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Jan van Dalen is an associate professor at the Department of Technology and Operations Management, Rotterdam School of Management University, Erasmus University Rotterdam.

Publications

Academic (1)
  • Kahlen, M., Ketter, W., & van Dalen, J. (2014). Agent-coordinated Virtual Power Plants of Electric Vehicles (Extended Abstract). 1547-1548.

Academic (31)
  • Vanheusden, W., van Dalen, J., & Mingardo, G. (2022). Governance and business policy impact on carsharing diffusion in European cities. Transportation Research Part D: Transport and Environment, 108, [103312]. https://doi.org/10.1016/j.trd.2022.103312

  • Paundra, J., Dalen, J., Rook, L., & Ketter, W. (2020). Ridesharing platform entry effects on ownership-based consumption in Indonesia. Journal of Cleaner Production, 265, [121535]. https://doi.org/10.1016/j.jclepro.2020.121535

  • Pennings, C., Dalen, J., & Rook, L. (2018). Coordinating judgmental forecasting: coping with intentional biases. Omega, 87, 46-56. https://doi.org/10.1016/j.omega.2018.08.007

  • Kahlen, M., Ketter, W., & Dalen, J. (2018). Electric vehicle virtual power plant dilemma: grid balancing versus customer mobility. Production and Operations Management, 27(11), 2054-2070. https://doi.org/10.1111/poms.12876

  • Li, T., Dalen, J., & Rees, PJ. (2018). More than just noise? Examining the Information Content of Stock Microblogs on Financial Markets. Journal of Information Technology, 33(1), 50-69. https://doi.org/10.1057/s41265-016-0034-2

  • Paundra, J., van Dalen, J., Rook, L., & Ketter, W. (2017). Preferences for car sharing services: Effects of instrumental attributes and psychological ownership. Journal of Environmental Psychology, 53, 121-130. https://doi.org/10.1016/j.jenvp.2017.07.003

  • Pennings, C., & van Dalen, J. (2017). Integrated Hierarchical Forecasting. European Journal of Operational Research, 263(2), 412-418. https://doi.org/10.1016/j.ejor.2017.04.047

  • Pennings, C., van Dalen, J., & Laan, E. (2017). Exploiting Elapsed Time for Managing Intermittent Demand for Spare Parts. European Journal of Operational Research, 258(3), 958-969. https://doi.org/10.1016/j.ejor.2016.09.017

  • Laan, E., van Dalen, J., Rohrmoser, M., & Simpson, R. (2016). Demand forecasting and order planning for humanitarian logistics: An empirical assessment. Journal of Operations Management, 45(july), 114-122. https://doi.org/10.1016/j.jom.2016.05.004

  • Hogenboom, A., Ketter, W., van Dalen, J., Kaymak, U., Collins, J., & Gupta, A. (2015). Adaptive Tactical Pricing in Multi-Agent Supply Chain Markets Using Economic Regimes. Decision Sciences, 46(4), 791-818. https://doi.org/10.1111/deci.12146

  • Liu, L., Daniels, H., Oosterhout, M., & van Dalen, J. (2013). Business Intelligence for Improving Supply Chain Risk Management. International Journal in Advanced Logistics, 2(2), 18-29. https://doi.org/10.1080/2287108X.2013.11006084

  • Ma, Y., van Dalen, J., de Blois, C., & Kroon, LG. (2011). Estimation of Dynamic Traffic Densities for Official Statistics. Transportation Research Record, (2256), 104-111. https://doi.org/10.3141/2256-13

  • Baaij, M., de Jong, A., & van Dalen, J. (2011). The dynamics of superior performance among the largest firms in the global oil industry, 1954-2008. Industrial and Corporate Change, 20(3), 789-824. https://doi.org/10.1093/icc/dtq065

  • Ma, Y., van Zuylen, HJ., Chen, Y., & van Dalen, J. (2011). Allocating Departure Time Slots to Optimize Dynamic Network Capacity. Transportation Research Record, 2(2197), 98-106. https://doi.org/10.3141/2197-12

  • Veenstra, A., & van Dalen, J. (2011). Ship Speed and Fuel Consumption Quotation in Ocean Shipping Time Charter Contracts. Journal of Transport Economics and Policy, 45(1), 41-61.

