Exploring the emergent quality management paradigm

Abstract

The development of successful production systems is affected by conflicting forces, that is, initiatives seemingly conducive for one line of work can be a constraint for another. Consequently, this paper presents an alternative perspective on how these issues could be managed in organisations. There are a number of key challenges in terms of the involved dichotomies for future innovative quality improvements in operations. These dichotomies are part of four interrelated processes that are the central elements of a production system. As such, aiming for stability or change is a production process dilemma in terms of the production and distribution of offerings and solutions. Control and creativity are the main dilemmas of the innovation process, that is, the creation and implementation of new offerings and solutions, while exploitation and exploration are the dilemmas of the knowledge creation process and efficiency and effectiveness of the value creation process. As the simultaneous existence of both parts of the dichotomy seems to be a paradox, this paper suggests the emergent quality management paradigm as an alternative perspective providing the guidance, examples, and practical solutions necessary to solve these dilemmas by recognising the dichotomies as mutually dependent.

Keywords:

• ambidexterity
• emergence
• quality management
• innovation
• production system
• operations management

Introduction

Quality management (QM) has reached a high maturity in both research and practice (Dean & Bowen, 1994; Evans, Foster, & Linderman, 2014; Radziwill, 2013). However, there are still numerous challenges to successfully integrating QM into operations (Eriksson et al., 2016; Fundin, 2018; Fundin, Bergquist, Eriksson, & Gremyr, 2018). Based on practical challenges, Fundin et al. (2018) present six propositions that could close the so-called relevance gap between research and practice. Among them is the perceived need to explore the role of QM in terms of organisational ambidexterity and adaptability, and Fundin et al. (2018) call, in line with Evans et al. (2014) and Radziwill (2013), for more research exploring how the improvement of organisational learning and innovation could be better integrated with QM.

In practice, QM has been used in terms of control and reduction of variation only, although this was not the intention of the early proponents of QM integration (Backström, Fundin, & Johansson, 2017; Fundin, Bergman, & Elg, 2017). Fundin et al. (2017) name this the QM dilemma, building on Abernathy’s (1978) productivity dilemma. While Abernathy and Wayne (1974) explain this phenomenon as something that limits the learning curve, the QM dilemma is about the challenge to both ‘do things right’ (efficiency) and to ‘do right things’ (effectiveness). It is therefore critical to revisit the QM concept to explore new ways of integrating it into contemporary operations, to achieve both efficiency and effectiveness.

However, this type of dilemma is not unique to QM, as the dilemma between the needs to exploit existing knowledge and explore new knowledge is central to the long-term sustainability of an organisation and has been the subject of significant research and development (Benner & Tushman, 2003, 2015). As such, in this conceptual paper, the proposal of an emergent QM (EQM) in operations is framed under four interrelated processes as key processes of a production system (Backström et al., 2017). Each process, as described by Backström et al. (2017), involves activities and dichotomies that contribute to a unique type of phenomenon in a system. The production process is an explicit process that focuses on activities that contribute to the production and distribution of offerings; examples of dichotomies in this process are stability and changes of practices for producing goods. The innovation process focuses on activities that develop new offerings and solutions; examples of dichotomies are the creativity used to develop unexpected solutions and control, which is necessary to realise solutions into a new product. The embedded knowledge creation process focuses on the amount of knowledge based on different types of learning and knowledge creation embedded in both the production and innovation processes; examples of dichotomies are exploitation of existing knowledge on how to perform and exploration of new knowledge on how to perform. Finally, also embedded in the production and innovation processes is the value creation process, which focuses on the amount of value created for customers. With dichotomies such as efficiency or ‘do things right’ for customers and effectiveness or ‘do right things’ for customers, value is dependent on customer and extent but also on the ways it is created.

