Multi-agent Modeling and Simulation for the Evolution of Enterprise IT Capability

Journal of Computational Information Systems 7: 6 (2011) 1855-1862 Available at http://www.jofcis.com Multi-agent Modeling and Simulation for the Evolution of Enterprise IT Capability Bing BAI, Xiuquan DENG, Dehua GAO The School of Economics and Management, Beihang University, Beijing 100191, China Abstract This research aims to provide a new perspective on the evolution of enterprise information technology (IT) capability. Based on complex adaptive system (CAS) theory, this paper built a multi-agent simulation conceptual model for the evolution of enterprise IT capability, designed interaction rules of agent, and realized the simulation by Swarm. The results show that the evolution of enterprise IT capability is a dynamic adaptive process. Under the assumption of limited rationality, the enterprises gradually begin to realize the advantage of IT capability. The enterprise IT capability possessed of value, scarcity, and inimitability is an important source of competitive advantage. Keywords: IT Investment; IT Capability; Competitive Advantage; Core Capability; Multi-Agent Simulation 1. Introduction The information technology (IT) capability of an enterprise is very important for the efficient execution of its management activities and to improve competitive potential in an IT environment [1]. Therefore, many researchers have theoretically studied enterprise IT capability. Many studies defined IT capability from the researchers viewpoints. Ross et al.(ross, Beath, Goodhue, 1996)argued that the enterprise IT capability is underlying resources, or management assets, which can offer sustainable competitive advantage [2]. They found that some firms do appear to generate competitive advantage from their IT, but the advantage results from their IT capabilities, not from their IT investment or applications. C.S.Leem et al. (C.S.Leem, S.K. Kim, 2002) defined enterprise IT capability as an important way to improve and preserve enterprise task performance in the ever-changing business environment [3]. Lee et al. (Lee, Trauth, Farwell, 1995) considered that IT capability is the organizational capability supporting organizational activities and workflows by the disposition of IT resources and integration of other relevant resources [4].From the resource-based perspective, Bharadwaj (Bharadwaj, 2000) described the IT capability is to integrate other organizational resources through the use and disposition of one s own IT resources [5]. H. Jiao et al. (H. Jiao, C. Chang, Y. Lu, 2008) proposed that IT capability is formed by IT system convention, IT infrastructure, human IT resources and IT relationship assets [6]. Although literature has shown that IT capability is a critical resource for enterprises in the 21st century, Corresponding author. Email addresses: szzxbb@163.com (Bing BAI) 1553-9105/ Copyright 2011 Binary Information Press June, 2011

1856 B. Bai et al. /Journal of Computational Information Systems 7:6 (2011) 1855-1862 little work has been carried out on how to build IT capability and how is the evolution of enterprise IT capability. So the study on its evolution is an important and inevitable subject of the management science. In addition, with the emergence and development of complex systems theory, some research literatures of enterprise capability theory began to advocate the combining of complex systems theory and enterprise capability theory[7-9]. Recently, a literature proved that complex systems theory to better explain the evolution of enterprise competitive capability [10]. Some literatures developed the study of enterprise capability based on complex systems theory, including the application of collaborative self-organization theory to explore the evolution rule of enterprise core capability, the application of complex adaptive system (CAS for short) theory to explore the evolution mechanism of enterprise capability [11-12]. Under the background of the rise of Complex systems theory, the momentum of studying the complexity of enterprise capability based on complex systems theory has appeared. Enterprise IT capability as an important part of enterprise capabilities can be analyzed from the CAS perspective. Therefore, this paper built a multi-agent simulation model for the evolution of enterprise IT capability based on CAS, simulated it by Swarm, and analyzed the evolution of enterprise IT capability. 