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This paper considers supply chain management organizations with the aid of 'chaotic systems theory' developed originally in physics and mathematics. Since innovations in supply chain management are vital for organizational survival 'complex systems theory' may assist in fine-tuning managerial philosophies that provide stability in supply chain management because it is on the boundary of chaos that the greatest innovational creativity occurs. Neither 'management by rigid objectives' (MBO) nor 'management by instruction' (MBI) will be suitable for the information society of the twenty-first century because chaotic social systems will no longer be effectively managed. However, the capacity for self-organization will be derived essentially from how supply chain management members accept a shared set of values or principles for action-'management by values' (MBV). Complex systems theory deals with systems that show complex structures in time or space, often hiding simple deterministic rules. This theory holds that once these rules are found, it is possible to make effective predictions and even to control the apparent complexity. The state of chaos that self-organizes is attributable to the appearance of the 'strange attractor' and provides the ideal basis for creativity and innovation in the twenty-first century. In the self-organized state of chaos, social members are not confined to narrow roles and gradually develop their capacity for differentiation and relationships, growing progressively towards their maximum potential contribution to the efficiency of the organization. In this meaning, values act as organizers of 'attractors' of disorder, which, in the theory of chaos, are systems represented by usually regular geometric configurations that predict the long-term behavior of complex systems. In supply chain management organizations (as in all kinds of social systems) the initial principles end up as the final principles in the long term. An attractor is a model representation of the behavioral results of the system. The attractor is not a force of attraction or a goal-oriented presence in the system; it simply depicts where the system is heading based on its rules of motion. In supply chain management organizations that cultivate or shares values of autonomy, responsibility, independence, innovation, creativity, and proactivity, the risk of short-term chaos is mitigated by external complexities that organizations are currently confronting. The strategy is to alter the supply chain management's surroundings so that they can benefit from management by values (MBV).

The purpose of this paper is to challenge how we have traditionally thought about organisations and introduce two frameworks to enable us to understand how change in organisations might be facilitated better.

The paper discusses organisations as complex adaptive systems and uses complexity theory to inform two new frameworks for facilitating organisational learning and change.

In order for organisational learning to occur we need to change our mind-set of how we see organisations and to think of learning not just as individual but also as generative “communicative action” that emerge out of collaborative relationships.

The frameworks proposed are grounded in organisational learning literature and the experience of the author. The proposed agenda for organisational learning has yet to be acted upon and evaluated.

The frameworks can be used to enhance understanding of learning and change in organisations. The agenda for enabling organisational transformation identifies key steps to put the ideas developed in the paper into practice.

The approach advocated for use within organisations is one of empowerment and collaboration rather than top down direction.

The paper introduces new frameworks and a practical agenda to bring about organisational transformation through work-applied learning.

The purpose of this study is to deepen understanding of the effects of using social media technologies to acquire technological knowledge and organizational learning competences, of technological knowledge competences on organizational learning and finally of organizational learning on organizational performance.

The study was performed by analyzing data from a sample of 197 technology firms located in Spain. The hypotheses were tested using a structural equations model with the program LISREL 8.80.

This study’s conceptual framework is grounded in complexity theory – along with dynamic capabilities theory, which complements the resource-based view. The study contributes to the literature by proposing a model that reflects empirically how business ecosystems that use social media technologies enable the development of interorganizational and social collaboration networks that encourage learning and development of technological knowledge competences.

It would be interesting for future studies to consider other elements to conceptualize and measure social media technologies, including (among others) significance of the various tools used and strategic integration. The model might also analyze other sectors and another combination of variables.

The results of this study have several managerial implications: developing social media technologies and interorganizational social collaboration networks not only enables the organizational learning process but also encourages technological knowledge competences. Through innovation processes, use of social media technologies also contributes to strengthening companies’ strategic positioning, which ultimately helps to improve firms’ organizational performance.

Since social media technologies drive information systems in contemporary society (because they enable interaction with numerous agents), the authors highlight the use of complexity theory to develop a conceptual framework.

The study also deepens understanding of the connections by which new experiential learning contributes to the generation of coevolutionary adaptive business ecosystems and digital strategies that enable development of interorganizational and social collaborative networks through technological knowledge competences. Only after examining the impact of social media technologies on organizational performance in prior literature, did the authors underscore that both quantity and frequency of social media technology use are positively related to improvement in knowledge processes that lead to employees’ creation and acquisition of new metaknowledge.

