Integrating Informal Learning into Deployment Planning and Project Scheduling
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Keywords

Informal Learning Behaviors
Hybrid Approach
Multi-Criteria Optimization
Deployment Planning
IT-Service Industries

How to Cite

Jahr, M., & Mynarek, F. (2022). Integrating Informal Learning into Deployment Planning and Project Scheduling. Journal of Business Strategies, 39(1), 33–59. https://doi.org/10.54155/jbs.39.1.33-59

Abstract

Dynamic organizations constantly search for new ways to improve the quality of their processes. A core element of these efforts is the integration of informal learning into daily workflows. Interdisciplinary research is required to accomplish this challenging task and make informal learning manageable. In this study, we propose a novel combination of organizational theory and operational research using a quantitative project scheduling approach to create efficient workflows, including systematized informal learning. The concept of integrating the informal learning activities of knowledge sharing, reflection, and self-organization is presented based on a multi-objective, multi-resource constrained project scheduling problem with limited renewable resources, activity splitting, and preemption. Additional simulation studies demonstrate the calculation of informal learning ratios, together with further discussion of strategic management options.

https://doi.org/10.54155/jbs.39.1.33-59
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References

Abedinnia, H., Glock, C. H., & Schneider, M. D. (2017). Machine scheduling in production: A content analysis. Applied Mathematical Modelling, 50, 279–299. https://doi.org/10.1016/j.apm.2017.05.016

Alt, D., & Raichel, N. (2020). Enhancing perceived digital literacy skills and creative self-concept through gamified learning environments: Insights from a longitudinal study. International Journal of Educational Research, 101, 101561. https://doi.org/https://doi.org/10.1016/j.ijer.2020.101561

Anderson, P. (1999). Perspective: Complexity theory and organization science. Organization science, 10 (3), 216–232. https://doi.org/10.1287/orsc.10.3.216

Ballestin, F., Valls, V., & Quintanilla, S. (2008). Pre-emption in resourceconstrained project scheduling. European Journal of Operational Research, 189 (3), 1136–1152. https://doi.org/https://doi.org/10.1016/j.ejor.2006.07.052

Ballestin, F., Valls, V., & Quintanilla, S. (2009). Scheduling projects with limited number of preemptions. Computers & Operations Research, 36 (11), 2913–2925. https://doi.org/https://doi.org/10.1016/j.cor.2009.01.006

Bednall, T. C., Sanders, K., & Runhaar, P. (2014). Stimulating informal learning activities through perceptions of performance appraisal quality and human resource management system strength: A two-wave study. Academy of Management Learning & Education, 13 (1), 45–61. https://doi.org//amle.2012.0162

Benkenstein, M., Bruhn, M., Büttgen, M., Hipp, C., Matzner, M., & Nerdinger, F. W. (2017). Topics for service management research–a european perspective. Journal of Service Management Research, 1 (1), 4–21.

Bigelow, L. S., & Barney, J. B. (2021). What can strategy learn from the business model approach? Journal of Management Studies, 58 (2), 528–539. https://doi.org/10.1111/joms.12579

Blit, J. (2017). Learning remotely: R&D satellites, intra-firm linkages, and knowledge sourcing. Journal of Economics & Management Strategy, 26 (4), 757–781. https://doi.org/10.1111/jems.12213

Blume, B. D., Ford, J. K., Baldwin, T. T., & Huang, J. L. (2010). Transfer of training: A meta-analytic review. Journal of management, 36 (4), 1065–1105. https://doi.org/10.1177/0149206309352880

Brucker, P., Drexl, A., M¨ohring, R., Neumann, K., & Pesch, E. (1999). Resource-constrained project scheduling: Notation, classification, models, and methods. European journal of operational research, 112 (1), 3–41. https://doi.org/10.1016/S0377-2217(98)00204-5

Buddhakulsomsiri, J., & Kim, D. S. (2006). Properties of multi-mode resourceconstrained

project scheduling problems with resource vacations and activity splitting. European Journal of Operational Research, 175 (1), 279–295. https://doi.org/10.1016/j.ejor.2005.04.030