Theories on emergence could actually manage the dilemmas of each key process and facilitate the QM transition to a new, emergent paradigm that integrates QM in practice. Based on the studies of Bahskar (1989) and Archer (1995) on how to understand social change in organisations, emergence is defined as the process where the interactions between actors such as co-workers in an organisation, lead to development structures that organise these interactions – self-organisation. A basic theoretical starting point for the EQM paradigm is that all activities in an organisation are organised by different structures and these structures are developed (consciously and unconsciously) through interactions between co-workers. Central to this theory is a group of co-workers that share tasks and interact recurrently. Further, EQM includes a process perspective on reality, where phenomena are constructed and reconstructed over time. This time dependent process, where interactions are at a lower system level, for example between individuals, leads to structures aggregating and forming higher system levels, for example, groups of co-workers and departments, and is central to EQM.

Through understanding these dichotomies, the dynamics of a production system can be described in terms of the interplay between change, creativity, exploration, and effectiveness on one hand, and constancy, control, exploitation, and efficiency on the other. EQM suggests the lower levels in an organisation are sources of change, while organising structures at aggregated levels lead to constancy. This paper proposes and describes five types of dynamics: stagnation, stability, adaptation, transformation, and disintegration. The first and last are dysfunctional, while the other three are needed for the long-term sustainability of a production system.

Consequently, by analysing how QM can develop depending on these types of dynamics in a production system with four critical interlinked processes with dichotomies, this conceptual paper explores new knowledge on how the theories of emergence could contribute to QM by offering guidance, examples, and practical solutions on how the EQM paradigm could be used in practice.

Theory and conceptual framework

The theoretical framework is designed by integrating the QM theory with the theory of emergence and social dynamics. These theories are applied to a production system with the four previously described interrelated key processes. This section then proposes a synthesis as a conceptual means of further exploring the EQM paradigm.

Quality management theories in practice

QM has reached a high maturity level based on its proposals of how to enable change, creativity, exploration, and effectiveness on one hand, and constancy, control, exploitation, and efficiency on the other. However, few previous studies focus on how to achieve the best of both these dichotomies that seem impossible to manage and are even more difficult to achieve in practice (Fundin et al., 2017). Since the 1990s, the most common QM programmes with different types of utilisation depending on needs and experience are TQM (Deming, 1986, 1994; Juran & Godfrey, 1999), Six Sigma (Aboelmaged, 2010), Lean Production (Marodin & Saurin, 2013), and operational excellence programmes/models (e.g. Malcolm Baldridge National Quality Award (MBNQA), European Foundation for Quality Management (EFQM) model, Swedish Institute for Quality Management (SIQ) management model), and ISO 9000 series standard programmes. Their common denominator is managing dichotomies. Theoretically, they all enable change, creativity, exploration, and effectiveness, but also stability, control, exploitation, and efficiency. For example, in theory, Six Sigma places equal effort in defining problems as well as opportunities. TQM programmes, similar to Lean Production, focus on creating new value exceeding customers’ expectations, but also producing stable value with low variation in processes. Operational excellence programmes, such as EFQM, MBNQA, and SIQ, focus on value principles to enable stable processes, but also to seek new solutions and opportunities for customers and users. Finally, the ISO 9000 series, which has reached significant exposure in the industry over the past three decades with its focus on the compliance towards a standard way of working, also defines the requirements for the processes that essentially create new value for customers. To determine why and how these different programmes interact and progress within a production system is important for decision-makers managing operations under conflicting demands. Here, the time perspective is clearly a building block that makes a difference in EQM. For an overview of examples of activities that make a difference in the various QM programmes in the short or long term, see Table 1.

Table 1. Time perspective as EQM building block.