This article couples organizational theory with practice with the union of action learning and the ambidextrous organization. It aims to show how action learning contributes to the creation and sustainment of an ambidextrous (learning) organization.

A side-by-side comparison of action learning and the ambidextrous organization was used.

Action learning “teaches” and promotes the framework and processes of ambidexterity and the practical creation of learning organizations. An action learning team in action performs like an ambidextrous organization to the extent that “acting” is synonymous with exploitation and “learning” with exploration.

Action learning is a powerful tool for the ambidextrous organization, serving as a template for the practitioner to create a learning organization.

This paper extends the literature on organizational structure, leadership, culture and change as it relates to ambidexterity, learning organizations and action learning. It integrates learning theory through action learning with the practice of the ambidextrous organization. A synergistic theory/practice circle is created through the combination of the processes of “theory informing theory” from academia and “practice informing practice” from industry, creating a “theory informing practice and practice validating and updating better theory” circle.

This study aims to introduce an alternative model, “volatility, uncertainty, complexity and ambiguity (VUCA), Virtue and Vice” (3V’s), to unleash leadership skills, promote organisational collaborative change and impact sales performance during an unprecedented crisis.

The methodology outlines action research based on the 3V’s model and its application in an international business-to-business sales organisation during Covid-19. It explores alternative paths informed by play-at-work and Plato’s philosophy applied to work-based-learning. Each action/iteration adds to the model, which becomes more likely appropriate for various situations.

The 3V’s boosted change implementation and improved sales performance. The 3V’s conceptualised an invitation to immerse oneself in the constant “river of change” (VUCA) and a means of understanding the role of leadership in navigating this change by embracing simple rules: searching for justice (Virtue) and overcoming the barrier of public opinion (Vice).

The 3V’s model is grounded in leadership literature and a sole application, providing real international data relevant to organisations and leaders. This has yet to be evaluated further.

3V’s can enhance the understanding of a leading collaborative change and re-frame team dynamics in post-pandemic times for the broader public.

The approach advocated is a practice of “swimming alongside the team”, which should enable empowerment and collaboration rather than a top-down direction. Focussing on leaders who are moral people, this approach becomes a differentiator in a digital world.

This study examines Plato’s philosophy, play-at-work and other leadership theories in a model which prepares organisations to respond to crisis by providing the ability to reflect on human aspects and straightforward, transferable skills.

Managers’ work is surrounded by complex environments, from which they need to learn, in order to understand them. However, complexity poses several challenges to managerial learning, for which usually management educational programs have not prepared managers. Thus, the purpose of this paper is to explore such challenges and possible ways to overcome them.

This is a conceptual paper that explores in depth the issue of managerial learning challenges in a complex world. Managers face these challenges during their practice, yet sometimes management education has not prepared them for this.

Three managerial learning challenges due to complexity are identified. First, through cognition and cognitive structures, managers simplify the world around them. Nevertheless, biases, inertia and inaccuracy emerge, as managers’ mental models are not truly capable of capturing complexity. Second, managers look for information to aid them in their learning processes, but the information they gather is sometimes bogus, invalid or unfounded. Third, managers could seek for support from management research to improve their learning. However, given management research intricacies, limitations and particularities, a learning challenge emerges as well, as management research has been rarely capable to capture complexity.

Having explored these managerial learning challenges due to complexity, this paper discusses a carefulness-based management learning ideal, which by being underpinned by the quality of carefulness and the related concepts of critical thinking, negative capability and a deep learning style, suggests a potential new way to approach management learning in light of complexity.

The purpose of this research is to systematically review the properties of supply chains demonstrating that they are complex systems, and that the management of supply chains is best achieved by steering rather than controlling these systems toward desired outcomes.

The research study was designed as both exploratory and explanatory. Data were collected from secondary sources using a comprehensive literature review process. In parallel with data collection, data were analyzed and synthesized.

The main finding is the introduction of an inductive framework for steering supply chains from a complex systems perspective by explaining why supply chains have properties of complex systems and how to deal with their complexity while steering them toward desired outcomes. Complexity properties are summarized in four inter-dependent categories: Structural, Dynamic, Behavioral and Decision making, which together enable the assessment of supply chains as complex systems. Furthermore, five mechanisms emerged for dealing with the complexity of supply chains: classification, modeling, measurement, relational analysis and handling.

