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This paper explored the relationship between the embeddedness of a firm’s managerial values and corporate financial performance in Swiss small and medium-sized enterprises (SMEs) by developing a conceptual maturity model of managerial values (MM-MV). The MM-MV articulates the extent to which managerial values are embedded within organizations, allowing the analysis of the interrelationship between the degree of values-embeddedness and financial performance in SMEs. The findings suggested that as managerial values become more embedded, financial performance increases; therefore, SMEs exhibiting highly embedded managerial values such as customer-minded, team spirit, innovation-driven reliability, persistency, competency, and engagement tend to financially outperform SMEs that have not fully embedded managerial values throughout the firm.

This chapter presents a new conceptual framework of institutional research (IR). The framework refines previously studied dimensions of IR and integrates them into the higher order concept of knowledge management. Previously studied dimensions of IR include the institution’s organizational sectors (e.g., academic, human resources), the functions for which information is used (e.g., operations, strategic management), and the resources supporting IR (e.g., technology, funding). The framework innovates by specifying what competencies are required to carry out IR activities and how to assign a level of development to each competency. This operationalization permits the creation of an assessment tool enabling us to move from general and intuitive statements about development to specific and behavioral levels which are actionable. The framework formulation was validated with a group of IR experts in Chile. The framework can be used to assess one institution, to compare an institution to a peer group, or to compare groups of institutions at the regional, national, or international levels.

Although it is widely acknowledged that health care delivery systems are complex adaptive systems, there are gaps in understanding the application of systems engineering approaches to systems analysis and redesign in the health care domain. Commonly employed methods, such as statistical analysis of risk factors and outcomes, are simply not adequate to robustly characterize all system requirements and facilitate reliable design of complex care delivery systems. This is especially apparent in institutional-level systems, such as patient safety programs that must mitigate the risk of infections and other complications that can occur in virtually any setting providing direct and indirect patient care. The case example presented here illustrates the application of various system engineering methods to identify requirements and intervention candidates for a critical patient safety problem known as failure to rescue. Detailed descriptions of the analysis methods and their application are presented along with specific analysis artifacts related to the failure to rescue case study. Given the prevalence of complex systems in health care, this practical and effective approach provides an important example of how systems engineering methods can effectively address the shortcomings in current health care analysis and design, where complex systems are increasingly prevalent.

Today, businesses, organizations and governments attach great importance to digital transformation to meet the needs of their customers, business partners, and employees to adapt to the developing technology in recent years. Digital transformation, which is a challenging and mandatory process, has been and continues to be passed by institutions today. However, the successful management of this transformation without conflict can be realized by accurately detecting new communication technologies and examining, understanding, and implementing the transformation process in detail. This process will be painful, where radical changes will take place in the structure, processes, functions, and business models of the organization. Different challenges may be encountered in each of the startup, execution, and governance subprocesses examined in the digital transformation process. Many conflicts such as time and budget shortages, inadequate digital skills and lack of vision for digital customer processes, cybersecurity threats, human resource shortages, difficulty in managing technology, failure to achieve cloud structure integration, vision, and culture differences are the reasons why this process cannot be managed fluently and accurately. For businesses that focus on this goal, regardless of scale, digital transformation has become a necessity, not an alternative to choose. In this study, the digital transformation process and maturity model were discussed, and technological and digital conflicts were emphasized. It seeks to shed light on the work they will do by making recommendations for institutions to manage this process in the best way.

In order to support transformational business change, IT needs to streamline the process of bringing new IT processes to life.

In today’s ever-changing business world, nobody knows what is around the corner, so improving agility is the best way to the future-proof organization.

IT Service Management is the ability to collect data, analyze it, to make reports, and to implement improvements in agile mode, sometimes make it challenging to manage all these informational organization assets effectively. To perform real-time monitoring of these activities, manage, and be able to involve the final user in the heart of the IT process, or reduce operating cost, agility is the ideal solution.

In this chapter, the authors propose a global strategic model to improve Information Technology Service Management service management processes with the additions of two drivers: agility management and security management.

There is a research gap in the explanation of cyber incident response approaches in management to increase cyber maturity for small–medium-size enterprises (SMEs). Therefore, based on the literature analysis, the chapter aims to (1) provide cyber incident response characteristics, (2) show the importance for SMEs, (3) identify cyber incident response feasibility and causal factors, (4) provide scenarios for consideration to create an incident response plan (IRP), and (5) discuss the cyber incident response and managerial approaches in SMEs. The authors used content analysis of scientific and professional articles to develop the theoretical foundation of incident response approaches in management for SMEs. The authors start from the fundamentals to obtain knowledge and understanding of the latest threats and opportunities, and how to defend themselves using the limited capacity of resources might be the starting point to building an extensive incident response capability. Incident response capabilities and maturity levels vary widely between various organisations. There is no simple one-size-fits-all process for incident response; each case is unique and requires continuous refinement. Differentiation and adaptation to different types of SMEs are pivotal to developing cyber maturity and defining requirements that fit the market’s needs and are therefore more efficient in achieving the goal of increasing cyber security (CS) among business management. SMEs may not have a mature IRP, but at least one readiness indicator could lead to the preparation of a mature IRP. Implementation of the secure undertakings and information processes requires using modern information and communication technologies, incident response processes, and other modules that could enhance support for decision-making processes in management. The approach requires a systematic approach to issues related to constructing these solutions. The authors highlight that building efficient incident response approaches in management to improve cyber maturity will begin with infrastructure and people factors.

Significant advances in digital technologies impact both organisations and knowledge workers alike. Organisations are now able to effectively analyse significant amounts of data, while accomplishing actionable insight and data-driven decision-making through knowledge workers that understand and manage greater complexity. For decision-makers to be in a position where sufficient information and data-driven insights enable them to make informed decisions, they need to better understand fundamental constructs that lead to the understanding of deep knowledge and wisdom. In an attempt to guide organisations in such a process of understanding, this research study focuses on the design of an organisational transformation framework for data-driven decision-making (OTxDD) based on the collaboration of human and machine for knowledge work. The OTxDD framework was designed through a design science research approach and consists of 4 major enablers (data analytics, data management, data platform, data-driven organisation ethos) and 12 sub-enablers. The OTxDD framework was evaluated in a real-world scenario, where after, based on the evaluation feedback, the OTxDD framework was improved and an organisational measurement tool developed. By considering such an OTxDD framework and measurement tool, organisations will be able to create a clear transformation path to data-driven decision-making, while applying the insight from both knowledge workers and intelligent machines.