Purpose: Kuwait has taken significant steps to reform its corporate governance (CG) by introducing the New Company Law (NCL) in 2013. This study investigates how this reform of CG mechanisms affects the disclosure of future-oriented information. Likewise, it explores how CG mechanisms affect the informativeness of this disclosure.Design/methodology/approach: The sample comprises the nonfinancial firms listed on the Boursa Kuwait from 2014 to 2018. The study uses an automated textual analysis to measure the level of future-oriented disclosure in the annual reports of these firms. The informativeness of disclosure is proxied by firm value at three months of the date of the annual report.Findings: The study finds that Kuwaiti firms with larger board sizes and substantial ownership by institutional investors are less likely to disseminate future-oriented information. Conversely, firms with more independent directors and larger audit committees are more inclined to provide future-oriented disclosure. Furthermore, the disclosure of future-oriented information carries contents that enhance investors' valuations of Kuwaiti firms, especially in firms with fewer institutional ownership and more prominent audit committees.Research limitations/implications: It focuses on management decisions to disclose information in the annual reports. Examining other channels of disseminating information, such as social media disclosure, provides avenues for future research.Practical implications: Policy setters in Kuwait should consider the importance of some CG mechanisms to improve the transparency of Kuwaiti firms, as suggested by the NCL. Likewise, investors should rely on such specific CG mechanisms to build their prospects about the firm's value.Originality/value: Apart from developed countries, the current study is the first evidence on how CG mechanisms could affect the informativeness of future-oriented disclosure in a developing economy. It is also the first to investigate the new CG mechanism introduced by Kuwait NCL in 2013.

This study probes the intersection of urbanization, environmental degradation, and corporate performance in China’s retail and automotive sectors. Utilizing data from 23 regions spanning 2000–2022, the research elucidates the impacts of urban growth, infrastructure development, and particulate matter 2.5 pollution (PM2.5) on these industries. The study uses panel data from 2000 to 2022 and the corresponding analytical random effect model, along with pre- and post-estimation tests for the main results. The findings reveal that while urban population growth bolsters retail sales, it adversely affects the automotive industry. Urban infrastructure does not influence conventional sectors, yet it negatively impacts online retail sales. PM2.5 pollution depresses retail and automotive sales but boosts online sales, underscoring the rising environmental consciousness among consumers. The urban population significantly moderates the relationship between PM2.5 pollution and sales across sectors, hinting at unique consumption patterns in populated urban areas. This study provides critical insights for policymakers aiming for sustainable economic growth, and encourages further research with more region-specific factors and extended time frames.

This study examines how stock markets dynamically adjust to armed-conflict announcements, moving beyond the conventional event-study focus on terminal cumulative abnormal returns. Using a nine-event archive covering conflict-related announcements between 2003 and 2022, we analyze 81 event–sector–measure trajectories for U.S.-listed firms in the aerospace and defense, oil and gas, and alternative energy sectors. The 2022 Ukraine event has observations through the [0,20] window but no [0,25] endpoint; accordingly, analyses requiring the 25-day endpoint use eight events and 72 series, whereas analyses that can accommodate the unequal trajectory lengths use all nine events and 81 series. Each trajectory captures cumulative abnormal performance across successive post-event windows, representing the timing, persistence, and direction of market adjustment. Dynamic time warping combined with average-linkage hierarchical clustering identifies three adjustment patterns: persistent amplification, transitory responses, and directional reversal. Persistent amplification characterizes 53% of trajectories, while 21% exhibit front-loaded responses that subsequently attenuate toward zero and 26% reverse direction over the post-event period. These classes are defined relative to the direction of the initial response and are sensitive to this normalization. The analysis further examines differences between conflict initiation and termination and across sectors. Given the limited number of independent conflict episodes, inference is conducted at the conflict level using exact permutation procedures and Bayesian hierarchical models with conflict-level random effects. In the eight-event endpoint sample, reversal is more frequent after conflict initiation than after termination (48.9% versus 14.8% of series), and the hierarchical model gives this difference a posterior probability of 0.974. The exact conflict-level test gives p = 0.071; no primary result survives a correction for multiple testing, and simulated power with eight conflicts is approximately one-half under the stated assumptions. The finding is therefore consistent in direction but statistically fragile. Reaction magnitude does not differ systematically by phase, and the timing and persistence of market responses vary considerably. These findings demonstrate that terminal event-study measures can mask economically distinct adjustment processes and highlight the value of modeling abnormal returns as dynamic trajectories.