  • Blindenbach-Driessen, FP., van Dalen, J., & van den Ende, J. (2010). Subjective Performance Assessment of Innovation Projects. Journal of Product Innovation Management, 27(4), 572-592. https://doi.org/10.1111/j.1540-5885.2010.00736.x

  • Chen, CM., & van Dalen, J. (2010). Measuring dynamic efficiency: theories and an integrated methodology. European Journal of Operational Research, 203(3), 749-760. https://doi.org/10.1016/j.ejor.2009.09.001

  • Madsen, E., van Dalen, J., van Gorp, J., Borel Rinkes, I., & van Dalen, T. (2008). Strategies for optimizing pathologic staging of sentinel lymph nodes in breast cancer patients. Virchows Archiv. An International Journal of Pathology, 453(1), 17-24. https://doi.org/10.1007/s00428-008-0601-1

  • Baaij, M., Greeven, MJ., & van Dalen, J. (2004). Persistent Superior Economic Performance, Sustainable Competitive Advantage, and Schumpeterian Innovation: Leading Established Computer Firms, 1954-2000. European Management Journal, 22(5), 517-531. https://doi.org/10.1016/j.emj.2004.09.010

  • van Dalen, J., & Bode, B. (2004). Quality-Corrected Price Indices: the Case of the Dutch New Passenger Car Market, 1990-1999. Applied Economics, 36(11), 1169-1197. https://doi.org/10.1080/0003684042000247361

  • van Dalen, J., & Bode, B. (2001). Kwaliteit- gecorrigeerde prijsontwikkelingen van nieuwe auto's in Nederland, 1990-1999. Kwantitatieve Methoden, 68, 5-40.

  • van Frederikslust, RAI., Leermakers, WTJ., Soedito, SN., & van Dalen, J. (2000). Een empirische verklaring voor het herstructureren van Nederlandse ondernemingen. MAB, 74(4), 129-144.

  • Kaptein, M., & van Dalen, J. (2000). The empirical assessment of corporate ethics: a case study. Journal of Business Ethics, 24(2), 95-114. https://doi.org/10.1023/A:1006360210646

  • van Dalen, J., & Bode, B. (1999). Kwalitatieve aspecten van kwantitatieve maatstaven: prijsindices in de schijnwerpers. Kwantitatieve Methoden, 61, 69-100.

  • van Dalen, J., & Thurik, R. (1998). A model of pricing behavior: an econometric case study. Journal of Economic Behavior and Organization, 36(2), 177-195.

  • van Dalen, J., & Thurik, R. (1995). Wholesale pricing in a small open economy. De Economist, 142(1), 55-76. https://doi.org/10.1007/BF01388355

  • van Dalen, J. (1993). Primeur: empirisch onderzoek in de groothandel. Economenblad, 15(5), 4-4.

  • van Dalen, J., & Thurik, R. (1991). Labour productivity and Profitability in the Dutch Flower Trade. Small Business Economics, 3(2), 131-144. https://doi.org/10.1007/BF00388447

  • van Dalen, J. (1990). De betekenis van de groothandel voor Nederland. MAB, 63(3), 65-71.

  • van Dalen, J., Koerts, J., & Thurik, R. (1990). Measurement of Labour Productivity in Wholesaling. International Journal of Research in Marketing, 7(1), 21-34.

  • van Dalen, J., Koerts, J., & Thurik, R. (1989). Disequilibrium in Dutch Retailing: the impact of demand factors. Kwantitatieve Methoden, 30, 5-20.

Professional (7)
  • Ketter, W., & van Dalen, J. (2020). Balancing Power Grids with Electric Vehicles. RSM Insight, 37(1), 22-24.

  • Laan, E., & van Dalen, J. (2017). Improving the supply chain in humanitarian logistics. RSM Discovery - Management Knowledge, 30(2), 8-10. http://hdl.handle.net/1765/100179

  • Fok, D., & van Dalen, J. (2015). Boosting business with data analysis. RSM Discovery - Management Knowledge, 21(1), 5-7. http://hdl.handle.net/1765/77991

  • Burgers, S., Baalen, P., & van Dalen, J. (2008). Is Open Source Beter dan Gesloten? TIEM: tijdschrift voor informatie en management, 27(September/Oktober), 28-30.