Quality Management Program	Examples of activities that drive stability, control, exploitation, and efficiency (short-term perspective)	Examples of activities that drive change, creativity, exploration, and effectiveness (long-term perspective/future oriented)
Six Sigma	In a DMAIC-project, define the problem that causes variation in current processes	In a DMAIC-project, define the opportunity for customers and development of new processes
Lean Production (LP)	Develop value streams with low variation and takt-time to deliver what is promised (Kaizen)	Initiate transformations towards new value-added solutions for customers (Kaikaku)
Total Quality Management (TQM)	Use of principle values that enable decisions based on facts	Use of principles that enable decisions based on knowledge
Operational Excellence Models (e.g. MBNQA, EFQM, and SIQ)	Leadership that fosters management of current business model (leadership towards constancy)	Leadership that fosters the management of a future potential business model (leadership towards a vision)
ISO 9000 series	Systematic development of company-specific manuals on how to manage current processes	Systematic development of new company-specific manuals for new processes

By knowing when to reinforce, modify, adapt, or even transform QM to a new state of operations, the EQM paradigm could provide enhanced support in practice. However, QM theories are insufficient in terms of explaining how or why to reinforce, modify, adapt, or transform a programme in terms of social dynamics, which is a critical element of a production system. Therefore, the subsequent theoretical subsection sheds light on how the theory of emergence could increase the abilities of managing change in operations.

Theory of emergence by means of the social dynamics of productions systems

The theory of emergence can be considered from different perspectives. Here, the emergent social dynamics perspective is selected as an analytical mean to further explore the EQM paradigm. The proposed theories are inspired by Langley, Smallman, Tsoukas, and van de Ven (2013) with an emergence perspective on process changes over time. We also draw from the research of Langley (1999), who uses alternative strategies for theorising from process data within the perspective of emergence, and Cronin, Weingart, and Todorova (2011) and McGrath, Arrow, and Berdahl (2000) in terms of understanding social dynamics in groups. The basic building block of the theory behind EQM is illustrated in Figure 1. This is both the simplest possible description of a dynamic process and the only required building block to describe dynamics. The building block is an analytical form of describing dynamics and has different contents depending on the studied system. Here, we use it in practice, at the group level of an organisation. It consists of:

1. Three types of structures at a certain time point, T1:

   1. External structures (ES, e.g. formal allocation of responsibilities, task formulations, standards, and the technical system) are similar to a barrier, defining the context within which the group works.

   2. Internal structures (IS, e.g. relations, common ways to understand things, and institutionalised habits) are the structures that emerge from the interaction between group members.

   3. Cognitive structures (CS, e.g. knowledge, understanding, and experiences) are the individual structures the individuals in the group use to decide how to act.

2. An interaction between individuals, with their own CS, organised by IS and ES at the next time point, T2. They interact while performing their tasks and there will be variances in the interaction, due to the working material, equipment, task, and those interacting.

3. There are three types of structures at the following time point, T3. ES are, by definition, not changed by this interaction, but CS and IS are. Instead, they are either reinforced or modified. A modified CS is equal to individual learning (individuals learn new, improved ways of performing tasks), while a modified IS can be called group learning (a group learns new, improved way of performing tasks). A reinforced CS is equal to enhanced stability (individuals improve the consistency of performing tasks), while a reinforced IS is equal to enhanced group stability (groups improve the consistency of performing tasks).

4. The structures of T3 are the starting point for the following building block, and the next interaction between individuals is at T4.

Figure 1. Basic building blocks in production system dynamics.

The five types of dynamics of production systems can be described using the following building block: stagnation, stability, adaptation, transformation, and disintegration (see Table 2). However, the dynamic is often different, depending on the level of the system. As such, the description below focuses on the group level. For stagnation, structures are constantly reinforced and no modifications exist. If the production system was perfectly fit for its current task, variations and changes over time decrease its fitness.

Table 2. EQM paradigm proposals.

