What is Continuity in Decision Maing
Table 1. Hard System and Soft System Approach in Decision Making
The systems approach is one of the specialties of the DMSN interest group. It is selected since DMSN is interested in decision-making issues in real-life contexts. In such context, people involved behave in a unique behavior based on their internal properties such as culture, experience, motivation, and interest. Furthermore, these situations may involve negotiation conduct. This research direction is highly relevant in Indonesia that is comprised of people with different cultural backgrounds. Together with theoretical perspective from the service science, social science, decision science, and design science fields, DMSN explore myriad of research areas with a systems perspective. Some of the research areas are decision analysis, negotiation and confrontation analysis, value co-creation platforms, agent-based social simulations, service-dominant logic, soft system approaches, big data analytics, etc. The research explored in DMSN is aimed to be applicable in real-life practice. Concurrently real-life practices are the source of inspiration to enrich the existing theories/models. The overview of DMSN perspective in viewing the research and practice mutualism is portrayed in the following figure.
Together with popular analytical research methods (e.g. quantitative, qualitative, and mixed research methods), the DMSN interest group also conducts research with methodologies known from the systems science domain. As shown in Figure 3, DMSN interest group conduct both hard and soft systems research approaches. Some of the systems methodologies employed in the DMSN interest group are soft systems methodology, total systems intervention, agent-based modeling, systems-dynamics modeling simulations, service science, big data analytics, etc.
There are five big areas in which members of the Decision Making and Strategic Negotiation interest group conduct their teaching, research, and community services activities. As shown, the five areas are decision making, social simulation, negotiation, service science, and business analytics. The decision-making area involves fields such as normative decision making, systems approaches in decision making, etc. The social simulation area involves fields such as systems approaches, agent-based simulation, system dynamics simulation, discrete-event simulation, etc. The negotiation area involves fields such as game theory, the interplay of competition and cooperation, negotiation analysis, etc. The service science area involves fields such as service systems, interdisciplinary approaches in service-science, etc. The "Business Analytics" area involves fields such big-data analytics, advanced statistics, decision support systems, digital platforms for value creations, etc. Moreover these five research pillars are in line with the competencies that future businesses requires defined by the World Economic Forum such as complex problem solving, critical thinking, judgment and decision making in a VUCA (Volatile, Uncertain, Complex, Ambiguous) environment, negotiation, etc.
Selected Publications
Continuity Decision in Strategic Alliances of Technology Development Stages. (2020). (Best Paper in for "Information system, technology management, and social science" category)
Sani, K., Siallagan, M., Putro, U. S., & Mangkusubroto, K. (2018). Indonesia energy mix modelling using system dynamics. International Journal of Sustainable Energy Planning and Management , 18 , 29-51.
Innovation success over time of alliances with different strategic and cooperation objectives. In Modeling and Simulation Techniques for Improved Business Processes (2018) (pp. 1-23). IGI Global." (Book Chapter )
Siallagan, M., Martono, N. P., & Putro, U. S. (2017). Agent-Based Simulations of Smallholder Decision-Making in Land Use Change/Cover (LUCC) Problem. In Agent-Based Approaches in Economics and Social Complex Systems IX (pp. 97-107). Springer, Singapore.
Wasesa, M., Stam, A., & van Heck, E. (2017). The seaport service rate prediction system: Using drayage truck trajectory data to predict seaport service rates. Decision Support Systems , 95 , 37-48.
Wasesa, M., Stam, A., & van Heck, E. (2017). Investigating agent-based inter-organizational systems and business network performance: Lessons learned from the logistics sector. Journal of Enterprise Information Management , 30 (2), 226-243.
Mangkusubroto, K., Putro, U. S., Novani, S., & Kijima, K. (Eds.). (2016). Systems Science for Complex Policy Making: A Study of Indonesia (Vol. 3). Springer.
Hermawan, P., & Yoshanti, G. (2016). Unfolding the problem of Batik waste pollution in Jenes River, Surakarta, using critical system heuristics and drama-theoretic dilemma analysis. In Systems Science for Complex Policy Making (pp. 93-108). Springer, Tokyo.
Nuraeni, S., Arru, A. P., & Novani, S. (2015). Understanding consumer decision-making in tourism sector: conjoint analysis. Procedia-Social and Behavioral Sciences , 169 , 312-317.
Mayangsari, L., Novani, S., & Hermawan, P. (2015). Understanding a viable value co-creation model for a sustainable entrepreneurial system: a case study of Batik Solo industrial cluster. International Journal of Entrepreneurship and Small Business , 26 (4), 416-434.
Bintoro, B. P. K., Simatupang, T. M., Putro, U. S., & Hermawan, P. (2015). Actors' interaction in the ERP implementation literature. Business Process Management Journal , 21 (2), 222-249.
Ariyanto, K. (2014). Analyzing the Conflict between Football Organizations in Indonesia. Procedia-Social and Behavioral Sciences , 115 , 430-435.
Novani, Santi, and Kyoichi Kijima. "Efficiency and effectiveness of C2C interactions and mutual learning for value co-creation: Agent-based simulation approach." International Journal of Business and Management 8.9 (2013): 50.
Sunitiyoso, Y., Avineri, E., & Chatterjee, K. (2013). Dynamic modelling of travellers' social interactions and social learning. Journal of Transport Geography , 31 , 258-266.
Novani, S., & Kijima, K. (2012). Value co-creation by customer-to-customer communication: Social media and face-to-face for case of airline service selection. Journal of Service Science and Management , 5 (1), 101-109.
Sunitiyoso, Y., Avineri, E., & Chatterjee, K. (2011). The effect of social interactions on travel behaviour: An exploratory study using a laboratory experiment. Transportation Research Part A: Policy and Practice , 45 (4), 332-344.
Hermawan, P., & Kijima, K. (2009). Conflict analysis of Citarum River Basin pollution in Indonesia: A drama-theoretic model. Journal of Systems Science and Systems Engineering , 18 (1), 16-37.
Sunitiyoso, Y., & Matsumoto, S. (2009). Modelling a social dilemma of mode choice based on commuters' expectations and social learning. European Journal of Operational Research , 193 (3), 904-914.
Putro, U. S., Novani, S., Siallagan, M., Deguchi, H., Kantani, Y., Kaneda, T., … & Tanuma, H. (2008). Searching for effective policies to prevent bird flu pandemic in Bandung city using agent‐based simulation. Systems Research and Behavioral Science , 25 (5), 663-673.
Putro, U. S., Kijima, K., & Takahashi, S. (2000). Adaptive learning of hypergame situations using a genetic algorithm. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans , 30 (5), 562-572.
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Source: https://www.sbm.itb.ac.id/faculty-research/decision-making-and-strategic-negotiation-dmsn/
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