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Ron S. Kenett

Personal Details

First Name:Ron
Middle Name:S.
Last Name:Kenett
Suffix:
RePEc Short-ID:pke139
http://www.kpa-group.com
POBox 2525, Raanana 43100, Israel

Affiliation

(60%) Samuel Neaman Institute, Technion (Samuel Neaman Institute, Technion)

http://www.neaman.org.il/EN/Ron-Kenett
Israel, Haifa

(24%) KPA Group (KPA Group)

http://www.kpa-group.com/
Israel

(14%) Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche
Università degli Studi di Torino

Torino, Italy
http://www.esomas.unito.it/
RePEc:edi:dstorit (more details at EDIRC)

(1%) Institute for Drug Research (Institute for Drug Research, School of Pharmacy, Hebrew University)

https://medicine.ekmd.huji.ac.il/schools/pharmacy/En/research/Pages/default.aspx
Israel, Jerusalem

(1%) Ekonomska fakuteta
Univerza v Ljubljani

Ljubljana, Slovenia
http://www.ef.uni-lj.si/
RePEc:edi:feuljsi (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Silvia Figini & Ron Kenett & SILVIA SALINI, 2010. "Integrating Operational and Financial Risk Assessments," UNIMI - Research Papers in Economics, Business, and Statistics unimi-1099, Universitá degli Studi di Milano.
  2. Silvia Salini & Ron Kenett, 2008. "Relative Linkage Disequilibrium: A New measure for association rules," UNIMI - Research Papers in Economics, Business, and Statistics unimi-1069, Universitá degli Studi di Milano.

Articles

  1. Ron S. Kenett & Abraham Rubinstein, 2021. "Generalizing research findings for enhanced reproducibility: an approach based on verbal alternative representations," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4137-4151, May.
  2. Ron S. Kenett, 2020. "A review of data science in business and industry and a future view by G. Vicario and S. Coleman," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 36(1), pages 30-32, January.
  3. Ron Kenett, 2019. "A review of: The class of CUB models: statistical foundations, inferential issues and empirical evidence by Domenico Piccolo and Rosaria Simone," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 457-458, September.
  4. Kenett Ron S. & Shmueli Galit, 2016. "From Quality to Information Quality in Official Statistics," Journal of Official Statistics, Sciendo, vol. 32(4), pages 867-885, December.
  5. Ron S. Kenett & Galit Shmueli, 2015. "A special issue on: Actual impact and future perspectives on stochastic modelling in business and industry," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 31(1), pages 1-2, January.
  6. Ron S. Kenett & Galit Shmueli, 2014. "On information quality," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 177(1), pages 3-38, January.
  7. Muslima Zahan & Ron S. Kenett, 2013. "Modeling and Forecasting Energy Consumption in the Manufacturing Industry in South Asia," International Journal of Energy Economics and Policy, Econjournals, vol. 3(1), pages 87-98.
  8. Ron S. Kenett & Shelemyahu Zacks, 2013. "Industrial statistics applications in the semiconductor industry: some examples," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 29(4), pages 319-333, July.
  9. Ron S. Kenett, 2012. "‘The COM‐Poisson model for count data: a survey of methods and applications’ by K. Sellers, S. Borle and G. Shmueli," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 28(2), pages 117-121, March.
  10. Ron S. Kenett & Silvia Salini, 2011. "Modern analysis of customer satisfaction surveys: comparison of models and integrated analysis," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 27(5), pages 465-475, September.
  11. Ron S. Kenett & Silvia Salini, 2011. "Rejoinder to ‘Modern analysis of customer satisfaction surveys: comparison of models and integrated analysis’," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 27(5), pages 484-486, September.
  12. Silvia Salini & Ron Kenett, 2009. "Bayesian networks of customer satisfaction survey data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(11), pages 1177-1189.
  13. Ron S. Kenett, 2009. "‘Post‐financial meltdown: What do the services industries need from us now?’ by Roger W. Hoerl and Ronald D. Snee: Discussion 2," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(5), pages 527-531, September.
  14. Ron Kenett, 2006. "On the planning and design of sample surveys," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(4), pages 405-415.
  15. R. Kenett & P. Thyregod, 2006. "Aspects of statistical consulting not taught by academia," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 60(3), pages 396-411, August.
  16. Agnihothri, Saligrama R. & Kenett, Ron S., 1995. "The impact of defects on a process with rework," European Journal of Operational Research, Elsevier, vol. 80(2), pages 308-327, January.

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

    Sorry, no citations of working papers recorded.

Articles

  1. Ron S. Kenett & Galit Shmueli, 2014. "On information quality," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 177(1), pages 3-38, January.