  • Bode, B., & van Dalen, J. (1999). De kwaliteit van de prijsindex van het beroepsgoederenvervoer over de weg (The quality of the price index for road haulage). Maandstatistiek van de Prijzen, 24, 4-9.

  • van Dalen, J., & Thurik, R. (1992). Plaats en rol van de Nederlandse groothandel. Economisch-Statistische Berichten, 77(3843), 76-80.

  • Thurik, R., & van Dalen, J. (1992). Plaats en rol van de Nederlandse groothandel. Bloembollenexport, 30(3), 3-7.

Academic (4)
  • van Dalen, J. (2010). Werkboek Statistische Onderzoek met Spss for Windows. Lemma.

  • van Dalen, J., & de Leede, E. (2009). Statistisch Onderzoek met Spss for Windows - tweede druk. Lemma.

  • van Dalen, J., & de Leede, E. (2000). Statistisch Onderzoek met SPSS for Windows. Lemma.

  • de Leede, E., & van Dalen, J. (1994). In & Uit: Handleiding SPSS/PC+. Uitgeverij Eburon.

Professional (1)
  • de Leede, E., & van Dalen, J. (1996). In & Uit, Statistisch Onderzoek met SPSS for Windows. Uitgeverij Eburon.

Academic (2)
  • Bode, B., van Dalen, J., & Klomp, L. (1996). 'Wat wil je nu eigenlijk zeggen?!'. Ridderprint B.V.

  • van Dalen, J., Bode, B., & Klomp, L. (1996). Wat Wil Je Nu Eigenlijk Zeggen?! Liber amicorum. Ridderprint.

Academic (9)
  • Edelenbos, J., Hirzalla, F., van Zoonen, L., van Dalen, J., Bouma, G., Slob, A., & Woestenburg, A. (2017). Governing the Complexity of Smart Data Cities: Setting a Research Agenda. In M. P. Rodriguez Bolivar (Ed.), Smart Technologies for Smart Governments. Transparency, Efficiency and Organizational Issues (pp. 35-54). Springer-Verlag.

  • Baalen, P., van Dalen, J., Smit, R., & Veenhof, W. (2011). Utilitarian and Hedonic Motivations in the Acceptance of Web Casts in Higher Education. In C. Wankel, & J. S. Law (Eds.), Streaming Media in Higher Education

  • Veenstra, A., & van Dalen, J. (2011). Fixtures-based Freight Rate Indices, and their Impact on Freight Rate Modelling in the Shipping Industry. In K. Cullinane (ed.) (Ed.), The International Handbook of Maritime Economics and Business (pp. 63-84)

  • van Dalen, J., van Nunen, JAEE., & Wilens, CM. (2005). The chip in crate: The Heineken Case. In S. D. P. Flapper, J. A. E. E. van Nunen, & L. N. van Wassenhove (Eds.), Managing Closed-Loop Supply Chains (pp. 43-55). Springer-Verlag.

  • van Dalen, J. (1997). Oordeelsvorming en prijsindexcijfers: ethiek rijmt op statistiek. In F. van Engeldorp Gastelaars (Ed.), Liberik de Leede - Sparring Partners (pp. 64-86). Ridderprint.

  • van Dalen, J. (1996). Kanttekeningen bij het meten van de prijs van groothandelsdiensten. In B. Bode, J. van Dalen, & L. Klomp (Eds.), 'Wat wil je nu eigenlijk zeggen?!' Opstellen over economie, statistiek en methodologie (pp. 165-179). Ridderprint B.V..

  • Bode, B., van Dalen, J., & Klomp, L. (1996). Inleiding. In B. Bode, J. van Dalen, & L. Klomp (Eds.), 'Wat wil je nu eigenlijk zeggen?!' (pp. 3-9). Ridderprint B.V..

  • van Dalen, J., Bode, B., & Klomp, L. (1996). Inleiding. In L. Klomp, J. van Dalen, & B. Bode (Eds.), Wat Wil Je Nu Eigenlijk Zeggen ?! (pp. 1-9). Ridderprint.

