The COVID-19 pandemic has forced the government to close the educational institutions globally, to contain the infection of the disease, which has affected the academic activities of local and international students significantly. This unexpected shift from offline classes to online learning has created psychological disruption among the students. At that backdrop, this study aims to investigate the influence of e-learning and emotional intelligence (EI) on the study stress, burnout, and performance of Pakistani students by applying emotion regulation theory. The data (N = 387) is based on international students, enrolled in 10 different universities in China. The results indicate that both e-learning and EI have significantly affected perceived study stress, burnout, and performance of students. These findings have provided evidence that online classes and EI can influence study stress, burnout, and performance of students. The study concludes that EI has significant impact on the psychological pressure of a student.

Overlapping between development activities stemming from concurrent engineering may not only reduce duration of a project but also create rework risk. This article presents a process modeling and analysis technique for managing complex product development projects using optimization and simulation techniques. In order to analyze the forced overlapped process with lead–risk, we propose evolution and sensitivity design structure matrix for reflecting overlapping and their impact on the degree of activity sensitivity and evolution in the process model. Using the design structure matrix, we present the schedule and cost model associated with iteration, overlapping, and rework by incorporating many more general characteristics of complex design processes. The model can be used for better project planning and control by identifying overlapping and risk for process improvements, and for evaluating alternative planning and execution strategies. An industrial example, a tactics aerocraft preliminary development design process at a company, is provided to illustrate the utility of the model using optimization and discrete-event simulation. The optimization model maximizes the compressed time associated with overlapping and yields several managerial insights, including optimization analysis of project activity sequence, how overlapping and rework risk impact on project schedule and cost, trading off schedule and cost risk.

In product development (PD) organizations, coordinating technical dependencies among teams with different expertise in overlapping processes is a fundamental challenge. This article takes a more sophisticated approach than prior methodologies to improve coordination via organizational clustering, by accounting for both team structural and attribute similarity from the perspective of social network analysis. We built models to quantify the impact of the overlapping processes on the interaction strength among PD teams, which we then used to construct structural similarity by combining tie strength and social cohesion among teams via the design structure matrix. To evaluate the organization network, we propose social embeddedness-related centrality indices within (intracluster) and across (intercluster) team groupings. To facilitate knowledge sharing, we base team attribute similarity on product- and process-related expertise among teams. We integrate the modularity index and an improved silhouette index to find an optimal number of clusters, which we then incorporate with team similarity measures as inputs to a spectral clustering algorithm. An industrial example illustrates the proposed model. The clustering results reinforce several managerial practices but also yield new insights, such as how to measure similarity among teams based on organizational network characteristics and how structural and attribute similarities impact the optimal organizational structure.

In today’s dynamic and global landscape, innovation and globalization are intricately linked drivers that propel modern businesses forward, serving as indispensable pillars upon which organizations heavily rely to maintain their competitive edge. Leveraging innovation within the context of global product development (GPD) practices is imperative for organizations seeking to survive and effectively compete in the rapidly evolving marketplace. While preceding studies have primarily focused on the importance of individual and organizational capabilities, policies, and cultural factors in driving product development (PD) performance, they often overlook their interconnectedness within a global context. To address this gap, this study delves into the relationship between organizational factors and global product development performance (GPDP) while examining the moderating influence of global innovation culture (GIC). These organizational factors encompass technological innovation capabilities (TICs), team creativity (TC), dynamic capabilities (DCA), and competitive advantage (CA). Our hypothesis suggests a positive impact of these factors on GPD performance. Employing a structural equation modeling (SEM) approach through SMART-PLS 3, we analyzed data collected from 480 questionnaire forms distributed among registered global product development (GPD) organizations operating in China. The empirical findings underscore the significant influence of organizational factors on GPD performance, highlighting the critical role of global innovation culture in shaping these relationships. These insights shed light on the importance of establishing a harmonious balance between organizational culture and various factors to enhance interaction among organizational elements and optimize global product development performance. Ultimately, these efforts can lead to improvements in the overall effectiveness and sustained global product development.

Although the e-commerce market is expanding rapidly, e-commerce platforms still capture only a small portion of the overall market, largely due to the limited habitual use of these platforms. This study examines the features that affect purchase intention when using an e-commerce channel. The Unified Theory of Acceptance and Use of Technology (UTAUT) serves as the theoretical aspect of the analysis. A survey was conducted, and the data were examined using structural equation modeling. The findings show that both performance expectancy and social influence have a strong positive impact on users’ purchase intention on new e-commerce platforms, whereas perceived risk negatively influences purchase intention. Perceived trust mediates the relationship between performance expectancy and purchase intention, social influence and purchase intention, and perceived risk and purchase intention. Furthermore, product quality perception moderates the connection between perceived trust and purchase intentions.