Emergent social dynamics		Interrelated processes in a production system with impact on QM in operations				Implications for QM
Type of social dynamic over time at the system level of study	Structural implications	Production process (explicit)	Innovation process (explicit)	Knowledge creation process (embedded)	Value creation process (embedded)
1. Stagnation (stability within ES, IS, CS)	ES, RIS, RCS	Constancy	Control	Exploitation	Efficiency	Stagnation of QM due to reinforced structures (internal and cognitive)
2. Stability (within ES, but also adaptation of IS and CS)	ES, MIS, RIS, MCS, RCS	Constancy and Change	Control and Creativity	Exploitation and Exploration	Efficiency and Effectiveness	Stability of QM through modified or reinforced structures (internal and cognitive)
3. Adaptation (stability within AES, but adaptation of ES, IS and CS)	MES, RES, MIS, RIS, MCS, RCS	Constancy and Change	Control and Creativity	Exploitation and Exploration	Efficiency and Effectiveness	Adaptation of QM through modified or reinforced structures (external, internal, and cognitive)
4. Transformation (stability while building the shadow system, and adaptation of the complete system)	AES, TAIS, TIS, TCS	Change	Creativity	Exploration	Effectiveness	Transformation to new QM structures (aggregated internal, internal, and cognitive)
5. Disintegration (stagnation within some parts of the organisation and transformation in other parts of the organisation)	TES, RIS, RCS or RES, TIS, TCS	Constancy or Change	Control or Creativity	Exploitation or Exploration	Efficiency or Effectiveness	Disintegration of QM due to stagnation within some parts of the organisation and transformation in other parts

Stability is when the system continues being fit, even when there are task variations. To achieve stability, IS and human CS develop over time. In other words, to achieve stability, conform to standards, and maintain tolerance levels, the group has to adjust its work within ES, as described by the building block. Stability at the group level thus includes adaptation at actors’ levels (individual co-workers’ level) but also a risk of stagnation or disintegration at a higher aggregated organisation level.

Adaptation occurs when the ES of the studied group changes to increase the fitness of the group’s performance. To understand adaptation, we use several building blocks. Since there are several parallel groups and building blocks, ES are built of several sub-structures, all IS of some group. This implies that ES for one group are IS for another, that is, the group is an owner of that structure. Adaptation occurs when another group, the owner of this part of the ES, changes the studied group’s ES. This may be at the owner’s initiative, for example when the owner has the responsibility to monitor and improve another groups’ performance, or as an initiative from the group during a negotiation with the owning group. In other words, to achieve adaption and develop higher level standards, ES have to be modified by another group.

Transformation is a change in the ES of such significance that all structures have to change. For adaptation, most ES remain unchanged and the identities of the group and organisation are maintained but after a transformation, the organisation is transformed. An aggregation of groups may thus involve a substantial part of the member groups’ ES, which become internal for the aggregation of groups and can be termed aggregated IS. This is the basic building block for the next system level, where the bottom structure is represented by groups instead of individuals and the top one by aggregated ES owned by groups not included in the aggregation, for instance, groups in another part of the organisation or at the national level. The interaction between groups can resemble a political process, with the representatives of different groups seeking alliances and support from other groups to hinder or reach transformation. This process may, at the time of transformation, lead to the aggregated IS to be ultimately transformed (TAIS), which then results in a new situation for the interaction within each group and thus implies the transformational development of the IS of each group. On one hand, this transformation is rapid because all structures have to be changed simultaneously to fit. At this moment, there is only change and no stability. On the other hand, this transformation has to be prepared before implementation. Alternatively, shadow aggregated IS could develop in interactions before the transformation occurs for aggregated IS. Transformation at the group level is similar to adaptation at the aggregated level.

Disintegration occurs when significant changes in ES are not recognised by the group and its members and when IS are not modified, although there is an ES transformation. This may reduce the opportunities for coordination between groups and lead to the differentiation between individuals’ understanding of the organisation’s tasks and goals. Over time, the organisation may stop functioning as a whole. Reasons for disintegration may be too many changes in ES over a too short period or changes not anchored in the individuals of the organisation.

As indicated in Table 2, the theory of emergence by means of social dynamics has implications for QM. This is further elaborated in the next subsection on the synthesis of QM and the theory of emergence as analytical conceptual means to further explore the EQM paradigm.

