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This paper aims to identify and empirically analyze useful and applicable metrics for measuring and managing the sustainability performance of small and medium-sized enterprises (SMEs).

To achieve the objective of the paper, potential metrics were adopted from previous research related to industrial sustainability and an empirical analysis was carried to assess the applicability of the metrics by collecting empirical data from Italian footwear SMEs using a structured questionnaire. The SMEs were selected using a convenience sampling method.

The results of the within-case analysis and the cross-case analysis indicate that the majority of the metrics were found to be useful and applicable to each of the SMEs and across the SMEs, respectively. These metrics emphasized measuring industrial sustainability performance related to financial benefits, costs and market competitiveness for the economic sustainability dimension; resources for the environmental sustainability dimension; and customers, employees and the community for the social sustainability dimension.

Apart from the within-case analysis and cross-case analysis, it was not possible to conduct statistical analysis since a small number of SMEs were accessible to collect empirical data.

The findings of the paper have considerable academic, managerial and policy implications and will provide a theoretical basis for future research on measuring and managing industrial sustainability performance. By providing a set of empirically supported metrics based on the triple bottom line approach (i.e. economic, environmental and social metrics), this paper contributes to the existing knowledge in the field of industrial sustainability performance measurement.

Frugal innovation focuses on the core functionalities with the highest stakeholder benefits and directly targets user requirements. It has been widely adopted in developing countries, and extensively researched from both consumer and sustainable perspectives. However, few studies on frugal innovation consider “quality”, a seminal business management concept. This study focuses on this gap and uses a quality lens to understand frugal innovation.

This study adopts a mixed methodology. The Delphi focus group method is first applied to identify two cases of frugal innovation in the construction industry and a cross-case analysis done. Then, the analytic hierarchy process (AHP) is used to examine eight product quality dimensions to draw the final conclusions.

From Garvin’s concept of quality, frugal innovation focuses on performance and conformance. Furthermore, it prioritises a value-based approach the most.

This study examines frugal innovation from quality perspective. This opens up a new line of research which contributes to both streams. The study is based on construction which is a limitation of the study.

A quality-based frugal innovation understanding can be helpful in the conceptualisation, implementation and acceptance of the frugal innovation business model. It can provide clarity on the innovation's value proposition and also help in operationalisation of the business model.

Frugal encourages social entrepreneurs and understanding of the concept from quality perspective shall facilitate the operationalisation will become easier for them.

To the author’s knowledge, this is the first study at the interface of frugal innovation and quality management. Furthermore, the use of AHP to prioritise equality approaches and dimensions is an original contribution.

Industry 4.0 technologies have the potential to improve the quality management performance of industrial companies. The paper analyses the influence of Industry 4.0 technologies on quality management aspects, but also the barriers that slow down the deployment of each Industry 4.0 technology and limit each impact.

The impact of Industry 4.0 technologies on quality management aspects (QMAs) is a heterogeneous and multidimensional phenomenon dependent on the current context, a holistic multiple case study has been applied. Twenty-six case studies were carried out on eight Industry 4.0 technologies, with a minimum of two cases per technology. These cases were selected from the 168 projects presented in the four editions of the BIND 4.0 program, winner of the 14th edition of the European Enterprise Promotion Awards. The cases were selected based on a preliminary survey of 124 project managers. Subsequently, individual case and cross-case analyses for each technology were carried out. Finally, these results were confirmed by interviews with a minimum of two customers per Industry 4.0.

Results show that the adoption of Industry 4.0 technologies positively affects QMAs. Specifically, the influences received by “process control” and “customer satisfaction” from all the Industry 4.0 technologies studied are medium to high. In addition, barriers from the “economic and legal” and “workers” categories exert greater influence than the barriers pertaining to “organization”, “lack of training and information” and “technology”.

The main limitation is the generalizability of the findings of qualitative studies (ergo the case study). In this sense, statistical generalizability, characteristic of a random sample, is not intended in this paper. Therefore, the use of multiple case studies has been chosen to reinforce analytical generalizations with corroborated evidence (literal replication).

