Proactive interventions at work

Data inizio
15 ottobre 2018
Durata (mesi) 
Scienze Umane
Responsabili (o referenti locali)
Ceschi Andrea

Decisions are a key issue in the organizational domain, and errors that could derive from bad choices are of terrible impact on the organization and its performance. In the financial and in the commercial sector, the exposure to overconfidence in decision-making is considered the main cause of target failing in companies (Frydman & Camerer, 2016; Russo & Schoemaker, 1989). Worst is the case of the health sector, where the medical error is estimated to be the third leading cause of death in the US connected to workplace decisions (Makary & Daniel, 2016), and most of these accidental deceases have been accounted for no-deliberative decisions made by the personnel (Zhang, Patel, Johnson, & Shortliffe, 2004). Research developed in organizations indicates that decisions taken in the workplace are often the result of entrenched preferences and subjective expectations, following the logic of situational appropriateness rather than rational procedure (March 1994). These illogical premises on which decisions often are based are named heuristics and cognitive biases. Heuristics, introduced by Herbert Simon (1957), are considered simple human algorithms present in peoples’ mind applied for economizing cognitive resources and simplify tasks, When such mind shortcut departs reasoning from logic and normative processes, it can sometimes show a bias, which is the tendency to induce an incorrect, illogical or irrational conclusion based on cognitive factors (Tversky & Kahneman, 1974). 
Based on research in the development psychology domain, Miller and Byrnes (2001) have defined and assessed the construct of Decision-Making Competency (DMCy), which relies on self-regulation and metacognitive processes for examining choice options and mastering decisions. The rising interest toward decisional competences and perceived job characteristics has lately met the recent psychology interventional paradigm, which is questioning if these are stable components or if some training programs can enhance them. 
In literature, the ultimate intervention for improving decision-making competences is named debiasing. Developed through experiments conducted in a laboratory, the debiasing aims at improving the awareness in decision-making processes, by addressing subjects to manage logical incongruences and incoherent perceptions (Gerling, 2009). Composed of several techniques, debiasing helps people to consider new information during the decision-making, which might support the generation of different solutions and avoid heuristics and biases. Recently, such a program has been revisited and applied in organizations as a single training session to improve employees’ decisional competences and much more their performance at work (Soll, Milkman, & Payne). Along with it, starting from empirical studies in the field, I/O psychologists have recently developed a new interventional program to improve the work experience. Namely, job crafting training, it aims to help employees to improve the control over perceived job characteristics and their psychological state, by shaping, molding, and redefining their work activities. Indeed, Job crafting is based on self-initiated change behaviors, and as a construct, it has been developed to study the alignment between employees’ expectations and their jobs (Petrou, Demerouti, Peeters, Schaufeli, & Hetland, 2012).  
Both interventional programs, built on single training sessions, have shown to improve significantly decision-making competencies and job crafting behaviors in participants. Whereas the former relies more on analytical improvements, and the latter is intrinsically related to motivational forces, they rely on similar processes. Both of them work by eliciting cognitive reframing (Hirt & Markman, 1995; Wrzesniewski & Dutton, 2001), developing self-regulation (Byrnes, Miller, & Reynolds, 1999; Tims, B. Bakker, & Derks, 2014), improving reflective thinking (Arkes, 1991; Niessen, Weseler, & Kostova, 2016) and proactivity (Bakker, Tims, & Derks, 2012; Emby & Finley, 1997). For what concerns the workplace, the effects of such training programs, are beneficial for the improvement of control over job resources and demands, and well-being at work. Still, evidence that both training programs can improve a work outcome as job performance is inconclusive at present (Claessens, Van Eerde, Rutte, & Roe, 2010; Morewedge et al., 2015; Tims, Bakker, Derks, & van Rhenen, 2013). Taking these training programs together, the current research project, by using a quasi-experiment grounded on two samples (experimental group VS control group) of employees from the health care and commercial sector, aims to empirically answer to some pragmatic questions. Firstly, with a one-shot intervention, is it possible to help employees to craft their jobs by improving also their decision-making processes? Secondly, can this combination, through better management of job characteristics and of the psychological state, enhance significantly the job performance? Before discussing the expected cross-benefits of such blend training, we first present the job crafting framework intervention considered in this study, and the debiasing program by introducing hypotheses related to the above questions. There are conceptual reasons to think how a joint intervention, composed of a debiasing and job crafting training together, can multiply the magnitude of improvements at work (e.g. better management of job resources and demands, less exhaustion, and finally greater job performance). These training present similarities in terms of cognitive mechanics and techniques, which can fruitfully interact together. Considering the practice, the use of daily or weekly diary studies is a common method for both approaches, which provides an accurate picture of the experience associated with work activity. Indeed, the development of awareness is the first step needed for eliciting reflective thinking and for learning new coping strategies over the heuristic response. Both of them, create a virtuous circle, which facilitate the elaboration of new information and the production of a less automatic response.
The distinctive characteristic of the job crafting intervention is that such a bottom-up redesign approach starts with the personal initiative of the employee, who can put into action his/her attitude toward proactive work behaviors (Tims et al., 2012). Such a peculiarity differentiates the job crafting intervention from most of the other bottom-up job redesign approaches, recognizing to the individual a central role and idiosyncratic deals or employees’ participation in job redesign. 
Debiasing training is defined as an improvement program, continually developed over the last 50 years, to reduce heuristics and biases in decision-making (Croskerry, Singhal, & Mamede, 2013). To date, it met a mixed success, which appears to be related to the sector of application. In the health sector, an experimental procedure has been designed and proved to work for preventing the framing effect in diagnosis among the medical personnel (McNeil, Pauker, Sox, & Tversky, 1982). Due to its nature, debiasing has been mostly applied in jobs characterized by high decisional control and high outcomes value (such as trading and finance, engineering, medical sector, etc.). Nevertheless, recent research has shown that whether the sector appears to be contingent, much more, the presence of certain job characteristics, such as the support of colleagues or feedbacks at work, is the determinants of the training performance (Harvey, 2011; Kohler, Brenner, & Griffin, 2002)  
The intervention proposed by this research project was designed for about four weeks and based on a one-day workshop delivered to participants, together with a notebook with the contents of the training, and a diary with the monitoring questionnaires. Before the workshop session, the research staff provided to participants the baseline questionnaire, they were asked to complete it and explained the anonymous nature of the data collection during the instructions. After this, the first part of the workshop, based on face-to-face soft skill training and conducted by professional HR trainers, started. The training was firstly aimed to develop awareness toward such constructs including background theory on the JD-R model (Bakker & Demerouti, 2007), participants first mapped their job demands, job resources, and recognized job crafting strategies, as well and decision-making processes that can be detrimental in such processes, such as biases or heuristics. Employees were trained to make small adjustments to their approach to decisions made at work and to formulate job crafting goals in a personal plan. Overall, results show that the intervention was fruitful for improving decision-making competences and an inclination toward the individual job redesign. Moreover, thanks to the use of growth models we were able to understand how these processes of learning develop over time. 
Finally, implications for companies consist of the employee-initiated improvement of job characteristics together with collaborative decision-making developed by this training, which in turn can positively increase the employee performance and as well job satisfaction.

