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The objective of this study is to examine developments in the discursive practice of non-financial reporting in the public healthcare sector. In doing so, the authors investigate how the main reform foci of productivity and quality are represented, with a specific focus on the patient.

Drawing on critical discourse analysis (CDA), the authors conduct a longitudinal study (2007–2018) of healthcare reporting foci across the five administrative regions responsible for public hospitals in Denmark. The study analyses sixty annual reports and draws on contemporary reform documents over this period. CDA enables a micro-textual analysis, combined with macro-insights and discussions on social practice.

The findings show complex webs of presentation strategies, but in particular two changes occur during the period. First, the patient is centred throughout but the framing changes from productivity and waiting lists to quality and dialogue. Second, in the first years, the regions present themselves as actively highlighting financial and quality concerns, which changes to a passive and indirect form of presentation steered by indicators and patient legislation enforced by central government. This enhances passivity and distance in healthcare regional non-financial reporting where the regions seek to conform to such demands. Simultaneously, however, the authors find a tendency to highlight very different local initiatives, which shows an attempt to go beyond a pure automatic mode of reporting found in earlier studies.

Responding to the literature on both healthcare and financial reporting, this study identifies novel links between micro-level texts and macro-level social practices, enabling insights into the potentially intertwined impacts of public-sector reporting. The authors offer insights into the complexity of the construction of non-financial reporting in the public sector, which has a wider impact and different intentions than private-sector reporting.

The purpose of this paper is to unearth various dimensions of employee experience (EX) and explore how pandemic impacted various EX factors using online employee reviews. The authors identify employee-discussed EX-factors and quantify the associated sentiments and importance.

This paper employs Latent Dirichlet Allocation on the online employee reviews to identify the key EX-factors. The authors probe sentiments and importance associated with key EX-factors using sentiment analysis, importance analysis, regression analysis and dominance analysis.

The result of topic modeling identifies 20 EX-factors that shape overall EX. While skill development plays a major role in shaping overall EX, employees perceived Salary and Growth as the most important EX-factor and expressed negative sentiments during the pandemic. Employee sentiments significantly influence overall EX.

When employees have extensive change experience, managers should consider various facets of EX to manage the smooth change and deliver a better EX. This research offers key EX-factors to be considered by managers while dealing with employees. Online employee reviews websites are recommended to include the identified key EX-factors to comprehend the holistic EX.

This study contributes to the growing literature on the employee experience as a concept by identifying various EX-factors. The authors expand the extant EX scales by identifying an inclusive and updated set of EX-factors.

Given the critical role of user-generated content (UGC) in e-commerce, exploring various aspects of UGC can aid in understanding user purchase intention and commodity recommendation. Therefore, this study investigates the impact of UGC on purchase decisions and proposes new recommendation models based on sentiment analysis, which are verified in Douban, one of the most popular UGC websites in China.

After verifying the relationship between various factors and product sales, this study proposes two models, collaborative filtering recommendation model based on sentiment (SCF) and hidden factors topics recommendation model based on sentiment (SHFT), by combining traditional collaborative filtering model (CF) and hidden factors topics model (HFT) with sentiment analysis.

The results indicate that sentiment significantly influences purchase intention. Furthermore, the proposed sentiment-based recommendation models outperform traditional CF and HFT in terms of mean absolute error (MAE) and root mean square error (RMSE). Moreover, the two models yield different outcomes for various product categories, providing actionable insights for organizers to implement more precise recommendation strategies.

The findings of this study advocate the incorporation of UGC sentimental factors into websites to heighten recommendation accuracy. Additionally, different recommendation strategies can be employed for different products types.

This study introduces a novel perspective to the recommendation algorithm field. It not only validates the impact of UGC sentiment on purchase intention but also evaluates the proposed models with real-world data. The study provides valuable insights for managerial decision-making aimed at enhancing recommendation systems.

Taking advantage of distinctive text-based measures of climate policy uncertainty and firm-specific exposure to climate change, this study aims to examine the impact of firm-specific vulnerability on dividend policy.

