By Carina Antonia Hallin and Julian J. U. Jensen (2017).
ISBN: 9788799957903
The book is published in Danish.
By Torben Juul Andersen, Carina Antonia Hallin, Kjeld Fredens (2018).
ISBN 9788702237252
The book is published in Danish.
By Torben Juul Andersen, Carina Antonia Hallin (2017).
ISBN 9781315469034
Global firms must operate in turbulent conditions, facing relentless pressure to be efficient, whilst also accommodating local factors and ways of thinking. This book offers an insight into how an adaptive multinational enterprise can achieve a sustainable competitive advantage in an uncertain environment.
Carina Antonia Hallin (2009)
By Flore Bridoux, Victor Zitian Chen, Carina Antonia Hallin, Michael A. Hitt, Marc van Essen, Weihua Zhou (2021/2022).
We are not doing just another call for papers. We are requesting revolutionary blueprints of our shared future
International Journal of Management Reviews- The leading global review journal in Organisation and Management Studies (OMS).
By Stephen Boucher, Carina Antonia Hallin and Lex Paulson (Upcoming editorial publication).
A collaborative academic book that will provide policy makers, students and civil society with an informed set of material that illustrate how collective intelligence can be mobilized in practice to develop more effective policies and strengthen democratic frameworks.
Koren, O., Hallin, C.A., Koren, M., Issa, A. A. (2021). AutoML Classifer Clustering Procedure. Interational Journal of Intelligent Systems. https://doi.org/10.1002/int.22718
Hallin, C.A., Jensen, J.J.U., Koren, O., Perel, N. and Tveteras, S. (2019) Testing Smart Crowds for the Economy. In:
Proceedings of the ACM Collective Intelligence 2019, Ed. Andrés Monroy-Hernández, Melissa Valentine. New York:
Association for Computing Machinery.
Koren, O., Hallin, C.A., Perel, N., and Bendet, D. (2019) Decision-Making Enhancement in a Big Data Environment: Application of the K-Means Algorithm to Mixed Data. Journal of Artificial Intelligence and Soft Computing Research.
Li, X., Andersen, T.J. and Hallin, C.A. (2019) A Zhong–Yong Perspective on Balancing the Top-down and Bottom-up Processes in Strategy-making.
Cross Cultural and Strategic Management, Vol. 26, No. 3, 2019, pp. 313–336.
Koren, O., Hallin, C.A., Perel, N. and Benet, D. (2018). Enhancement of the K-Means Algorithm for Mixed Data in Big Data Platforms, Intelligent Systems and Applications, Proceedings of the 2018 Intelligent Systems Conference (IntelliSys) Volume 1.
Hallin, C.A., Andersen, T.J. and Tveterås, S. (2017). Harnessing the Frontline Sensing of Capabilities for Decision Support.
Decision Support Systems, Vol. 97: 104-112
Hallin, C.A., Øgaard, T., and Marnburg, E. (2009). Exploring Qualitative Differences in Knowledge Sources: A Study of Hierarchical Effects of Judgmental Confidence and Accuracy Performance. International Journal of Knowledge Management, 5 (4), 1-25.
Hallin, C.A. and Marnburg, E. (2008). Knowledge Management in the Hospitality Industry: A Review of Empirical Research. Tourism Management, 29, 366-381.
Andersen, T.J., Hallin C.A., and Li, X. (2014). An Integrative Model of Dynamic Strategy-Making: A Yin- Yang Perspective of Central and Peripheral Mechanisms in (Global) Strategy Formation. Frederiksberg: Center for Global Strategic Responsiveness. CBS, (2014), 30 p. (CGSR Working Paper Series, No. 5).
Hallin, C.A., Andersen, T.J. Tveterås, S. (2013) Fuzzy Predictions for Strategic Decision Making: A Third- Generation Prediction Market. Frederiksberg: Copenhagen Business School, (CGSR Working Paper Series No. 2).
Hallin, C.A., Andersen, T.J. and Tveterås, S. A (2012). Prediction Contest: The Sensing of Frontline Employees Against Executive Expectations. Frederiksberg: Department of Strategic Management and Globalization. Copenhagen Business School, (SMG Working Paper; No. 2).
Hallin, C.A. Tveterås, S. and Andersen, T.J. (2012). Judgmental Forecasting of Operational Capabilities: Exploring a New Indicator to Predict Financial Performance. Frederiksberg: Copenhagen Business School, INT Working Paper.
Jie Zhang and Nino Javakhishvili-Larsen (2021). Asymmetries of local economic impacts of digital entrepreneurship in Denmark: The case of Airbnb. E. Vinogradov, B. Leick and D. Assadi (Eds.) Digital Entrepreneurship and the Sharing Economy, Routledge. pp.: 91-108. DOI: 10.4324/9781003036821-8.
Andersen, T.J. and Hallin, C.A. (2017). Democratizing the Multinational Corporation (MNC): Interaction between Intent at Headquarters and Autonomous Subsidary Initiatives. In The Responsive Global Organization: New Insights from Global Strategy and International Business. Ed. Torben Juul Andersen. Bingley: Emerald Group Publishing Limited, pp. 71-86.
Andersen, T.J., and Hallin, C.A. (2016) The Adaptive Organization and Fast-Slow Systems. Oxford Research Encyclopedias: Business and Management. A Community of Experts. red. Ramon J. Aldag. New York: Oxford University Press.
Hallin, C.A. (2016). Aggregating Strategic Risk Information from the Operational Frontline: A new Proactive Risk Management Practice. The Routledge Companion on Strategic Risk Management. (Routledge Companions in Business, Management and Accounting). Abingdon: Routledge, pp. 487-500.