Managers interested in adopting Industry 4.0 technologies Ts should plan the implementation process to minimize the impact of these barriers and optimize the results for each stakeholder. In this sense, the barriers that concern the workers should be managed. It is the responsibility of managers to inform and explain how data will be handled, and how privacy concerns will be addressed.

It is essential to explain and convince workers about the need for a renewal of tasks. New types of jobs (i.e. the use of robots) will involve training for workers to enable their integration alongside the new technologies.

This paper addresses two under-researched areas that are essential when defining strategies in the industrial business context. Firstly, the paper analyses the influence of each I40 T on each QMA. Secondly, it analyses the barriers to adopt that slow down the rollout of each I40 T and limits each impact.

Despite extensive academic research related to digital technologies (DT), their integration into architecture, engineering and construction (AEC) projects lags in practice. This paper aims to discover DT deployment patterns and emerging trends in real-life AEC projects.

A case study methodology was adopted, including individual case analyses and comparative multiple-case analyses.

The results revealed the temporal distribution of DT in practical AEC projects, specific DT products/software, major project types integrated with digital solutions, DT application areas and project stages and associated project performance. Three distinct patterns in DT adoption have been observed, reflecting the evolution of DT applications, the progression from single to multiple DT integration and alignment with emerging industry requirements. The DT adoption behavior in the studied cases has been examined using the technology-organization-environment-human (TOE + H) framework. Further, eight emerging trend streams for future DT adoption were identified, with “leveraging the diverse features of certain mature DT” being a shared recognition of all studied companies.

This research offers actionable insights for AEC companies, facilitating the development of customized DT implementation roadmaps aligned with organizational needs. Policymakers, industry associations and DT suppliers may leverage these findings for informed decision-making, collaborative educational initiatives and product/service customization.

This research provides empirical evidence of applicable products/software, application areas and project performance. The examination of the TOE + H framework offers a holistic understanding of the collective influences on DT adoption. The identification of emerging trends addresses the evolving demands of the AEC industry in the digital era.

This study aims to explore the management learning during a long-term crisis like a pandemic. The paper addresses both what health-care managers have learnt during the COVID-19 pandemic and how the management learning is characterized.

The paper is based on a qualitative case study carried out during the COVID-19 pandemic at two different public hospitals in Sweden. The study, conducted with semi-structured interviews, applies a combination of within-case analysis and cross-case comparison. The data were analyzed using thematic deductive analysis with the themes, i.e. sensemaking, decision-making and meaning-making.

The COVID-19 pandemic was characterized by uncertainty and a need for continuous learning among the managers at the case hospitals. The learning process that arose was circular in nature, wherein trust played a crucial role in facilitating the flow of information and enabling the managers to get a good sense of the situation. This, in turn, allowed the managers to make decisions meaningful for the organization, which improved the trust for the managers. This circular process was iterated with higher frequency than usual and was a prerequisite for the managers’ learning. The practical implications are that a combined management with hierarchical and distributed management that uses the normal decision routes seems to be the most successful management method in a prolonged crisis as a pandemic.

The gained knowledge can benefit hospital organizations, be used in crisis education and to develop regional contingency plans for pandemics.

This study has explored learning during the COVID-19 pandemic and found a circular process, “the management learning wheel,” which supports management learning in prolonged crises.

The increasing capabilities of artificial intelligence (AI) are changing the way organizations operate and interact with users both internally and externally. The insurance sector is currently using AI in several ways but its potential to disrupt insurance is not clear. This research evaluated the implementation of AI-led automation in 20 insurance companies. The findings indicate four business models (BM) emerging: In the first model the insurer takes a smaller part of the value chain allowing others with superior AI and data to take a larger part. In the second model the insurer keeps the same model and value chain but uses AI to improve effectiveness. In the third model the insurer adapts their model to fully utilize AI and seek new sources of data and customers. Lastly in the fourth model a technology focused company uses their existing AI prowess, superior data and extensive customer base, and adds insurance provision.