Emergent quality management

In reviewing emergent social dynamics perspectives, the transformative phase leads to a critical question: how are contemporary QM programmes able to adapt or transform to new situations? In terms of modification, QM programmes seem to be able to reach stability by modifying IS, for example, use facts from deviations to decrease variation in current production processes (MIS, modification of IS). QM programmes are also able to use principles, methods, and tools to hinder behavioural variances to inadequately control and change structures (RIS, reinforcement of IS). In other words, QM are well fitted to adjust within ES.

Even if more efforts are expended on QM programmes, QM can also adapt by modifying ES to better fit the work tasks of a group, e.g. adapt to new ways of producing current parts of products (reinforcement) in a production system (RES, reinforcement of ES) or changing and adapting to producing new variants of current products (MES, modification of ES). Both ways implicate an enhanced capability of managing a product system.

For transformations, however, QM seems to be, in practice, embedded in current structures, depending on ownership of the QM way of working (external and internal). These are also situations when new theories could challenge the current QM paradigm. In evaluating how QM are supportive in managing dichotomies considering the four interrelated key processes of a production system, the theories on emergent social dynamics could offer new perspectives, with structural implications. The theories are altogether critical of a proposal for a new paradigm – EQM.

The EQM paradigm implicates that not only the capabilities for stability and adaptation are important in dynamics, but also those to transform and avoid stagnation and disintegration (if stagnation not is a conscious decision while exiting the marketplace). Transformation in the EQM paradigm thus means to radically change, explore, and enable creativity to achieve new effective value for customers. As such, three types of social dynamics – stability, adaptation, and transformation – are equally important. First, all seem to compete with limited resources, but with an understanding of the social dynamics in organisations, one could better utilise the conflicting demands (dichotomies) to enable development without limitations. Resources are not in conflict, depending on the considered level (actors, IS, ES). The emergent social dynamics enable both stability through its structures and change through actors (co-workers in the workplace). Both short- and long-term perspectives and both current and future customers are made possible through the different types of dynamics.

Keywords related to stagnation are, for example, constant production, invariability, immobility, and serenity, where deviations from non-conformance are corrected but not used to change operations. Keywords related to stability are, for example, standard, fast reactions, facts, and negative feedback processes, where deviations are devastating. Keywords related to adaptation are facts, action within frames, management/control from others, and negative and positive feedback processes, where deviations are driving forces. Keywords related to transformation are radical new ways of working (butterfly metaphor), political process, together creating a better future, developed together with the partners/market/customers, beyond oneself, and knowledge, where positive and negative feedback processes are driving forces. Finally, keywords related to disintegration are, for example, discrepancy, incongruity, and incompatibility, where deviations, for example from non-conformance, are potential sources of disintegration in organisations.

While there are few examples of how EQM is used in practice, the examples in the next subsection show guidelines for different situations.

Examples of integrating EQM in operations

These examples provide a perspective on how deviations can be acted upon or, in other words, how one could make different decisions based on failures that initiate variation. The first example is about disruptions in production, the second about dissatisfaction feedback from customers, and the third about external dynamic conditions on the marketplace. All examples are common phenomena in operations, which could influence decision-makers in several ways. As such, the EQM paradigm could offer several options, depending on the situation.

Disruptions in a production line

One critical but common example is how to manage disruption in a production line through the production system. By using an emergent way of managing quality, social dynamics propose five options:

1. Resources work on few deviations to maintain constancy; the product/company will exit the marketplace (stagnation).

2. Most commonly, one can solve the disruption and continue according to the previous production system design (stability).

3. One can test a new way of working to modify or reinforce the production system design with new processes (adaptation).

4. Ultimately, these production disruptions cost too much, underlining the need to explore a radical new way of working in the production system together with customers (transformation).

5. There is no shared view on the deviations that cause disruption in the production line, which leads to stagnation within parts of the organisation and transformation in others (disintegration).

Options (2)–(4) are equally important for how QM can be used to efficiently manage disruption in a production line. However, the critical point in the EQM paradigm is that the three options cannot be achieved in isolation.

