Web-Based Decision Support for E-Business Strategies: A Balanced Scorecard Approach

Abstract

This paper describes the design and proof of concept of a web-based e-business decision-making support system (EBDMSS), to deliver a balanced scorecard (BSC)-based modeling and analysis in support of e-business strategic management. EBDMSS is designed, built and validated through a conceptual design research method. Its design is theoretically underpinned in three DMSS design schemes: an e-business BSC (EBBSC) framework for decision-making process (DMP), a DMSS architecture, and a DMSS design-evaluation framework. The EBBSC scheme aims to support e-business managers during the business strategy making process in a comprehensive, integrated, and continuous manner. The DMSS architecture and the DMSS design-evaluation frameworks help to deliver the expected design capabilities of an integrated DMSS. The paper reports related literature review, conceptual design methodology and principles, EBDMSS design and prototype implementation, and illustrates how practitioners can use this system to deliver a valuable range of embodied e-business strategy expertise in support of real-time decision making. The paper concludes with limitations of design, implementation and validation, recommendations for further research, and conclusions.

iCHAMPSS: Usability and Psychosocial Impact for Increasing Implementation of Sexual Health Education

“…A decision support system is a computer-based system designed to support complex decision making and problem solving (Shim et al, 2002). Decision support systems are designed to facilitate the decision-making process, not to replace the decision makers, and have been used effectively in a variety of settings, including health care (Holstiege, Mathes, & Pieper, 2015), business (Wang, Mora, & Raisinghani, 2015), agriculture (Gallardo, Thompson, Gimenez, Padilla, & Stockle, 2014), and forest management (Nobre, Eriksson, & Trubins, 2016). For example, clinical decision support systems have had positive effects on ordering or completing preventive care services, prescribing treatments, and ordering clinical studies (Bright et al, 2012), as well as lowering the risk of morbidity among clinical populations (Moja et al, 2014).…”