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Presentation of R&D expenditures of the largest banks in Poland
No full textInnovation is the foundation of economic development. The subject of this paper was to identify how banks communicate to their stakeholders about their R&D activities and spending. The financial statements and non-financial reports of the 6 largest banks in Poland in 2017-2022 were verified. It was decided to choose business entities from this sector, as it was considered that banks are characterized by high expenditures on modern technologies and innovation. It is a sector that is developing rapidly, using the latest technological solutions to meet the ever-growing needs of customers for new banking products and the security of their operation. Unfortunately, despite the high expenditure on intangible assets disclosed in the balance sheet, it turned out that the banks do not boast about their research. There is no precise information on what expenditures on development work or the increase in expenditure on software, patents or licenses are about. Such information cannot be found either in the notes or in the non-financial reports.
This paper contributes to the sustainability reporting literature by providing new insights into banks\u27 R&D spending reporting practices. Although the subject of R&D expenditure appears quite often in the literature on the subject, it is quite rare in the context of financial statements and non-financial reports. There is, therefore, a research gap in this area
Digital transformation, human capital upgrading, and enterprise ESG performance: Evidence from Chinese listed enterprises
No full textResearch background: With the rapid development of digital technologies such as artificial intelligence (AI), big data, cloud computing, and blockchain, the deep integration of digital technology and traditional industries offers unprecedented opportunities and has become an important technological force driving the development of enterprise environmental, social, and governance (ESG) performance. Digital transformation increases the complementarity between the production and operation processes of enterprises and highly skilled labour, specifically manifested in the adaptive change of the human capital structure of enterprises in labour relations. Meanwhile, transforming enterprises’ human capital structure also affects ESG performance.
Purpose of the article: This study investigates the effects of digital transformation on enterprise ESG performance and its underlying mechanisms of human capital upgrading. First, it combines cutting-edge literature to analyse the theoretical mechanism between digital transformation, human capital upgrading, and enterprise ESG performance, revealing the internal driving factors and implementation paths for improving enterprise ESG performance. Second, we use the data of 3928 listed enterprises in the Shanghai and Shenzhen A-share markets from 2009–2022 to analyse the impact of digital transformation on enterprise ESG performance from the perspective of human capital upgrading as well as the mechanism by which digital transformation affects enterprise ESG performance through human capital upgrading. Third, we provide policy recommendations for optimising the labour structure and enhancing enterprise ESG performance from the perspective of optimising human capital and digital technology applications.
Methods: Based on data from 3928 listed enterprises in Chinese A-share markets from 2009-2022, we investigate the effects of digital transformation on enterprise ESG performance and the mechanisms of human capital upgrading. The panel mediation effect model tests the relationships between digital transformation, human capital upgrading, and enterprise ESG performance.
Findings & value added: In theory, digital transformation is beneficial for optimising human capital structure, accelerating green technological innovation, and improving management efficiency, thus improving enterprise ESG performance. Mechanism testing shows that digital transformation enhances enterprise ESG performance through human capital upgrading. Heterogeneity analysis shows that the impact of digital transformation on ESG performance is more significant in enterprises that are capital- and technical-intensive, and located in the eastern and central regions. This study examines the microeconomic consequences of digital transformation, contributing to a deeper understanding of the theoretical logic inherent in enterprises’ optimisation of their labour structure. It also provides empirical evidence and decision support for developing industrial talent policies
The Expectancy-Disconfirmation Model in the analysis of citizen satisfaction in depopulated regions: Implications for sustainable long term rural development policy
No full textResearch background: Understanding the cognitive processes used by citizens to form their satisfaction is essential in the design of sustainable rural policies. This research holds significant relevance for other countries facing rural depopulation, governance and demographic challenges. The authors apply the Expectancy-Disconfirmation Model (EDM) to explain citizen satisfaction with rural development policies, considering the unique challenges and expectations of rural communities.
Purpose of the article: The authors investigate the EDM capacity to explain satisfaction in the under-researched rural context. Incorporating a territorial perspective into the study of satisfaction may offer a better understanding of the decision-making processes rural citizens use to make evaluations of government policies. In addition, it is interesting to address the lack of consensus on the ability of expectations to act as a predictor of citizen satisfaction and the insufficient attention paid to the distinction between normative and predictive expectations.
Methods: The article is based on the results of a survey to rural citizens of the so-called "Hollowed-out Spain”. The authors apply the Structural Equation Modelling methodology to estimate two alternative models that explain the behavior of the variable satisfaction. These two models differ in the variable used to measure expectations.
Findings & value added: The results obtained allow us to affirm that the EDM acceptably adapts to the rural context. Perceived disconfirmation exerts the largest effect on satisfaction. The central prediction of the EDM that expectations are a primary driver of satisfaction is not confirmed, although empirical expectations do improve the performance of the model. Some governance implications arise: only if expectations are considered will investments in improving a public service impact positively on citizen satisfaction. Administrations may attempt to influence such expectations, albeit deploying an ethical approach. Enhancing transparency could be useful to reduce dissonances between actual performance and that perceived by citizens
A novel integrated structural model of green consumer purchasing behavior: A systematic literature review with COM-B framework perspective
No full textResearch background: Research on Green Consumer Purchasing Behavior (GCPB) has been conducted in many product contexts. However, even though the role of green non-food products and the bioeconomy is significant and continuously expanding with the growing demand for non-food (nF), bio-based products, GCPB analyses in these sectors remain fragmented and require systematization to effectively utilize existing knowledge. The COM-B (capability, opportunity, and motivation) model provides an interesting framework for such research.
