On the inclusion of sustainability and digitalisation in quality management – an overview from past to present

Sustainability and Quality Management: has EFQM fostered a Sustainability Orientation that delivers to stakeholders?

Purpose

As a Quality Management (QM) framework, the European Foundation for Quality Management (EFQM) Excellence Model has stakeholder management at its core. In EFQM (2012), based on which assessments were made until 2021, “creating a sustainable future” was a fundamental principle, but how it translated to a Sustainability Orientation and delivered to stakeholders remains questionable. This study aims to investigates the Sustainability Orientation within EFQM (2012) and its associations with Results for stakeholders.

Design/methodology/approach

Longitudinal assessments of recognized-for-excellence organizations by a partner of EFQM are considered. Using factor analysis, scores on the sub-criteria that defined “creating a sustainable future” are investigated, and a Sustainability Orientation is inferred. Panel regressions and structural equation modeling assess the correlations between Sustainability Orientation and Results. A qualitative analysis follows, where sustainability reports from role-models within this population are text mined to examine whether and how they reflected the guidance in EFQM (2012) concerning “creating a sustainable future”.

Findings

Direct and indirect positive associations between the Sustainability Orientation implied by EFQM (2012) and stakeholder-performance are confirmed. Yet, inferences from text mining of reported priorities of role-models of excellence illustrate that EFQM (2012) might have driven different strategies towards sustainability.

Originality/value

Despite conceptualizations that the EFQM model embeds a Sustainability Orientation, to the best of the researchers’ knowledge, its existence and likely impact remain to be examined. By combining longitudinal statistical analysis, structural equation models and text mining, consistent insights on the link between Sustainability Orientation and organizational performance are obtained.

The Contribution of Data-Driven Technologies in Achieving the Sustainable Development Goals

The United Nations’ Sustainable Development Goals (SDGs) set out to improve the quality of life of people in developed, emerging, and developing countries by covering social and economic aspects, with a focus on environmental sustainability. At the same time, data-driven technologies influence our lives in all areas and have caused fundamental economical and societal changes. This study presents a comprehensive literature review on how data-driven approaches have enabled or inhibited the successful achievement of the 17 SDGs to date. Our findings show that data-driven analytics and tools contribute to achieving the 17 SDGs, e.g., by making information more reliable, supporting better-informed decision-making, implementing data-based policies, prioritizing actions, and optimizing the allocation of resources. Based on a qualitative content analysis, results were aggregated into a conceptual framework, including the following categories: (1) uses of data-driven methods (e.g., monitoring, measurement, mapping or modeling, forecasting, risk assessment, and planning purposes), (2) resulting positive effects, (3) arising challenges, and (4) recommendations for action to overcome these challenges. Despite positive effects and versatile applications, problems such as data gaps, data biases, high energy consumption of computational resources, ethical concerns, privacy, ownership, and security issues stand in the way of achieving the 17 SDGs.

Quality 4.0 conceptualisation: an emerging quality management concept for manufacturing industries

Purpose

Quality 4.0 refers to a modern quality management approach that uses Industry 4.0 technologies, integration and digitalisation. This research explores the current understandings of Quality 4.0 in various publications. The focus is on Quality 4.0 concepts or explanations, available models, motivation and readiness factors for adoption, enablers and technologies that can be leveraged.

Design/methodology/approach

A qualitative approach was deployed to collect the findings. This paper employs bibliometric, scientometric and visual analytic tools to identify and analyse articles from Scopus, Web of Science (WOS), Google Scholar databases and other sources such as ScienceDirect and Taylor and Francis.

Findings

The bibliometric results revealed that Quality 4.0 publications began in 2016 and increased dramatically in 2020 and 2021, with India leading the way while scientometric analysis found no clear definition of Quality 4.0 hitherto. However, several authors have defined the concept of Quality 4.0, arguing that it is characterised by digitalisation and integration, Industry 4.0 technologies applications and big data management. Some of the Quality 4.0 models published in the theoretical underpinnings include total quality management (TQM) in the basis of Industry 4.0 model, the European Foundation for quality management model, Quality 4.0 model combining operational technology (OT) and information technology (IT) through digital transformation and the LSN Research eleven axes of Quality 4.0 model. The research highlights key enablers of Quality 4.0 adoption, such as enabling technologies, big data capability, skilled and competent workers, collaboration and leadership support.

Research limitations/implications

The findings can benefit Quality 4.0 researchers and practitioners on the available Quality 4.0 models, motivation and readiness factors for Quality 4.0 adoption, enablers and leveraged technologies in Quality 4.0.

Originality/value

This study attempted to explore the current understandings of Quality 4.0 concepts to sediment these emerging quality management concepts for manufacturing industries.