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This survey explores the application of real options theory to the field of health economics. The integration of options theory offers a valuable framework to address these challenges, providing insights into healthcare investments, policy analysis and patient care pathways.

This research employs the real options theory, a financial concept, to delve into health economics challenges. Through a systematic approach, three distinct models rooted in this theory are crafted and analyzed. Firstly, the study examines the value of investing in emerging health technology, factoring in future advantages, associated costs and unpredictability. The second model is patient-centric, evaluating the choice between immediate treatment switch and waiting for more clarity, while also weighing the associated risks. Lastly, the research assesses pandemic-related government policies, emphasizing the importance of delaying decisions in the face of uncertainties, thereby promoting data-driven policymaking.

Three different real options models are presented in this study to illustrate their applicability and value in aiding decision-makers. (1) The first evaluates investments in new technology, analyzing future benefits, discount rates and benefit volatility to determine investment value. (2) In the second model, a patient has the option of switching treatments now or waiting for more information before optimally switching treatments. However, waiting has its risks, such as disease progression. By modeling the potential benefits and risks of both options, and factoring in the time value, this model aids doctors and patients in making informed decisions based on a quantified assessment of potential outcomes. (3) The third model concerns pandemic policy: governments can end or prolong lockdowns. While awaiting more data on the virus might lead to economic and societal strain, the model emphasizes the economic value of deferring decisions under uncertainty.

This research provides a quantified perspective on various decisions in healthcare, from investments in new technology to treatment choices for patients to government decisions regarding pandemics. By applying real options theory, stakeholders can make more evidence-driven decisions.

Decisions about patient care pathways and pandemic policies have direct societal implications. For instance, choices regarding the prolongation or ending of lockdowns can lead to economic and societal strain.

The originality of this study lies in its application of real options theory, a concept from finance, to the realm of health economics, offering novel insights and analytical tools for decision-makers in the healthcare sector.

Drawing insights from institutional theory, this paper aims to examine whether and to what extent banks have reconfigured their management control systems (MCSs) in response to growing institutional pressures towards sustainability, understood as environmental, social and governance (ESG) issues.

The authors conducted an exploratory study at the three largest Italian banking groups to shed light on changes made in MCSs to account for ESG issues. The analysis is based on 12 semi-structured interviews with managers from the sustainability and controls areas, as well as from other relevant operational areas particularly concerned with the integration process of ESG issues. Additionally, secondary data sources were used. The Malmi and Brown (2008) MCS framework, consisting of a package of five types of formal and informal control mechanisms, was used to structure and analyse the empirical data.

The examined banks widely implemented numerous changes to their MCSs as a response to the heightened sustainability pressures from regulatory bodies and stakeholders. In particular, with the exception of action planning, the results show an extensive integration of ESG issues into the five control mechanisms of Malmi and Brown’s framework, namely, long-term planning, cybernetic, reward/compensation, administrative and cultural controls.

By identifying the approaches banks followed in reconfiguring traditional MCSs, this research sheds light on how adequate MCSs can promote banks’ “sustainable behaviours”. The results can, thus, contribute to defining best practices on how MCSs can be redesigned to support the integration of ESG issues into the banks’ way of doing business.

Overall, the findings support the theoretical assertion that institutional pressures influence the design of banks’ MCSs, and that both formal and informal controls are necessary to ensure a real engagement towards sustainability. More specifically, this study reveals that MCSs, by encompassing both formal and informal controls, are central to enabling banks to appropriately understand, plan and control the transition towards business models fully oriented to the integration of ESG issues. Thereby, this allows banks to effectively respond to the increased stakeholder demands around ESG concerns.

The main goal of the article is to determine the mediating role of human resources management (HRM) outcomes in the relationships between shaping employee work engagement and job satisfaction (SEWE&JS) and company performance results and to establish whether there are any identifiable regularities in this scope in the pre-pandemic and pandemic period in the headquarters (HQs) and foreign subsidiaries of multinational companies (MNCs).

The empirical research included 200 MNCs headquartered in Central Europe. The raw data in the variables were adjusted with the efficiency index (EI) to capture the actual relations between the variables under study. The partial least squares structural equation modeling (PLS-SEM) was used to verify the research hypotheses and assess the mediating effects.

The research findings show that the HRM outcomes positively mediate the relationships between SEWE&JS and the company performance results. HRM outcomes turned out to be a stronger mediator between SEWE&JS and company performance results in finance and quality in the HQs during the pandemic. By contrast, in the local subsidiaries, they were a stronger mediator of the relationships between the results in innovativeness and quality during the pandemic.

In addition to confirming the results of some other researchers, the research findings also provide new knowledge. They determine the mediating role of HRM outcomes in the relationship between SEWE&JS and the three categories of company performance results, namely finance, innovativeness and quality. In addition, they identify certain regularities in the four studied contexts, which is a novelty in this type of research. A novelty is also the use of employee key performance indicators (KPIs) in the data analysis as the efficiency index in analyzing the effect of the variables under study. The value of the research is also the fact that it covers HRM in MNCs established in Central Europe, which, compared to MNCs from the Western world, is not a frequent subject of research.

