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This study aims to investigate how dynamic capabilities, i.e. sensing, learning, integrating and coordinating trigger sustainable innovation performance. It also examines the direct and moderating role of environmental turbulence towards the sustainable innovation performance of small and medium-sized enterprises (SMEs).

The data were collected through a cross-sectional survey of 169 SMEs in Oman and analysed through structural equation modelling using SmartPLS software.

Findings of this study reveal that the sustainable innovation performance of SMEs is greatly influenced by the synergy of learning, integrating and coordinating capabilities. Notably, among these capabilities, coordinating capability emerges as the most important capability for SMEs with a primary emphasis on fostering both human and organizational well-being. However, this research reveals that building dynamic capabilities alone might not be sufficient to address social, ecological and economic sustainability criteria, and SMEs may need to extend their view beyond internal processes and integrate various environmental contingencies into their approaches while focusing on sustainable innovation performance.

This research is useful for business managers while allocating resources in their business efficiently and effectively to achieve sustainable innovation performance. It also highlights that SMEs need to integrate various environmental contingencies into their approaches while focusing on sustainable innovation performance.

To the best of the authors’ knowledge, this study is one of the first to contribute to SME scholarship by mainly investigating the effect of specific four types of dynamic capabilities on sustainable innovation performance in a turbulent environment. This study is likely to contribute to the SMEs addressing sustainability innovation performance and develop capabilities to be sustainable in a turbulent environment.

Project selection management is a matter of challenge for project-oriented organizations, particularly, if the decision-makers are confronted with limited resources. One of the main concerns is selecting an optimal subset that can successfully satisfy the requirements of the organization providing enough resources to the best subset of the project. The projects for which there are not enough resources or those requiring whole resources of the organization will collapse soon after failed to success. Therefore, the issue is in the risk of choosing a set of projects so that can make a balance in investment versus on collective benefit.

A model is presented for project selection and has been tested on the 37 available projects. This model could increase the efficiency of the whole subset of the project significantly in comparison to the other model and it was because of choosing a diverse subset of projects.

Provides a general framework for project selection and a diverse and balanced subset of projects to increase the efficiency of the selected subset. Also, reduces the impact of uncertainty risk on the project selection process.

For the purposes of project selection, any project whose results are uncertain is a risky project because, if the project fails, it will reduce combined project value. For example, a pharmaceutical company’s R&D project is affected by the uncertain results of a specific compound. If the company invests in different compounds, a failure with one will be offset by a good result on another. Therefore, with selecting a diverse set of projects, this paper will have a different set of risks.

This paper discusses the risk of selecting or being responsible for selecting a project under uncertainty. Most of the projects in the field of project selection generally consider the risks facing the projects or existing models that do not take into account the risk.