To mitigate endogeneity, the authors apply an instrumental-variable analysis based on climate policy uncertainty as well as use additional analysis using propensity score matching and entropy balancing.

The authors show that an increase in climate policy uncertainty exacerbates firm-specific exposure considerably. Exploiting climate policy uncertainty to generate exogenous variation in firm-specific exposure, the authors demonstrate that companies more susceptible to climate change are significantly less likely to pay dividends and those that do pay dividends pay significantly smaller dividends. For instance, a rise in firm-specific exposure by one standard deviation weakens the propensity to pay dividends by 5.11%. Climate policy uncertainty originates at the national level, beyond the control of individual firms and is thus plausibly exogenous, making endogeneity less likely.

To the best of the authors’ knowledge, this study is the first attempt in the literature to investigate the effect of firm-specific exposure on dividend policy using a rigorous empirical framework that is less vulnerable to endogeneity and is more likely to show a causal influence, rather than a mere correlation.

This paper aims to analyze the impact of tax digitalization, focusing on artificial intelligence (AI), machine learning and blockchain technologies, on enhancing tax compliance behavior in various contexts. It seeks to understand how these emerging digital tools influence taxpayer behaviors and compliance levels and to assess their effectiveness in reducing tax evasion and avoidance practices.

Using a systematic review technique with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses method, this study evaluates 62 papers collected from the Scopus database. The papers were analyzed through textometry of titles, abstracts and keywords to identify prevailing trends and insights.

The review reveals that digitalization, particularly through AI and blockchain, significantly enhances tax compliance and operational efficiency. However, challenges persist, especially in emerging economies, regarding the adoption and integration of these technologies in tax systems. The findings indicate a global trend toward digital Tax Administration 3.0, emphasizing the importance of regulatory frameworks, capacity building and simplification for small and medium enterprises (SMEs).

The findings provide guidance for policymakers and tax administrations, underscoring the necessity of strategic planning, regulatory backing and global cooperation to effectively use digital technologies in tax compliance. Emphasizing the need for tailored support for SMEs, the study also calls for expanded research in less represented areas and specific sectors, such as SMEs and developing economies, to deepen global insights into digital tax compliance.

This study has attempted to fill the gap in the literature on the comprehensive impact of fiscal digitalization, particularly AI-based, on tax compliance across different global contexts, adding to the discourse on digital taxation.

This paper studies the Digital Service Innovation (DSI) concept by systematically reviewing earlier studies from various scholarly communities. This study aims to recognize how recent advances in DSI literature from different research streams complement and can be incorporated into the growing digital servitization literature to define better and understand DSI.

After systematically identifying 123 relevant articles, this study employed complementary methods, such as author bibliographic coupling, linguistic text mining/textual analysis and qualitative content analyses.

This paper first maps the intellectual structure and boundaries of the DSI-related communities and qualitatively assesses their characteristics. These communities are (1) Innovation for digital servitization, (2) Service innovation in the digital age and (3) Adoption of novel e-services enabled by information system development. Next, the composition of the DSI concept is examined and depicted to comprehend the notion's critical dimensions. The findings discuss the range of theories and methods in the existing research, including antecedents, processes and outcomes of DSI.

This study reviews, extends the understanding of origins and critically evaluates DSI-related research. Moreover, the paper redefines and clarifies the structure and boundaries of the DSI-concept. In doing so, it elaborates on the substance of DSI and identifies the essential themes for its understanding and conceptualization. Thus, the study helps the future development of the concept and allows knowledge accumulation by bridging adjacent research communities. It helps researchers and managers navigate the foggy emerging research landscape.

The authors study the effect of increasing environmental awareness on shareholders' activism. Specificallly, this study aims to examine whether growing environmental awareness is reflected in more aggressive environmental shareholder proposals.

This study uses the 2010 Deepwater Horizon oil spill disaster as an exogenous event that increased shareholders' environmental awareness. This study analyzes the spill’s effect on the tone of proposals about environmental issues and nonenvironmental topics.

