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The development of complex products and systems is a continuously iterative process from customer requirements to a mature design. Design changes derived from multisources occur frequently during the design process. Furthermore, change propagation will impose impacts on design costs and lead times. In view of this, how to predict and control the propagation of multisource design change to reduce the changes impact is an urgent issue in the development of complex product.

In this paper, a new four-phase routing approach based on weighted and directed complex networks is proposed for multisource design change propagation. Phase I: as the foundation of this research, a product network model is established to quantify describe the complex product. Phase II: the hub nodes are identified based on the LeaderRank algorithm, which can be regarded as multisource nodes of design changes. Phase III: a calculation method for change propagation intensity is proposed, which improves the systematicness and accuracy of the evaluation results. In this paper, change propagation intensity is defined by four assessment factors: importance degree of parts, execution time of design tasks, coupling strength between parts and propagation likelihood. Phase IV: a routing method of multisource design change propagation and ant colony optimization algorithm are proposed in this paper, which can solve the coupling conflicts among change propagation paths and improve the search efficiency by using the parallel search strategy.

The proposed method and another method are used to search the optimal propagation path of multisource design change of a motorcycle engine; the results indicate that this method designed in this study has a positive effect on reducing the change impact, market response time and product design costs when design change occurs in the products design process.

The authors find a new method (a network-based four-phase routing approach) to search the optimal propagation path of multisource design change in complex products design.

The purpose of this paper is to report a study investigating the predictors of acceptance of multisource feedback (MSF) by managers. Specifically, it investigates the extent to which locus of control, cynicism and perceptions of procedural justice predicted acceptance by feedback recipients.

Quantitative data were analysed from 520 questionnaires completed by managers who participated in a multisource feedback programme as part of a leadership development process.

The study findings reveal that managers' perception of procedural justice was most significant in explaining variance in acceptance of MSF. Cynicism also explained significant variance in acceptance.

The findings highlight the importance of attending to procedural justice issues when implementing MSF. They also highlight the need to assess cynicism levels in the organisation.

The study combines variables not included in previous studies.

Benchmark surveys regarding talent management assessment practices and interventions of choice for organization development (OD) practitioners have shown 360-degree feedback to be a popular tool for both development and decision-making in the field today. Although much has been written about implementing 360-degree feedback since its inception in the 1990s, few longitudinal case examples exist where interventions have been applied and their impact measured successfully. This chapter closes the gap by providing research findings and key learnings from five different implementation strategies for enhancing 360-degree feedback in a large multi-national organization. Recommendations and implications for future research are discussed.

Organization development is focused on implementing a planned process of positive humanistic change in organizations through the use of social science theory, action research, and data-based feedback methods. The role of personality in that change process, however, has historically been ignored or relegated to a limited set of interventions. The purpose of this chapter is to provide a conceptual overview of the linkages between personality and OD, discuss the current state of personality in the field including key trends in talent management, and offer a new multi-level framework for conceptualizing applications of personality for different types of OD efforts. The chapter concludes with implications for research and practice.

Although research on multisource ratings indicates that different rater sources provide different information, little research has investigated how ratees attend to such information. Understanding how ratees attend to feedback information from different rater sources is important because such attention likely impacts subsequent behavior. Using a policy‐capturing design, managers (n = 213) completed scenarios in which supervisor, peer, and subordinate ratings were varied across different performance dimensions. Results indicated that ratees attended to all three rater sources, with supervisor ratings being attended to more than peer or subordinate ratings. Further, results indicated a significant interaction between rater source and performance dimension such that some rater sources were attended to more, for certain dimensions, than for others.

Part I of this research study identified the top five leadership deficiencies that confront managers in periods of rapid organizational change and transformation. This article aims to discuss the remainder of the top 10 leadership deficiencies and to provide a call to action for both individual leaders and professionals responsible for leadership training.

The leadership deficiencies were identified using a multisource feedback (MSF) methodology that was employed as a needs assessment tool which was a component of a formal leadership development program.

The leadership deficiencies include ineffective coaching/feedback and employee development practices, and ineffective problem‐solving and decision‐making practices.

This article provides a call to action for both individual leaders and professionals responsible for training and development of leaders needed for driving organizational change and improvement.

This article aims to report the results of a study concerning the key performance deficiencies found in leaders in rapidly changing organizations.

A sample of 153 middle and front‐line managers from a cross‐section of US manufacturing and service organizations were asked to assemble a multisource feedback (MSF) team consisting of five people who responded to the following question: “What specific things should this individual be working on to become more effective as a leader in their rapidly changing work situation?” In turn, 765 raters rated 153 middle and front‐line managers on their leadership performance deficiencies.