2. Theoretical Foundations 2.1. A Brief Introduction of CAS Theory The theory of complex adaptive system is proposed by SFI School which is one of five schools of complex science [13]. Its core idea is Adaptability creating Complexity that the evolution of system benefited from the living agent. In order to adapt to the environment or win the right to survive, agents will adjust their behaviors constantly according to the external environment and other agents behaviors [14]. To use a resource, an agent must contact the agent that provides it [15]. Complex adaptive system theory provides a new perspective to explain the evolution of enterprise IT capability. 2.2. Multi-agent Simulation Platform-Swarm Multi-agent modeling and simulation is a main tool to study complex adaptive system. Until now, there have been a few platforms for multi-agent modeling and simulation. Among them, Swarm is regarded as a popular one. The basic architecture of Swarm is the collection of concurrently interacting agents. With this architecture, a large variety of agent-based models can be implemented. Swarm provides abundant components and a program framework for researchers to create system models [16]. 3. Model Analysis 3.1. Assumptions of the Model Before establishing the simulation model for the evolution of enterprise IT capability, we should accurately definite the system boundary firstly, and finish the confirmation of boundary. In order to simplify the program, we definite following premise and assumptions: 1) The agents in the model are the enterprises. We do not carry on the segmentation according to the profession. 2) The enterprises in the model are limited rationality. The limited rational enterprises refer to the

B. Bai et al. /Journal of Computational Information Systems 7:6 (2011) 1855-1862 1857 organizations that can not find the optimum strategy from the very beginning, but find the optimum strategy through continuous learning and adaptation. 3) The enterprises are created in the market space according to the structure function. Different enterprises carry on IT investment according to the rules. 4) When describing the differences among enterprises, we only consider the indicators of IT investment strategy, IT capability, core capability, development potential, and competitive advantage. We assume that other indicators are the same. 5) Using random to simulate the preferences feelings and needs of agent. Using random to replace the parameters can not be measured and the information can not be obtained estimate accurately [17]. 3.2. Conceptual Model Conceptual model is the foundation for building a multi-agent simulation model. The conceptual model for the evolution of enterprise IT capability is decomposed into three layers in the model. The first layer is the conversion process, and describes that IT investment change into IT assets. The second layer is the configuration process, and depicts that IT assets evolves IT capability. The third layer is the competitive process, and describes that IT capability influences the competitive advantage. The IT Conversion Process The IT Use Process The Competitive Process IT INVESTMENT IT ASSETS IT CAPABILITY COMPETITIVE ADVANTAGE IT Management Conversion Activities Appropriate Inappropriate Use Competitive Position Competitive Dynamics Fig.1 Conceptual Model of Evolution of Enterprise IT Capability [18] 3.3. Defining the Agent and It s Attributes The agents in the model are the abstract of enterprises, and have following attributes: 1) IT Investment Strategy (ITIS for short). The agents in the model have different attitudes for IT investment. 1 denoted that the agents tend to carry on IT Investment, and 0 denoted the agents tend not to carry on IT Investment. The attribute value is generated by 0.5 probabilities with each agent. 2) IT Capability (ITC for short). IT capability is bundles of IT related resources, skills and accumulated knowledge that help the enterprises gain competitive advantage. If an enterprise carries on IT investment, it will promote the formation of IT capability. 3) Market Share (MS for short). The market share is the market space that the enterprise owns. The enterprises are created in the market space according to the structure function 4) Development Potential Index (DPI for short). The development potential index represents the sustained development situation of enterprise in the future. If the enterprise carries on IT investment, it will

