. H. (2021). One size does not fit all: Strategy configurations, complex environments, and new venture performance in emerging economies. Journal of Business Research, 124, 272–285. https://doi.org/10.1016/j.jbusres.2020.11.059
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Dul, J., Hauff, S., & Tóth, Z. (2021). Necessary condition analysis in marketing research. In R. Nunkoo, V. Teeroovengadum, & C. Ringle (Eds.), Handbook of research methods for marketing management. Edward Elgar Publishing. https://www.e-elgar.com/shop/gbp/handbook-of-research-methods-for-marketing-management-9781788976947.html
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Dul, J., Van der Laan, E., & Kuik, R. (2020). A statistical significance test for necessary condition analysis. Organizational Research Methods, 23(2), 385–395. https://doi.org/10.1177/1094428118795272
Eggers, F., Risselada, H., Niemand, T., & Robledo, S. (2022). Referral campaigns for software startups: The impact of network characteristics on product adoption. Journal of Business Research, 145, 309–324. https://doi.org/10.1016/j.jbusres.2022.03.007
Franke, H., & Foerstl, K. (2021). Goals, conflict, politics, and performance of cross-functional sourcing teams—results from a social team experiment. Journal of Business Logistics, 41(1), 6–30. https://doi.org/10.1111/jbl.12225
Frommeyer, B., Wagner, E., Hossiep, C. R., & Schewe, G. (2022). The utility of intention as a proxy for sustainable buying behavior–a necessary condition analysis. Journal of Business Research, 143, 201–213. https://doi.org/10.1016/j.jbusres.2022.01.041
Gantert, T. M., Fredrich, V., Bouncken, R. B., & Kraus, S. (2022). The moral foundations of makerspaces as unconventional sources of innovation: A study of narratives and performance. Journal of Business Research, 139, 1564–1574. https://doi.org/10.1016/j.jbusres.2021.10.076
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Hauff, S., Guerci, M., Dul, J., & Rhee, H. van. (2021). Exploring necessary conditions in HRM research: Fundamental issues and methodological implications. Human Resource Management Journal, 31(1), 18–36. https://doi.org/10.1111/1748-8583.12231
Jain, N. K., Bhaskar, K., & Jain, S. (2021). What drives adoption intention of electric vehicles in india? An integrated UTAUT model with environmental concerns, perceived risk and government support. Research in Transportation Business & Management, 100730. https://doi.org/10.1016/j.rtbm.2021.100730
Jaiswal, M., & Zane, L. J. (2022). Drivers of sustainable new technology diffusion in national markets: The case of electric vehicles. Thunderbird International Business Review, 64(1), 25–38. https://doi.org/10.1002/tie.22243
Karwowski, M., Jankowska, D. M., Brzeski, A., Czerwonka, M., Gajda, A., Lebuda, I., & Beghetto, R. A. (2020). Delving into creativity and learning. Creativity Research Journal, 32(1), 4–16. https://doi.org/10.1080/10400419.2020.1712165
Klimas, P., Czakon, W., & Fredrich, V. (2021). Strategy frames in coopetition: An examination of coopetition entry factors in high-tech firms. European Management Journal. https://doi.org/10.1016/j.emj.2021.04.005
Koay, K. Y., Cheah, C. W., & Chang, Y. X. (2022). A model of online food delivery service quality, customer satisfaction and customer loyalty: A combination of PLS-SEM and NCA approaches. British Food Journal. https://doi.org/10.1108/BFJ-10-2021-1169
Kobarg, S., Stumpf-Wollersheim, J., Schlägel, C., & Welpe, I. M. (2020). Green together? The effects of companies’ innovation collaboration with different partner types on ecological process and product innovation. Industry and Innovation, 27(9), 953–990. https://doi.org/10.1080/13662716.2020.1713733
Kopplin, C. S., Gantert, T. M., & Maier, J. V. (2021). Acceptance of matchmaking tools in coworking spaces: An extended perspective. Review of Managerial Science, 1–33. https://doi.org/10.1007/s11846-021-00498-1
Kopplin, C. S., & Rausch, T. M. (2021). Above and beyond meat: The role of consumers’ dietary behavior for the purchase of plant-based food substitutes. Review of Managerial Science, 1–30. https://doi.org/10.1007/s11846-021-00480-x
Kopplin, C. S., & Rösch, S. F. (2021). Equifinal causes of sustainable clothing purchase behavior: An fsQCA analysis among generation y. Journal of Retailing and Consumer Services, 63, 102692. https://doi.org/10.1016/j.jretconser.2021.102692