Arkes, H. R. (1991). Costs and benefits of judgment errors: Implications for debiasing. Psychological Bulletin, 110(3), 486.

Bakker, A. B., Tims, M., & Derks, D. (2012). Proactive personality and job performance: The role of job crafting and work engagement. Human Relations, 65(10), 1359-1378.

Byrnes, J. P., Miller, D. C., & Reynolds, M. (1999). Learning to make good decisions: A self‐regulation perspective. Child Development, 70(5), 1121-1140.

Ceschi, A., Sartori, R., Tommasi, F., Noventa, S., Morandini, S., & Zagarese, V. (2021). A combined resources‐strength intervention: Empirical evidence from two streams of the positive psychology approach. International Journal of Training and Development.

Claessens, B. J., Van Eerde, W., Rutte, C. G., & Roe, R. A. (2010). Things to do today...: A daily diary study on task completion at work. Applied Psychology, 59(2), 273-295.

Costantini, A., Ceschi, A., Viragos, A., De Paola, F., & Sartori, R. (2019). The role of a new strength-based intervention on organisation-based self-esteem and work engagement: A three-wave intervention study. Journal of Workplace Learning.

Costantini, A., Demerouti, E., Ceschi, A., & Sartori, R. (2020). Implementing job crafting behaviors: Exploring the effects of a job crafting intervention based on the theory of planned behavior. The Journal of Applied Behavioral Science, 0021886320975913.

Croskerry, P., Singhal, G., & Mamede, S. (2013). Cognitive debiasing 2: impediments to and strategies for change. BMJ quality & safety, bmjqs-2012-001713.

Emby, C., & Finley, D. (1997). Debiasing framing effects in auditors' internal control judgments and testing decisions. Contemporary Accounting Research, 14(2), 55-77.

Frydman, C., & Camerer, C. F. (2016). The psychology and neuroscience of financial decision making. Trends in cognitive sciences, 20(9), 661-675.

Gerling, P. (2009). Debiasing of managerial decisions: a new function of management accounting? Management, 169-189

Hirt, E. R., & Markman, K. D. (1995). Multiple explanations: A consider-an-alternative strategy for debiasing judgments. Journal of personality and social psychology, 69, 1069-1086.

