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This study aims to analyze the factors that drive or prevent interorganizational data sharing in the context of digital transformation (DT). Data sharing appears as a precondition for companies to capture emerging opportunities in supply chain management and for product-related servitization; however, there are ongoing concerns, and data are often perceived as the “new oil.” It is thus important to gain a better understanding of the determinants of firms’ decisions.

The authors develop an embedded case study analysis involving 16 firms within an extended supply network in the automotive industry. The authors focus on the peculiarities of the new context, as opposed to elements highlighted by research prior to the advent of the latest technologies. Abductive reasoning is applied to the theoretical foundations of the resource-based view, resource dependence theory and the complex adaptive systems perspective.

Data sharing is largely underpinned by factors identified prior to DT, such as data specificity, dependence dynamics and protection mechanisms and the dynamism of the business context. DT, however, can influence the extent of data sharing. New factors concern complementarities whenever data are pooled from different sources and digital platforms, as well as different forms of data ownership protection.

This study stresses that data sharing in the context of DT can be explained through established theoretical lenses, providing the integration of elements accounting for new technological opportunities.

Existing literature demonstrates the important role of information transparency in enterprise development and market surveillance. However, little empirical research has examined the information transparency effect in supply chain management. This study aims to fill this gap by exploring the significant role of information transparency on supply chain financing and its mechanism, taking trade credit as the starting point.

From the data set comprising 3,880 Chinese firms with A-shares listed on the Shenzhen and Shanghai Stock Exchanges from 2011 to 2020, we obtain the basic picture of information transparency and trade credit. Panel fixed effects regression is used to test the hypotheses concerning the antecedents to trade credit.

The empirical results show that: first, information transparency can significantly support corporate access to trade credit and is found to facilitate financing by mitigating perceived risk. Second, among companies with higher levels of financing constraints, weaker market power and more concentration of suppliers, information transparency promotes trade credit more markedly. Third, the outbreak of COVID-19 causes a substantial increase in uncertainty and risk in external circumstances and then the effect of information transparency is weakened. Fourth, the contribution to trade credit is likely to be stronger for disclosures containing management transparency elements compared to single financial transparency.

To the best of our knowledge, this study is one of the first to explore the positive role of information transparency to supply chain financing, which to a certain extent makes up for the lack of information transparency research in the supply chain. It provides new ideas for enterprises to obtain trade credit financing and promote the improvement of supervision departments’ disclosure policies.

While existing research explores the impact of audit market competition on audit fees and audit quality, there is limited investigation into how competition in the audit market influences auditors' writing style. This study examines the relationship between audit market competition and the readability of audit reports in Iran, where competition is particularly intense, especially among private audit firms.

The sample comprises 1,050 firm-year observations in Iran from 2012 to 2018. Readability measures, including the Fog index, Flesch-Reading-Ease (FRE) and Simple Measure of Gobbledygook (SMOG), are employed to assess the readability of auditors' reports. The Herfindahl–Hirschman Index (HHI) is utilized to measure audit market competition, with lower index values indicating higher auditor competition. The concentration measure is multiplied by −1 to obtain the competition measure (AudComp). Alternative readability measures, such as the Flesch–Kincaid (FK) and Automated Readability Index (ARI) are used in additional robustness tests. Data on textual features of audit reports, auditor characteristics and other control variables are manually collected from annual reports of firms listed on the Tehran Stock Exchange (TSE).

The regression analysis results indicate a significant and positive association between audit market competition and audit report readability. Furthermore, a stronger positive and significant association is observed among private audit firms, where competition is more intense compared to state audit firms. These findings remain robust when using alternative readability measures and other sensitivity checks. Additional analysis reveals that the positive effect of competition on audit report readability is more pronounced in situations where the auditor remains unchanged and the audit market size is small.

This paper expands the existing literature by examining the impact of audit market competition on audit report readability. It focuses on a unique audit market (Iran), where competition among audit firms is more intense than in developed countries due to the liberalization of the Iranian audit market in 2001 and the establishment of numerous private audit firms.

In this study, the authors explore the association between employee education level and the efficiency of corporate investment using data from a sample of Chinese listed firms during the period from 2011 to 2018. By examining the impact of education on investment efficiency, the authors' study provides valuable insights that contribute to a deeper understanding of the underlying economic mechanisms related to education.

The authors conduct multivariate regression analyses to examine the relationship between investment efficiency (following Richardson, 2006) and the level of employee education, along with a series of control variables. To ensure the reliability of the authors' findings, the authors subject the their results to a comprehensive set of robustness tests, such as a staggered difference-in-difference (DiD) regression approach, an instrumental variable (IV) method and the use of alternative employee education level and investment efficiency measurements.

The findings offer compelling evidence that higher levels of education have a positive impact on firms' investment efficiency, and this effect remains robust across various model specifications and endogeneity considerations. Moreover, the influence of education is more pronounced in firms that prioritize employee training, maintain effective internal communication and offer attractive financial rewards. Furthermore, the results suggest that the relationship between education and investment efficiency is influenced by the firms' business nature and competitive environment. Factors such as business complexity, labor intensity and business location also play a role in shaping the impact of education on investment outcomes.

The study emphasizes the crucial role of education in influencing investment decisions and performance within firms. By delving into this previously unexplored area, the authors' research contributes to the existing literature, establishing that the level of employee education is a significant determinant of corporate investment efficiency. This valuable insight has substantial implications for firms aiming to enhance their investment decision-making processes and overall performance. Understanding the positive impact of education on investment efficiency can empower organizations to leverage their human capital effectively and achieve better investment outcomes, ultimately contributing to long-term success and competitiveness in the market.