A Simulation-Based Approach to Understanding the Wisdom of Crowds Phenomenon in Aggregating Expert Judgment

2021 | Business & Information Systems Engineering | Citations: 0

Authors: Afflerbach, Patrick; van Dun, Christopher; Gimpel, Henner; Parak, Dominik; Seyfried, Johannes

Abstract: Research has shown that aggregation of independent expert judgments significantl ... Expand

Abstract: Research has shown that aggregation of independent expert judgments significantly improves the quality of forecasts as compared to individual expert forecasts. This “wisdom of crowds” (WOC) has sparked substantial interest. However, previous studies on strengths and weaknesses of aggregation algorithms have been restricted by limited empirical data and analytical complexity. Based on a comprehensive analysis of existing knowledge on WOC and aggregation algorithms, this paper describes the design and implementation of a static stochastic simulation model to emulate WOC scenarios with a wide range of parameters. The model has been thoroughly evaluated: the assumptions are validated against propositions derived from literature, and the model has a computational representation. The applicability of the model is demonstrated by investigating aggregation algorithm behavior on a detailed level, by assessing aggregation algorithm performance, and by exploring previously undiscovered suppositions on WOC. The simulation model helps expand the understanding of WOC, where previous research was restricted. Additionally, it gives directions for developing aggregation algorithms and contributes to a general understanding of the WOC phenomenon. Collapse

Topics: open source knowledge base Python programming language crowdsourcing

Methods: computational algorithm simulation conceptual modelling experiment descriptive statistic

University Operations During a Pandemic: A Flexible Decision Analysis Toolkit

2021 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Kharkwal, Himanshu; Olson, Dakota; Huang, Jiali; Mohan, Abhiraj; Mani, Ankur; Srivastava, Jaideep

Abstract: Modeling infection spread during pandemics is not new, with models using past da ... Expand

Abstract: Modeling infection spread during pandemics is not new, with models using past data to tune simulation parameters for predictions. These help in understanding of the healthcare burden posed by a pandemic and responding accordingly. However, the problem of how college/university campuses should function during a pandemic is new for the following reasons: (i) social contact in colleges are structured and can be engineered for chosen objectives; (ii) the last pandemic to cause such societal disruption was more than 100 years ago, when higher education was not a critical part of society; (iii) not much was known about causes of pandemics, and hence effective ways of safe operations were not known; and (iv) today with distance learning, remote operation of an academic institution is possible. As one of the first to address this problem, our approach is unique in presenting a flexible simulation system, containing a suite of model libraries, one for each major component. The system integrates agent-based modeling and the stochastic network approach, and models the interactions among individual entities (e.g., students, instructors, classrooms, residences) in great detail. For each decision to be made, the system can be used to predict the impact of various choices, and thus enables the administrator to make informed decisions. Although current approaches are good for infection modeling, they lack accuracy in social contact modeling. Our agent-based modeling approach, combined with ideas from Network Science, presents a novel approach to contact modeling. A detailed case study of the University of Minnesota’s Sunrise Plan is presented. For each decision made, its impact was assessed, and results were used to get a measure of confidence. We believe that this flexible tool can be a valuable asset for various kinds of organizations to assess their infection risks in pandemic-time operations, including middle and high schools, factories, warehouses, and small/medium-sized businesses. Collapse

Topics: pandemic online learning system

Methods: simulation computational algorithm case study experiment stochastic model

Towards an Organizationally-Relevant Quantification of Cyber Resilience

2021 | HICSS | Citations: 0

Authors: Llanso, Thomas; Mcneil, Martha

Abstract: Given the difficulty of fully securing complex cyber systems, there is growing i ... Expand

Abstract: Given the difficulty of fully securing complex cyber systems, there is growing interest in making cyber systems resilient to the cyber threat. However, quantifying the resilience of a system in an organizationallyrelevant manner remains a challenge. This paper describes initial research into a novel metric for quantifying the resilience of a system to cyber threats called the Resilience Index (RI). We calculate the RI via an effects-based discrete event stochastic simulation that runs a large number of trials over a designated mission timeline. During the trials, adverse cyber events (ACEs) occur against cyber assets in a target system. We consider a trial a failure if an ACE causes the performance of any of the target system’s mission essential functions (MEFs) to fall below its assigned threshold level. Once all trials have completed, the simulator computes the ratio of successful trials to the total number of trials, yielding RI. The linkage of ACEs to MEFs provides the organizational tie. Collapse

