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The goal of this work is to evaluate how digital transformation disclosure in corporate news and press releases affects stock prices. We examine American and Chinese companies from the energy and industry sectors for two periods: pre-COVID-19 and during the COVID-19 pandemic.

To estimate the effects of disclosure of information related to digital transformation, we applied the bag-of-words (BOW) method. As the benchmark dictionary, we used Kindermann et al. (2021), with the addition of original dictionaries created via Latent Dirichlet allocation (LDA) analysis. We also employed panel regression analysis and random forest.

For USA energy sector, all aspects of digital transformation were insignificant in pre-COVID-19 period, while sustainability topics became significant during the pandemic. As for the Chinese energy sector, digital strategy implementation was significant in pre-pandemic period, while digital technologies adoption and business model innovation became relevant in COVID-19 period. The results show the greater significance of digital transformation aspects for industrials sectors compared to the energy sector. The result of random forest analysis proves the efficiency of the authors’ dictionary which could be applied in practice. The developed methodology can be considered relevant.

The research contributes to the existing literature in theoretical, empirical and methodological ways. It applies signaling and information asymmetry theories to the financial markets, digital transformation being used as an instrument. The methodological contribution of this article can be described in several ways. Firstly, our data collection process differs from that in previous papers, as the data are gathered “from investor’s point of view”, i.e. we use all public information published by the company. Secondly, in addition to the use of existing dictionaries based on Kindermann et al. (2021), with our own modifications, we apply the original methodology based on LDA analysis. The empirical contribution of this research is the following. Unlike past works, we do not focus on particular technologies (Hong et al., 2023) connected with digital transformation, but try to cover all multi-dimensional aspects of the transformational process and aim to discover the most significant one.

The increasing awareness and adoption of technology, particularly artificial intelligence (AI), reshapes industries and daily life, fostering a proactive approach to risk management and leveraging advanced analytics, which may affect the stock price crash risk (SPCR). The main objective of the current study is to explore how AI adoption influences SPCR.

This study employs an Ordinary Least Squares (OLS) fixed-effect regression model to explore the impact of AI on SPCR in Chinese A-share listed companies from 2010 to 2020. Further, number of robustness analysis (2SLS, PSM and Sys-GMM) and channel analysis are used to validate the findings.

The primary findings emphasize that AI adoption significantly reduces SPCR likelihood. Further, channel analysis indicates that AI adoption enhances internal control quality, contributing to a reduction in firm SPCR. Additionally, the observed relationship is notably more pronounced in non-state-owned enterprises (non-SOEs) compared to state-owned enterprises (SOEs). Similarly, this distinction is heightened in nonforeign enterprises (non-FEs) as opposed to foreign enterprises (FEs). The study finding also supports the notion that financial analysts enhance transparency, reducing the SPCR. Moreover, the study results consistently align across different statistical methodologies, including 2SLS, PSM and Sys-GMM, employed to effectively address endogeneity concerns.

Our study stands out for its distinctive focus on the financial implications of AI adoption, particularly how it influences firm-level SPCR, an area that has been overlooked in previous research. Through the lens of information asymmetry theory, agency theory, and the economic implications of integrating AI into financial markets, our study makes a substantial contribution in mitigating SPCR.

This study underscores the pivotal role of AI adoption in influencing stock markets for enterprises in China. Embracing digital strategies, fostering transparency and prioritizing talent development are key for reaping substantial benefits. The study recommends regulatory bodies and service providers to promote AI adoption in strengthening financial supervision and ensure market stability, emphasizing the importance of investing in technologies and advancing talent development.

This study aims to investigate the use of voluntary disclosure on mainstream social media platforms to examine strategic responses to the COVID-19 pandemic. It examines the influential factors and institutional pressures organisations faced when making disclosures on social media during the pandemic.

A two-stage qualitative approach was adopted. Stage one used content analysis to examine voluntary disclosures made by international organisations on social media during the emergence of the COVID-19 pandemic. Stage two comprised semi-structured interviews with individuals who were involved in the decision-making process around the social media disclosures.

This study’s findings reveal significant changes in disclosure practices due to COVID-19-related pressures. In addition to the utilisation of social media for signalling conformance with new pandemic-related norms and connecting with stakeholders, the evidence also reveals how organisations made use of strategic responses to COVID-19-related institutional pressures.

The findings reveal how social media was used as a means of timely voluntary disclosure during the examined crisis. The findings can inform the development of organisational guidelines and policies for the use of social media as a disclosure medium.

This study reveals how organisations used voluntary disclosure on social media as a strategic response to institutional pressures and the COVID-19 pandemic; this context is under-researched. The study also extends the application of the strategic response framework regarding voluntary disclosure via social media.

This paper aims to identify, examine, and present an empirical research design of behavioral finance of potential investors during Covid-19.

