Collaborators: Jan Dul

Theoretical ‘‘necessary but not sufficient’’ statements are common in the organizational sciences. Traditional data analyses approaches (e.g., correlation or multiple regression) are not appropriate for testing or inducing such statements. This article proposes necessary condition analysis (NCA) as a general and straightforward methodology for identifying necessary conditions in data sets. The article presents the logic and methodology of necessary but not sufficient contributions of organizational determinants (e.g., events, characteristics, resources, efforts) to a desired outcome (e.g., good performance). A necessary determinant must be present for achieving an outcome, but its presence is not sufficient to obtain that outcome. Without the necessary condition, there is guaranteed failure, which cannot be compensated by other determinants of the outcome. This logic and its related methodology are fundamentally different from the traditional sufficiency-based logic and methodology. Practical recommendations and free software are offered to support researchers to apply NCA.

Publications:

Dul, J. (2016) Necessary Condition Analysis (NCA): Logic and methodology of “necessary but not sufficient” causality. Organizational Research Methods 19(1), 10-52.

Collaborators: Jan Dul

Single necessary (but not sufficient) conditions are critically important for business theory and practice.Without them, the outcomes cannot occur, and other conditions cannot compensate for this absence. Currently two analytical approaches are available for identifying single necessary conditions: Necessary Condition Analysis (NCA), which was recently developed, and fuzzy-set qualitative comparative analysis (fsQCA), which is a more established approach. FsQCA normally focuses on sufficient but not necessary configurations, but can also identify necessary but not sufficient conditions. This study uses NCA to analyze two examples of empirical datasets published in the Journal of Business Research that use fsQCA to identify single necessary conditions. A comparison of the results of NCA and fsQCA shows that NCA can identify more necessary conditions than fsQCA and can specify the level of the condition that is required for a given level of the outcome. 

Publications:

Dul, J. (2016). Identifying single necessary conditions with NCA and fsQCA. Journal of Business Research, 69(4):1516-1523.

Collaborators: James LeBreton and Jan Dul

We compare Necessary Condition Analysis (NCA) with  Ordinary Least Squares regression analysis (OLS). We discuss the underlying assumptions of NCA and OLS, and show that NCA is insensitive to a common problem of OLS: omitted variable bias, implying that models for testing single necessary conditions can be simple and do not require inclusion of control variables. We conclude that NCA and OLS are complementary logical approaches. NCA can explain why outcomes, that are possible according to OLS, may not be produced because the right level of the necessary condition is not in place. OLS can explain how outcomes can be produced on average when all necessary conditions are in place. We believe that by applying both logics and methods organizational phenomena can be better understood.

Collaborators: Zsófia Tóth and Jan Dul

We study the supplier management of a world-class provider of integrated power systems, propulsion solutions and other services that developed a strong position in civil aerospace. As in the aerospace industry the entry barriers and the need for continuous innovation are high, the company needs to make relationship-specific investments to forge relationships with existing and potential future suppliers. In order to allocate resources most effectively, the strategic consideration of supplier attractiveness based on past experiences, future expectations, risks and dependencies is vital. Based on an extensive general literature review of potential drivers of supplier attractiveness we formulate hypotheses on necessary conditions and sufficient configurations to be tested in the company’s setting. After in-depth interviews of senior managers / executives at the company and other data collection approaches we apply NCA and fsQCA to test the hypotheses.

Collaborators: Wendy van der Valk, Regien Sumo, Jan Dul, Roger Schroeder

Main stream research predominantly views contracts as being sufficient for (i.e., driving) performance. In contrast, necessity-thinking implies that contracts allow performance to exist: if the necessary condition is not in place (at the right level), the desired performance will not occur, irrespective of other drivers of performance. Statements implying necessity are common in supply management research; yet, to date, an appropriate tool for testing such statements has been lacking. This article makes the case for the newly developed Necessary Condition Analysis (NCA) method, and applies it to data on forty-eight buyer-supplier service outsourcing relationships to explore the necessity of contracts for a specific relationship outcome, i.e., supplier-led innovation. Also, the necessity of trust is explored, as contracts are implemented within a broader context that involves social characteristics of relationships. The results show that successful relationships, i.e., relationships that have high levels of innovation (as observed in the top ten percent of the relationships studied) must necessarily have contracts with at least medium levels of contractual detail, as well as the highest levels of trust. In relationships with low levels of innovation (i.e., innovation levels that can be achieved by about half of the relationships), neither of the conditions (i.e., contracts and trust) is necessary. As such, applying NCA results in a fundamentally different understanding of the relationship between innovation, and contracts and trust. The results indicate that managers should first ensure the right levels of these necessary conditions, before giving attention to other factors that (on average) produce innovation.

