Macro-level Analysis Research Articles

Workplace democracy and democratic legitimacy in Europe

This study investigates the political spillover and stealth democracy hypotheses as complementary mechanisms to account for any relationship between workplace democracy and democratic legitimacy in Europe from micro (employee-level) and macro (country-level) perspectives. The results from the micro-level analyses reveal that neither workplace democracy nor self-reported membership in trade unions has any direct impact on democratic legitimacy; rather, past union membership produces a negative impact. However, the effect of workplace democracy on democratic legitimacy becomes salient only when mediated by job satisfaction and political interest. On the other hand, the macro-level analysis demonstrates that union density, a measure of workplace democracy at the country level, plays a significant role in explaining democratic legitimacy. The relevance of union density may indicate that employees wish to keep democratic institutions in check by recruiting into the trade unions and applying legal and mobilizational pressure on the mainstream political institutions.

The effect of financial soundness variables on bank performance: a macro-level analysis in MSCI Emerging Market Index countries

PurposeThe present study investigates the impact of financial soundness variables on bank performance in emerging countries.Design/methodology/approachThis study uses macro-level panel data from 17 countries from 2011 to 2020. The analysis adopts six models. While four models include bank profitability, the dependent variable of the other models is Bank Z Scores. Regulatory Capital to Risk-Weighted Assets, Liquid Assets to Total Assets, Non-Performing Loans to Total Gross Loans and Non-Interest Expenses to Gross Income are proxies of financial soundness variables.FindingsThe authors estimate fixed and random effects models with the Arellano, Froot and Rogers methods. Empirical results show that Non-Performing Loans to Total Gross Loans harm ROA and ROE. Regulatory Capital to Risk-Weighted Assets negatively affects ROE. Non-Interest Expenses to Gross Income on Bank Z Scores have a significant and negative effect. Moreover, Inflation, Foreign Direct Investment and GDP are macroeconomic variables that increase bank profitability.Originality/valueThis study contributes to the literature in different aspects. The first is the model of the study. The authors contribute to the literature regarding the variables used to measure financial soundness. Secondly, emerging countries are samples in the study. A significant part of the studies on financial soundness has focused on developed countries. Finally, the authors analyze the macro-level data. Bank soundness studies mainly investigate country-level variables. Macro-level analysis may provide an advantage in combating global financial crises.

When injured product users may also stay satisfied: A macro-level analysis

Product-harm crises literature has mostly studied product user harm proxies i.e., risk of injury or fictitious crises. Our macro-level study is the first to determine the consequences of actual non-automobile product-related injuries on customer satisfaction. We leverage a dataset statistically representative of injuries reported at over 5,000 U.S. hospitals. Employing the expectation-disconfirmation paradigm, we study 800 product categories, 52 industries and 30 injury diagnoses to find that severe product-related injury (SPI), on average, hurts customer satisfaction. Our research reveals that varying types of consumers’ expectations can result in asymmetric effects. Consumer sentiment and future growth may set varying boundary conditions for product users’ expectations; while higher consumer sentiment is found to worsen the association between SPI and customer satisfaction, future economic growth attenuates that relationship. Also, the type of hospital may help account for consumers’ disconfirmation of product beliefs, as it is found to improve the negative effect of SPI.

Closer than ever: Growing business-level connections between Australia and Europe

Despite the growing presence of European firms in Australia and vice versa, studies of these business-level connections have been few and far between. Building on points made in our earlier macro-level analysis of Australian-European relations, this study examines business-to-business and business-to-consumer activity at the micro-level between the two continents.We focus on three themes illustrative of these growing business-level relations. First, we examine the different pathways taken by Australian businesses in their quest to develop a European market presence. Second, we discuss instances of business and technological innovation in the Australian context, including stories of success in digital innovation and university-corporate collaboration as well as cautionary tales for European institutions arising from the Australian experience. Third, we compare and contrast how Australian and European businesses have responded to the challenge of climate change, focussing on the issues of green lending and retail insurer performance.In foregrounding these three themes, we offer reflections on the implications and lessons for the growing number of businesses operating across both continents.