A well-structured questionnaire was designed; a survey was conducted among potential investors using convenience sampling, and 200 valid responses were collected. The research work uses multiple regression and discriminant function analysis to evaluate the influence of cognitive factors on the financial decision-making of investors.

Recency and familiarity bias are proven to have the highest significant impact on the financial decisions of investors followed by confirmation bias. Overconfidence bias had a negligible effect on the decision-making process of the respondents and found insignificant.

Covid-19 is a temporary phase that may lead to changes in financial behavior and investors’ decisions in the near future.

The paper will help academicians, scholars, analysts, practitioners, policymakers and firms dealing with capital markets to execute their job responsibilities with respect to the cognitive bias in terms of taking financial decisions.

The present investigation attempts to fill the gap in the literature on the intended topic because it is evident from literature on the chosen subject that no study has been undertaken to evaluate the impact of cognitive biases on financial behavior of investors during Covid-19.

Digital transformation misalignment refers to disparities in digital transformation levels between suppliers and buyers across the production and operation process. It has negatively affected supply chain stability. However, the existing research concerning the economic consequences has not been adequately addressed. Therefore, this paper aims to investigate whether such digital transformation misalignment increases supplier financial risk and to identify the factors influencing this relationship.

This paper examines binary combinations of suppliers and buyers listed on China’s A-share market between 2011 and 2021. This group constitutes a sample to empirically test the influence of digital transformation misalignment on the supplier’s financial risk, as well as the moderating effect of the geographical and organizational distances.

The paper’s findings demonstrate that digital transformation misalignment has indeed a significant increase in the supplier’s financial risk. Moreover, the impact is more intense when the geographical or organizational distance between the supplier and the buyer is relatively large.

The existing literature rarely explores the potential risks arising from digital transformation misalignment between supply chain partners. Therefore, this paper fills a notable gap as it is the first to study the impact of digital transformation misalignment on the supplier’s financial risk and the specific applied mechanisms. The contribution significantly improves the field of corporate digital transformation, particularly, within the context of supply chain management.

Digital transformation and innovation-driven development have become an international consensus. The purpose of this paper is to examine the effects of relationships, mechanisms and economic consequences between digital transformation and enterprise innovation quality in order to provide a benchmark for developing countries to implement digital transformation strategies and innovation-driven strategies and provide a major support for economic recovery in the post-coronavirus disease 2019 (COVID-19) era.

Using microdata from A-share listed enterprises in Shanghai and Shenzhen from 2010 to 2021, this study examines the relationship between digital transformation and enterprise innovation quality and further reveals the internal logic and economic consequences of digital transformation to improve enterprise innovation quality through the mediating effect and moderating effect models.

The results demonstrate that digital transformation is beneficial for improving enterprise innovation quality. The heterogeneity test demonstrates that digital transformation has a larger effect on improving enterprise innovation quality in non-state-owned enterprises and eastern enterprises in China. The mechanism test demonstrates that digital transformation can improve enterprise innovation quality by improving internal control quality and analyst attention. Furthermore, with the increase in enterprise innovation inputs, digital transformation plays a significantly stronger role in improving enterprise innovation quality. The extended analysis demonstrates that digital transformation can significantly improve enterprise financial performance by improving innovation quality.

First, the construction of the core explanatory variable digital transformation index in this study is based on the Python data analysis software, which calculates the frequency of digital transformation in the text of the business situation analysis portion of the annual report of the listed companies and then obtains the degree of digital transformation of the company in this year. There may be some deviation from the degree of digital transformation in the actual production and operation of enterprises. Second, in addition to internal control quality and analyst attention, are there other mediating mechanisms for the impact of digital transformation on the quality of enterprise innovation? Third, whether the moderating effect of innovation input on digital transformation and innovation quality is related to human capital factors of the research and development (R&D) team, such as the technical background of R&D personnel, etc.

This study enriches the relevant theories of digital transformation and broadens the research boundaries of digital transformation and enterprise innovation. This study's result provides an empirical basis for enterprises to improve enterprise innovation quality and financial performance from the perspective of digital transformation at the micro level and points out specific practical directions, combining theory with practice.

This study aims to reveal the mechanism of CEO overconfidence in the digital transformation of specialized, refined, distinctive and innovative (SRDI) enterprises, thereby enriching research related to upper echelons theory and corporate digital transformation.

This study uses listed SRDI companies in China from 2017 to 2022 as a sample and adopts a fixed-effects regression model to analyze the direct, mediating, and moderating effects of CEO overconfidence on corporate digital transformation.

First, CEO overconfidence significantly promotes SRDI enterprises' digital transformation. Second, according to the “cognition-behavior-outcome” model, we found that entrepreneurial orientation plays a mediating role. Third, based on the principle of procedural rationality and the interaction perspective between the CEO and the executive team, we introduce the heterogeneity of the executive team as a moderating variable. Our findings indicate that age heterogeneity within the executive team has a negative moderating effect, whereas educational and occupational heterogeneities have positive moderating effects.