1858 B. Bai et al. /Journal of Computational Information Systems 7:6 (2011) 1855-1862 enhance the DPI. 5) Core Capability (CC for short). Core capability is one of the sources of competitive advantage. Core capability does not include IT capability in the model. The initial core capability sets the same. If IT capability is increased, it will promote the enhancement of core capability. 6) Competitive Advantage (CA for short). Competitive advantage is decided by market share, IT capability, core capability, and development potential index together. 7) The Expected return (ER for short). After decision-making in every time, the enterprises start to assess their strategy. If the expected return is lower than the current competitive advantage, the enterprise will change strategy in the next time. On the contrary, the enterprise will maintain the original strategy. 3.4. The Design of the Interaction of Agent 3.4.1. Model Initialization 1) Creating the market space. Market space is composed of by the X*Y two-dimensional grid. The initial space sets 100*100. Market share is scattered by 0.6 probabilities. If the grid value is 1, it indicates that there is 1 unit space to share. If the grid value is 0, it indicates that this grid has been occupied. 2) The establishment of the agents. The agents are established by 0.8 probabilities in the grid. If the grid is not occupied, the agent obtains the current market share. If the grid is occupied, the agent continues to searching. The initial value of IT investment strategy is generated by [0, 1] uniform integer random number. The expected return of agent is generated by [1,100] uniform integer random number. 3.4.2. Setting the Learning Algorithm of Agents The agents in the market space through adaptive learning and assessment gradually realize that choosing IT investment is better than giving up IT investment. This process is implemented by learning algorithm in the model [19]. The learning algorithm is followed: ITIS = ( ITIS, CA, ER ) (1) ( x, y), t+ 1 ( x, y), t ( x, y), t ( x, y), t ITIS represents the IT investment strategy that the agent laying on ( x, y ) position takes on t ( x, y ), t schedule. CA stands for the value of competitive advantage that agent gains on t schedule. ER ( x, y ), t ( x, y), t is the expected return of agent on t schedule. ITIS represents the IT investment strategy that the ( x, y ), t + 1 agent laying on ( x, y ) position will take on t + 1 schedule. The agents evaluate their strategy by imitating and learning, and then improve their strategy choice. if ( ITIS = 0, CA ( t) < ER ) ITIS = 1; ( x, y), t ( x, y) ( x, y), t ( x, y), t+ 1 if ( ITIS = 0, CA ( t) > ER ) ITIS = 0; ( x, y), t ( x, y) ( x, y), t ( x, y), t+ 1 if ( ITIS = 1, CA ( t) < ER ) ITIS = 0; ( x, y), t ( x, y) ( x, y), t ( x, y), t+ 1 if ( ITIS = 1, CA ( t) > ER ) ITIS = 1; ( x, y), t ( x, y), t ( x, y), t+ 1 ( x, y) (2)

B. Bai et al. /Journal of Computational Information Systems 7:6 (2011) 1855-1862 1859 3.4.3. Model Interaction From t schedule to t+1 schedule, the operating mechanism is that the current agent makes a strategic decision, and then evaluates the decision. Model interaction is to repeat the above process. Agents Searching Market Gain the market? N Y Market Share Raising Core Capability Increasing N Core Capability 5? DPI decreasing N Y IT Investment? Y Cost increasing DPI increasing Competitiveness Evaluating and Deciding Fig.2 The Internal Operation Mechanism of Model 1) The agent searches the market share unceasingly according to the rule in the two-dimensional grid. If the grid is not occupied, the agent will obtain the current market share, the market share adds 1 unit, and the core capability adds 2 units. If the grid is occupied, the agent will continue to searching. MS = CC = MS + 1 if ( thevalue of Grid = 1) MS + 0 if ( thevalue of Grid = 0) CC + 2 if ( MS = MS + 1) CC + 0 if ( MS = MS + 0) 2) If the core capability is greater than 5, the agent will decide whether or not to carry on IT investment according to the attribute value of IT investment strategy. If the value is 1, the agent will carry on IT investment. Simultaneously, the development potential index will add 0.2. Since carrying on IT investment needs to pay part of cost, we reduce 1 unit core capability for cost. If the value is 0, the agent will not carry on IT investment. Since the competitive pressure is increased relative to the agents carrying on IT investment, the development potential index will reduce 0.1. (3)

