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We investigate the role of fiscal policy, through several measures of government revenues and expenditures and redistribution, on disposable and market income inequality and economic growth as well as the interaction between inequality and growth for 31 European countries from 1995 to 2019.

We use a simultaneous equations model to assess the linkage between economic growth, inequalities and fiscal policy variables.

(1) While disposable income inequality has a negative effect on all fiscal policy variables, market income inequality has a mixed effects; (2) for Eastern European countries, public consumption and direct taxation positively influence economic growth; conversely, for Western European countries, the effects are negative; (3) disposable and market income inequality have a positive effect on growth for Eastern European countries, and a negative influence on growth for Western European countries; (4) growth contributes to the increase of disposable and market income inequality for Eastern European countries; for Western European countries, the effects are opposite; and (5) fiscal policy allows for the attenuation of disposable income inequality.

The different results between the role of market and disposable income inequality levels lead us to suggest tax progressivity as an important feature to consider when analyse the trivariate relationship between inequalities, fiscal policy and growth. Furthermore, there are different dynamics between inequality and growth, and the role of fiscal policy, on both Eastern and Western European countries.

Green hospitality studies have not adequately focused on the diffusion of eco-innovative hotels amongst visitors. This study aims to fill this gap by identifying green hotel attributes that influence visitors’ adoption of eco-friendly hotel and their intentions to partake in green initiatives.

The paper uses a mixed-method approach to explore the drivers of customers’ green hotel adoption and consumption. In the qualitative phase, data were collected via 20 open-ended interviews and analyzed to derive a measurement scale. The scale was then tested through a survey comprising 500 respondents using structural equation modelling.

The study results elucidate how guests’ visit intentions and green consumption behavior is built through their perception of newness and uniqueness of eco-innovative attributes. Findings shed light on how green hotel’s sustainable communication and corporate social responsibility outreach efforts positively influence guest visit intentions.

Study results reveal perceived eco-innovativeness as an important antecedent of visit intentions. Based on guest’s preferences, green hotels striving to increase its visitors’ base could begin by expanding their eco-innovative attributes.

Contrasting previous studies that have exclusively used the theory of planned behavior constructs, this study argues that diffusion of innovation constructs also offer valuable insights into guests’ visit intentions. While existing studies have covered limited number of eco-innovative attributes, this study adds to the literature by presenting a comprehensive set of attributes including trustworthiness of communication and observability of its social impacts.

The scarcity of women in advertising creative departments has been reported globally, particularly in creative managerial roles. This study goes a step beyond this evidence since this paper aims to test whether having at least one token woman in creative managerial positions (token+) may be associated with a larger presence of females in low-level creative jobs compared to creative departments led only by male creative managers.

A content analysis of the credit forms of 839 Spanish campaigns released in 2019 was conducted to determine the gender composition of 116 creative departments with more than three professionals.

Generalized Poisson Regressions indicated that when at least a token woman is present in a creative management role within agency networks, the number of females in low-level positions doubles with respect to creative departments led only by male managers. This relation was not found for independent agencies, though. The results are discussed under the lens of critical mass theory, attraction paradigm and homophily theory.

To the best of the authors’ knowledge, it is the first time in the literature that the relation among the number of token+ advertising female creative managers and the amount of females in lower-level creative positions is tested. This research is also original because the sample is from a non-Anglo-Saxon country. Moreover, the use of the Generalized Poisson Regressions technique is another novelty of this paper.

Human brands in the music industry use self-presentation tactics on social media to manage audience impressions. This practice has led to many posts asking followers to adopt behaviors favoring the human brand. However, its effectiveness in leveraging relevant performance metrics for musicians outside social media, such as popularity in specialized media, music sales and number of contracted concerts, needs further exploration. This study aims to reveal the effect of impression management tactics conveyed on social media on the market performance of musicians’ human brands.

Secondary data research classifies 5,940 social media posts from 11 music artists into self-presentation tactics (self-promotion, exemplification, supplication and ingratiation). It shows their predictions on three market performance metrics in an annual balanced panel study.

