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The main purpose of this study is to examine the effect of corporate digital transformation on bond credit spreads. Additionally, it also explores the two potential channels, information asymmetry and default risk, through which digital transformation can influence bond credit spreads.

We use the bond issuance data of Chinese listed companies over the period 2008–2020. Corporate digital transformation of these companies is measured with textual analysis of the management discussion and analysis part of annual reports. We employ a panel regression model to estimate the effect of digital transformation on bond credit spreads.

We find robust evidence that companies with higher digital transformation experience lower bond credit spreads. We further observe that credit spread reduction is higher for firms that are smaller, non-state-owned, have lower credit ratings and have less analyst coverage. We also find evidence that digital transformation reduces credit spreads by reducing the information asymmetry between firms and investors with enhanced information transformation mechanisms and lowering corporate default risk by strengthening operating efficiency.

To the best of our knowledge, this study is the first attempt to understand the impact of corporate digital transformation on bond credit spreads. Our findings help to understand the effect of digital transformation on firms’ credit worthiness and access to capital.

The purpose of this study aims to shorten the running-in time and improve the running-in quality of cylinder liner piston rings (CLPRs), the running-in tests were carried out and running-in parameters of CLPRs were designed based on running-in attractor theory, which can guide the choice of optimal working conditions for other friction pairs.

The running-in state and time under different working conditions are identified by the evolution law of the running-in attractor phase trajectory and fractal and chaotic characteristic quantities. The CLPRs running-in tests under different conditions were conducted and the friction signals were collected. The constructed phase trajectories and calculated chaotic parameters of the running-in attractor are obtained and the running-in state and time are identified by the evolution law of phase trajectories and chaotic characteristic quantities. The running-in quality is obtained by the surface morphology fractal dimension and characteristic roughness parameters.

The running-in parameters for short running-in time and good running-in quality are designed based on the fractal and chaotic theory and the optimal solution method are used to verify the results through the single objective or multi-objective optimization, and the corresponding optimal running-in parameters are obtained.

The optimal working condition parameters obtained from the design have guiding significance for the selection of CLPR running-in parameters, and this work can provide ideas for the other friction pairs.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0179/

This study aims to investigate how two different types of brand-to-brand dialogues – “roasting” versus “toasting” – impact consumers’ brand perceptions, particularly perceived entertainment, and influence brand attitudes.

The research design comprises four studies. The preliminary study involves Web scraping to gauge consumer perception about the two communication approaches followed by two well-known brands. Study 1 involves an online experiment to compare these communication types within each brand tested in the pilot study and examines the mediation effect of perceived entertainment. Study 2, also an online experiment, investigates the role of message neutralization, demonstrating that “roasting” can be acceptable when the humor is neutralized. Study 3 further tests the effects of neutralized “roasting” at different levels of brand familiarity and personality.

Roasting can lead to more favorable consumer perceptions than toasting. The effect can be explained by roasting’s higher level of perceived entertainment. However, this positive outcome is contingent on the successful neutralization of the aggressive humor in the “roasting” messages. When it comes to brand familiarity and personality, familiar brands benefit more from neutralized “roasting,” whereas brand personality does not have a strong influence.

The findings suggest that “roasting” can be effective when messages are neutralized, and “toasting” works best when spontaneous and genuine. It highlights how brand familiarity and personality influence consumer reactions, thus, offering strategic insights for both established and lesser-known brands. The study also prompts further research to examine other brand traits, cultural factors and behavioral dimensions in brand-to-brand dialogue, signifying the complexity and richness of this growing research area.

This study advises lesser-known brands to adopt “toasting” strategies to build a positive image, while established brands can try “roasting,” ensuring message neutrality to avoid negativity. The research emphasizes the role of brand familiarity and personality in shaping brand dialogues. Marketers must consider these to make humor strategies effective and bolster positive brand image.

This research uniquely examines message neutralization through contextual cues as a strategy brands can use to aid their sensitive dialogues with others on social media. The findings provide new insights into how brands can use different types of messages in digital communications to attract consumers and ensure positive reception, offering valuable guidance for academics and practitioners in brand-to-brand dialogue.

Given the regional heterogeneity of economic development, electricity consumption in various regions exhibits a discrepant growth pattern. The purpose of this study is to construct a grey system forecasting model with intelligent parameters for predicting provincial electricity consumption in China.

