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The purpose of this paper is to develop a bi-objective optimization framework to select prefabricated construction service composition. An improved algorithm-genetic simulated annealing algorithm (GSA) is employed to demonstrate the application of the framework.

The weighted aggregate multi-dimensional collaborative relationship is used to quantitatively evaluate the synergistic effect. The quality of service is measured using the same method. The research proposed a service combination selection framework of prefabricated construction that comprehensively considers the quality of service and synergistic effect. The framework is demonstrated by using a GSA that can accept poor solutions with a certain probability. Furthermore, GSA is compared with the genetic algorithm (GA), simulated annealing algorithm (SA) and particle swarm optimization algorithm (PSO) to validate the performance.

The results indicated that GSA has the largest optimal fitness value and synergistic effect compared with other algorithms, and the convergence time and convergence iteration of the improved algorithm are generally at a low level.

The contribution of this study is that the proposed framework enables project managers to clarify the interactions of the prefabricated construction process and provides guidance for project collaborative management. In addition, GSA helps to improve the probability of successful collaboration between potential partners, therefore enhancing client satisfaction.

The purpose of this paper is to develop a model considering synergy effect for prefabricated construction service combination selection.

This research defines prefabricated construction service as a service-led construction method that meets the specific requirements of clients. Based on network theory, the multi-dimensional collaborative relationships of the prefabricated construction inter-services are formulated. The synergy effect is quantitatively calculated through the linear weighting of the strengths of collaborative relationships. Further, a weighted synergy network (WSN) is developed, from which a service composition selection model considering the synergy effect is established. Then, a genetic algorithm is employed to implement the model.

The results showed that (1) when the number of prefabricated construction services is increased, the synergy effect of combination options is enhanced; (2) The finer-grained prefabricated construction services, the stronger the synergy effect of service combination; (3) Clients have heterogeneous preferences for collaborative relationships, and there are differences in the synergy effect of service combination.

The contribution of this research includes proposed a method to quantify the synergy effect from the perspective of collaborative relationships, explored the specific procedure for the prefabricated construction service combination selection under the service-led construction, and provided a reference for promoting the development in construction. Besides, the model proposed could be applied to prefabricated construction service composition selection with diverse research boundaries or client preferences by executing the same procedure.

This study aims to investigate how a firm’s sustainable competitive advantage is influenced by the combination of entrepreneurial ecological orientation, digital transformation and dynamic capabilities.

Based on the qualitative comparative analysis method, this study systematically explores the significant key conditions and configuration effects that affect the growth of sustainable competitive advantage. This study uncovers the causal relationship and complex mechanisms underlying the sustainable and unsustainable competitive advantages for new ventures, by examining the grouping effects of the above three factors – entrepreneurial ecological orientation, digital transformation and dynamic capabilities on those advantages.

A single factor fails to constitute a necessary condition for sustainable competitive advantage. Three types of configurations are beneficial to sustainable competitive advantage, namely, flexible and responsive type, dynamically adjusted type and type of opportunity resource integration, whereas four types of configurations lead to the unsustainable competitive advantage of new ventures, namely, type of organizational rigidity, informal entrepreneurial type, information-blocking type and technology-deficient type.

According to this study, adopting an entrepreneurial ecological orientation is a novel strategic move. This study offers an extensive review of three aspects of entrepreneurial ecological orientation, dynamic capacities and digital transformation and their mutually synergistic cascading effects on the sustainable competitive advantage of new ventures. This study investigates how three dimensions interact to achieve sustainable competitive advantage for firms, ultimately contributing to the study of sustainable competitive advantage strategies from an entrepreneurial ecosystem perspective.