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Our paper studies a central issue with a long history in economics: the relationship between population and economic growth. We analyze the joint dynamics of economic and demographic growth in 111 countries during the period 1960–2019.

Using the concept of economic regime, the paper introduces the notion of distance between the dynamical paths of different countries. Then, a minimal spanning tree (MST) and a hierarchical tree (HT) are constructed to detect groups of countries sharing similar dynamic performance.

The methodology confirms the existence of three country clubs, each of which exhibits a different dynamic behavior pattern. The analysis also shows that the clusters clearly differ with respect to the evolution of other fundamental variables not previously considered [gross domestic product (GDP) per capita, human capital and life expectancy, among others].

Our results indirectly suggest the existence of dynamic interdependence in the trajectories of economic growth and population change between countries. It also provides evidence against single-model approaches to explain the interdependence between demographic change and economic growth.

We introduce a methodology that allows for a model-free topological and hierarchical description of the interplay between economic growth and population.

This study aims to evaluate the effectiveness of machine learning models to yield profitability over the market benchmark, notably in periods of systemic instability, such as the ongoing war between Russia and Ukraine.

This study made computational experiments using support vector machine (SVM) classifiers to predict stock price movements for three financial markets and construct profitable trading strategies to subsidize investors’ decision-making.

On average, machine learning models outperformed the market benchmarks during the more volatile period of the Russia–Ukraine war, but not during the period before the conflict. Moreover, the hyperparameter combinations for which the profitability is superior were found to be highly sensitive to small variations during the model training process.

Investors should proceed with caution when applying machine learning models for stock price forecasting and trading recommendations, as their superior performance for volatile periods – in terms of generating abnormal gains over the market – was not observed for a period of relative stability in the economy.

This paper’s approach to search for financial strategies that succeed in outperforming the market provides empirical evidence about the effectiveness of state-of-the-art machine learning techniques before and after the conflict deflagration, which is of potential value for researchers in quantitative finance and market professionals who operate in the financial segment.

Social practices of work humor among engineering workers are a lesser studied phenomenon. We examine the social practices of an engineering work team through acts of a peculiar form of humorous expression we identify as installation humor. In these cases of installation humor, an anonymous member of the team created a temporary, inappropriate, yet neutral installation of a physical object to amuse the other members of the team. We provide three mini-cases of installation humor; these installations appeared as the team subtly resisted a managerial initiative. We contribute knowledge to the practices of engineers at work and to the practices of resistive humorous expression.

Qualitative, full-participant ethnographic research with multiple data collection methods and utilizing abductive analysis. During the data collection, one of the researchers was a full member of the engineering team.

We identified anonymous, artefact-based enactments of resistive humorous expression, which we named installation humor. We identify and describe installation humor, which occurred at the intersectionality of work and self-expression and served as momentary artefacts symbolic of engineering worker resistance in a high-tech environment.

Managerial awareness of the unfolding forms of worker-led, fleeting signals of resistance, such as acts of installation humor, would provide another dimension of perception for identifying salient signals surrounding the phenomenon of resistance to managerial-led change initiatives. Further research is needed on engineering humor in the R&D workplace to better understand the complexity and dynamics of phenomena such as worker resistance through humorous acts. We suggest future studies on forms of humor in the engineering workplace, including incidences of installation humor as they exist in other professional work environments and organizations, to understand common and shared practices across professional boundaries.

We advance and extend the understanding of humor as a social practice in the context of professional engineers in their R&D workplace and we identify humorous acts serving as a response to negative emotions (Huber, 2022) toward the organization related to a newly instated form of managerial control. This paper contributes to the studies of social practices of humor and emotions (Fine and De Soucey, 2005) in the engineering workplace (Buch and Andersen, 2013; Buch, 2016; Mazzurco et al., 2021) as unsupervised activity at work (Gabriel, 1995), with the social practice of humor adopting a non-verbal form that we identified as installation humor. We named this specific form of humor that we observed as installation humor and defined its specificity and differences from more traditional methods of humor (t. ex. Fine and De Soucey, 2005; Martin and Ford, 2018), shop floor humor (t. ex. Roy 1959), workplace humor (t. ex. Rosenberg et al., 2021) and engineering student humor (Holmila et al., 2007; Bender, 2011; Berge, 2017).The results of this study also suggest that ethnography for studying humor as a social practice is useful in identifying micro-level occurrences of unfolding engineering humor, including humor as a form of resistance.

The study of humor in high-tech engineering settings enhances the literature of engineering work (t. ex. Mazzurco et al., 2021) and emerging humorous phenomena (Jarzabkowski and Lê, 2017). This case study highlights and extends the understanding of the non-technical competencies of engineers and the role of peer-to-peer humor in the engineering workplace as a form of resistance during managerial initiatives within an organization.

The study extends and contributes new knowledge to research on emotions and humor by engineers at work, including the identification of a peculiar form of humor used by the engineers. This study also contributes to nascent research on the social practices of engineers at work. The research material was gathered as a full-member ethnography, increasing methodological knowledge of researching a site from within.