Makary, M. A., & Daniel, M. (2016). Medical error—the third leading cause of death in the US. BMJ, 353. doi:10.1136/bmj.i2139

March, J. (1994). A primer on decision making: How decisions happen. New York: The Free Press.

Miller, D. C., & Byrnes, J. P. (2001). Adolescents' decision making in social situations A self-regulation perspective. Journal of Applied Developmental Psychology, 22(3), 237-256. doi:10.1016/S0193-3973(01)00082-X

Morewedge, C. K., Yoon, H., Scopelliti, I., Symborski, C. W., Korris, J. H., & Kassam, K. S. (2015). Debiasing decisions: Improved decision making with a single training intervention. Policy Insights from the Behavioral and Brain Sciences, 2(1), 129-140.

Niessen, C., Weseler, D., & Kostova, P. (2016). When and why do individuals craft their jobs? The role of individual motivation and work characteristics for job crafting. Human Relations, 0018726715610642.

Petrou, P., Demerouti, E., Peeters, M. C., Schaufeli, W. B., & Hetland, J. (2012). Crafting a job on a daily basis: Contextual correlates and the link to work engagement. Journal of organizational behavior, 33(8), 1120-1141.

Sartori, R., Costantini, A., Ceschi, A., & Tommasi, F. (2018). How do you manage change in organizations? Training, development, innovation, and their relationships. Frontiers in psychology, 9, 313.

Simon, H. A. (1957). Models of man: Social and rational. New York: Wiley.

Soll, J. B., Milkman, K. L., & Payne, J. W. (2014). A user's guide to debiasing.

Stanovich, K. E., Toplak, M. E., & West, R. F. (2008). The development of rational thought: A taxonomy of heuristics and biases. Advances in child development and behavior, 36, 251-285.

Tims, M., B. Bakker, A., & Derks, D. (2014). Daily job crafting and the self-efficacy–performance relationship. Journal of Managerial Psychology, 29(5), 490-507.

Tims, M., Bakker, A. B., Derks, D., & van Rhenen, W. (2013). Job crafting at the team and individual level: Implications for work engagement and performance. Group & Organization Management, 1059601113492421.

Tommasi, F., Ceschi, A., Gostimir, M., Perini, M., & Sartori, R. (2021). Game-based training: an effective method for reducing behavioral-finance biases.

Tommasi, F., Ceschi, A., Weller, J., Costantini, A., Passaia, G., Gostimir, M., & Sartori, R. (2021). An empirical evaluation of tech interventions to improve financial decision-making. European Journal of Training and Development.

Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124.

Wrzesniewski, A., & Dutton, J. E. (2001). Crafting a job: Revisioning employees as active crafters of their work. Academy of management review, 26(2), 179-201.

Zhang, J., Patel, V. L., Johnson, T. R., & Shortliffe, E. H. (2004). A cognitive taxonomy of medical errors. Journal of biomedical informatics, 37(3), 193-204.


Enti finanziatori:

Finanziamento: assegnato e gestito dal Dipartimento

Partecipanti al progetto

Riccardo Sartori
Professore associato
Francesco Tommasi
Professore a contratto

Collaboratori esterni

Joshua Weller
Tilburg University
Evangelia Demerouti
Eindhoven University of Technology
Aree di ricerca coinvolte dal progetto
Formazione e organizzazioni
work and organizational psychology
Titolo Autori Anno
An empirical evaluation of tech interventions to improve financial decision-making Tommasi, Francesco; Ceschi, Andrea; Weller, Joshua; Costantini, Arianna; Passaia, Giulia; Gostimir, Marija; Sartori, Riccardo 2021
GAME-BASED TRAINING: AN EFFECTIVE METHOD FOR REDUCING BEHAVIOURAL-FINANCE BIASES Tommasi, Francesco; Ceschi, Andrea; Gostimir, Marija; Perini, Marco; Sartori, Riccardo 2021
Implementing Job Crafting Behaviors: Exploring the Effects of a Job Crafting Intervention Based on the Theory of Planned Behavior Costantini, Arianna; Demerouti, Evangelia; Ceschi, Andrea; Sartori, Riccardo 2020
The role of a new strength-based intervention on organisation-based self-esteem and work engagement: A three-wave intervention study Costantini, Arianna; Ceschi, Andrea; Viragos, Anna; De Paola, Francesco; Sartori, Riccardo 2019
How Do You Manage Change in Organizations? Training, Development, Innovation, and Their Relationships Sartori, Riccardo; Costantini, Arianna; Ceschi, Andrea; Tommasi, Francesco 2018