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The COVID-19 pandemic has had a significant impact on higher education. Steering academic institutions through the pandemic is a complex and multifaceted task that can be supported with model-based scenario analysis. This article studies the short-term and long-term effects of the pandemic on the financial health of a college using scenario analysis and stress testing with a system dynamics model of a representative tuition-dependent college. We find that different combinations of the pandemic mitigation protocols have varying effects on the financial sustainability of an academic institution. By simulating six individual components of the COVID-19 shock, we learn that due to the causal complexity, nonlinear responses and delays in the system, the negative shocks can propagate widely through the college, sometimes with considerable delays and disproportionate effects. Scenario analysis shows that some pandemic mitigation choices may destabilize even financially healthy institutions. The article concludes that higher education needs new sustainable business models.
Oleg Pavlov; Evangelos Katsamakas. COVID-19 and Financial Sustainability of Academic Institutions. Sustainability 2021, 13, 3903 .
AMA StyleOleg Pavlov, Evangelos Katsamakas. COVID-19 and Financial Sustainability of Academic Institutions. Sustainability. 2021; 13 (7):3903.
Chicago/Turabian StyleOleg Pavlov; Evangelos Katsamakas. 2021. "COVID-19 and Financial Sustainability of Academic Institutions." Sustainability 13, no. 7: 3903.
Crowdfunding is a novel and important economic mechanism for funding projects and promoting innovation in the digital economy. This article explores most recent structured and unstructured data from a crowdfunding platform. It provides an in-depth exploration of the data using text analytics techniques, such as sentiment analysis and topic modeling. It uses novel natural language processing to represent project descriptions, and evaluates machine learning models, including neural network models, to predict project fundraising success. It discusses the findings of the performance evaluation, and summarizes lessons for crowdfunding platforms and their users.
Evangelos Katsamakas; Hao Sun. Machine Learning Crowdfunding. International Journal of Knowledge-Based Organizations 2020, 10, 1 -11.
AMA StyleEvangelos Katsamakas, Hao Sun. Machine Learning Crowdfunding. International Journal of Knowledge-Based Organizations. 2020; 10 (2):1-11.
Chicago/Turabian StyleEvangelos Katsamakas; Hao Sun. 2020. "Machine Learning Crowdfunding." International Journal of Knowledge-Based Organizations 10, no. 2: 1-11.
Evangelos Katsamakas; Mingdi Xin. Open source adoption strategy. Electronic Commerce Research and Applications 2019, 36, 1 .
AMA StyleEvangelos Katsamakas, Mingdi Xin. Open source adoption strategy. Electronic Commerce Research and Applications. 2019; 36 ():1.
Chicago/Turabian StyleEvangelos Katsamakas; Mingdi Xin. 2019. "Open source adoption strategy." Electronic Commerce Research and Applications 36, no. : 1.
Platform competition and behavioural economics are two fast-growing areas of research with multiple contributions across a variety of domains. However, the two research areas are disjoint. This article attempts to integrate the two by incorporating behavioural economics concepts into platform competition. In particular, it analyzes the effects of user cognitive biases on platform competition. The effects are characterised in a rigorous way, via a computational agent-based model (ABM). The article presents a variety of computational experiments that show that biases have a significant effect on the dynamics and outcomes of platform competition. It discusses implications for platform designers, who seek to provide user decision support in a strategic way.
Evangelos Katsamakas; Heba Madany. Effects of user cognitive biases on platform competition. Journal of Decision Systems 2019, 28, 138 -161.
AMA StyleEvangelos Katsamakas, Heba Madany. Effects of user cognitive biases on platform competition. Journal of Decision Systems. 2019; 28 (2):138-161.
Chicago/Turabian StyleEvangelos Katsamakas; Heba Madany. 2019. "Effects of user cognitive biases on platform competition." Journal of Decision Systems 28, no. 2: 138-161.