Data analysis indicated the top ten leadership performance deficiencies were: ineffective communication practices, poor time and priority management skills, failing to clarify direction and performance expectations, ineffective interpersonal/teaming skills, inability in handling stress/pressure and staying poised, ineffective coaching/feedback and employee development practices, poor planning skills, ineffective problem‐solving and decision‐making activities, ego issues and disorganization.

Based on these data, a series of leadership lessons for individual business leaders, organizations they serve and those responsible for the training and development of leaders are provided.

Followers’ affective commitment to change has been found to constitute a strong predictor of the success of change initiatives in organizations. Several studies have yet shown positive effects of transformational leadership on followers’ commitment to change. However, up to date there is no study examining the direct effects of different transformational leadership behaviors on followers’ commitment to change and the moderating impact of leaders’ commitment to change on these relationships. The paper aims to discuss these issues.

This study uses a cross-sectional, multilevel design based on multisource date from 38 teams from different organizations with a total of 177 participating team members. Data of leaders’ and followers’ commitment to change as well as ratings of transformational leadership behavior were captured applying a quantitative approach.

Results show a significant positive effect of the transformational leadership behavior “individual support” on followers’ affective commitment toward change. Moreover, the transformational leadership behavior “providing an appropriate model” was shown as only positively contributing to followers’ commitment to change when leaders’ own commitment toward change was high.

Due to the multilevel and multisource data, the sample is relatively small which limits the external validity of findings. Also, future studies should invest in longitudinal replication of relationships. Research on leaders’ and followers’ commitment to change should continue to develop more complete models of interacting influence factors.

For team leaders and organizations, results underline the importance of individual support of team members. Thus, leaders need to be enabled to invest individual leadership in the long run. Also, leaders need to become aware of their own commitment toward the change and, going beyond, need to develop a positive bond to the change if they want to be able to act as successful role models.

This paper contributes to existing literature by offering a more detailed insight for researchers and practitioners into the effectiveness of transformational leadership in change by exploring the impact of different transformational leadership behaviors effecting followers’ commitment to change. Moreover, it provides important knowledge about the relevance of leaders’ own commitment to change as a moderator of effective leadership in change.

The purpose of this paper is to describe a two‐level hierarchical control strategy for electrical energy transfers in multisource renewable energy systems. The aim of the control design is to perform the energy transfers, according to the sources power variations and the load characteristics.

The controller determines the operating mode of the multisource renewable energy system and the power ratio provided by each source to satisfy the load demand. The study is based on an accurate model of the DC/DC converters coupled on the DC bus. The performance of the controller is compared with the usual method based on the measurements of the system variables with sensors (solar radiation, shaft speed, voltages, and currents).

The proposed method does not need extra sensors to measure the available power for each source.

The method is developed for an hybrid system with two sources (photovoltaic and lead‐acid battery bank) and specific zero voltage switch full‐bridge isolated buck DC/DC power converters but can easily extended to more sources and other classes of DC/DC converters.

The method is assessed through computer simulations using a simple comprehensive model. An experimental device is also developed by the GREAH Research Group of University Le Havre (France). The GREAH also participates to a technologic centre with similar topology on the site of Fecamp (France).

The proposed autonomous control schema is suitable to control hybrid systems with several energy sources in remote areas.

The main contributions of this work are first to introduce a two stages controller and second to use the duty cycle value of the power converters as decision criteria to switch off/on the sources.

The multisource uncertainties, including material dispersion, load fluctuation and geometrical tolerance, have crucial effects on fatigue performance of turbine bladed disks. In view of the aim of this paper, it is essential to develop an advanced approach to efficiently quantify their influences and evaluate the fatigue life of turbine bladed disks.

In this study, a novel combined machine learning strategy is performed to fatigue assessment of turbine bladed disks. Proposed model consists of two modeling phases in terms of response surface method (RSM) and support vector regression (SVR), namely RSM-SVR. Two different input sets obtained from basic variables were used as the inputs of RSM, then the predicted results by RSM in first phase is used as inputs of SVR model by using a group data-handling strategy. By this way, the nonlinear flexibility of SVR inputs is improved and RSM-SVR model presents the high-tendency and efficiency characteristics.

The accuracy and tendency of the RSM-SVR model, applied to the fatigue life estimation of turbine bladed disks, are validated. The results indicate that the proposed model is capable of accurately simulating the nonlinear response of turbine bladed disks under multisource uncertainties, and SVR-RSM model provides an accurate prediction strategy compared to RSM and SVR for fatigue analysis of complex structures.

The results indicate that the proposed model is capable of accurately simulate the nonlinear response of turbine bladed disks under multisource uncertainties, and SVR-RSM model provides an accurate prediction compared to RSM and SVRE for fatigue analysis of turbine bladed disk.