First, parameter optimization and structural expansion are simultaneously integrated into a unified grey system prediction framework, enhancing its adaptive capabilities. Second, by setting the minimum simulation percentage error as the optimization goal, the authors apply the particle swarm optimization (PSO) algorithm to search for the optimal grey generation order and background value coefficient. Third, to assess the performance across diverse power consumption systems, the authors use two electricity consumption cases and select eight other benchmark models to analyze the simulation and prediction errors. Further, the authors conduct simulations and trend predictions using data from all 31 provinces in China, analyzing and predicting the development trends in electricity consumption for each province from 2021 to 2026.

The study identifies significant heterogeneity in the development trends of electricity consumption systems among diverse provinces in China. The grey prediction model, optimized with multiple intelligent parameters, demonstrates superior adaptability and dynamic adjustment capabilities compared to traditional fixed-parameter models. Outperforming benchmark models across various evaluation indicators such as root mean square error (RMSE), average percentage error and Theil’s index, the new model establishes its robustness in predicting electricity system behavior.

Acknowledging the limitations of traditional grey prediction models in capturing diverse growth patterns under fixed-generation orders, single structures and unadjustable background values, this study proposes a fractional grey intelligent prediction model with multiple parameter optimization. By incorporating multiple parameter optimizations and structure expansion, it substantiates the model’s superiority in forecasting provincial electricity consumption.

The primary aim of this field research study is to fill the void about the long-run performance of the crosslisting event of companies listed on NYSE-Euronext Paris.

Our sample consisted of an overall sample of 138 listed companies officially listed on the French Stock Exchange over the period 1994–2019 using three empirical methods, including the Time Abnormal Return (CTAR) calendar, the three-factor model of Fama and French (1993), and the method of Fama and Macbeth (1973).

We find significant long-term underperformance. Over the long term, the returns of cross-listed companies are lower than the returns of control companies. Also, we find that cross-listed companies' performance deteriorates over the long term.

This study can help investors and financial analysts make informed decisions about the timing and effectiveness of investment strategies. In addition, it contributes to academic research to assess the efficiency of capital markets and provide evidence on the effectiveness of market regulations.

This study differs from previous studies in terms of applying a variety of different statistical methods to test the existence of abnormal long-term performance after the crosslisting announcement and the first study that analyses the long-term performance of cross-listed firms in the French context.

This research study aims to delve into the enduring relationship between housing property prices and economic policy uncertainty across eight major Indian cities.

Using the panel non-linear autoregressive distributed lag model, this study meticulously investigates the asymmetric impact of economic policy uncertainty on apartment and house (unit) prices in India during the period from 2000 to 2022.

The findings of this study indicate that economic policy uncertainty exerts a negative influence on property prices, but noteworthy asymmetry is observed, with positive changes in effect having a more pronounced impact than negative changes. This asymmetrical effect is particularly prominent in the case of unit prices.

This research reveals that long-run price trends are also influenced by factors such as interest rates, building costs and housing loans. Through a comprehensive analysis of these factors and their interplay with property prices, this research paper contributes valuable insights to the understanding of the real estate market dynamics in Indian cities.

Entrepreneurial passion is constantly considered a core driver of the entrepreneurial process. In reality, however, many passionate entrepreneurs still fail to persist in their ventures. Whether entrepreneurial passion negatively affects entrepreneurial persistence is not well known. The current study explores how entrepreneurial passion inhibits entrepreneurial persistence based on self-regulation theory. The moderating role of the perceived entrepreneurial institutional environment on the relationship is further investigated.

The study collected data from 200 entrepreneurs using a two-stage questionnaire. In the first stage, demographic information was obtained from the respondents, and their entrepreneurial passion, self-regulatory assessment mode and perceived entrepreneurial institutional environment were measured. Three months later, in the second stage, entrepreneurial persistence was evaluated.

The results show that entrepreneurial passion has a positive effect on self-regulatory assessment mode. Further, self-regulatory assessment mode negatively impacts entrepreneurial persistence and mediates the negative relationship between entrepreneurial passion and persistence. In addition, the greater the perceived level of the entrepreneurial institutional environment is, the weaker the positive association between entrepreneurial passion and self-regulatory assessment mode and the weaker the mediating effect of self-regulatory assessment mode on the relationship between entrepreneurial passion and entrepreneurial persistence and vice versa.