The best companies compete with people analytics. They maximize the business value of their people to gain competitive advantage. This article proposes a network data science approach to people analytics. Using data from a software development organization, the article models developer contributions to project repositories as a bipartite weighted graph. This graph is projected into a weighted one-mode developer network to model collaboration. Techniques applied include centrality metrics, power-law estimation, community detection, and complex network dynamics. Among other results, the authors validate the existence of power-law relationships on project sizes (number of developers). As a methodological contribution, the article demonstrates how network data science can be used to derive a broad spectrum of insights about employee effort and collaboration in organizations. The authors discuss implications for managers and future research directions.
Nan Wang; Evangelos Katsamakas. A Network Data Science Approach to People Analytics. Information Resources Management Journal 2019, 32, 28 -51.
AMA StyleNan Wang, Evangelos Katsamakas. A Network Data Science Approach to People Analytics. Information Resources Management Journal. 2019; 32 (2):28-51.
Chicago/Turabian StyleNan Wang; Evangelos Katsamakas. 2019. "A Network Data Science Approach to People Analytics." Information Resources Management Journal 32, no. 2: 28-51.
Digital goods, such as software, are significant elements of the contemporary digital economy. The authors propose a model that characterizes dynamic profit-maximizing competitive pricing strategies of digital goods with network effects. In a two-period game theory model, an incumbent firm has a quality advantage in period 1, but the potential disrupter has a quality advantage in period 2. They analyze pricing strategies and characterize conditions under which the potential disrupter becomes an actual disrupter. They discuss implications for user adoption of digital goods and opportunities for future research.
Evangelos Katsamakas. Effects of Quality Improvement and Upgrading on Software Market Disruption. International Journal of Strategic Decision Sciences 2018, 9, 1 -15.
AMA StyleEvangelos Katsamakas. Effects of Quality Improvement and Upgrading on Software Market Disruption. International Journal of Strategic Decision Sciences. 2018; 9 (4):1-15.
Chicago/Turabian StyleEvangelos Katsamakas. 2018. "Effects of Quality Improvement and Upgrading on Software Market Disruption." International Journal of Strategic Decision Sciences 9, no. 4: 1-15.
Nicholas C. Georgantzas; Evangelos Katsamakas. How service customers tidy their service quality perceptions. Human Systems Management 2016, 35, 129 -139.
AMA StyleNicholas C. Georgantzas, Evangelos Katsamakas. How service customers tidy their service quality perceptions. Human Systems Management. 2016; 35 (2):129-139.
Chicago/Turabian StyleNicholas C. Georgantzas; Evangelos Katsamakas. 2016. "How service customers tidy their service quality perceptions." Human Systems Management 35, no. 2: 129-139.
Creating an Enterprise 2.0 extends from employee content creation and collaboration to building an architecture that enables mobility and where possible allows for emerging technologies and methodologies. Yet, in many cases implementing this new architecture may find resistance, not from knowledge workers, but from IT managers who are apprehensive because of the potential security compromise, proliferation of multiple standards, and delegation of procurement authority to individual users or business units. In this research article, the authors describe a structured and deliberate approach towards building Enterprise 2.0 environment. Many elements of the approach were defined and developed at Vanguard, Inc. as it developed an integrated communication and collaboration environment over several years. The authors emphasize the process followed and lessons learned.
Abha Kumar; Aditya Saharia; Evangelos Katsamakas; Glenn A. Bixby Iii. Enterprise 2.0 Implementation at Vanguard. International Journal of Strategic Information Technology and Applications 2015, 6, 23 -34.
AMA StyleAbha Kumar, Aditya Saharia, Evangelos Katsamakas, Glenn A. Bixby Iii. Enterprise 2.0 Implementation at Vanguard. International Journal of Strategic Information Technology and Applications. 2015; 6 (3):23-34.
Chicago/Turabian StyleAbha Kumar; Aditya Saharia; Evangelos Katsamakas; Glenn A. Bixby Iii. 2015. "Enterprise 2.0 Implementation at Vanguard." International Journal of Strategic Information Technology and Applications 6, no. 3: 23-34.