  • van Dalen, J., & Eijkhout, MP. (1990). Een Margemodel voor de Groothandel. In CBS Select 6: statistische opstellen (pp. 75-90). Centraal Bureau voor de Statistiek.

Professional (4)
  • van Dalen, J., & Bode, B. (2005). Estimation Biases in Quality-Adjusted Hedonic Price Indices. In Erwin Diewert, & Alice Nakamura (Eds.), Diewert papers Trafford Press.

  • Hillebrand, ME., van Dalen, J., ten Veen, JH., & Besselink, BMBT. (2000). Risk Factors for Lipodystrophy. In Proceedings of the Fourth World Aids Congres

  • Hillebrand, ME., ten Veen, JH., van Dalen, J., & Besselink, BMBT. (1999). The Smart Study I: Efficacy First Triple. In Proceedings of the Third World Aids Congres

  • van Dalen, J. (1997). Oordeelsvorming en prijsindexcijfers: ethiek rijmt op statistiek. In P. van Engeldorp Gastelaars (Ed.), Liberik de Leede : Sparringpartners : Liber Amicorum voor Erik de Leede (pp. 64-87). ServicePost B.V.. NUGI Vol. 681

Academic (6)
  • Lu, Y., van Iterson, P., Gupta, A., Ketter, W., van Dalen, J., & van Heck, E. (2013). Buy It Now or Later: The Impact of Mari on Multi-unit Sequential Dutch Auctions. Winter Conference on Business Intelligence, Snowbird, USA.

  • Lu, Y., Ketter, W., van Dalen, J., Gupta, A., & van Heck, E. (2012). A Stochastic Model of Winning Bids in the Dutch Flower Auctions. The 8th Symposium on Statistical Challenges in Electronic Commerce Research (SCECR 2012), Montreal, Canada.

  • Lu, Y., Ketter, W., van Dalen, J., Gupta, A., & van Heck, E. (2012). An Empirical Model of Multi-unit Sequential Dutch Auctions. Winter Conference on Business Intelligence, Snowbird, USA.

  • van Dalen, J., & Bode, B. (2004). Estimation Biases in Quality-Adjusted Hedonic Price Indices. SSHRC, International Conference on Index Number Theory and Measurement of Prices and Productivity, Vancouver, Canada.

  • van Dalen, J., & Bode, B. (2002). Quality-Corrected Price Indexes of New Passenger Cars in the Netherlands, 1990-1999. ZEW-conference on Price Indices and the Measurement of Quality Change, Mannheim.

  • van Dalen, J., & Bode, B. (2001). Quality-Corrected Price Indexes of New Passenger Cars in the Netherlands, 1990-1999. Sixth Meeting of the International Working Group on Price Indices, Canberra (Australia).

Professional (1)
  • van Frederikslust, RAI., Leermakers, WTJ., Soedito, SN., & van Dalen, J. (2003). European Financial Management Association.

Academic (21)
  • Ketter, W., van Dalen, J., Rook, L., & Paundra, J. (2018). Multiple ridesharing platforms entrance and their influence to new vehicle sales. In 14th Symposium on Statistical Challenges in Electronic Commerce Research (SCECR 2018)

  • Kahlen, M., Ketter, W., & van Dalen, J. (2014). Balancing with Electric Vehicles: A Profitable Business Model. In Proceedings of the 22nd European Conference on Information Systems (pp. 1-15). http://hdl.handle.net/1765/76119

  • Baalen, P., van Dalen, J., & Malsen, J. (2013). Relational Model Conflicts in Knowledge Sharing Behavior. In - http://hdl.handle.net/1765/40100

  • Ketter, W., Haghpanah, Y., van Dalen, J., & Des Jardin, M. (2012). SmartRate: A Rating Interpretation Mechanism for Agents in Smart Grid Markets. In AAMAS Joint Workshop on Trading Agent Design and Analysis (TADA) and Agent- Mediated Electronic Commerce (AMEC)

  • Lu, Y., van Iterson, P., Gupta, A., Ketter, W., van Dalen, J., & van Heck, E. (2012). Buy it now or later: the Impact of Mari on Multi-unit Sequential Dutch Auctions. In Workshop on Information Technology and Systems (WITS-12)

