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This chapter introduces the concept of an intelligent organization in the context of the twenty-first-century knowledge economy. An intelligent organization is one in which individuals behave intelligently, work is grounded in intelligent methods and choices, and rich stocks of intelligence in the form of knowledge capital to support intelligence work and choices. Intelligence is defined as both a thing and attribute and behavior and way of working. The chapter also highlights examples of intelligent behaviors and or organizational pathologies. The chapter also highlights the importance of becoming aware of intelligent and unintelligent choices.

This paper aims to improve understanding of the process through which knowledge acquisition, technical tools and organisation actors can contribute to an organisation development in developing knowledge as a systemic competitive weapon. It examines the relationships between the technology and human value, because they are vital instruments of the knowledge management (KM) process. By considering that KM is related to intelligent agents, information technology (IT), and strategic decision‐support systems (SDSS), it attempts to provide useful insights on KM efficiency. A conceptual model of KM efficiency in the organisations supported by the combination of intelligent agents’ role and intelligent systems resources is presented. The model is divided in two areas: the area of technical tools for specification of intelligent systems resources and the area of intelligent agents destined to focus their roles on organisations’ performance. The major factors are discussed and directions for future research are suggested.

Organizations are fast adopting new technologies such as automation, analytics and artificial intelligence, collectively called intelligent automation, to drive digital transformation. When adopting intelligent automation, there is a need to understand the success factors of these new technologies and adapt agile software development (ASD) practices to meet customer expectations. The purpose of this paper is to explore the success factors of intelligent automation and create a framework for managers and practitioners to meet dynamic business demands. Total interpretive structural modeling (TISM) framework is a suitable approach to integrate quantitative measurement with qualitative semi-structured interviews capturing the context of the individual organization environment.

This paper identified agility factors and their interrelationships using a TISM framework. TISM results were validated using a one-tailed t-test to confirm the interrelationships between factors. Furthermore, the agility index of a case project organization was assessed using a graph-theoretic approach (GTA) to identify both the triggering factors for agility success and improvement proposals.

Results showed that leadership vision, organization structure and program methodology were driving factors. The TISM model was validated statistically and the agility index of the intelligent automation case project organization was calculated to be79.5%. Here, a GTA was applied and the triggering factors for improvement of the agility index were identified.

The limitations of the study are described along with the opportunities for future research as the field evolves through the rapid innovation of technology and products.

The increasing role of digital transformation in enterprise strategy and operations requires practitioners to understand how ASD practices must be planned, measured and/or improved over time through the implementation of automation, analytics and artificial intelligence programs. The TISM digraph provides a framework of hierarchical structure to organize the influencing factors, which assists in achieving organizational goals. This study highlights the driving factors which contribute to the success of intelligent automation projects and project organizations.

This is a first attempt to analyze the interrelationships among agility factors in intelligent automation projects (IAP) using TISM and the assessment of the agility index of a case IAP organization using a GTA.

The purpose of this paper is to compare the contribution of organizational intelligence quotient (OIQ) and organizational emotional quotient (OEQ) for intelligent organizations.

This paper develops a framework of OIQ and OEQ, based on the structure of intellectual capital (intellectual capital). Then, a specific questionnaire is designed and sent to ten national research institutes in China. Data from nine of them are analyzed as case study samples.

Data show that intelligent organizations are related with high OIQ as well as high OEQ. In the case of average-intelligent organizations, even if around high-IQ employees, “collective stupidity” caused by the failure of synergy of structural capital is the major gap to be a smart organization, just like a football team grouped by brilliant players always loses due to the dearth of coordination. OEQ, or the synergy between structural capital and human capital, is the critical point to avoid collective stupidity for organizations with intelligent employees.

Research results are based on case study in a particular country. Measurement tools for OIQ and OEQ are in bound of the IC concept.

The paper helps organizations to find out the critical problems causing collective stupidity in a changing environment.

Analogic to human beings’ intelligence, this paper develops a frame of OIQ and OEQ, and compares their contribution to intelligent organization building in a changing environment.