Evangelos Katsamakas. Value network competition and information technology. Human Systems Management 2014, 33, 7 -17.
AMA StyleEvangelos Katsamakas. Value network competition and information technology. Human Systems Management. 2014; 33 (1-2):7-17.
Chicago/Turabian StyleEvangelos Katsamakas. 2014. "Value network competition and information technology." Human Systems Management 33, no. 1-2: 7-17.
This chapter presents a System Dynamics (SD) simulation model that not only replicates self-organizing system uncertainty results but also looks at self-organization causally. The SD simulation and model analysis results show exactly how distributed control leads positive feedback to explosive growth, which ends when all dynamics have been absorbed into an attractor, leaving the system in a stable, negative feedback state. The chapter's SD model analysis helps explain why phenomena of interest emerge in agent-based models, a topic crucial in understanding and designing Complex Adaptive Self-Organizing Systems (CASOS).
Nicholas C. Georgantzas; Evangelos Katsamakas. Modeling a Simple Self-Organizing System. Advances in Systems Analysis, Software Engineering, and High Performance Computing 2014, 134 -148.
AMA StyleNicholas C. Georgantzas, Evangelos Katsamakas. Modeling a Simple Self-Organizing System. Advances in Systems Analysis, Software Engineering, and High Performance Computing. 2014; ():134-148.
Chicago/Turabian StyleNicholas C. Georgantzas; Evangelos Katsamakas. 2014. "Modeling a Simple Self-Organizing System." Advances in Systems Analysis, Software Engineering, and High Performance Computing , no. : 134-148.
The dynamic interactions of interdependent components in complex, adaptive, self-organizing systems (CASOS) often seem to sequester system entropy or uncertainty through distributed, as opposed to central, control. This article presents a system dynamics (SD) simulation model that not only replicates self-organizing system uncertainty results, but also looks at self-organization causally. The model analysis articulates how circular causal pathways or feedback loops in CASOS produce nonlinear dynamics spontaneously out of local interactions. The SD simulation and model analysis results show exactly how distributed control leads positive feedback to explosive growth, which ends when all dynamics have been absorbed into an attractor, leaving the system in a stable, negative feedback state. Cast as a methodological contribution, the article’s SD model analysis explains why phenomena of interest emerge in agent-based models, a topic crucial in understanding and designing CASOS. Moreover, CASOS concepts inspired by nature and biology can motivate biologically-inspired IS research.
Nicholas C. Georgantzas; Evangelos Katsamakas. Prominent Causal Paths in a Simple Self-Organizing System. International Journal of Information Technologies and Systems Approach 2012, 5, 25 -40.
AMA StyleNicholas C. Georgantzas, Evangelos Katsamakas. Prominent Causal Paths in a Simple Self-Organizing System. International Journal of Information Technologies and Systems Approach. 2012; 5 (2):25-40.
Chicago/Turabian StyleNicholas C. Georgantzas; Evangelos Katsamakas. 2012. "Prominent Causal Paths in a Simple Self-Organizing System." International Journal of Information Technologies and Systems Approach 5, no. 2: 25-40.
Evangelos G. Katsamakas; Nicholas C. Georgantzas. Open source disruptive-innovation strategy. Human Systems Management 2010, 29, 217 -229.
AMA StyleEvangelos G. Katsamakas, Nicholas C. Georgantzas. Open source disruptive-innovation strategy. Human Systems Management. 2010; 29 (4):217-229.
Chicago/Turabian StyleEvangelos G. Katsamakas; Nicholas C. Georgantzas. 2010. "Open source disruptive-innovation strategy." Human Systems Management 29, no. 4: 217-229.
Performance effects of information systems integration:: A system dynamics study in a media firm
Nicholas C. Georgantzas; Evangelos G. Katsamakas. Performance effects of information systems integration:. Business Process Management Journal 2010, 16, 822 -846.
AMA StyleNicholas C. Georgantzas, Evangelos G. Katsamakas. Performance effects of information systems integration:. Business Process Management Journal. 2010; 16 (5):822-846.