Dissatisfaction from customers

Customer focused operations continuously measure trends in customer satisfaction, aiming to increase their numbers over time. However, equally important are the facts and knowledge grounded in customer dissatisfaction. One can look upon customer dissatisfaction in several ways, and the EQM way of making decisions proposes five options:

1. Resources work on decreasing and maintaining to a minimum the number of dissatisfied customers – dissatisfaction drives constancy as the company/product will exit the market.

2. Most commonly, one can solve customer dissatisfaction and continue according to previous production system design (stability).

3. Based on facts or knowledge about dissatisfaction, one can test a new way of working to modify or reinforce the production system design with new processes (adaptation). For example, service personnel working closely with customers by means of contextual knowledge could support development.

4. At the end of the day, customer dissatisfaction loses customers, underlining the need to explore a radical new way of working in the production system together with the market (users and/or customers). Consequently, dissatisfaction could be turned into a transformation of the production system that can offer new processes or solutions to customers. Paradoxically, the higher the dissatisfaction, the more satisfaction (transformation) there is.

5. Customer dissatisfaction is used as a constructive deviation (source for transformation) in one part of the organisation, but as a destructive deviation in another (source for stagnation). Consequently, there is no shared view within the organisation that leads towards disintegration.

Options (2)–(4) are all equally important regarding how QM can be used to manage customer dissatisfaction to improve production system design. Consequently, the critical point of the EQM paradigm is that the three options cannot be achieved in isolation.

External dynamic conditions on the marketplace

Operations face challenges on how to adapt to the external dynamic conditions in the marketplace. The dynamic conditions that impact production systems are, for example, different customer needs of product mixes or high versus low volume demands. This implicates changes and re-engineering production systems. One can look at the re-engineering processes in several ways, and the EQM way of making decisions proposes five options:

1. Resources continue working in existing production system design without re-engineering changes; in other words, external dynamics are not considered and the company/product will exit the market while the interest for the company products is decreasing (stagnation).

2. Most commonly, one can develop the quality of products with low variations in current production system design with current volume and product mix (stability).

3. Based on the facts or knowledge on external dynamics, one can modify or reinforce production system design with new processes (adaptation to external dynamic conditions). For example, service personnel working closely with customers could support the re-engineering process through contextual knowledge about changing needs. This could enable a higher variation in the product mix, adaptable to different volume demands.

4. Ultimately, the cycles of external dynamic conditions are so frequent that require exploring a radical new way of working in the production system, together with the market (users and/or customers). This way, external dynamic conditions could transform a production system into a new design so that it produces new products, processes, or solutions for customers.

5. Finally, production system reengineering is, for example, created using external resources with limited knowledge about the current way of working and organising. While new ideas meet ‘old ways of doing things around here’, the initiation of a transformation easily become fragmented in an organisation, which ultimately leads to disintegration.

Options (2)–(4) are equally important in using QM to manage external dynamics to re-engineer the production system design. Consequently, the critical point in the EQM paradigm is that the three options cannot be achieved in isolation.

Discussion and conclusions

Using the new EQM paradigm could make a difference in terms of not only achieving stability but also adaptation and managing transformations. This section discusses this proposal and concludes with implications for both theory and practice, ending with a discussion on the limitations of the proposals and ideas for future research.

Entering the EQM paradigm

One can reflect on what type of dynamic is most relevant but, in EQM, all five types could make a difference. The types of social dynamics depend both on time and the system level. In the examples of integrating EQM in operations, fast reactions to achieve short-term (2) stability are obviously critical. Still, one can reflect on two more pathways for this critical dilemma: (3) adaptation to new ways of working by reinforcing or modifying ES, IS, and CS or (4) a full transformation of the production system that requires stability while also building a shadow system; finally, the adoption of a complete new production system transformation is also important. In the latter case, more disruptions in production imply a better chance for transformation, with both positive and negative feedback processes as driving forces. However, time is required to reach that state, as is the decision on the level of study (individual, group, or organisation). Adaptation entails stability within AES and adaptations to ES, IS, and CS, while transformations entail stability when building the shadow system; finally, the adaptation of the complete system entails changes such as a radically changed production system design.

