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The employees’ need of appreciation emerges in the form of rewards, empowerment and training, the supply of which fuels up performance of employees gaining indirectly by the organization through the interactive organizational practices grooming their skills which is tested and hypothesized many times. This study contributes by taking into account the inclusion of Creative Performance along with the other tested performance levels and also tests the mediating role of Work Engagement in the established relationships. This study helps in establishing this unique relationship observing the role of mediation also. The effects are analyzed with SPSS (21) and AMOS with Structural Equation modeling. Data is gathered from frontline employees of 06 cities of the Bahawalpur Division in Pakistan. The results show that rewards, empowerment and training foster Work Engagement that in turn elevates levels of Performance of Hotel Industry employees. The findings of this study will rebound to the benefit of the organizations regarding the success factors of their employees at workplace as they can get novelty of service ideas through employees. Its implementation will ultimately result in HR techniques to be adopted to achieve higher levels of performance in future. There are many other High-Performance tools like, Realistic Job Previews, Innovation Programs and Performance based Pay. Future studies can be conducted to assess the impact of these factors also. In addition, some psychological constructs may be included to enhance its area of application and know underlying reasons of divert behaviors. There are many other High-Performance tools like, Realistic Job Previews, Innovation Programs and Performance based Pay. Future studies can be conducted to assess the impact of these factors.

Food waste reduction have global attention by promoting suboptimal food. The purpose of the study is to develop an extended Theory of Planned Behavior (TPB) research model, which includes price consciousness and environmental concern to predict suboptimal food purchase intention. The data was collected through survey (paper and online based) from grocery consumers. In total, 420 respondents were from cities of southern Punjab Pakistan namely Multan, D G Khan, Bahawalpur, and Rahim Yar khan. SPSS 22 was used to analyze data. The findings revealed that the constructs of TPB, such as attitude (ATT), subjective norms (SN) and perceived behavioral control (PBC) have significant effect on consumer purchase intention (PI). Consistently, price consciousness (PC) and environmental concern have positive affect on consumer purchase intention (PI). The findings add to the growing body of knowledge about suboptimal food purchase intentions, especially in developing nations like Pakistan. For marketers, and sellers the findings have both theoretical and practical implications.

The content-based image retrieval (CBIR) based on sparse visual features is a challenging research problem to categorize images into semantically meaningful classes. Different robust feature representation methods have been proposed to address the semantic gap issue of CBIR. In this article, we propose a novel robust image representation for CBIR, which is based on complementary visual words integration of speeded up robust features (SURF) and co-occurrence histograms of oriented gradients (CoHOG). The SURF is a local feature descriptor, while CoHOG is a global feature descriptor. The local features give better performance for images belonging to different semantic classes and having close visual appearance among their visual contents, while global features give better performance to retrieval images at large scale. To ensure image retrieval accuracy, the proposed method build two smaller size dictionaries, each containing visual words of SURF and CoHOG descriptors, which are assimilated to form one larger size dictionary. In the CBIR system, a dictionary of smaller size produces better sensitivity, while a dictionary of larger sizes produces better specificity. The dictionary of the larger sizes also yields an overfitting problem to affect CBIR performance, which is addressed by introducing a linear discriminant analysis (LDA) and relevance feedback with the proposed method. The comparative performance analysis of the proposed method is performed with the competitor CBIR methods (i.e., feature integration of SURF–CoHOG descriptors’ based on the bag-of-visual-words (BoVW), a single feature of SURF–BoVW and CoHOG–BoVW methods). The quantitative and qualitative analysis carried out on four standard image databases proves the robust performance of the proposed method as compared to its competitor and recent CBIR methods.