  • Kahlen, M., Valogianni, K., Ketter, W., & van Dalen, J. (2012). A Profitable Business Model for Electric Vehicle Fleet Owners. In International Conference on Smart Grid Technology, Economics and Policies (SG-TEP 2012) (pp. 1-5). IEEE Xplore. https://doi.org/10.1109/SG-TEP.2012.6642395

  • Verhagen, E., Rook, L., van Dalen, J., & Ketter, W. (2012). Tariff selection. In Conference on Smart Grid – Technologies, Economics, and Policies (SG-TEP)

  • Lucchese, G., Ketter, W., van Dalen, J., & Collins, J. (2011). Forecasting prices in dynamic heterogeneous product markets using multivariate prediction methods. In 13th International Conference on Electronic Commerce (ICEC-11)

  • Hogenboom, A., Hogenboom, F., Kaymak, U., Ketter, W., van Dalen, J., & Collins, J. (2010). Towards a Dynamic Model of Supply Chain Regimes for Complex Multi-Agent Markets. In 2010 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2010) (pp. 3219-3225). IEEE. https://doi.org/10.1109/ICSMC.2010.5642406

  • Ma, Y., van Zuylen, H., Chen, Y., & van Dalen, J. (2010). Allocation Departure Time Slots to Optimize Dynamic Network Capacity. In the 89th Transporation Resarch Board

  • Ma, Y., van Dalen, J., de Blois, C., & van Nunen, J. (2010). Estimation of Dynamice Traffic Density for Official Statisitcs based on Conbined Use of GPS and Loop Detector Data. In proceeding of the 12th World Conference on Trasnportation Resarch

  • van Dalen, J., Ketter, W., Lucchese, G., & Collins, J. (2010). A Kalman Filter Approach to Analyze Multivariate Hedonic Pricing in Dynamic Supply-Chain Markets. In 12th International Conference on Electronic Commerce (ICEC-10) (pp. 57-66).

  • Ma, Y., van Dalen, J., de Blois, C., & van Nunen, J. (2010). Estimating Dynamic Transport Population for Official Statistics based on GPS/GSM. In proceeding of the Seventh International Conference on Traffic and Transport Study

  • Gupta, A., Ketter, W., van Dalen, J., van Heck, E., & Wasesa, M. (2010). Neural Network Based Recommendation Agent for Determining the Starting Price in Multi-Unit Sequential Dutch Auctions. In 20th Workshop on Information Systems and Technology (WITS-10)

  • Hogenboom, A., Ketter, W., van Dalen, J., Kaymak, U., Collins, J., & Gupta, A. (2009). Adaptive Pricing in Multi-Agent Supply Chain Markets using Economic Regimes. In Conference on Information Systems and Technology (CIST 2009)

  • Hogenboom, A., Ketter, W., van Dalen, J., Kaymak, U., Collins, J., & Gupta, A. (2009). Product Pricing using Adaptive Real-Time Probability of Acceptance Estimations based on Economic Regimes. In Proceedings of the Eleventh International Conference on Electronic Commerce (ICEC 2009) (pp. 176-185). ACM. https://doi.org/10.1145/1593254.1593281

  • Hogenboom, F., Ketter, W., van Dalen, J., Kaymak, U., Collins, J., & Gupta, A. (2009). Identifying and Predicting Economic Regimes in Supply Chains Using Sales and Procurement Information. In Proceedings of the Eleventh International Conference on Electronic Commerce (ICEC 2009) (pp. 19-28). https://doi.org/10.1145/1593254.1593258

  • Hogenboom, A., Ketter, W., van Dalen, J., Kaymak, U., Collins, J., & Gupta, A. (2009). Product Pricing in TAC SCM using Adaptive Real-Time Probability of Acceptance Estimations based on Economic Regimes. In Proceedings of the IJCAI'09 Workshop on Trading Agent Design and Analysis (TADA 2009) (pp. 15-24).

  • Hogenboom, F., Ketter, W., van Dalen, J., Kaymak, U., Collins, J., & Gupta, A. (2009). Economic Regime Identification and Prediction in TAC SCM Using Sales and Procurement Information. In E. H. Gerding (Ed.), Proceedings of the IJCAI'09 Workshop on Trading Agent Design and Analysis (TADA 2009) (pp. 25-34).