EQM also acknowledges to continuously managing dichotomies as part of four interrelated processes. The implication is that the different shares of the dichotomies are equally important. Reinforcement or modification of structures depends on the type of social dynamics: (1) stagnation, (2) stability, (3) adaptation, (4) transformation, and (5) disintegration. While stagnation anticipates a product/company exiting the market, EQM focuses on constancy, control, exploitation, and efficiency until there are no operations left to manage. However, stability and adaptation entail the management of dichotomies: constancy and change, control and creativity, exploitation and exploration, and efficiency and effectiveness. Most efforts are apparently made towards the social dynamic that entails transformation. The proposed conceptual framework of EQM describes this type of dynamics at the highest level of study (operation), preceded by a shadow structure that ultimately transforms aggregated IS, IS, and CS. When the transformation eventually takes place, the four interlinked processes of the production system are managing change, creativity, exploration, and effectiveness. For example, when lacking contextual knowledge about organisations, integrating QM could lead to disintegration due to stagnation within some parts of the organisation and transformation in others.

Managerial implications

The EQM paradigm entails a new type of decision support that entails several implications. While consciously managing different types of social dynamics over time at different system levels is important, they should not, ideally, compete for scarce resources. While stability, adaptation, and transformation are conscious decisions towards a better future state, stagnation and disintegration impede development. As such, the four interrelated processes and their dichotomies are part of a production system development better fitted to the dynamic conditions of the marketplace. The new EQM paradigm could thus enable an integrated decision support that facilitates managing production systems, for example, during external dynamic conditions.

Theoretical implications

This conceptual paper contributes to the ongoing discussion on how to manage and change production systems (see e.g. Marodin & Saurin, 2013) and responds to the calls of Fundin et al. (2018), Evans et al. (2014), and Radziwill (2013) for more research that explores how the improvement of organisational learning and innovation could be better integrated with QM. In other words, it contributes to the ongoing development of QM theories in managing change using the theories of social dynamics and of emergence as analytical means. By combining QM theories with complex systems theory to describe social dynamics at different levels of study from the emergence perspective, QM theories are developed by shedding light on how QM programmes could be used under dynamic conditions. In other words, the EQM paradigm implicates QM should be consciously adopted, based on knowledge about social dynamics in organisations. This paper uses four interrelated processes to describe the EQM paradigm: while the production and innovation processes are explicit in a production system design, the equally critical processes of knowledge and value creation are both embedded. As these processes realise critical dichotomies in a production system, the proposed EQM paradigm also contributes to the ongoing discourse on theorising process data from the perspective of emergence (see e.g. Langley et al., 2013).

Limitations and future research

Our paper has some limitations that also lead to proposals for future research. Despite the conceptual design of this paper, future research should empirically integrate the EQM way of working. As such, studying the effects of managing change should be based on the different dynamic conditions in the marketplace that trigger different dynamics in organisations. This is critical, as these dynamics have a significant impact on ongoing QM programmes. Similarly, while this paper describes five different scenarios from the perspective of how deviations could be acted upon under the EQM paradigm, future research should elaborate on supplementary critical scenarios that challenge how QM could be better adopted into operations under dynamic conditions.

Acknowledgements

We are grateful to both reviewers and the editor for their constructive feedback that made us improve our article. The authors would also like to acknowledge Editage for proof-reading our manuscript. This research is part of the initiative for Excellence in Production Research (XPRES), which is a joint project between Mälardalen University, the Royal Institute of Technology, and RISE. XPRES is one of two Swedish government-funded strategic initiatives for research excellence in production engineering.

Disclosure statement

No potential conflict of interest was reported by the authors.