The purpose of this paper is to explore and disseminate knowledge about quantum-inspired computing technology's potential to solve complex challenges faced by the operational agility capability in Industry 4.0 manufacturing and logistics operations.

A multi-case study approach is used to determine the impact of quantum-inspired computing technology in manufacturing and logistics processes from the supplier perspective. A literature review provides the basis for a framework to identify a set of flexibility and agility operational capabilities enabled by Industry 4.0 Information and Digital Technologies. The use cases are analyzed in depth, first individually and then jointly.

Study results suggest that quantum-inspired computing technology has the potential to harness and boost companies' operational flexibility to enhance operational agility in manufacturing and logistics operations management, particularly in the Industry 4.0 context. An exploratory model is proposed to explain the relationships between quantum-inspired computing technology and the deployment of operational agility capabilities.

This is study explores the use of quantum-inspired computing technology in Industry 4.0 operations management and contributes to understanding its potential to enable operational agility capability in manufacturing and logistics operations.

This paper aims to provide a comprehensive view of the different competition-based approaches that policymakers can exploit to foster external knowledge search and their positioning among innovation policy measures. A growing number of companies have implemented initiatives to access external knowledge to increase their innovativeness, consistently with the open innovation paradigm. Competition-based approaches have received increasing attention by the private sector as a way to access external knowledge. However, despite their potential role as innovation policy measures, a limited attention has been devoted so far to investigate them from the policymakers’ perspective.

To this aim, a two-stage empirical analysis has been carried out to develop a taxonomy of competition-based approaches. The first stage leveraged a multiple case study methodology including a sample of 20 competition-based approaches, while the second one leveraged interviews with Italian and European key informants.

This paper proposes a novel taxonomy including eight competition-based approaches, which differ among each other in terms of policy strategy, scope breadth and output required. Moreover, this paper enriches a well-established taxonomy of innovation policy instruments with the identified competition-based approaches.

This study contributes to the current debate on innovation policy by providing a taxonomy that includes eight competition-based approaches that can be exploited by policymakers to foster external knowledge search as well as their positioning among the innovation policy instruments. The taxonomy will hopefully support policymakers in identifying of the most suitable instruments in the light of their policy strategy and objectives.

This study aims to examine the international market selection process of entrepreneurs operating internationally.

Four small and medium-sized comparative and rich-information case studies were purposefully selected from among Australian and Arabian firms. Data were collected via in-depth personal interviews, follow-up interviews and questionnaire instrument.

The results revealed that entrepreneurs used a four-stage systematic decision-making process to attain profitable foreign market choices. The decision process was influenced by cognitive boundaries as entrepreneurs relied on the availability experiential, anchoring and adjustment heuristic.

The research’s findings and the proposed decision model will, significantly, assist entrepreneurs, willing to expand internationally, in enhancing their decision-making to attain profitable foreign market choices. Further, it provides benefits to foreign investment policymakers in host countries by assisting them to attract more inward foreign direct investments, and, accordingly, enhance the economic and social development movement in their countries.

This study provides a significant theoretical contribution to the literature on the internationalization process of entrepreneurs and small- and medium-sized enterprises through developing a decision model for selecting and entering foreign markets by entrepreneurs in a cross-country context. Further, the study provides significant methodological contributions with regard to the effectiveness of the qualitative case study method in capturing elements of the foreign market selection process.

This paper explores the orchestration of digital innovation in Industry 4.0 organisations.

The study applies the activity theory to explorative multiple case studies. Observations of innovation activities in five business cases take place at two large international organisations.

The results underline five logics of action that drive digital innovation: (1) digital transformation, (2) technology translation, (3) catalyst agents, (4) digital thread and (5) empowerment. Further, the case study organisations highlight the importance of developing a sustainable culture capable of continuously adopting new technologies, processes and infrastructure that will allow the management of digital innovations.

The study empirically shows the motivations and challenges in orchestrating digital innovation in Industry 4.0 organisations.