    Cited by:

    1. Inbal Yahav & Galit Shmueli, 2014. "Outcomes matter: estimating pre-transplant survival rates of kidney-transplant patients using simulator-based propensity scores," Annals of Operations Research, Springer, vol. 216(1), pages 101-128, May.
    2. Mahsa Ashouri & Kate Cai & Furen Lin & Galit Shmueli, 2018. "Assessing the Value of an Information System for Developing Predictive Analytics: The Case of Forecasting School-Level Demand in Taiwan," Service Science, INFORMS, vol. 10(1), pages 58-75, March.
    3. Pierpaolo D’Urso & Vincenzina Vitale, 2020. "Bayesian Networks Model Averaging for Bes Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 151(3), pages 897-919, October.
    4. Kenett Ron S. & Shmueli Galit, 2016. "From Quality to Information Quality in Official Statistics," Journal of Official Statistics, Sciendo, vol. 32(4), pages 867-885, December.
    5. Askitas, Nikos, 2016. "Big Data Is a Big Deal But How Much Data Do We Need?," IZA Discussion Papers 9988, Institute of Labor Economics (IZA).
    6. Coleman Shirley Y., 2016. "Data-Mining Opportunities for Small and Medium Enterprises with Official Statistics in the UK," Journal of Official Statistics, Sciendo, vol. 32(4), pages 849-865, December.
    7. Ron S. Kenett & Abraham Rubinstein, 2021. "Generalizing research findings for enhanced reproducibility: an approach based on verbal alternative representations," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4137-4151, May.
    8. Paola Zola & Paulo Cortez & Costantino Ragno & Eugenio Brentari, 2019. "Social Media Cross-Source and Cross-Domain Sentiment Classification," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(05), pages 1469-1499, September.
    9. Pierpaolo D’Urso & Vincenzina Vitale, 2021. "Modeling Local BES Indicators by Copula-Based Bayesian Networks," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 153(3), pages 823-847, February.
    10. Domenico Piccolo & Rosaria Simone, 2019. "Rejoinder to the discussion of “The class of cub models: statistical foundations, inferential issues and empirical evidence”," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 477-493, September.
    11. Ruojing Zhang & Marta Indulska & Shazia Sadiq, 2019. "Discovering Data Quality Problems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(5), pages 575-593, October.
    12. Federica Cugnata & Silvia Salini, 2014. "Model-based approach for importance–performance analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(6), pages 3053-3064, November.
    13. Galit Shmueli, 2020. "Discussion on “Assessing the goodness of fit of logistic regression models in large samples: A modification of the Hosmer‐Lemeshow test” by Giovanni Nattino, Michael L. Pennell, and Stanley Lemeshow," Biometrics, The International Biometric Society, vol. 76(2), pages 561-563, June.
    14. Rosaria Simone, 2023. "Uncertainty Diagnostics of Binomial Regression Trees for Ordered Rating Data," Journal of Classification, Springer;The Classification Society, vol. 40(1), pages 79-105, April.
    15. Biemer Paul & Trewin Dennis & Bergdahl Heather & Japec Lilli, 2014. "A System for Managing the Quality of Official Statistics," Journal of Official Statistics, Sciendo, vol. 30(3), pages 1-35, September.

  2. Muslima Zahan & Ron S. Kenett, 2013. "Modeling and Forecasting Energy Consumption in the Manufacturing Industry in South Asia," International Journal of Energy Economics and Policy, Econjournals, vol. 3(1), pages 87-98.

    Cited by:

    1. Irina A. Firsova & Dinara G. Vasbieva & Nikolay N. Kosarenko & Maria A. Khvatova & Lev R. Klebanov, 2019. "Energy Consumption Forecasting for Power Supply Companies," International Journal of Energy Economics and Policy, Econjournals, vol. 9(1), pages 1-6.
    2. Köppelová, J. & Jindrová, A., 2017. "Comparative Study of Short-Term Time Series Models: Use of Mobile Telecommunication Services in CR Regions," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 9(1), March.

  3. Ron S. Kenett & Silvia Salini, 2011. "Modern analysis of customer satisfaction surveys: comparison of models and integrated analysis," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 27(5), pages 465-475, September.

