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This study aims to build on the dynamic capability view by examining dynamic capabilities associated with public value in public procurement.

A qualitative case study approach is used in this study. The interview and secondary data consist of eight cases of value-creating procurement from four public organizations.

The findings connect dynamic capabilities and public value in terms of innovation generation and promotion, well-functioning supplier markets, public procurement process effectiveness, environmental and social sustainability and quality and availability of products or services.

Dynamic capabilities in public procurement are necessary to improve public procurement.

This study extends understanding of how sensing, seizing and transforming capabilities contribute to public value creation in both innovative and less innovative (i.e. ordinary) procurement scenarios.

The authors study how enabling perceptions (flexibility, reparability and internal and global transparency) of a budgetary control system are formed, and whether enabling perceptions empower lower-level managers and make them form less negative attitudes about red tape in the organization. This study research is warranted because of the lack of knowledge on how perceptual variation in flexibility, repairability and transparency of a control system within an organization, where managers experiencing the same control system design, can be explained.

Survey data with answers from 211 managers from a large local government organization in Sweden is analyzed with structural equation modeling.

The extent to which the budget system is perceived as having enabling qualities (being flexible, reparable and transparent) is explained by the safeness of the individual manager's psychological climate. This climate is characterized by trust and fairness perceptions in upper management. In turn, enabling perceptions positively affect a sense of psychological empowerment and reduces attitudes toward red tape in the organization.

The authors contribute by identifying an important factor explaining individual-level variability in enabling perceptions of control systems within organizations. Compared to previous research that has taken an interest in the organizational-level climate, the authors theorize about and investigate (parts of) the individual-level psychological climate as an explanation of within-system variability.

The purpose of this study is to develop a method to assess social performance. Traditionally, environment, social and governance (ESG) rating providers use subjectively weighted arithmetic averages to combine a set of social performance (SP) indicators into one single rating. To overcome this problem, this study investigates the preconditions for a new methodology for rating the SP component of the ESG by applying machine learning (ML) and artificial intelligence (AI) anchored to social controversies.

This study proposes the use of a data-driven rating methodology that derives the relative importance of SP features from their contribution to the prediction of social controversies. The authors use the proposed methodology to solve the weighting problem with overall ESG ratings and further investigate whether prediction is possible.

The authors find that ML models are able to predict controversies with high predictive performance and validity. The findings indicate that the weighting problem with the ESG ratings can be addressed with a data-driven approach. The decisive prerequisite, however, for the proposed rating methodology is that social controversies are predicted by a broad set of SP indicators. The results also suggest that predictively valid ratings can be developed with this ML-based AI method.

This study offers practical solutions to ESG rating problems that have implications for investors, ESG raters and socially responsible investments.

The proposed ML-based AI method can help to achieve better ESG ratings, which will in turn help to improve SP, which has implications for organizations and societies through sustainable development.

To the best of the authors’ knowledge, this research is one of the first studies that offers a unique method to address the ESG rating problem and improve sustainability by focusing on SP indicators.