Topics: desktop computer Microsoft Windows IT security threat business function

Methods: simulation design artifact stochastic simulation design science literature study

Partial order resolution of event logs for process conformance checking

2020 | Decision Support Systems | Citations: 0

Authors: van der Aa, Han; Leopold, Henrik; Weidlich, Matthias

Abstract: While supporting the execution of business processes, information systems record ... Expand

Abstract: While supporting the execution of business processes, information systems record event logs. Conformance checking relies on these logs to analyze whether the recorded behavior of a process conforms to the behavior of a normative specification. A key assumption of existing conformance checking techniques, however, is that all events are associated with timestamps that allow to infer a total order of events per process instance. Unfortunately, this assumption is often violated in practice. Due to synchronization issues, manual event recordings, or data corruption, events are only partially ordered. In this paper, we put forward the problem of partial order resolution of event logs to close this gap. It refers to the construction of a probability distribution over all possible total orders of events of an instance. To cope with the order uncertainty in real-world data, we present several estimators for this task, incorporating different notions of behavioral abstraction. Moreover, to reduce the runtime of conformance checking based on partial order resolution, we introduce an approximation method that comes with a bounded error in terms of accuracy. Our experiments with real-world and synthetic data reveal that our approach improves accuracy over the state-of-the-art considerably. Collapse

Topics: Java source code process mining open source data management

Methods: event log experiment business process modeling modeling language business process model and notation

Investigating the diffusion of IT consumerization in the workplace: A case study using social network analysis

2019 | Information Systems Frontiers | Citations: 0

Authors: Dang-Pham, Duy; Pittayachawan, Siddhi; Bruno, Vince; Kautz, Karlheinz

Abstract: IT consumerization, or the end-user’s adoption of consumer IT for work purpose, ... Expand

Abstract: IT consumerization, or the end-user’s adoption of consumer IT for work purpose, is an emerging topic which recently attracted the attention of researchers and practitioners. This research adopted social network analysis techniques to investigate the determinants of the social influence that resulted in IT consumerization, as well as the structural features of such influence’s network. By testing theoretically-based hypotheses with the exponential random graph modeling approach, our findings suggested that IT consumerization’s influence tended to occur between employees in the same department, coming especially from those who frequently gave work advice, life advice, and organizational updates to others, as well as those who were trusted for expertise by colleagues. The research revealed that IT consumerization’s influence was highly transitive, hierarchical, and non-reciprocal. The research concluded by elaborating future directions about the adoption of social network analysis techniques in technology adoption research, as well as practical recommendations about harnessing the determinants of such influence to manage IT consumerization. Collapse

Topics: social influence technology adoption network effect data security IT manager

Methods: network analysis survey statistical hypothesis test social network analysis Markov chain Monte Carlo

Theories: technology acceptance model theory of planned behavior

Investigating the Impact of Network Effects on Content Generation: Evidence from a Large Online Student Network

2015 | International Conference on Information Systems | Citations: 0

Authors: Bhattacharya, Prasanta; Phan, Tuan Q.; Airoldi, Edoardo M.

Abstract: Estimating the impact of network effects on content production and friendship fo ... Expand

Abstract: Estimating the impact of network effects on content production and friendship formation on social network sites (SNS) is of key importance to the platforms owners and online advertisers. However, past research on modeling network effects using observational data is limited by their inability to separate the effects of network formation from network influence. In the current study, we adapt an actor-based continuous-time model to jointly estimate the co-evolution of the users' social network and their content production behavior using a Markov Chain Monte Carlo (MCMC) based approach. Our analysis on a dataset of university students reveals that: 1) users tend to connect with others with similar posting behavior, 2) however, after connecting, they gradually diverge from their peers, and 3) the network effects are moderated by the level of the posting behavior. Our findings offer useful insights about the role of network effects to platform owners and social network researchers. Collapse

Topics: social network network effect social media social influence

Methods: simulation Markov chain Monte Carlo digital trace data Markov chain longitudinal research

Theories: co-evolution theory

Service-oriented intelligent group decision support system: Application in transportation management

2014 | Information Systems Frontiers | Citations: 0

Authors: He, Shiwei; Song, Rui; Chaudhry, Sohail S.

