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Globally, the challenges of the oil and gas industry are unique due to the nature of its operations that is full of risks. Issues like volatile market prices, health and safety, environmental performance and high cost of production are affecting the operational performance of the sector. These problems if left unchecked could change the level of production and revenue generation to the Malaysian government and would as well influence the country's regional position in oil and gas production. As a result, many oil and gas firms including PETRONAS adopted operational excellence strategy, but some of the challenges kept re-occurring. It is against this circumstance that this research is aimed at determining the effect of enterprise risk management determinants on operational excellence in the Malaysian oil and gas industry. It is also aimed at exploring the mediating effect of enterprise risk management implementation on such a relationship. The article used a conceptual approach where journal articles, conference papers, professional reports, thesis and term papers were reviewed. Conceptual and theoretical frameworks were proposed in this paper, and literature was reviewed to lay a foundation for empirical research that would establish the relationship between the postulated variables in the study. Dimensions and measurement of the variables in the current study were drawn from earlier researches and recommendations. However, data were not collected, and a result of the analysis was not presented in the paper.

The new technology paradigm of big data captured by flooded data from billion devices is the hottest buzzword trending in this 21st century. Big data is generated of data at high volume, high velocity, and in a variety of format that is complex (veracity) which necessitates analytical procedures and active management of data to extract meaningful insights. Similarly, big data is also known as a game-changer proficient of transforming the way businesses operate in different organisation for sustainable competitive advantage. This paper introduces an integrated overview of big data technology in the higher education sector and discusses how the application of big data analytics can create value for Higher Education Institutions to sustained competitive advantage. As the education sector is operating in an increasingly complex and competitive environment, given the growing advantage of the educational institutions as one of the sources of revenue that boost the economy.

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Abstract-Due to the increasing of global competitive pressure, shortened product life cycles and ease of imitation, organizations must continue to innovate to ensure the organization sustainability. One of the major factors contributing to organization sustainability is innovation. Previous studies have shown significant impact of organizational innovation capabilities on product and service quality. Literature has identified various types of innovation in organization. Among them are business innovation capabilities and technological innovation capabilities. In the Malaysian context, business and technological innovation capabilities-related research, particularly among food SMEs are still not comprehensive. Many studies have overlooked at the process of successful TIC building in the industrialization of developing countries. To address the gap, this current empirical research identifies the relationship of BIC and TIC components at 30 Malaysian food SMEs in northern area. Using case study approach, the questionnaires were distributed among the top and middle management level staff. A total of 30 respondents involved in the survey. Data were analyzed using descriptive and inferential techniques. The study found that, BIC and TIC have moderate relationship on organizational performance. Business innovation capability was found to have the most influential impact. The findings could help food SMEs particularly in order to increase the level of innovation. The paper finalizes with some conclusions for industry and other actors, and also future research.

Abstract. In today's highly competitive market, the demand for quality is the single most critical factor for companies to survive in the ever-expanding global marketplace. Total Quality Management (TQM) has been developed as a result of intense global competition. Most of the previous works show that TQM has significant relationship with business performance. However, the examining of moderators is less given in previous work, which mediators are known generally as general tools and techniques without specific focus on types of improvement. The purpose of this paper is to propose relationship between TQM practices and business performance with mediators effect of Total Productive Maintenance (TPM) based on extensive review of the literature. The main contribution of this paper is to identify the relationships among TQM, TPM practices and business performance as a conceptual model. This proposed conceptual model will help the academicians and industry players to have better understanding on the relationship between the practices.

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The application of big data analytics is significantly gaining awareness in the educational sector as universities are operating under pressure in an increasingly competitive environment. Quite a number of researchers have reported the use and application of big data in different fields with few publications addressing the integrative application of big data analytics in institutions of higher education. The purpose of this paper is to explore the applicability of big data analytics in higher institutions. This paper outlines the major areas in which big data analytics can be of use in the higher institutions such as in academic and management levels. The ultimate goal is to optimize using big data analytics in learning and decision-making.