This study aims to deepen the understanding of the challenges and implications entailed by deploying mobile clinics in conflict zones to reach populations affected by violence and cut off from health-care services.

This research combines an integrated literature review and an instrumental case study. The literature review comprises two targeted reviews to provide insights: one on conflict zones and one on mobile clinics. The case study describes the process and challenges faced throughout a mobile clinic deployment during and after the Iraq War. The data was gathered using mixed methods over a two-year period (2017–2018).

Armed conflicts directly impact the populations’ health and access to health care. Mobile clinic deployments are often used and recommended to provide health-care access to vulnerable populations cut off from health-care services. However, there is a dearth of peer-reviewed literature documenting decision support tools for mobile clinic deployments.

This study highlights the gaps in the literature and provides direction for future research to support the development of valuable insights and decision support tools for practitioners.

Supply chains need to be made viable in this volatile and competitive market, which could be possible through digitalization. This study is an attempt to explore the role of Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business performance from the lens of natural resource-based view.

The study tests the proposed model using a covariance-based structural equation modelling and further investigates the ranking of each construct using the artificial neural networks approach in AMOS and SPSS respectively. A total of 234 respondents selected using purposive sampling aided in capturing the industry practices across supply chains in the UK. The full collinearity test was carried out to study the common method bias and the content validity was carried out using the item content validity index and scale content validity index. The convergent and discriminant validity of the constructs and mediation study was carried out in SPSS and AMOS V.23.

The results are overtly inferring the significant impact of Industry 4.0 practices on creating smart and ultimately sustainable supply chains. A partial relationship is established between Industry 4.0 and supply chain agility through a smart supply chain. This work empirically reinstates the combined significance of green practices, Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business value. The study also uses the ANN approach to determine the relative importance of each significant variable found in SEM analysis. ANN determines the ranking among the significant variables, i.e. supply chain resilience > green practices > Industry 4.0> smart supply chain > supply chain agility presented in descending order.

This study is a novel attempt to establish the role of digitalization in SCs for attaining sustainable business value, providing empirical support to the mediating role of supply chain agility, supply chain resilience and smart supply chain and manifests a significant integrated framework. This work reinforces the integrated model that combines all the constructs dealt with in silos so far in prior literature.

Academic literature calls for research on the impact of psychological states derived from mental illness on detrimental consumer behaviour. The purpose of this study is to assess the impact of anxiety on the consumer’s buying processes (compulsive and impulsive) and emotional regulation.

To carry out the statistical analysis, the data were obtained through an online survey (n = 726) of supermarket consumers. The treatment of the data was using partial least squares structural equation modelling (PLS-SEM).

The results obtained show that anxiety influences the generation of harmful behaviour, as it has a positive impact on compulsive and impulsive buying. In addition, compulsive and impulsive buying generate higher levels of consumers’ emotional regulation.

This study contributes to the management of anxiety as a priority element to reduce harmful behaviour. Therefore, it provides useful information for marketing managers and professionals in psychological and healthy consumer processes.

學術文獻不斷呼籲研究人員和學者去探討來自精神病的心理狀態如何產生有害的消費者行為。本研究擬評定焦慮對消費者購買流程 (強迫性購物和衝動購物) 和情緒調節所產生的影響。

為能進行統計分析,研究人員透過超級市場消費者的在線調查 (n = 726) 取得數據,繼而以結構方程 (PLS-SEM) 處理數據。

研究結果顯示,焦慮會導致有害行為的產生,這是因為焦慮對強迫性購物和衝動購物均產生積極的影響; 而且,強迫性購物和衝動購物會產生較高水平的消費者情緒調節。

本研究的貢獻在於把焦慮視為減少有害行為的優先元素而予以管理; 因此,本研究為市場經理以及於心理上的和健康的消費者進程的專業人員提供了有用的資料。

Drawing on COR theory and based on a person-centered approach, this study aims to explore profiles of both leadership behavior (transformational leadership, abusive supervision) and well-being indicators (cognitive irritation, emotional exhaustion). Additionally, we consider whether certain resource-draining (work intensification) and resource-creating factors (leader autonomy, psychological contract fulfillment) from the leaders' work context are related to profile membership.

The profiles are built using LPA on data from 153 leaders and their 1,077 followers. The relationship between profile membership and correlates from the leaders' work context is examined using multinomial logistic regression analyses.

LPA results in an interpretable four-profile solution with the profiles named (1) Good health – constructive leading, (2) Average health – inconsistent leading, (3) Impaired health – constructive leading and (4) Impaired health – destructive leading. The two groups with the highest sample share – Profiles 1 and 3 – both show highly constructive leadership behavior but differ significantly in their well-being indicators. The regression analyses show that work intensification and psychological contract fulfillment are significantly related to profile membership.

The person-centered approach provides a more nuanced view of the leadership behavior – leader well-being relationship, which can address inconsistencies in previous research. In terms of practical relevance, the person-centered approach allows for the identification of risk groups among leaders for whom organizations can provide additional resources and health-promoting interventions.