Purpose of the article: The purpose of this paper is to map research tendencies and systematically analyze and synthesize existing research on the factors influencing GCPB-nF to provide a comprehensive understanding of the drivers of sustainable consumption and to offer foundation for building conceptual structural model as well multi-research - grounded justification for practical implications.
Methods: A systematic literature review (SLR) and bibliometric analysis were conducted on 199 peer-reviewed articles sourced from the Scopus database. The selection followed rigorous criteria, including article quality, relevance, and methodological clarity. The Antecedents-Decisions-Outcomes (ADO) and COM-B model were utilized as frameworks.
Findings & value added: The study offers a comprehensive synthesis of green consumer purchasing behavior (GCPB) in the non-food sector (nF), revealing that psychological capabilities, particularly environmental knowledge or reflective motivation including green attitude are well-established predictors, whereas physical capabilities and automatic motivations remain underexplored. Importantly, the analysis underscores that external opportunities, such as social norms, green branding, and credible communication substantially influence consumer decision-making. The proposed integrated structural model, grounded in the COM-B and ADO frameworks, systematically maps key behavioral drivers and their interrelations. This framework not only contributes to theory-building by unifying fragmented insights, but also provides a robust theoretical foundation for future structural modeling, hypothesis formulation, and necessary condition analysis (NCA). The findings generate actionable implications for marketers aiming to promote sustainable consumption and enable researchers to test causal mechanisms driving green behavior in the bio-based non-food product domain
Facing the financial risk, embracing the opportunity: How financial perceptions shape entrepreneurial behavior in recession periods
No full textResearch background: Although bank credit is a widely used external source for businesses, access to this source becomes more limited during periods of economic recessions. Small firms and young entrepreneurs, in particular, may have a more pessimistic perception of bank lending accessibility due to their limited financial assets, lack of credit history, and insufficient financial statements, which cause information asymmetry. For these reasons, enterprises might have heightened perceptions of the bank credit application process, interest rates, and credit conditions that discourage them from undertaking entrepreneurial initiatives, leading to lower entrepreneurial intention (EI).
Purpose of the article: This paper examines whether a more intense perception difficulty in accessing bank credit is negatively associated with EI.
Methods: The paper analyzes 1367 firm executives who are purposively selected based on their job status. Ordinal Logistic Regression analysis is applied to perform research analyses.
Findings & value added: The findings reveal that a negative relationship exists between a more intense perception of credit access conditions and EI. The respondents who consider access to finance, credit conditions, and interest rates as inappropriate report greater EI, and vice versa. The results can be explained by Institutional Theory-related factors, such as banking sector competitiveness and economic development of countries. This paper makes several theoretical and practical contributions, including the integration of RBV and TPB approaches that represent the importance of financial management and entrepreneurial capabilities, respectively. On a practical level, the generation of soft loans and gaining insights into entrepreneurs are some practical contributions that borrowers and lenders can benefit from during times of economic downturn
AI-generated versus human-created advertising: Effects on consumer trust and purchase intent
No full textResearch background: The rapid advancement of Generative Artificial Intelligence (AI) technologies has profoundly influenced the marketing landscape, particularly advertising practices. Despite significant growth and widespread integration of AI-generated content, consumer reactions toward explicit disclosure of AI involvement remain uncertain. Previous studies indicate that while AI-generated advertisements can enhance efficiency and personalisation, they may negatively affect consumer perceptions of authenticity and credibility. However, the role of disclosure ("created by AI" vs. "created by human") and product involvement level (high vs. low involvement) as moderators of consumer trust and purchase intentions remains under-explored.
Purpose of the article: The purpose of this research is to empirically investigate how advertisement generation source (AI vs. human) combined with explicit labelling influences consumer trust and purchase intent, while also considering product involvement as a moderating factor.
Methods: The study employed a 2 (ad generation source: AI vs. human) × 2 (ad labelling: labelled as AI vs. labelled as human) between-subjects experimental design. Participants were randomly assigned to four conditions, assessing advertisements for both low-involvement (snacks) and high-involvement products (laptops). Consumer trust and purchase intent were measured across multiple validated dimensions. Data analysis included one-way ANOVA and Tukey post-hoc tests to identify significant group differences.
