Narrow Results

In the present competitive and disruptive arena, big data analytics has emerged as a revolutionary approach enabling sound decision making leading to enhanced organisational performance. However, extant studies on big data analytics in organisational perspective is limited, specifically in the case of SMEs. The tenet is that organisations bank on superior decisionmaking capabilities through data-driven insights, like big data analytics. So, it is imperative to explore the intertwined themes from organisational perspectives. In this backdrop, this chapter addresses the key concerns with focus on the enablers and deterrents in big data and its analytics in the context of SMEs and mainly to decipher the ways it contributes to their enhanced organisational performance It investigates the moderating role of big data analytics on the relationship between decision making rationality and organisational performance. So, it adopts a crosssectional research approach, based on primary data collected from the SMEs firms in Delhi NCR. The key finding of the study emanating from the regression and interaction effect of big data analytics reinforce the use of big data analytics as the moderator, which affects the relationship between decision making and organisational performance. Thus, it reinstates that the use of rational decision making model in the organisation to result in higher performance. The chapter thus presents important insights for developing data-driven insights using the BDA in context of SMEs for driving organisational performance.

In modern manufacturing companies, new product design is a matter of great importance that can directly affect their profitabilities. Nowadays, customers demand higher quality products, lower prices, and better performance in delivery time. The intense competition of companies in global markets stimulates a significant change in the way products are designed, manufactured and delivered. These situations are forcing to designers and manufacturing engineers to consider the use of tools for the process of new product design. In this paper, we propose an intelligent decision support system (DSS) based on a proposed distributed multi-agent architecture. This DSS implements a New Product Design Multicriteria Methodology based on consumer preferences. The system is composed by elements of Marketing Decision Support Systems, agent technologies, multi-objective evolutionary algorithms and multicriteria methods. Finally, we show a Marketing Intelligent Decision Support System prototype to support new product design decisions which is a combination of MDSS, agent technologies, multi-objective evolutionary algorithms and multicriteria ELECTRE III method.

Virtual reality, a new paradigm for relationship between humans and computers, has been recently well-known and currently investigated for practical use in the various industrial fields. Using three-dimensional computer graphics, interactive devices, and high-resolution display, a virtual world can be realized in which one can pick up imaginary objects as if they were physical world. Using this technology, Matsushita Electric Works, Ltd. has been developing several application systems for industrial use since 1990. This paper details three VR application systems operating in the real world: Virtual Space Decision Support System employing Kansei Engineering which is applied for production and sales mainly in the system kitchen business, a telepresence robot system employing semi-autonomous mobile function which is utilized for security field and a low-cost VR system employing physiological feedback mechanism which is used for health care field.