Abstract: In today’s ever changing consumer driven market economy, it is imperative for pr ... Expand

Abstract: In today’s ever changing consumer driven market economy, it is imperative for providers to respond expeditiously to the changes demanded by the customer. This phenomenon is no different in the transportation sector in which a service-oriented Group Decision Support System (GDSS) provides an important role in transportation enterprise to effectively manage and rapidly respond to the varying needs of the customer. In this paper, we explore the integration problem of service-oriented system and intelligence technology through the use of a GDSS. Initially, we analyze a service-oriented architecture and then, propose the design architecture of a service-oriented GDSS. Next, we put forward a general framework that integrates the intelligent techniques as a component into the architecture of service oriented GDSS. In addition, we illustrate how Artificial Intelligence techniques can resolve the conflicts of distributed group decisions. The paper is concluded by providing a number of applications in the railway management system that demonstrates the benefits of the utilization of a service oriented intelligent GDSS. Collapse

Topics: group decision support system transportation management artificial intelligence service oriented architecture fuzzy logic

Methods: computational algorithm optimization model stochastic simulation simulation

Theories: fuzzy set theory

Airline Codeshare Alliances: Marketing Boon and Revenue Management Information Systems Challenge

2013 | Business & Information Systems Engineering | Citations: 0

Authors: Gerlach, Max; Cleophas, Catherine; Kliewer, Natalia

Abstract: Codeshare alliances are a popular instrument for airlines to grow profitably. T ... Expand

Abstract: Codeshare alliances are a popular instrument for airlines to grow profitably. This paper juxtaposes the challenges that they create for analytical information systems on the one hand and their motivation from a marketing perspective on the other. In this regard, revenue management systems as a central tool of the ticketing process are of particular interest. Complementary codesharing reduces alliance-wide revenues by up to 1 %. Losses disseminate over the whole network and increase with total demand and the degree of codeshare demand. Virtual codesharing causes losses of up to 1.5 % depending on the discount level offered by the marketing carrier and on the demand structure. Based on the findings, recommendations for airline management and future research are derived. Collapse

Topics: price management dynamic pricing marketing management analytical information system marketing information system

Methods: simulation stochastic simulation literature study

Optimal planning of sensor networks for asset tracking in hospital environments

2013 | Decision Support Systems | Citations: 0

Authors: Pietrabissa, Antonio; Poli, Cecilia; Ferriero, Dario Giuseppe; Grigioni, Mauro

Abstract: An optimization framework is proposed to plan a sensor network in hospital envir ... Expand

Abstract: An optimization framework is proposed to plan a sensor network in hospital environments aimed at tracking medical assets. Firstly, an innovative statistical simulation model of the asset movements is developed, to define the critical levels of the hospital locations. The model feeds an optimization algorithm, which determines the optimal placements of the sensors, modeled by their coverage characteristics. Since the optimization framework is modular, it can be used for different network technologies. Simulation results are presented, considering a case-study based on the plan of the cardiology department of the “San Camillo” hospital in Rome and on interviews with the personnel. Collapse

Topics: radio frequency identification frequency of use

Methods: simulation computational algorithm optimization model qualitative interview case study

Using time-driven activity-based costing to manage digital forensic readiness in large organisations

2012 | Information Systems Frontiers | Citations: 0

Authors: Reddy, K.; Venter, H. S.; Olivier, M. S.

Abstract: A digital forensic readiness (DFR) programme consists of a number of activities ... Expand

Abstract: A digital forensic readiness (DFR) programme consists of a number of activities that should be chosen and managed with respect to cost constraints and risk. Traditional cost systems, however, can not provide the cost of individual activities. This makes it difficult or impossible for organisations to consider cost when making decisions about specific activities. In this paper we show that the relatively new cost system, time-driven activity-based costing (TDABC), can be used to determine the cost of implementing and managing activities required for DFR. We show through analysis and simulation that the cost information from a TDABC model can be used for such decisions. We also discuss some of the factors that ought to be considered when implementing or managing the use of TDABC in a large organisation. Collapse

Topics: firewall data security decision making privacy Java

Methods: simulation literature study survey stochastic simulation computational algorithm