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Quality management (QM) can support organisations in contributing to sustainable development. As a result of an expanding focus from customers towards stakeholders within QM, the perspectives to consider multiply. Understanding how practices and tools for process management are specifically affected by this increase in perspectives is key to creating the right conditions for improvement initiatives that support sustainable development.

This paper constructs a typology wherein the use of process management practices and tools is described in nine distinguished system contexts. Inductive discrimination is used to differentiate the system contexts and different use cases for process practices and tools.

Using the system of systems grid (SOSG), mainstream business process management (BPM) practices are positioned in a simple unitary context, whilst sustainability challenges also involve more complex contexts. Addressing these challenges requires integrating new tools and methods from paradigms outside of traditional functionalist business process management practices.

This paper highlights the necessity to consider system contexts when developing feasible practices and tools for effective process management.

Practical implications are that quality practitioners aiming to exploit the potential in process management to support sustainability get support for planning and conducting process improvement initiatives aiming to consider several stakeholder perspectives.

This paper presents a new typology for understanding the context of QM process initiatives and BPM in light of a contemporary sustainability focus.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.

The purpose of this paper is to explore how process management (PM) can support small- and medium-sized enterprises (SMEs) in pursuing sustained competitive advantage. For this purpose, a dynamic capabilities (DC) lens was used.

A narrative literature review and a multiple case study with an action research approach at two road freight transport companies were used.

PM provides structure and system thinking to support the development of competitive advantage. Concerning PM, management of knowledge, management style and process orientation are key factors for the generation of competitive advantage for SMEs.

This study contributes to PM literature by studying its support for and implementation at SMEs. Furthermore, the study contributes to the literature on DC by providing concrete examples of activities linked to such capabilities.

This study contributes to practitioners by providing examples of implementing PM and identifying competitive advantage, connected with PM elements.

This study has social and environmental implications for the quality of life of the Swedish people.

This paper contributes to clarifying the connection between the research fields of quality management and DC to explore how PM can support SMEs in pursuing sustained competitive advantage.

Hyperautomation is a technological concept whose popularity has been growing continuously since the German manufacturing industry “initiated” the Fourth Industrial Revolution (Industry 4.0), whereas, on the basis of theory, hyperautomation is a term still new and little recognized. This applies equally to scientific studies (articles, conference reports) and empirical studies (quantitative, qualitative). Therefore, this article attempts to fill definition gap that exists in the literature on management and quality sciences on the term hyperautomation.

The authors use literature review approach to identify the gaps in the existing literature on hyperautomation. They present a nominal definition of hyperautomation, discuss related issues and provide a comparative perspective between hyperautomation and automation.

The article’s findings include a precise definition of hyperautomation and the problems it raises. The authors point out that the term “hyperautomation” is still relatively new and underutilized in the management and quality sciences literature. It also compares hyperautomation to automation from several angles and emphasizes how it affects businesses, industries and other economic sectors.

Authors emphasize that in order to deploy hyperautomation successfully, enterprises must take a distributed and integrated approach.

This article addresses a gap in the management and quality sciences literature about the definition of hyperautomation. Authors give a thorough explanation of hyperautomation, along with relevant problems, useful implications and a comparison between hyperautomation versus automation.