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This study aims to evaluate the presence of abnormal returns due to stock splits or reverse stock splits in the Brazilian capital market context.

The event study technique was used on data from 518 events that occurred in a 30-year period (1987–2016), comprising 167 stock splits and 351 reverse stock splits.

The results revealed the occurrence of abnormal returns around the time the shares began trading stock splits or reverse stock splits at a statistical significance level of 5%. The main conclusion is that stock split and reverse stock split operations represent opportunities for extraordinary gains and may serve as a reference for investment strategies in the Brazilian stock market.

This study innovates by including reverse stock splits, as the existing literature focuses on stock splits, and by testing two distinct “zero” dates that of the ordinary general meeting that approved the share alteration and the “ex” date of the alteration, when the shares were effectively traded, reverse split or split.

This paper aims to examine two indirect mechanisms through which employees' perceptions of high-performance work systems (HPWS) foster employees' innovative behaviour (IB). Particularly, this study analyses the sequential mediating role of work engagement and knowledge-sharing in this relationship at the individual level.

Using researchers and professors working at a Spanish state university as an empirical sample and applying partial least squares structural equation modelling (PLS-SEM), the authors test hypotheses regarding the impact of the indirect and sequential effect of engagement and knowledge-sharing on the relationship between employees' perceptions of HPWS and IB.

Findings indicate the existence of a sequential mediating effect of work engagement and knowledge-sharing. The authors' results suggest that the existence of engagement is necessary for the influence of HPWS on IB to become effective.

The authors' results also highlighted the importance of suitable design and implementation for HPWS so that employees feel motivated and dedicated to their work.

The authors' findings contribute to the understanding of the mechanisms by which HPWS enhance employees' IB, and the results are especially salient in advancing the theoretical understanding of how HPWS, engagement and knowledge-sharing are relevant variables for IB.

本文擬探討兩個間接機制,透過這兩個機制,僱員對高績效工作系統的看法,會促進其創新行為。具體地說,本文擬分析在個人層面上,工作參與和知識共享在高績效工作系統與創新行為之間的關係中所扮演的有序中介角色 。

我們以於一所西班牙州立大學工作的研究人員和教授為實證樣本,並使用偏最小平方法的結構方程模型 (PLS-SEM) 來進行研究。研究乃對一些假設進行試驗。這些假設,是關於工作參與和知識共享對高績效工作系統與創新行為之間關係的間接順序效應之影響。

研究結果顯示、工作參與和知識共享有其有序的中介效應。

我們的研究結果暗示、若要使高績效工作系統能有效地影響創新行為,工作參與是不可或缺的。

研究結果也強調了若要僱員盡心盡力、抱有積極的工作態度,企業必須設計合適的高績效工作系統,並予以有效的執行。

本研究的結果,幫助我們了解高績效工作系統能增強僱員創新行為的機制; 更重要的是,研究結果促進了我們對高績效工作系統、工作參與和知識共享作為創新行為的相關變數的理論理解。

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.