The circular economy business models (CEBMs) provide ways for firms operating in the construction industry to move from a linear to a circular approach. Thus, this study aims to explore CEBM research within the construction sector to show the focus area of studies, highlighting new areas that require attention.

This study adopted a bibliometric approach, using the Scopus database as the data source. The keywords used for paper extraction from the database were “circular economy business” OR “circular business” AND “model” OR “models” AND “construction industry” OR “building industry”. The VOSviewer software was then used to prepare a co-occurrence and co-authorship map based on the bibliographic data gathered.

The study’s findings reveal five research clusters in the construction industry. These clusters include circular construction intelligence, modular business modelling, eco-construction, sustainable construction economics and smart energy-efficient buildings. The two most cited scholars had two publications each, while the top journals are the Journal of Cleaner Production and Sustainable Production and Consumption. This study concludes that there is a need for research within the construction sector to focus on CEBMs’ archetypes and frameworks. This will enable a smooth transition from linear to circular business models in the sector.

The information was gathered from a single database, Scopus; hence, using other databases, including Web of Science, Google Scholar and Dimensions, might produce more articles for examination and, consequently, different findings on the subject under investigation.

These findings would assist researchers in considering the areas mentioned, which are yet to receive attention, and, by extension, enhance economic development while maintaining environmental sustainability.

This paper made a significant contribution to the body of knowledge by identifying scholars and platforms that have been instrumental in advancing CEBM research and highlighting new areas that require attention in the construction sector.

Foreign subsidiaries incur substantial institutional conformity costs because they have to respond to host-country institutional pressures (Slangen & Hennart, 2008). The purpose of this paper is to study this type of cost from institutional and regulatory perspectives. The authors argue that these costs decrease when the host country adopts concepts of international regulations that multinationals may be familiar with due to their own home country regulation experience. This prior regulatory experience gives foreign subsidiaries an advantage of foreignness (AoF), which can offset their liability of foreignness (LoF).

This study compared the returns on assets of 35 domestic firms with those of foreign subsidiaries in the Brazilian energy industry between 2002 and 2021, using regression dynamic panel data.

The existence of a relationship between the international regulatory norm and the Brazilian regulator has transformed the LoF into an advantage of foreignness to compete with local energy firms. The results also suggest that the better the regulatory quality of the subsidiary’s country of origin, the better its performance in Brazil, as it can reduce compliance costs. Finally, the greater the psychic distance between Brazil and the foreign subsidiary’s home country, the worse its performance.

The research suggests that one of the keys to competitiveness in host countries is local regulatory ties. Prior international regulatory experience gives foreign subsidiaries an asset of foreignness (AoF). This result complements the current institutional and regulatory foreignness studies on emerging economies (Cuervo-Cazurra & Genc, 2008; Mallon et al., 2022) and the institutional asymmetry between home and host country (Mallon & Fainshmidt, 2017).

This research suggests that one of the keys to competitiveness in host countries is local regulatory ties. Prior international regulatory experience gives foreign subsidiaries an asset of foreignness (AoF). This result complements the current institutional and regulatory foreignness studies on emerging economies (Cuervo-Cazurra & Genc, 2008; Mallon et al., 2022) and the institutional asymmetry between home and host country (Mallon & Fainshmidt, 2017). The practical implication is that the relationship between conformity costs, capital budget calculation and strategic planning for internationalization will be related to the governance quality of the home country of multinationals. The social implication is that a country interested in attracting more direct foreign investment to areas that need foreign technology transfer and resources may consider adopting international regulatory standards.

The social implication is that a country interested in attracting more direct foreign investment to areas that need foreign technology transfer and resources may consider adopting international regulatory standards.

This research discuss firm and local regulator tie is one of core competitiveness in host countries (Yang and Meyer, 2020). This study also complements the current institutional and regulatory foreignness studies in emerging economy (Cuervo-Cazurra & Genc, 2008; Mallon et al., 2022). Second, prior regulatory experience of multinational enterprise in similar environment can affect its foreign affiliate performance (Perkins, 2014). Third, this study confirms current literature that argues that knowledge and ability to operate in an institutionalized country can be transferred from parent to affiliate. In the end, this study investigates whether AoF persists when host governments improve the governance of their industries.

The performance of financial markets is significantly influenced by the political environment during general elections. This study investigates the effect of general elections on stock market performance in selected African markets.

Prior studies have been inconsistent in determining whether electioneering events negatively or positively influence stock market performance. The study utilized panel data set with annual observations from 1990 to 2020. The generalized method of moments (GMM) is employed to investigate the effect of electioneering and change in government on key stock market performance indicators, including stock market capitalization, stock market turnover ratio and the value of stock traded.