Recognizing that supply chains are complex systems allows for a better grasp of the effect of positive feedback on change and transformation, and also interactions leading to dynamic equilibria, nonlinearity and the role of inter-organizational learning, as well as emerging capabilities, and existing trade-offs and paradoxical tensions in decision-making. It recognizes changing dynamics and the co-evolution of supply chain phenomena in different scales and contexts.

This paper aims to investigate how organizational learning (OL) affects the development of anticipatory adaptation to climate change in companies. Because the need to learn increases in circumstances of greater uncertainty such as the case of climate change, one of the processes that can explain different levels of anticipatory adaptation to climate change (AACC) by companies is OL.

The research uses a case study design. Following the procedures of qualitative sampling, an exemplary case of organizational adaptation to climate change in a sector that is extremely affected by the impacts of weather events was chosen. Empirical data collection includes semi-structured interviews and the collection of private and public documents. Such data were analyzed through thematic analysis.

The process of OL for anticipatory adaptation to climate change presents substantial differences from the traditional OL process presented by the specialized literature. In particular, the concepts of single- and double-loop learning were challenging to fit into the learning processes required for AACC.

Organizations have historically been working towards the adaption to external unforeseen events, but anticipatory adaptation to climate change presents new challenges and requires new forms of learning. Previous research has examined the interplay between learning and climate change adaptation, especially at the inter-organizational level. By developing research at the organizational level, this paper addresses a gap in the literature and shows that the required learning to adapt to climate change differs from the traditional learning, described in the management literature.

Recent advancements in Artificial Intelligence (AI) and, at its core, Machine Learning (ML) offer opportunities for organizations to develop new or enhance existing capabilities. Despite the endless possibilities, organizations face operational challenges in harvesting the value of ML-based capabilities (MLbC), and current research has yet to explicate these challenges and theorize their remedies. To bridge the gap, this study explored the current practices to propose a systematic way of orchestrating MLbC development, which is an extension of ongoing digitalization of organizations.

Data were collected from Finland's Artificial Intelligence Accelerator (FAIA) and complemented by follow-up interviews with experts outside FAIA in Europe, China and the United States over four years. Data were analyzed through open coding, thematic analysis and cross-comparison to develop a comprehensive understanding of the MLbC development process.

The analysis identified the main components of MLbC development, its three phases (development, release and operation) and two major MLbC development challenges: Temporal Complexity and Context Sensitivity. The study then introduced Fostering Temporal Congruence and Cultivating Organizational Meta-learning as strategic practices addressing these challenges.

This study offers a better theoretical explanation for the MLbC development process beyond MLOps (Machine Learning Operations) and its hindrances. It also proposes a practical way to align ML-based applications with business needs while accounting for their structural limitations. Beyond the MLbC context, this study offers a strategic framework that can be adapted for different cases of digital transformation that include automation and augmentation of work.

The purpose of this paper is to apply the aspects of decision theory (DT) to performance measurement and management (PMM), thereby enabling the theoretical elaboration of volatility, uncertainty, complexity and ambiguity in the business environment, which are identified as barriers to effective PMM.

A review of decision theory and PMM literature establishes the Cynefin framework as the basis for extending the performance alignment matrix. Case research with seven companies explores the relationship between two concepts under-examined in the performance alignment matrix – internal dominant logic (DL) as the attribute of organisational culture affecting decision making, and the external environment – in line with the concept of alignment or fit in PMM. A focus area is PMM related to sustainable operations and sustainable supply chain management.

Alignment between DL, external environment and PMM is found, as are instances of misalignment. The Cynefin framework offers a deeper theoretical explanation about the nature of this alignment. Other findings consider the nature of organisational ownership on DL.

The cases are exploratory not exhaustive, and limited in number. Organisations showing contested logic were excluded.

Some organisations have cultures of predictability and control; others have cultures that recognise their external environment as fundamentally unpredictable, and hence there is a need for responsive, decentralised PMM. Some have sought to change their culture and PMM. Being attentive to how cultural logic affects decision making can help reduce the misalignment in PMM.

A novel contribution is made by applying decision theory to PMM, extending the theoretical depth of the subject.