This study expands on earlier research that focuses primarily on CEO demographic characteristics. It enriches the analytical perspective of upper echelons theory on corporate digital transformation by analyzing the psychological characteristics of CEOs, that is, overconfidence and its mediating pathways. Moreover, this study goes beyond the previous literature that does not differentiate between CEOs and executive teams by introducing the concept of CEOs' interactions with the executive team and including the heterogeneity of the executive team as a moderating variable in the literature. Thus, continuing to deepen the application of upper echelons theory to corporate digital transformation. Additionally, this study contributes to the literature on the positive consequences of overconfidence.

Positive psychology helps us understand the knowledge required to contribute to adolescents' societal development and adjustability. Adolescence is the crucial stage to work on for a balanced personality. The present study concerned adolescents' self-strength, happiness, and help-seeking behaviour. The authors aimed to explore the relationship between adolescents' self-strength and happiness and investigate the mediational effect of adolescents' help-seeking behaviour on their self-strength and happiness.

The research design of the current quantitative study was correlational, and 809 adolescents from China and Pakistan participated in the present study. Data were personally collected from participants through self-developed scales.

We deployed Pearson correlation and simple mediation using SPSS software and found a linear, positive, strong (r = 0.654, n = 809, p = 0.000 < 0.01) and statistically significant correlation between adolescents' self-strength and happiness. The authors also found a significant indirect effect of help-seeking on adolescents' self-strength and happiness at (β = 0.373, t(907) = 7.01).

Using self-reported scales to gather information was one of the study's limitations. Adolescents may have misunderstood the notion or construct narrated in words or responded biasedly despite the bilingual scales.

This study offers social and practical implications for educators, parents, and school administrators to address the development of adolescents' personalities using a positive psychology lens.

The findings are of significant importance for teachers working in the elementary schools. They may work on adolescents' self-strength, happiness, and help-seeking to develop balanced personalities.

This paper aims to promote the higher quality development of high-tech enterprises in China. While science and technology have greatly promoted human civilization, resources have been excessively consumed and the environment has been sharply polluted. Therefore, it is particularly important for current enterprises to make use of scientific and technological innovation to maximize the benefits of mankind, minimize the loss of nature, and promote the sustainable development of our country.

By using DEA-Banker-Charnes-Cooper (BCC) model and DEA-Malmquist model, this paper comprehensively examines the innovation efficiency of high-tech enterprises from both static and dynamic perspectives, and conducts a provincial comparative study with the panel data of ten representative provinces from 2011 to 2020.

The research findings are as follows: the rapid number increase of high-tech enterprises in most provinces (cities) is accompanied by an ineffective input–output efficiency; the quality of high-tech enterprises needs to comprehensively examine both input–output efficiency and total factor productivity; and there is not a positive correlation between element investment and innovation performance.

Because the DEA model used in this paper assumes that the improvement direction of invalid units is to ensure that the input ratio of various production factors remains unchanged but sometimes the proportion of scientific and technological activities personnel and the total research and development investment is not constant. In the future, the nonradial DEA model can be considered for further research. Due to historical data statistics, more provinces, cities and longer panel data are difficult to obtain. The samples studied in this paper mainly refer to the provinces and cities that ranked first in the number of national high-tech enterprises in 2020. Limited by the number of samples, DEA analysis failed to select more input and output indicators. In the future, with the accumulation of statistical data, the existing efficiency analysis will be further optimized.

Aiming at the misunderstanding of emphasizing quantity and neglecting quality in the cultivation of high-tech enterprises, this paper comprehensively uses DEA-BCC model and DEA Malmquist index decomposition method to make a comprehensive comparative study on the development of high-tech enterprises in ten representative provinces (cities) from two aspects of static efficiency evaluation and dynamic efficiency evaluation.

Innovation has become extremely important, especially concerning manufacturing firms, as it is known to foster robust and healthy competition. The study aims to examine the effect of innovation orientation and supply chain integration on structural flexibility and strategic business performance.

Using the quantitative approach, 315 questionnaires were distributed to manufacturing firms in three cities (Accra, Kumasi and Takoradi) in Ghana out of which 305 usable responses were retrieved. The partial least square structural equation modeling technique and the statistical package for social sciences software version 27 were used for the data analysis.

The findings showed that supply chain integration and innovation orientation have a strong beneficial association. A substantial favorable association between structural flexibility and supply chain integration was found in the study once more. What is more, the research revealed a strong positive relationship between supply chain integration and strategic business performance. Furthermore, the study found a strong relation between innovation orientation and strategic business performance.

The research paper adds to the body of knowledge by examining how supply chain integration affects the relationship between innovation orientation, structural flexibility and strategic business performance.