IDEAS home Printed from https://ideas.repec.org/f/pka1386.html
   My authors  Follow this author

Harleen Kaur

Personal Details

First Name:Harleen
Middle Name:
Last Name:Kaur
Suffix:
RePEc Short-ID:pka1386

Affiliation

Department of Accountancy, Economics and Finance
Heriot-Watt University

Edinburgh, United Kingdom
https://www.hw.ac.uk/uk/schools/social-sciences/accountancy-economics-finance.htm
RePEc:edi:dehwuuk (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Books

Working papers

  1. Lechman, Ewa & Kaur, Harleen, 2016. "Social development and ICT adoption. Developing world perspective," MPRA Paper 69354, University Library of Munich, Germany.
    repec:gdk:wpaper:34 is not listed on IDEAS
    repec:gdk:wpaper:33 is not listed on IDEAS

Articles

  1. Baboota, Rahul & Kaur, Harleen, 2019. "Predictive analysis and modelling football results using machine learning approach for English Premier League," International Journal of Forecasting, Elsevier, vol. 35(2), pages 741-755.
  2. Adam Marszk & Ewa Lechman & Harleen Kaur, 2017. "Financial Markets Diffusion Patterns. The Case Of Mexican Investment Funds," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 12(1), pages 83-100, March.
  3. Ritu Chauhan & Harleen Kaur, 2017. "A feature-based selection technique for reduction of large scale data," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 9(3), pages 207-221.
  4. Harleen Kaur & Ajay Pandit, 2015. "Modelling Consumer Evaluation of Brand Extensions: Empirical Evidence from India," Vision, , vol. 19(1), pages 37-48, March.

Books

  1. Harleen Kaur & Ewa Lechman & Adam Marszk (ed.), 2017. "Catalyzing Development through ICT Adoption," Springer Books, Springer, number 978-3-319-56523-1, November.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Lechman, Ewa & Kaur, Harleen, 2016. "Social development and ICT adoption. Developing world perspective," MPRA Paper 69354, University Library of Munich, Germany.

    Cited by:

    1. Bryan Coyne & Eleanor Denny, 2021. "Applying a Model of Technology Diffusion to Quantify the Potential Benefit of Improved Energy Efficiency in Data Centres," Energies, MDPI, vol. 14(22), pages 1-18, November.

Articles

  1. Baboota, Rahul & Kaur, Harleen, 2019. "Predictive analysis and modelling football results using machine learning approach for English Premier League," International Journal of Forecasting, Elsevier, vol. 35(2), pages 741-755.

    Cited by:

    1. Christoph Schlembach & Sascha L. Schmidt & Dominik Schreyer & Linus Wunderlich, 2020. "Forecasting the Olympic medal distribution during a pandemic: a socio-economic machine learning model," Papers 2012.04378, arXiv.org, revised Jun 2021.
    2. Daniel Goller & Michael C. Knaus & Michael Lechner & Gabriel Okasa, 2021. "Predicting match outcomes in football by an Ordered Forest estimator," Chapters, in: Ruud H. Koning & Stefan Kesenne (ed.), A Modern Guide to Sports Economics, chapter 22, pages 335-355, Edward Elgar Publishing.
    3. Green, Lawrence & Sung, Ming-Chien & Ma, Tiejun & Johnson, Johnnie E. V., 2019. "To what extent can new web-based technology improve forecasts? Assessing the economic value of information derived from Virtual Globes and its rate of diffusion in a financial market," European Journal of Operational Research, Elsevier, vol. 278(1), pages 226-239.
    4. Galli, L. & Galvan, G. & Levato, T. & Liti, C. & Piccialli, V. & Sciandrone, M., 2021. "Football: Discovering elapsing-time bias in the science of success," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    5. Wheatcroft Edward, 2021. "Evaluating probabilistic forecasts of football matches: the case against the ranked probability score," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 17(4), pages 273-287, December.
    6. Chunyang Huang & Shaoliang Zhang, 2023. "Explainable artificial intelligence model for identifying Market Value in Professional Soccer Players," Papers 2311.04599, arXiv.org, revised Nov 2023.
    7. Maurizio Carpita & Enrico Ciavolino & Paola Pasca, 2021. "Players’ Role-Based Performance Composite Indicators of Soccer Teams: A Statistical Perspective," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 815-830, August.
    8. Harleen Kaur & Shafqat Ul Ahsaan & Bhavya Alankar & Victor Chang, 2021. "A Proposed Sentiment Analysis Deep Learning Algorithm for Analyzing COVID-19 Tweets," Information Systems Frontiers, Springer, vol. 23(6), pages 1417-1429, December.
    9. Wheatcroft, Edward, 2021. "Evaluating probabilistic forecasts of football matches: the case against the ranked probability score," LSE Research Online Documents on Economics 111494, London School of Economics and Political Science, LSE Library.
    10. Federico Fioravanti & Fernando Delbianco & Fernando Tohmé, 2023. "The relative importance of ability, luck and motivation in team sports: a Bayesian model of performance in the English Rugby Premiership," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(3), pages 715-731, September.
    11. Hassanniakalager, Arman & Sermpinis, Georgios & Stasinakis, Charalampos & Verousis, Thanos, 2020. "A conditional fuzzy inference approach in forecasting," European Journal of Operational Research, Elsevier, vol. 283(1), pages 196-216.
    12. Schlembach, Christoph & Schmidt, Sascha L. & Schreyer, Dominik & Wunderlich, Linus, 2022. "Forecasting the Olympic medal distribution – A socioeconomic machine learning model," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    13. da Costa, Igor Barbosa & Marinho, Leandro Balby & Pires, Carlos Eduardo Santos, 2022. "Forecasting football results and exploiting betting markets: The case of “both teams to score”," International Journal of Forecasting, Elsevier, vol. 38(3), pages 895-909.
    14. Butler, David & Butler, Robert & Eakins, John, 2021. "Expert performance and crowd wisdom: Evidence from English Premier League predictions," European Journal of Operational Research, Elsevier, vol. 288(1), pages 170-182.
    15. Koopman, Siem Jan & Lit, Rutger, 2019. "Forecasting football match results in national league competitions using score-driven time series models," International Journal of Forecasting, Elsevier, vol. 35(2), pages 797-809.
    16. Fry, John & Serbera, Jean-Philippe & Wilson, Rob, 2021. "Managing performance expectations in association football," Journal of Business Research, Elsevier, vol. 135(C), pages 445-453.