Determinants of Maternal Mortality in Southern Africa: A Macro-Level Analysis

This study sought to investigate the macro determinants of maternal mortality in Southern African Development Community (SADC) states. The study drew on the fact that maternal mortality remains a major public health issue in developing countries. The Millennium Development Goals (MDGs) were adopted by UN member states in 2000, and one of them was to reduce maternal deaths by three-quarters by 2015. While the Millennium Development Goals increased efforts, the goal was not met in the countries with the highest death rates. The World Health Organisation (WHO) estimates that every single day about 810 women die from pregnancy or childbirth-related complications around the world. This is despite several international initiatives being adopted to reduce maternal mortality. The study was quantitative, and it used secondary data to achieve its objective. A panel data estimation (Generalized Method of Moments) covering the period from 2005–2019 was used to examine how various factors affect maternal mortality. The analysis included the following variables: education, fertility, GDP per capita, institutional quality, health expenditure and HIV infection. The econometric analysis reveals a significant positive impact of fertility, GDP per capita and HIV on maternal mortality. This implies that when fertility, GDP per capita and HIV are increasing, maternal mortality also increases. The analysis also showed that education has a negative relationship with maternal mortality. This implies that when literacy levels (education) increase, maternal mortality decreases. Based on the results, this study emphasizes that, in order to improve maternal health and consequently reduce maternal mortality, access to family planning (to reduce fertility), access to early prenatal care and promoting women’s access to education should be a priority in government policies.

Editorial Introduction: Contributing to the policy process literatures

Editorial Introduction: Contributing to the policy process literatures

Implications of utilization shifts of marine fish in India: a macro-level empirical analysis

Implications of utilization shifts of marine fish in India: a macro-level empirical analysis

Flow Characterization in Triply Periodic Minimal Surface (TPMS)-Based Porous Geometries: Part 1—Hydrodynamics

The modeling of flow and heat transfer in porous media systems has always been a challenge, and the extended Darcy transport models are used for macro-level analysis. However, these models are subjected to the limitations depending upon the porous geometry such as pore size, pore type, effective porosity, tortuosity, permeability, and the flow characteristics. The forced convective flow of an incompressible viscous fluid through a channel filled with four different types of porous geometries constructed using the Triply Periodic Minimal Surface (or TPMS) model is presented in this study. Four TPMS lattice shapes, namely Diamond, I-WP, Primitive, and Gyroid, are created with same volume fraction of solid subdomain as 0.68 (or void fraction as 0.32). Using different configurations for the solid subdomain by treating it as (a) solid, (b) fluid, and (c) porous zone, three different classes of porous structures are further generated for each TPMS lattice. The present study is executed with the objective to investigate the effect of shape–morphology, tortuosity, microporosity, and effective porosity on permeability and inertial drag factor. A pore-scale direct numerical simulation approach is performed for the first two types of porous media by solving the Navier–Stokes equations. The specific microporosity is quantitatively induced in the solid subdomain where Darcy–Forchheimer equation is solved, whereas the Navier–Stokes equations are solved for the void subdomain in the third type of porous media. The results reveal that Darcy flow regime exists up to the mean velocity value of U < 0.0025 m/s (Re < 10) for all the cases discussed here, and it deviates at the higher mean velocity. The conductance to the flow shown by Darcy number has the maximum and minimum values for the Primitive Type 2 and I-WP Type 1 cases. The inertial drag coefficient is minimum in Diamond lattice and maximum in Primitive lattice at lower porosity (0.32), while Primitive lattice has minimum and I-WP lattice has maximum value of inertial drag coefficient for higher porosity (~ 1).

Death Inequality During the First Year of Life in Morocco: A Macro Level Analysis

Disparities in child mortality are a reality in Morocco. These disparities coexist with inequalities in: (i) the availability of primary health care (PHCs); (ii) the socioeconomic status of the population as reflected by the prevalence of various forms of poverty; as well as (iii) fertility levels (TFRs) and the status of women in literacy and employment rates. Despite its limitations, this research provides a macro-level understanding of the link between infant mortality and a range of aggregates (political, economic, social and demographic).The metadata collected in the 2014 census (RGPH-2014) RGPH-2014 was used to construct a provincial proxy indicator of infant mortality by area of residence.This is considered as a dependent variable that we have tried to explain by the above-mentioned indicators. This is considered as a dependent variable that we have tried to explain by the above-mentioned indicators. The latter indicators reflect the socio-economic conditions prevailing in each of the provinces by area of residence. In addition, they give information on the availability of basic health services and on the woman's status. A key finding is that the level of current fertility as measured by the TFR negatively affects child survival. With a statistically significant regression coefficient of 2.912 (Pvalue =0.000), it can be argued that high fertility increases the risk of infant mortality. In turn, the prevalence of overall poverty also has a statistically significant effect on infant survival (β= -0.213 with a pvalue =0.029).