Impression management tactics via posts on social media are mostly self-promotion, improving the musicians’ market performance by increasing the number of contracted concerts. Conversely, ingratiation generated the most positive effect on the musician’s popularity but reduced music sales. Besides lowering the musicians’ popularity, exemplification also reduced the number of contracted concerts, while the supplication had no significant effect.

To the best of the authors’ knowledge, the research is the first to use social media postings of musicians’ official human brand profiles based on self-presentation typologies as a complete impression management tool. Furthermore, it is the first to test the effects of these posts on market performance metrics (i.e. outside of social media) in a longitudinal study.

The purpose of this paper is to provide a transcript of a dialogue among literacy educators and researchers on the impact of generative aritficial intelligence (AI) in the field. In the spring of 2023, a lively conversation emerged on the National Council of Research on Language and Literacy (NCRLL)’s listserv. Stephanie initiated the conversation by sharing an op-ed she wrote for Atlanta Journal-Constitution about the rise of ChatGPT and similar generative AI platforms, moving beyond the general public’s concerns about student cheating and robot takeovers. NCRLL then convened a webinar of eight leading scholars in writing and literacies development, inspired by that listerv conversation and an organizational interest in promoting intergenerational collaboration among literacy scholars.

As former doctoral students of two of the panel participants, webinar facilitators Grace and Victoria positioned themselves primarily as learners about this topic and gathered questions from colleagues, P-16 practitioners and those outside the field of education to assess the concerns and wonderings that ChatGPT and generative AI have raised. The following webinar conversation was recorded on two different days due to scheduling conflicts. It has been merged and edited into one dialogue for coherence and convergence.

Panel participants raise a host of questions and issues that go beyond topics of ethics, morality and basic writing instruction. Furthermore, in dialogue with one another, they describe possibilities for meaningful pedagogy and critical literacy to ensure that generative AI is used for a socially just future for students. While the discussion addressed matters of pedagogy, definitions of literacy and the purpose of (literacy) education, other themes included a critique of capitalism; an interrogation of the systems of power and oppression involved in using generative AI; and the philosophical, ontological, ethical and practical life questions about being human.

This paper provides a glimpse into one of the first panel conversations about ChatGPT and generative AI in the field of literacy. Not only are the panel members respected scholars in the field, they are also former doctoral students and advisors of one another, thus positioning all involved as both learners and teachers of this new technology.

This study considers the “technology creation” characteristic of technical knowledge-intensive business services (T-KIBS) and examines how human capital and intellectual property rights (IPR) protection affect the location choice of foreign direct investment (FDI) in China for two types of T-KIBS: (1) information transmission, software and information technology (ICT) services and (2) scientific research and technology (SCI) services.

Our empirical analysis is based on panel data on 22 Chinese provinces from 2009 to 2017. We use the generalized method of moments estimation for the regression analysis.

FDI in ICT services prefers regions with high human capital, while FDI in SCI services favors regions with good IPR protection.

Future research could use more comprehensive data and qualitative interviews to enhance the findings.

These findings provide a foundation for China’s future policy on attracting FDI into T-KIBS, especially in areas related to human capital and IPR protection.

This study bridges the research gap on the FDI location choice of T-KIBS in China by clarifying the influences of human capital and IPR protection and providing theoretical support for the location choice of T-KIBS FDI.

China’s foreign aid efforts in Africa remain contentious. Chinese foreign aid tends to be different from “traditional” development assistance in that it frequently involves firms as the implementing agents of projects. Firms bring unique resources to public–private partnerships (PPPs) formed with government agencies, but their possible self-interested nature also gives rise to concerns over their development impact. Yet, on a larger scale, little is known about the characteristics of Chinese PPPs in foreign aid. Using project-level data available for 1,308 Chinese aid projects in 50 countries across Africa, the author characterizes the projects undertaken by firms and government agencies in a PPP and contrasts them to those executed by Chinese government agencies without firm involvement. This exploratory data analysis suggests that important differences apply, as Chinese PPPs tend to target different sustainable development goals (SDGs), work on the basis of distinct aid conditions, and implement projects that tend to be larger than those that are solely run by government agencies. Such observations raise important questions of an ethical, theoretical, and international nature, and warrant further research. The author develops a research agenda that aims at issues particularly important for business ethics scholars, organization theorists, and international business scholarship.

