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Due to population ageing, the European Union (EU) has adopted active ageing as a guiding principle in labour and retirement policies. Among the strategies for active ageing, age-friendly workplaces play a crucial role. This study compares age-friendly human resource (HR) practices in the Baltic and Nordic countries. The latter are pioneers in active ageing, and as the employment rate of older employees in the Baltics is like that in the Nordic countries, we may assume equally age-friendly workplaces in both regions.

We used the latest CRANET survey data (2021–2022) from 1,452 large firms in seven countries and constructed the fuzzy logic model on age-friendliness at the workplace.

Despite a high employment rate of older individuals in the Baltics, HR practices in these countries fall short of being age-friendly compared to their Nordic counterparts. Larger firms in the Nordic countries excel in every studied aspect, but deficiencies in the Baltics are primarily attributed to the absence of employer-provided health and pension schemes. The usage of early retirement is more frequent in the Nordic countries; however, its conceptualisation as an age-friendly HR practice deserves closer examination. Our findings suggest that the success of active ageing in employment has translated into age-friendly HR practices in larger organisations in the Nordics, but not in the Baltics. It is likely that high employment of older individuals in Estonia, Latvia and Lithuania is a result of the relative income poverty rate.

Our model represents one of the few attempts to utilise fuzzy logic methodology for studying human resource practices and their quantitative evaluation, especially concerning age-friendly workplaces.

Measuring shared value (SV) created in innovation ecosystems (IEs) is increasingly relevant but complex, given the multidimensional and multiactor nature of both concepts, which challenges traditional performance measurement systems (PMSs). Moving from this gap, the authors propose an integrated approach to extend the balanced scorecard (BSC) for measuring and monitoring SV creation at IE level.

The proposed approach combines the most recent contributions on PMS in IEs and SV to define perspectives and dimensions that are better suited to deal with the nature of both IEs and SV. The approach is also applied to the real case (Alpha) of an Italian IE through a step wise method. Starting from the IE vision, the authors identify in the strategy map the specific objectives related to each perspective/dimension combination and then associate a performance indicator with each objective.

The resulting SV BSC is composed of indicators interconnected along different perspectives and dimensions. The application of the approach to the real case proves its feasibility and highlights characteristics, advantages and disadvantages of the SV BSC when used at IE level. The authors also provide guidelines for its application to other IEs.

The study contributes to the research on PMS by introducing and applying to a real case an integrated approach to assess SV in IEs, overcoming the shortcomings of PMS framed for single firms. It can be of interest for both researchers in the field of ecosystems value creation and practitioners managing or promoting such complex structures.

Responding to calls for deeper analysis of the conceptual foundations of service infusion in manufacturing, this paper examines the underlying assumptions that: (i) manufacturing firms incorporating services follow a pathway, moving from pure-product to pure-service offerings, and (ii) profits increase linearly with this process. We propose that these assumptions are inconsistent with the premises of behavioural and learning theories.

Machine learning algorithms are applied to test whether a successive process, from a basic to a more advanced offering, creates optimal performance. The data were gathered through two surveys administered to USA manufacturing firms in 2021 and 2023. The first included a training sample comprising 225 firms, whilst the second encompassed a testing sample of 105 firms.

Analysis shows that following the base-intermediate-advanced services pathway is not the best predictor of optimal performance. Developing advanced services and then later adding less complex offerings supports better performance.

Manufacturing firms follow heterogeneous pathways in their service development journey. Non-servitised firms need to carefully consider their contextual conditions when selecting their initial service offering. Starting with a single service offering appears to be a superior strategy over providing multiple services.

The machine learning approach is novel to the field and captures the key conditions for manufacturers to successfully servitise. Insight is derived from the adoption and implementation year datasets for 17 types of services described in previous qualitative studies. The methods proposed can be extended to assess other process-based models in related management fields (e.g., sand cone).

This study investigates the impact of entrepreneurial orientation (EO) and knowledge management (KM) on firm performance (PERF), as well as the mediating role of KM in the EO–PERF (EO-PERF relationship). In particular, this study aims to explain the impact of KM on the relationship between the EO dimensions and PERF; dimensions are risk-taking (RT), innovativeness (IN) and proactiveness (PR).

This study uses structural equation modelling and fuzzy-set qualitative comparative analysis (fsQCA) methodologies to explore target relationships. The sample consists of 150 small furniture manufacturers operating in Poland (out of 1,480 in the population).