Korman, J. V., Van Quaquebeke, N., & Tröster, C. (2022). Managers are less burned-out at the top: The roles of sense of power and self-efficacy at different hierarchy levels. Journal of Business and Psychology, 37, 151–171. https://doi.org/10.1007/s10869-021-09733-8
Kumar, D. (2021). Meteorological barriers to bike rental demands: A case of washington DC using NCA approach. Case Studies on Transport Policy, 9(2), 830–841. https://doi.org/10.1016/j.cstp.2021.04.002
Lee, W., & Jeong, C. (2020). Beyond the correlation between tourist eudaimonic and hedonic experiences: Necessary condition analysis. Current Issues in Tourism, 23(17), 2182–2194. https://doi.org/10.1080/13683500.2019.1611747
Lee, W., & Jeong, C. (2021). Distinctive roles of tourist eudaimonic and hedonic experiences on satisfaction and place attachment: Combined use of SEM and necessary condition analysis. Journal of Hospitality and Tourism Management, 47, 58–71. https://doi.org/10.1016/j.jhtm.2021.02.012
Liu, Y., Yu, C., & Damberg, S. (2021). Exploring the drivers and consequences of the “awe” emotion in outdoor sports–a study using the latest partial least squares structural equation modeling technique and necessary condition analysis. International Journal of Sports Marketing and Sponsorship. https://doi.org/10.1108/IJSMS-12-2020-0232
Lyu, V. C., Chin, W., Zhang, H., & Liu, V. (2021). Value added or overload? A study of the countervailing effects of non-core features on mobile banking apps. Journal of Consumer Behaviour. https://doi.org/10.1002/cb.2003
Mazumder, S., & Garg, S. (2021). Decoding digital transformational outsourcing: The role of service providers’ capabilities. International Journal of Information Management, 58, 102295. https://doi.org/10.1016/j.ijinfomgt.2020.102295
Ortigueira-Sánchez, L. C., Welsh, D. H., & Stein, W. C. (2022). Innovation drivers for export performance. Sustainable Technology and Entrepreneurship, 1(2), 100013. https://doi.org/10.1016/j.stae.2022.100013
Pangarso, A., Winarno, A., Aulia, P., & Ritonga, D. A. (2022). Exploring the predictor and the consequence of digital organisational culture: A quantitative investigation using sufficient and necessity approach. Leadership & Organization Development Journal. https://doi-org.eur.idm.oclc.org/10.1108/LODJ-11-2021-0516
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Sharma, A., Dwivedi, R., Mariani, M. M., & Islam, T. (2022). Investigating the effect of advertising irritation on digital advertising effectiveness: A moderated mediation model. Technological Forecasting and Social Change, 180, 121731. https://doi.org/10.1016/j.techfore.2022.121731
Stek, K., & Schiele, H. (2021). How to train supply managers–necessary and sufficient purchasing skills leading to success. Journal of Purchasing and Supply Management, 27(4), 100700. https://doi.org/10.1016/j.pursup.2021.100700
Sukhov, A., Olsson, L. E., & Friman, M. (2022). Necessary and sufficient conditions for attractive public transport: Combined use of PLS-SEM and NCA. Transportation Research Part A: Policy and Practice, 158, 239–250. https://doi.org/10.1016/j.tra.2022.03.012
Torres, P., & Godinho, P. (2021). Levels of necessity of entrepreneurial ecosystems elements. Small Business Economics, 1–17. https://doi.org/10.1007/s11187-021-00515-3
Tóth, Z., Dul, J., & Li, C. (2019). Necessary condition analysis in tourism research. Annals of Tourism Research, 79. https://doi.org/10.1016/j.annals.2019.102821
Tuuli, M. M., & Rhee, H. van. (2021). How ability, motivation, and opportunity drive individual performance behaviors in projects: Tests of competing theories. Journal of Management in Engineering, 37(6), 04021070. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000969
Tynan, M. C., Credé, M., & Harms, P. D. (2020). Are individual characteristics and behaviors necessary-but-not-sufficient conditions for academic success?: A demonstration of Dul’s (2016) necessary condition analysis. Learning and Individual Differences, 77, 101815. https://doi.org/10.1016/j.lindif.2019.101815
Zahrai, K., Veer, E., Ballantine, P. W., Vries, H. P. de, & Prayag, G. (2022). Either you control social media or social media controls you: Understanding the impact of self-control on excessive social media use from the dual-system perspective. Journal of Consumer Affairs. https://doi.org/10.1111/joca.12449