Hallin, C.A. (2012). An Organizational Prediction Market: Turning Frontline Employees into Visionaires. In Current Research in Hospitality and Tourism Research. Norway, Bergen: Fagbokforlaget.
Gammelgaard, F. B., & Hallin, C. A. (2018). Changing the Innovation Game: Crowdsourcing in Incumbent Firms. Paper præsenteret på 6th Collective Intelligence, Zurich, Schweiz.
Hallin, C.A. (2017). The State of Collective Intelligence Behavior and Practices. Paper presented at Collective Intelligence Conference 2017, New York, USA.
Andersen, T. J., Bresser, R. K. F., & Hallin, C. A. (2016). The Dynamics of Strategic Decision-Making: Using Updated Information from the Frontline. Paper præsenteret på SMS Special Conference Rome, Rom, Italien.
Hallin, C.A. and Lind, A.S. (2016). Identification of Strategic Issues for Crowd Predictions. Paper presented at the 2016 Collective Intelligence Conference, New York, USA.
Hallin, C.A., Andersen, T.J and Levine, S.S. (2015). The Evolution of Prediction Aggregation Mechanisms: Towards Leveraging the Frontline for Strategic Issue Identification under Uncertainty. MIT’s Collective Intelligence Conference 2015, California, US.
Andersen, T.J., Hallin, C.A. and Li, X. (2014). A Model of Dynamic Strategy-Making : The Yin-Yang Process of Top-Down and Bottom-Up Mechanisms. Paper presented at Strategic Management Society Special Conference Sydney, Australia. 2014.
Hallin, C.A. and Andersen. T.J. (2014) Responding to the Challenge of True Uncertainty: Stakeholder Sensing and Predictions of Emergent Strategic Issues. Paper presented at Strategic Management Society 34th Annual International Conference. SMS 2014, Madrid, Spain. 2014
Hallin, C.A., Andersen, T.J. and Ooi, C.S. (2014). How Stakeholder Sensing and Anticipations Shape the Firm’s Strategic Response Capability. Paper presented at Strategic Management Society 34th Annual International Conference. SMS 2014, Madrid, Spain. 2014.
Hallin, C.A., Andersen, T.J. and Tveterås, S. (2014). 'Red Flag' Predictions: Using Frontline Employees to Assess the State of Operational Capabilities. Paper presented at Strategic Management Society Special Conference Tel Aviv, Israel. 2014.
Hallin, C.A. (2013). Collecting Strategic Risk Information from the Operational Frontline. Poster session presented at 6th International Risk Management Conference 2013, Frederiksberg, Denmark. 2013.
Hallin, C.A., Andersen, T.J. & Tveterås, S. (2013). Wbo are the Better Predictors: Frontline Employees or Executive Managers. SMS 33rd Annual International Conference. ed. / Pamela Barr; Frank T. Rothaermel. Atlanta: Strategic Management Society, 2013.
Hallin, C.A., Andersen & Tveterås, S. (2012). The Sensing of Operational Capabilities by Frontline Employees Against Executive Judgements : Who Wins the Prediction Contest?.Abstract presented at the International Conference on Business Performance Measurement and Management, Lima, Peru., September 11-13
Hallin, C.A., Andersen, T.J., Foss, N.J. & Tveterås, S. (2011). Forecasting Firm Performance: Why Firms should Rely on Employee Sensing. Paper presented at the Iberoamerican Academy of Management, Seventh International Meeting, Lima, Peru, December 5-7, 2011.Reports
Hallin et al. (2020). Crowd-Forudsigelser fra Frontlinjen Afrapportering. Industriens Fond. https://flipflashpages.uniflip.com/3/80821/1114371/pub/html5.html#page/1
Hallin et al. (2020).
Crowd-Forudsigelser fra Frontlinjen Casestudier.
Industriens Fond
https://flipflashpages.uniflip.com/3/80821/1114275/pub/html5.html
Hallin et al. (2020).
Ideation, Filtrering og Forudsigelsesdesign I Fem Faser: En Praktisk Guide til Danske Virksomheder.
Industriens Fond
https://flipflashpages.uniflip.com/3/80821/1114276/pub/html5.html
Hallin, C. A., & Jensen, J. J. U. (2017).
Kollektiv intelligens: Adfærd og praksis i Danmarks største virksomheder.
Department of International Economics and Management, Copenhagen Business School. Forskningsrapport CBS-INT, Nr. 1/2017
https://research.cbs.dk/en/publications/kollektiv-intelligens-adf%C3%A6rd-og-praksis-i-danmarks-st%C3%B8rste-virkso
Hallin, C.A. Evidence of Collective Intelligence in Organizations.
Gammelgaard, F.B. and Hallin, C.A. Barriers to Crowdsourcing in Large Organizations.
Hallin, C.A. and Gammelgaard, F.B. The adoption of Collective Intelligence Behavior and Practices in Strategy-Making.
Hallin, C.A. Collective Intelligence: An Emergent Discipline in Management.
Hallin, C.A. On the Outlook for Weak Signals: Harnessing Collective Intelligence for Strategic Issue Management.
Hallin, C.A., Tveteraas, S., Koren, O., and Perel, N. Identify Smart Crowds for the Economy.
Hallin, C.A. A Typology of “The Predictive Wisdom” of Stakeholders for Decision-Making.
Aminpour, P., Gray, S., Paulson, L., Hallin, C.A. et al. Becoming Intelligent about Collective Intelligence for Public Policy.
Boucher, S., Hallin, C.A., and Paulson, L.
Smarter Together: 50 Case Studies on Collective Intelligence for Public Policy.
Koren, O., Koren, M., and Hallin, C.A. Classifier Clustering Procedure in Big Data Platforms.