This paper clarifies the unknown negative effects of entrepreneurial passion, contributes to the theoretical relationship between the constructs of entrepreneurial passion and persistence and provides insights for decision-making by entrepreneurs, government and venture capital institutions.

The authors examine the volatility connections between the equity markets of China and its trading partners from developed and emerging markets during the various crises episodes (i.e. the Asian Crisis of 1997, the Global Financial Crisis, the Chinese Market Crash of 2015 and the COVID-19 outbreak).

The authors use the GARCH and Wavelet approaches to estimate causalities and connectedness.

According to the findings, China and developed equity markets are connected via risk transmission in the long term across various crisis episodes. In contrast, China and emerging equity markets are linked in short and long terms. The authors observe that China leads the stock markets of India, Indonesia and Malaysia at higher frequencies. Even China influences the French, Japanese and American equity markets despite the Chinese crisis. Finally, these causality findings reveal a bi-directional causality among China and its developed trading partners over short- and long-time scales. The connectedness varies across crisis episodes and frequency (short and long run). The study's findings provide helpful information for portfolio hedging, especially during various crises.

The authors examine the volatility connections between the equity markets of China and its trading partners from developed and emerging markets during the various crisis episodes (i.e. the Asian Crisis of 1997, the Global Financial Crisis, the Chinese Market Crash of 2015 and the COVID-19 outbreak). Previously, none of the studies have examined the connectedness between Chinese and its trading partners' equity markets during these all crises.

This paper aims to investigate the impact of combined assurance on tax avoidance in South Africa.

This study is founded on a sample of 76 South African firms listed on the Johannesburg Stock Exchange over the 2014–2022 period. The authors used the feasible generalized least squares regression estimation technique to test the hypothesis. To address endogeneity issues, this study conducted a difference-in-differences (DID) analysis based on propensity score matching.

The results reveal that combined assurance negatively impacts tax avoidance. Implementing combined assurance, as an integrated risk management approach, significantly minimizes tax risk. The DID analysis provides well-founded evidence attributing the decline in tax avoidance levels to the availability of combined assurance. The inferences are robust to using alternative measures of tax avoidance, testing combined assurance impact across various tax avoidance levels and controlling for the COVID-19 effect.

This study presents valuable insights for firms, managers and policymakers. The findings encourage companies to bolster their risk management practices, opting for combined assurance over a sole risk monitoring mechanism. This approach enables the company to ensure better compliance with tax regulations, thereby enhancing overall efficiency. Besides, the disciplining effect of combined assurance motivates managers to make informed decisions, avoid tax avoidance strategies and safeguard corporate reputation. Moreover, this research calls upon policymakers to promote effective global regulatory frameworks for combined assurance practices.

The research brings original insights by exploring the influence of combined assurance on tax avoidance. This addresses a gap in the current literature that has predominantly focused on the relationship between tax avoidance and individual lines of defense.

The present paper offers a literature review on the application of institutional theory in the context of small and medium-sized enterprises (SMEs). The study aims to synthesize existing research on how institutional factors, both formal and informal, shape the strategic behaviors of SMEs through the lens of new institutionalism and its three strands – rational-action neoinstitutionalism (RAN), social-constructionist neoinstitutionalism (SCN) and mediated-conflict neoinstitutionalism (MCN). It also identifies critical gaps and proposes avenues for future research.

Employing the B-SLR’s multi-method framework, this study integrates bibliometric analysis and a systematic literature review. The analysis examines 202 articles, categorizing them into four key research clusters related to the application of institutional theory to SMEs.

The literature on SMEs and institutional theory is framed around the following clusters: (1) institutional theory and innovation in SMEs, (2) institutional theory and the environmental sustainability of SMEs, (3) institutional theory and the internationalization of SMEs and (4) institutional theory and SME strategies in emerging markets.

This study represents the first literature review applying institutional theory to SMEs, offering a framework for understanding how institutional factors influence SME strategic decisions. The paper also identifies research gaps, proposing directions for future studies within each of the four clusters and contributes to bridging the fragmented research on SMEs and institutional theory.