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High-growth firms generate a large share of new jobs and are thus the key drivers of innovation and industry dynamics. As the employees' education supports innovation and productivity, this article hypothesizes that employee competences explain high growth.

The study approaches this by examining intangible capital and specialized knowledge to evaluate how these characteristics support the probability of becoming a high-growth firm. The estimation uses linked employer–employee data from Danish registers from 2005 to 2013.

As the authors measure high growth with the size-neutral Birch index, they can examine the determinants of high growth across different firm size classes. The findings imply that intangible capital relates positively to the firm's high growth.

Previous research on high-growth firms is concentrated on the owners’ education. This article broadens to the high education of all employees and accounts for the employees’ occupation and capitalization of knowledge with intangible capital.

This paper aims to evaluate the impact of the subsidies established by Measure 123 of the Rural Development Policy on the productivity of a sample of agri-food and forestry companies in the region of Asturias over the period 2006-2009.

The authors estimate a stochastic frontier function which allows subsidies to be considered as affecting both the level of technical efficiency and technical progress.

The results show that while subsidies have a positive effect on the technical progress of companies in the agri-food industry, for the forestry industry, the effect materializes as an improvement in technical efficiency. Additionally, other factors affecting either, technical progress and technical efficiency were identified.

This study adopts a model that allows the separate identification of the effect of subsidies on the level of efficiency, on the one hand, and on the technical progress, on the other.

The objective of this study is to construct a theoretical framework concerning wage determination, grounded in principles and supplemented by conventional theories. It discusses the Islamic perspectives on minimum wage and examines contemporary challenges and intricacies in its application.

This study uses thematic analysis to create the conceptual framework, drawing upon a review of pertinent literature such as academic papers, books and articles published up to 2023.

The framework encompasses various categories, namely, employee characteristics, job characteristics, market factors, compensation practices and Islamic principles. Each category consists of multiple variables. The resulting framework offers a holistic and ethically grounded methodology for wage determination, aligning with both Islamic and conventional perspectives. This study notes the absence of a universally agreed-upon minimum wage. Islamic economics faces challenges due to the unclear application of principles, limited awareness, legal constraints and a lack of empirical evidence on wage systems, along with complexities in their implementation.

The paper’s limited scope focuses solely on the Islamic perspective on wage determination, without comparing it to the conventional viewpoint. This may have implications for future research.

The insights on Islamic principles and wage determination guide scholars and policymakers interested in promoting just and equitable wages.

This study is distinct in its integration of various factors to propose an all-encompassing framework for wage determination, rooted in the Quran and principles, while also reinforcing the framework with conventional theories. Additionally, it adds to the growing body of literature by investigating the Quran’s stance and principles on minimum wage, as well as discusses the challenges involved in implementing an Islamic approach to wage determination, which has received limited attention in Islamic literature.

The authors provide a novel interpretation of the relationship between skill demand and labour market concentration based on the training rationale.

The authors use a novel data set on Italian online job vacancies during 2013–2018 to analyse the relationship between labour market concentration and employers' skill demand. The authors construct measures of market concentration and skill intensity in the local labour market. The authors regress the measures of skill demand on market concentration, controlling for sector, occupations and other features of the labour market. The authors also use the Hausman–Nevo instrument for market concentration.

The authors show that employers in a highly concentrated labour market demand competencies associated with the ability of workers to learn faster (e.g. social skills) rather than actual knowledge. They also require less experience but higher education. These results are consistent with the hypothesis that employers in more concentrated labour markets are more prone to train their employees. Instead of looking for workers who already have job-specific skills, they look for workers who can acquire them faster and efficiently. The authors provide a theoretical framework within which to analyse these aspects as well as providing a test for the relevant hypotheses.

In addition to cross-countries differences in labour market regulations, the authors' findings suggest that policy authorities should consider the local labour market structure when studying workforce development programmes aimed at bridging the skill gap of displaced workers. Moreover, the authors show that market concentration can have relevant implications for human resource (HR) managers by affecting their recruitment behaviour through the demand for skills. In fact, concentrated markets tend to favour firms' collusion and anti-competitive behaviour that could strongly affect HR management practices.

The authors' paper innovates on the literature in a number of ways. First, the authors provide evidence of local labour market concentration in Italy. Second, the authors provide evidence of skill demand at the local level using a detailed skill taxonomy that goes beyond the classical distinction between high and low skills. Third, and most importantly, the authors provide evidence of the relationship between skill demand and labour market concentration. By analysing detailed skills and competencies, the authors take one step beyond understanding the features of labour demand in monopsonistic markets.

The study examines the remote integration process of advanced manufacturing technology (AMT) into the production system and identifies key challenges and mitigating actions for a smoother introduction and integration process.

The study adopts a case study approach to a cyber-physical production system at an industrial technology center using a mobile robot as an AMT.

By applying the plug-and-produce concept, the study exemplifies an AMT's remote integration process into a cyber-physical production system in nine steps. Eleven key challenges and twelve mitigation actions for remote integration are described based on technology–organization–environment theory. Finally, a remote integration framework is proposed to facilitate AMT integration into production systems.

The study presents results purely from a practical perspective, which could reduce dilemmas in early decision-making related to smart production. The proposed framework can improve flexibility and decrease the time needed to configure new AMTs in existing production systems.

The area of remote integration for AMT has not been addressed in depth before. The consequences of lacking in-depth studies for remote integration imply that current implementation processes do not match the needs and the existing situation in the industry and often underestimate the complexity of considering both technological and organizational issues. The new integrated framework can already be deployed by industry professionals in their efforts to integrate new technologies with shorter time to volume and increased quality but also as a means for training employees in critical competencies required for remote integration.

This paper proposes a progressive, multi-level framework for diagnosing maintenance performance: rapid performance health checks of key performance for different equipment groups and end-to-end process diagnostics to further locate potential performance issues. A question-based performance evaluation approach is introduced to support the selection and derivation of case-specific indicators based on diagnostic aspects.

The case research method is used to develop the proposed framework. The generic parts of the framework are built on existing maintenance performance measurement theories through a literature review. In the case study, empirical maintenance data of 196 emergency shutdown valves (ESDVs) are collected over a two-year period to support the development and validation of the proposed approach.

To improve processes, companies need a separate performance measurement structure. This paper suggests a hierarchical model in four layers (objective, domain, aspect and performance measurement) to facilitate the selection and derivation of indicators, which could potentially reduce management complexity and help prioritize continuous performance improvement. Examples of new indicators are derived from a case study that includes 196 ESDVs at an offshore oil and gas production plant.

Methodological approaches to deriving various performance indicators have rarely been addressed in the maintenance field. The proposed diagnostic framework provides a structured way to identify and locate process performance issues by creating indicators that can bridge generic evaluation aspects and maintenance data. The framework is highly adaptive as data availability functions are used as inputs to generate indicators instead of passively filtering out non-applicable existing indicators.