Measurement of environmental and energy economics presents an analytical foundation for environmental decision making and policy analysis. Applications of data envelopment analysis (DEA) models in the assessment of environmental and energy economics are increasing notably. The main objective of this review paper is to provide the comprehensive overview of the application of DEA models in the fields of environmental and energy economics. In this regard, a total 145 articles published in the high-quality international journals extracted from two important databases (Web of Science and Scopus) were selected for review. The 145 selected articles are reviewed and classified based on different criteria including author(s), application scheme, different DEA models, application fields, the name of journals and year of publication. This review article provided insights into the methodological and conceptualization study in the application of DEA models in the environmental and energy economics fields. This study should enable scholars and practitioners to understand the state of art of input and output indicators of DEA in the fields of environmental and energy economics.

Impacts of harmonics on step-down transformer are presented in this paper. Transformer failure had been reported due to harmonic current causing excessive winding temperature rise. Excessive temperature rise of transformer is due to harmonic effect result in higher power loss than normal operating mode. An experimental setup is proposed which allow for observation of harmonics. This research focuses on the transformer losses under nonlinear load with different power consumption. Moreover, the trends of Total Harmonic Distortion (THD) with nonlinear load are reported.

This paper provides a conceptual architecture for a cloud based platform design, that implements continuously data storage and analysis services for large maritime ships, with the purpose to provide valuable insights for maritime transportation business. We do this by first identifying the need on the shipping market for such kind of systems and also the significance and impact of different factors related to shipping business processes. The architecture presented throughout this paper will be defined around some of the most currently used ICT technologies, like Amazon Cloud Services, Sql Server Databases, .NET Platform, Matlab 2016 or javascript visualization libraries. The proposed system makes possible for a maritime company to gain more knowledge for optimizing the efficiency of its operations, to increase its financial benefits and its competitive advantage. The platform architecture was designed to make possible the storage and manipulation of very large datasets, also allowing the possibility of using different data mining techniques for inferring knowledge or to validate already existent models. Ultimately, the developed methodology and the presented outcomes demonstrate a vast potential of creating better technological management systems for the shipping industry, starting from the challenges but also from the huge opportunities this sector can offer.

The major goal of knowledge management (KM) is to enhance innovation. Previous research on innovation andknowledge management has shown a positive relationship between innovation and effective knowledgemanagement (Smith et al., 2005; Darroch & McNaughton, 2002; Dougherty et al., 2002; Nonaka & Takeuchi,1995). Some scholars have maintained that the innovation that accelerates creative solutions depend greatly onthe accumulation of new knowledge in an organization. Knowledge accumulated is the organization isessentially utilized by people via four major knowledge management processes. Unfortunately, KM literatureoverpraises the technological aspects neglecting the people dimensions and the soft aspect of people whoactually possess the knowledge that could spark innovation. In a bid to fill this void, this paper contributions toknowledge by considering the need for a theoretical model of the attitudinal and behavioural conditions of theemployees who engage in knowledge management processes to push the boundaries of their firm’s innovationcapabilities.

Purpose: This paper investigates the role of patron dining experience (PDE) and emotions on relationship quality in the chain restaurant industry.Design/methodology: Stratified random sampling method was used where questionnaires were distributed to the respondents in 16 selected ‘Kopitiam’ outlets throughout Malaysia. The empirical findings from 316 customers of those outlets were examined using Partial Least Squares (PLS).Findings: The findings provide strong evidence of the relationships between PDE and emotions with relationship quality, where relationship quality in turn is an essential determinant of customer loyalty.Research limitations/implications: The sample of this study was obtained from a single local chain restaurant in Malaysia.Practical implications: The findings of this study highlighted the importance for service firms, generally those in the restaurant industry to strengthen the relationship with their customers in pursuit of better competitive advantage and long-term profit.Originality/value: This study contributes to theoretical knowledge by providing an empirical study on the effect of emotions construct towards the formation of relationship quality within the hospitality industry context.