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The research study provides empirical insights on the relationship between entrepreneurial leadership (EL), entrepreneurial passion for founding (EPF), entrepreneurial bricolage (EB) and project success (PS), in the case of freelancers. The study aims to get a better understanding of whether freelancers, who behave like entrepreneurial leaders, can successfully complete projects through EB.

The study collected data from 209 freelancers through snowball sampling, in two waves, with a time-lag of fourteen days, to better examine the causality of variables. Data were analyzed by Model No. 4 and 7 (i.e. mediation and moderation, respectively) of Process macro.

Drawing on the effectuation theory, the results show that EB mediates the relationship between EL and PS and EPF moderates this relationship.

The freelancers can formally establish businesses later, after knowing whether they can complete these new types of projects. These online freelancing platforms can provide special services to freelancers who first want to test their skills on unrelated projects. In sum, the paper suggests that freelancers can be successful entrepreneurial leaders.

The EL, EPF, EB and PS are studied in the context of the informal sector, i.e. freelancing, which is the emerging working style in the world. It provides an in-depth understanding of phenomena in freelancers that lacks background literature.

We present an approach for pricing American put options with a regime-switching volatility. Our method reveals that the option price can be expressed as the sum of two components: the price of a European put option and the premium associated with the early exercise privilege. Our analysis demonstrates that, under these conditions, the perpetual put option consistently commands a higher price during periods of high volatility compared to those of low volatility. Moreover, we establish that the optimal exercise boundary is lower in high-volatility regimes than in low-volatility regimes. Additionally, we develop an analytical framework to describe American puts with an Erlang-distributed random-time horizon, which allows us to propose a numerical technique for approximating the value of American puts with finite expiry. We also show that a combined approach involving randomization and Richardson extrapolation can be a robust numerical algorithm for estimating American put prices with finite expiry.

This paper aims to verify whether the integration of sustainability in executive compensation positively affects firms’ non-financial performance and whether corporate governance characteristics enhance the relationship between sustainability compensation and firms’ non-financial performance and to expand the domain of the impact of sustainability on non-financial performance.

This analysis is based on a sample of companies listed on the Milan Italian Stock Exchange from the Financial Times Milan Stock Exchange Index over the 2016–2020 period. Regression analysis was used by using data retrieved from the Refinitiv Eikon database and the sample firms’ remuneration reports.

The findings of this paper show that embedding sustainability in executive compensation positively affects firms’ non-financial performance. The results of this paper also reveal that specific corporate governance features can improve the impact of sustainability on non-financial performance.

This analysis is limited to Italian firms included in the Financial Times Milan Stock Exchange Index; however, the findings are highly significant.

The findings provide regulators with useful insights for considering the integration of sustainability goals into executive remuneration. Another implication is that policymakers should require – at least – listed firms to fulfil specific corporate governance structural requirements. Finally, the findings can provide investors and financial analysts with a greater awareness of the role played by executive remuneration in the long-term value-creation process.

This paper contributes to addressing the relationship among sustainability, remuneration and non-financial disclosure, drawing on the stakeholder–agency theoretical framework and focusing on Italian firms. This issue has received limited attention with controversial results in the literature.

The purpose of this paper is to investigate and quantify the impact of product complexity, including architectural complexity, on operator learning, productivity and quality performance in both assembly and disassembly operations. This topic has not been extensively investigated in previous research.

An extensive experimental campaign involving 84 operators was conducted to repeatedly assemble and disassemble six different products of varying complexity to construct productivity and quality learning curves. Data from the experiment were analysed using statistical methods.

The human learning factor of productivity increases superlinearly with the increasing architectural complexity of products, i.e. from centralised to distributed architectures, both in assembly and disassembly, regardless of the level of overall product complexity. On the other hand, the human learning factor of quality performance decreases superlinearly as the architectural complexity of products increases. The intrinsic characteristics of product architecture are the reasons for this difference in learning factor.

The results of the study suggest that considering product complexity, particularly architectural complexity, in the design and planning of manufacturing processes can optimise operator learning, productivity and quality performance, and inform decisions about improving manufacturing operations.

While previous research has focussed on the effects of complexity on process time and defect generation, this study is amongst the first to investigate and quantify the effects of product complexity, including architectural complexity, on operator learning using an extensive experimental campaign.