A semiparametric stochastic frontier model is proposed for panel data, incorporating several flexible features. First, a constant elasticity of substitution (CES) production frontier is considered without log-transformation to prevent induced non-negligible estimation bias. Second, the model flexibility is improved via semiparameterization, where the technology is an unknown function of a set of environment variables. The technology function accounts for latent heterogeneity across individual units, which can be freely correlated with inputs, environment variables, and/or inefficiency determinants. Furthermore, the technology function incorporates a single-index structure to circumvent the curse of dimensionality. Third, distributional assumptions are eschewed on both stochastic noise and inefficiency for model identification. Instead, only the conditional mean of the inefficiency is assumed, which depends on related determinants with a wide range of choice, via a positive parametric function. As a result, technical efficiency is constructed without relying on an assumed distribution on composite error. The model provides flexible structures on both the production frontier and inefficiency, thereby alleviating the risk of model misspecification in production and efficiency analysis. The estimator involves a series based nonlinear least squares estimation for the unknown parameters and a kernel based local estimation for the technology function. Promising finite-sample performance is demonstrated through simulations, and the model is applied to investigate productive efficiency among OECD countries from 1970–2019.

Environmental degradation resulting from human activities may adversely affect human health in multiple ways. Until now, policies aimed at mitigating environmental problems such as climate change, environmental pollution and damage to biodiversity have failed to clearly identify and drive the potential benefits of these policies on health. The conducted study assesses and demonstrates how specific environmental policies and instruments influence perceived human health in order to ensure input for a data-driven decision process.

The study was conducted for the 2004–2020 period in European Union (EU) countries with the use of dynamic panel data modeling. Verification of specific policies' impact on dependent variables allows to indicate this their effectiveness and importance. As a result of the computed dynamic panel data models, it has been confirmed that a number of significant and meaningful relationships between the self-perceived health index and environmental variables can be identified.

There is a strong positive impact of environmental taxation on the health index, and the strength of this relationship causes effects to be observed in the very short term, even the following year. In addition, the development of renewable energy sources (RES) and the elimination of fossil fuels from the energy mix exert positive, although milder, effects on health. The reduction of ammonia emissions from agriculture and reducing noise pollution are other health-supporting factors that have been shown to be statistically valid. Results allow to identify the most efficient policies in the analyzed area in order to introduce those with the best results or a mix of such measures.

The results of the authors' research clearly indicate the health benefits of measures primarily aimed at improving environmental factors, such as environmental taxes in general. The authors have also discovered an unexpected negative impact of an increase in the share of energy taxes in total taxes on the health index. The presented study opens several possibilities for further investigation, especially in the context of the rapidly changing geopolitical environment and global efforts to respond to environmental and health challenges. The authors believe that the outcome of the authors' study may provide new arguments to policymakers pursuing solutions that are not always easily acceptable by the public.

China's Belt and Road Initiative (BRI) is the most ambitious investment strategy for infrastructural development belonging to the significant potential for stimulating regional economic growth in Asia, Europe and Africa. This study aims to investigate the impact of infrastructure on spurring inward foreign direct investment (FDI) within the purview of human capital, GDP per capita, foreign aid, trade, domestic investment, population and institutional quality in BRI countries.

In doing so, the authors analyze panel data from 2000 to 2019 within the framework of the system generalized method of movement (GMM) approach for 66 BRI countries from Europe, Asia, Africa and the Middle East.

The investigated results demonstrate that aggregate and disaggregate infrastructure indices, e.g. transport, telecommunications, financial and energy infrastructures, are the driving forces in attracting foreign direct investment (FDI) in the BRI countries. In addition, control variables (i.e. institutional quality, human capital, trade, domestic investment, foreign aid and GDP per capita) play an essential role in spurring FDI inflows.

The authors’ study uniquely investigates both the pre- (2000–2012) and post- (2013–2019) BRI scenarios using the aggregate and disaggregate infrastructural components from the perspectives of full and clustered sample regions, such as Asia, Europe, Africa and the Middle East. The study provides several policy implications.