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Institutional, economic, social and technological advancements enable openness to cope with wicked public management issues. Although open innovation (OI) is becoming a new normality for public sector entities, scholarly knowledge on this topic is not fully systematized. The article fills this gap, providing a thick and integrative account of OI to inspire public management decisions.

Following the SPAR-4-SLR protocol, a domain-based literature review has been accomplished. Consistently with the study purpose, a hybrid methodology has been designed. Bibliographic coupling permitted us to discover the research streams populating the scientific debate. The core arguments addressed within and across the streams were reported through an interpretive approach.

Starting from an intellectual core of 94 contributions, 5 research streams were spotted. OI in the public sector unfolds through an evolutionary path. Public sector entities conventionally acted as “senior partners” of privately-owned companies, providing funding (yellow cluster) and data (purple cluster) to nurture OI. An advanced perspective envisages OI as a public management model purposefully enacted by public sector entities to co-create value with relevant stakeholders (red cluster). Fitting architectures (green cluster) and mechanisms (blue cluster) should be arranged to release the potential of OI in the public sector.

The role of public sector entities in enacting OI should be revised embracing a value co-creation perspective. Tailored organizational interventions and management decisions are required to make OI a reliable and dependable public value generation model.

The article originally systematizes the scholarly knowledge about OI, presenting it as a new normality for public value generation.

Building trust and living interpersonal trust are crucial corporate executive virtues that are needed today. Once you have developed and solidified a high level of genuine interpersonal trust with all your stakeholders, especially customers, suppliers, and employees, then you are on the right path of managing and transforming your company. A high level of interpersonal trust between all stakeholders and corporates in a business situation will break down communication barriers, foster serious conversation and sharing of ideas, and will eliminate corporate transactional anxieties of fear, mistrust, guilt, rigidity, blame, and resentment. When stakeholders trust you and you trust them, then you speak freely, they speak freely, and your mutual sustained transparency is a gateway to survival, revival, and sustained corporate recovery and transformation, and steady growth and prosperity. Conversely, when there is low trust, high mistrust, and high distrust among stakeholders in a business situation, communications and conversations are stressed and fragmented, teamwork and team spirit are very low, and the company is heading toward its ruin and extermination. Such is the crucial role of interpersonal trust in business. This chapter explores the crucial phenomenon of corporate interpersonal trust. We review various cases, models, concepts, definitions, and theories of trust from the management literature in general, and from the marketing field in particular, to derive psychological, behavioral, ethical, and moral principles of corporate trust, trusting relations, and trusting strategies.

The purpose of this paper is to lay out the data competence maturity model (DCMM) and discuss how the application of the model can serve as a foundation for a measured and deliberate use of data in secondary education.

Although the model is new, its implications, and its application are derived from key findings and best practices from the software development, data analytics and secondary education performance literature. These principles can guide educators to better manage student and operational outcomes. This work builds and applies the DCMM model to secondary education.

The conceptual model reveals significant opportunities to improve data-driven decision making in schools and local education agencies (LEAs). Moving past the first and second stages of the data competency maturity model should allow educators to better incorporate data into the regular decision-making process.

Moving up the DCMM to better integrate data into their decision-making process has the potential to produce profound improvements for schools and LEAs. Data science is about making better decisions. Understanding the path laid out in the DCMM to helping an organization move to a more mature data-driven decision-making process will help improve both student and operational outcomes.

This paper brings a new concept, the DCMM, to the educational literature and discusses how these principles can be applied to improve decision making by integrating them into their decision-making process and trying to help the organization mature within this framework.