    Cited by:

    1. Paolo Castelnovo & Martina Dal Molin, 2021. "The learning mechanisms through public procurement for innovation: The case of government‐funded basic research organizations," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 92(3), pages 411-446, September.
    2. Domenico Piccolo & Rosaria Simone, 2019. "The class of cub models: statistical foundations, inferential issues and empirical evidence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 389-435, September.
    3. Violetta Simonacci & Michele Gallo, 2017. "Statistical tools for student evaluation of academic educational quality," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(2), pages 565-579, March.
    4. Alfio Ferrara & Silvia Salini, 2012. "Ten challenges in modeling bibliographic data for bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(3), pages 765-785, December.
    5. Hamed Taherdoost & Mitra Madanchian, 2021. "Empirical Modeling of Customer Satisfaction for E-Services in Cross-Border E-Commerce," Post-Print hal-03741849, HAL.
    6. Peter Martey Addo & Dominique Guegan & Bertrand Hassani, 2018. "Credit Risk Analysis Using Machine and Deep Learning Models," Risks, MDPI, vol. 6(2), pages 1-20, April.
    7. Mohamed Hanafy & Ruixing Ming, 2021. "Machine Learning Approaches for Auto Insurance Big Data," Risks, MDPI, vol. 9(2), pages 1-23, February.
    8. Federica Cugnata & Silvia Salini, 2014. "Model-based approach for importance–performance analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(6), pages 3053-3064, November.
    9. Ron S. Kenett & Giancarlo Manzi & Carmit Rapaport & Silvia Salini, 2022. "Integrated Analysis of Behavioural and Health COVID-19 Data Combining Bayesian Networks and Structural Equation Models," IJERPH, MDPI, vol. 19(8), pages 1-26, April.
    10. Antonino Mario Oliveri & Gabriella Polizzi & Anna Maria Parroco, 2019. "Measuring Tourist Satisfaction Through a Dual Approach: The 4Q Methodology," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 361-382, November.

  4. Ron S. Kenett & Silvia Salini, 2011. "Rejoinder to ‘Modern analysis of customer satisfaction surveys: comparison of models and integrated analysis’," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 27(5), pages 484-486, September.

    Cited by:

    1. Paolo Castelnovo & Martina Dal Molin, 2021. "The learning mechanisms through public procurement for innovation: The case of government‐funded basic research organizations," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 92(3), pages 411-446, September.
    2. Domenico Piccolo & Rosaria Simone, 2019. "The class of cub models: statistical foundations, inferential issues and empirical evidence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 389-435, September.
    3. Hamed Taherdoost & Mitra Madanchian, 2021. "Empirical Modeling of Customer Satisfaction for E-Services in Cross-Border E-Commerce," Post-Print hal-03741849, HAL.
    4. Ron S. Kenett & Giancarlo Manzi & Carmit Rapaport & Silvia Salini, 2022. "Integrated Analysis of Behavioural and Health COVID-19 Data Combining Bayesian Networks and Structural Equation Models," IJERPH, MDPI, vol. 19(8), pages 1-26, April.

  5. Silvia Salini & Ron Kenett, 2009. "Bayesian networks of customer satisfaction survey data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(11), pages 1177-1189.

    Cited by:

    1. Massimo Florio, 2021. "Knowledge creation: new frontiers for public investment," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 92(3), pages 379-386, September.
    2. F. Cugnata & G. Perucca & S. Salini, 2017. "Bayesian networks and the assessment of universities' value added," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(10), pages 1785-1806, July.
    3. P. Berchialla & S. Snidero & A. Stancu & C. Scarinzi & R. Corradetti & D. Gregori, 2012. "Understanding the epidemiology of foreign body injuries in children using a data-driven Bayesian network," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(4), pages 867-874, September.
    4. Claudia Tarantola & Paola Vicard & Ioannis Ntzoufras, 2012. "Monitoring and Improving Greek Banking Services Using Bayesian Networks: an Analysis of Mystery Shopping Data," Quaderni di Dipartimento 160, University of Pavia, Department of Economics and Quantitative Methods.
    5. Lidia Ceriani & Chiara Gigliarano, 2020. "Multidimensional Well-Being: A Bayesian Networks Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(1), pages 237-263, November.
    6. Flaminia Musella & Paola Vicard, 2015. "Object-oriented Bayesian networks for complex quality management problems," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(1), pages 115-133, January.
    7. Massimo Florio & Francesco Giffoni & Anna Giunta & Emanuela Sirtori, 2018. "Big science, learning, and innovation: evidence from CERN procurement," Industrial and Corporate Change, Oxford University Press, vol. 27(5), pages 915-936.
    8. Donata Marasini & Piero Quatto & Enrico Ripamonti, 2017. "Inferential confidence intervals for fuzzy analysis of teaching satisfaction," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(4), pages 1513-1529, July.
    9. Di Pietro, Laura & Guglielmetti Mugion, Roberta & Musella, Flaminia & Renzi, Maria Francesca & Vicard, Paola, 2017. "Monitoring an airport check-in process by using Bayesian networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 235-247.
    10. Federica Cugnata & Silvia Salini, 2014. "Model-based approach for importance–performance analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(6), pages 3053-3064, November.
    11. Zhang, Ya & Zhao, Hai & He, Xuan & Pei, Fan-Dong & Li, Guang-Guang, 2016. "Bayesian prediction of earthquake network based on space–time influence domain," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 138-149.
    12. Mandhani, Jyoti & Nayak, Jogendra Kumar & Parida, Manoranjan, 2020. "Interrelationships among service quality factors of Metro Rail Transit System: An integrated Bayesian networks and PLS-SEM approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 320-336.
    13. Pier Ferrari & Silvia Salini, 2011. "Complementary Use of Rasch Models and Nonlinear Principal Components Analysis in the Assessment of the Opinion of Europeans About Utilities," Journal of Classification, Springer;The Classification Society, vol. 28(1), pages 53-69, April.
    14. E. Cene & F. Karaman, 2015. "Analysing organic food buyers' perceptions with Bayesian networks: a case study in Turkey," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1572-1590, July.

