Business Process Improvement for Sustainable Technologies Investments in Construction: A Configurational Approach

Abstract

Given the importance of investments in business process improvements for sustainable technologies, many industry sectors are forced to examine and balance new investments with long-term economic viability. There are disputes with regard to the value of investments, particularly within the construction sector, which is characterized by poor capitalization, over-leveraged firms, and high risks, often coupled with business cycles or boom and bust periods. Understanding when construction firms should engage in business process improvements with sustainable technologies is not clear due to the risks and investment costs. To address this problem, the study takes a configurational approach to examine the factors of leverage and use of capital to examine their impact on firm performance with qualitative comparative analysis (QCA). We show distinct configurational outcomes that are associated with superior success, giving construction firms viable pathways to evaluate potential investments in sustainable technologies. Specifically, one configuration, focusing on incremental innovations, consistently produces positive firm performance. Two configurations that lead to the absence of performance are associated with radical innovations in firms that struggle to manage their working capital.

The Transition of Cities towards Innovations in Mobility: Searching for a Global Perspective

“…Additionally, the intermediate solution was chosen for the presentation of the results. The intermediate solution is considered the preferred solution in QCA as it is the most successful in discovering robust sufficiency [ 76 , 77 ], and allows a more comprehensive and meaningful interpretation [ 73 ]. With the intermediate solution, all those remainders that are in line with the directional expectations are incorporated in the minimization process, those theoretical affirmations that guide the investigation by proposing the way in which the causal conditions could affect the presence of the outcome [ 75 , 78 ].…”

“…In this way, it is possible to identify both the causes that explain the outcome and the impact of each of them [ 71 ]. Complementing the assessment of the explanatory and predictive power of the model offered by statistical techniques, QCA generates deeper insights into the relationship between variables, offering a way to reach better management conclusions [ 72 , 73 ].…”