Carbonell, P., Rodriguez-Escudero, A. I., & Pujari, D. (2009). Customer involvement in new service development: An examination of antecedents and outcomes. Journal of Product Innovation Management, 26 (5), 536–550. https://doi.org/10.1111/j.1540-5885.2009.00679.x

Cefis, E., Marsili, O., & Rigamonti, D. (2020). In and out of balance: Industry relatedness, learning capabilities and post-acquisition innovative performance. Journal of Management Studies, 57 (2), 210–245. https://doi.org/https://doi.org/10.1111/joms.12441

Cerasoli, C. P., Alliger, G. M., Donsbach, J. S., Mathieu, J. E., Tannenbaum, S. I., & Orvis, K. A. (2018). Antecedents and Outcomes of Informal Learning Behaviors: A Meta-Analysis. Journal of Business and Psychology, 33 (2), 203–230. https://doi.org/10.1007/s10869-017-9492-y

Chen, R., Liang, C., Gu, D., & Zhao, H. (2020). A competence-time-quality scheduling model of multi-skilled staff for IT project portfolio. Computers & Industrial Engineering, 139, 106183. https://doi.org/10.1016/j.cie.2019.106183

Claver-Cortes, E., Pertusa-Ortega, E. M., & Molina-Azor´ın, J. F. (2012). Characteristics of organizational structure relating to hybrid competitive strategy: Implications for performance. Journal of Business Research, 65 (7), 993–1002. https://doi.org/10.1016/j.jbusres.2011.04.012

Coelho, J., & Vanhoucke, M. (2011). Multi-mode resource-constrained project scheduling using RCPSP and SAT solvers. European Journal of Operational Research, 213 (1), 73–82. https://doi.org/10.1016/j.ejor.2011.03.019

De Reyck, B., & Herroelen, W. (1999). The multi-mode resource-constrained project scheduling problem with generalized precedence relations. European Journal of Operational Research, 119 (2), 538–556. https://doi.org/https://doi.org/10.1016/S0377-2217(99)00151-4

Edmondson, A. C., & Mcmanus, S. E. (2007). Methodological fit in management field research. Academy of Management Review, 32 (4), 1246–1264. https://doi.org/10.5465/amr.2007.26586086

Elmaghraby, S. E. (1977). Activity networks: Project planning and control by network models. John Wiley & Sons.

Fang, C., Lee, J., & Schilling, M. A. (2010). Balancing exploration and exploitation through structural design: The isolation of subgroups and

organizational learning. Organization Science, 21 (3), 625–642. https://doi.org/10.1287/orsc.1090.0468

Freigang, S., Schlenker, L., & K¨ohler, T. (2018). A conceptual framework for designing smart learning environments. Smart Learning Environments, 5 (1), 27. https://doi.org/10.1186/s40561-018-0076-8

Garc´ıa-Pe˜nalvo, F. J., & Conde, M. ´A. (2014). Using informal learning for business decision making and knowledge management. Journal of

Business Research, 67 (5), 686–691. https://doi.org/10.1016/j.jbusres.2013.11.028

Greve, H. R. (2020). Learning theory: The pandemic research challenge. Journal of Management Studies, 57 (8), 1759–1762. https://doi.org/

1111/joms.12631

Guadalupi, C. (2018). Learning quality through prices and word-of-mouth communication. Journal of Economics & Management Strategy, 27 (1), 53–70. https://doi.org/10.1111/jems.12230

Gulati, R., & Puranam, P. (2009). Renewal through reorganization: The value of inconsistencies between formal and informal organization.

Organization Science, 20 (2), 422–440. https://doi.org/10.1287/orsc.1090.0421

Hartmann, S., & Briskorn, D. (2010). A survey of variants and extensions of the resource-constrained project scheduling problem. European Journal of Operational Research, 207 (1), 1–14. https://doi.org/10.1016/j.ejor.2009.11.005

Hartmann, S., & Drexl, A. (1998). Project scheduling with multiple modes: A comparison of exact algorithms. Networks, 32 (4), 283–297. https:

//doi.org/10.1002/(SICI)1097-0037(199812)32:4⟨283::AID-NET5⟩3.0.CO;2-I

Heimicke, J., Chen, R., & Albers, A. (2020). Agile meets plan-driven-hybrid approaches in product development: A systematic literature review.

