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Because of the key role of joint torque in industrial robots (IRs) motion performance control and energy consumption calculation and efficiency optimization, the purpose of this paper is to propose a deep learning torque prediction method based on long short-term memory (LSTM) recurrent neural networks optimized by particle swarm optimization (PSO), which can accurately predict the the joint torque.

The proposed model optimized the LSTM with PSO algorithm to accurately predict the IRs joint torque. The authors design an excitation trajectory for ABB 1600–10/145 experimental robot and collect its relative dynamic data. The LSTM model was trained with the experimental data, and PSO was used to find optimal number of LSTM nodes and learning rate, then a torque prediction model is established based on PSO-LSTM deep learning method. The novel model is used to predict the robot’s six joint torque and the root mean error squares of the predicted data together with least squares (LS) method were comparably studied.

The predicted joint torque value by PSO-LSTM deep learning approach is highly overlapped with those from real experiment robot, and the error is quite small. The average square error between the predicted joint torque data and experiment data is 2.31 N.m smaller than that with the LS method. The accuracy of the novel PSO-LSTM learning method for joint torque prediction of IR is proved.

PSO and LSTM model are deeply integrated for the first time to predict the joint torque of IR and the prediction accuracy is verified.

This paper aims to examine how channel whistleblowing intensity affects a distributor’s compliance to the manufacturer’s request and how that impact is influenced by institutional environments.

Based on paired survey data, which was collected from an automobile manufacturer in China and its 211 distributors, combined with secondary data, this study used hierarchical regression analyses to test the hypotheses.

The study finds that channel whistleblowing intensity has an inverted U-shaped effect on distributor compliance. In addition, this curvilinear effect is stronger in regions with more effective legal systems and higher social trust, but the authors do not find perceived vertical control moderating the effect of whistleblowing intensity on distributor compliance.

First, this study enriches the marketing literature by highlighting the significance of whistleblowing and especially its downside in marketing channel management. Second, moving beyond prior marketing studies’ focus on bilateral controls, it recognizes channel whistleblowing as a peer-enforced control mechanism. Third, it identifies environmental factors as shift parameters that alter the impact of channel whistleblowing, attesting to the importance of “discriminating alignment.”

The findings caution channel managers against the double-edged effects of whistleblowing and inform the conditions that amplify this impact.

This work highlights the bright and dark sides of channel whistleblowing and uncovers situations in which it works or fails to promote distributor compliance.

Transport megaprojects often struggle to offer social value (SV) that meets local communities' needs. This problem is embedded in how local communities' views are captured and incorporated into SV plans through local community engagement (LCE). By problematising the literature, this article aims to identify LCE issues and their impacts on SV plans at the front-end of transport megaprojects.

The theoretical lens of the study is the practice theory developed by Schatzki (2016, 2005). The authors conceptualised LCE as a practice and conducted 32 semi-structured interviews with UK practitioners. The authors collected data in three steps from three types of practitioners involved in LCE practice and SV planning: project managers, LCE experts and SV experts.

The authors identified 18 LCE issues with thematic analysis and clustered them into five themes. These issues impact LCE with five mechanisms. Findings show that a weak link between LCE and SV plans due to the issues reduces LCE to a tick-box exercise and presents a distorted view of local communities. This reduces SV plans to the bare minimum for project approval instead of offering relevant SV to local communities. Addressing the issues goes beyond changing the approach of project teams to engagement (from instrumental to normative) and requires changing the practices.

For the first time, the study uses practice theory to conceptualise LCE as a practice, following the notion of project as practice. The study problematises the literature to address the under-represented link between LCE and SV plans.