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Aims at the structuring of an analytical tool that traces the time course of geophysical phenomena, regional or global, and compares it to that of long‐term solar conditions – long term meaning decades or centuries. The model is based on the postulate that since in a previous analysis the preponderance of atmospheric, hydrospheric, and some aspects of geospheric phenomena are powered by energy from the sun, now or in the past, the long‐term behaviour of such phenomena is ultimately “connected” to long‐term changes occurring in the sun itself. Proposes and models a stable surrogate pattern for the long‐term solar activity; introduces a transfer‐function for modelling the connection between the surrogate and terrestrial phenomena viewed as partners in the connection; and probes the connection outcome for episodic or unanticipated effects that may arise due to the fact that in the present context, the connection, should it exist, is very likely non‐linear. Presents the theory of the concept, and demonstrates its pertinence to terrestrial phenomena.

There is a growing literature in nonparametric econometrics in the recent two decades. Given the space limitation, it is impossible to survey all the important recent developments in nonparametric econometrics. Therefore, we choose to limit our focus on the following areas. In Section 2, we review the recent developments of nonparametric estimation and testing of regression functions with mixed discrete and continuous covariates. We discuss nonparametric estimation and testing of econometric models for nonstationary data in Section 3. Section 4 is devoted to surveying the literature of nonparametric instrumental variable (IV) models. We review nonparametric estimation of quantile regression models in Section 5. In Sections 2–5, we also point out some open research problems, which might be useful for graduate students to review the important research papers in this field and to search for their own research interests, particularly dissertation topics for doctoral students. Finally, in Section 6 we highlight some important research areas that are not covered in this paper due to space limitation. We plan to write a separate survey paper to discuss some of the omitted topics.

A common assertion, strongly supported by country‐specific empirical evidence, is that individual returns to investment in human capital change slowly over time. The research results reported in this paper indicate that this is not necessarily the outcome if the economy, like the Finnish one at the turn of the decade (1980/90), undergoes rapid shifts in the activity level coupled with increasing turbulence in the labour market. Not surprisingly, the changes in wage conditions are stronger within the private sector. Less expected is perhaps the finding of highly differing effects among men and women employed in the same sector.

This chapter suggests a robust Hausman and Taylor (1981), hereafter HT, estimator that deals with the possible presence of outliers. This entails two modifications of the classical HT estimator. The first modification uses the Bramati and Croux (2007) robust Within MS estimator instead of the Within estimator in the first stage of the HT estimator. The second modification uses the robust Wagenvoort and Waldmann (2002) two-stage generalized MS estimator instead of the 2SLS estimator in the second step of the HT estimator. Monte Carlo simulations show that, in the presence of vertical outliers or bad leverage points, the robust HT estimator yields large gains in MSE as compared to its classical Hausman–Taylor counterpart. We illustrate this robust version of the HT estimator using an empirical application.

This chapter analyzes markets with an “infinite variety” of goods, such as large parts of the service economy and creative industries such as the book, film, and music market. I argue that the infinite variety of supply that characterizes such markets does not lead to discoordination, because of the emergence of cognitive institutions in the form of market categories, reference points such as exemplary goods, and instruments of interpretation which facilitate the (quality) coordination process. These cognitive institutions function as an extended mind of market participants and enable what is termed interpretative rationality, as distinct from calculative rationality. This interpretative rationality consists of the ability to recognize relevant differences and similarities between goods. These cognitive institutions, like the price system, are an emergent order which can be analyzed through the lens of Austrian economics. This chapter further demonstrates the potential convergence between particular strands of economic sociology and Austrian economics.

This work aims to establish the relationship between painting art and sustainability, which allows for highlighting implications likely to improve sustainability for humanity's welfare.

To achieve this objective, painting art is measured by a composite index aggregating the quantity and quality represented by the market value. As for sustainable development, it is represented by a composite index comprising three variables: the climate change performance index (ecological dimension), the wage index reflecting distributive justice (social dimension) and the gross domestic product (economic dimension). The composite indices were determined through adjusted data envelopment analysis. In addition, two other methods are used in this work: correlation analysis and a neural network method. These methods are applied to data from 2007 to 2021 across the world.

The correlation method highlighted a perfect positive correlation between painting art and sustainability. As for the neural network method, it revealed that the quality of painting has the greatest impact on sustainability. The neural network method also showed that the most positively impacted variable of sustainability by painting art is the social variable, with a pseudo-probability of 0.90.