Proceedings of the Design Society: DESIGN Conference, 1, 577–586. https://doi.org/10.1017/dsd.2020.259

Hoyle, R. (2015). Informal learning in organizations: How to create a continuous learning culture. Kogan Page Publishers.

Hyndman, R. J., & Athanasopoulos, G. (2021). Forecasting: Principles and practice (3rd ed.). OTexts.

Jahr, M. (2014). A hybrid approach to quantitative software project scheduling within agile frameworks. Project Management Journal, 45 (3), 35–45. https://doi.org/10.1002/pmj.21411

Jiang, Y., Jackson, S. E., & Colakoglu, S. (2016). An empirical examination of personal learning within the context of teams: Personal Learning

in Teams. Journal of Organizational Behavior, 37 (5), 654–672. https://doi.org/10.1002/job.2058

Kataoka, T., Morikawa, K., & Takahashi, K. (2019). Strategic human resource management simulation considering work elements, skills, learning and forgetting. Procedia Manufacturing, 39, 1633–1640. https://doi.org/10.1016/j.promfg.2020.01.278

Kelley, J. E. (1963). The critical-path method: Resource planning and scheduling. Industrial scheduling.

Kılınc, M. R., & Sahinidis, N. V. (2018). Exploiting integrality in the global optimization of mixed-integer nonlinear programming problems with

baron. Optimization Methods and Software, 33 (3), 540–562.

Kolisch, R., & Hartmann, S. (1999). Heuristic algorithms for the resourceconstrained project scheduling problem: Classification and computational analysis. In Project scheduling (pp. 147–178). Springer.

Liu, Z., & Cheng, T. E. (2004). Minimizing total completion time subject to job release dates and preemption penalties. Journal of Scheduling,

(4), 313–327. https://doi.org/10.1023/B:JOSH.0000031424.35504.c4

Lova, A., Tormos, P., & Barber, F. (2006). Multi-mode resource constrained project scheduling: Scheduling schemes, priority rules and mode selection rules. INTELIGENCIA ARTIFICIAL, 10 (30), 495. https://doi.org/10.4114/ia.v10i30.947

Manifesto for agile software development. (2001). Agile Alliance. http ://www/agilemanifesto.org

Manifesto for half-arsed agile software development. (2001). Agile Alliance. http://www.halfarsedagilemanifesto.org/

March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2 (1), 71–87. https://doi.org/10.1287/orsc.2.

71

Matsuo, M. (2019). Empowerment through self-improvement skills: The role of learning goals and personal growth initiative. Journal of Vocational Behavior, 115, 103311. https://doi.org/10.1016/j.jvb.2019.05.008

Nasrallah, W., Levitt, R., & Glynn, P. (2003). Interaction value analysis: When structured communication benefits organizations. Organization

Science, 14 (5), 541–557. https://doi.org/10.1287/orsc.14.5.541.16764

Neininger, A., Lehmann-Willenbrock, N., Kauffeld, S., & Henschel, A. (2010). Effects of team and organizational commitment – A longitudinal

study. Journal of Vocational Behavior, 76 (3), 567–579. https://doi.org/10.1016/j.jvb.2010.01.009

Noe, R. A., Tews, M. J., & McConnell Dachner, A. (2010). Learner engagement: A new perspective for enhancing our understanding of learner

motivation and workplace learning. Academy of Management Annals, 4 (1), 279–315. https://doi.org/10.5465/19416520.2010.493286

Olson, D. L. (2001). Comparison of three multicriteria methods to predict known outcomes. European Journal of Operational Research, 130 (3), 576–587. https://doi.org/10.1016/S0377-2217(99)00416-6

Posen, H. E., & Levinthal, D. A. (2012). Chasing a moving target: Exploitation and exploration in dynamic environments. Management Science,

(3), 587–601. https://doi.org/10.1287/mnsc.1110.1420

Razavi, N., & Mozayani, N. (2007). A resource leveling model based on genetic algorithms: Activity splitting allowed. IMECS, 109–114.