The study finds that electioneering activities generally have a positive impact on the performance of the stock market, whereas a change in government has a negative impact. As a result, the study recommends that stakeholders of the stock market remain vigilant and actively monitor electioneering events to devise and implement effective policies aimed at mitigating political risks during general elections. By adopting these measures, investor confidence can be significantly enhanced, fostering a more robust and secure investment environment.

The study investigates a neglected section of the literature by highlighting not only the effect of elections on stock market indicators but also possible change in government during elections.

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.

In this paper, the authors aim to introduce international dynamic marketing capabilities (IDMCs) theoretically derived from marketing capabilities (MCs), dynamic marketing capabilities (DMCs) and international marketing capabilities (IMCs) and provide a novel conceptualization of the concept by applying a holistic view of the international enterprise.

This is a literature review that maps the current research on MCs, DMCs and IMCs and serves as a basis for the theoretical conceptualization of a novel IDMCs concept as well as for the identification of research gaps and the development of future research directions on this phenomenon.

Existing typologies of MCs, DMCs and IMCs are classified into four categories: strategic, operational, analytical and value creation capabilities. A new typology of IDMCs is proposed, consisting of digital MC and dynamic internationalization capability as strategic capabilities, agile IMC, IM excellence and absorptive capability in IM as operational capabilities, IM resilience capability, IM knowledge management capability, AI-enabled IDMC and Industry 4.0-enabled IDMC as analytical capabilities, and ambidextrous IM innovation capability as value creation capability. Finally, the authors identify research gaps and develop research questions that open future research avenues for the coming years.

This paper offers a novel view of MCs, DMCs and IMCs and argues that, in contrast to the majority of previous research, a comprehensive understanding of these is only possible if all levels are considered simultaneously: the strategic, the operational, the analytical and the value creation level. A new conceptualization and typology of IDMCs follows this logic.

Optimal application and commitment toward financial management practices enhance organization performance. This study aims to assess the influence of financial management practices on organizational performance of small- and medium-scale enterprises.

Data were collected from 45 small-sized and 72 medium-sized firms. Data supported the hypothesized relationships. Construct reliability and validity were established through confirmatory factor analysis. The conceptual model and hypotheses were evaluated by using structural equation modeling.

The results indicate that working capital significantly influenced organizational performance. Capital budget management significantly influenced organizational performance. A non-significant influence of asset management on organizational performance was observed.

The generalizability of the findings will be constrained due to the research’s SMEs focus and cross-sectional data.

The study’s findings will serve as valuable pointers for stakeholders and decision-makers of SMEs in the development of well-articulated and proactive financial management systems to ensure competitiveness, sustainability, viability and financial competences.

The study adds to the corpus of literature by evidencing empirically that financial management practices significantly influenced SMEs’ performance.

Accounting information systems are mainly rule-based, and data are usually available and well-structured. However, many accounting systems are yet to catch up with current technological developments. Thus, artificial intelligence (AI) in financial accounting is often applied only in pilot projects. Using AI-based forecasts in accounting enables proactive management and detailed analysis. However, thus far, there is little knowledge about which prediction models have already been evaluated for accounting problems. Given this lack of research, our study aims to summarize existing findings on how AI is used for forecasting purposes in financial accounting. Therefore, the authors aim to provide a comprehensive overview and agenda for future researchers to gain more generalizable knowledge.

The authors identify existing research on AI-based forecasting in financial accounting by conducting a systematic literature review. For this purpose, the authors used Scopus and Web of Science as scientific databases. The data collection resulted in a final sample size of 47 studies. These studies were analyzed regarding their forecasting purpose, sample size, period and applied machine learning algorithms.

The authors identified three application areas and presented details regarding the accuracy and AI methods used. Our findings show that sociotechnical and generalizable knowledge is still missing. Therefore, the authors also develop an open research agenda that future researchers can address to enable the more frequent and efficient use of AI-based forecasts in financial accounting.

Owing to the rapid development of AI algorithms, our results can only provide an overview of the current state of research. Therefore, it is likely that new AI algorithms will be applied, which have not yet been covered in existing research. However, interested researchers can use our findings and future research agenda to develop this field further.

Given the high relevance of AI in financial accounting, our results have several implications and potential benefits for practitioners. First, the authors provide an overview of AI algorithms used in different accounting use cases. Based on this overview, companies can evaluate the AI algorithms that are most suitable for their practical needs. Second, practitioners can use our results as a benchmark of what prediction accuracy is achievable and should strive for. Finally, our study identified several blind spots in the research, such as ensuring employee acceptance of machine learning algorithms in companies. However, companies should consider this to implement AI in financial accounting successfully.

To the best of our knowledge, no study has yet been conducted that provided a comprehensive overview of AI-based forecasting in financial accounting. Given the high potential of AI in accounting, the authors aimed to bridge this research gap. Moreover, our cross-application view provides general insights into the superiority of specific algorithms.