1860 B. Bai et al. /Journal of Computational Information Systems 7:6 (2011) 1855-1862 DPI + 0.2 CC 1 if ( CC > 5 and ITIS = 1) (4) DPI 0.1 CC + 0 if ( CC < 5 or ITIS = 0) (5) The competitive advantage is calculated according to the following formula: CA = f ( MS, ITC, CC, DPI ) (6) 3) When the agent has finished a decision-making, it will evaluate the decision-making. 3.4.4. Evolution of the System From t schedule to t + 1 schedule, the model begins to repeat the above process. 4. Implementation of Simulation 4.1. Initial Parameter The initial value of core capability sets 3. The end time of simulation is 200.The displayfrequency sets 1 and zoomfactor sets 4. 4.2. Analysis of the Simulation Result From 1 schedule to 200 schedules, the process of changes about the distribution of agents in the market space is followed: Fig. 3 The Evolution Process of the Enterprise IT Investment The white grids represent the agent whose strategy is to carry on IT investment strategy, and the red grids represent the opposite. As you can see from the figure 3, they show that the amount of agents whose strategy is not to carry on IT investment is decline sharply. The main reason is that the agents through adaptive learning and assessment gradually began to realize the advantages of choosing IT investment under the assumption of limited rationality. So many agents decide to change strategy. These cause the amount of white grids increase obviously, yet the amount of red grids decreased rapidly.

B. Bai et al. /Journal of Computational Information Systems 7:6 (2011) 1855-1862 1861 Fig.4 The Curve of IT Capability Fig.5 The Curve of Core Capability Fig.6 The Curve of Competitive Advantage We can see from the figure 4 that the initial value of IT capability is 0. But when the model begins to run, IT capability is increasing obviously. This is due to the agents which carry on IT investment going up quickly. The agents in the market space according to learning algorithm gradually realize the advantage of choosing IT investment. This will promote the enhancement of IT capability. The initial value of core capability is 3. After the model runs, the enterprises will search the market share unceasingly. When an enterprise obtains the current market share, its core capability will add 2 units. So the core capability grows rapidly in the beginning. But after running a period of time, the enterprise will carry on IT investment when the core capability is greater than 5, which will consume a certain core capabilities. So the curve of core capability is fluctuant in the middle. But the general trend is still growing, as you can see from the figure 5. Competitive advantage is decided by IT capability, core capability, and development potential index together. As you can see from the figure 6, the curve of competitive advantage goes up gradually. This is mainly because the IT capability and the core capability are both increasing. So according to the algorithm, competitive advantage is going up. From the analysis of the simulation result, the enterprises through adaptive learning and assessment gradually will realize the advantages of choosing IT investment under the assumption of limited rationality. The enterprise carrying on IT investment will promote the enhancement of IT capability and DPI. The enhancement of IT capability and DPI will accelerate the augment of core capability. These factors will ultimately heighten competitive advantage. 5. Conclusion This paper, using the Swarm simulation platform, from the perspective of complex adaptive system, studied the evolution problem of enterprise IT capability. Through modeling the multi-agent simulation model, we analyzed the process of evolution, and drew the following conclusions: 1) The enterprise carrying on IT investment will promote competitive advantage through the certain mechanism. The mechanism is the formation of enterprise IT capability. IT capability possessing of value, scarcity, and inimitability is an important source of competitive advantage. 2) The enterprise need to reposition the strategic value of IT investments. The focus of IT investments should change into how to build IT capability. In order to obtain the success of IT investment, the enterprise should not only focus on constructing IT infrastructure, but also pay more attention to configuring IT intangible resources and IT human resources to promote the formation of IT capability. 3) The evolution of enterprise IT capability has complexity, and is a dynamic learning process. The enterprises gradually realize the importance of IT capability through adaptive learning and assessing.

