An Agent–Based Model of the Impact of Computer–Mediated Communication on Organizational Culture and Performance: An example of the Application of Complex Systems Analysis Tools to the Study of CIS

Canessa, Enrique; Riolo, Rick L.

doi:10.1057/palgrave.jit.2000078

Cited by 28 publications

(16 citation statements)

References 45 publications

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“…Since generally ABMs' outputs are nondeterministic time series [1] ). These expressions involve that the fitness function of the GA must calculate the expected value of the difference in mean and standard deviation between points of the time series generated by the ABM and the corresponding ones of the real system.…”

Section: State Of the Artmentioning

confidence: 99%

“…Agent-Based Models (ABMs) (among other tools) are particularly well-suited to studying Complex Adaptive Systems (CAS) [1], cf. [2].…”

Section: Introductionmentioning

confidence: 99%

“…Generally speaking, a CAS is one where numerous elements, parts, or agents (homogeneous or not) interact non-linearly with each other and with their environment such as that their properties may be modified as a result of those interactions [3]. Traditional approaches to studying CAS [4] often limit our ability to understand the full complexity of these systems, in part because the characteristics of CAS (e.g., path dependent dynamics) violate many of the statistical assumptions necessary to use those approaches (i.e., survey research, controlled experiments, game theory) [1].…”

Section: Introductionmentioning

confidence: 99%

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Calibrating Agent-Based Models Using a Genetic Algorithm

Canessa¹,

Chaigneau²

2015

SIC

Self Cite

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We present a Genetic Algorithm (GA)-based tool that calibrates Agent-based Models (ABMs). The GA searches through a user-defined set of input parameters of an ABM, delivering values for those parameters so that the output time series of an ABM may match the real system's time series to certain precision. Once that set of possible values has been available, then a domain expert can select among them, the ones that better make sense from a practical point of view and match the explanation of the phenomenon under study. In developing the GA, we have had three main goals in mind. First, the GA should be easily used by non-expert computer users and allow the seamless integration of the GA with different ABMs. Secondly, the GA should achieve a relatively short convergence time, so that it may be practical to apply it to many situations, even if the corresponding ABMs exhibit complex dynamics. Thirdly, the GA should use a few data points of the real system's time series and even so, achieve a sufficiently good match with the ABM's time series to attaining relational equivalence between the real system under study and the ABM that models it. That feature is important since social science longitudinal studies commonly use few data points. The results show that all of those goals have been accomplished.

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Section: State Of the Artmentioning

confidence: 99%

“…Agent-Based Models (ABMs) (among other tools) are particularly well-suited to studying Complex Adaptive Systems (CAS) [1], cf. [2].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Calibrating Agent-Based Models Using a Genetic Algorithm

Canessa¹,

Chaigneau²

2015

SIC

Self Cite

View full text Add to dashboard Cite

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“…There have been a number of recent empirical papers pertaining to the various applications of agent-based simulations such as knowledge exchange (Wang et al 2009), social activity generation and scheduling (Ronald et al 2012), computermediated communication (Canessa and Riolo 2006), innovation diffusion within market networks (Bohlmann et al 2010), and innovation networks (Ahrweiler et al 2011). Table 13.1 provides examples of these research studies.…”

Section: Background Literaturementioning

confidence: 99%

Modeling Dynamic Organizational Network Structure

Song

Choi

2014

Reshaping Society Through Analytics, Collaboration, and Decision Support

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The organizational social networks, where the creation and recombination of knowledge typically takes place, are recognized as a crucial enabler for improving the organizational innovation and performance. While the recent research endeavors have been insightful in explaining the effect of the organizational social networks, we may need more effective tools to investigate the dynamics of the evolving network structures within an organization. Agent-based modeling has been considered a powerful tool for thoroughly studying the dynamics of the system. In this study, we propose an agent-based simulation model to provide a deeper understanding the dynamics of organizational network structures along with its task environment.

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“…The ability of senior leadership to understand the potential cultural challenges is key in mitigating cultural resistance. Canessa and Riolo (2006) studied how different implementations of computer-mediated communication would strengthen or dilute organizational culture, leading to differences in communication effectiveness. In their study, IT was shown to be able to have a direct impact on the resilience of culture over time.…”

Section: Embeddednessmentioning

confidence: 99%

Cultural Challenges in Information Systems Innovation: The Need for Differentiation Studies

Lawrence

Oivo

2012

Shaping the Future of ICT Research. Methods and Approaches

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Abstract. Information technology (IT) innovations have been vital to the success of organizations seeking to improve efficiency and productivity. IT's global diffusion has however raised serious questions about its neutral application across cultures and contexts. This paper synthesizes a sample of the literature to conceptualize the key cultural challenges in IS innovation as, differentiation, externality, compatibility, embeddeness. The study shows that the adoption decision is challenged by differentiation, and the adoption phase exhibits issues of externality. During implementation, compatibility is the key challenge of innovators and the assimilation literature revealed that embeddeness was the cultural challenge that phase. The synthesis also revealed that the comprehension phase where adoption decisions are made was lacking significant study. The paper proposes two opportunities for research and examples of research methods that can be use to investigate pre-adoption phenomena.Keywords: Innovation, culture, differentiation, comprehension, methods. IntroductionInformation technology (IT) is a significant investment for any organization, thus extracting the most value from these innovations is vital, and can be highly rewarding (Rau & Bye, 2003). As a key resource for business in a new competitive age, IT innovations enable the complex interactions that are required to support our global economy (M. Barrett, Jarvenpaa, Silva, & Walsham, 2003). IT has become a symbol of progress throughout the world, driving greater global interactions. Information systems (IS) researchers view mitigating the challenges of innovating with IT as imperative to participating in, and reaping the benefits of our new globally connected economy (Mustonen-Ollila & Lyytinen, 2004). Many organizations do not possess the technical expertise to develop new IT innovations, thus they are more likely to adopt them. Thus, IS innovation is the adoption of IT innovations for use in unique ways and the term has normally been restricted to early adopters (B. Swanson, 1994; E. B. Swanson, 2010). While many studies have focused on adoption, it is not the initiation of the innovation process. Prior to adoption, the adoption decision must be made, and after adoption, the innovation needs to be implemented, and assimilated by the organization. The benefits of innovation adoption can only truly be realized when it has been integrated into the activities of the organization's value chain (Armstrong & Sambamurthy, 1999). C. Lawrence and M. OivoThe importance of IT in our global society should not allow for the naive assumptions that innovations will exhibit the same productive attributes in organizations and individuals existing in culturally distant contexts (Ein-Dor, Segev, & Orgad, 1993;Kaye & Little, 1996;Vodanovich, Sundaram, & Myers, 2010;Wagner & Newell, 2004). Globalization has generated significant research interest in culture and IS, as organizations, seeking to keep pace with a growing competitive marketplace, are motived to adopt the latest...

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An Agent–Based Model of the Impact of Computer–Mediated Communication on Organizational Culture and Performance: An example of the Application of Complex Systems Analysis Tools to the Study of CIS

Cited by 28 publications

References 45 publications

Calibrating Agent-Based Models Using a Genetic Algorithm

Calibrating Agent-Based Models Using a Genetic Algorithm

Modeling Dynamic Organizational Network Structure

Cultural Challenges in Information Systems Innovation: The Need for Differentiation Studies

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