Leadership in the Context of Corporate and Employee Social Responsibility in the Czech Company

Nowadays CSR research concentrates mainly on the macro-level analysis of the phenomena connected to CSR. However, differences exist among the members of stakeholder groups concerned with CSR, which can cause different results in implementing CSR strategies, it is crucial to study CSR also on the individual (micro) level. The article aims to analyse the Czech brewery’s corporate and employee social responsibility in the context of leadership. Several studies reveal how important ethical leadership is because it can affect not only organizational culture, which fosters employee commitment to corporate values but also the range of CSR activities, individuals’ engagement and participation. The authors of these studies stress the importance of ethical leadership, managers' encouragement, and supervisors' attitude toward the topic. The method chosen for the research is the micro-level analysis of employee perceptions, reactions, and attitudes towards the company's CSR together with their determinants. The model of psychological micro-foundations and the ESR-CSR congruence model are used. We opted for semi-structured interviews to gain in-depth and detailed inside into the thinking and perceiving of 13 administrative employees of the company. The coding and content analysis of the respondents' testimonies was conducted in the program MAXQDA. We found amongst our respondents, who represent the group of administrative employees of the Czech brewery, that the most important determinant of their CSR engagement was corporate socialization. Many of the respondents engaged in CSR activities that were related to their job. Therefore, we found room for improvement in the extra-role CSR participation of administrative employees, but also in the encouragement from the part of their supervisors. The chosen group of employees framed their CSR perceptions by trying to look at the issue from the point of view of different stakeholders. They saw the sense of doing CSR in the need for sustainability, and a positive for the company is that these employees regarded its CSR as authentic. We found mainly positive CSR reactions on the side of respondents, such as job satisfaction, organizational pride, or job pursuit intention.

Representación del colectivo LGBT+ en la ficción televisiva española contemporánea (2015-2020)

La investigación examina la construcción de personajes LGBT+ en la ficción seriada española incluida en plataformas de distribución en la última década. Se utiliza un análisis crítico del discurso articulado en un nivel macro, donde se estudian los grandes discursos, y en un nivel micro, donde se presta atención a las temáticas, la lexicalización y las estructuras proposicionales. Los resultados muestran, entre otros, la perpetuación de estereotipos recurrentes, la ubicación marginal de estos personajes y que la construcción de la realidad LGBT+ se presenta de manera negativa o ambigua.

Is the American Public Really Turning Away from Democracy? Backsliding and the Conceptual Challenges of Understanding Public Attitudes

Recent scholarship has warned that the American public is turning away from democracy, with many focusing on the role of polarization in driving these trends. While these studies devote a great deal of attention to conceptualizing and measuring polarization, however, there is much less attention to the concept of democracy itself. As a result, they encounter several problems: First, lack of attention to the categorical and contextual differences between various democratic transgressions can lead to misleading findings. Second, slippage between macro and micro level analysis of backsliding can make it difficult to draw solid inferences about attitudes. Finally, lack of attention to contestation within the concept of democracy obscures a different kind of regime contention reflected in public attitudes. These problems confound efforts to understand whether the American public is truly turning away from democracy and point to the need for greater collaboration among scholars from different intellectual traditions and methodological orientations.

A Study of Femicide in Turkey From 2010 to 2017

This paper presents a Turkey-wide analysis of 1,000 femicide cases, collected from 100 newspapers between 2010 and 2017. The study seeks to contribute to the international femicide literature by highlighting the background and reasons for these murders, as characterized by the newspapers. The methodology involved frequency and chi-square analysis of the data retrieved from 100 newspapers collected from the homepage of kadincinayetleri.org. The study reveals that a woman’s intimate partner is the perpetrator in the highest number of femicide cases. The most common motives for femicides in international micro-level studies are (1) possessiveness and jealousy and (2) loss, separation, or divorce. The present study found these to be the first- and third-highest motives for femicide in Turkey. The motives of femicides can be interpreted in the macro-level analysis as women’s resistance to men’s domination; their demand for control over women escalates to murdering the woman as a form of backlash.

