The photovoltaic performance of Sb2Se3‐sensitized heterojunction solar cells, which were fabricated by a simple deposition of Sb2Se3 on mesoporous TiO2 by an approach that features multiple cycles of spin coating with a single‐source precursor solution and thermal decomposition, is reported. Poly[2,6‐(4,4‐bis(2‐ethylhexyl)‐4H‐cyclopenta[2,1‐b;3,4‐b′]dithiophene)‐alt‐4,7(2,1,3‐benzothioadiazole)] was used as the hole‐transporting material. The most efficient cell exhibited a short‐circuit current density of 22.3 mA cm−2, an open‐circuit voltage of 304.5 mV, and a fill factor of 47.2 %, yielding a power conversion efficiency of 3.21 % under standard test conditions (irradiation of 1000 W m−2, air mass=1.5 G). The results of this study imply that the developed approach has a high potential as a simple and effective route for the fabrication of efficient and inexpensive solar cells.

Despite an enduring interest in emotional labor, the effects of social capital on the emotional regulation process remain relatively underexplored. Using the job demands-resources model, we propose that social capital provides employees with the job resources required for deep acting. We also propose a double-mediation effect of deep or surface acting and job engagement, through which employee social capital can increase organizational citizenship behavior (OCB). Empirical results using data from 330 employees selling financial or insurance products in South Korea support our hypotheses that deep acting by sales employees and job engagement sequentially mediate the positive relationship between social capital and OCB.

The purpose of this study is to examine the unexplored mechanisms through which employee job performance is affected by compassion experienced at work. While the relationship between compassion and job performance is relatively well established in the literature, our knowledge of the actual mechanisms underlying this relationship is still in a nascent state. In this study, we propose two paths through which increased job performance results from workplace compassion. Our empirical results, obtained through 360 full-time employees including 182 males and 178 females working in South Korea, provide support for the serial double mediation effects of positive work-related identity and collective self-esteem in the positive relationship between compassion experienced at work and job performance. In addition, the positive relationship between workplace compassion and job performance is mediated by positive psychological capital.

The positive relationship between leader behavioral integrity and an employee’s in-role performance is well-established, but explanations for why this effect exists are still in a nascent stage. Drawing upon leader behavioral integrity theory and job-demands resources theory, the authors explain how leader behavioral integrity facilitates employee in-role performance and the boundary conditions influencing the relationship between leader behavioral integrity and employee in-role performance. Using multisource data from 209 employee-manager dyads in South Korea, this paper found support for the mediating effect of coworker support in the positive relationship between leader behavior integrity and employees’ in-role autonomy. Furthermore, compared to those who perceive low job autonomy, the positive indirect effect of leader behavioral integrity on in-role performance via coworker support was stronger for employees who perceive high job autonomy. The findings emphasize the importance of a leader’s individual difference (i.e., leader behavioral integrity) and job resources (i.e., job autonomy) facilitating the receipt of team members’ supporting behaviors which, in turn, energize employee in-role performance. Theoretical and practical implications are discussed.

In this paper, we present techniques for automatically classifying players and tracking ball movements in basketball game video clips under poor conditions, where the camera angle dynamically shifts and changes. In the core of our system lies Yolo, a realtime object detection system. Given the ground truth boxes collected by our data specialists, Yolo is trained to detect the presence of objects in every video frame. In addition, Yolo uses Darknet that implements convolution neural networks to classify a detected object to a player and to recognize its jersey numbers of specific movements. By identifying players and ball possessions, we can automatically compute ball distributions that are reflected on complex networks. With original Yolo system, player movement can be interrupted, when the players move out of the frame due to camera shift and when players overlap each other on a two-dimensional frame. We have adapted Yolo to keep track of players even under such poor condition by considering contextual information available from the framework preceding and/or succeeding problematic video frames. In addition to the novel movement inference method, we provide a framework for analyzing the pass networks in various perspectives to help the managing staff to reveal critical determinants of team performance and to design better game strategies. We assess the performance of our system in terms of accuracy by making a comparison with the analytical reports generated by human experts.INDEX TERMS Sports analytics, object detection, complex networks, deep learning, video processing.