Findings & value added: The results confirm significant differences in consumer trust and purchase intent based on advertisement generation source and labelling conditions, fully supporting all hypothesised effects. Specifically, advertisements labelled as human-generated received higher consumer trust and purchase intent ratings, even if they were AI-generated. Conversely, transparently labelled AI-generated ads caused lower trust and intent, particularly for high-involvement products. These findings reveal context-specific reactions to AI disclosures, underscore the importance of authenticity in digital marketing, and advise marketers to manage AI disclosures carefully to preserve trust and drive purchases
The impact of formal and informal institutions on corporate environmental investment: Evidence from China
No full textResearch background: China’s rapid economic growth has been accompanied by increasingly severe environmental pollution. As critical market entities, corporations are often major sources of pollution from production and operational activities. To enhance environmental protection, China must rely on the dual regulatory forces of formal and informal institutions.
Purpose of the article: This study analyzes the impact of formal and informal institutions on corporate environmental investment (CEI). We also explore the mechanisms and heterogeneity of this impact.
Methods: We investigate the impact of formal and informal institutions on CEI using the panel fixed effects model with panel data from Chinese A-share market listed companies between 2010 and 2023.
Findings & value added: Our findings reveal that formal and informal institutions significantly promote corporations’ strengthened environmental protection. Notably, formal institutions primarily affect non-state-owned enterprises, and those in high-pollution industries, high-carbon-emissions regions, and the western region, while informal institutions primarily affect others. We also demonstrate that this positive impact operates by promoting corporate green innovation and reducing transaction costs. This study highlights the complex relationship between institutions and corporate environmental practices in developing or transitional economies
Decision-making support system for travel planning for people with disabilities based on fuzzy set theory
No full textResearch background: In recent years, there has been increasing attention to the needs of tourists with disabilities. Several international studies confirm that this target group has been marginalized in tourism due to physical, economic, social, and environmental barriers. However, the integration of intelligent decision-support systems can significantly enhance accessibility and inclusion in tourism.
Purpose of the article: This research aims to develop effective methods and algorithms for constructing intelligent systems and software that generate precise and high-quality travel plans for tourists with disabilities. The primary objective is to create a decision support system for trip planning, using the example of Visegrad Group countries (the Czech Republic, Hungary, Poland, Slovakia).
Methods: The decision support system is structured around two core components: the data level and the knowledge level. The data layer compiles a structured database of actual visits by disabled tourists. The knowledge layer consists of mathematical models forming a comprehensive decision-making framework. The formalization of the system employs fuzzy set theory, fuzzy logic, expert evaluation, and intelligent knowledge analysis. This research introduces: an information model for assessing the accessibility of destinations; fuzzy method of determining the degree of accessibility of destination, considering the level of limited capabilities of the participant of the tourist movement; decision-making method when travel planning on the accessibility of the region on goal needs.
Findings & value added: The decision-making support system was verified and tested on real data from 41 participants in the Visegrad Group countries. A distinctive feature of this research is the development of a dynamic, adaptive decision-support mechanism that evolves with real-world user data. Unlike standard accessibility evaluation approaches, this system provides personalized travel recommendations and continuously refines its ranking model based on user experiences. This ensures a long-term impact on smart tourism, sustainable travel planning, and enhanced accessibility for people with disabilities
Integrating green transformational leadership, green HRM, and green innovation to enhance sustainable performance in hotels: Insights from PLS-SEM, NCA, and cIPMA
No full textResearch background: As environmental concerns rise globally, an increasing number of hotels are implementing sustainable performance (SP) management practices, making sustainability a strategic priority in the hospitality industry. These efforts aim to balance economic growth with environmental responsibility. Although SP strategies are widely embraced, the mechanisms through which Green Transformational Leadership (GTL), Green Human Resource Management (GHRM), and Green Innovation (GI) synergistically influence SP remain insufficiently explored.
Purpose of the article: This study aims to investigate how GTL and GHRM practices cultivate employees’ internal capabilities to foster GI, thereby enhancing SP within the hotel industry. Guided by the resource-based view and ability–motivation–opportunity theories, this research addresses a critical gap in existing studies by examining the complex relationships among GTL, GHRM, GI, and SP with a unique hybrid methodological approach, and offers comprehensive insights into how these constructs jointly shape sustainability outcomes in hotels.
Methods: Adopting a quantitative, survey-based research design, data were collected from 310 employees across 17 three- to five-star hotels in Taiwan via a 5-point Likert-type-scale questionnaire. SmartPLS 4 facilitated the analysis. The methodological approach was combined with partial least squares structural equation modeling (PLS-SEM), necessity-based logic via necessary condition analysis (NCA), and combined importance-performance map analysis (cIPMA).
Findings & value added: PLS-SEM results indicate GTL, GHRM, and GI significantly influence hotels\u27 SP. GHRM and GI exert a sequential co-mediating effect on the GTL–SP relationship; however, GTL\u27s direct impact on GI is not significant. NCA confirms all predictors are necessary conditions for SP. With an SP target of 85, cIPMA quantifies the minimum thresholds necessary to enhance SP as 31.464% for GHRM, 41.902% for GI, and 53.705% for GTL. This study enriches sustainable hospitality literature by exploring the GTL–GHRM–GI–SP nexus. It contributes a multi-method integrated PLS-SEM, NCA, and cIPMA model to sustainability research, integrating sufficiency and necessity logics. It offers theoretical insights into the interplay of GTL, GHRM, and GI, and provides practical strategies for hoteliers’ SP