  • Ma, Y., van Zuylen, H., Chen, Y., & van Dalen, J. (2009). Modeling and Analyzing Departure Time Slots Allocation to Optimize Dynamic Network Capacity-- the Case of A15-Motorway to Rotterdam Port. In Proceedings of the Fifth Advanced Forum on Transportation of China (pp. 214-222). the Instituion of Engineering and Technology.

  • Veenstra, A., & van Dalen, J. (2007). Speed and fuel consumption quotations in ocean shipping time charter contracts. In J. witlox, & C. ruijgrok (Eds.), Vervoerslogistieke werkdagen 2007 (pp. 120-142). Nautilus academic books.

Internal (1)
  • van Dalen, J. (1992). Quantitative Studies in Wholesaling. [Doctoral Thesis, Erasmus University Rotterdam]. Erasmus Universiteit Rotterdam (EUR).

Academic (9)
  • Bode, B., & van Dalen, J. (2002). The Cost of Private Transportation in the Netherlands, 1992-1999. (ECB Working Paper Series 134 ed.) ECB. ECB Working Paper Series Vol. 134

  • Kaptein, M., & van Dalen, J. (1999). The empirical assessment of corporate ethics. (ERASM Management Report Series 18-1999 ed.) [publisher unknown]. ERASM Management Report Series Vol. 18-1999

  • Bode, B., & van Dalen, J. (1999). Audit Prijsindexcijfer van het Beroepsgoederenvervoer over de weg. Centraal Bureau voor de Statistiek (CBS).

  • van Dalen, J., & Bode, B. (1998). Kwalitatieve aspecten van kwantitatieve maatstaven: prijsindices in de schijnwerpers. (ERASM management report series 61 ed.) [publisher unknown]. ERASM management report series Vol. 61

  • van Dalen, J. (1998). Kwalitatieve aspecten van kwantitatieve maatstaven: prijsindices in de schijnwerpers. (Management Report Serie 61-1998 ed.) [publisher unknown]. Management Report Serie Vol. 61-1998

  • van Dalen, J., & Thurik, R. (1996). A model of the price behaviour of Dutch flower exporters. (Tinbergen Institute 96-069 ed.) Tinbergen Institute. Tinbergen Institute Vol. 96-069

  • van Dalen, J., & Thurik, R. (1995). A Model of the Price behaviour of Dutch Flower Exporters. (Management Report 218 ed.) Erasmus. Management Report Vol. 218

  • van Dalen, J., & Thurik, R. (1993). Pricing Differences Between Wholesale Business Types in a Small Open Economy. (Management Report Series 162 ed.) Erasmus University Rotterdam (EUR).

  • van Dalen, J., Koerts, J., de Jong, G., & Thurik, R. (1988). Groothandel: zijn rol in de geschiedenis, de huidige economie en de moderne theorie. (EIM Research Publicatie nr. 22 ed.) EIM. EIM Research Publicatie Vol. nr. 22

Professional (1)
  • Zuidwijk, R., Veenstra, A., van Dalen, J., & Oosterhout, M. (2009). INTEGRITY benefits analysis and measurement plan, Deliverable 6.1. INTEGRITY consortium.

Courses

Advanced Statistics & Programming

  • Study year: 2022/2023, 2021/2022, 2020/2021
  • Code: BM01BAM
  • Level: Master

Business Analytics

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  • Code: BM21MIM
  • ECTS: 6 Level: Master

Business Analytics PT

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  • Code: BM21MIM-P
  • ECTS: 6 Level: Master

Supply chain forecasting

  • Study year: 2022/2023, 2021/2022, 2020/2021, 2019/2020, 2018/2019, 2017/2018, 2016/2017, 2015/2016
  • Code: BMME075
  • Level: Master, Master, Master, Master

BIM Master Thesis

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  • Code: BMMTBIM
  • Level: Master

BAM Master Thesis & Internship

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  • Code: BMMTIBAM
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MiM Master Thesis

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  • ECTS: 16 Level: Master

OLD STYLE - Research Methods and Skills

  • Study year: 2022/2023, 2021/2022, 2020/2021
  • Code: BMRM3SCM
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Statistics