After the disaster, the tone of environmental proposals (i.e. the treatment group) is significantly more negative. In contrast, the tone of nonenvironmental proposals (i.e. the control group) is unaffected. This study interprets this finding as direct evidence that the oil spill led to increased shareholder environmental activism through proposals that targeted the environmental risks surrounding the business more aggressively. By contrast, this study finds no effect of the oil spill on the tone of managers' responses to the proposals, consistent with managers refraining from emphasizing environmental threats.

Anecdotal evidence and recent studies suggest a link between environmental disasters and shareholder pressure for corporate change. However, no prior research has investigated the channel through which shareholders could have exerted such pressure or has looked for direct evidence of it in the negotiations between shareholders and managers. By finding such evidence in shareholder proposals, this study fills in this gap.

The authors explore how the sentiment expressed by emojis in comments on stocks is associated with the stocks' subsequent returns.

By applying our own analyzer, the authors find a sentiment effect of emojis on stocks returns separately to the plain text-expressed sentiment in Reddit posts about meme stocks such as Gamestop during the Covid-19 pandemic.

The authors document that a one-standard deviation change in emoji sentiment magnitude measured as the quantity of positive emoji sentiment posts over the previous hour is associated with an 0.06% (annualized: 109.2%) one-hour abnormal stock return compared to a mean of 0.03% (annualized: 54.6%). If the stock exhibits a higher intra-hour volatility, a proxy for uninformed noise trading, this relation is more pronounced and even stronger compared to stock return's relation to plain text sentiment.

The authors are not able to show causation that is open to future research. It also remains an open question how emojis impact market price efficiency.

Emojis are positively related to stock returns in addition to plain text-expressed content if they are discussed heavily by retail investors in Internet boards such as Reddit.

Shared emotions expressed by emojis might have an influence on how disconnected individuals make homogeneous decisions. This argument might explain our found relation of emojis and stock returns.

So, the study findings provide empirical evidence that emojis in Reddit posts convey information on future short-term stocks returns distinct from information expressed in plain text, in the case of volatile stocks, with a higher magnitude.

Focusing on critical discourse analysis, this paper aims to propose a framework for analysing the way activist anti-tourism groups construct their social action of protest. The authors argue that activist groups use different narrative strategies to construct and legitimise their discourse of protest to convey social meanings for social action practices. This study represents an attempt to explain how anti-tourism activist groups have the agency to build different paradigms of protest rooted in particular views of tourism.

As a result of the lack of research in this area, this study used a comparative case study methodology drawn on four case studies in the field of anti-tourism protest. Case study is deemed adequate to explore a complex social phenomenon, how activist groups differ from each other, in a specific socio-economic context. A critical discourse analysis method is used to study primary (interviews) and secondary sources (reports, websites and online campaigns documents) of information, which express the activist group motivations and objectives to protest against tourism.

This study’s findings provide evidence in how discourse differs among the protest groups. Three narrative paradigms of protest are identified, which guide their agency: scepticism, based on a global and ecological approach; non-interventionist transformation, rooted in local community issues; and direct transformation, based on a sectoral problem-solving approach. These differences are interpreted as the consequences of the emergence and the development of different paths of protest according to specific social contexts and power relations in which anti-tourism groups are embedded.

This paper provides a contemporary approach to anti-tourism activism within the context of social movements. This case study may be of interest to practitioners and international destination managers interested in gaining a better understanding of anti-tourism protest strategies, new anti-tourism narratives following COVID-19 and the opportunities and challenges for opening a dialogue with those involved in activism and social urban movements as part of sustainable tourism governance. Our results can also help activists to rethink how they integrate differences and particular strategic positions to avoid hindering collective action. This knowledge is especially useful for managers and authorities seeking to develop more accurate collaborative governance practices with local activists, and especially those interested in fostering participative action without marginalising the diverse range of local community perspectives.