Ghosts and the haunting of the American dream: The pragmatics of stance and suspense in making the improbable sound possible

This paper analyzes the discourse of 19 episodes from Seasons 1 and 2 of “Paranormal Survivor,” a reality TV show about ghosts, haunted property, eeriness, fear, dread, and relief. Using various approaches to discourse analysis and multimodal discourse analysis we uncover the macro-, meso, and micro-level patterns of meaning creation in “Paranormal Survivor” that relate dually to the affective/psychological/sensory experiences of the protagonists as well as the cognitive puzzles, doubts, and (un)certainties underlying such paranormal phenomena. The macro-level analysis relates to the narrative structure of the program delivered through achronological multi-party perspectives, reflecting varying levels of emotional intensity/objectivity. The meso-level uncovers the various coherently related themes underlying the program. The micro-level examines the smaller bits of discourse that combine as they build the meso- (thematic) and macro- (structural) components of the larger spates of discourse through affect, emotion, believability, evidence, and empathy. This three-tiered analytic approach serves to systematically reveal the ways in which discursive mechanisms combine to enhance suspense, intensify horror, bolster both believability and relatability, and ultimately seek to establish and augment audience engagement.

Magnetic Resonance Imaging Studies of Neurodegenerative Disease: From Methods to Translational Research.

Neurodegenerative diseases (NDs) have become a significant threat to an aging human society. Numerous studies have been conducted in the past decades to clarify their pathologic mechanisms and search for reliable biomarkers. Magnetic resonance imaging (MRI) is a powerful tool for investigating structural and functional brain alterations in NDs. With the advantages of being non-invasive and non-radioactive, it has been frequently used in both animal research and large-scale clinical investigations. MRI may serve as a bridge connecting micro- and macro-level analysis and promoting bench-to-bed translational research. Nevertheless, due to the abundance and complexity of MRI techniques, exploiting their potential is not always straightforward. This review aims to briefly introduce research progress in clinical imaging studies and discuss possible strategies for applying MRI in translational ND research.

The network nature of language endangerment hotspots

Language endangerment is one of the most urgent issues of the twenty-first century. Languages are disappearing at unprecedented rates, with dire consequences that affect speaker communities, scientific community and humanity. There is impetus for understanding the nature of language endangerment, and we investigate where language endangerment occurs by performing network analysis on 3423 languages at various levels of risk. Macro-level analysis shows evidence of positive assortative mixing of endangerment statuses—critically endangered languages are surrounded by similarly endangered languages, indicating the prevalence of linguistic hotspots throughout the world. Meso-level analysis using community detection returned 13 communities experiencing different levels of threat. Micro-level analysis of closeness centrality shows that more geographically isolated languages tend to be more critically endangered. Even after accounting for the statistical contributions of linguistic diversity, the structural properties of the spatial network were still significantly associated with endangerment outcomes. Findings support that the notion of hotspots is useful when accounting for language endangerment but go beyond that to establish that quantifying spatial structure is crucial. Language preservation in these hotspots and understanding why endangered languages pattern the way they do in their environments becomes more vital than ever.

Macro-level literature analysis on pedestrian safety: Bibliometric overview, conceptual frames, and trends

Due to the high volume of documents in the pedestrian safety field, the current study conducts a systematic bibliometric analysis on the researches published before October 3, 2021, based on the science-mapping approach. Science mapping enables us to present a broad picture and comprehensive review of a significant number of documents using co-citation, bibliographic coupling, collaboration, and co-word analysis. To this end, a dataset of 6311 pedestrian safety papers was collected from the Web of Science Core Collection database. First, a descriptive analysis was carried out, covering whole yearly publications, most-cited papers, and most-productive authors, as well as sources, affiliations, and countries. In the next steps, science mapping was implemented to clarify the social, intellectual, and conceptual structures of pedestrian-safety research using the VOSviewer and Bibliometrix R-package tools. Remarkably, based on intellectual structure, pedestrian safety demonstrated an association with seven research areas: “Pedestrian crash frequency models”, “Pedestrian injury severity crash models”, “Traffic engineering measures in pedestrians’ safety”, “Global reports around pedestrian accident epidemiology”, “Effect of age and gender on pedestrians’ behavior”, “Distraction of pedestrians”, and “Pedestrian crowd dynamics and evacuation”. Moreover, according to conceptual structure, five major research fronts were found to be relevant, namely “Collision avoidance and intelligent transportation systems (ITS)”, “Epidemiological studies of pedestrian injury and prevention”, “Pedestrian road crossing and behavioral factors”, “Pedestrian flow simulation”, and “Walkable environment and pedestrian safety”. Finally, “autonomous vehicle”, “pedestrian detection”, and “collision avoidance” themes were identified as having the greatest centrality and development degrees in recent years.

