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Although the significant performance implications of exploratory learning and exploitative learning have been well documented, the issue of whether they are complementarities or substitutes still remains a puzzle. This study investigates the relationship between exploratory learning and exploitative learning in different organizational structures. Based on a survey of Chinese firms, we find that exploratory learning and exploitative learning are substitutes when the organizational structure is mechanistic, and they are complementarities when the organizational structure is organic. Overall, this study joins the debate on the relationship between exploratory learning and exploitative learning by connecting different perspectives with the characteristics of organizational structure to offer a more comprehensive understanding on such an issue.

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Recently, the incidence of inflammatory bowel diseases, especially the Crohn's disease (CD) and gastrointestinal luminal tuberculosis (ITB), has grown rapidly worldwide. Currently there is no general gold standard to distinguish between CD and ITB tissues, which both have tuberculosis and surrounding fibrous structures. Mueller matrix imaging technique is suitable for describing the location, density and distribution behavior of such fibrous structures. In this study, we apply the Mueller matrix microscopic imaging to the CD and ITB tissue samples. The 2D Mueller matrix images of the CD and ITB tissue slices are measured using the Mueller matrix microscope developed in our previous study, then the Mueller matrix polar decomposition and Mueller matrix transformation parameters are calculated. To evaluate the distribution features of the fibrous structures surrounding the tuberculosis areas more quantitatively and precisely, we analyze the retardance related Mueller matrix derived parameters, which show clear different distribution behaviors between the CD and ITB tissues, using the Tamura image processing method. It is demonstrated that the Mueller matrix derived parameters can reveal the structural features of tuberculosis areas and be used as quantitative indicators to distinguish between CD and ITB tissues, which may be useful for the clinical diagnosis.