The relationship between painting art and sustainability is underexplored, in particular in terms of statistical analysis. Therefore, this research intends to fill this gap. Moreover, analysis of the relationship between both using composite indices computed via an original method (adjusted data envelopment analysis) and a neural network method is nonexistent, which constitutes the novelty of this work.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2023-0006

The aim of the study was to analyze the use of power in a strategic change process within a large forest industry company. The organization in question had a total of 7,700 employees, 6‐8 organizational levels, over 30 production units and a widespread international sales network. The study highlighted the organization's internal narration as an important element in the use of power. It started in conjunction with the appointment of the new management group and continued throughout the two‐year monitoring period, so that gradually all organizational layers were involved in interpreting their roles and positions in the new structure.

The empirical data were collected during a period of more than two years through participatory observation and the change narrative was made using the change report method. The use of power was observed from the perspective of the management group. The researcher had a dual role; he served both as a researcher and a member of the management group.

The first conclusion revealed that the change did not represent a separate process that was taking place outside the normal, established functioning and management process of the organization. The second conclusion was that implementing a transformative change in a large organization is a multi‐stage and challenging learning process, both for the change makers as well as for other members of the organization. The third conclusion was that there were no shortcuts to change. It took place through the thinking and actions of the people starting from the understanding of the measures required for the change.

There are three limitations to the study. First, its findings are based on the viewpoint of the new management group. Second, the role of the researcher and the episodic progress narrative edited by himself defined the change process as a five‐phased process. Third, and closely linked to the previous limitation, the possible narrowness of the researcher in his thinking is also a potential limitation.

The results of the study could pave the way to a more realistic understanding of power and change in large multinational companies.

This article is a genuine research paper with profound fieldwork. It broadens viewpoints considering power, change and the role of top management in a large and global Finnish forest industry corporation.

Some of the unique properties of distributed RC thick film components are reviewed and discussed. In particular the evolution of a method of functionally adjusting active low pass filters containing distributed RC components is presented. The use of a finite element computer programme, specially written for this work, to justify the validity of the trimming method is demonstrated. The problems remaining in the development of the technique are mentioned and the potential for overcoming them is discussed.

European performing arts companies, intrinsically fragile, have been severely hit by the economic crisis. Within the global search for new economic models in the sector, a growing number of initiatives have been taken in the form of establishing collective and participatory firms. Their forms vary from simple interorganization resource pooling to proper registration of a cooperative. Our research aims to understand the motivations of project initiators for collectively organizing their business. We test the influence of instrumental versus ideologically driven motives as well as the influence of the socio-economic context on the decisions of performing arts entrepreneurs (artists, producers, or directors) to establish participatory firms. We relate these results to the success or failure of collective firms and to the degree of cooperation. We use a qualitative method based on semi-directive interviews conducted in 21 performing arts collective organizations, over two years and in six European countries. Interviews were integrally transcripted and processed using qualitative data analysis software (QSR NVivo 10) in order to realize axial coding. We found that while the context, instrumental logic, and ideologically driven motives influence the decision to establish collective organizations in performing arts, it is the ideological dimensions that are predominant and constitute a necessary condition for the success of a participatory organization. We observe that the more collective organizations are ideologically motivated, the more they are likely to be successful in the long run (success being assimilated to economic sustainability). We also find that the greater the importance of the ideological motive, the more integrated the cooperation. Eventually, these results provide significant information regarding the form of collective firms in performing arts. We observe the emergence of new forms of cooperatives that comprise cooperatives of production and projects or companies, establishing participatory and democratic governance, and pooling resources and financial risk while preserving the artistic freedom of artists. We view these emerging types of cooperatives as a promising avenue both for the sector itself and for the development of the cooperative movement beyond its traditional sectors. The findings suggest that public incentives, as they are currently set up, may miss their objective of promoting shared practices in the arts or even be counterproductive; thus, it would be to their advantage to be modified in light of the above results. We also defend the interest of trans-border cooperative organizations inspired by the cooperatives of production and their governance models and organizations. Despite a number of studies highlighting cooperation in the cultural sector, research on cooperatives in this sector remains embryonic. This paper contributes to this literature. We argue that applied research in this sector can be of contributive value to the literature on cooperatives and participatory firms.

This chapter proposes M-estimators of a fractional response model with an endogenous count variable under the presence of time-constant unobserved heterogeneity. To address the endogeneity of the right-hand-side count variable, I use instrumental variables and a two-step procedure estimation approach. Two methods of estimation are employed: quasi-maximum likelihood (QML) and nonlinear least squares (NLS). Using these methods, I estimate the average partial effects, which are shown to be comparable across linear and nonlinear models. Monte Carlo simulations verify that the QML and NLS estimators perform better than other standard estimators. For illustration, these estimators are used in a model of female labor supply with an endogenous number of children. The results show that the marginal reduction in women's working hours per week is less as women have one additional kid. In addition, the effect of the number of children on the fraction of hours that a woman spends working per week is statistically significant and more significant than the estimates in all other linear and nonlinear models considered in the chapter.