Unravelling the asymmetric effects of procurement practices on firm performance: A complexity theory approach to complementing fsQCA with NCA

Current economic upheavals and supply chain uncertainty have threatened the profitability and sustainability of business organisations. Procurement has proved to be one of the strategies for enhancing firm performance without necessarily increasing revenue with its attendant increase in costs. However, rather than investigating the complex asymmetric relationship between procurement practices and firm performance (which this study advocates), past research engaged in a symmetric evaluation of the relationship between the phenomena. Accordingly, this study, using complexity theory, employs fsQCA and NCA on a sample of 150 respondents from private universities in Ghana to (a) identify different combinations of procurement practices, namely procurement planning, supplier partnership, contract management, and compliance, that lead to firm performance and (b) explore the necessity of these procurement practices (in kind and degree) for firm performance. Whereas the findings from fsQCA reveal three distinct combinations of procurement practices for high firm performance and further suggest that none of the procurement practices was necessary for firm performance, the NCA results suggest that two out of the four procurement practices investigated are necessary for firm performance and hence must be present in the causal recipes produced by fsQCA to guarantee that they lead to firm performance. The study offers pathways to firm performance through procurement practices and demonstrates how to complement fsQCA with NCA to ensure that causal recipes produced by fsQCA can produce the outcome.

Dataset on an extended technology acceptance model: A combined application of PLS-SEM and NCA

As technology has become indispensable in consumers' daily life and economic growth, understanding how and why consumers decide to accept and use a new technology has become essential to both academic researchers and practice. This article provides a detailed dataset based on a questionnaire that utilizes an extended technology acceptance model (TAM), incorporating the theory of consumer values and the innovation diffusion theory. Data collection was done with an online survey among French consumers, resulting in a sample size of 174. The dataset contains measures on various consumer attitudes and perceptions (e.g., consumption values) that influence intention and behaviors (adoption intention and technology use). This article supplements a published research article by Richter, Schubring, Hauff, Ringle and Sarstedt [1] which provides a detailed guide on how to combine partial least squares structural equation modeling (PLS-SEM) with necessary condition analysis (NCA) and a related illustration in a standard software published by Richter, Hauff, Ringle, Sarstedt, Kolev and Schubring [2].

An extended version of Necessary Condition Analysis (NCA) allows more specific conclusions: an example involving well-being and resilience

BACKGROUND

After conducting necessary condition analysis (NCA), researchers have concluded that a certain, not too low, level of well-being is necessary but not sufficient for a high level of resilience. However, as acknowledged by the developers of the test, NCA only evaluates if the association between two variables is characterized by some unspecified type of non-randomness and not conditions of necessity.

METHOD

Earlier reported data on the association between well-being and resilience among Filipino adults (N = 533) in COVID-19 quarantine were re-analyzed with an extended version of NCA.

RESULTS

Analyses indicated a significant necessity effect of resilience on overall well-being, which is not logically compatible with well-being being necessary but not sufficient for resilience. Analyses with an extended version of NCA suggested that the association between overall well-being and resilience was characterized by equal degrees of necessity and sufficiency.

CONCLUSIONS

The original version of NCA is only capable of evaluating if the association between two variables is characterized by some unspecified type of non-randomness. The extended version of NCA allows researchers to draw more specific conclusions.