What is organizational emotional intelligence? Does it matter? And how can organizations increase their level of organizational emotional intelligence? In an attempt to find answers to these questions, this chapter provides a conceptualization of organizational emotional intelligence, discusses what we know about its associations with organizational outcomes, and proposes several practically relevant ways to improve organizational emotional intelligence. Specifically, organizational emotional intelligence is conceptualized as a combination of the aggregate level of individual emotional intelligence of employees and the utilization of emotionally intelligent procedures, norms, and behaviors throughout an organization. Preliminary evidence suggests that organizational emotional intelligence is positively associated with organizational performance and employees’ health. Organizations might be able to increase their organizational emotional intelligence by accumulating individual emotional intelligence among their employees and by applying emotionally intelligent procedures, some of which are discussed in this chapter.

In this chapter, we extend existing models of individual and collective emotional intelligence to the organizational level and provide an empirical study on the performance impact of organizational emotional intelligence. We propose that organizational emotional intelligence is composed of the average level of individual emotional intelligence of organization members and the collectively shared emotionally intelligent norms, values, and behaviors that shape their interaction. Across 156 organizations, we demonstrate sufficient within-organization consistency and between-organization difference to consider emotional intelligence a collective organizational characteristic. In addition, we show that the level of organizational emotional intelligence is positively associated with operational performance, financial performance, and innovation performance, and negatively associated with involuntary absence. Thus, organizational emotional intelligence can be considered a valuable asset for organizations.

Core competences, emanating from an organisation and that provide distinctive benefits to customers, are commonly viewed as the basis of competitive advantage. While these exist in many forms, the role of individual and organisational knowledge is increasingly important in the formation of knowledge‐based core competences. This paper explores the ideas of knowledge management, making reference to a number of sectors and companies, and specifically the airline industry, arguing that the culture, structure and infrastructure of an organisation are integral elements that facilitate and nurture learning. As a consequence, competences are built and developed within the “intelligent” organisation, which in turn, contribute to its competitive success.

This chapter explains how organizations can build intelligence capabilities into their everyday working environments. The definition of capacity building builds upon the organizational management and the strategic workforce development literatures. This chapter also derives essential guidance from another series focused on critical capabilities and capacity building. The authors highlight the role of a strong intelligence culture and learning in building intelligence capacity. Capacity building is achieved through short- and long-term efforts. This chapter also highlights the importance of balancing capacity building across everyday business operations and specialized intelligence functions.

This study aims to systematically map the state of work on human–machine collaboration in organizations using bibliometric analysis.

The authors used a systematic literature review to survey 111 articles on human–machine collaboration published in leading journals to categorize the theories used and to construct a framework of human–machine collaboration in organizations. A bibliometric analysis is applied to statistically evaluate the published materials and measure the influence of the publications using co-citation, coupling and keyword analyses.

The results inform that the research on human–machine collaboration in the organizational field is targeted at four aspects: performance, innovation, human resource management and information technology (IT).

This work is the first exploratory piece to assess the extent and depth of research on human–machine collaboration.

Drawing on a number of strategic management theories, the purpose of this paper is to explore the relationship between strategic thinking (in other words, systems perspective, focused intent, intelligent opportunism, thinking in time and hypothesis-driven analysis) and organizational performance. It also investigates whether the notion and content of high performance work practices, as identified in developed countries, can be used to amplify the effects of strategic thinking within the banking industry in a developing country.

Utilizing cross-sectional data obtained from commercial banks in Jordan, this paper applied structural equation modeling (SEM) to examine the banking sector in a developing country. Data were collected through self-administered questionnaires.

According to the results, focused intent, intelligent opportunism, thinking in time and hypothesis-driven analysis have positive impacts on organizational performance, except when considered from the systems perspective. Consequently, high performance work practices were found to only moderate the relationship between focused intent, intelligent opportunism, thinking in time and organizational performance.

The authors examined the impact of strategic thinking on the organizational performance through the moderation role of high performance work practices. The results of this paper extend the existing literature by providing evidence from Jordan, a developing country outside of the western world.