The study findings show that KM partially mediates the IN–PERF relationship. Furthermore, fsQCA reveals that KM accompanied by IN is a core condition that leads to PERF. Moreover, the absence of KM (accompanied by the absence of RT and IN) leads to the absence of PERF. In addition, the results show that all the variables examined (RT, IN, PR and KM) positively impact PERF.

This study explores the role of KM in the context of EO and its impact on PERF in the low-tech industry. The study uses simultaneously two methodologies that represent different approaches in the search for the expected relationships. The findings reveal that KM mediates the EO-PERF relationship.

This study aims to investigate which configurations of organizational-level and group-level management controls support an identity fit for management accountants in the management accounting profession. It aims to complement recent qualitative management accounting research. This stream just begun to use role and identity theory to investigate role expectations, conflicts and coping strategies of management accountants when they struggle with their work identity.

Based on configuration theory, this study uses a fuzzy-set qualitative comparative analysis to indicate all possible configurations of formal and informal management controls that improve management accountants’ sense of their identity in an organization. The analyses are based on the results of a cross-sectional survey of 277 management accountants from Germany, Austria, Switzerland and Liechtenstein.

The results show that a strong group culture and high psychological safety at the group level are relevant conditions for a high identity fit. Further, the configurations differ regarding the career stages of management accountants.

This study contributes to work identity research of management accountants and to research on formal and informal control configurations as a control package. It is of particular importance for various professions that are affected by role change, as from the findings on management accountants’ identity fit, implications can also be made for other organizational functions that need to engage in identity work.

This study explores the differences and similarities of work value profiles in samples of business students from four countries with markedly different cultures and labor markets.

We used multiple-group latent profile analysis (LPA) to explore the differences and similarities in work value profiles across cultures (n = 317 from Switzerland, n = 313 from Spain, n = 326 from the United States and n = 327 from China).

The latent profiles mostly show similarities across countries: the largest profiles are a want it all and a humble profile with overall high and intermediate levels in all work values. An overall low work value levels profile and one stressing high security and pay emerged in all countries except Switzerland. In the Swiss sample, two unique profiles emerged: the no status and freelancers profiles.

This study has implications for employee attraction, relations and career counseling with culturally diverse populations.

Studies on work values across cultures most often make direct comparisons between samples, which can lead to excessive emphasis on sometimes small differences. By first studying within-culture differences before comparing the results across cultures, we find that there may be more similarities than differences in work values across cultures and that cross-cultural differences may have often been overstated.

Land is the basis for economic development as well as tourism development. There is a close relationship between tourism development and the land market. However, research on the effect of tourism development on land prices is insufficient. This paper aims to investigate the effect and mechanism of tourism development on land prices.

The econometric paradigm is the main research method. Fixed effect models, instrumental variable models and mediating effect models are introduced to examine the impact of tourism development on land prices. The data include three types: land transaction data, city-level data and scenic spot data. More than 360,000 samples of land transactions for 284 prefecture-level cities in China from 2007 to 2021 are applied.

Tourism development can significantly increase land prices. This conclusion holds after using instrumental variables to address endogeneity and testing for robustness. Meanwhile, tourism development’s effect on land price is influenced by land type, city type, city tier and city location. The land price increase effect of tourism is more significant for tourism land, tourist cities, central cities and Western cities. The paper also reveals the mechanisms of the public service enhancement effect, infrastructure upgrading effect and environmental optimization effect in tourism development’s effect on land price.

The study contributes to the literature on the relationship between tourism development and land market. The generality and specificity of tourism development’s effect on land price are revealed from the micro and macrolevel research level. The findings enrich the literature on tourism price effects, point to rational ways to optimize and regulate land prices and provide new ideas for land-market development.

This paper seeks to explore the sensitivity of these parameters and their impact on fiscal policy outcomes. We use the existing literature to establish possible ranges for each parameter, and we examine how changes within these ranges can alter the outcomes of fiscal policy. In this way, we aim to highlight the importance of these parameters in the formulation and evaluation of fiscal policy.

The role of fiscal policy, its effects and multipliers continues to be a subject of intense debate in macroeconomics. Despite adopting a New Keynesian approach within a macroeconomic model, the reactions of macroeconomic variables to fiscal shocks can vary across different contexts and theoretical frameworks. This paper aims to investigate these diverse reactions by conducting a sensitivity analysis of parameters. Specifically, the study examines how key variables respond to fiscal shocks under different parameter settings. By analyzing the behavioral dynamics of these variables, this research contributes to the ongoing discussion on fiscal policy. The findings offer valuable insights to enrich the understanding of the complex relationship between fiscal shocks and macroeconomic outcomes, thus facilitating informed policy debates.