Ryan, R. M., & Deci, E. L. (Eds.). (2017). Self-determination theory: Basic psychological needs in motivation, development, and wellness. Guilford Press. https://doi.org/10.1521/978.14625/28806

Sambrook, S. (2005). Factors influencing the context and process of workrelated learning: Synthesizing findings from two research projects.

Human Resource Development International, 8 (1), 101–119. https://doi.org/10.1080/1367886052000342591

Sauermann, H., & Stephan, P. (2013). Conflicting Logics? A Multidimensional View of Industrial and Academic Science. Organization Science,

(3), 889–909. https://doi.org/10.1287/orsc.1120.0769

Schaufeli, W. B., Bakker, A. B., & Van Rhenen, W. (2009). How changes in job demands and resources predict burnout, work engagement,

and sickness absenteeism. Journal of Organizational Behavior, 30 (7), 893–917. https://doi.org/10.1002/job.595

Schmidt, T. S. (2019). Agile development of physical products: An empirical study about potentials, transition and applicability.

Shepherd, D. A., Patzelt, H., Williams, T. A., & Warnecke, D. (2014). How does project termination impact project team members? Rapid

termination, ‘creeping death’, and learning from failure. Journal of Management Studies, 51 (4), 513–546. https://doi.org/10.1111/joms.

Speranza, M., & Vercellis, C. (1993). Hierarchical models for multi-project planning and scheduling. European Journal of Operational Research, 64 (2), 312–325. https://doi.org/10.1016/0377-2217(93)90185-P

Tews, M. J., Michel, J. W., & Noe, R. A. (2017). Does fun promote learning? The relationship between fun in the workplace and informal learning.

Journal of Vocational Behavior, 98, 46–55. https://doi.org/10.1016/j.jvb.2016.09.006

Thomas, J. B., Sussman, S. W., & Henderson, J. C. (2001). Understanding “strategic learning”: Linking organizational learning, knowledge

management, and sensemaking. Organization Science, 12 (3), 331–345. https://doi.org/10.1287/orsc.12.3.331.10105

T’kindt, V., & Billaut, J.-C. (2001). Multicriteria scheduling problems: A survey. RAIRO - Operations Research, 35 (2), 143–163. https://doi.

org/10.1051/ro:2001109

Vanhoucke, M., & Coelho, J. (2019). Resource-constrained project scheduling with activity splitting and setup times. Computers & Operations

Research, 109, 230–249. https://doi.org/10.1016/j.cor.2019.05.004

Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Qi Dong, J., Fabian, N., & Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901. https://doi.org/10.1016/j.jbusres.2019.09.022

Vigerske, S., & Gleixner, A. (2018). SCIP: Global optimization of mixed integer nonlinear programs in a branch-and-cut framework. Optimization Methods and Software, 33 (3), 563–593. https://doi.org/10.1080/10556788.2017.1335312

Wright, T. P. (1936). Factors Affecting the Cost of Airplanes. Journal of the Aeronautical Sciences, 3 (4), 122–128. https://doi.org/10.2514/8.155

Yakhlef, A. (2010). The corporeality of practice-based learning. Organization Studies, 31 (4), 409–430. https://doi.org/10.1177/0170840609357384

Zare, Z. (2012). Preemption multi-mode resource-constrained project scheduling problem. Interdisciplinary Journal of Contemporary Research in Business, 3 (9), 636–642.

Zareei, M., & Hassan-Pour, H. A. (2015). A multi-objective resource-constrained optimization of time-cost trade-off problems in scheduling project. Iranian Journal of Management Studies, 8 (4). https://doi.org/10.22059/ijms.2015.55006

Zhang, C., Nahrgang, J. D., Ashford, S. J., & DeRue, D. S. (2020). The risky side of leadership: Conceptualizing risk perceptions in informal

leadership and investigating the effects of their over-time changes in teams. Organization Science, 31 (5), 1138–1158. https://doi.org/10.

/orsc.2019.1350

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