1862 B. Bai et al. /Journal of Computational Information Systems 7:6 (2011) 1855-1862 These conclusions are advantageous for us to make a more reasonable explanation for the evolution of enterprise IT capability. But the model also has insufficiencies to be improved. We will further study in the coming work. Acknowledgement The research work in this paper is supported by the grants from National Natural Science Foundation of China (No. 70872008) and Aviation Science Foundation of China (No. 2010ZG51076). References [1] Chui Young Yoon. Measuring enterprise IT capability: A total IT capability perspective Knowledge-Based Systems.2010, 29 (7): 1-6. [2] Ross J W,Beath C M,Goodhue D L. Develop Long-term Competitiveness through IT assets Sloan Management Review,1996, 38(1):31-42. [3] C.S. Leem, S.K. Kim. Introduction to an integrated methodology for development and implementation of enterprise information systems. Journal of Systems and Software 2002 (60): 249 261. [4] D.M. Lee, E.M. Trauth, D. Farwell. Critical skills and knowledge requirement of IS professionals: a joint academic and industry investigation. MIS Quarterly 1995, 19 (3) 313 340. [5] A.S. Bharadwaj. A resource-based perspective on information technology capability and firm performance: an empirical investigation. MIS Quarterly 2000, 24 (1): 169 196. [6] H. Jiao, C. Chang, Y. Lu, The relationship on information technology capability and performance: An empirical research in the context of China s Yangtze River delta region. Proceeding of The IEEE International Conference on Industrial Engineering and Engineering Management, 2008, pp. 872 876. [7] R. Sanchez, A. Heene, Reinventing Strategic Management: New Theory and Practice for Competence-Based Competition. European Management Journal, 1997,15(3):303-317. [8] Shijuan Cui. Probing into the Nuclear Capacity of Enterprises from the Angle of Complex System. Economist, 2004(7): 157-158. [9] Giovanni Battista Dagnino. Complex Systems as Key Drivers for the Emergence of a Resource- and Capability-based Interorganizational Network. Emergence: Complexity & Organization, 2004,6(1-2): 61-69. [10] John Brocklesby, Colin Campbell-Hunt. The Evolution of Competitive Capability: A Cognition and Complex Systems Perspective. Journal of Organizational Transformation and Social Change, 2004, 1(2-3): 143-162. [11] Zhengren Fan. Analyzing internal coordination process of core competence of the enterprises. Science and Technology Management Research, 2000(3): 24-28. [12] Pengcheng Zhang, Libin Zhang. Exploring the Mechanism of Evolution of Core Rigidities in the Complex Adaptive System s Perspective. China Industrial Economics, 2006(7): 117-123. [13] Holland, J.H., Hidden Order: How Adaptation Builds Complexity.Addison Wesley Publishing Company, 1995 [14] Guoling Lao, Luyuan Xiao, Rong Zhou. CAS-based Enterprise Knowledge Sharing Modeling and Simulation.Wireless Communications, Networking and Mobile Computing, WiCOM 08. 4th International Conference 2008: 1-4 [15] Yunsong TAN, Jianjun HAN, Yuntao WU. A Multi-agent Based Efficient Resource Discovery Mechanism for Grid Systems. Journal of Computational Information Systems,2010. 6 (11) : 3623-3631 [16] Honglei Li. Fuquan Sun. A Parallel Multi-Agent Simulation Planning Approach to Complex Logistics System with Genetic Optimization.Wireless Communications, Networking and Mobile Computing, WiCom 2007.International Conference. 2007: 4843-4846 [17] Xiuquan Deng, Haorun Huang. Research on the Concept Model of Enterprise Capability Multi-Agent Simulation Based on CAS. The 38th International Conference on Computers &Industrial Engineering, China, 2008: 818-828 [18] Soh, C. and Markus, M.L. How IT creates business value: a process theory synthesis. Proceedings of the 16th International Conference on Information Systems, 1995 (11): 10-13 [19] Meng CHEN, Jian JIAO, Yi YANG, Min LUO, Chunhe XIA. Research on Task-Deployment for the Distributed Simulation of Computer Network Attack and Defense Exercises. Journal of Computational Information Systems, 2010.6 (4) : 1037-1050