This paper aims to investigate key elements of New Keynesian Dynamic Stochastic General Equilibrium (DSGE) models. The focus is on the calibration of parameters and their impact on macroeconomic variables, such as output and inflation. The study also examines how different parameter settings affect the response of monetary policy to fiscal measures. In conclusion, this study has relied on theoretical exploration and a comprehensive review of existing literature. The parameters and their relationships have been analyzed within a robust theoretical framework, offering valuable insights for further research on how these factors influence model forecasts and inform policy recommendations derived from New Keynesian DSGE models. Moving forward, it is recommended that future work includes empirical analyses to test the reliability and effectiveness of parameter calibrations in real-world conditions. This will contribute to enhancing the accuracy and relevance of DSGE models for economic policy decision-making.

This study is motivated by the aim to provide a deeper understanding of the roles macroeconomic model parameters play concerning responses to expansionary fiscal policies and the subsequent reactions of monetary authorities. Comprehensive reviews that encompass this breadth of relationships within a single text are rare in the literature, making this work a valuable contribution to stimulating discussions on macroeconomic policies.

This study investigates the pathways for adopting IoTs and BDA technologies to improve healthcare management.

The study relied on 445 healthcare professionals' perspectives to explore different causal pathways to IoTs and BDA adoption and usage for daily healthcare management. The Fussy-set Qualitative Comparative Analysis was adopted to explore the underlying pathways for healthcare management.

The empirical analysis revealed six different configural paths influencing the acceptance and use of IoTs and BDA for healthcare improvement. Two key user topologies from the six configural paths, digital literacy and ease of use and social influence and behavioural intentions, mostly affect the paths for using digital health technologies by healthcare physicians.

Despite this study's novel contributions, limitations include the fsQCA methodology, perceptual data and the context of the study. The fsQCA methodology is still evolving with different interpretations, although it reveals new insights and as such further studies are required to explain the configural paths of social phenomena. Additionally, future research should consider other constructs beyond the UTAUT and digital literacy to illustrate configural paths to healthcare technology acceptance and usage. Again, the views of healthcare professionals are perceptual data. Hence future research on operational data will support significant contributions towards pathways to accept and use emerging technologies for healthcare improvement. Lastly, this study is from a developing country perspective where emerging digital healthcare technology is still emerging to support healthcare management. Hence, more investigation from other cross-country analyses of configural paths for digital technology deployment in healthcare will enhance the conversation with IoTs and BDA for healthcare management.

Holistically, the acceptance and use of healthcare technologies and platforms is not solely on their capabilities, but a combination of distinct factors driven by users' perspectives. This offers healthcare administrators and institutions to essentially reflect on the distinct combinations of conditions favourable to health professionals who can use IoTs and BDA for healthcare improvement.

This study is among the few scholarly works to empirically investigate the configural paths to support healthcare improvement with emerging technologies. Using fsQCA is a unique contribution to existing information system literature for configural paths for healthcare improvement with emerging digital technologies.

The purpose of this study is to analyse the gender wage gap (GWG) in Spain adopting a labour market segmentation approach. Once we obtain the different labour segments (or idiosyncratic labour markets), we are able to decompose the GWG into its observed and unobserved heterogeneity components.

We use the data from the Continuous Sample of Working Lives for the year 2021 (matched employer–employee [EE] data). Contingency tables and clustering techniques are applied to employment data to identify idiosyncratic labour markets where men and/or women of different ages tend to match/associate with different sectors of activity and occupation groups. Once this “heatmap” of labour associations is known, we can analyse its hottest areas (the idiosyncratic labour markets) from the perspective of wage discrimination by gender (Oaxaca-Blinder model).

In Spain, in general, men are paid more than women, and this is not always justified by their respective attributes. Among our results, the fact stands out that women tend to move to those idiosyncratic markets (biclusters) where the GWG (in favour of men) is smaller.

It has not been possible to obtain remuneration data by job-placement, but an annual EE relationship is used. Future research should attempt to analyse the GWG across the wage distribution in the different idiosyncratic markets.

Our combination of methodologies can be adapted to other economies and variables and provides detailed information on the labour-matching process and gender wage discrimination in segmented labour markets.

Our contribution is very important for labour market policies, trying to reduce unfair inequalities.

The study of the GWG from a novel labour segmentation perspective can be interesting for other researchers, institutions and policy makers.