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  • Code: BPE1101

Research Training I

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  • Code: BPE1103

Research Training II

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  • Code: BPE1104

Statistics

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  • Code: BPM1101

Research Training I

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  • Code: BPM1102

Research Training II

  • Study year: 2022/2023, 2021/2022
  • Code: BPM1103

Statistiek

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  • Code: BPN1101

iOnderzoekstraining 1

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  • Code: BPN1103

Onderzoekstraining II

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  • Code: BPN1104

Past courses

Applied Business Methods

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Applied Business Methods - Case

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Applied Business Methods - Exam

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BAM Master Thesis & Internship

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  • Code: BMMTBAM
  • ECTS: 16 Level: Master

Statistical methods & techniques examination

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  • Code: BKB0019T
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Business Information Management

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  • Code: BT1213
  • Level: Bachelor 1, Bachelor 3, Pre-master

Onderzoeksproject

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  • Code: BK2103
  • Level: Bachelor 2, Pre-master

Onderzoekstraining

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  • Code: BP1103
  • ECTS: 5

Research Project

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  • Code: BT2103
  • Level: Bachelor 2, Bachelor 3, Pre-master

Statistical methods & techniques case

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  • Code: BKB0019C
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Statistiek

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  • Code: BP1101
  • ECTS: 4

Big Data and Business Analytics

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  • ECTS: 6 Level: Master, Master, Master

BIM Research Methods I - Old style

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  • ECTS: 2

Business Information Management

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  • Code: BT1113
  • Level: Bachelor 1, Bachelor 3, Pre-master

SCM Honours Programme

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  • Code: BMHONSCM
  • ECTS: 8 Level: Master

Research methods

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  • Code: BM07MIM
  • ECTS: 2 Level: Master

Advances in SCM

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Advances in SCM

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Research clinic

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Big Data and Business Analytics

  • Study year: 2014/2015, 2013/2014
  • Code: RSMME011
  • ECTS: 6 Level: Master

Forecasting in supply chains

  • Study year: 2014/2015, 2013/2014
  • Code: RSMME070
  • ECTS: 6 Level: Master

Research methods

  • Study year: 2014/2015
  • Code: BKM24GM
  • ECTS: 2 Level: Master

BIM research topics block 1

  • Study year: 2013/2014
  • Code: RSM03BIM
  • ECTS: 1 Level: Master

BIM research topics block 2

  • Study year: 2013/2014
  • Code: RSM06BIM
  • ECTS: 1 Level: Master

Research methods

  • Study year: 2013/2014
  • Code: BKM07GM
  • ECTS: 1 Level: Master

Statistische methoden en technieken

  • Study year: 2013/2014
  • Code: BKB0019
  • ECTS: 6 Level: Bachelor 2

Featured in the media

  • New algorithm uses twitter to predict the stock market researchers develop a way for traders to use twitter to make better investment decisions

    New research by Ting Li and Jan van Dalen of RSM has found that information taken from Twitter posts could be used to predict the stock market – and help traders to make better investment decisions. “This study shows the potential…

  • Can Twitter tell you how to invest?

    Ting Li, Professor of Digital Business and Jan van Dalen, Associate Professor of Statistics at RSM recently analysed over a million Twitter messages that mentioned stocks listed on the S&P 100 share index. They then developed an…

  • Can Twitter predict the stock market? These researchers think so

    Analysis of more than one million Twitter posts by Ting Li and Jan van Dalen of RSM found that they could predict stock market movements and help traders make decisions on investments. “This study shows the potential value of…

  • Can Twitter predict the stock market? These researchers think so

    Analysis of more than one million Twitter posts by Ting Li and Jan van Dalen of RSM found that they could predict stock market movements and help traders make better decisions on investments. "This study shows the potential value…

  • Can traders rely on Twitter for investment decisions?