Улс төрийн дискурс судалгаанд тм аргыг ашиглах нь буюу орчин үеийн чиг хандлага

Text mining as an approach, referred to a text data mining, is the text analytics process of normalizing, integrating and grouping big data information including free (unstructured) texts and speeches unto the well-organized schematic models according to the research made by Cutting, 1992. Thus it is developed more in exploring text analysis, armed with Artificial intelligence, Natural learning process and other computational statistics applied in natural language as the mathematical approaches, Hearst (1999). Currently TM is used as the statistical tool approaches based on the key words which make mental model of the texts in discourse. One example is IBM’s Watson (Upbin, 2013). Further, with the support of TM algorithm, it is highly advantage of deriving important databases by its value from both texts and speeches with the methods such as sentiment analysis, clustering, figuring texts into images, macro structure and mental modelling in discourse of linguistic. Therefore, text mining is interdisciplinary manner approaches for data analysis, information processing, categorization in combination of mathematical statistics and linguistic analysis. To be collecting statistic databases, analyzing topic models, creating language model under the text mining approach, it brings us the specific characteristics of linguistics as text mining is to allow tounderstand the texts in different levels such as sentence, proposition, paragraph, context, idea of the whole discourse and to pre-calculate relations in between ideas and key and chosen words of the speakers. Text mining is also used for allocating, sub-parting and grouping the data into structured models of key concepts. Specifically, in linguistics, the text mining is importantly advised to release the same thought data the same as human language understands and processes. Another significance of the text mining, it works very well when variety different types of documents and data in various types including verbal and nonverbal through the language use are observed and created in semantic network which is fundamental upon to the topic concepts. The semantic network and nodes in key words is worthwhile to calculate correlations in between words’ meanings and values of the key expressions in the context of the discourse. With this advantage, this paper is explored the opportunities on how to parallel research on the political discourse and its global concepts and macro structures in the way the speakers choose the appropriate language and how they express their ideas, ideologies, political positions, implications, speech trends, and emotions in words-one hand, it is analyzed by the researcher’s view and other hand, NLP, ML, IA algorithms and mathematical statistics are used for collecting research data and mapping the superstructure and imaging global concepts and discourses-are in need of macro level analysis of discourse. And all the results from comprehensive method and TM approaches are re-proved according to the reliability of the analysis through the quantitative and qualitative analysis.

Scoping the state of the sharing economy and its antecedents at the country level: Cross-country differences in Europe

Recent technological advances have contributed to the rise of a new economic paradigm, the so-called sharing economy (SE), where peer-to-peer digital platforms allow individuals to temporarily share their assets. It has involved several industrial sectors generating significant economic impacts worldwide and attracting interest of the academic community. Much emphasis has been put on studying the conditions affecting its growth or establishment. However, these studies have been focused on one or few sectors, or on specific platforms. Moreover, most studies have mainly investigated factors affecting the participation in these platforms at the individual (i.e., user) level even if it has been hinted that the institutional context (i.e., cities or countries) may also affect the state of a SE model. As a result, there is much knowledge about micro-level factors explaining the state of SE, but a comprehensive macro-level analysis is still overlooked. Thus, we aim to fill this gap by performing an empirical analysis on European countries to scope the state of SE and its institutional antecedents.

Managing Supply Chain Complexity and Sustainability: The Case of the Food Industry

Consumer demand for organic products, rapidly growing urbanizations levels requires the food supply chain to reduce lead-time and maintain higher product quality. For the food supply chain to cope with the raising issues an e-commerce type of supply chain must be implemented. This approach creates challenges for supply chain, because the food industry must shift towards high variety and low quantity freight forwarding with multiple delivery points. The methodology of the paper consists of scientific literature analysis and macro indicator clustering. The author of the paper proposes a supply chain management framework, which is grounded through complexity theory. The framework mainly consists of 3 characteristics, which organizations should operationalize to maintain system resilience and which in the long-run would evolve to sustainable development–capabilities, collaboration, complexity management. The proposed framework defines how operational and tactical levels should be automated through cyber-physical systems, while the automation should be controlled through strategic level variables. The macro level analysis of existing EU markets of the food industry has been conducted to identify the food industry’s contingencies, in which an agent-based model will be used to validate the proposed framework. Main 3 clusters were identified, which number was chosen based on the elbow method and validated with the silhouette score of 0.749. The food industry can be categorized in to developing, underdeveloped, and developed food industries. Moreover, singularities of different contingencies have been identified which considers population size, population density, market size of the food industry and disruption intensity. The application of the framework depends on the identified contingencies. From strategic level the SCMF is similar in all contingencies, however, depending on the type of market, more emphasize on vehicle routing or demand forecasting should be made.