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Megaprojects have large impact on the environment and stakeholders should take collective action to ensure that these projects are developed in a socially responsible manner. Hitherto, it is not known whether group and subjective norms and social identity could compel stakeholders to take socially responsible collective actions in megaprojects. The aim of this study is to design and test a model to boost stakeholders' intention to take socially responsible collective action in the context of mega water transfer projects in China.

A quasi-experimental causal research design was adopted to establish cause–effect relationships among the dependent variable (we-intention) and independent variables (subjective norms, group norms, social identity and desire). This study adopts the belief–desire–intention model and social influence theory to empirically investigate how to boost the stakeholders' intention to participate in socially responsible collective action. An online questionnaire survey was conducted and data was collected from 365 respondents who were involved in mega water transfer projects in China. The partial least squares structural equation modeling technique was employed to analyze the data.

The results from partial least squares analyses indicate that the presence of subjective norms, group norms and social identity (collectively known as social influence process) could increase stakeholders' intention to take socially responsible collective action. In addition, the desire to be socially responsible also boosts stakeholders' intention to take collective action. Desire partially mediates the relationship between social influence process and intention to take socially responsible collective action.

This study adds to existing knowledge by discovering social influence process as an antecedent to taking socially responsible collective action in megaprojects. Strong group norms and subjective norms could propel stakeholders to be more socially responsible. The study also adds to knowledge by discovering that stakeholders' desire to fulfill social responsibility also leads them to take concrete actions. Implications and recommendations are provided on how to manipulate different types of social influence processes to facilitate stakeholders to adopt socially responsible collective action in the process of managing megaprojects.

This research aims to analyzes how megaproject top managers engaged in stewardship behaviors. Studying megaprojects from the micro-foundations rooted in individual action and interaction, this research examines the gaps between literature and top managers' positive behavior to challenge the current theoretical underpinnings of megaproject governance research and practice.

An extensive literature review was performed in the initial phase. Then, a case study of South-to-North Water Diversion project was conducted based on following this project and on access to its top executives. Data was collected from multiple sources and analyzed by Nvivo (version 12). Further analysis was then carried out in two stages to identify megaproject stewardship behavior and related governance patterns.

Results show that stewardship behavior is prevalently existing and is possibly to be identified through psychological, situational, relational dimensions. Also, 16 factors have been found to describe the precise nature of megaproject stewardship behavior. Further explorative findings were discussed from three perspectives: possible theoretical development, self-actualization motivation and temporalities of megaprojects.

Building upon the ideas on how to extend steward theory towards project field, this research conducts a first exploration of stewardship behavior in megaprojects. This study contributes to complement the research into top-level organizational behavior in megaprojects, and it provides helpful implications for how to govern top managers in the following megaprojects with the cooperative spirit that can be valued by megaproject stakeholders.

This paper aims to present a novel robust control method based on an adaptive PI controller (APIC) to compensate for different disturbances and unknown dynamics for multi-phase induction machines.

The gains of the APIC are adapted online according to the tracking error. Proposed APIC is accompanied with designed linear disturbance observer (LDO) to present robust behavior to machine parameter variations and fault disturbances.

The results show remarkable dynamic performance in both healthy and faulty conditions when the six-phase induction machine works under APIC and LDO schemes.

The proposed controller need not readjust current controllers for the post-fault condition. The developed Simulink model efficiency is confirmed through experimental tests.