    Ting Li and Jan van Dalen of RSM have found a way for traders to use Twitter to make better investment decisions. Over a million twitter messages that mentioned stocks listed on the S&P 100 share index were analysed. Li comments…

  • Researchers develop algo that uses Twitter to predict the stock market

    Ting Li and Jan van Dalen of RSM have developed an algorithm that scans tweets about stocks, successfully predicting price fluctuations. "This could be used by institutional investors or home-based day traders, and proves that…

  • 荷兰推出最新研究成果,利用推特预测股价变动

    Ting Li and Jan van Dalen of RSM analysed more than a million tweets that involved stocks listed on the S&P 100 index and developed an algorithm to scan stock tweets and predict price changes.

  • New Algorithm Uses Twitter to Predict the Stock Market

    Ting Li and Jan van Dalen of RSM have analysed over a million Twitter messages that mentioned stocks listed on the S&P 100 share index. The researchers then developed an algorithm that looked at the sentiment of the tweets and…

  • Aandeelhouder Maakt Shell Groen

    An interview with Jan van Dalen of RSM about his new study, which discusses how investors can make better financial decisions by using big data to analyse information about stocks on Twitter. Fast-forward to 36:57 to listen. …

  • Aandeelhouder Maakt Shell Groen

    This edition of BNR's "Zakendoen" references Jan van Dalen and his new study (with Ting Li) on how social media can help investors make better decisions.

  • Erasmus Universiteit voorspelt aandelenkoersen met big data-analyse van tweets

    Research by Prof Ting Li, Dr Jan van Dalen and alumnus Pieter Jan van Rees of RSM shows that a big data analysis of tweets can be used to predict developments in the stock market in the short and long term. This discovery can help…

  • Aandelenkoersen zijn te voorspellen met big data-analyse van tweets

    Noteworthy financial events end up on Twitter, but conversely, financial tweets can also have an influence on developments in finance. Research by Ting Li and Jan van Dalen of RSM shows that big data analyses of tweets can be used…

  • 'Twitterberichten goede voorspeller beurskoers'

    It is possible to make better investment decisions based on big data analyses of Twitter messages, say researchers Ting Li and Jan van Dalen of RSM in their new study.

  • Verdienen op de beurs? 'Kijk naar berichten op Twitter'

    If you want to earn money by investing, it also makes sense to pay attention to what appears on social media. Ting Li and Dr Jan van Dalen of RSM shows that a big data analysis of tweets can be used to predict developments in the…

  • Twitterdata nuttig bij voorspellen aandelenkoersen

    Noteworthy financial events end up on Twitter, but conversely, financial tweets can also have an influence on developments in finance. Research by Ting Li and Jan van Dalen of RSM shows that big data analyses of tweets can be used…

  • Predict stock prices with big data analysis of tweets

    Do tweets about the stock market contain valuable information for investors, or can they be ignored as noise produced by self-proclaimed financial gurus? A study by Ting Li and Jan van Dalen of RSM shows that a big data analysis…

  • Aandelenkoersen voorspellen met big data-analyse van tweets

    A new study by Ting Li and Jan van Dalen of RSM shows that a big data analysis of tweets can be used to predict developments in the stock market in the short and long term. This discovery can help investors make better decisions. …

  • Must read: 13% koerswinst China in 2018

    A study by Professor Ting Li and Dr Jan van Dalen of RSM shows that a big data analysis of tweets can be used to predict developments in the stock market in the short and long term. This discovery can help investors make better…

  • RSM: Aandelenkoersen voorspellen met big data-analyse van tweets

    Do tweets about the stock market contain valuable information for investors, or can they be ignored as noise produced by self-proclaimed financial gurus? A study by Professor Ting Li and Dr Jan van Dalen of RSM shows that a big…

Featured on RSM Discovery

RSM Discovery magazine 37 – out now!

Issue 37: devoted to understand the benefits of data analytics in an age where big data have become woven into the very fabric of our lives.

How to promote car-sharing to people who love their own cars

Car-sharing schemes can reduce the environmental impact of driving. But how do you entice car owners that are really attached to their cars?

Predicting the stock market with big-data analysis of tweets

"The big challenge was to determine what all the emoji, slang expressions and negations in tweets actually say about stock sentiment."

Improving the supply chain in humanitarian logistics

How RSM researchers help Doctors Without Borders to organise their humanitarian aid logistics.

Boosting business with data analysis

Pretty much every modern organisation collects a mountain of data on a daily basis as it goes about its business.