Chicago/Turabian StyleNicholas C. Georgantzas; Evangelos G. Katsamakas. 2010. "Performance effects of information systems integration:." Business Process Management Journal 16, no. 5: 822-846.
The dynamic complexity of the social phenomena that characterize ‘globalization’ accentuates a divisive public discourse with strong arguments for and against the globalization process and its effects. To help unearth the dynamic processes underlying globalization, this paper makes three contributions. First, it shows the recursive relations among technology, institutional structures, beliefs and social behaviour, which sociologist Giddens has posited on globalization. It incorporates not only favourable conditions, such as the development of telecommunications and global economic integration, but also political transformations and transnational corporation growth. Second, selected Giddens' globalization concerns about unemployment and welfare outline the components of a system dynamics modelling example. The model analysis reveals the dynamic complexity of the phenomenon and, most importantly, it shows how welfare‐support can fail in the long run. Third, the paper calls for a wider adoption of dynamic simulation modelling in the analysis of the globalization process and its effects. Copyright © 2010 John Wiley & Sons, Ltd.
Nicholas C Georgantzas; Evangelos Katsamakas; Dominik Solowiej. Exploring dynamics of Giddens' globalization. Systems Research and Behavioral Science 2010, 27, 622 -638.
AMA StyleNicholas C Georgantzas, Evangelos Katsamakas, Dominik Solowiej. Exploring dynamics of Giddens' globalization. Systems Research and Behavioral Science. 2010; 27 (6):622-638.
Chicago/Turabian StyleNicholas C Georgantzas; Evangelos Katsamakas; Dominik Solowiej. 2010. "Exploring dynamics of Giddens' globalization." Systems Research and Behavioral Science 27, no. 6: 622-638.
This chapter combines disruptive innovation strategy (DIS) theory with the system dynamics (SD) modeling method. It presents a simulation model of the hard-disk (HD) maker population overshoot and collapse dynamics, showing that DIS can crucially affect the dynamics of the IT industry. Data from the HD maker industry help calibrate the parameters of the SD model and replicate the HD makers’ overshoot and collapse dynamics, which DIS allegedly caused from 1973 through 1993. SD model analysis entails articulating exactly how the structure of feedback relations among variables in a system determines its performance through time. The HD maker population model analysis shows that, over five distinct time phases, four different feedback loops might have been most prominent in generating the HD maker population dynamics. The chapter shows the benefits of using SD modeling software, such as iThink®, and SD model analysis software, such as Digest®. The latter helps detect exactly how changes in loop polarity and prominence determine system performance through time. Strategic scenarios computed with the model also show the relevance of using SD for information system management and research in areas where dynamic complexity rules.
Nicholas C. Georgantzas; Evangelos Katsamakas. Information Technology Industry Dynamics. Emerging Systems Approaches in Information Technologies 2010, 274 -293.
AMA StyleNicholas C. Georgantzas, Evangelos Katsamakas. Information Technology Industry Dynamics. Emerging Systems Approaches in Information Technologies. 2010; ():274-293.
Chicago/Turabian StyleNicholas C. Georgantzas; Evangelos Katsamakas. 2010. "Information Technology Industry Dynamics." Emerging Systems Approaches in Information Technologies , no. : 274-293.
Nicholas C. Georgantzas; Evangelos Katsamakas. Disruptive Internet-service innovation diffusion. Human Systems Management 2009, 28, 163 -181.
AMA StyleNicholas C. Georgantzas, Evangelos Katsamakas. Disruptive Internet-service innovation diffusion. Human Systems Management. 2009; 28 (4):163-181.
Chicago/Turabian StyleNicholas C. Georgantzas; Evangelos Katsamakas. 2009. "Disruptive Internet-service innovation diffusion." Human Systems Management 28, no. 4: 163-181.