  6. Ron Kenett, 2006. "On the planning and design of sample surveys," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(4), pages 405-415.

    Cited by:

    1. Silvia SALINI & Ron S. KENETT, 2007. "Bayesian networks of customer satisfaction survey data," Departmental Working Papers 2007-33, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.

  7. R. Kenett & P. Thyregod, 2006. "Aspects of statistical consulting not taught by academia," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 60(3), pages 396-411, August.

    Cited by:

    1. Adrian Bowman, 2007. "Interdisciplinary research: the importance of learning other people’s language," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 91(4), pages 361-365, December.
    2. Ian G. McHale & Philip A. Scarf & David E. Folker, 2012. "On the Development of a Soccer Player Performance Rating System for the English Premier League," Interfaces, INFORMS, vol. 42(4), pages 339-351, August.
    3. Estrada, Samantha & Floren, Michael & Harding, Justin & Wroblewski, Matthew, 2021. "What is your research question? A mixed methods evaluation of an academic statistical consulting center," Evaluation and Program Planning, Elsevier, vol. 89(C).
    4. Ron S. Kenett, 2009. "‘Post‐financial meltdown: What do the services industries need from us now?’ by Roger W. Hoerl and Ronald D. Snee: Discussion 2," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(5), pages 527-531, September.

  8. Agnihothri, Saligrama R. & Kenett, Ron S., 1995. "The impact of defects on a process with rework," European Journal of Operational Research, Elsevier, vol. 80(2), pages 308-327, January.

    Cited by:

    1. Jaber, Mohamad Y. & Guiffrida, Alfred L., 2004. "Learning curves for processes generating defects requiring reworks," European Journal of Operational Research, Elsevier, vol. 159(3), pages 663-672, December.
    2. Jaber, Mohamad Y. & Guiffrida, Alfred L., 2008. "Learning curves for imperfect production processes with reworks and process restoration interruptions," European Journal of Operational Research, Elsevier, vol. 189(1), pages 93-104, August.
    3. Ashoke Kumar Bera & Dipak Kumar Jana, 2017. "Multi-item imperfect production inventory model in Bi-fuzzy environments," OPSEARCH, Springer;Operational Research Society of India, vol. 54(2), pages 260-282, June.
    4. Sarker, Bhaba R. & Jamal, A.M.M. & Mondal, Sanjay, 2008. "Optimal batch sizing in a multi-stage production system with rework consideration," European Journal of Operational Research, Elsevier, vol. 184(3), pages 915-929, February.
    5. Bazan, Ehab & Jaber, Mohamad Y. & Zanoni, Simone & Zavanella, Lucio E., 2014. "Vendor Managed Inventory (VMI) with Consignment Stock (CS) agreement for a two-level supply chain with an imperfect production process with/without restoration interruptions," International Journal of Production Economics, Elsevier, vol. 157(C), pages 289-301.
    6. Jaber, M.Y. & Bonney, M. & Moualek, I., 2009. "An economic order quantity model for an imperfect production process with entropy cost," International Journal of Production Economics, Elsevier, vol. 118(1), pages 26-33, March.
    7. Modak, Nikunja Mohan & Panda, Shibaji & Sana, Shib Sankar, 2016. "Three-echelon supply chain coordination considering duopolistic retailers with perfect quality products," International Journal of Production Economics, Elsevier, vol. 182(C), pages 564-578.
    8. Y H Kang & S S Kim & H J Shin, 2010. "A dispatching algorithm for parallel machines with rework processes," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(1), pages 144-155, January.
    9. Yuan-Shyi Peter Chiu & Chih-An Katherine Lin & Huei-Hsin Chang & Victoria Chiu, 2010. "Mathematical modelling for determining economic batch size and optimal number of deliveries for EPQ model with quality assurance," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 16(4), pages 373-388, July.

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