  2. Adam Marszk & Ewa Lechman & Harleen Kaur, 2017. "Financial Markets Diffusion Patterns. The Case Of Mexican Investment Funds," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 12(1), pages 83-100, March.

    Cited by:

  3. Harleen Kaur & Ajay Pandit, 2015. "Modelling Consumer Evaluation of Brand Extensions: Empirical Evidence from India," Vision, , vol. 19(1), pages 37-48, March.

    Cited by:

    1. Richa Joshi & Rajan Yadav, 2018. "An Integrated SEM Neural Network Approach to Study Effectiveness of Brand Extension in Indian FMCG Industry," Business Perspectives and Research, , vol. 6(2), pages 113-128, July.
    2. Richa Joshi & Rajan Yadav, 2017. "Evaluating the Feedback Effects of Brand Extension on Parent Brand Equity: A Study on Indian FMCG Industry," Vision, , vol. 21(3), pages 305-313, September.

Books

  1. Harleen Kaur & Ewa Lechman & Adam Marszk (ed.), 2017. "Catalyzing Development through ICT Adoption," Springer Books, Springer, number 978-3-319-56523-1, November.

    Cited by:

    1. Kyunghun Min & Moonyoung Yoon & Katsunori Furuya, 2019. "A Comparison of a Smart City’s Trends in Urban Planning before and after 2016 through Keyword Network Analysis," Sustainability, MDPI, vol. 11(11), pages 1-25, June.
    2. Ibukun Beecroft & Evans S. Osabuohien & Uchenna R. Efobi & Isaiah Olurinola & Romanus A. Osabohien, 2019. "Manufacturing Export and ICT Infrastructure in West Africa: Investigating the Roles of Economic and Political Institutions," Working Papers of the African Governance and Development Institute. 19/098, African Governance and Development Institute..
    3. Nkoumou Ngoa, Gaston Brice & Song, Jacques Simon, 2021. "Female participation in African labor markets: The role of information and communication technologies," Telecommunications Policy, Elsevier, vol. 45(9).
    4. Antonio Rodríguez Andrés & Abraham Otero & Voxi Heinrich Amavilah, 2022. "Knowledge economy classification in African countries: A model-based clustering approach," Information Technology for Development, Taylor & Francis Journals, vol. 28(2), pages 372-396, April.
    5. Voxi Heinrich Amavilah & Antonio Rodriguez Andres, 2022. "Knowledge Economy and the Economic Performance of African Countries: A Seemingly Unrelated and Recursive Approach," Working Papers 57, The German University in Cairo, Faculty of Management Technology.
    6. Beáta Gavurová & Antonio José Balloni & Miriama Tarhaničová & Viliam Kováč, 2018. "Information and Communication Technology in the Role of Information System of Healthcare Facility in the Slovak Republic," Economies, MDPI, vol. 6(3), pages 1-15, August.
    7. Baboota, Rahul & Kaur, Harleen, 2019. "Predictive analysis and modelling football results using machine learning approach for English Premier League," International Journal of Forecasting, Elsevier, vol. 35(2), pages 741-755.
    8. Monica Răileanu Szeles & Mihaela Simionescu, 2020. "Regional Patterns and Drivers of the EU Digital Economy," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 150(1), pages 95-119, July.
    9. Muhammad Mofizur Rahman, 2020. "Impact of digital technology in higher education: Perspective from Bangladesh," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 9(5), pages 318-325, September.
    10. Monica RĂILEANU SZELES & Carmen ANTON & Mirela BABA & Steliana BUSUIOCEANU & Adriana LITRĂ & Titus SUCIU, 2019. "Explaining The EU Regional Economic Growth upon Regional- and Country- Level Achievements in Education," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 143-157, March.
    11. Jeremiah O. Ejemeyovwi & Evans S. Osabuohien & Olawale D. Johnson & Ebenezer I. K. Bowale, 2019. "Internet usage, innovation and human development nexus in Africa: the case of ECOWAS," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 8(1), pages 1-16, December.
    12. Donou-Adonsou, Ficawoyi, 2019. "Technology, education, and economic growth in Sub-Saharan Africa," Telecommunications Policy, Elsevier, vol. 43(4), pages 353-360.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ICT: Information and Communication Technologies (1) 2016-02-23. Author is listed

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Harleen Kaur should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.