Publications:

Van der Valk, Sumo, R., Dul, J. & Schroeder, R. (2016). When are contracts and trust necessary for innovation in buyer-supplier relationships? A Necessary Condition Analysis. Journal of Purchasing and Supply Management  (in press).

Collaborators: Barbara Vis and  Jan Dul

Analyzing relationships of necessity is important for both scholarly and applied research questions in the social sciences. An often-used technique for identifying such relationships—fuzzy set Qualitative Comparative Analysis (fsQCA)—has limited ability to make the most out of the data used. The set-theoretical technique fsQCA makes statements in kind (e.g., ‘‘a condition or configuration is necessary or not for an outcome’’), thereby ignoring the variation in degree. We propose to apply a recently developed technique for identifying relationships of necessity that can make both statements in kind and in degree, thus making full use of variation in the data: Necessary Condition Analysis (NCA).With its ability to also make statements in degree (‘‘a specific level of a condition is necessary or not for a specific level of the outcome’’), NCA can complement the in kind analysis of necessity with fsQCA.

Publications: 

Vis, B. & Dul, J. (2016), Analyzing relationships of necessity not just in kind but also in degree: Complementing fsQCA with NCA, Sociological Methods and Research

Collaborators: Tony Hak, Ferdinand Jaspers, and Jan Dul

In organizational research the object of study is often a process, that is, a complex of events and activities that unfolds over time. In this chapter we focus on temporally ordered configurations, which can be defined as those configurations in which conditions occur in a specific temporal order. We illustrate the aims, characteristics, and limitations of several approaches that have been proposed as tools for the analysis of temporal order. Our illustration involves an analysis of the ‘‘gestation activities’’ of nascent entrepreneurs, that is, persons involved in the creation of a new firm. We aim to identify temporal sequences of gestation activities that generate or allow a successful outcome of the gestation process, while an occurrence of the same activities in another temporal order will not generate or allow that outcome. First we discuss Event Structure Analysis and Optimal Matching and conclude that these approaches cannot provide the kind of analysis that we are aiming at in this chapter. Then we discuss Temporal Qualitative Comparative Analysis, for which our analysis points to technical limitations that constrain its application. We then present and discuss an alternative approach, Temporal Necessary Condition Analysis.

Publications:

Hak, T., Jaspers, F., & Dul, J. (2013). The analysis of temporally ordered configurations: Challenges and solutions. In P. Fiss, B. Cambre, & A. Marx (Eds), Configurational theory and methods in organizational research. Vol. 38: 107–127. Bingley: Emerald.

Collaborators: Gerarda Westerhuis, Jan Dul, Abe de Jong and Tony Hak

This paper investigates the necessary conditions for successful performance in mergers and acquisitions in banking. In mergers and large acquisitions the success of the restructuring may depend on a set of conditions that must be present or, in other words, of which the presence is «necessary». This paper specifies a set of hypotheses about such necessary conditions and performs tests on a set of Dutch mergers and acquisitions in the Dutch financial sector in the period 1960-1991. The mergers in our sample include both domestic and cross-border transactions. This allows us to relate to the conference theme as we will discuss the additional tension that arises in international acquisitions, when compared to domestic takeovers. This paper has two contributions to the literature. First, the paper describes and applies necessary condition analysis (NCA), a new method of theory-building and theory-testing that requires only a small number of cases (Dul et al., 2010). Second, the paper describes the conditions that were necessary for the success of mergers and acquisitions in the Dutch financial sector in the period 1960-1991. The business history literature currently contains many case studies of companies or industries. These studies are eclectic in their view on the companies and therefore present broad perspectives. Several review studies have been written, which generalize based on sets of case studies. Business history researchers struggle with a Catch 22 situation where the historical approach requires in depth analysis of individual cases, while generalizations require larger sets of cases (Coleman, 1987; Wilson, 1995). In their recent review Jones and Zeitlin (2007) conclude that the core of business history research is case study research, while increasingly comparative studies are published. Necessary Condition Analysis is a form of analysis in which generalization can be achieved based on an in-depth analysis of a small number of cases. We study mergers and focus on the performance during the trajectory of integration immediately following the merger decision. Integration of the companies is our measure of performance of the merger process. Successful integration occurs when the goals set at the time of the merger are reached. We study mergers in which the leading company is Dutch in the period 1960-1991. We study mergers in the financial industry, including commercial and investment banking and insurance. Our sources are secondary sources, including company histories, newspaper/magazine articles, and biographies.

Publication:

Westerhuis, G., Dul, J., De Jong, A., & Hak, T. (2012). Success in bank mergers. An application of Necessary Condition Analysis (NCA) in business history. Book of Abstracts, p.31. 16^th Annual conference of the European Business History Association congress, Paris, Aug-1 Sep 2012.