A critical challenge increasingly becoming part of the day-to-day industry business is reconciling competitiveness and profitability with the sustainability of industrial value creation. With the increased frequency of natural disasters caused by climate change, customer awareness of sustainability is changing. Additionally, governments are increasingly taking regulatory action to limit harmful effects of climate change. Hence, the sustainability of a company is gradually becoming a competitive advantage. Sustainable scheduling represents a short-term potential for companies. Concurrently, due to globalization, sustainable scheduling in production networks is attracting significant research interest. The complexity of these optimization problems is high because of a large number of influencing factors, e.g., the geographical location of the customers, the number and the heterogeneity of the factories. As a result, causal relationships often overlap and cannot be separated. In this article, effects are ascertained separately with the help of single-factor experiments in an extensive computational experiment for a distributed permutation flow shop scheduling problem by using a lexicographic mixed-integer-linear-programming model and fast construction heuristics. Thereby, reasoning about the cause-effect relationships is enabled, promoting the integration of problem-specific knowledge for an efficient design of metaheuristics. Furthermore, valuable insights for management and research result from the derivation of implications.