Little has been published about the application profiles and development patterns of open source software (OSS) in health and medical informatics. This study explores these issues with an analysis of health and medical informatics related OSS projects on SourceForge, a large repository of open source projects. A search was conducted on the SourceForge website during the period from May 1 to 15, 2007, to identify health and medical informatics OSS projects. This search resulted in a sample of 174 projects. A Java-based parser was written to extract data for several of the key variables of each project. Several visually descriptive statistics were generated to analyze the profiles of the OSS projects. Many of the projects have sponsors, implying a growing interest in OSS among organizations. Sponsorship, we discovered, has a significant impact on project success metrics. Nearly two-thirds of the projects have a restrictive license type. Restrictive licensing may indicate tighter control over the development process. Our sample includes a wide range of projects that are at various stages of development (status). Projects targeted towards the advanced end user are primarily focused on bio-informatics, data formats, database and medical science applications. We conclude that there exists an active and thriving OSS development community that is focusing on health and medical informatics. A wide range of OSS applications are in development, from bio-informatics to hospital information systems. A profile of OSS in health and medical informatics emerges that is distinct and unique to the health care field. Future research can focus on OSS acceptance and diffusion and impact on cost, efficiency and quality of health care.
Balaji Janamanchi; Evangelos Katsamakas; Wullianallur Raghupathi; Wei Gao. The State and Profile of Open Source Software Projects in health and medical informatics. International Journal of Medical Informatics 2009, 78, 457 -472.
AMA StyleBalaji Janamanchi, Evangelos Katsamakas, Wullianallur Raghupathi, Wei Gao. The State and Profile of Open Source Software Projects in health and medical informatics. International Journal of Medical Informatics. 2009; 78 (7):457-472.
Chicago/Turabian StyleBalaji Janamanchi; Evangelos Katsamakas; Wullianallur Raghupathi; Wei Gao. 2009. "The State and Profile of Open Source Software Projects in health and medical informatics." International Journal of Medical Informatics 78, no. 7: 457-472.
Nicholas C. Georgantzas; Evangelos Katsamakas. Tampering dynamics: SD-SPC insight. Human Systems Management 2008, 27, 89 -108.
AMA StyleNicholas C. Georgantzas, Evangelos Katsamakas. Tampering dynamics: SD-SPC insight. Human Systems Management. 2008; 27 (2):89-108.
Chicago/Turabian StyleNicholas C. Georgantzas; Evangelos Katsamakas. 2008. "Tampering dynamics: SD-SPC insight." Human Systems Management 27, no. 2: 89-108.
To encourage premium-quality information systems (IS) research in areas where dynamic complexity rules, this article combines disruptive innovation strategy (DIS) theory with the system dynamics (SD) modeling method. It presents a computer simulation model of the hard disk (HD) maker population overshoot and collapse dynamics. Data from the HD maker industry help calibrate the parameters of the SD model and replicate the HD makers’ overshoot and collapse dynamics, which DIS allegedly caused from 1973 through 1993. SD model analysis entails articulating exactly how the structure of feedback relations among variables in a system determines its performance through time. The analysis of the HD maker population model shows that, over five distinct time phases, four different feedback loops might have been most prominent in generating the HD maker population dynamics. The article shows the benefits of using SD modeling software, such as iThink®, and SD model analysis software, such as Digest®. The latter helps detect exactly how changes in loop polarity and prominence determine system performance through time. Strategic scenarios computed with the model also show the relevance of using SD for IS research and practice.
Nicholas C. Georgantzas; Evangelos Katsamakas. Disruptive Innovation Strategy Effects on Hard-Disk Maker Population. Information Resources Management Journal 2007, 20, 90 -107.
AMA StyleNicholas C. Georgantzas, Evangelos Katsamakas. Disruptive Innovation Strategy Effects on Hard-Disk Maker Population. Information Resources Management Journal. 2007; 20 (2):90-107.
Chicago/Turabian StyleNicholas C. Georgantzas; Evangelos Katsamakas. 2007. "Disruptive Innovation Strategy Effects on Hard-Disk Maker Population." Information Resources Management Journal 20, no. 2: 90-107.